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TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #
| #
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Coin sums
Problem 31: https://projecteuler.net/problem=31
In England the currency is made up of pound, £, and pence, p, and there are
eight coins in general circulation:
1p, 2p, 5p, 10p, 20p, 50p, £1 (100p) and £2 (200p).
It is possible to make £2 in the following way:
1×£1 + 1×50p + 2×20p + 1×5p + 1×2p + 3×1p
How many different ways can £2 be made using any number of coins?
"""
def one_pence() -> int:
return 1
def two_pence(x: int) -> int:
return 0 if x < 0 else two_pence(x - 2) + one_pence()
def five_pence(x: int) -> int:
return 0 if x < 0 else five_pence(x - 5) + two_pence(x)
def ten_pence(x: int) -> int:
return 0 if x < 0 else ten_pence(x - 10) + five_pence(x)
def twenty_pence(x: int) -> int:
return 0 if x < 0 else twenty_pence(x - 20) + ten_pence(x)
def fifty_pence(x: int) -> int:
return 0 if x < 0 else fifty_pence(x - 50) + twenty_pence(x)
def one_pound(x: int) -> int:
return 0 if x < 0 else one_pound(x - 100) + fifty_pence(x)
def two_pound(x: int) -> int:
return 0 if x < 0 else two_pound(x - 200) + one_pound(x)
def solution(n: int = 200) -> int:
"""Returns the number of different ways can n pence be made using any number of
coins?
>>> solution(500)
6295434
>>> solution(200)
73682
>>> solution(50)
451
>>> solution(10)
11
"""
return two_pound(n)
if __name__ == "__main__":
print(solution(int(input().strip())))
| """
Coin sums
Problem 31: https://projecteuler.net/problem=31
In England the currency is made up of pound, £, and pence, p, and there are
eight coins in general circulation:
1p, 2p, 5p, 10p, 20p, 50p, £1 (100p) and £2 (200p).
It is possible to make £2 in the following way:
1×£1 + 1×50p + 2×20p + 1×5p + 1×2p + 3×1p
How many different ways can £2 be made using any number of coins?
"""
def one_pence() -> int:
return 1
def two_pence(x: int) -> int:
return 0 if x < 0 else two_pence(x - 2) + one_pence()
def five_pence(x: int) -> int:
return 0 if x < 0 else five_pence(x - 5) + two_pence(x)
def ten_pence(x: int) -> int:
return 0 if x < 0 else ten_pence(x - 10) + five_pence(x)
def twenty_pence(x: int) -> int:
return 0 if x < 0 else twenty_pence(x - 20) + ten_pence(x)
def fifty_pence(x: int) -> int:
return 0 if x < 0 else fifty_pence(x - 50) + twenty_pence(x)
def one_pound(x: int) -> int:
return 0 if x < 0 else one_pound(x - 100) + fifty_pence(x)
def two_pound(x: int) -> int:
return 0 if x < 0 else two_pound(x - 200) + one_pound(x)
def solution(n: int = 200) -> int:
"""Returns the number of different ways can n pence be made using any number of
coins?
>>> solution(500)
6295434
>>> solution(200)
73682
>>> solution(50)
451
>>> solution(10)
11
"""
return two_pound(n)
if __name__ == "__main__":
print(solution(int(input().strip())))
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This script demonstrates the implementation of the ReLU function.
It's a kind of activation function defined as the positive part of its argument in the
context of neural network.
The function takes a vector of K real numbers as input and then argmax(x, 0).
After through ReLU, the element of the vector always 0 or real number.
Script inspired from its corresponding Wikipedia article
https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
"""
from __future__ import annotations
import numpy as np
def relu(vector: list[float]):
"""
Implements the relu function
Parameters:
vector (np.array,list,tuple): A numpy array of shape (1,n)
consisting of real values or a similar list,tuple
Returns:
relu_vec (np.array): The input numpy array, after applying
relu.
>>> vec = np.array([-1, 0, 5])
>>> relu(vec)
array([0, 0, 5])
"""
# compare two arrays and then return element-wise maxima.
return np.maximum(0, vector)
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| """
This script demonstrates the implementation of the ReLU function.
It's a kind of activation function defined as the positive part of its argument in the
context of neural network.
The function takes a vector of K real numbers as input and then argmax(x, 0).
After through ReLU, the element of the vector always 0 or real number.
Script inspired from its corresponding Wikipedia article
https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
"""
from __future__ import annotations
import numpy as np
def relu(vector: list[float]):
"""
Implements the relu function
Parameters:
vector (np.array,list,tuple): A numpy array of shape (1,n)
consisting of real values or a similar list,tuple
Returns:
relu_vec (np.array): The input numpy array, after applying
relu.
>>> vec = np.array([-1, 0, 5])
>>> relu(vec)
array([0, 0, 5])
"""
# compare two arrays and then return element-wise maxima.
return np.maximum(0, vector)
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This is pure Python implementation of fibonacci search.
Resources used:
https://en.wikipedia.org/wiki/Fibonacci_search_technique
For doctests run following command:
python3 -m doctest -v fibonacci_search.py
For manual testing run:
python3 fibonacci_search.py
"""
from functools import lru_cache
@lru_cache
def fibonacci(k: int) -> int:
"""Finds fibonacci number in index k.
Parameters
----------
k :
Index of fibonacci.
Returns
-------
int
Fibonacci number in position k.
>>> fibonacci(0)
0
>>> fibonacci(2)
1
>>> fibonacci(5)
5
>>> fibonacci(15)
610
>>> fibonacci('a')
Traceback (most recent call last):
TypeError: k must be an integer.
>>> fibonacci(-5)
Traceback (most recent call last):
ValueError: k integer must be greater or equal to zero.
"""
if not isinstance(k, int):
raise TypeError("k must be an integer.")
if k < 0:
raise ValueError("k integer must be greater or equal to zero.")
if k == 0:
return 0
elif k == 1:
return 1
else:
return fibonacci(k - 1) + fibonacci(k - 2)
def fibonacci_search(arr: list, val: int) -> int:
"""A pure Python implementation of a fibonacci search algorithm.
Parameters
----------
arr
List of sorted elements.
val
Element to search in list.
Returns
-------
int
The index of the element in the array.
-1 if the element is not found.
>>> fibonacci_search([4, 5, 6, 7], 4)
0
>>> fibonacci_search([4, 5, 6, 7], -10)
-1
>>> fibonacci_search([-18, 2], -18)
0
>>> fibonacci_search([5], 5)
0
>>> fibonacci_search(['a', 'c', 'd'], 'c')
1
>>> fibonacci_search(['a', 'c', 'd'], 'f')
-1
>>> fibonacci_search([], 1)
-1
>>> fibonacci_search([.1, .4 , 7], .4)
1
>>> fibonacci_search([], 9)
-1
>>> fibonacci_search(list(range(100)), 63)
63
>>> fibonacci_search(list(range(100)), 99)
99
>>> fibonacci_search(list(range(-100, 100, 3)), -97)
1
>>> fibonacci_search(list(range(-100, 100, 3)), 0)
-1
>>> fibonacci_search(list(range(-100, 100, 5)), 0)
20
>>> fibonacci_search(list(range(-100, 100, 5)), 95)
39
"""
len_list = len(arr)
# Find m such that F_m >= n where F_i is the i_th fibonacci number.
i = 0
while True:
if fibonacci(i) >= len_list:
fibb_k = i
break
i += 1
offset = 0
while fibb_k > 0:
index_k = min(
offset + fibonacci(fibb_k - 1), len_list - 1
) # Prevent out of range
item_k_1 = arr[index_k]
if item_k_1 == val:
return index_k
elif val < item_k_1:
fibb_k -= 1
elif val > item_k_1:
offset += fibonacci(fibb_k - 1)
fibb_k -= 2
else:
return -1
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
This is pure Python implementation of fibonacci search.
Resources used:
https://en.wikipedia.org/wiki/Fibonacci_search_technique
For doctests run following command:
python3 -m doctest -v fibonacci_search.py
For manual testing run:
python3 fibonacci_search.py
"""
from functools import lru_cache
@lru_cache
def fibonacci(k: int) -> int:
"""Finds fibonacci number in index k.
Parameters
----------
k :
Index of fibonacci.
Returns
-------
int
Fibonacci number in position k.
>>> fibonacci(0)
0
>>> fibonacci(2)
1
>>> fibonacci(5)
5
>>> fibonacci(15)
610
>>> fibonacci('a')
Traceback (most recent call last):
TypeError: k must be an integer.
>>> fibonacci(-5)
Traceback (most recent call last):
ValueError: k integer must be greater or equal to zero.
"""
if not isinstance(k, int):
raise TypeError("k must be an integer.")
if k < 0:
raise ValueError("k integer must be greater or equal to zero.")
if k == 0:
return 0
elif k == 1:
return 1
else:
return fibonacci(k - 1) + fibonacci(k - 2)
def fibonacci_search(arr: list, val: int) -> int:
"""A pure Python implementation of a fibonacci search algorithm.
Parameters
----------
arr
List of sorted elements.
val
Element to search in list.
Returns
-------
int
The index of the element in the array.
-1 if the element is not found.
>>> fibonacci_search([4, 5, 6, 7], 4)
0
>>> fibonacci_search([4, 5, 6, 7], -10)
-1
>>> fibonacci_search([-18, 2], -18)
0
>>> fibonacci_search([5], 5)
0
>>> fibonacci_search(['a', 'c', 'd'], 'c')
1
>>> fibonacci_search(['a', 'c', 'd'], 'f')
-1
>>> fibonacci_search([], 1)
-1
>>> fibonacci_search([.1, .4 , 7], .4)
1
>>> fibonacci_search([], 9)
-1
>>> fibonacci_search(list(range(100)), 63)
63
>>> fibonacci_search(list(range(100)), 99)
99
>>> fibonacci_search(list(range(-100, 100, 3)), -97)
1
>>> fibonacci_search(list(range(-100, 100, 3)), 0)
-1
>>> fibonacci_search(list(range(-100, 100, 5)), 0)
20
>>> fibonacci_search(list(range(-100, 100, 5)), 95)
39
"""
len_list = len(arr)
# Find m such that F_m >= n where F_i is the i_th fibonacci number.
i = 0
while True:
if fibonacci(i) >= len_list:
fibb_k = i
break
i += 1
offset = 0
while fibb_k > 0:
index_k = min(
offset + fibonacci(fibb_k - 1), len_list - 1
) # Prevent out of range
item_k_1 = arr[index_k]
if item_k_1 == val:
return index_k
elif val < item_k_1:
fibb_k -= 1
elif val > item_k_1:
offset += fibonacci(fibb_k - 1)
fibb_k -= 2
else:
return -1
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import random
from .binary_exp_mod import bin_exp_mod
# This is a probabilistic check to test primality, useful for big numbers!
# if it's a prime, it will return true
# if it's not a prime, the chance of it returning true is at most 1/4**prec
def is_prime_big(n, prec=1000):
"""
>>> from maths.prime_check import is_prime
>>> # all(is_prime_big(i) == is_prime(i) for i in range(1000)) # 3.45s
>>> all(is_prime_big(i) == is_prime(i) for i in range(256))
True
"""
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
d = n - 1
exp = 0
while d % 2 == 0:
d /= 2
exp += 1
# n - 1=d*(2**exp)
count = 0
while count < prec:
a = random.randint(2, n - 1)
b = bin_exp_mod(a, d, n)
if b != 1:
flag = True
for _ in range(exp):
if b == n - 1:
flag = False
break
b = b * b
b %= n
if flag:
return False
count += 1
return True
if __name__ == "__main__":
n = abs(int(input("Enter bound : ").strip()))
print("Here's the list of primes:")
print(", ".join(str(i) for i in range(n + 1) if is_prime_big(i)))
| import random
from .binary_exp_mod import bin_exp_mod
# This is a probabilistic check to test primality, useful for big numbers!
# if it's a prime, it will return true
# if it's not a prime, the chance of it returning true is at most 1/4**prec
def is_prime_big(n, prec=1000):
"""
>>> from maths.prime_check import is_prime
>>> # all(is_prime_big(i) == is_prime(i) for i in range(1000)) # 3.45s
>>> all(is_prime_big(i) == is_prime(i) for i in range(256))
True
"""
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
d = n - 1
exp = 0
while d % 2 == 0:
d /= 2
exp += 1
# n - 1=d*(2**exp)
count = 0
while count < prec:
a = random.randint(2, n - 1)
b = bin_exp_mod(a, d, n)
if b != 1:
flag = True
for _ in range(exp):
if b == n - 1:
flag = False
break
b = b * b
b %= n
if flag:
return False
count += 1
return True
if __name__ == "__main__":
n = abs(int(input("Enter bound : ").strip()))
print("Here's the list of primes:")
print(", ".join(str(i) for i in range(n + 1) if is_prime_big(i)))
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #
| #
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Information on 2's complement: https://en.wikipedia.org/wiki/Two%27s_complement
def twos_complement(number: int) -> str:
"""
Take in a negative integer 'number'.
Return the two's complement representation of 'number'.
>>> twos_complement(0)
'0b0'
>>> twos_complement(-1)
'0b11'
>>> twos_complement(-5)
'0b1011'
>>> twos_complement(-17)
'0b101111'
>>> twos_complement(-207)
'0b100110001'
>>> twos_complement(1)
Traceback (most recent call last):
...
ValueError: input must be a negative integer
"""
if number > 0:
raise ValueError("input must be a negative integer")
binary_number_length = len(bin(number)[3:])
twos_complement_number = bin(abs(number) - (1 << binary_number_length))[3:]
twos_complement_number = (
(
"1"
+ "0" * (binary_number_length - len(twos_complement_number))
+ twos_complement_number
)
if number < 0
else "0"
)
return "0b" + twos_complement_number
if __name__ == "__main__":
import doctest
doctest.testmod()
| # Information on 2's complement: https://en.wikipedia.org/wiki/Two%27s_complement
def twos_complement(number: int) -> str:
"""
Take in a negative integer 'number'.
Return the two's complement representation of 'number'.
>>> twos_complement(0)
'0b0'
>>> twos_complement(-1)
'0b11'
>>> twos_complement(-5)
'0b1011'
>>> twos_complement(-17)
'0b101111'
>>> twos_complement(-207)
'0b100110001'
>>> twos_complement(1)
Traceback (most recent call last):
...
ValueError: input must be a negative integer
"""
if number > 0:
raise ValueError("input must be a negative integer")
binary_number_length = len(bin(number)[3:])
twos_complement_number = bin(abs(number) - (1 << binary_number_length))[3:]
twos_complement_number = (
(
"1"
+ "0" * (binary_number_length - len(twos_complement_number))
+ twos_complement_number
)
if number < 0
else "0"
)
return "0b" + twos_complement_number
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
https://cp-algorithms.com/string/prefix-function.html
Prefix function Knuth–Morris–Pratt algorithm
Different algorithm than Knuth-Morris-Pratt pattern finding
E.x. Finding longest prefix which is also suffix
Time Complexity: O(n) - where n is the length of the string
"""
def prefix_function(input_string: str) -> list:
"""
For the given string this function computes value for each index(i),
which represents the longest coincidence of prefix and suffix
for given substring (input_str[0...i])
For the value of the first element the algorithm always returns 0
>>> prefix_function("aabcdaabc")
[0, 1, 0, 0, 0, 1, 2, 3, 4]
>>> prefix_function("asdasdad")
[0, 0, 0, 1, 2, 3, 4, 0]
"""
# list for the result values
prefix_result = [0] * len(input_string)
for i in range(1, len(input_string)):
# use last results for better performance - dynamic programming
j = prefix_result[i - 1]
while j > 0 and input_string[i] != input_string[j]:
j = prefix_result[j - 1]
if input_string[i] == input_string[j]:
j += 1
prefix_result[i] = j
return prefix_result
def longest_prefix(input_str: str) -> int:
"""
Prefix-function use case
Finding longest prefix which is suffix as well
>>> longest_prefix("aabcdaabc")
4
>>> longest_prefix("asdasdad")
4
>>> longest_prefix("abcab")
2
"""
# just returning maximum value of the array gives us answer
return max(prefix_function(input_str))
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
https://cp-algorithms.com/string/prefix-function.html
Prefix function Knuth–Morris–Pratt algorithm
Different algorithm than Knuth-Morris-Pratt pattern finding
E.x. Finding longest prefix which is also suffix
Time Complexity: O(n) - where n is the length of the string
"""
def prefix_function(input_string: str) -> list:
"""
For the given string this function computes value for each index(i),
which represents the longest coincidence of prefix and suffix
for given substring (input_str[0...i])
For the value of the first element the algorithm always returns 0
>>> prefix_function("aabcdaabc")
[0, 1, 0, 0, 0, 1, 2, 3, 4]
>>> prefix_function("asdasdad")
[0, 0, 0, 1, 2, 3, 4, 0]
"""
# list for the result values
prefix_result = [0] * len(input_string)
for i in range(1, len(input_string)):
# use last results for better performance - dynamic programming
j = prefix_result[i - 1]
while j > 0 and input_string[i] != input_string[j]:
j = prefix_result[j - 1]
if input_string[i] == input_string[j]:
j += 1
prefix_result[i] = j
return prefix_result
def longest_prefix(input_str: str) -> int:
"""
Prefix-function use case
Finding longest prefix which is suffix as well
>>> longest_prefix("aabcdaabc")
4
>>> longest_prefix("asdasdad")
4
>>> longest_prefix("abcab")
2
"""
# just returning maximum value of the array gives us answer
return max(prefix_function(input_str))
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Implementing Newton Raphson method in Python
# Author: Syed Haseeb Shah (github.com/QuantumNovice)
# The Newton-Raphson method (also known as Newton's method) is a way to
# quickly find a good approximation for the root of a real-valued function
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F401, F403
from sympy import diff
def newton_raphson(
func: str, a: float | Decimal, precision: float = 10**-10
) -> float:
"""Finds root from the point 'a' onwards by Newton-Raphson method
>>> newton_raphson("sin(x)", 2)
3.1415926536808043
>>> newton_raphson("x**2 - 5*x +2", 0.4)
0.4384471871911695
>>> newton_raphson("x**2 - 5", 0.1)
2.23606797749979
>>> newton_raphson("log(x)- 1", 2)
2.718281828458938
"""
x = a
while True:
x = Decimal(x) - (Decimal(eval(func)) / Decimal(eval(str(diff(func)))))
# This number dictates the accuracy of the answer
if abs(eval(func)) < precision:
return float(x)
# Let's Execute
if __name__ == "__main__":
# Find root of trigonometric function
# Find value of pi
print(f"The root of sin(x) = 0 is {newton_raphson('sin(x)', 2)}")
# Find root of polynomial
print(f"The root of x**2 - 5*x + 2 = 0 is {newton_raphson('x**2 - 5*x + 2', 0.4)}")
# Find Square Root of 5
print(f"The root of log(x) - 1 = 0 is {newton_raphson('log(x) - 1', 2)}")
# Exponential Roots
print(f"The root of exp(x) - 1 = 0 is {newton_raphson('exp(x) - 1', 0)}")
| # Implementing Newton Raphson method in Python
# Author: Syed Haseeb Shah (github.com/QuantumNovice)
# The Newton-Raphson method (also known as Newton's method) is a way to
# quickly find a good approximation for the root of a real-valued function
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F401, F403
from sympy import diff
def newton_raphson(
func: str, a: float | Decimal, precision: float = 10**-10
) -> float:
"""Finds root from the point 'a' onwards by Newton-Raphson method
>>> newton_raphson("sin(x)", 2)
3.1415926536808043
>>> newton_raphson("x**2 - 5*x +2", 0.4)
0.4384471871911695
>>> newton_raphson("x**2 - 5", 0.1)
2.23606797749979
>>> newton_raphson("log(x)- 1", 2)
2.718281828458938
"""
x = a
while True:
x = Decimal(x) - (Decimal(eval(func)) / Decimal(eval(str(diff(func)))))
# This number dictates the accuracy of the answer
if abs(eval(func)) < precision:
return float(x)
# Let's Execute
if __name__ == "__main__":
# Find root of trigonometric function
# Find value of pi
print(f"The root of sin(x) = 0 is {newton_raphson('sin(x)', 2)}")
# Find root of polynomial
print(f"The root of x**2 - 5*x + 2 = 0 is {newton_raphson('x**2 - 5*x + 2', 0.4)}")
# Find Square Root of 5
print(f"The root of log(x) - 1 = 0 is {newton_raphson('log(x) - 1', 2)}")
# Exponential Roots
print(f"The root of exp(x) - 1 = 0 is {newton_raphson('exp(x) - 1', 0)}")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 1: https://projecteuler.net/problem=1
Multiples of 3 and 5
If we list all the natural numbers below 10 that are multiples of 3 or 5,
we get 3, 5, 6 and 9. The sum of these multiples is 23.
Find the sum of all the multiples of 3 or 5 below 1000.
"""
def solution(n: int = 1000) -> int:
"""
Returns the sum of all the multiples of 3 or 5 below n.
>>> solution(3)
0
>>> solution(4)
3
>>> solution(10)
23
>>> solution(600)
83700
"""
result = 0
for i in range(n):
if i % 3 == 0 or i % 5 == 0:
result += i
return result
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 1: https://projecteuler.net/problem=1
Multiples of 3 and 5
If we list all the natural numbers below 10 that are multiples of 3 or 5,
we get 3, 5, 6 and 9. The sum of these multiples is 23.
Find the sum of all the multiples of 3 or 5 below 1000.
"""
def solution(n: int = 1000) -> int:
"""
Returns the sum of all the multiples of 3 or 5 below n.
>>> solution(3)
0
>>> solution(4)
3
>>> solution(10)
23
>>> solution(600)
83700
"""
result = 0
for i in range(n):
if i % 3 == 0 or i % 5 == 0:
result += i
return result
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 8: https://projecteuler.net/problem=8
Largest product in a series
The four adjacent digits in the 1000-digit number that have the greatest
product are 9 × 9 × 8 × 9 = 5832.
73167176531330624919225119674426574742355349194934
96983520312774506326239578318016984801869478851843
85861560789112949495459501737958331952853208805511
12540698747158523863050715693290963295227443043557
66896648950445244523161731856403098711121722383113
62229893423380308135336276614282806444486645238749
30358907296290491560440772390713810515859307960866
70172427121883998797908792274921901699720888093776
65727333001053367881220235421809751254540594752243
52584907711670556013604839586446706324415722155397
53697817977846174064955149290862569321978468622482
83972241375657056057490261407972968652414535100474
82166370484403199890008895243450658541227588666881
16427171479924442928230863465674813919123162824586
17866458359124566529476545682848912883142607690042
24219022671055626321111109370544217506941658960408
07198403850962455444362981230987879927244284909188
84580156166097919133875499200524063689912560717606
05886116467109405077541002256983155200055935729725
71636269561882670428252483600823257530420752963450
Find the thirteen adjacent digits in the 1000-digit number that have the
greatest product. What is the value of this product?
"""
from functools import reduce
N = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445244523161731856403098711121722383113"
"62229893423380308135336276614282806444486645238749"
"30358907296290491560440772390713810515859307960866"
"70172427121883998797908792274921901699720888093776"
"65727333001053367881220235421809751254540594752243"
"52584907711670556013604839586446706324415722155397"
"53697817977846174064955149290862569321978468622482"
"83972241375657056057490261407972968652414535100474"
"82166370484403199890008895243450658541227588666881"
"16427171479924442928230863465674813919123162824586"
"17866458359124566529476545682848912883142607690042"
"24219022671055626321111109370544217506941658960408"
"07198403850962455444362981230987879927244284909188"
"84580156166097919133875499200524063689912560717606"
"05886116467109405077541002256983155200055935729725"
"71636269561882670428252483600823257530420752963450"
)
def solution(n: str = N) -> int:
"""
Find the thirteen adjacent digits in the 1000-digit number n that have
the greatest product and returns it.
>>> solution("13978431290823798458352374")
609638400
>>> solution("13978431295823798458352374")
2612736000
>>> solution("1397843129582379841238352374")
209018880
"""
return max(
# mypy cannot properly interpret reduce
int(reduce(lambda x, y: str(int(x) * int(y)), n[i : i + 13]))
for i in range(len(n) - 12)
)
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 8: https://projecteuler.net/problem=8
Largest product in a series
The four adjacent digits in the 1000-digit number that have the greatest
product are 9 × 9 × 8 × 9 = 5832.
73167176531330624919225119674426574742355349194934
96983520312774506326239578318016984801869478851843
85861560789112949495459501737958331952853208805511
12540698747158523863050715693290963295227443043557
66896648950445244523161731856403098711121722383113
62229893423380308135336276614282806444486645238749
30358907296290491560440772390713810515859307960866
70172427121883998797908792274921901699720888093776
65727333001053367881220235421809751254540594752243
52584907711670556013604839586446706324415722155397
53697817977846174064955149290862569321978468622482
83972241375657056057490261407972968652414535100474
82166370484403199890008895243450658541227588666881
16427171479924442928230863465674813919123162824586
17866458359124566529476545682848912883142607690042
24219022671055626321111109370544217506941658960408
07198403850962455444362981230987879927244284909188
84580156166097919133875499200524063689912560717606
05886116467109405077541002256983155200055935729725
71636269561882670428252483600823257530420752963450
Find the thirteen adjacent digits in the 1000-digit number that have the
greatest product. What is the value of this product?
"""
from functools import reduce
N = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445244523161731856403098711121722383113"
"62229893423380308135336276614282806444486645238749"
"30358907296290491560440772390713810515859307960866"
"70172427121883998797908792274921901699720888093776"
"65727333001053367881220235421809751254540594752243"
"52584907711670556013604839586446706324415722155397"
"53697817977846174064955149290862569321978468622482"
"83972241375657056057490261407972968652414535100474"
"82166370484403199890008895243450658541227588666881"
"16427171479924442928230863465674813919123162824586"
"17866458359124566529476545682848912883142607690042"
"24219022671055626321111109370544217506941658960408"
"07198403850962455444362981230987879927244284909188"
"84580156166097919133875499200524063689912560717606"
"05886116467109405077541002256983155200055935729725"
"71636269561882670428252483600823257530420752963450"
)
def solution(n: str = N) -> int:
"""
Find the thirteen adjacent digits in the 1000-digit number n that have
the greatest product and returns it.
>>> solution("13978431290823798458352374")
609638400
>>> solution("13978431295823798458352374")
2612736000
>>> solution("1397843129582379841238352374")
209018880
"""
return max(
# mypy cannot properly interpret reduce
int(reduce(lambda x, y: str(int(x) * int(y)), n[i : i + 13]))
for i in range(len(n) - 12)
)
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
The following undirected network consists of seven vertices and twelve edges
with a total weight of 243.

The same network can be represented by the matrix below.
A B C D E F G
A - 16 12 21 - - -
B 16 - - 17 20 - -
C 12 - - 28 - 31 -
D 21 17 28 - 18 19 23
E - 20 - 18 - - 11
F - - 31 19 - - 27
G - - - 23 11 27 -
However, it is possible to optimise the network by removing some edges and still
ensure that all points on the network remain connected. The network which achieves
the maximum saving is shown below. It has a weight of 93, representing a saving of
243 - 93 = 150 from the original network.
Using network.txt (right click and 'Save Link/Target As...'), a 6K text file
containing a network with forty vertices, and given in matrix form, find the maximum
saving which can be achieved by removing redundant edges whilst ensuring that the
network remains connected.
Solution:
We use Prim's algorithm to find a Minimum Spanning Tree.
Reference: https://en.wikipedia.org/wiki/Prim%27s_algorithm
"""
from __future__ import annotations
import os
from collections.abc import Mapping
EdgeT = tuple[int, int]
class Graph:
"""
A class representing an undirected weighted graph.
"""
def __init__(self, vertices: set[int], edges: Mapping[EdgeT, int]) -> None:
self.vertices: set[int] = vertices
self.edges: dict[EdgeT, int] = {
(min(edge), max(edge)): weight for edge, weight in edges.items()
}
def add_edge(self, edge: EdgeT, weight: int) -> None:
"""
Add a new edge to the graph.
>>> graph = Graph({1, 2}, {(2, 1): 4})
>>> graph.add_edge((3, 1), 5)
>>> sorted(graph.vertices)
[1, 2, 3]
>>> sorted([(v,k) for k,v in graph.edges.items()])
[(4, (1, 2)), (5, (1, 3))]
"""
self.vertices.add(edge[0])
self.vertices.add(edge[1])
self.edges[(min(edge), max(edge))] = weight
def prims_algorithm(self) -> Graph:
"""
Run Prim's algorithm to find the minimum spanning tree.
Reference: https://en.wikipedia.org/wiki/Prim%27s_algorithm
>>> graph = Graph({1,2,3,4},{(1,2):5, (1,3):10, (1,4):20, (2,4):30, (3,4):1})
>>> mst = graph.prims_algorithm()
>>> sorted(mst.vertices)
[1, 2, 3, 4]
>>> sorted(mst.edges)
[(1, 2), (1, 3), (3, 4)]
"""
subgraph: Graph = Graph({min(self.vertices)}, {})
min_edge: EdgeT
min_weight: int
edge: EdgeT
weight: int
while len(subgraph.vertices) < len(self.vertices):
min_weight = max(self.edges.values()) + 1
for edge, weight in self.edges.items():
if (edge[0] in subgraph.vertices) ^ (edge[1] in subgraph.vertices):
if weight < min_weight:
min_edge = edge
min_weight = weight
subgraph.add_edge(min_edge, min_weight)
return subgraph
def solution(filename: str = "p107_network.txt") -> int:
"""
Find the maximum saving which can be achieved by removing redundant edges
whilst ensuring that the network remains connected.
>>> solution("test_network.txt")
150
"""
script_dir: str = os.path.abspath(os.path.dirname(__file__))
network_file: str = os.path.join(script_dir, filename)
adjacency_matrix: list[list[str]]
edges: dict[EdgeT, int] = {}
data: list[str]
edge1: int
edge2: int
with open(network_file) as f:
data = f.read().strip().split("\n")
adjaceny_matrix = [line.split(",") for line in data]
for edge1 in range(1, len(adjaceny_matrix)):
for edge2 in range(edge1):
if adjaceny_matrix[edge1][edge2] != "-":
edges[(edge2, edge1)] = int(adjaceny_matrix[edge1][edge2])
graph: Graph = Graph(set(range(len(adjaceny_matrix))), edges)
subgraph: Graph = graph.prims_algorithm()
initial_total: int = sum(graph.edges.values())
optimal_total: int = sum(subgraph.edges.values())
return initial_total - optimal_total
if __name__ == "__main__":
print(f"{solution() = }")
| """
The following undirected network consists of seven vertices and twelve edges
with a total weight of 243.

The same network can be represented by the matrix below.
A B C D E F G
A - 16 12 21 - - -
B 16 - - 17 20 - -
C 12 - - 28 - 31 -
D 21 17 28 - 18 19 23
E - 20 - 18 - - 11
F - - 31 19 - - 27
G - - - 23 11 27 -
However, it is possible to optimise the network by removing some edges and still
ensure that all points on the network remain connected. The network which achieves
the maximum saving is shown below. It has a weight of 93, representing a saving of
243 - 93 = 150 from the original network.
Using network.txt (right click and 'Save Link/Target As...'), a 6K text file
containing a network with forty vertices, and given in matrix form, find the maximum
saving which can be achieved by removing redundant edges whilst ensuring that the
network remains connected.
Solution:
We use Prim's algorithm to find a Minimum Spanning Tree.
Reference: https://en.wikipedia.org/wiki/Prim%27s_algorithm
"""
from __future__ import annotations
import os
from collections.abc import Mapping
EdgeT = tuple[int, int]
class Graph:
"""
A class representing an undirected weighted graph.
"""
def __init__(self, vertices: set[int], edges: Mapping[EdgeT, int]) -> None:
self.vertices: set[int] = vertices
self.edges: dict[EdgeT, int] = {
(min(edge), max(edge)): weight for edge, weight in edges.items()
}
def add_edge(self, edge: EdgeT, weight: int) -> None:
"""
Add a new edge to the graph.
>>> graph = Graph({1, 2}, {(2, 1): 4})
>>> graph.add_edge((3, 1), 5)
>>> sorted(graph.vertices)
[1, 2, 3]
>>> sorted([(v,k) for k,v in graph.edges.items()])
[(4, (1, 2)), (5, (1, 3))]
"""
self.vertices.add(edge[0])
self.vertices.add(edge[1])
self.edges[(min(edge), max(edge))] = weight
def prims_algorithm(self) -> Graph:
"""
Run Prim's algorithm to find the minimum spanning tree.
Reference: https://en.wikipedia.org/wiki/Prim%27s_algorithm
>>> graph = Graph({1,2,3,4},{(1,2):5, (1,3):10, (1,4):20, (2,4):30, (3,4):1})
>>> mst = graph.prims_algorithm()
>>> sorted(mst.vertices)
[1, 2, 3, 4]
>>> sorted(mst.edges)
[(1, 2), (1, 3), (3, 4)]
"""
subgraph: Graph = Graph({min(self.vertices)}, {})
min_edge: EdgeT
min_weight: int
edge: EdgeT
weight: int
while len(subgraph.vertices) < len(self.vertices):
min_weight = max(self.edges.values()) + 1
for edge, weight in self.edges.items():
if (edge[0] in subgraph.vertices) ^ (edge[1] in subgraph.vertices):
if weight < min_weight:
min_edge = edge
min_weight = weight
subgraph.add_edge(min_edge, min_weight)
return subgraph
def solution(filename: str = "p107_network.txt") -> int:
"""
Find the maximum saving which can be achieved by removing redundant edges
whilst ensuring that the network remains connected.
>>> solution("test_network.txt")
150
"""
script_dir: str = os.path.abspath(os.path.dirname(__file__))
network_file: str = os.path.join(script_dir, filename)
adjacency_matrix: list[list[str]]
edges: dict[EdgeT, int] = {}
data: list[str]
edge1: int
edge2: int
with open(network_file) as f:
data = f.read().strip().split("\n")
adjaceny_matrix = [line.split(",") for line in data]
for edge1 in range(1, len(adjaceny_matrix)):
for edge2 in range(edge1):
if adjaceny_matrix[edge1][edge2] != "-":
edges[(edge2, edge1)] = int(adjaceny_matrix[edge1][edge2])
graph: Graph = Graph(set(range(len(adjaceny_matrix))), edges)
subgraph: Graph = graph.prims_algorithm()
initial_total: int = sum(graph.edges.values())
optimal_total: int = sum(subgraph.edges.values())
return initial_total - optimal_total
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import os
import sys
from . import rsa_key_generator as rkg
DEFAULT_BLOCK_SIZE = 128
BYTE_SIZE = 256
def get_blocks_from_text(
message: str, block_size: int = DEFAULT_BLOCK_SIZE
) -> list[int]:
message_bytes = message.encode("ascii")
block_ints = []
for block_start in range(0, len(message_bytes), block_size):
block_int = 0
for i in range(block_start, min(block_start + block_size, len(message_bytes))):
block_int += message_bytes[i] * (BYTE_SIZE ** (i % block_size))
block_ints.append(block_int)
return block_ints
def get_text_from_blocks(
block_ints: list[int], message_length: int, block_size: int = DEFAULT_BLOCK_SIZE
) -> str:
message: list[str] = []
for block_int in block_ints:
block_message: list[str] = []
for i in range(block_size - 1, -1, -1):
if len(message) + i < message_length:
ascii_number = block_int // (BYTE_SIZE**i)
block_int = block_int % (BYTE_SIZE**i)
block_message.insert(0, chr(ascii_number))
message.extend(block_message)
return "".join(message)
def encrypt_message(
message: str, key: tuple[int, int], block_size: int = DEFAULT_BLOCK_SIZE
) -> list[int]:
encrypted_blocks = []
n, e = key
for block in get_blocks_from_text(message, block_size):
encrypted_blocks.append(pow(block, e, n))
return encrypted_blocks
def decrypt_message(
encrypted_blocks: list[int],
message_length: int,
key: tuple[int, int],
block_size: int = DEFAULT_BLOCK_SIZE,
) -> str:
decrypted_blocks = []
n, d = key
for block in encrypted_blocks:
decrypted_blocks.append(pow(block, d, n))
return get_text_from_blocks(decrypted_blocks, message_length, block_size)
def read_key_file(key_filename: str) -> tuple[int, int, int]:
with open(key_filename) as fo:
content = fo.read()
key_size, n, eor_d = content.split(",")
return (int(key_size), int(n), int(eor_d))
def encrypt_and_write_to_file(
message_filename: str,
key_filename: str,
message: str,
block_size: int = DEFAULT_BLOCK_SIZE,
) -> str:
key_size, n, e = read_key_file(key_filename)
if key_size < block_size * 8:
sys.exit(
"ERROR: Block size is %s bits and key size is %s bits. The RSA cipher "
"requires the block size to be equal to or greater than the key size. "
"Either decrease the block size or use different keys."
% (block_size * 8, key_size)
)
encrypted_blocks = [str(i) for i in encrypt_message(message, (n, e), block_size)]
encrypted_content = ",".join(encrypted_blocks)
encrypted_content = f"{len(message)}_{block_size}_{encrypted_content}"
with open(message_filename, "w") as fo:
fo.write(encrypted_content)
return encrypted_content
def read_from_file_and_decrypt(message_filename: str, key_filename: str) -> str:
key_size, n, d = read_key_file(key_filename)
with open(message_filename) as fo:
content = fo.read()
message_length_str, block_size_str, encrypted_message = content.split("_")
message_length = int(message_length_str)
block_size = int(block_size_str)
if key_size < block_size * 8:
sys.exit(
"ERROR: Block size is %s bits and key size is %s bits. The RSA cipher "
"requires the block size to be equal to or greater than the key size. "
"Did you specify the correct key file and encrypted file?"
% (block_size * 8, key_size)
)
encrypted_blocks = []
for block in encrypted_message.split(","):
encrypted_blocks.append(int(block))
return decrypt_message(encrypted_blocks, message_length, (n, d), block_size)
def main() -> None:
filename = "encrypted_file.txt"
response = input(r"Encrypt\Decrypt [e\d]: ")
if response.lower().startswith("e"):
mode = "encrypt"
elif response.lower().startswith("d"):
mode = "decrypt"
if mode == "encrypt":
if not os.path.exists("rsa_pubkey.txt"):
rkg.make_key_files("rsa", 1024)
message = input("\nEnter message: ")
pubkey_filename = "rsa_pubkey.txt"
print(f"Encrypting and writing to {filename}...")
encrypted_text = encrypt_and_write_to_file(filename, pubkey_filename, message)
print("\nEncrypted text:")
print(encrypted_text)
elif mode == "decrypt":
privkey_filename = "rsa_privkey.txt"
print(f"Reading from {filename} and decrypting...")
decrypted_text = read_from_file_and_decrypt(filename, privkey_filename)
print("writing decryption to rsa_decryption.txt...")
with open("rsa_decryption.txt", "w") as dec:
dec.write(decrypted_text)
print("\nDecryption:")
print(decrypted_text)
if __name__ == "__main__":
main()
| import os
import sys
from . import rsa_key_generator as rkg
DEFAULT_BLOCK_SIZE = 128
BYTE_SIZE = 256
def get_blocks_from_text(
message: str, block_size: int = DEFAULT_BLOCK_SIZE
) -> list[int]:
message_bytes = message.encode("ascii")
block_ints = []
for block_start in range(0, len(message_bytes), block_size):
block_int = 0
for i in range(block_start, min(block_start + block_size, len(message_bytes))):
block_int += message_bytes[i] * (BYTE_SIZE ** (i % block_size))
block_ints.append(block_int)
return block_ints
def get_text_from_blocks(
block_ints: list[int], message_length: int, block_size: int = DEFAULT_BLOCK_SIZE
) -> str:
message: list[str] = []
for block_int in block_ints:
block_message: list[str] = []
for i in range(block_size - 1, -1, -1):
if len(message) + i < message_length:
ascii_number = block_int // (BYTE_SIZE**i)
block_int = block_int % (BYTE_SIZE**i)
block_message.insert(0, chr(ascii_number))
message.extend(block_message)
return "".join(message)
def encrypt_message(
message: str, key: tuple[int, int], block_size: int = DEFAULT_BLOCK_SIZE
) -> list[int]:
encrypted_blocks = []
n, e = key
for block in get_blocks_from_text(message, block_size):
encrypted_blocks.append(pow(block, e, n))
return encrypted_blocks
def decrypt_message(
encrypted_blocks: list[int],
message_length: int,
key: tuple[int, int],
block_size: int = DEFAULT_BLOCK_SIZE,
) -> str:
decrypted_blocks = []
n, d = key
for block in encrypted_blocks:
decrypted_blocks.append(pow(block, d, n))
return get_text_from_blocks(decrypted_blocks, message_length, block_size)
def read_key_file(key_filename: str) -> tuple[int, int, int]:
with open(key_filename) as fo:
content = fo.read()
key_size, n, eor_d = content.split(",")
return (int(key_size), int(n), int(eor_d))
def encrypt_and_write_to_file(
message_filename: str,
key_filename: str,
message: str,
block_size: int = DEFAULT_BLOCK_SIZE,
) -> str:
key_size, n, e = read_key_file(key_filename)
if key_size < block_size * 8:
sys.exit(
"ERROR: Block size is %s bits and key size is %s bits. The RSA cipher "
"requires the block size to be equal to or greater than the key size. "
"Either decrease the block size or use different keys."
% (block_size * 8, key_size)
)
encrypted_blocks = [str(i) for i in encrypt_message(message, (n, e), block_size)]
encrypted_content = ",".join(encrypted_blocks)
encrypted_content = f"{len(message)}_{block_size}_{encrypted_content}"
with open(message_filename, "w") as fo:
fo.write(encrypted_content)
return encrypted_content
def read_from_file_and_decrypt(message_filename: str, key_filename: str) -> str:
key_size, n, d = read_key_file(key_filename)
with open(message_filename) as fo:
content = fo.read()
message_length_str, block_size_str, encrypted_message = content.split("_")
message_length = int(message_length_str)
block_size = int(block_size_str)
if key_size < block_size * 8:
sys.exit(
"ERROR: Block size is %s bits and key size is %s bits. The RSA cipher "
"requires the block size to be equal to or greater than the key size. "
"Did you specify the correct key file and encrypted file?"
% (block_size * 8, key_size)
)
encrypted_blocks = []
for block in encrypted_message.split(","):
encrypted_blocks.append(int(block))
return decrypt_message(encrypted_blocks, message_length, (n, d), block_size)
def main() -> None:
filename = "encrypted_file.txt"
response = input(r"Encrypt\Decrypt [e\d]: ")
if response.lower().startswith("e"):
mode = "encrypt"
elif response.lower().startswith("d"):
mode = "decrypt"
if mode == "encrypt":
if not os.path.exists("rsa_pubkey.txt"):
rkg.make_key_files("rsa", 1024)
message = input("\nEnter message: ")
pubkey_filename = "rsa_pubkey.txt"
print(f"Encrypting and writing to {filename}...")
encrypted_text = encrypt_and_write_to_file(filename, pubkey_filename, message)
print("\nEncrypted text:")
print(encrypted_text)
elif mode == "decrypt":
privkey_filename = "rsa_privkey.txt"
print(f"Reading from {filename} and decrypting...")
decrypted_text = read_from_file_and_decrypt(filename, privkey_filename)
print("writing decryption to rsa_decryption.txt...")
with open("rsa_decryption.txt", "w") as dec:
dec.write(decrypted_text)
print("\nDecryption:")
print(decrypted_text)
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Number letter counts
Problem 17: https://projecteuler.net/problem=17
If the numbers 1 to 5 are written out in words: one, two, three, four, five,
then there are 3 + 3 + 5 + 4 + 4 = 19 letters used in total.
If all the numbers from 1 to 1000 (one thousand) inclusive were written out in
words, how many letters would be used?
NOTE: Do not count spaces or hyphens. For example, 342 (three hundred and
forty-two) contains 23 letters and 115 (one hundred and fifteen) contains 20
letters. The use of "and" when writing out numbers is in compliance withBritish
usage.
"""
def solution(n: int = 1000) -> int:
"""Returns the number of letters used to write all numbers from 1 to n.
where n is lower or equals to 1000.
>>> solution(1000)
21124
>>> solution(5)
19
"""
# number of letters in zero, one, two, ..., nineteen (0 for zero since it's
# never said aloud)
ones_counts = [0, 3, 3, 5, 4, 4, 3, 5, 5, 4, 3, 6, 6, 8, 8, 7, 7, 9, 8, 8]
# number of letters in twenty, thirty, ..., ninety (0 for numbers less than
# 20 due to inconsistency in teens)
tens_counts = [0, 0, 6, 6, 5, 5, 5, 7, 6, 6]
count = 0
for i in range(1, n + 1):
if i < 1000:
if i >= 100:
# add number of letters for "n hundred"
count += ones_counts[i // 100] + 7
if i % 100 != 0:
# add number of letters for "and" if number is not multiple
# of 100
count += 3
if 0 < i % 100 < 20:
# add number of letters for one, two, three, ..., nineteen
# (could be combined with below if not for inconsistency in
# teens)
count += ones_counts[i % 100]
else:
# add number of letters for twenty, twenty one, ..., ninety
# nine
count += ones_counts[i % 10]
count += tens_counts[(i % 100 - i % 10) // 10]
else:
count += ones_counts[i // 1000] + 8
return count
if __name__ == "__main__":
print(solution(int(input().strip())))
| """
Number letter counts
Problem 17: https://projecteuler.net/problem=17
If the numbers 1 to 5 are written out in words: one, two, three, four, five,
then there are 3 + 3 + 5 + 4 + 4 = 19 letters used in total.
If all the numbers from 1 to 1000 (one thousand) inclusive were written out in
words, how many letters would be used?
NOTE: Do not count spaces or hyphens. For example, 342 (three hundred and
forty-two) contains 23 letters and 115 (one hundred and fifteen) contains 20
letters. The use of "and" when writing out numbers is in compliance withBritish
usage.
"""
def solution(n: int = 1000) -> int:
"""Returns the number of letters used to write all numbers from 1 to n.
where n is lower or equals to 1000.
>>> solution(1000)
21124
>>> solution(5)
19
"""
# number of letters in zero, one, two, ..., nineteen (0 for zero since it's
# never said aloud)
ones_counts = [0, 3, 3, 5, 4, 4, 3, 5, 5, 4, 3, 6, 6, 8, 8, 7, 7, 9, 8, 8]
# number of letters in twenty, thirty, ..., ninety (0 for numbers less than
# 20 due to inconsistency in teens)
tens_counts = [0, 0, 6, 6, 5, 5, 5, 7, 6, 6]
count = 0
for i in range(1, n + 1):
if i < 1000:
if i >= 100:
# add number of letters for "n hundred"
count += ones_counts[i // 100] + 7
if i % 100 != 0:
# add number of letters for "and" if number is not multiple
# of 100
count += 3
if 0 < i % 100 < 20:
# add number of letters for one, two, three, ..., nineteen
# (could be combined with below if not for inconsistency in
# teens)
count += ones_counts[i % 100]
else:
# add number of letters for twenty, twenty one, ..., ninety
# nine
count += ones_counts[i % 10]
count += tens_counts[(i % 100 - i % 10) // 10]
else:
count += ones_counts[i // 1000] + 8
return count
if __name__ == "__main__":
print(solution(int(input().strip())))
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 074: https://projecteuler.net/problem=74
The number 145 is well known for the property that the sum of the factorial of its
digits is equal to 145:
1! + 4! + 5! = 1 + 24 + 120 = 145
Perhaps less well known is 169, in that it produces the longest chain of numbers that
link back to 169; it turns out that there are only three such loops that exist:
169 → 363601 → 1454 → 169
871 → 45361 → 871
872 → 45362 → 872
It is not difficult to prove that EVERY starting number will eventually get stuck in a
loop. For example,
69 → 363600 → 1454 → 169 → 363601 (→ 1454)
78 → 45360 → 871 → 45361 (→ 871)
540 → 145 (→ 145)
Starting with 69 produces a chain of five non-repeating terms, but the longest
non-repeating chain with a starting number below one million is sixty terms.
How many chains, with a starting number below one million, contain exactly sixty
non-repeating terms?
Solution approach:
This solution simply consists in a loop that generates the chains of non repeating
items using the cached sizes of the previous chains.
The generation of the chain stops before a repeating item or if the size of the chain
is greater then the desired one.
After generating each chain, the length is checked and the counter increases.
"""
from math import factorial
DIGIT_FACTORIAL: dict[str, int] = {str(digit): factorial(digit) for digit in range(10)}
def digit_factorial_sum(number: int) -> int:
"""
Function to perform the sum of the factorial of all the digits in number
>>> digit_factorial_sum(69.0)
Traceback (most recent call last):
...
TypeError: Parameter number must be int
>>> digit_factorial_sum(-1)
Traceback (most recent call last):
...
ValueError: Parameter number must be greater than or equal to 0
>>> digit_factorial_sum(0)
1
>>> digit_factorial_sum(69)
363600
"""
if not isinstance(number, int):
raise TypeError("Parameter number must be int")
if number < 0:
raise ValueError("Parameter number must be greater than or equal to 0")
# Converts number in string to iterate on its digits and adds its factorial.
return sum(DIGIT_FACTORIAL[digit] for digit in str(number))
def solution(chain_length: int = 60, number_limit: int = 1000000) -> int:
"""
Returns the number of numbers below number_limit that produce chains with exactly
chain_length non repeating elements.
>>> solution(10.0, 1000)
Traceback (most recent call last):
...
TypeError: Parameters chain_length and number_limit must be int
>>> solution(10, 1000.0)
Traceback (most recent call last):
...
TypeError: Parameters chain_length and number_limit must be int
>>> solution(0, 1000)
Traceback (most recent call last):
...
ValueError: Parameters chain_length and number_limit must be greater than 0
>>> solution(10, 0)
Traceback (most recent call last):
...
ValueError: Parameters chain_length and number_limit must be greater than 0
>>> solution(10, 1000)
26
"""
if not isinstance(chain_length, int) or not isinstance(number_limit, int):
raise TypeError("Parameters chain_length and number_limit must be int")
if chain_length <= 0 or number_limit <= 0:
raise ValueError(
"Parameters chain_length and number_limit must be greater than 0"
)
# the counter for the chains with the exact desired length
chains_counter = 0
# the cached sizes of the previous chains
chain_sets_lengths: dict[int, int] = {}
for start_chain_element in range(1, number_limit):
# The temporary set will contain the elements of the chain
chain_set = set()
chain_set_length = 0
# Stop computing the chain when you find a cached size, a repeating item or the
# length is greater then the desired one.
chain_element = start_chain_element
while (
chain_element not in chain_sets_lengths
and chain_element not in chain_set
and chain_set_length <= chain_length
):
chain_set.add(chain_element)
chain_set_length += 1
chain_element = digit_factorial_sum(chain_element)
if chain_element in chain_sets_lengths:
chain_set_length += chain_sets_lengths[chain_element]
chain_sets_lengths[start_chain_element] = chain_set_length
# If chain contains the exact amount of elements increase the counter
if chain_set_length == chain_length:
chains_counter += 1
return chains_counter
if __name__ == "__main__":
import doctest
doctest.testmod()
print(f"{solution()}")
| """
Project Euler Problem 074: https://projecteuler.net/problem=74
The number 145 is well known for the property that the sum of the factorial of its
digits is equal to 145:
1! + 4! + 5! = 1 + 24 + 120 = 145
Perhaps less well known is 169, in that it produces the longest chain of numbers that
link back to 169; it turns out that there are only three such loops that exist:
169 → 363601 → 1454 → 169
871 → 45361 → 871
872 → 45362 → 872
It is not difficult to prove that EVERY starting number will eventually get stuck in a
loop. For example,
69 → 363600 → 1454 → 169 → 363601 (→ 1454)
78 → 45360 → 871 → 45361 (→ 871)
540 → 145 (→ 145)
Starting with 69 produces a chain of five non-repeating terms, but the longest
non-repeating chain with a starting number below one million is sixty terms.
How many chains, with a starting number below one million, contain exactly sixty
non-repeating terms?
Solution approach:
This solution simply consists in a loop that generates the chains of non repeating
items using the cached sizes of the previous chains.
The generation of the chain stops before a repeating item or if the size of the chain
is greater then the desired one.
After generating each chain, the length is checked and the counter increases.
"""
from math import factorial
DIGIT_FACTORIAL: dict[str, int] = {str(digit): factorial(digit) for digit in range(10)}
def digit_factorial_sum(number: int) -> int:
"""
Function to perform the sum of the factorial of all the digits in number
>>> digit_factorial_sum(69.0)
Traceback (most recent call last):
...
TypeError: Parameter number must be int
>>> digit_factorial_sum(-1)
Traceback (most recent call last):
...
ValueError: Parameter number must be greater than or equal to 0
>>> digit_factorial_sum(0)
1
>>> digit_factorial_sum(69)
363600
"""
if not isinstance(number, int):
raise TypeError("Parameter number must be int")
if number < 0:
raise ValueError("Parameter number must be greater than or equal to 0")
# Converts number in string to iterate on its digits and adds its factorial.
return sum(DIGIT_FACTORIAL[digit] for digit in str(number))
def solution(chain_length: int = 60, number_limit: int = 1000000) -> int:
"""
Returns the number of numbers below number_limit that produce chains with exactly
chain_length non repeating elements.
>>> solution(10.0, 1000)
Traceback (most recent call last):
...
TypeError: Parameters chain_length and number_limit must be int
>>> solution(10, 1000.0)
Traceback (most recent call last):
...
TypeError: Parameters chain_length and number_limit must be int
>>> solution(0, 1000)
Traceback (most recent call last):
...
ValueError: Parameters chain_length and number_limit must be greater than 0
>>> solution(10, 0)
Traceback (most recent call last):
...
ValueError: Parameters chain_length and number_limit must be greater than 0
>>> solution(10, 1000)
26
"""
if not isinstance(chain_length, int) or not isinstance(number_limit, int):
raise TypeError("Parameters chain_length and number_limit must be int")
if chain_length <= 0 or number_limit <= 0:
raise ValueError(
"Parameters chain_length and number_limit must be greater than 0"
)
# the counter for the chains with the exact desired length
chains_counter = 0
# the cached sizes of the previous chains
chain_sets_lengths: dict[int, int] = {}
for start_chain_element in range(1, number_limit):
# The temporary set will contain the elements of the chain
chain_set = set()
chain_set_length = 0
# Stop computing the chain when you find a cached size, a repeating item or the
# length is greater then the desired one.
chain_element = start_chain_element
while (
chain_element not in chain_sets_lengths
and chain_element not in chain_set
and chain_set_length <= chain_length
):
chain_set.add(chain_element)
chain_set_length += 1
chain_element = digit_factorial_sum(chain_element)
if chain_element in chain_sets_lengths:
chain_set_length += chain_sets_lengths[chain_element]
chain_sets_lengths[start_chain_element] = chain_set_length
# If chain contains the exact amount of elements increase the counter
if chain_set_length == chain_length:
chains_counter += 1
return chains_counter
if __name__ == "__main__":
import doctest
doctest.testmod()
print(f"{solution()}")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
The sum-of-subsetsproblem states that a set of non-negative integers, and a
value M, determine all possible subsets of the given set whose summation sum
equal to given M.
Summation of the chosen numbers must be equal to given number M and one number
can be used only once.
"""
from __future__ import annotations
def generate_sum_of_subsets_soln(nums: list[int], max_sum: int) -> list[list[int]]:
result: list[list[int]] = []
path: list[int] = []
num_index = 0
remaining_nums_sum = sum(nums)
create_state_space_tree(nums, max_sum, num_index, path, result, remaining_nums_sum)
return result
def create_state_space_tree(
nums: list[int],
max_sum: int,
num_index: int,
path: list[int],
result: list[list[int]],
remaining_nums_sum: int,
) -> None:
"""
Creates a state space tree to iterate through each branch using DFS.
It terminates the branching of a node when any of the two conditions
given below satisfy.
This algorithm follows depth-fist-search and backtracks when the node is not
branchable.
"""
if sum(path) > max_sum or (remaining_nums_sum + sum(path)) < max_sum:
return
if sum(path) == max_sum:
result.append(path)
return
for index in range(num_index, len(nums)):
create_state_space_tree(
nums,
max_sum,
index + 1,
path + [nums[index]],
result,
remaining_nums_sum - nums[index],
)
"""
remove the comment to take an input from the user
print("Enter the elements")
nums = list(map(int, input().split()))
print("Enter max_sum sum")
max_sum = int(input())
"""
nums = [3, 34, 4, 12, 5, 2]
max_sum = 9
result = generate_sum_of_subsets_soln(nums, max_sum)
print(*result)
| """
The sum-of-subsetsproblem states that a set of non-negative integers, and a
value M, determine all possible subsets of the given set whose summation sum
equal to given M.
Summation of the chosen numbers must be equal to given number M and one number
can be used only once.
"""
from __future__ import annotations
def generate_sum_of_subsets_soln(nums: list[int], max_sum: int) -> list[list[int]]:
result: list[list[int]] = []
path: list[int] = []
num_index = 0
remaining_nums_sum = sum(nums)
create_state_space_tree(nums, max_sum, num_index, path, result, remaining_nums_sum)
return result
def create_state_space_tree(
nums: list[int],
max_sum: int,
num_index: int,
path: list[int],
result: list[list[int]],
remaining_nums_sum: int,
) -> None:
"""
Creates a state space tree to iterate through each branch using DFS.
It terminates the branching of a node when any of the two conditions
given below satisfy.
This algorithm follows depth-fist-search and backtracks when the node is not
branchable.
"""
if sum(path) > max_sum or (remaining_nums_sum + sum(path)) < max_sum:
return
if sum(path) == max_sum:
result.append(path)
return
for index in range(num_index, len(nums)):
create_state_space_tree(
nums,
max_sum,
index + 1,
path + [nums[index]],
result,
remaining_nums_sum - nums[index],
)
"""
remove the comment to take an input from the user
print("Enter the elements")
nums = list(map(int, input().split()))
print("Enter max_sum sum")
max_sum = int(input())
"""
nums = [3, 34, 4, 12, 5, 2]
max_sum = 9
result = generate_sum_of_subsets_soln(nums, max_sum)
print(*result)
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from __future__ import annotations
def find_primitive(n: int) -> int | None:
for r in range(1, n):
li = []
for x in range(n - 1):
val = pow(r, x, n)
if val in li:
break
li.append(val)
else:
return r
return None
if __name__ == "__main__":
q = int(input("Enter a prime number q: "))
a = find_primitive(q)
if a is None:
print(f"Cannot find the primitive for the value: {a!r}")
else:
a_private = int(input("Enter private key of A: "))
a_public = pow(a, a_private, q)
b_private = int(input("Enter private key of B: "))
b_public = pow(a, b_private, q)
a_secret = pow(b_public, a_private, q)
b_secret = pow(a_public, b_private, q)
print("The key value generated by A is: ", a_secret)
print("The key value generated by B is: ", b_secret)
| from __future__ import annotations
def find_primitive(n: int) -> int | None:
for r in range(1, n):
li = []
for x in range(n - 1):
val = pow(r, x, n)
if val in li:
break
li.append(val)
else:
return r
return None
if __name__ == "__main__":
q = int(input("Enter a prime number q: "))
a = find_primitive(q)
if a is None:
print(f"Cannot find the primitive for the value: {a!r}")
else:
a_private = int(input("Enter private key of A: "))
a_public = pow(a, a_private, q)
b_private = int(input("Enter private key of B: "))
b_public = pow(a, b_private, q)
a_secret = pow(b_public, a_private, q)
b_secret = pow(a_public, b_private, q)
print("The key value generated by A is: ", a_secret)
print("The key value generated by B is: ", b_secret)
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # @Author : lightXu
# @File : convolve.py
# @Time : 2019/7/8 0008 下午 16:13
from cv2 import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import array, dot, pad, ravel, uint8, zeros
def im2col(image, block_size):
rows, cols = image.shape
dst_height = cols - block_size[1] + 1
dst_width = rows - block_size[0] + 1
image_array = zeros((dst_height * dst_width, block_size[1] * block_size[0]))
row = 0
for i in range(0, dst_height):
for j in range(0, dst_width):
window = ravel(image[i : i + block_size[0], j : j + block_size[1]])
image_array[row, :] = window
row += 1
return image_array
def img_convolve(image, filter_kernel):
height, width = image.shape[0], image.shape[1]
k_size = filter_kernel.shape[0]
pad_size = k_size // 2
# Pads image with the edge values of array.
image_tmp = pad(image, pad_size, mode="edge")
# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
image_array = im2col(image_tmp, (k_size, k_size))
# turn the kernel into shape(k*k, 1)
kernel_array = ravel(filter_kernel)
# reshape and get the dst image
dst = dot(image_array, kernel_array).reshape(height, width)
return dst
if __name__ == "__main__":
# read original image
img = imread(r"../image_data/lena.jpg")
# turn image in gray scale value
gray = cvtColor(img, COLOR_BGR2GRAY)
# Laplace operator
Laplace_kernel = array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
out = img_convolve(gray, Laplace_kernel).astype(uint8)
imshow("Laplacian", out)
waitKey(0)
| # @Author : lightXu
# @File : convolve.py
# @Time : 2019/7/8 0008 下午 16:13
from cv2 import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import array, dot, pad, ravel, uint8, zeros
def im2col(image, block_size):
rows, cols = image.shape
dst_height = cols - block_size[1] + 1
dst_width = rows - block_size[0] + 1
image_array = zeros((dst_height * dst_width, block_size[1] * block_size[0]))
row = 0
for i in range(0, dst_height):
for j in range(0, dst_width):
window = ravel(image[i : i + block_size[0], j : j + block_size[1]])
image_array[row, :] = window
row += 1
return image_array
def img_convolve(image, filter_kernel):
height, width = image.shape[0], image.shape[1]
k_size = filter_kernel.shape[0]
pad_size = k_size // 2
# Pads image with the edge values of array.
image_tmp = pad(image, pad_size, mode="edge")
# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
image_array = im2col(image_tmp, (k_size, k_size))
# turn the kernel into shape(k*k, 1)
kernel_array = ravel(filter_kernel)
# reshape and get the dst image
dst = dot(image_array, kernel_array).reshape(height, width)
return dst
if __name__ == "__main__":
# read original image
img = imread(r"../image_data/lena.jpg")
# turn image in gray scale value
gray = cvtColor(img, COLOR_BGR2GRAY)
# Laplace operator
Laplace_kernel = array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
out = img_convolve(gray, Laplace_kernel).astype(uint8)
imshow("Laplacian", out)
waitKey(0)
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Approximates the area under the curve using the trapezoidal rule
"""
from __future__ import annotations
from collections.abc import Callable
def trapezoidal_area(
fnc: Callable[[int | float], int | float],
x_start: int | float,
x_end: int | float,
steps: int = 100,
) -> float:
"""
Treats curve as a collection of linear lines and sums the area of the
trapezium shape they form
:param fnc: a function which defines a curve
:param x_start: left end point to indicate the start of line segment
:param x_end: right end point to indicate end of line segment
:param steps: an accuracy gauge; more steps increases the accuracy
:return: a float representing the length of the curve
>>> def f(x):
... return 5
>>> f"{trapezoidal_area(f, 12.0, 14.0, 1000):.3f}"
'10.000'
>>> def f(x):
... return 9*x**2
>>> f"{trapezoidal_area(f, -4.0, 0, 10000):.4f}"
'192.0000'
>>> f"{trapezoidal_area(f, -4.0, 4.0, 10000):.4f}"
'384.0000'
"""
x1 = x_start
fx1 = fnc(x_start)
area = 0.0
for _ in range(steps):
# Approximates small segments of curve as linear and solve
# for trapezoidal area
x2 = (x_end - x_start) / steps + x1
fx2 = fnc(x2)
area += abs(fx2 + fx1) * (x2 - x1) / 2
# Increment step
x1 = x2
fx1 = fx2
return area
if __name__ == "__main__":
def f(x):
return x**3 + x**2
print("f(x) = x^3 + x^2")
print("The area between the curve, x = -5, x = 5 and the x axis is:")
i = 10
while i <= 100000:
print(f"with {i} steps: {trapezoidal_area(f, -5, 5, i)}")
i *= 10
| """
Approximates the area under the curve using the trapezoidal rule
"""
from __future__ import annotations
from collections.abc import Callable
def trapezoidal_area(
fnc: Callable[[int | float], int | float],
x_start: int | float,
x_end: int | float,
steps: int = 100,
) -> float:
"""
Treats curve as a collection of linear lines and sums the area of the
trapezium shape they form
:param fnc: a function which defines a curve
:param x_start: left end point to indicate the start of line segment
:param x_end: right end point to indicate end of line segment
:param steps: an accuracy gauge; more steps increases the accuracy
:return: a float representing the length of the curve
>>> def f(x):
... return 5
>>> f"{trapezoidal_area(f, 12.0, 14.0, 1000):.3f}"
'10.000'
>>> def f(x):
... return 9*x**2
>>> f"{trapezoidal_area(f, -4.0, 0, 10000):.4f}"
'192.0000'
>>> f"{trapezoidal_area(f, -4.0, 4.0, 10000):.4f}"
'384.0000'
"""
x1 = x_start
fx1 = fnc(x_start)
area = 0.0
for _ in range(steps):
# Approximates small segments of curve as linear and solve
# for trapezoidal area
x2 = (x_end - x_start) / steps + x1
fx2 = fnc(x2)
area += abs(fx2 + fx1) * (x2 - x1) / 2
# Increment step
x1 = x2
fx1 = fx2
return area
if __name__ == "__main__":
def f(x):
return x**3 + x**2
print("f(x) = x^3 + x^2")
print("The area between the curve, x = -5, x = 5 and the x axis is:")
i = 10
while i <= 100000:
print(f"with {i} steps: {trapezoidal_area(f, -5, 5, i)}")
i *= 10
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Wiggle Sort.
Given an unsorted array nums, reorder it such
that nums[0] < nums[1] > nums[2] < nums[3]....
For example:
if input numbers = [3, 5, 2, 1, 6, 4]
one possible Wiggle Sorted answer is [3, 5, 1, 6, 2, 4].
"""
def wiggle_sort(nums: list) -> list:
"""
Python implementation of wiggle.
Example:
>>> wiggle_sort([0, 5, 3, 2, 2])
[0, 5, 2, 3, 2]
>>> wiggle_sort([])
[]
>>> wiggle_sort([-2, -5, -45])
[-45, -2, -5]
>>> wiggle_sort([-2.1, -5.68, -45.11])
[-45.11, -2.1, -5.68]
"""
for i, _ in enumerate(nums):
if (i % 2 == 1) == (nums[i - 1] > nums[i]):
nums[i - 1], nums[i] = nums[i], nums[i - 1]
return nums
if __name__ == "__main__":
print("Enter the array elements:")
array = list(map(int, input().split()))
print("The unsorted array is:")
print(array)
print("Array after Wiggle sort:")
print(wiggle_sort(array))
| """
Wiggle Sort.
Given an unsorted array nums, reorder it such
that nums[0] < nums[1] > nums[2] < nums[3]....
For example:
if input numbers = [3, 5, 2, 1, 6, 4]
one possible Wiggle Sorted answer is [3, 5, 1, 6, 2, 4].
"""
def wiggle_sort(nums: list) -> list:
"""
Python implementation of wiggle.
Example:
>>> wiggle_sort([0, 5, 3, 2, 2])
[0, 5, 2, 3, 2]
>>> wiggle_sort([])
[]
>>> wiggle_sort([-2, -5, -45])
[-45, -2, -5]
>>> wiggle_sort([-2.1, -5.68, -45.11])
[-45.11, -2.1, -5.68]
"""
for i, _ in enumerate(nums):
if (i % 2 == 1) == (nums[i - 1] > nums[i]):
nums[i - 1], nums[i] = nums[i], nums[i - 1]
return nums
if __name__ == "__main__":
print("Enter the array elements:")
array = list(map(int, input().split()))
print("The unsorted array is:")
print(array)
print("Array after Wiggle sort:")
print(wiggle_sort(array))
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # https://en.m.wikipedia.org/wiki/Electric_power
from __future__ import annotations
from collections import namedtuple
def electric_power(voltage: float, current: float, power: float) -> tuple:
"""
This function can calculate any one of the three (voltage, current, power),
fundamental value of electrical system.
examples are below:
>>> electric_power(voltage=0, current=2, power=5)
result(name='voltage', value=2.5)
>>> electric_power(voltage=2, current=2, power=0)
result(name='power', value=4.0)
>>> electric_power(voltage=-2, current=3, power=0)
result(name='power', value=6.0)
>>> electric_power(voltage=2, current=4, power=2)
Traceback (most recent call last):
File "<stdin>", line 15, in <module>
ValueError: Only one argument must be 0
>>> electric_power(voltage=0, current=0, power=2)
Traceback (most recent call last):
File "<stdin>", line 19, in <module>
ValueError: Only one argument must be 0
>>> electric_power(voltage=0, current=2, power=-4)
Traceback (most recent call last):
File "<stdin>", line 23, in <modulei
ValueError: Power cannot be negative in any electrical/electronics system
>>> electric_power(voltage=2.2, current=2.2, power=0)
result(name='power', value=4.84)
"""
result = namedtuple("result", "name value")
if (voltage, current, power).count(0) != 1:
raise ValueError("Only one argument must be 0")
elif power < 0:
raise ValueError(
"Power cannot be negative in any electrical/electronics system"
)
elif voltage == 0:
return result("voltage", power / current)
elif current == 0:
return result("current", power / voltage)
elif power == 0:
return result("power", float(round(abs(voltage * current), 2)))
else:
raise ValueError("Exactly one argument must be 0")
if __name__ == "__main__":
import doctest
doctest.testmod()
| # https://en.m.wikipedia.org/wiki/Electric_power
from __future__ import annotations
from collections import namedtuple
def electric_power(voltage: float, current: float, power: float) -> tuple:
"""
This function can calculate any one of the three (voltage, current, power),
fundamental value of electrical system.
examples are below:
>>> electric_power(voltage=0, current=2, power=5)
result(name='voltage', value=2.5)
>>> electric_power(voltage=2, current=2, power=0)
result(name='power', value=4.0)
>>> electric_power(voltage=-2, current=3, power=0)
result(name='power', value=6.0)
>>> electric_power(voltage=2, current=4, power=2)
Traceback (most recent call last):
File "<stdin>", line 15, in <module>
ValueError: Only one argument must be 0
>>> electric_power(voltage=0, current=0, power=2)
Traceback (most recent call last):
File "<stdin>", line 19, in <module>
ValueError: Only one argument must be 0
>>> electric_power(voltage=0, current=2, power=-4)
Traceback (most recent call last):
File "<stdin>", line 23, in <modulei
ValueError: Power cannot be negative in any electrical/electronics system
>>> electric_power(voltage=2.2, current=2.2, power=0)
result(name='power', value=4.84)
"""
result = namedtuple("result", "name value")
if (voltage, current, power).count(0) != 1:
raise ValueError("Only one argument must be 0")
elif power < 0:
raise ValueError(
"Power cannot be negative in any electrical/electronics system"
)
elif voltage == 0:
return result("voltage", power / current)
elif current == 0:
return result("current", power / voltage)
elif power == 0:
return result("power", float(round(abs(voltage * current), 2)))
else:
raise ValueError("Exactly one argument must be 0")
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Jacobi Iteration Method - https://en.wikipedia.org/wiki/Jacobi_method
"""
from __future__ import annotations
import numpy as np
from numpy import float64
from numpy.typing import NDArray
# Method to find solution of system of linear equations
def jacobi_iteration_method(
coefficient_matrix: NDArray[float64],
constant_matrix: NDArray[float64],
init_val: list[int],
iterations: int,
) -> list[float]:
"""
Jacobi Iteration Method:
An iterative algorithm to determine the solutions of strictly diagonally dominant
system of linear equations
4x1 + x2 + x3 = 2
x1 + 5x2 + 2x3 = -6
x1 + 2x2 + 4x3 = -4
x_init = [0.5, -0.5 , -0.5]
Examples:
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
[0.909375, -1.14375, -0.7484375]
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Coefficient matrix dimensions must be nxn but received 2x3
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Coefficient and constant matrices dimensions must be nxn and nx1 but
received 3x3 and 2x1
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Number of initial values must be equal to number of rows in coefficient
matrix but received 2 and 3
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 0
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Iterations must be at least 1
"""
rows1, cols1 = coefficient_matrix.shape
rows2, cols2 = constant_matrix.shape
if rows1 != cols1:
raise ValueError(
f"Coefficient matrix dimensions must be nxn but received {rows1}x{cols1}"
)
if cols2 != 1:
raise ValueError(f"Constant matrix must be nx1 but received {rows2}x{cols2}")
if rows1 != rows2:
raise ValueError(
f"""Coefficient and constant matrices dimensions must be nxn and nx1 but
received {rows1}x{cols1} and {rows2}x{cols2}"""
)
if len(init_val) != rows1:
raise ValueError(
f"""Number of initial values must be equal to number of rows in coefficient
matrix but received {len(init_val)} and {rows1}"""
)
if iterations <= 0:
raise ValueError("Iterations must be at least 1")
table: NDArray[float64] = np.concatenate(
(coefficient_matrix, constant_matrix), axis=1
)
rows, cols = table.shape
strictly_diagonally_dominant(table)
# Iterates the whole matrix for given number of times
for _ in range(iterations):
new_val = []
for row in range(rows):
temp = 0
for col in range(cols):
if col == row:
denom = table[row][col]
elif col == cols - 1:
val = table[row][col]
else:
temp += (-1) * table[row][col] * init_val[col]
temp = (temp + val) / denom
new_val.append(temp)
init_val = new_val
return [float(i) for i in new_val]
# Checks if the given matrix is strictly diagonally dominant
def strictly_diagonally_dominant(table: NDArray[float64]) -> bool:
"""
>>> table = np.array([[4, 1, 1, 2], [1, 5, 2, -6], [1, 2, 4, -4]])
>>> strictly_diagonally_dominant(table)
True
>>> table = np.array([[4, 1, 1, 2], [1, 5, 2, -6], [1, 2, 3, -4]])
>>> strictly_diagonally_dominant(table)
Traceback (most recent call last):
...
ValueError: Coefficient matrix is not strictly diagonally dominant
"""
rows, cols = table.shape
is_diagonally_dominant = True
for i in range(0, rows):
total = 0
for j in range(0, cols - 1):
if i == j:
continue
else:
total += table[i][j]
if table[i][i] <= total:
raise ValueError("Coefficient matrix is not strictly diagonally dominant")
return is_diagonally_dominant
# Test Cases
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
Jacobi Iteration Method - https://en.wikipedia.org/wiki/Jacobi_method
"""
from __future__ import annotations
import numpy as np
from numpy import float64
from numpy.typing import NDArray
# Method to find solution of system of linear equations
def jacobi_iteration_method(
coefficient_matrix: NDArray[float64],
constant_matrix: NDArray[float64],
init_val: list[int],
iterations: int,
) -> list[float]:
"""
Jacobi Iteration Method:
An iterative algorithm to determine the solutions of strictly diagonally dominant
system of linear equations
4x1 + x2 + x3 = 2
x1 + 5x2 + 2x3 = -6
x1 + 2x2 + 4x3 = -4
x_init = [0.5, -0.5 , -0.5]
Examples:
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
[0.909375, -1.14375, -0.7484375]
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Coefficient matrix dimensions must be nxn but received 2x3
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Coefficient and constant matrices dimensions must be nxn and nx1 but
received 3x3 and 2x1
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5]
>>> iterations = 3
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Number of initial values must be equal to number of rows in coefficient
matrix but received 2 and 3
>>> coefficient = np.array([[4, 1, 1], [1, 5, 2], [1, 2, 4]])
>>> constant = np.array([[2], [-6], [-4]])
>>> init_val = [0.5, -0.5, -0.5]
>>> iterations = 0
>>> jacobi_iteration_method(coefficient, constant, init_val, iterations)
Traceback (most recent call last):
...
ValueError: Iterations must be at least 1
"""
rows1, cols1 = coefficient_matrix.shape
rows2, cols2 = constant_matrix.shape
if rows1 != cols1:
raise ValueError(
f"Coefficient matrix dimensions must be nxn but received {rows1}x{cols1}"
)
if cols2 != 1:
raise ValueError(f"Constant matrix must be nx1 but received {rows2}x{cols2}")
if rows1 != rows2:
raise ValueError(
f"""Coefficient and constant matrices dimensions must be nxn and nx1 but
received {rows1}x{cols1} and {rows2}x{cols2}"""
)
if len(init_val) != rows1:
raise ValueError(
f"""Number of initial values must be equal to number of rows in coefficient
matrix but received {len(init_val)} and {rows1}"""
)
if iterations <= 0:
raise ValueError("Iterations must be at least 1")
table: NDArray[float64] = np.concatenate(
(coefficient_matrix, constant_matrix), axis=1
)
rows, cols = table.shape
strictly_diagonally_dominant(table)
# Iterates the whole matrix for given number of times
for _ in range(iterations):
new_val = []
for row in range(rows):
temp = 0
for col in range(cols):
if col == row:
denom = table[row][col]
elif col == cols - 1:
val = table[row][col]
else:
temp += (-1) * table[row][col] * init_val[col]
temp = (temp + val) / denom
new_val.append(temp)
init_val = new_val
return [float(i) for i in new_val]
# Checks if the given matrix is strictly diagonally dominant
def strictly_diagonally_dominant(table: NDArray[float64]) -> bool:
"""
>>> table = np.array([[4, 1, 1, 2], [1, 5, 2, -6], [1, 2, 4, -4]])
>>> strictly_diagonally_dominant(table)
True
>>> table = np.array([[4, 1, 1, 2], [1, 5, 2, -6], [1, 2, 3, -4]])
>>> strictly_diagonally_dominant(table)
Traceback (most recent call last):
...
ValueError: Coefficient matrix is not strictly diagonally dominant
"""
rows, cols = table.shape
is_diagonally_dominant = True
for i in range(0, rows):
total = 0
for j in range(0, cols - 1):
if i == j:
continue
else:
total += table[i][j]
if table[i][i] <= total:
raise ValueError("Coefficient matrix is not strictly diagonally dominant")
return is_diagonally_dominant
# Test Cases
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 6: https://projecteuler.net/problem=6
Sum square difference
The sum of the squares of the first ten natural numbers is,
1^2 + 2^2 + ... + 10^2 = 385
The square of the sum of the first ten natural numbers is,
(1 + 2 + ... + 10)^2 = 55^2 = 3025
Hence the difference between the sum of the squares of the first ten
natural numbers and the square of the sum is 3025 - 385 = 2640.
Find the difference between the sum of the squares of the first one
hundred natural numbers and the square of the sum.
"""
def solution(n: int = 100) -> int:
"""
Returns the difference between the sum of the squares of the first n
natural numbers and the square of the sum.
>>> solution(10)
2640
>>> solution(15)
13160
>>> solution(20)
41230
>>> solution(50)
1582700
"""
sum_of_squares = 0
sum_of_ints = 0
for i in range(1, n + 1):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 6: https://projecteuler.net/problem=6
Sum square difference
The sum of the squares of the first ten natural numbers is,
1^2 + 2^2 + ... + 10^2 = 385
The square of the sum of the first ten natural numbers is,
(1 + 2 + ... + 10)^2 = 55^2 = 3025
Hence the difference between the sum of the squares of the first ten
natural numbers and the square of the sum is 3025 - 385 = 2640.
Find the difference between the sum of the squares of the first one
hundred natural numbers and the square of the sum.
"""
def solution(n: int = 100) -> int:
"""
Returns the difference between the sum of the squares of the first n
natural numbers and the square of the sum.
>>> solution(10)
2640
>>> solution(15)
13160
>>> solution(20)
41230
>>> solution(50)
1582700
"""
sum_of_squares = 0
sum_of_ints = 0
for i in range(1, n + 1):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sol1 import PokerHand
SORTED_HANDS = (
"4S 3H 2C 7S 5H",
"9D 8H 2C 6S 7H",
"2D 6D 9D TH 7D",
"TC 8C 2S JH 6C",
"JH 8S TH AH QH",
"TS KS 5S 9S AC",
"KD 6S 9D TH AD",
"KS 8D 4D 9S 4S", # pair
"8C 4S KH JS 4D", # pair
"QH 8H KD JH 8S", # pair
"KC 4H KS 2H 8D", # pair
"KD 4S KC 3H 8S", # pair
"AH 8S AS KC JH", # pair
"3H 4C 4H 3S 2H", # 2 pairs
"5S 5D 2C KH KH", # 2 pairs
"3C KH 5D 5S KH", # 2 pairs
"AS 3C KH AD KH", # 2 pairs
"7C 7S 3S 7H 5S", # 3 of a kind
"7C 7S KH 2H 7H", # 3 of a kind
"AC KH QH AH AS", # 3 of a kind
"2H 4D 3C AS 5S", # straight (low ace)
"3C 5C 4C 2C 6H", # straight
"6S 8S 7S 5H 9H", # straight
"JS QS 9H TS KH", # straight
"QC KH TS JS AH", # straight (high ace)
"8C 9C 5C 3C TC", # flush
"3S 8S 9S 5S KS", # flush
"4C 5C 9C 8C KC", # flush
"JH 8H AH KH QH", # flush
"3D 2H 3H 2C 2D", # full house
"2H 2C 3S 3H 3D", # full house
"KH KC 3S 3H 3D", # full house
"JC 6H JS JD JH", # 4 of a kind
"JC 7H JS JD JH", # 4 of a kind
"JC KH JS JD JH", # 4 of a kind
"2S AS 4S 5S 3S", # straight flush (low ace)
"2D 6D 3D 4D 5D", # straight flush
"5C 6C 3C 7C 4C", # straight flush
"JH 9H TH KH QH", # straight flush
"JH AH TH KH QH", # royal flush (high ace straight flush)
)
TEST_COMPARE = (
("2H 3H 4H 5H 6H", "KS AS TS QS JS", "Loss"),
("2H 3H 4H 5H 6H", "AS AD AC AH JD", "Win"),
("AS AH 2H AD AC", "JS JD JC JH 3D", "Win"),
("2S AH 2H AS AC", "JS JD JC JH AD", "Loss"),
("2S AH 2H AS AC", "2H 3H 5H 6H 7H", "Win"),
("AS 3S 4S 8S 2S", "2H 3H 5H 6H 7H", "Win"),
("2H 3H 5H 6H 7H", "2S 3H 4H 5S 6C", "Win"),
("2S 3H 4H 5S 6C", "3D 4C 5H 6H 2S", "Tie"),
("2S 3H 4H 5S 6C", "AH AC 5H 6H AS", "Win"),
("2S 2H 4H 5S 4C", "AH AC 5H 6H AS", "Loss"),
("2S 2H 4H 5S 4C", "AH AC 5H 6H 7S", "Win"),
("6S AD 7H 4S AS", "AH AC 5H 6H 7S", "Loss"),
("2S AH 4H 5S KC", "AH AC 5H 6H 7S", "Loss"),
("2S 3H 6H 7S 9C", "7H 3C TH 6H 9S", "Loss"),
("4S 5H 6H TS AC", "3S 5H 6H TS AC", "Win"),
("2S AH 4H 5S 6C", "AD 4C 5H 6H 2C", "Tie"),
("AS AH 3H AD AC", "AS AH 2H AD AC", "Win"),
("AH AC 5H 5C QS", "AH AC 5H 5C KS", "Loss"),
("AH AC 5H 5C QS", "KH KC 5H 5C QS", "Win"),
("7C 7S KH 2H 7H", "3C 3S AH 2H 3H", "Win"),
("3C 3S AH 2H 3H", "7C 7S KH 2H 7H", "Loss"),
("6H 5H 4H 3H 2H", "5H 4H 3H 2H AH", "Win"),
("5H 4H 3H 2H AH", "5H 4H 3H 2H AH", "Tie"),
("5H 4H 3H 2H AH", "6H 5H 4H 3H 2H", "Loss"),
("AH AD KS KC AC", "AH KD KH AC KC", "Win"),
("2H 4D 3C AS 5S", "2H 4D 3C 6S 5S", "Loss"),
("2H 3S 3C 3H 2S", "3S 3C 2S 2H 2D", "Win"),
("4D 6D 5D 2D JH", "3S 8S 3H TC KH", "Loss"),
("4S 6C 8S 3S 7S", "AD KS 2D 7D 7C", "Loss"),
("6S 4C 7H 8C 3H", "5H JC AH 9D 9C", "Loss"),
("9D 9H JH TC QH", "3C 2S JS 5C 7H", "Win"),
("2H TC 8S AD 9S", "4H TS 7H 2C 5C", "Win"),
("9D 3S 2C 7S 7C", "JC TD 3C TC 9H", "Loss"),
)
TEST_FLUSH = (
("2H 3H 4H 5H 6H", True),
("AS AH 2H AD AC", False),
("2H 3H 5H 6H 7H", True),
("KS AS TS QS JS", True),
("8H 9H QS JS TH", False),
("AS 3S 4S 8S 2S", True),
)
TEST_STRAIGHT = (
("2H 3H 4H 5H 6H", True),
("AS AH 2H AD AC", False),
("2H 3H 5H 6H 7H", False),
("KS AS TS QS JS", True),
("8H 9H QS JS TH", True),
)
TEST_FIVE_HIGH_STRAIGHT = (
("2H 4D 3C AS 5S", True, [5, 4, 3, 2, 14]),
("2H 5D 3C AS 5S", False, [14, 5, 5, 3, 2]),
("JH QD KC AS TS", False, [14, 13, 12, 11, 10]),
("9D 3S 2C 7S 7C", False, [9, 7, 7, 3, 2]),
)
TEST_KIND = (
("JH AH TH KH QH", 0),
("JH 9H TH KH QH", 0),
("JC KH JS JD JH", 7),
("KH KC 3S 3H 3D", 6),
("8C 9C 5C 3C TC", 0),
("JS QS 9H TS KH", 0),
("7C 7S KH 2H 7H", 3),
("3C KH 5D 5S KH", 2),
("QH 8H KD JH 8S", 1),
("2D 6D 9D TH 7D", 0),
)
TEST_TYPES = (
("JH AH TH KH QH", 23),
("JH 9H TH KH QH", 22),
("JC KH JS JD JH", 21),
("KH KC 3S 3H 3D", 20),
("8C 9C 5C 3C TC", 19),
("JS QS 9H TS KH", 18),
("7C 7S KH 2H 7H", 17),
("3C KH 5D 5S KH", 16),
("QH 8H KD JH 8S", 15),
("2D 6D 9D TH 7D", 14),
)
def generate_random_hand():
play, oppo = randrange(len(SORTED_HANDS)), randrange(len(SORTED_HANDS))
expected = ["Loss", "Tie", "Win"][(play >= oppo) + (play > oppo)]
hand, other = SORTED_HANDS[play], SORTED_HANDS[oppo]
return hand, other, expected
def generate_random_hands(number_of_hands: int = 100):
return (generate_random_hand() for _ in range(number_of_hands))
@pytest.mark.parametrize("hand, expected", TEST_FLUSH)
def test_hand_is_flush(hand, expected):
assert PokerHand(hand)._is_flush() == expected
@pytest.mark.parametrize("hand, expected", TEST_STRAIGHT)
def test_hand_is_straight(hand, expected):
assert PokerHand(hand)._is_straight() == expected
@pytest.mark.parametrize("hand, expected, card_values", TEST_FIVE_HIGH_STRAIGHT)
def test_hand_is_five_high_straight(hand, expected, card_values):
player = PokerHand(hand)
assert player._is_five_high_straight() == expected
assert player._card_values == card_values
@pytest.mark.parametrize("hand, expected", TEST_KIND)
def test_hand_is_same_kind(hand, expected):
assert PokerHand(hand)._is_same_kind() == expected
@pytest.mark.parametrize("hand, expected", TEST_TYPES)
def test_hand_values(hand, expected):
assert PokerHand(hand)._hand_type == expected
@pytest.mark.parametrize("hand, other, expected", TEST_COMPARE)
def test_compare_simple(hand, other, expected):
assert PokerHand(hand).compare_with(PokerHand(other)) == expected
@pytest.mark.parametrize("hand, other, expected", generate_random_hands())
def test_compare_random(hand, other, expected):
assert PokerHand(hand).compare_with(PokerHand(other)) == expected
def test_hand_sorted():
poker_hands = [PokerHand(hand) for hand in SORTED_HANDS]
list_copy = poker_hands.copy()
shuffle(list_copy)
user_sorted = chain(sorted(list_copy))
for index, hand in enumerate(user_sorted):
assert hand == poker_hands[index]
def test_custom_sort_five_high_straight():
# Test that five high straights are compared correctly.
pokerhands = [PokerHand("2D AC 3H 4H 5S"), PokerHand("2S 3H 4H 5S 6C")]
pokerhands.sort(reverse=True)
assert pokerhands[0].__str__() == "2S 3H 4H 5S 6C"
def test_multiple_calls_five_high_straight():
# Multiple calls to five_high_straight function should still return True
# and shouldn't mutate the list in every call other than the first.
pokerhand = PokerHand("2C 4S AS 3D 5C")
expected = True
expected_card_values = [5, 4, 3, 2, 14]
for _ in range(10):
assert pokerhand._is_five_high_straight() == expected
assert pokerhand._card_values == expected_card_values
def test_euler_project():
# Problem number 54 from Project Euler
# Testing from poker_hands.txt file
answer = 0
script_dir = os.path.abspath(os.path.dirname(__file__))
poker_hands = os.path.join(script_dir, "poker_hands.txt")
with open(poker_hands) as file_hand:
for line in file_hand:
player_hand = line[:14].strip()
opponent_hand = line[15:].strip()
player, opponent = PokerHand(player_hand), PokerHand(opponent_hand)
output = player.compare_with(opponent)
if output == "Win":
answer += 1
assert answer == 376
| import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sol1 import PokerHand
SORTED_HANDS = (
"4S 3H 2C 7S 5H",
"9D 8H 2C 6S 7H",
"2D 6D 9D TH 7D",
"TC 8C 2S JH 6C",
"JH 8S TH AH QH",
"TS KS 5S 9S AC",
"KD 6S 9D TH AD",
"KS 8D 4D 9S 4S", # pair
"8C 4S KH JS 4D", # pair
"QH 8H KD JH 8S", # pair
"KC 4H KS 2H 8D", # pair
"KD 4S KC 3H 8S", # pair
"AH 8S AS KC JH", # pair
"3H 4C 4H 3S 2H", # 2 pairs
"5S 5D 2C KH KH", # 2 pairs
"3C KH 5D 5S KH", # 2 pairs
"AS 3C KH AD KH", # 2 pairs
"7C 7S 3S 7H 5S", # 3 of a kind
"7C 7S KH 2H 7H", # 3 of a kind
"AC KH QH AH AS", # 3 of a kind
"2H 4D 3C AS 5S", # straight (low ace)
"3C 5C 4C 2C 6H", # straight
"6S 8S 7S 5H 9H", # straight
"JS QS 9H TS KH", # straight
"QC KH TS JS AH", # straight (high ace)
"8C 9C 5C 3C TC", # flush
"3S 8S 9S 5S KS", # flush
"4C 5C 9C 8C KC", # flush
"JH 8H AH KH QH", # flush
"3D 2H 3H 2C 2D", # full house
"2H 2C 3S 3H 3D", # full house
"KH KC 3S 3H 3D", # full house
"JC 6H JS JD JH", # 4 of a kind
"JC 7H JS JD JH", # 4 of a kind
"JC KH JS JD JH", # 4 of a kind
"2S AS 4S 5S 3S", # straight flush (low ace)
"2D 6D 3D 4D 5D", # straight flush
"5C 6C 3C 7C 4C", # straight flush
"JH 9H TH KH QH", # straight flush
"JH AH TH KH QH", # royal flush (high ace straight flush)
)
TEST_COMPARE = (
("2H 3H 4H 5H 6H", "KS AS TS QS JS", "Loss"),
("2H 3H 4H 5H 6H", "AS AD AC AH JD", "Win"),
("AS AH 2H AD AC", "JS JD JC JH 3D", "Win"),
("2S AH 2H AS AC", "JS JD JC JH AD", "Loss"),
("2S AH 2H AS AC", "2H 3H 5H 6H 7H", "Win"),
("AS 3S 4S 8S 2S", "2H 3H 5H 6H 7H", "Win"),
("2H 3H 5H 6H 7H", "2S 3H 4H 5S 6C", "Win"),
("2S 3H 4H 5S 6C", "3D 4C 5H 6H 2S", "Tie"),
("2S 3H 4H 5S 6C", "AH AC 5H 6H AS", "Win"),
("2S 2H 4H 5S 4C", "AH AC 5H 6H AS", "Loss"),
("2S 2H 4H 5S 4C", "AH AC 5H 6H 7S", "Win"),
("6S AD 7H 4S AS", "AH AC 5H 6H 7S", "Loss"),
("2S AH 4H 5S KC", "AH AC 5H 6H 7S", "Loss"),
("2S 3H 6H 7S 9C", "7H 3C TH 6H 9S", "Loss"),
("4S 5H 6H TS AC", "3S 5H 6H TS AC", "Win"),
("2S AH 4H 5S 6C", "AD 4C 5H 6H 2C", "Tie"),
("AS AH 3H AD AC", "AS AH 2H AD AC", "Win"),
("AH AC 5H 5C QS", "AH AC 5H 5C KS", "Loss"),
("AH AC 5H 5C QS", "KH KC 5H 5C QS", "Win"),
("7C 7S KH 2H 7H", "3C 3S AH 2H 3H", "Win"),
("3C 3S AH 2H 3H", "7C 7S KH 2H 7H", "Loss"),
("6H 5H 4H 3H 2H", "5H 4H 3H 2H AH", "Win"),
("5H 4H 3H 2H AH", "5H 4H 3H 2H AH", "Tie"),
("5H 4H 3H 2H AH", "6H 5H 4H 3H 2H", "Loss"),
("AH AD KS KC AC", "AH KD KH AC KC", "Win"),
("2H 4D 3C AS 5S", "2H 4D 3C 6S 5S", "Loss"),
("2H 3S 3C 3H 2S", "3S 3C 2S 2H 2D", "Win"),
("4D 6D 5D 2D JH", "3S 8S 3H TC KH", "Loss"),
("4S 6C 8S 3S 7S", "AD KS 2D 7D 7C", "Loss"),
("6S 4C 7H 8C 3H", "5H JC AH 9D 9C", "Loss"),
("9D 9H JH TC QH", "3C 2S JS 5C 7H", "Win"),
("2H TC 8S AD 9S", "4H TS 7H 2C 5C", "Win"),
("9D 3S 2C 7S 7C", "JC TD 3C TC 9H", "Loss"),
)
TEST_FLUSH = (
("2H 3H 4H 5H 6H", True),
("AS AH 2H AD AC", False),
("2H 3H 5H 6H 7H", True),
("KS AS TS QS JS", True),
("8H 9H QS JS TH", False),
("AS 3S 4S 8S 2S", True),
)
TEST_STRAIGHT = (
("2H 3H 4H 5H 6H", True),
("AS AH 2H AD AC", False),
("2H 3H 5H 6H 7H", False),
("KS AS TS QS JS", True),
("8H 9H QS JS TH", True),
)
TEST_FIVE_HIGH_STRAIGHT = (
("2H 4D 3C AS 5S", True, [5, 4, 3, 2, 14]),
("2H 5D 3C AS 5S", False, [14, 5, 5, 3, 2]),
("JH QD KC AS TS", False, [14, 13, 12, 11, 10]),
("9D 3S 2C 7S 7C", False, [9, 7, 7, 3, 2]),
)
TEST_KIND = (
("JH AH TH KH QH", 0),
("JH 9H TH KH QH", 0),
("JC KH JS JD JH", 7),
("KH KC 3S 3H 3D", 6),
("8C 9C 5C 3C TC", 0),
("JS QS 9H TS KH", 0),
("7C 7S KH 2H 7H", 3),
("3C KH 5D 5S KH", 2),
("QH 8H KD JH 8S", 1),
("2D 6D 9D TH 7D", 0),
)
TEST_TYPES = (
("JH AH TH KH QH", 23),
("JH 9H TH KH QH", 22),
("JC KH JS JD JH", 21),
("KH KC 3S 3H 3D", 20),
("8C 9C 5C 3C TC", 19),
("JS QS 9H TS KH", 18),
("7C 7S KH 2H 7H", 17),
("3C KH 5D 5S KH", 16),
("QH 8H KD JH 8S", 15),
("2D 6D 9D TH 7D", 14),
)
def generate_random_hand():
play, oppo = randrange(len(SORTED_HANDS)), randrange(len(SORTED_HANDS))
expected = ["Loss", "Tie", "Win"][(play >= oppo) + (play > oppo)]
hand, other = SORTED_HANDS[play], SORTED_HANDS[oppo]
return hand, other, expected
def generate_random_hands(number_of_hands: int = 100):
return (generate_random_hand() for _ in range(number_of_hands))
@pytest.mark.parametrize("hand, expected", TEST_FLUSH)
def test_hand_is_flush(hand, expected):
assert PokerHand(hand)._is_flush() == expected
@pytest.mark.parametrize("hand, expected", TEST_STRAIGHT)
def test_hand_is_straight(hand, expected):
assert PokerHand(hand)._is_straight() == expected
@pytest.mark.parametrize("hand, expected, card_values", TEST_FIVE_HIGH_STRAIGHT)
def test_hand_is_five_high_straight(hand, expected, card_values):
player = PokerHand(hand)
assert player._is_five_high_straight() == expected
assert player._card_values == card_values
@pytest.mark.parametrize("hand, expected", TEST_KIND)
def test_hand_is_same_kind(hand, expected):
assert PokerHand(hand)._is_same_kind() == expected
@pytest.mark.parametrize("hand, expected", TEST_TYPES)
def test_hand_values(hand, expected):
assert PokerHand(hand)._hand_type == expected
@pytest.mark.parametrize("hand, other, expected", TEST_COMPARE)
def test_compare_simple(hand, other, expected):
assert PokerHand(hand).compare_with(PokerHand(other)) == expected
@pytest.mark.parametrize("hand, other, expected", generate_random_hands())
def test_compare_random(hand, other, expected):
assert PokerHand(hand).compare_with(PokerHand(other)) == expected
def test_hand_sorted():
poker_hands = [PokerHand(hand) for hand in SORTED_HANDS]
list_copy = poker_hands.copy()
shuffle(list_copy)
user_sorted = chain(sorted(list_copy))
for index, hand in enumerate(user_sorted):
assert hand == poker_hands[index]
def test_custom_sort_five_high_straight():
# Test that five high straights are compared correctly.
pokerhands = [PokerHand("2D AC 3H 4H 5S"), PokerHand("2S 3H 4H 5S 6C")]
pokerhands.sort(reverse=True)
assert pokerhands[0].__str__() == "2S 3H 4H 5S 6C"
def test_multiple_calls_five_high_straight():
# Multiple calls to five_high_straight function should still return True
# and shouldn't mutate the list in every call other than the first.
pokerhand = PokerHand("2C 4S AS 3D 5C")
expected = True
expected_card_values = [5, 4, 3, 2, 14]
for _ in range(10):
assert pokerhand._is_five_high_straight() == expected
assert pokerhand._card_values == expected_card_values
def test_euler_project():
# Problem number 54 from Project Euler
# Testing from poker_hands.txt file
answer = 0
script_dir = os.path.abspath(os.path.dirname(__file__))
poker_hands = os.path.join(script_dir, "poker_hands.txt")
with open(poker_hands) as file_hand:
for line in file_hand:
player_hand = line[:14].strip()
opponent_hand = line[15:].strip()
player, opponent = PokerHand(player_hand), PokerHand(opponent_hand)
output = player.compare_with(opponent)
if output == "Win":
answer += 1
assert answer == 376
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """Matrix Exponentiation"""
import timeit
"""
Matrix Exponentiation is a technique to solve linear recurrences in logarithmic time.
You read more about it here:
https://zobayer.blogspot.com/2010/11/matrix-exponentiation.html
https://www.hackerearth.com/practice/notes/matrix-exponentiation-1/
"""
class Matrix:
def __init__(self, arg):
if isinstance(arg, list): # Initializes a matrix identical to the one provided.
self.t = arg
self.n = len(arg)
else: # Initializes a square matrix of the given size and set values to zero.
self.n = arg
self.t = [[0 for _ in range(self.n)] for _ in range(self.n)]
def __mul__(self, b):
matrix = Matrix(self.n)
for i in range(self.n):
for j in range(self.n):
for k in range(self.n):
matrix.t[i][j] += self.t[i][k] * b.t[k][j]
return matrix
def modular_exponentiation(a, b):
matrix = Matrix([[1, 0], [0, 1]])
while b > 0:
if b & 1:
matrix *= a
a *= a
b >>= 1
return matrix
def fibonacci_with_matrix_exponentiation(n, f1, f2):
# Trivial Cases
if n == 1:
return f1
elif n == 2:
return f2
matrix = Matrix([[1, 1], [1, 0]])
matrix = modular_exponentiation(matrix, n - 2)
return f2 * matrix.t[0][0] + f1 * matrix.t[0][1]
def simple_fibonacci(n, f1, f2):
# Trivial Cases
if n == 1:
return f1
elif n == 2:
return f2
fn_1 = f1
fn_2 = f2
n -= 2
while n > 0:
fn_1, fn_2 = fn_1 + fn_2, fn_1
n -= 1
return fn_1
def matrix_exponentiation_time():
setup = """
from random import randint
from __main__ import fibonacci_with_matrix_exponentiation
"""
code = "fibonacci_with_matrix_exponentiation(randint(1,70000), 1, 1)"
exec_time = timeit.timeit(setup=setup, stmt=code, number=100)
print("With matrix exponentiation the average execution time is ", exec_time / 100)
return exec_time
def simple_fibonacci_time():
setup = """
from random import randint
from __main__ import simple_fibonacci
"""
code = "simple_fibonacci(randint(1,70000), 1, 1)"
exec_time = timeit.timeit(setup=setup, stmt=code, number=100)
print(
"Without matrix exponentiation the average execution time is ", exec_time / 100
)
return exec_time
def main():
matrix_exponentiation_time()
simple_fibonacci_time()
if __name__ == "__main__":
main()
| """Matrix Exponentiation"""
import timeit
"""
Matrix Exponentiation is a technique to solve linear recurrences in logarithmic time.
You read more about it here:
https://zobayer.blogspot.com/2010/11/matrix-exponentiation.html
https://www.hackerearth.com/practice/notes/matrix-exponentiation-1/
"""
class Matrix:
def __init__(self, arg):
if isinstance(arg, list): # Initializes a matrix identical to the one provided.
self.t = arg
self.n = len(arg)
else: # Initializes a square matrix of the given size and set values to zero.
self.n = arg
self.t = [[0 for _ in range(self.n)] for _ in range(self.n)]
def __mul__(self, b):
matrix = Matrix(self.n)
for i in range(self.n):
for j in range(self.n):
for k in range(self.n):
matrix.t[i][j] += self.t[i][k] * b.t[k][j]
return matrix
def modular_exponentiation(a, b):
matrix = Matrix([[1, 0], [0, 1]])
while b > 0:
if b & 1:
matrix *= a
a *= a
b >>= 1
return matrix
def fibonacci_with_matrix_exponentiation(n, f1, f2):
# Trivial Cases
if n == 1:
return f1
elif n == 2:
return f2
matrix = Matrix([[1, 1], [1, 0]])
matrix = modular_exponentiation(matrix, n - 2)
return f2 * matrix.t[0][0] + f1 * matrix.t[0][1]
def simple_fibonacci(n, f1, f2):
# Trivial Cases
if n == 1:
return f1
elif n == 2:
return f2
fn_1 = f1
fn_2 = f2
n -= 2
while n > 0:
fn_1, fn_2 = fn_1 + fn_2, fn_1
n -= 1
return fn_1
def matrix_exponentiation_time():
setup = """
from random import randint
from __main__ import fibonacci_with_matrix_exponentiation
"""
code = "fibonacci_with_matrix_exponentiation(randint(1,70000), 1, 1)"
exec_time = timeit.timeit(setup=setup, stmt=code, number=100)
print("With matrix exponentiation the average execution time is ", exec_time / 100)
return exec_time
def simple_fibonacci_time():
setup = """
from random import randint
from __main__ import simple_fibonacci
"""
code = "simple_fibonacci(randint(1,70000), 1, 1)"
exec_time = timeit.timeit(setup=setup, stmt=code, number=100)
print(
"Without matrix exponentiation the average execution time is ", exec_time / 100
)
return exec_time
def main():
matrix_exponentiation_time()
simple_fibonacci_time()
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 1: https://projecteuler.net/problem=1
Multiples of 3 and 5
If we list all the natural numbers below 10 that are multiples of 3 or 5,
we get 3, 5, 6 and 9. The sum of these multiples is 23.
Find the sum of all the multiples of 3 or 5 below 1000.
"""
def solution(n: int = 1000) -> int:
"""
Returns the sum of all the multiples of 3 or 5 below n.
>>> solution(3)
0
>>> solution(4)
3
>>> solution(10)
23
>>> solution(600)
83700
>>> solution(-7)
0
"""
return sum(e for e in range(3, n) if e % 3 == 0 or e % 5 == 0)
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 1: https://projecteuler.net/problem=1
Multiples of 3 and 5
If we list all the natural numbers below 10 that are multiples of 3 or 5,
we get 3, 5, 6 and 9. The sum of these multiples is 23.
Find the sum of all the multiples of 3 or 5 below 1000.
"""
def solution(n: int = 1000) -> int:
"""
Returns the sum of all the multiples of 3 or 5 below n.
>>> solution(3)
0
>>> solution(4)
3
>>> solution(10)
23
>>> solution(600)
83700
>>> solution(-7)
0
"""
return sum(e for e in range(3, n) if e % 3 == 0 or e % 5 == 0)
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def alternative_string_arrange(first_str: str, second_str: str) -> str:
"""
Return the alternative arrangements of the two strings.
:param first_str:
:param second_str:
:return: String
>>> alternative_string_arrange("ABCD", "XY")
'AXBYCD'
>>> alternative_string_arrange("XY", "ABCD")
'XAYBCD'
>>> alternative_string_arrange("AB", "XYZ")
'AXBYZ'
>>> alternative_string_arrange("ABC", "")
'ABC'
"""
first_str_length: int = len(first_str)
second_str_length: int = len(second_str)
abs_length: int = (
first_str_length if first_str_length > second_str_length else second_str_length
)
output_list: list = []
for char_count in range(abs_length):
if char_count < first_str_length:
output_list.append(first_str[char_count])
if char_count < second_str_length:
output_list.append(second_str[char_count])
return "".join(output_list)
if __name__ == "__main__":
print(alternative_string_arrange("AB", "XYZ"), end=" ")
| def alternative_string_arrange(first_str: str, second_str: str) -> str:
"""
Return the alternative arrangements of the two strings.
:param first_str:
:param second_str:
:return: String
>>> alternative_string_arrange("ABCD", "XY")
'AXBYCD'
>>> alternative_string_arrange("XY", "ABCD")
'XAYBCD'
>>> alternative_string_arrange("AB", "XYZ")
'AXBYZ'
>>> alternative_string_arrange("ABC", "")
'ABC'
"""
first_str_length: int = len(first_str)
second_str_length: int = len(second_str)
abs_length: int = (
first_str_length if first_str_length > second_str_length else second_str_length
)
output_list: list = []
for char_count in range(abs_length):
if char_count < first_str_length:
output_list.append(first_str[char_count])
if char_count < second_str_length:
output_list.append(second_str[char_count])
return "".join(output_list)
if __name__ == "__main__":
print(alternative_string_arrange("AB", "XYZ"), end=" ")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
The Fibonacci sequence is defined by the recurrence relation:
Fn = Fn−1 + Fn−2, where F1 = 1 and F2 = 1.
Hence the first 12 terms will be:
F1 = 1
F2 = 1
F3 = 2
F4 = 3
F5 = 5
F6 = 8
F7 = 13
F8 = 21
F9 = 34
F10 = 55
F11 = 89
F12 = 144
The 12th term, F12, is the first term to contain three digits.
What is the index of the first term in the Fibonacci sequence to contain 1000
digits?
"""
def solution(n: int = 1000) -> int:
"""Returns the index of the first term in the Fibonacci sequence to contain
n digits.
>>> solution(1000)
4782
>>> solution(100)
476
>>> solution(50)
237
>>> solution(3)
12
"""
f1, f2 = 1, 1
index = 2
while True:
i = 0
f = f1 + f2
f1, f2 = f2, f
index += 1
for _ in str(f):
i += 1
if i == n:
break
return index
if __name__ == "__main__":
print(solution(int(str(input()).strip())))
| """
The Fibonacci sequence is defined by the recurrence relation:
Fn = Fn−1 + Fn−2, where F1 = 1 and F2 = 1.
Hence the first 12 terms will be:
F1 = 1
F2 = 1
F3 = 2
F4 = 3
F5 = 5
F6 = 8
F7 = 13
F8 = 21
F9 = 34
F10 = 55
F11 = 89
F12 = 144
The 12th term, F12, is the first term to contain three digits.
What is the index of the first term in the Fibonacci sequence to contain 1000
digits?
"""
def solution(n: int = 1000) -> int:
"""Returns the index of the first term in the Fibonacci sequence to contain
n digits.
>>> solution(1000)
4782
>>> solution(100)
476
>>> solution(50)
237
>>> solution(3)
12
"""
f1, f2 = 1, 1
index = 2
while True:
i = 0
f = f1 + f2
f1, f2 = f2, f
index += 1
for _ in str(f):
i += 1
if i == n:
break
return index
if __name__ == "__main__":
print(solution(int(str(input()).strip())))
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from collections import Counter
def sock_merchant(colors: list[int]) -> int:
"""
>>> sock_merchant([10, 20, 20, 10, 10, 30, 50, 10, 20])
3
>>> sock_merchant([1, 1, 3, 3])
2
"""
return sum(socks_by_color // 2 for socks_by_color in Counter(colors).values())
if __name__ == "__main__":
import doctest
doctest.testmod()
colors = [int(x) for x in input("Enter socks by color :").rstrip().split()]
print(f"sock_merchant({colors}) = {sock_merchant(colors)}")
| from collections import Counter
def sock_merchant(colors: list[int]) -> int:
"""
>>> sock_merchant([10, 20, 20, 10, 10, 30, 50, 10, 20])
3
>>> sock_merchant([1, 1, 3, 3])
2
"""
return sum(socks_by_color // 2 for socks_by_color in Counter(colors).values())
if __name__ == "__main__":
import doctest
doctest.testmod()
colors = [int(x) for x in input("Enter socks by color :").rstrip().split()]
print(f"sock_merchant({colors}) = {sock_merchant(colors)}")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 203: https://projecteuler.net/problem=203
The binomial coefficients (n k) can be arranged in triangular form, Pascal's
triangle, like this:
1
1 1
1 2 1
1 3 3 1
1 4 6 4 1
1 5 10 10 5 1
1 6 15 20 15 6 1
1 7 21 35 35 21 7 1
.........
It can be seen that the first eight rows of Pascal's triangle contain twelve
distinct numbers: 1, 2, 3, 4, 5, 6, 7, 10, 15, 20, 21 and 35.
A positive integer n is called squarefree if no square of a prime divides n.
Of the twelve distinct numbers in the first eight rows of Pascal's triangle,
all except 4 and 20 are squarefree. The sum of the distinct squarefree numbers
in the first eight rows is 105.
Find the sum of the distinct squarefree numbers in the first 51 rows of
Pascal's triangle.
References:
- https://en.wikipedia.org/wiki/Pascal%27s_triangle
"""
from __future__ import annotations
def get_pascal_triangle_unique_coefficients(depth: int) -> set[int]:
"""
Returns the unique coefficients of a Pascal's triangle of depth "depth".
The coefficients of this triangle are symmetric. A further improvement to this
method could be to calculate the coefficients once per level. Nonetheless,
the current implementation is fast enough for the original problem.
>>> get_pascal_triangle_unique_coefficients(1)
{1}
>>> get_pascal_triangle_unique_coefficients(2)
{1}
>>> get_pascal_triangle_unique_coefficients(3)
{1, 2}
>>> get_pascal_triangle_unique_coefficients(8)
{1, 2, 3, 4, 5, 6, 7, 35, 10, 15, 20, 21}
"""
coefficients = {1}
previous_coefficients = [1]
for _ in range(2, depth + 1):
coefficients_begins_one = previous_coefficients + [0]
coefficients_ends_one = [0] + previous_coefficients
previous_coefficients = []
for x, y in zip(coefficients_begins_one, coefficients_ends_one):
coefficients.add(x + y)
previous_coefficients.append(x + y)
return coefficients
def get_squarefrees(unique_coefficients: set[int]) -> set[int]:
"""
Calculates the squarefree numbers inside unique_coefficients.
Based on the definition of a non-squarefree number, then any non-squarefree
n can be decomposed as n = p*p*r, where p is positive prime number and r
is a positive integer.
Under the previous formula, any coefficient that is lower than p*p is
squarefree as r cannot be negative. On the contrary, if any r exists such
that n = p*p*r, then the number is non-squarefree.
>>> get_squarefrees({1})
{1}
>>> get_squarefrees({1, 2})
{1, 2}
>>> get_squarefrees({1, 2, 3, 4, 5, 6, 7, 35, 10, 15, 20, 21})
{1, 2, 3, 5, 6, 7, 35, 10, 15, 21}
"""
non_squarefrees = set()
for number in unique_coefficients:
divisor = 2
copy_number = number
while divisor**2 <= copy_number:
multiplicity = 0
while copy_number % divisor == 0:
copy_number //= divisor
multiplicity += 1
if multiplicity >= 2:
non_squarefrees.add(number)
break
divisor += 1
return unique_coefficients.difference(non_squarefrees)
def solution(n: int = 51) -> int:
"""
Returns the sum of squarefrees for a given Pascal's Triangle of depth n.
>>> solution(1)
1
>>> solution(8)
105
>>> solution(9)
175
"""
unique_coefficients = get_pascal_triangle_unique_coefficients(n)
squarefrees = get_squarefrees(unique_coefficients)
return sum(squarefrees)
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 203: https://projecteuler.net/problem=203
The binomial coefficients (n k) can be arranged in triangular form, Pascal's
triangle, like this:
1
1 1
1 2 1
1 3 3 1
1 4 6 4 1
1 5 10 10 5 1
1 6 15 20 15 6 1
1 7 21 35 35 21 7 1
.........
It can be seen that the first eight rows of Pascal's triangle contain twelve
distinct numbers: 1, 2, 3, 4, 5, 6, 7, 10, 15, 20, 21 and 35.
A positive integer n is called squarefree if no square of a prime divides n.
Of the twelve distinct numbers in the first eight rows of Pascal's triangle,
all except 4 and 20 are squarefree. The sum of the distinct squarefree numbers
in the first eight rows is 105.
Find the sum of the distinct squarefree numbers in the first 51 rows of
Pascal's triangle.
References:
- https://en.wikipedia.org/wiki/Pascal%27s_triangle
"""
from __future__ import annotations
def get_pascal_triangle_unique_coefficients(depth: int) -> set[int]:
"""
Returns the unique coefficients of a Pascal's triangle of depth "depth".
The coefficients of this triangle are symmetric. A further improvement to this
method could be to calculate the coefficients once per level. Nonetheless,
the current implementation is fast enough for the original problem.
>>> get_pascal_triangle_unique_coefficients(1)
{1}
>>> get_pascal_triangle_unique_coefficients(2)
{1}
>>> get_pascal_triangle_unique_coefficients(3)
{1, 2}
>>> get_pascal_triangle_unique_coefficients(8)
{1, 2, 3, 4, 5, 6, 7, 35, 10, 15, 20, 21}
"""
coefficients = {1}
previous_coefficients = [1]
for _ in range(2, depth + 1):
coefficients_begins_one = previous_coefficients + [0]
coefficients_ends_one = [0] + previous_coefficients
previous_coefficients = []
for x, y in zip(coefficients_begins_one, coefficients_ends_one):
coefficients.add(x + y)
previous_coefficients.append(x + y)
return coefficients
def get_squarefrees(unique_coefficients: set[int]) -> set[int]:
"""
Calculates the squarefree numbers inside unique_coefficients.
Based on the definition of a non-squarefree number, then any non-squarefree
n can be decomposed as n = p*p*r, where p is positive prime number and r
is a positive integer.
Under the previous formula, any coefficient that is lower than p*p is
squarefree as r cannot be negative. On the contrary, if any r exists such
that n = p*p*r, then the number is non-squarefree.
>>> get_squarefrees({1})
{1}
>>> get_squarefrees({1, 2})
{1, 2}
>>> get_squarefrees({1, 2, 3, 4, 5, 6, 7, 35, 10, 15, 20, 21})
{1, 2, 3, 5, 6, 7, 35, 10, 15, 21}
"""
non_squarefrees = set()
for number in unique_coefficients:
divisor = 2
copy_number = number
while divisor**2 <= copy_number:
multiplicity = 0
while copy_number % divisor == 0:
copy_number //= divisor
multiplicity += 1
if multiplicity >= 2:
non_squarefrees.add(number)
break
divisor += 1
return unique_coefficients.difference(non_squarefrees)
def solution(n: int = 51) -> int:
"""
Returns the sum of squarefrees for a given Pascal's Triangle of depth n.
>>> solution(1)
1
>>> solution(8)
105
>>> solution(9)
175
"""
unique_coefficients = get_pascal_triangle_unique_coefficients(n)
squarefrees = get_squarefrees(unique_coefficients)
return sum(squarefrees)
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Convolutional Neural Network
Objective : To train a CNN model detect if TB is present in Lung X-ray or not.
Resources CNN Theory :
https://en.wikipedia.org/wiki/Convolutional_neural_network
Resources Tensorflow : https://www.tensorflow.org/tutorials/images/cnn
Download dataset from :
https://lhncbc.nlm.nih.gov/LHC-publications/pubs/TuberculosisChestXrayImageDataSets.html
1. Download the dataset folder and create two folder training set and test set
in the parent dataste folder
2. Move 30-40 image from both TB positive and TB Negative folder
in the test set folder
3. The labels of the iamges will be extracted from the folder name
the image is present in.
"""
# Part 1 - Building the CNN
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
classifier = models.Sequential()
# Step 1 - Convolution
classifier.add(
layers.Conv2D(32, (3, 3), input_shape=(64, 64, 3), activation="relu")
)
# Step 2 - Pooling
classifier.add(layers.MaxPooling2D(pool_size=(2, 2)))
# Adding a second convolutional layer
classifier.add(layers.Conv2D(32, (3, 3), activation="relu"))
classifier.add(layers.MaxPooling2D(pool_size=(2, 2)))
# Step 3 - Flattening
classifier.add(layers.Flatten())
# Step 4 - Full connection
classifier.add(layers.Dense(units=128, activation="relu"))
classifier.add(layers.Dense(units=1, activation="sigmoid"))
# Compiling the CNN
classifier.compile(
optimizer="adam", loss="binary_crossentropy", metrics=["accuracy"]
)
# Part 2 - Fitting the CNN to the images
# Load Trained model weights
# from keras.models import load_model
# regressor=load_model('cnn.h5')
train_datagen = tf.keras.preprocessing.image.ImageDataGenerator(
rescale=1.0 / 255, shear_range=0.2, zoom_range=0.2, horizontal_flip=True
)
test_datagen = tf.keras.preprocessing.image.ImageDataGenerator(rescale=1.0 / 255)
training_set = train_datagen.flow_from_directory(
"dataset/training_set", target_size=(64, 64), batch_size=32, class_mode="binary"
)
test_set = test_datagen.flow_from_directory(
"dataset/test_set", target_size=(64, 64), batch_size=32, class_mode="binary"
)
classifier.fit_generator(
training_set, steps_per_epoch=5, epochs=30, validation_data=test_set
)
classifier.save("cnn.h5")
# Part 3 - Making new predictions
test_image = tf.keras.preprocessing.image.load_img(
"dataset/single_prediction/image.png", target_size=(64, 64)
)
test_image = tf.keras.preprocessing.image.img_to_array(test_image)
test_image = np.expand_dims(test_image, axis=0)
result = classifier.predict(test_image)
training_set.class_indices
if result[0][0] == 0:
prediction = "Normal"
if result[0][0] == 1:
prediction = "Abnormality detected"
| """
Convolutional Neural Network
Objective : To train a CNN model detect if TB is present in Lung X-ray or not.
Resources CNN Theory :
https://en.wikipedia.org/wiki/Convolutional_neural_network
Resources Tensorflow : https://www.tensorflow.org/tutorials/images/cnn
Download dataset from :
https://lhncbc.nlm.nih.gov/LHC-publications/pubs/TuberculosisChestXrayImageDataSets.html
1. Download the dataset folder and create two folder training set and test set
in the parent dataste folder
2. Move 30-40 image from both TB positive and TB Negative folder
in the test set folder
3. The labels of the iamges will be extracted from the folder name
the image is present in.
"""
# Part 1 - Building the CNN
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
classifier = models.Sequential()
# Step 1 - Convolution
classifier.add(
layers.Conv2D(32, (3, 3), input_shape=(64, 64, 3), activation="relu")
)
# Step 2 - Pooling
classifier.add(layers.MaxPooling2D(pool_size=(2, 2)))
# Adding a second convolutional layer
classifier.add(layers.Conv2D(32, (3, 3), activation="relu"))
classifier.add(layers.MaxPooling2D(pool_size=(2, 2)))
# Step 3 - Flattening
classifier.add(layers.Flatten())
# Step 4 - Full connection
classifier.add(layers.Dense(units=128, activation="relu"))
classifier.add(layers.Dense(units=1, activation="sigmoid"))
# Compiling the CNN
classifier.compile(
optimizer="adam", loss="binary_crossentropy", metrics=["accuracy"]
)
# Part 2 - Fitting the CNN to the images
# Load Trained model weights
# from keras.models import load_model
# regressor=load_model('cnn.h5')
train_datagen = tf.keras.preprocessing.image.ImageDataGenerator(
rescale=1.0 / 255, shear_range=0.2, zoom_range=0.2, horizontal_flip=True
)
test_datagen = tf.keras.preprocessing.image.ImageDataGenerator(rescale=1.0 / 255)
training_set = train_datagen.flow_from_directory(
"dataset/training_set", target_size=(64, 64), batch_size=32, class_mode="binary"
)
test_set = test_datagen.flow_from_directory(
"dataset/test_set", target_size=(64, 64), batch_size=32, class_mode="binary"
)
classifier.fit_generator(
training_set, steps_per_epoch=5, epochs=30, validation_data=test_set
)
classifier.save("cnn.h5")
# Part 3 - Making new predictions
test_image = tf.keras.preprocessing.image.load_img(
"dataset/single_prediction/image.png", target_size=(64, 64)
)
test_image = tf.keras.preprocessing.image.img_to_array(test_image)
test_image = np.expand_dims(test_image, axis=0)
result = classifier.predict(test_image)
training_set.class_indices
if result[0][0] == 0:
prediction = "Normal"
if result[0][0] == 1:
prediction = "Abnormality detected"
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Problem 81: https://projecteuler.net/problem=81
In the 5 by 5 matrix below, the minimal path sum from the top left to the bottom right,
by only moving to the right and down, is indicated in bold red and is equal to 2427.
[131] 673 234 103 18
[201] [96] [342] 965 150
630 803 [746] [422] 111
537 699 497 [121] 956
805 732 524 [37] [331]
Find the minimal path sum from the top left to the bottom right by only moving right
and down in matrix.txt (https://projecteuler.net/project/resources/p081_matrix.txt),
a 31K text file containing an 80 by 80 matrix.
"""
import os
def solution(filename: str = "matrix.txt") -> int:
"""
Returns the minimal path sum from the top left to the bottom right of the matrix.
>>> solution()
427337
"""
with open(os.path.join(os.path.dirname(__file__), filename)) as in_file:
data = in_file.read()
grid = [[int(cell) for cell in row.split(",")] for row in data.strip().splitlines()]
dp = [[0 for cell in row] for row in grid]
n = len(grid[0])
dp = [[0 for i in range(n)] for j in range(n)]
dp[0][0] = grid[0][0]
for i in range(1, n):
dp[0][i] = grid[0][i] + dp[0][i - 1]
for i in range(1, n):
dp[i][0] = grid[i][0] + dp[i - 1][0]
for i in range(1, n):
for j in range(1, n):
dp[i][j] = grid[i][j] + min(dp[i - 1][j], dp[i][j - 1])
return dp[-1][-1]
if __name__ == "__main__":
print(f"{solution() = }")
| """
Problem 81: https://projecteuler.net/problem=81
In the 5 by 5 matrix below, the minimal path sum from the top left to the bottom right,
by only moving to the right and down, is indicated in bold red and is equal to 2427.
[131] 673 234 103 18
[201] [96] [342] 965 150
630 803 [746] [422] 111
537 699 497 [121] 956
805 732 524 [37] [331]
Find the minimal path sum from the top left to the bottom right by only moving right
and down in matrix.txt (https://projecteuler.net/project/resources/p081_matrix.txt),
a 31K text file containing an 80 by 80 matrix.
"""
import os
def solution(filename: str = "matrix.txt") -> int:
"""
Returns the minimal path sum from the top left to the bottom right of the matrix.
>>> solution()
427337
"""
with open(os.path.join(os.path.dirname(__file__), filename)) as in_file:
data = in_file.read()
grid = [[int(cell) for cell in row.split(",")] for row in data.strip().splitlines()]
dp = [[0 for cell in row] for row in grid]
n = len(grid[0])
dp = [[0 for i in range(n)] for j in range(n)]
dp[0][0] = grid[0][0]
for i in range(1, n):
dp[0][i] = grid[0][i] + dp[0][i - 1]
for i in range(1, n):
dp[i][0] = grid[i][0] + dp[i - 1][0]
for i in range(1, n):
for j in range(1, n):
dp[i][j] = grid[i][j] + min(dp[i - 1][j], dp[i][j - 1])
return dp[-1][-1]
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Factorial of a number using memoization
from functools import lru_cache
@lru_cache
def factorial(num: int) -> int:
"""
>>> factorial(7)
5040
>>> factorial(-1)
Traceback (most recent call last):
...
ValueError: Number should not be negative.
>>> [factorial(i) for i in range(10)]
[1, 1, 2, 6, 24, 120, 720, 5040, 40320, 362880]
"""
if num < 0:
raise ValueError("Number should not be negative.")
return 1 if num in (0, 1) else num * factorial(num - 1)
if __name__ == "__main__":
import doctest
doctest.testmod()
| # Factorial of a number using memoization
from functools import lru_cache
@lru_cache
def factorial(num: int) -> int:
"""
>>> factorial(7)
5040
>>> factorial(-1)
Traceback (most recent call last):
...
ValueError: Number should not be negative.
>>> [factorial(i) for i in range(10)]
[1, 1, 2, 6, 24, 120, 720, 5040, 40320, 362880]
"""
if num < 0:
raise ValueError("Number should not be negative.")
return 1 if num in (0, 1) else num * factorial(num - 1)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """ A Queue using a linked list like structure """
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class Node:
def __init__(self, data: Any) -> None:
self.data: Any = data
self.next: Node | None = None
def __str__(self) -> str:
return f"{self.data}"
class LinkedQueue:
"""
>>> queue = LinkedQueue()
>>> queue.is_empty()
True
>>> queue.put(5)
>>> queue.put(9)
>>> queue.put('python')
>>> queue.is_empty()
False
>>> queue.get()
5
>>> queue.put('algorithms')
>>> queue.get()
9
>>> queue.get()
'python'
>>> queue.get()
'algorithms'
>>> queue.is_empty()
True
>>> queue.get()
Traceback (most recent call last):
...
IndexError: dequeue from empty queue
"""
def __init__(self) -> None:
self.front: Node | None = None
self.rear: Node | None = None
def __iter__(self) -> Iterator[Any]:
node = self.front
while node:
yield node.data
node = node.next
def __len__(self) -> int:
"""
>>> queue = LinkedQueue()
>>> for i in range(1, 6):
... queue.put(i)
>>> len(queue)
5
>>> for i in range(1, 6):
... assert len(queue) == 6 - i
... _ = queue.get()
>>> len(queue)
0
"""
return len(tuple(iter(self)))
def __str__(self) -> str:
"""
>>> queue = LinkedQueue()
>>> for i in range(1, 4):
... queue.put(i)
>>> queue.put("Python")
>>> queue.put(3.14)
>>> queue.put(True)
>>> str(queue)
'1 <- 2 <- 3 <- Python <- 3.14 <- True'
"""
return " <- ".join(str(item) for item in self)
def is_empty(self) -> bool:
"""
>>> queue = LinkedQueue()
>>> queue.is_empty()
True
>>> for i in range(1, 6):
... queue.put(i)
>>> queue.is_empty()
False
"""
return len(self) == 0
def put(self, item: Any) -> None:
"""
>>> queue = LinkedQueue()
>>> queue.get()
Traceback (most recent call last):
...
IndexError: dequeue from empty queue
>>> for i in range(1, 6):
... queue.put(i)
>>> str(queue)
'1 <- 2 <- 3 <- 4 <- 5'
"""
node = Node(item)
if self.is_empty():
self.front = self.rear = node
else:
assert isinstance(self.rear, Node)
self.rear.next = node
self.rear = node
def get(self) -> Any:
"""
>>> queue = LinkedQueue()
>>> queue.get()
Traceback (most recent call last):
...
IndexError: dequeue from empty queue
>>> queue = LinkedQueue()
>>> for i in range(1, 6):
... queue.put(i)
>>> for i in range(1, 6):
... assert queue.get() == i
>>> len(queue)
0
"""
if self.is_empty():
raise IndexError("dequeue from empty queue")
assert isinstance(self.front, Node)
node = self.front
self.front = self.front.next
if self.front is None:
self.rear = None
return node.data
def clear(self) -> None:
"""
>>> queue = LinkedQueue()
>>> for i in range(1, 6):
... queue.put(i)
>>> queue.clear()
>>> len(queue)
0
>>> str(queue)
''
"""
self.front = self.rear = None
if __name__ == "__main__":
from doctest import testmod
testmod()
| """ A Queue using a linked list like structure """
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class Node:
def __init__(self, data: Any) -> None:
self.data: Any = data
self.next: Node | None = None
def __str__(self) -> str:
return f"{self.data}"
class LinkedQueue:
"""
>>> queue = LinkedQueue()
>>> queue.is_empty()
True
>>> queue.put(5)
>>> queue.put(9)
>>> queue.put('python')
>>> queue.is_empty()
False
>>> queue.get()
5
>>> queue.put('algorithms')
>>> queue.get()
9
>>> queue.get()
'python'
>>> queue.get()
'algorithms'
>>> queue.is_empty()
True
>>> queue.get()
Traceback (most recent call last):
...
IndexError: dequeue from empty queue
"""
def __init__(self) -> None:
self.front: Node | None = None
self.rear: Node | None = None
def __iter__(self) -> Iterator[Any]:
node = self.front
while node:
yield node.data
node = node.next
def __len__(self) -> int:
"""
>>> queue = LinkedQueue()
>>> for i in range(1, 6):
... queue.put(i)
>>> len(queue)
5
>>> for i in range(1, 6):
... assert len(queue) == 6 - i
... _ = queue.get()
>>> len(queue)
0
"""
return len(tuple(iter(self)))
def __str__(self) -> str:
"""
>>> queue = LinkedQueue()
>>> for i in range(1, 4):
... queue.put(i)
>>> queue.put("Python")
>>> queue.put(3.14)
>>> queue.put(True)
>>> str(queue)
'1 <- 2 <- 3 <- Python <- 3.14 <- True'
"""
return " <- ".join(str(item) for item in self)
def is_empty(self) -> bool:
"""
>>> queue = LinkedQueue()
>>> queue.is_empty()
True
>>> for i in range(1, 6):
... queue.put(i)
>>> queue.is_empty()
False
"""
return len(self) == 0
def put(self, item: Any) -> None:
"""
>>> queue = LinkedQueue()
>>> queue.get()
Traceback (most recent call last):
...
IndexError: dequeue from empty queue
>>> for i in range(1, 6):
... queue.put(i)
>>> str(queue)
'1 <- 2 <- 3 <- 4 <- 5'
"""
node = Node(item)
if self.is_empty():
self.front = self.rear = node
else:
assert isinstance(self.rear, Node)
self.rear.next = node
self.rear = node
def get(self) -> Any:
"""
>>> queue = LinkedQueue()
>>> queue.get()
Traceback (most recent call last):
...
IndexError: dequeue from empty queue
>>> queue = LinkedQueue()
>>> for i in range(1, 6):
... queue.put(i)
>>> for i in range(1, 6):
... assert queue.get() == i
>>> len(queue)
0
"""
if self.is_empty():
raise IndexError("dequeue from empty queue")
assert isinstance(self.front, Node)
node = self.front
self.front = self.front.next
if self.front is None:
self.rear = None
return node.data
def clear(self) -> None:
"""
>>> queue = LinkedQueue()
>>> for i in range(1, 6):
... queue.put(i)
>>> queue.clear()
>>> len(queue)
0
>>> str(queue)
''
"""
self.front = self.rear = None
if __name__ == "__main__":
from doctest import testmod
testmod()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Calculate the nth Proth number
Source:
https://handwiki.org/wiki/Proth_number
"""
import math
def proth(number: int) -> int:
"""
:param number: nth number to calculate in the sequence
:return: the nth number in Proth number
Note: indexing starts at 1 i.e. proth(1) gives the first Proth number of 3
>>> proth(6)
25
>>> proth(0)
Traceback (most recent call last):
...
ValueError: Input value of [number=0] must be > 0
>>> proth(-1)
Traceback (most recent call last):
...
ValueError: Input value of [number=-1] must be > 0
>>> proth(6.0)
Traceback (most recent call last):
...
TypeError: Input value of [number=6.0] must be an integer
"""
if not isinstance(number, int):
raise TypeError(f"Input value of [number={number}] must be an integer")
if number < 1:
raise ValueError(f"Input value of [number={number}] must be > 0")
elif number == 1:
return 3
elif number == 2:
return 5
else:
"""
+1 for binary starting at 0 i.e. 2^0, 2^1, etc.
+1 to start the sequence at the 3rd Proth number
Hence, we have a +2 in the below statement
"""
block_index = int(math.log(number // 3, 2)) + 2
proth_list = [3, 5]
proth_index = 2
increment = 3
for block in range(1, block_index):
for _ in range(increment):
proth_list.append(2 ** (block + 1) + proth_list[proth_index - 1])
proth_index += 1
increment *= 2
return proth_list[number - 1]
if __name__ == "__main__":
import doctest
doctest.testmod()
for number in range(11):
value = 0
try:
value = proth(number)
except ValueError:
print(f"ValueError: there is no {number}th Proth number")
continue
print(f"The {number}th Proth number: {value}")
| """
Calculate the nth Proth number
Source:
https://handwiki.org/wiki/Proth_number
"""
import math
def proth(number: int) -> int:
"""
:param number: nth number to calculate in the sequence
:return: the nth number in Proth number
Note: indexing starts at 1 i.e. proth(1) gives the first Proth number of 3
>>> proth(6)
25
>>> proth(0)
Traceback (most recent call last):
...
ValueError: Input value of [number=0] must be > 0
>>> proth(-1)
Traceback (most recent call last):
...
ValueError: Input value of [number=-1] must be > 0
>>> proth(6.0)
Traceback (most recent call last):
...
TypeError: Input value of [number=6.0] must be an integer
"""
if not isinstance(number, int):
raise TypeError(f"Input value of [number={number}] must be an integer")
if number < 1:
raise ValueError(f"Input value of [number={number}] must be > 0")
elif number == 1:
return 3
elif number == 2:
return 5
else:
"""
+1 for binary starting at 0 i.e. 2^0, 2^1, etc.
+1 to start the sequence at the 3rd Proth number
Hence, we have a +2 in the below statement
"""
block_index = int(math.log(number // 3, 2)) + 2
proth_list = [3, 5]
proth_index = 2
increment = 3
for block in range(1, block_index):
for _ in range(increment):
proth_list.append(2 ** (block + 1) + proth_list[proth_index - 1])
proth_index += 1
increment *= 2
return proth_list[number - 1]
if __name__ == "__main__":
import doctest
doctest.testmod()
for number in range(11):
value = 0
try:
value = proth(number)
except ValueError:
print(f"ValueError: there is no {number}th Proth number")
continue
print(f"The {number}th Proth number: {value}")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Program to calculate the amortization amount per month, given
- Principal borrowed
- Rate of interest per annum
- Years to repay the loan
Wikipedia Reference: https://en.wikipedia.org/wiki/Equated_monthly_installment
"""
def equated_monthly_installments(
principal: float, rate_per_annum: float, years_to_repay: int
) -> float:
"""
Formula for amortization amount per month:
A = p * r * (1 + r)^n / ((1 + r)^n - 1)
where p is the principal, r is the rate of interest per month
and n is the number of payments
>>> equated_monthly_installments(25000, 0.12, 3)
830.3577453212793
>>> equated_monthly_installments(25000, 0.12, 10)
358.67737100646826
>>> equated_monthly_installments(0, 0.12, 3)
Traceback (most recent call last):
...
Exception: Principal borrowed must be > 0
>>> equated_monthly_installments(25000, -1, 3)
Traceback (most recent call last):
...
Exception: Rate of interest must be >= 0
>>> equated_monthly_installments(25000, 0.12, 0)
Traceback (most recent call last):
...
Exception: Years to repay must be an integer > 0
"""
if principal <= 0:
raise Exception("Principal borrowed must be > 0")
if rate_per_annum < 0:
raise Exception("Rate of interest must be >= 0")
if years_to_repay <= 0 or not isinstance(years_to_repay, int):
raise Exception("Years to repay must be an integer > 0")
# Yearly rate is divided by 12 to get monthly rate
rate_per_month = rate_per_annum / 12
# Years to repay is multiplied by 12 to get number of payments as payment is monthly
number_of_payments = years_to_repay * 12
return (
principal
* rate_per_month
* (1 + rate_per_month) ** number_of_payments
/ ((1 + rate_per_month) ** number_of_payments - 1)
)
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
Program to calculate the amortization amount per month, given
- Principal borrowed
- Rate of interest per annum
- Years to repay the loan
Wikipedia Reference: https://en.wikipedia.org/wiki/Equated_monthly_installment
"""
def equated_monthly_installments(
principal: float, rate_per_annum: float, years_to_repay: int
) -> float:
"""
Formula for amortization amount per month:
A = p * r * (1 + r)^n / ((1 + r)^n - 1)
where p is the principal, r is the rate of interest per month
and n is the number of payments
>>> equated_monthly_installments(25000, 0.12, 3)
830.3577453212793
>>> equated_monthly_installments(25000, 0.12, 10)
358.67737100646826
>>> equated_monthly_installments(0, 0.12, 3)
Traceback (most recent call last):
...
Exception: Principal borrowed must be > 0
>>> equated_monthly_installments(25000, -1, 3)
Traceback (most recent call last):
...
Exception: Rate of interest must be >= 0
>>> equated_monthly_installments(25000, 0.12, 0)
Traceback (most recent call last):
...
Exception: Years to repay must be an integer > 0
"""
if principal <= 0:
raise Exception("Principal borrowed must be > 0")
if rate_per_annum < 0:
raise Exception("Rate of interest must be >= 0")
if years_to_repay <= 0 or not isinstance(years_to_repay, int):
raise Exception("Years to repay must be an integer > 0")
# Yearly rate is divided by 12 to get monthly rate
rate_per_month = rate_per_annum / 12
# Years to repay is multiplied by 12 to get number of payments as payment is monthly
number_of_payments = years_to_repay * 12
return (
principal
* rate_per_month
* (1 + rate_per_month) ** number_of_payments
/ ((1 + rate_per_month) ** number_of_payments - 1)
)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class Node:
def __init__(self, data: Any):
self.data: Any = data
self.next: Node | None = None
class CircularLinkedList:
def __init__(self):
self.head = None
self.tail = None
def __iter__(self) -> Iterator[Any]:
node = self.head
while self.head:
yield node.data
node = node.next
if node == self.head:
break
def __len__(self) -> int:
return len(tuple(iter(self)))
def __repr__(self):
return "->".join(str(item) for item in iter(self))
def insert_tail(self, data: Any) -> None:
self.insert_nth(len(self), data)
def insert_head(self, data: Any) -> None:
self.insert_nth(0, data)
def insert_nth(self, index: int, data: Any) -> None:
if index < 0 or index > len(self):
raise IndexError("list index out of range.")
new_node = Node(data)
if self.head is None:
new_node.next = new_node # first node points itself
self.tail = self.head = new_node
elif index == 0: # insert at head
new_node.next = self.head
self.head = self.tail.next = new_node
else:
temp = self.head
for _ in range(index - 1):
temp = temp.next
new_node.next = temp.next
temp.next = new_node
if index == len(self) - 1: # insert at tail
self.tail = new_node
def delete_front(self):
return self.delete_nth(0)
def delete_tail(self) -> Any:
return self.delete_nth(len(self) - 1)
def delete_nth(self, index: int = 0) -> Any:
if not 0 <= index < len(self):
raise IndexError("list index out of range.")
delete_node = self.head
if self.head == self.tail: # just one node
self.head = self.tail = None
elif index == 0: # delete head node
self.tail.next = self.tail.next.next
self.head = self.head.next
else:
temp = self.head
for _ in range(index - 1):
temp = temp.next
delete_node = temp.next
temp.next = temp.next.next
if index == len(self) - 1: # delete at tail
self.tail = temp
return delete_node.data
def is_empty(self) -> bool:
return len(self) == 0
def test_circular_linked_list() -> None:
"""
>>> test_circular_linked_list()
"""
circular_linked_list = CircularLinkedList()
assert len(circular_linked_list) == 0
assert circular_linked_list.is_empty() is True
assert str(circular_linked_list) == ""
try:
circular_linked_list.delete_front()
raise AssertionError() # This should not happen
except IndexError:
assert True # This should happen
try:
circular_linked_list.delete_tail()
raise AssertionError() # This should not happen
except IndexError:
assert True # This should happen
try:
circular_linked_list.delete_nth(-1)
raise AssertionError()
except IndexError:
assert True
try:
circular_linked_list.delete_nth(0)
raise AssertionError()
except IndexError:
assert True
assert circular_linked_list.is_empty() is True
for i in range(5):
assert len(circular_linked_list) == i
circular_linked_list.insert_nth(i, i + 1)
assert str(circular_linked_list) == "->".join(str(i) for i in range(1, 6))
circular_linked_list.insert_tail(6)
assert str(circular_linked_list) == "->".join(str(i) for i in range(1, 7))
circular_linked_list.insert_head(0)
assert str(circular_linked_list) == "->".join(str(i) for i in range(0, 7))
assert circular_linked_list.delete_front() == 0
assert circular_linked_list.delete_tail() == 6
assert str(circular_linked_list) == "->".join(str(i) for i in range(1, 6))
assert circular_linked_list.delete_nth(2) == 3
circular_linked_list.insert_nth(2, 3)
assert str(circular_linked_list) == "->".join(str(i) for i in range(1, 6))
assert circular_linked_list.is_empty() is False
if __name__ == "__main__":
import doctest
doctest.testmod()
| from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class Node:
def __init__(self, data: Any):
self.data: Any = data
self.next: Node | None = None
class CircularLinkedList:
def __init__(self):
self.head = None
self.tail = None
def __iter__(self) -> Iterator[Any]:
node = self.head
while self.head:
yield node.data
node = node.next
if node == self.head:
break
def __len__(self) -> int:
return len(tuple(iter(self)))
def __repr__(self):
return "->".join(str(item) for item in iter(self))
def insert_tail(self, data: Any) -> None:
self.insert_nth(len(self), data)
def insert_head(self, data: Any) -> None:
self.insert_nth(0, data)
def insert_nth(self, index: int, data: Any) -> None:
if index < 0 or index > len(self):
raise IndexError("list index out of range.")
new_node = Node(data)
if self.head is None:
new_node.next = new_node # first node points itself
self.tail = self.head = new_node
elif index == 0: # insert at head
new_node.next = self.head
self.head = self.tail.next = new_node
else:
temp = self.head
for _ in range(index - 1):
temp = temp.next
new_node.next = temp.next
temp.next = new_node
if index == len(self) - 1: # insert at tail
self.tail = new_node
def delete_front(self):
return self.delete_nth(0)
def delete_tail(self) -> Any:
return self.delete_nth(len(self) - 1)
def delete_nth(self, index: int = 0) -> Any:
if not 0 <= index < len(self):
raise IndexError("list index out of range.")
delete_node = self.head
if self.head == self.tail: # just one node
self.head = self.tail = None
elif index == 0: # delete head node
self.tail.next = self.tail.next.next
self.head = self.head.next
else:
temp = self.head
for _ in range(index - 1):
temp = temp.next
delete_node = temp.next
temp.next = temp.next.next
if index == len(self) - 1: # delete at tail
self.tail = temp
return delete_node.data
def is_empty(self) -> bool:
return len(self) == 0
def test_circular_linked_list() -> None:
"""
>>> test_circular_linked_list()
"""
circular_linked_list = CircularLinkedList()
assert len(circular_linked_list) == 0
assert circular_linked_list.is_empty() is True
assert str(circular_linked_list) == ""
try:
circular_linked_list.delete_front()
raise AssertionError() # This should not happen
except IndexError:
assert True # This should happen
try:
circular_linked_list.delete_tail()
raise AssertionError() # This should not happen
except IndexError:
assert True # This should happen
try:
circular_linked_list.delete_nth(-1)
raise AssertionError()
except IndexError:
assert True
try:
circular_linked_list.delete_nth(0)
raise AssertionError()
except IndexError:
assert True
assert circular_linked_list.is_empty() is True
for i in range(5):
assert len(circular_linked_list) == i
circular_linked_list.insert_nth(i, i + 1)
assert str(circular_linked_list) == "->".join(str(i) for i in range(1, 6))
circular_linked_list.insert_tail(6)
assert str(circular_linked_list) == "->".join(str(i) for i in range(1, 7))
circular_linked_list.insert_head(0)
assert str(circular_linked_list) == "->".join(str(i) for i in range(0, 7))
assert circular_linked_list.delete_front() == 0
assert circular_linked_list.delete_tail() == 6
assert str(circular_linked_list) == "->".join(str(i) for i in range(1, 6))
assert circular_linked_list.delete_nth(2) == 3
circular_linked_list.insert_nth(2, 3)
assert str(circular_linked_list) == "->".join(str(i) for i in range(1, 6))
assert circular_linked_list.is_empty() is False
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # https://github.com/rupansh/QuantumComputing/blob/master/rippleadd.py
# https://en.wikipedia.org/wiki/Adder_(electronics)#Full_adder
# https://en.wikipedia.org/wiki/Controlled_NOT_gate
from qiskit import Aer, QuantumCircuit, execute
from qiskit.providers import Backend
def store_two_classics(val1: int, val2: int) -> tuple[QuantumCircuit, str, str]:
"""
Generates a Quantum Circuit which stores two classical integers
Returns the circuit and binary representation of the integers
"""
x, y = bin(val1)[2:], bin(val2)[2:] # Remove leading '0b'
# Ensure that both strings are of the same length
if len(x) > len(y):
y = y.zfill(len(x))
else:
x = x.zfill(len(y))
# We need (3 * number of bits in the larger number)+1 qBits
# The second parameter is the number of classical registers, to measure the result
circuit = QuantumCircuit((len(x) * 3) + 1, len(x) + 1)
# We are essentially "not-ing" the bits that are 1
# Reversed because its easier to perform ops on more significant bits
for i in range(len(x)):
if x[::-1][i] == "1":
circuit.x(i)
for j in range(len(y)):
if y[::-1][j] == "1":
circuit.x(len(x) + j)
return circuit, x, y
def full_adder(
circuit: QuantumCircuit,
input1_loc: int,
input2_loc: int,
carry_in: int,
carry_out: int,
):
"""
Quantum Equivalent of a Full Adder Circuit
CX/CCX is like 2-way/3-way XOR
"""
circuit.ccx(input1_loc, input2_loc, carry_out)
circuit.cx(input1_loc, input2_loc)
circuit.ccx(input2_loc, carry_in, carry_out)
circuit.cx(input2_loc, carry_in)
circuit.cx(input1_loc, input2_loc)
# The default value for **backend** is the result of a function call which is not
# normally recommended and causes flake8-bugbear to raise a B008 error. However,
# in this case, this is accptable because `Aer.get_backend()` is called when the
# function is defined and that same backend is then reused for all function calls.
def ripple_adder(
val1: int,
val2: int,
backend: Backend = Aer.get_backend("qasm_simulator"), # noqa: B008
) -> int:
"""
Quantum Equivalent of a Ripple Adder Circuit
Uses qasm_simulator backend by default
Currently only adds 'emulated' Classical Bits
but nothing prevents us from doing this with hadamard'd bits :)
Only supports adding positive integers
>>> ripple_adder(3, 4)
7
>>> ripple_adder(10, 4)
14
>>> ripple_adder(-1, 10)
Traceback (most recent call last):
...
ValueError: Both Integers must be positive!
"""
if val1 < 0 or val2 < 0:
raise ValueError("Both Integers must be positive!")
# Store the Integers
circuit, x, y = store_two_classics(val1, val2)
"""
We are essentially using each bit of x & y respectively as full_adder's input
the carry_input is used from the previous circuit (for circuit num > 1)
the carry_out is just below carry_input because
it will be essentially the carry_input for the next full_adder
"""
for i in range(len(x)):
full_adder(circuit, i, len(x) + i, len(x) + len(y) + i, len(x) + len(y) + i + 1)
circuit.barrier() # Optional, just for aesthetics
# Measure the resultant qBits
for i in range(len(x) + 1):
circuit.measure([(len(x) * 2) + i], [i])
res = execute(circuit, backend, shots=1).result()
# The result is in binary. Convert it back to int
return int(list(res.get_counts())[0], 2)
if __name__ == "__main__":
import doctest
doctest.testmod()
| # https://github.com/rupansh/QuantumComputing/blob/master/rippleadd.py
# https://en.wikipedia.org/wiki/Adder_(electronics)#Full_adder
# https://en.wikipedia.org/wiki/Controlled_NOT_gate
from qiskit import Aer, QuantumCircuit, execute
from qiskit.providers import Backend
def store_two_classics(val1: int, val2: int) -> tuple[QuantumCircuit, str, str]:
"""
Generates a Quantum Circuit which stores two classical integers
Returns the circuit and binary representation of the integers
"""
x, y = bin(val1)[2:], bin(val2)[2:] # Remove leading '0b'
# Ensure that both strings are of the same length
if len(x) > len(y):
y = y.zfill(len(x))
else:
x = x.zfill(len(y))
# We need (3 * number of bits in the larger number)+1 qBits
# The second parameter is the number of classical registers, to measure the result
circuit = QuantumCircuit((len(x) * 3) + 1, len(x) + 1)
# We are essentially "not-ing" the bits that are 1
# Reversed because its easier to perform ops on more significant bits
for i in range(len(x)):
if x[::-1][i] == "1":
circuit.x(i)
for j in range(len(y)):
if y[::-1][j] == "1":
circuit.x(len(x) + j)
return circuit, x, y
def full_adder(
circuit: QuantumCircuit,
input1_loc: int,
input2_loc: int,
carry_in: int,
carry_out: int,
):
"""
Quantum Equivalent of a Full Adder Circuit
CX/CCX is like 2-way/3-way XOR
"""
circuit.ccx(input1_loc, input2_loc, carry_out)
circuit.cx(input1_loc, input2_loc)
circuit.ccx(input2_loc, carry_in, carry_out)
circuit.cx(input2_loc, carry_in)
circuit.cx(input1_loc, input2_loc)
# The default value for **backend** is the result of a function call which is not
# normally recommended and causes flake8-bugbear to raise a B008 error. However,
# in this case, this is accptable because `Aer.get_backend()` is called when the
# function is defined and that same backend is then reused for all function calls.
def ripple_adder(
val1: int,
val2: int,
backend: Backend = Aer.get_backend("qasm_simulator"), # noqa: B008
) -> int:
"""
Quantum Equivalent of a Ripple Adder Circuit
Uses qasm_simulator backend by default
Currently only adds 'emulated' Classical Bits
but nothing prevents us from doing this with hadamard'd bits :)
Only supports adding positive integers
>>> ripple_adder(3, 4)
7
>>> ripple_adder(10, 4)
14
>>> ripple_adder(-1, 10)
Traceback (most recent call last):
...
ValueError: Both Integers must be positive!
"""
if val1 < 0 or val2 < 0:
raise ValueError("Both Integers must be positive!")
# Store the Integers
circuit, x, y = store_two_classics(val1, val2)
"""
We are essentially using each bit of x & y respectively as full_adder's input
the carry_input is used from the previous circuit (for circuit num > 1)
the carry_out is just below carry_input because
it will be essentially the carry_input for the next full_adder
"""
for i in range(len(x)):
full_adder(circuit, i, len(x) + i, len(x) + len(y) + i, len(x) + len(y) + i + 1)
circuit.barrier() # Optional, just for aesthetics
# Measure the resultant qBits
for i in range(len(x) + 1):
circuit.measure([(len(x) * 2) + i], [i])
res = execute(circuit, backend, shots=1).result()
# The result is in binary. Convert it back to int
return int(list(res.get_counts())[0], 2)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #
| #
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Problem 34: https://projecteuler.net/problem=34
145 is a curious number, as 1! + 4! + 5! = 1 + 24 + 120 = 145.
Find the sum of all numbers which are equal to the sum of the factorial of their digits.
Note: As 1! = 1 and 2! = 2 are not sums they are not included.
"""
from math import factorial
DIGIT_FACTORIAL = {str(d): factorial(d) for d in range(10)}
def sum_of_digit_factorial(n: int) -> int:
"""
Returns the sum of the factorial of digits in n
>>> sum_of_digit_factorial(15)
121
>>> sum_of_digit_factorial(0)
1
"""
return sum(DIGIT_FACTORIAL[d] for d in str(n))
def solution() -> int:
"""
Returns the sum of all numbers whose
sum of the factorials of all digits
add up to the number itself.
>>> solution()
40730
"""
limit = 7 * factorial(9) + 1
return sum(i for i in range(3, limit) if sum_of_digit_factorial(i) == i)
if __name__ == "__main__":
print(f"{solution() = }")
| """
Problem 34: https://projecteuler.net/problem=34
145 is a curious number, as 1! + 4! + 5! = 1 + 24 + 120 = 145.
Find the sum of all numbers which are equal to the sum of the factorial of their digits.
Note: As 1! = 1 and 2! = 2 are not sums they are not included.
"""
from math import factorial
DIGIT_FACTORIAL = {str(d): factorial(d) for d in range(10)}
def sum_of_digit_factorial(n: int) -> int:
"""
Returns the sum of the factorial of digits in n
>>> sum_of_digit_factorial(15)
121
>>> sum_of_digit_factorial(0)
1
"""
return sum(DIGIT_FACTORIAL[d] for d in str(n))
def solution() -> int:
"""
Returns the sum of all numbers whose
sum of the factorials of all digits
add up to the number itself.
>>> solution()
40730
"""
limit = 7 * factorial(9) + 1
return sum(i for i in range(3, limit) if sum_of_digit_factorial(i) == i)
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
author: Christian Bender
date: 21.12.2017
class: XORCipher
This class implements the XOR-cipher algorithm and provides
some useful methods for encrypting and decrypting strings and
files.
Overview about methods
- encrypt : list of char
- decrypt : list of char
- encrypt_string : str
- decrypt_string : str
- encrypt_file : boolean
- decrypt_file : boolean
"""
from __future__ import annotations
class XORCipher:
def __init__(self, key: int = 0):
"""
simple constructor that receives a key or uses
default key = 0
"""
# private field
self.__key = key
def encrypt(self, content: str, key: int) -> list[str]:
"""
input: 'content' of type string and 'key' of type int
output: encrypted string 'content' as a list of chars
if key not passed the method uses the key by the constructor.
otherwise key = 1
"""
# precondition
assert isinstance(key, int) and isinstance(content, str)
key = key or self.__key or 1
# make sure key is an appropriate size
key %= 255
return [chr(ord(ch) ^ key) for ch in content]
def decrypt(self, content: str, key: int) -> list[str]:
"""
input: 'content' of type list and 'key' of type int
output: decrypted string 'content' as a list of chars
if key not passed the method uses the key by the constructor.
otherwise key = 1
"""
# precondition
assert isinstance(key, int) and isinstance(content, list)
key = key or self.__key or 1
# make sure key is an appropriate size
key %= 255
return [chr(ord(ch) ^ key) for ch in content]
def encrypt_string(self, content: str, key: int = 0) -> str:
"""
input: 'content' of type string and 'key' of type int
output: encrypted string 'content'
if key not passed the method uses the key by the constructor.
otherwise key = 1
"""
# precondition
assert isinstance(key, int) and isinstance(content, str)
key = key or self.__key or 1
# make sure key can be any size
while key > 255:
key -= 255
# This will be returned
ans = ""
for ch in content:
ans += chr(ord(ch) ^ key)
return ans
def decrypt_string(self, content: str, key: int = 0) -> str:
"""
input: 'content' of type string and 'key' of type int
output: decrypted string 'content'
if key not passed the method uses the key by the constructor.
otherwise key = 1
"""
# precondition
assert isinstance(key, int) and isinstance(content, str)
key = key or self.__key or 1
# make sure key can be any size
while key > 255:
key -= 255
# This will be returned
ans = ""
for ch in content:
ans += chr(ord(ch) ^ key)
return ans
def encrypt_file(self, file: str, key: int = 0) -> bool:
"""
input: filename (str) and a key (int)
output: returns true if encrypt process was
successful otherwise false
if key not passed the method uses the key by the constructor.
otherwise key = 1
"""
# precondition
assert isinstance(file, str) and isinstance(key, int)
try:
with open(file) as fin:
with open("encrypt.out", "w+") as fout:
# actual encrypt-process
for line in fin:
fout.write(self.encrypt_string(line, key))
except OSError:
return False
return True
def decrypt_file(self, file: str, key: int) -> bool:
"""
input: filename (str) and a key (int)
output: returns true if decrypt process was
successful otherwise false
if key not passed the method uses the key by the constructor.
otherwise key = 1
"""
# precondition
assert isinstance(file, str) and isinstance(key, int)
try:
with open(file) as fin:
with open("decrypt.out", "w+") as fout:
# actual encrypt-process
for line in fin:
fout.write(self.decrypt_string(line, key))
except OSError:
return False
return True
# Tests
# crypt = XORCipher()
# key = 67
# # test encrypt
# print(crypt.encrypt("hallo welt",key))
# # test decrypt
# print(crypt.decrypt(crypt.encrypt("hallo welt",key), key))
# # test encrypt_string
# print(crypt.encrypt_string("hallo welt",key))
# # test decrypt_string
# print(crypt.decrypt_string(crypt.encrypt_string("hallo welt",key),key))
# if (crypt.encrypt_file("test.txt",key)):
# print("encrypt successful")
# else:
# print("encrypt unsuccessful")
# if (crypt.decrypt_file("encrypt.out",key)):
# print("decrypt successful")
# else:
# print("decrypt unsuccessful")
| """
author: Christian Bender
date: 21.12.2017
class: XORCipher
This class implements the XOR-cipher algorithm and provides
some useful methods for encrypting and decrypting strings and
files.
Overview about methods
- encrypt : list of char
- decrypt : list of char
- encrypt_string : str
- decrypt_string : str
- encrypt_file : boolean
- decrypt_file : boolean
"""
from __future__ import annotations
class XORCipher:
def __init__(self, key: int = 0):
"""
simple constructor that receives a key or uses
default key = 0
"""
# private field
self.__key = key
def encrypt(self, content: str, key: int) -> list[str]:
"""
input: 'content' of type string and 'key' of type int
output: encrypted string 'content' as a list of chars
if key not passed the method uses the key by the constructor.
otherwise key = 1
"""
# precondition
assert isinstance(key, int) and isinstance(content, str)
key = key or self.__key or 1
# make sure key is an appropriate size
key %= 255
return [chr(ord(ch) ^ key) for ch in content]
def decrypt(self, content: str, key: int) -> list[str]:
"""
input: 'content' of type list and 'key' of type int
output: decrypted string 'content' as a list of chars
if key not passed the method uses the key by the constructor.
otherwise key = 1
"""
# precondition
assert isinstance(key, int) and isinstance(content, list)
key = key or self.__key or 1
# make sure key is an appropriate size
key %= 255
return [chr(ord(ch) ^ key) for ch in content]
def encrypt_string(self, content: str, key: int = 0) -> str:
"""
input: 'content' of type string and 'key' of type int
output: encrypted string 'content'
if key not passed the method uses the key by the constructor.
otherwise key = 1
"""
# precondition
assert isinstance(key, int) and isinstance(content, str)
key = key or self.__key or 1
# make sure key can be any size
while key > 255:
key -= 255
# This will be returned
ans = ""
for ch in content:
ans += chr(ord(ch) ^ key)
return ans
def decrypt_string(self, content: str, key: int = 0) -> str:
"""
input: 'content' of type string and 'key' of type int
output: decrypted string 'content'
if key not passed the method uses the key by the constructor.
otherwise key = 1
"""
# precondition
assert isinstance(key, int) and isinstance(content, str)
key = key or self.__key or 1
# make sure key can be any size
while key > 255:
key -= 255
# This will be returned
ans = ""
for ch in content:
ans += chr(ord(ch) ^ key)
return ans
def encrypt_file(self, file: str, key: int = 0) -> bool:
"""
input: filename (str) and a key (int)
output: returns true if encrypt process was
successful otherwise false
if key not passed the method uses the key by the constructor.
otherwise key = 1
"""
# precondition
assert isinstance(file, str) and isinstance(key, int)
try:
with open(file) as fin:
with open("encrypt.out", "w+") as fout:
# actual encrypt-process
for line in fin:
fout.write(self.encrypt_string(line, key))
except OSError:
return False
return True
def decrypt_file(self, file: str, key: int) -> bool:
"""
input: filename (str) and a key (int)
output: returns true if decrypt process was
successful otherwise false
if key not passed the method uses the key by the constructor.
otherwise key = 1
"""
# precondition
assert isinstance(file, str) and isinstance(key, int)
try:
with open(file) as fin:
with open("decrypt.out", "w+") as fout:
# actual encrypt-process
for line in fin:
fout.write(self.decrypt_string(line, key))
except OSError:
return False
return True
# Tests
# crypt = XORCipher()
# key = 67
# # test encrypt
# print(crypt.encrypt("hallo welt",key))
# # test decrypt
# print(crypt.decrypt(crypt.encrypt("hallo welt",key), key))
# # test encrypt_string
# print(crypt.encrypt_string("hallo welt",key))
# # test decrypt_string
# print(crypt.decrypt_string(crypt.encrypt_string("hallo welt",key),key))
# if (crypt.encrypt_file("test.txt",key)):
# print("encrypt successful")
# else:
# print("encrypt unsuccessful")
# if (crypt.decrypt_file("encrypt.out",key)):
# print("decrypt successful")
# else:
# print("decrypt unsuccessful")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This algorithm (k=33) was first reported by Dan Bernstein many years ago in comp.lang.c
Another version of this algorithm (now favored by Bernstein) uses xor:
hash(i) = hash(i - 1) * 33 ^ str[i];
First Magic constant 33:
It has never been adequately explained.
It's magic because it works better than many other constants, prime or not.
Second Magic Constant 5381:
1. odd number
2. prime number
3. deficient number
4. 001/010/100/000/101 b
source: http://www.cse.yorku.ca/~oz/hash.html
"""
def djb2(s: str) -> int:
"""
Implementation of djb2 hash algorithm that
is popular because of it's magic constants.
>>> djb2('Algorithms')
3782405311
>>> djb2('scramble bits')
1609059040
"""
hash_value = 5381
for x in s:
hash_value = ((hash_value << 5) + hash_value) + ord(x)
return hash_value & 0xFFFFFFFF
| """
This algorithm (k=33) was first reported by Dan Bernstein many years ago in comp.lang.c
Another version of this algorithm (now favored by Bernstein) uses xor:
hash(i) = hash(i - 1) * 33 ^ str[i];
First Magic constant 33:
It has never been adequately explained.
It's magic because it works better than many other constants, prime or not.
Second Magic Constant 5381:
1. odd number
2. prime number
3. deficient number
4. 001/010/100/000/101 b
source: http://www.cse.yorku.ca/~oz/hash.html
"""
def djb2(s: str) -> int:
"""
Implementation of djb2 hash algorithm that
is popular because of it's magic constants.
>>> djb2('Algorithms')
3782405311
>>> djb2('scramble bits')
1609059040
"""
hash_value = 5381
for x in s:
hash_value = ((hash_value << 5) + hash_value) + ord(x)
return hash_value & 0xFFFFFFFF
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def norm_squared(vector: ndarray) -> float:
"""
Return the squared second norm of vector
norm_squared(v) = sum(x * x for x in v)
Args:
vector (ndarray): input vector
Returns:
float: squared second norm of vector
>>> norm_squared([1, 2])
5
>>> norm_squared(np.asarray([1, 2]))
5
>>> norm_squared([0, 0])
0
"""
return np.dot(vector, vector)
class SVC:
"""
Support Vector Classifier
Args:
kernel (str): kernel to use. Default: linear
Possible choices:
- linear
regularization: constraint for soft margin (data not linearly separable)
Default: unbound
>>> SVC(kernel="asdf")
Traceback (most recent call last):
...
ValueError: Unknown kernel: asdf
>>> SVC(kernel="rbf")
Traceback (most recent call last):
...
ValueError: rbf kernel requires gamma
>>> SVC(kernel="rbf", gamma=-1)
Traceback (most recent call last):
...
ValueError: gamma must be > 0
"""
def __init__(
self,
*,
regularization: float = np.inf,
kernel: str = "linear",
gamma: float = 0,
) -> None:
self.regularization = regularization
self.gamma = gamma
if kernel == "linear":
self.kernel = self.__linear
elif kernel == "rbf":
if self.gamma == 0:
raise ValueError("rbf kernel requires gamma")
if not (isinstance(self.gamma, float) or isinstance(self.gamma, int)):
raise ValueError("gamma must be float or int")
if not self.gamma > 0:
raise ValueError("gamma must be > 0")
self.kernel = self.__rbf
# in the future, there could be a default value like in sklearn
# sklear: def_gamma = 1/(n_features * X.var()) (wiki)
# previously it was 1/(n_features)
else:
raise ValueError(f"Unknown kernel: {kernel}")
# kernels
def __linear(self, vector1: ndarray, vector2: ndarray) -> float:
"""Linear kernel (as if no kernel used at all)"""
return np.dot(vector1, vector2)
def __rbf(self, vector1: ndarray, vector2: ndarray) -> float:
"""
RBF: Radial Basis Function Kernel
Note: for more information see:
https://en.wikipedia.org/wiki/Radial_basis_function_kernel
Args:
vector1 (ndarray): first vector
vector2 (ndarray): second vector)
Returns:
float: exp(-(gamma * norm_squared(vector1 - vector2)))
"""
return np.exp(-(self.gamma * norm_squared(vector1 - vector2)))
def fit(self, observations: list[ndarray], classes: ndarray) -> None:
"""
Fits the SVC with a set of observations.
Args:
observations (list[ndarray]): list of observations
classes (ndarray): classification of each observation (in {1, -1})
"""
self.observations = observations
self.classes = classes
# using Wolfe's Dual to calculate w.
# Primal problem: minimize 1/2*norm_squared(w)
# constraint: yn(w . xn + b) >= 1
#
# With l a vector
# Dual problem: maximize sum_n(ln) -
# 1/2 * sum_n(sum_m(ln*lm*yn*ym*xn . xm))
# constraint: self.C >= ln >= 0
# and sum_n(ln*yn) = 0
# Then we get w using w = sum_n(ln*yn*xn)
# At the end we can get b ~= mean(yn - w . xn)
#
# Since we use kernels, we only need l_star to calculate b
# and to classify observations
(n,) = np.shape(classes)
def to_minimize(candidate: ndarray) -> float:
"""
Opposite of the function to maximize
Args:
candidate (ndarray): candidate array to test
Return:
float: Wolfe's Dual result to minimize
"""
s = 0
(n,) = np.shape(candidate)
for i in range(n):
for j in range(n):
s += (
candidate[i]
* candidate[j]
* classes[i]
* classes[j]
* self.kernel(observations[i], observations[j])
)
return 1 / 2 * s - sum(candidate)
ly_contraint = LinearConstraint(classes, 0, 0)
l_bounds = Bounds(0, self.regularization)
l_star = minimize(
to_minimize, np.ones(n), bounds=l_bounds, constraints=[ly_contraint]
).x
self.optimum = l_star
# calculating mean offset of separation plane to points
s = 0
for i in range(n):
for j in range(n):
s += classes[i] - classes[i] * self.optimum[i] * self.kernel(
observations[i], observations[j]
)
self.offset = s / n
def predict(self, observation: ndarray) -> int:
"""
Get the expected class of an observation
Args:
observation (Vector): observation
Returns:
int {1, -1}: expected class
>>> xs = [
... np.asarray([0, 1]), np.asarray([0, 2]),
... np.asarray([1, 1]), np.asarray([1, 2])
... ]
>>> y = np.asarray([1, 1, -1, -1])
>>> s = SVC()
>>> s.fit(xs, y)
>>> s.predict(np.asarray([0, 1]))
1
>>> s.predict(np.asarray([1, 1]))
-1
>>> s.predict(np.asarray([2, 2]))
-1
"""
s = sum(
self.optimum[n]
* self.classes[n]
* self.kernel(self.observations[n], observation)
for n in range(len(self.classes))
)
return 1 if s + self.offset >= 0 else -1
if __name__ == "__main__":
import doctest
doctest.testmod()
| import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def norm_squared(vector: ndarray) -> float:
"""
Return the squared second norm of vector
norm_squared(v) = sum(x * x for x in v)
Args:
vector (ndarray): input vector
Returns:
float: squared second norm of vector
>>> norm_squared([1, 2])
5
>>> norm_squared(np.asarray([1, 2]))
5
>>> norm_squared([0, 0])
0
"""
return np.dot(vector, vector)
class SVC:
"""
Support Vector Classifier
Args:
kernel (str): kernel to use. Default: linear
Possible choices:
- linear
regularization: constraint for soft margin (data not linearly separable)
Default: unbound
>>> SVC(kernel="asdf")
Traceback (most recent call last):
...
ValueError: Unknown kernel: asdf
>>> SVC(kernel="rbf")
Traceback (most recent call last):
...
ValueError: rbf kernel requires gamma
>>> SVC(kernel="rbf", gamma=-1)
Traceback (most recent call last):
...
ValueError: gamma must be > 0
"""
def __init__(
self,
*,
regularization: float = np.inf,
kernel: str = "linear",
gamma: float = 0,
) -> None:
self.regularization = regularization
self.gamma = gamma
if kernel == "linear":
self.kernel = self.__linear
elif kernel == "rbf":
if self.gamma == 0:
raise ValueError("rbf kernel requires gamma")
if not (isinstance(self.gamma, float) or isinstance(self.gamma, int)):
raise ValueError("gamma must be float or int")
if not self.gamma > 0:
raise ValueError("gamma must be > 0")
self.kernel = self.__rbf
# in the future, there could be a default value like in sklearn
# sklear: def_gamma = 1/(n_features * X.var()) (wiki)
# previously it was 1/(n_features)
else:
raise ValueError(f"Unknown kernel: {kernel}")
# kernels
def __linear(self, vector1: ndarray, vector2: ndarray) -> float:
"""Linear kernel (as if no kernel used at all)"""
return np.dot(vector1, vector2)
def __rbf(self, vector1: ndarray, vector2: ndarray) -> float:
"""
RBF: Radial Basis Function Kernel
Note: for more information see:
https://en.wikipedia.org/wiki/Radial_basis_function_kernel
Args:
vector1 (ndarray): first vector
vector2 (ndarray): second vector)
Returns:
float: exp(-(gamma * norm_squared(vector1 - vector2)))
"""
return np.exp(-(self.gamma * norm_squared(vector1 - vector2)))
def fit(self, observations: list[ndarray], classes: ndarray) -> None:
"""
Fits the SVC with a set of observations.
Args:
observations (list[ndarray]): list of observations
classes (ndarray): classification of each observation (in {1, -1})
"""
self.observations = observations
self.classes = classes
# using Wolfe's Dual to calculate w.
# Primal problem: minimize 1/2*norm_squared(w)
# constraint: yn(w . xn + b) >= 1
#
# With l a vector
# Dual problem: maximize sum_n(ln) -
# 1/2 * sum_n(sum_m(ln*lm*yn*ym*xn . xm))
# constraint: self.C >= ln >= 0
# and sum_n(ln*yn) = 0
# Then we get w using w = sum_n(ln*yn*xn)
# At the end we can get b ~= mean(yn - w . xn)
#
# Since we use kernels, we only need l_star to calculate b
# and to classify observations
(n,) = np.shape(classes)
def to_minimize(candidate: ndarray) -> float:
"""
Opposite of the function to maximize
Args:
candidate (ndarray): candidate array to test
Return:
float: Wolfe's Dual result to minimize
"""
s = 0
(n,) = np.shape(candidate)
for i in range(n):
for j in range(n):
s += (
candidate[i]
* candidate[j]
* classes[i]
* classes[j]
* self.kernel(observations[i], observations[j])
)
return 1 / 2 * s - sum(candidate)
ly_contraint = LinearConstraint(classes, 0, 0)
l_bounds = Bounds(0, self.regularization)
l_star = minimize(
to_minimize, np.ones(n), bounds=l_bounds, constraints=[ly_contraint]
).x
self.optimum = l_star
# calculating mean offset of separation plane to points
s = 0
for i in range(n):
for j in range(n):
s += classes[i] - classes[i] * self.optimum[i] * self.kernel(
observations[i], observations[j]
)
self.offset = s / n
def predict(self, observation: ndarray) -> int:
"""
Get the expected class of an observation
Args:
observation (Vector): observation
Returns:
int {1, -1}: expected class
>>> xs = [
... np.asarray([0, 1]), np.asarray([0, 2]),
... np.asarray([1, 1]), np.asarray([1, 2])
... ]
>>> y = np.asarray([1, 1, -1, -1])
>>> s = SVC()
>>> s.fit(xs, y)
>>> s.predict(np.asarray([0, 1]))
1
>>> s.predict(np.asarray([1, 1]))
-1
>>> s.predict(np.asarray([2, 2]))
-1
"""
s = sum(
self.optimum[n]
* self.classes[n]
* self.kernel(self.observations[n], observation)
for n in range(len(self.classes))
)
return 1 if s + self.offset >= 0 else -1
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Given a array of length n, max_subarray_sum() finds
the maximum of sum of contiguous sub-array using divide and conquer method.
Time complexity : O(n log n)
Ref : INTRODUCTION TO ALGORITHMS THIRD EDITION
(section : 4, sub-section : 4.1, page : 70)
"""
def max_sum_from_start(array):
"""This function finds the maximum contiguous sum of array from 0 index
Parameters :
array (list[int]) : given array
Returns :
max_sum (int) : maximum contiguous sum of array from 0 index
"""
array_sum = 0
max_sum = float("-inf")
for num in array:
array_sum += num
if array_sum > max_sum:
max_sum = array_sum
return max_sum
def max_cross_array_sum(array, left, mid, right):
"""This function finds the maximum contiguous sum of left and right arrays
Parameters :
array, left, mid, right (list[int], int, int, int)
Returns :
(int) : maximum of sum of contiguous sum of left and right arrays
"""
max_sum_of_left = max_sum_from_start(array[left : mid + 1][::-1])
max_sum_of_right = max_sum_from_start(array[mid + 1 : right + 1])
return max_sum_of_left + max_sum_of_right
def max_subarray_sum(array, left, right):
"""Maximum contiguous sub-array sum, using divide and conquer method
Parameters :
array, left, right (list[int], int, int) :
given array, current left index and current right index
Returns :
int : maximum of sum of contiguous sub-array
"""
# base case: array has only one element
if left == right:
return array[right]
# Recursion
mid = (left + right) // 2
left_half_sum = max_subarray_sum(array, left, mid)
right_half_sum = max_subarray_sum(array, mid + 1, right)
cross_sum = max_cross_array_sum(array, left, mid, right)
return max(left_half_sum, right_half_sum, cross_sum)
array = [-2, -5, 6, -2, -3, 1, 5, -6]
array_length = len(array)
print(
"Maximum sum of contiguous subarray:", max_subarray_sum(array, 0, array_length - 1)
)
| """
Given a array of length n, max_subarray_sum() finds
the maximum of sum of contiguous sub-array using divide and conquer method.
Time complexity : O(n log n)
Ref : INTRODUCTION TO ALGORITHMS THIRD EDITION
(section : 4, sub-section : 4.1, page : 70)
"""
def max_sum_from_start(array):
"""This function finds the maximum contiguous sum of array from 0 index
Parameters :
array (list[int]) : given array
Returns :
max_sum (int) : maximum contiguous sum of array from 0 index
"""
array_sum = 0
max_sum = float("-inf")
for num in array:
array_sum += num
if array_sum > max_sum:
max_sum = array_sum
return max_sum
def max_cross_array_sum(array, left, mid, right):
"""This function finds the maximum contiguous sum of left and right arrays
Parameters :
array, left, mid, right (list[int], int, int, int)
Returns :
(int) : maximum of sum of contiguous sum of left and right arrays
"""
max_sum_of_left = max_sum_from_start(array[left : mid + 1][::-1])
max_sum_of_right = max_sum_from_start(array[mid + 1 : right + 1])
return max_sum_of_left + max_sum_of_right
def max_subarray_sum(array, left, right):
"""Maximum contiguous sub-array sum, using divide and conquer method
Parameters :
array, left, right (list[int], int, int) :
given array, current left index and current right index
Returns :
int : maximum of sum of contiguous sub-array
"""
# base case: array has only one element
if left == right:
return array[right]
# Recursion
mid = (left + right) // 2
left_half_sum = max_subarray_sum(array, left, mid)
right_half_sum = max_subarray_sum(array, mid + 1, right)
cross_sum = max_cross_array_sum(array, left, mid, right)
return max(left_half_sum, right_half_sum, cross_sum)
array = [-2, -5, 6, -2, -3, 1, 5, -6]
array_length = len(array)
print(
"Maximum sum of contiguous subarray:", max_subarray_sum(array, 0, array_length - 1)
)
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from collections.abc import Sequence
def evaluate_poly(poly: Sequence[float], x: float) -> float:
"""Evaluate a polynomial f(x) at specified point x and return the value.
Arguments:
poly -- the coefficients of a polynomial as an iterable in order of
ascending degree
x -- the point at which to evaluate the polynomial
>>> evaluate_poly((0.0, 0.0, 5.0, 9.3, 7.0), 10.0)
79800.0
"""
return sum(c * (x**i) for i, c in enumerate(poly))
def horner(poly: Sequence[float], x: float) -> float:
"""Evaluate a polynomial at specified point using Horner's method.
In terms of computational complexity, Horner's method is an efficient method
of evaluating a polynomial. It avoids the use of expensive exponentiation,
and instead uses only multiplication and addition to evaluate the polynomial
in O(n), where n is the degree of the polynomial.
https://en.wikipedia.org/wiki/Horner's_method
Arguments:
poly -- the coefficients of a polynomial as an iterable in order of
ascending degree
x -- the point at which to evaluate the polynomial
>>> horner((0.0, 0.0, 5.0, 9.3, 7.0), 10.0)
79800.0
"""
result = 0.0
for coeff in reversed(poly):
result = result * x + coeff
return result
if __name__ == "__main__":
"""
Example:
>>> poly = (0.0, 0.0, 5.0, 9.3, 7.0) # f(x) = 7.0x^4 + 9.3x^3 + 5.0x^2
>>> x = -13.0
>>> # f(-13) = 7.0(-13)^4 + 9.3(-13)^3 + 5.0(-13)^2 = 180339.9
>>> print(evaluate_poly(poly, x))
180339.9
"""
poly = (0.0, 0.0, 5.0, 9.3, 7.0)
x = 10.0
print(evaluate_poly(poly, x))
print(horner(poly, x))
| from collections.abc import Sequence
def evaluate_poly(poly: Sequence[float], x: float) -> float:
"""Evaluate a polynomial f(x) at specified point x and return the value.
Arguments:
poly -- the coefficients of a polynomial as an iterable in order of
ascending degree
x -- the point at which to evaluate the polynomial
>>> evaluate_poly((0.0, 0.0, 5.0, 9.3, 7.0), 10.0)
79800.0
"""
return sum(c * (x**i) for i, c in enumerate(poly))
def horner(poly: Sequence[float], x: float) -> float:
"""Evaluate a polynomial at specified point using Horner's method.
In terms of computational complexity, Horner's method is an efficient method
of evaluating a polynomial. It avoids the use of expensive exponentiation,
and instead uses only multiplication and addition to evaluate the polynomial
in O(n), where n is the degree of the polynomial.
https://en.wikipedia.org/wiki/Horner's_method
Arguments:
poly -- the coefficients of a polynomial as an iterable in order of
ascending degree
x -- the point at which to evaluate the polynomial
>>> horner((0.0, 0.0, 5.0, 9.3, 7.0), 10.0)
79800.0
"""
result = 0.0
for coeff in reversed(poly):
result = result * x + coeff
return result
if __name__ == "__main__":
"""
Example:
>>> poly = (0.0, 0.0, 5.0, 9.3, 7.0) # f(x) = 7.0x^4 + 9.3x^3 + 5.0x^2
>>> x = -13.0
>>> # f(-13) = 7.0(-13)^4 + 9.3(-13)^3 + 5.0(-13)^2 = 180339.9
>>> print(evaluate_poly(poly, x))
180339.9
"""
poly = (0.0, 0.0, 5.0, 9.3, 7.0)
x = 10.0
print(evaluate_poly(poly, x))
print(horner(poly, x))
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Hey, we are going to find an exciting number called Catalan number which is use to find
the number of possible binary search trees from tree of a given number of nodes.
We will use the formula: t(n) = SUMMATION(i = 1 to n)t(i-1)t(n-i)
Further details at Wikipedia: https://en.wikipedia.org/wiki/Catalan_number
"""
"""
Our Contribution:
Basically we Create the 2 function:
1. catalan_number(node_count: int) -> int
Returns the number of possible binary search trees for n nodes.
2. binary_tree_count(node_count: int) -> int
Returns the number of possible binary trees for n nodes.
"""
def binomial_coefficient(n: int, k: int) -> int:
"""
Since Here we Find the Binomial Coefficient:
https://en.wikipedia.org/wiki/Binomial_coefficient
C(n,k) = n! / k!(n-k)!
:param n: 2 times of Number of nodes
:param k: Number of nodes
:return: Integer Value
>>> binomial_coefficient(4, 2)
6
"""
result = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
k = n - k
# Calculate C(n,k)
for i in range(k):
result *= n - i
result //= i + 1
return result
def catalan_number(node_count: int) -> int:
"""
We can find Catalan number many ways but here we use Binomial Coefficient because it
does the job in O(n)
return the Catalan number of n using 2nCn/(n+1).
:param n: number of nodes
:return: Catalan number of n nodes
>>> catalan_number(5)
42
>>> catalan_number(6)
132
"""
return binomial_coefficient(2 * node_count, node_count) // (node_count + 1)
def factorial(n: int) -> int:
"""
Return the factorial of a number.
:param n: Number to find the Factorial of.
:return: Factorial of n.
>>> import math
>>> all(factorial(i) == math.factorial(i) for i in range(10))
True
>>> factorial(-5) # doctest: +ELLIPSIS
Traceback (most recent call last):
...
ValueError: factorial() not defined for negative values
"""
if n < 0:
raise ValueError("factorial() not defined for negative values")
result = 1
for i in range(1, n + 1):
result *= i
return result
def binary_tree_count(node_count: int) -> int:
"""
Return the number of possible of binary trees.
:param n: number of nodes
:return: Number of possible binary trees
>>> binary_tree_count(5)
5040
>>> binary_tree_count(6)
95040
"""
return catalan_number(node_count) * factorial(node_count)
if __name__ == "__main__":
node_count = int(input("Enter the number of nodes: ").strip() or 0)
if node_count <= 0:
raise ValueError("We need some nodes to work with.")
print(
f"Given {node_count} nodes, there are {binary_tree_count(node_count)} "
f"binary trees and {catalan_number(node_count)} binary search trees."
)
| """
Hey, we are going to find an exciting number called Catalan number which is use to find
the number of possible binary search trees from tree of a given number of nodes.
We will use the formula: t(n) = SUMMATION(i = 1 to n)t(i-1)t(n-i)
Further details at Wikipedia: https://en.wikipedia.org/wiki/Catalan_number
"""
"""
Our Contribution:
Basically we Create the 2 function:
1. catalan_number(node_count: int) -> int
Returns the number of possible binary search trees for n nodes.
2. binary_tree_count(node_count: int) -> int
Returns the number of possible binary trees for n nodes.
"""
def binomial_coefficient(n: int, k: int) -> int:
"""
Since Here we Find the Binomial Coefficient:
https://en.wikipedia.org/wiki/Binomial_coefficient
C(n,k) = n! / k!(n-k)!
:param n: 2 times of Number of nodes
:param k: Number of nodes
:return: Integer Value
>>> binomial_coefficient(4, 2)
6
"""
result = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
k = n - k
# Calculate C(n,k)
for i in range(k):
result *= n - i
result //= i + 1
return result
def catalan_number(node_count: int) -> int:
"""
We can find Catalan number many ways but here we use Binomial Coefficient because it
does the job in O(n)
return the Catalan number of n using 2nCn/(n+1).
:param n: number of nodes
:return: Catalan number of n nodes
>>> catalan_number(5)
42
>>> catalan_number(6)
132
"""
return binomial_coefficient(2 * node_count, node_count) // (node_count + 1)
def factorial(n: int) -> int:
"""
Return the factorial of a number.
:param n: Number to find the Factorial of.
:return: Factorial of n.
>>> import math
>>> all(factorial(i) == math.factorial(i) for i in range(10))
True
>>> factorial(-5) # doctest: +ELLIPSIS
Traceback (most recent call last):
...
ValueError: factorial() not defined for negative values
"""
if n < 0:
raise ValueError("factorial() not defined for negative values")
result = 1
for i in range(1, n + 1):
result *= i
return result
def binary_tree_count(node_count: int) -> int:
"""
Return the number of possible of binary trees.
:param n: number of nodes
:return: Number of possible binary trees
>>> binary_tree_count(5)
5040
>>> binary_tree_count(6)
95040
"""
return catalan_number(node_count) * factorial(node_count)
if __name__ == "__main__":
node_count = int(input("Enter the number of nodes: ").strip() or 0)
if node_count <= 0:
raise ValueError("We need some nodes to work with.")
print(
f"Given {node_count} nodes, there are {binary_tree_count(node_count)} "
f"binary trees and {catalan_number(node_count)} binary search trees."
)
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Horizontal Projectile Motion problem in physics.
This algorithm solves a specific problem in which
the motion starts from the ground as can be seen below:
(v = 0)
**
* *
* *
* *
* *
* *
GROUND GROUND
For more info: https://en.wikipedia.org/wiki/Projectile_motion
"""
# Importing packages
from math import radians as angle_to_radians
from math import sin
# Acceleration Constant on Earth (unit m/s^2)
g = 9.80665
def check_args(init_velocity: float, angle: float) -> None:
"""
Check that the arguments are valid
"""
# Ensure valid instance
if not isinstance(init_velocity, (int, float)):
raise TypeError("Invalid velocity. Should be a positive number.")
if not isinstance(angle, (int, float)):
raise TypeError("Invalid angle. Range is 1-90 degrees.")
# Ensure valid angle
if angle > 90 or angle < 1:
raise ValueError("Invalid angle. Range is 1-90 degrees.")
# Ensure valid velocity
if init_velocity < 0:
raise ValueError("Invalid velocity. Should be a positive number.")
def horizontal_distance(init_velocity: float, angle: float) -> float:
"""
Returns the horizontal distance that the object cover
Formula:
v_0^2 * sin(2 * alpha)
---------------------
g
v_0 - initial velocity
alpha - angle
>>> horizontal_distance(30, 45)
91.77
>>> horizontal_distance(100, 78)
414.76
>>> horizontal_distance(-1, 20)
Traceback (most recent call last):
...
ValueError: Invalid velocity. Should be a positive number.
>>> horizontal_distance(30, -20)
Traceback (most recent call last):
...
ValueError: Invalid angle. Range is 1-90 degrees.
"""
check_args(init_velocity, angle)
radians = angle_to_radians(2 * angle)
return round(init_velocity**2 * sin(radians) / g, 2)
def max_height(init_velocity: float, angle: float) -> float:
"""
Returns the maximum height that the object reach
Formula:
v_0^2 * sin^2(alpha)
--------------------
2g
v_0 - initial velocity
alpha - angle
>>> max_height(30, 45)
22.94
>>> max_height(100, 78)
487.82
>>> max_height("a", 20)
Traceback (most recent call last):
...
TypeError: Invalid velocity. Should be a positive number.
>>> horizontal_distance(30, "b")
Traceback (most recent call last):
...
TypeError: Invalid angle. Range is 1-90 degrees.
"""
check_args(init_velocity, angle)
radians = angle_to_radians(angle)
return round(init_velocity**2 * sin(radians) ** 2 / (2 * g), 2)
def total_time(init_velocity: float, angle: float) -> float:
"""
Returns total time of the motion
Formula:
2 * v_0 * sin(alpha)
--------------------
g
v_0 - initial velocity
alpha - angle
>>> total_time(30, 45)
4.33
>>> total_time(100, 78)
19.95
>>> total_time(-10, 40)
Traceback (most recent call last):
...
ValueError: Invalid velocity. Should be a positive number.
>>> total_time(30, "b")
Traceback (most recent call last):
...
TypeError: Invalid angle. Range is 1-90 degrees.
"""
check_args(init_velocity, angle)
radians = angle_to_radians(angle)
return round(2 * init_velocity * sin(radians) / g, 2)
def test_motion() -> None:
"""
>>> test_motion()
"""
v0, angle = 25, 20
assert horizontal_distance(v0, angle) == 40.97
assert max_height(v0, angle) == 3.73
assert total_time(v0, angle) == 1.74
if __name__ == "__main__":
from doctest import testmod
testmod()
# Get input from user
init_vel = float(input("Initial Velocity: ").strip())
# Get input from user
angle = float(input("angle: ").strip())
# Print results
print()
print("Results: ")
print(f"Horizontal Distance: {str(horizontal_distance(init_vel, angle))} [m]")
print(f"Maximum Height: {str(max_height(init_vel, angle))} [m]")
print(f"Total Time: {str(total_time(init_vel, angle))} [s]")
| """
Horizontal Projectile Motion problem in physics.
This algorithm solves a specific problem in which
the motion starts from the ground as can be seen below:
(v = 0)
**
* *
* *
* *
* *
* *
GROUND GROUND
For more info: https://en.wikipedia.org/wiki/Projectile_motion
"""
# Importing packages
from math import radians as angle_to_radians
from math import sin
# Acceleration Constant on Earth (unit m/s^2)
g = 9.80665
def check_args(init_velocity: float, angle: float) -> None:
"""
Check that the arguments are valid
"""
# Ensure valid instance
if not isinstance(init_velocity, (int, float)):
raise TypeError("Invalid velocity. Should be a positive number.")
if not isinstance(angle, (int, float)):
raise TypeError("Invalid angle. Range is 1-90 degrees.")
# Ensure valid angle
if angle > 90 or angle < 1:
raise ValueError("Invalid angle. Range is 1-90 degrees.")
# Ensure valid velocity
if init_velocity < 0:
raise ValueError("Invalid velocity. Should be a positive number.")
def horizontal_distance(init_velocity: float, angle: float) -> float:
"""
Returns the horizontal distance that the object cover
Formula:
v_0^2 * sin(2 * alpha)
---------------------
g
v_0 - initial velocity
alpha - angle
>>> horizontal_distance(30, 45)
91.77
>>> horizontal_distance(100, 78)
414.76
>>> horizontal_distance(-1, 20)
Traceback (most recent call last):
...
ValueError: Invalid velocity. Should be a positive number.
>>> horizontal_distance(30, -20)
Traceback (most recent call last):
...
ValueError: Invalid angle. Range is 1-90 degrees.
"""
check_args(init_velocity, angle)
radians = angle_to_radians(2 * angle)
return round(init_velocity**2 * sin(radians) / g, 2)
def max_height(init_velocity: float, angle: float) -> float:
"""
Returns the maximum height that the object reach
Formula:
v_0^2 * sin^2(alpha)
--------------------
2g
v_0 - initial velocity
alpha - angle
>>> max_height(30, 45)
22.94
>>> max_height(100, 78)
487.82
>>> max_height("a", 20)
Traceback (most recent call last):
...
TypeError: Invalid velocity. Should be a positive number.
>>> horizontal_distance(30, "b")
Traceback (most recent call last):
...
TypeError: Invalid angle. Range is 1-90 degrees.
"""
check_args(init_velocity, angle)
radians = angle_to_radians(angle)
return round(init_velocity**2 * sin(radians) ** 2 / (2 * g), 2)
def total_time(init_velocity: float, angle: float) -> float:
"""
Returns total time of the motion
Formula:
2 * v_0 * sin(alpha)
--------------------
g
v_0 - initial velocity
alpha - angle
>>> total_time(30, 45)
4.33
>>> total_time(100, 78)
19.95
>>> total_time(-10, 40)
Traceback (most recent call last):
...
ValueError: Invalid velocity. Should be a positive number.
>>> total_time(30, "b")
Traceback (most recent call last):
...
TypeError: Invalid angle. Range is 1-90 degrees.
"""
check_args(init_velocity, angle)
radians = angle_to_radians(angle)
return round(2 * init_velocity * sin(radians) / g, 2)
def test_motion() -> None:
"""
>>> test_motion()
"""
v0, angle = 25, 20
assert horizontal_distance(v0, angle) == 40.97
assert max_height(v0, angle) == 3.73
assert total_time(v0, angle) == 1.74
if __name__ == "__main__":
from doctest import testmod
testmod()
# Get input from user
init_vel = float(input("Initial Velocity: ").strip())
# Get input from user
angle = float(input("angle: ").strip())
# Print results
print()
print("Results: ")
print(f"Horizontal Distance: {str(horizontal_distance(init_vel, angle))} [m]")
print(f"Maximum Height: {str(max_height(init_vel, angle))} [m]")
print(f"Total Time: {str(total_time(init_vel, angle))} [s]")
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # flake8: noqa
"""
This is pure Python implementation of tree traversal algorithms
"""
from __future__ import annotations
import queue
class TreeNode:
def __init__(self, data):
self.data = data
self.right = None
self.left = None
def build_tree():
print("\n********Press N to stop entering at any point of time********\n")
check = input("Enter the value of the root node: ").strip().lower() or "n"
if check == "n":
return None
q: queue.Queue = queue.Queue()
tree_node = TreeNode(int(check))
q.put(tree_node)
while not q.empty():
node_found = q.get()
msg = f"Enter the left node of {node_found.data}: "
check = input(msg).strip().lower() or "n"
if check == "n":
return tree_node
left_node = TreeNode(int(check))
node_found.left = left_node
q.put(left_node)
msg = f"Enter the right node of {node_found.data}: "
check = input(msg).strip().lower() or "n"
if check == "n":
return tree_node
right_node = TreeNode(int(check))
node_found.right = right_node
q.put(right_node)
def pre_order(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> pre_order(root)
1,2,4,5,3,6,7,
"""
if not isinstance(node, TreeNode) or not node:
return
print(node.data, end=",")
pre_order(node.left)
pre_order(node.right)
def in_order(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> in_order(root)
4,2,5,1,6,3,7,
"""
if not isinstance(node, TreeNode) or not node:
return
in_order(node.left)
print(node.data, end=",")
in_order(node.right)
def post_order(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> post_order(root)
4,5,2,6,7,3,1,
"""
if not isinstance(node, TreeNode) or not node:
return
post_order(node.left)
post_order(node.right)
print(node.data, end=",")
def level_order(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> level_order(root)
1,2,3,4,5,6,7,
"""
if not isinstance(node, TreeNode) or not node:
return
q: queue.Queue = queue.Queue()
q.put(node)
while not q.empty():
node_dequeued = q.get()
print(node_dequeued.data, end=",")
if node_dequeued.left:
q.put(node_dequeued.left)
if node_dequeued.right:
q.put(node_dequeued.right)
def level_order_actual(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> level_order_actual(root)
1,
2,3,
4,5,6,7,
"""
if not isinstance(node, TreeNode) or not node:
return
q: queue.Queue = queue.Queue()
q.put(node)
while not q.empty():
list = []
while not q.empty():
node_dequeued = q.get()
print(node_dequeued.data, end=",")
if node_dequeued.left:
list.append(node_dequeued.left)
if node_dequeued.right:
list.append(node_dequeued.right)
print()
for node in list:
q.put(node)
# iteration version
def pre_order_iter(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> pre_order_iter(root)
1,2,4,5,3,6,7,
"""
if not isinstance(node, TreeNode) or not node:
return
stack: list[TreeNode] = []
n = node
while n or stack:
while n: # start from root node, find its left child
print(n.data, end=",")
stack.append(n)
n = n.left
# end of while means current node doesn't have left child
n = stack.pop()
# start to traverse its right child
n = n.right
def in_order_iter(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> in_order_iter(root)
4,2,5,1,6,3,7,
"""
if not isinstance(node, TreeNode) or not node:
return
stack: list[TreeNode] = []
n = node
while n or stack:
while n:
stack.append(n)
n = n.left
n = stack.pop()
print(n.data, end=",")
n = n.right
def post_order_iter(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> post_order_iter(root)
4,5,2,6,7,3,1,
"""
if not isinstance(node, TreeNode) or not node:
return
stack1, stack2 = [], []
n = node
stack1.append(n)
while stack1: # to find the reversed order of post order, store it in stack2
n = stack1.pop()
if n.left:
stack1.append(n.left)
if n.right:
stack1.append(n.right)
stack2.append(n)
while stack2: # pop up from stack2 will be the post order
print(stack2.pop().data, end=",")
def prompt(s: str = "", width=50, char="*") -> str:
if not s:
return "\n" + width * char
left, extra = divmod(width - len(s) - 2, 2)
return f"{left * char} {s} {(left + extra) * char}"
if __name__ == "__main__":
import doctest
doctest.testmod()
print(prompt("Binary Tree Traversals"))
node = build_tree()
print(prompt("Pre Order Traversal"))
pre_order(node)
print(prompt() + "\n")
print(prompt("In Order Traversal"))
in_order(node)
print(prompt() + "\n")
print(prompt("Post Order Traversal"))
post_order(node)
print(prompt() + "\n")
print(prompt("Level Order Traversal"))
level_order(node)
print(prompt() + "\n")
print(prompt("Actual Level Order Traversal"))
level_order_actual(node)
print("*" * 50 + "\n")
print(prompt("Pre Order Traversal - Iteration Version"))
pre_order_iter(node)
print(prompt() + "\n")
print(prompt("In Order Traversal - Iteration Version"))
in_order_iter(node)
print(prompt() + "\n")
print(prompt("Post Order Traversal - Iteration Version"))
post_order_iter(node)
print(prompt())
| # flake8: noqa
"""
This is pure Python implementation of tree traversal algorithms
"""
from __future__ import annotations
import queue
class TreeNode:
def __init__(self, data):
self.data = data
self.right = None
self.left = None
def build_tree():
print("\n********Press N to stop entering at any point of time********\n")
check = input("Enter the value of the root node: ").strip().lower() or "n"
if check == "n":
return None
q: queue.Queue = queue.Queue()
tree_node = TreeNode(int(check))
q.put(tree_node)
while not q.empty():
node_found = q.get()
msg = f"Enter the left node of {node_found.data}: "
check = input(msg).strip().lower() or "n"
if check == "n":
return tree_node
left_node = TreeNode(int(check))
node_found.left = left_node
q.put(left_node)
msg = f"Enter the right node of {node_found.data}: "
check = input(msg).strip().lower() or "n"
if check == "n":
return tree_node
right_node = TreeNode(int(check))
node_found.right = right_node
q.put(right_node)
def pre_order(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> pre_order(root)
1,2,4,5,3,6,7,
"""
if not isinstance(node, TreeNode) or not node:
return
print(node.data, end=",")
pre_order(node.left)
pre_order(node.right)
def in_order(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> in_order(root)
4,2,5,1,6,3,7,
"""
if not isinstance(node, TreeNode) or not node:
return
in_order(node.left)
print(node.data, end=",")
in_order(node.right)
def post_order(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> post_order(root)
4,5,2,6,7,3,1,
"""
if not isinstance(node, TreeNode) or not node:
return
post_order(node.left)
post_order(node.right)
print(node.data, end=",")
def level_order(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> level_order(root)
1,2,3,4,5,6,7,
"""
if not isinstance(node, TreeNode) or not node:
return
q: queue.Queue = queue.Queue()
q.put(node)
while not q.empty():
node_dequeued = q.get()
print(node_dequeued.data, end=",")
if node_dequeued.left:
q.put(node_dequeued.left)
if node_dequeued.right:
q.put(node_dequeued.right)
def level_order_actual(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> level_order_actual(root)
1,
2,3,
4,5,6,7,
"""
if not isinstance(node, TreeNode) or not node:
return
q: queue.Queue = queue.Queue()
q.put(node)
while not q.empty():
list = []
while not q.empty():
node_dequeued = q.get()
print(node_dequeued.data, end=",")
if node_dequeued.left:
list.append(node_dequeued.left)
if node_dequeued.right:
list.append(node_dequeued.right)
print()
for node in list:
q.put(node)
# iteration version
def pre_order_iter(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> pre_order_iter(root)
1,2,4,5,3,6,7,
"""
if not isinstance(node, TreeNode) or not node:
return
stack: list[TreeNode] = []
n = node
while n or stack:
while n: # start from root node, find its left child
print(n.data, end=",")
stack.append(n)
n = n.left
# end of while means current node doesn't have left child
n = stack.pop()
# start to traverse its right child
n = n.right
def in_order_iter(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> in_order_iter(root)
4,2,5,1,6,3,7,
"""
if not isinstance(node, TreeNode) or not node:
return
stack: list[TreeNode] = []
n = node
while n or stack:
while n:
stack.append(n)
n = n.left
n = stack.pop()
print(n.data, end=",")
n = n.right
def post_order_iter(node: TreeNode) -> None:
"""
>>> root = TreeNode(1)
>>> tree_node2 = TreeNode(2)
>>> tree_node3 = TreeNode(3)
>>> tree_node4 = TreeNode(4)
>>> tree_node5 = TreeNode(5)
>>> tree_node6 = TreeNode(6)
>>> tree_node7 = TreeNode(7)
>>> root.left, root.right = tree_node2, tree_node3
>>> tree_node2.left, tree_node2.right = tree_node4 , tree_node5
>>> tree_node3.left, tree_node3.right = tree_node6 , tree_node7
>>> post_order_iter(root)
4,5,2,6,7,3,1,
"""
if not isinstance(node, TreeNode) or not node:
return
stack1, stack2 = [], []
n = node
stack1.append(n)
while stack1: # to find the reversed order of post order, store it in stack2
n = stack1.pop()
if n.left:
stack1.append(n.left)
if n.right:
stack1.append(n.right)
stack2.append(n)
while stack2: # pop up from stack2 will be the post order
print(stack2.pop().data, end=",")
def prompt(s: str = "", width=50, char="*") -> str:
if not s:
return "\n" + width * char
left, extra = divmod(width - len(s) - 2, 2)
return f"{left * char} {s} {(left + extra) * char}"
if __name__ == "__main__":
import doctest
doctest.testmod()
print(prompt("Binary Tree Traversals"))
node = build_tree()
print(prompt("Pre Order Traversal"))
pre_order(node)
print(prompt() + "\n")
print(prompt("In Order Traversal"))
in_order(node)
print(prompt() + "\n")
print(prompt("Post Order Traversal"))
post_order(node)
print(prompt() + "\n")
print(prompt("Level Order Traversal"))
level_order(node)
print(prompt() + "\n")
print(prompt("Actual Level Order Traversal"))
level_order_actual(node)
print("*" * 50 + "\n")
print(prompt("Pre Order Traversal - Iteration Version"))
pre_order_iter(node)
print(prompt() + "\n")
print(prompt("In Order Traversal - Iteration Version"))
in_order_iter(node)
print(prompt() + "\n")
print(prompt("Post Order Traversal - Iteration Version"))
post_order_iter(node)
print(prompt())
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Audio Filter
Audio filters work on the frequency of an audio signal to attenuate unwanted frequency and amplify wanted ones.
They are used within anything related to sound, whether it is radio communication or a hi-fi system.
* <https://www.masteringbox.com/filter-types/>
* <http://ethanwiner.com/filters.html>
* <https://en.wikipedia.org/wiki/Audio_filter>
* <https://en.wikipedia.org/wiki/Electronic_filter>
| # Audio Filter
Audio filters work on the frequency of an audio signal to attenuate unwanted frequency and amplify wanted ones.
They are used within anything related to sound, whether it is radio communication or a hi-fi system.
* <https://www.masteringbox.com/filter-types/>
* <http://ethanwiner.com/filters.html>
* <https://en.wikipedia.org/wiki/Audio_filter>
* <https://en.wikipedia.org/wiki/Electronic_filter>
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| MIT License
Copyright (c) 2016-2022 TheAlgorithms and contributors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
| MIT License
Copyright (c) 2016-2022 TheAlgorithms and contributors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Gaussian Naive Bayes Example
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import plot_confusion_matrix
from sklearn.model_selection import train_test_split
from sklearn.naive_bayes import GaussianNB
def main():
"""
Gaussian Naive Bayes Example using sklearn function.
Iris type dataset is used to demonstrate algorithm.
"""
# Load Iris dataset
iris = load_iris()
# Split dataset into train and test data
x = iris["data"] # features
y = iris["target"]
x_train, x_test, y_train, y_test = train_test_split(
x, y, test_size=0.3, random_state=1
)
# Gaussian Naive Bayes
nb_model = GaussianNB()
nb_model.fit(x_train, y_train)
# Display Confusion Matrix
plot_confusion_matrix(
nb_model,
x_test,
y_test,
display_labels=iris["target_names"],
cmap="Blues",
normalize="true",
)
plt.title("Normalized Confusion Matrix - IRIS Dataset")
plt.show()
if __name__ == "__main__":
main()
| # Gaussian Naive Bayes Example
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import plot_confusion_matrix
from sklearn.model_selection import train_test_split
from sklearn.naive_bayes import GaussianNB
def main():
"""
Gaussian Naive Bayes Example using sklearn function.
Iris type dataset is used to demonstrate algorithm.
"""
# Load Iris dataset
iris = load_iris()
# Split dataset into train and test data
x = iris["data"] # features
y = iris["target"]
x_train, x_test, y_train, y_test = train_test_split(
x, y, test_size=0.3, random_state=1
)
# Gaussian Naive Bayes
nb_model = GaussianNB()
nb_model.fit(x_train, y_train)
# Display Confusion Matrix
plot_confusion_matrix(
nb_model,
x_test,
y_test,
display_labels=iris["target_names"],
cmap="Blues",
normalize="true",
)
plt.title("Normalized Confusion Matrix - IRIS Dataset")
plt.show()
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| MMMMDCLXXII
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XXXXVIIII | -1 |
TheAlgorithms/Python | 7,339 | Follow Flake8 pep3101 and remove modulo formatting | ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T20:16:16Z" | "2022-10-16T20:50:11Z" | 7f6e0b656f6362e452b11d06acde50b8b81cb31a | f15cc2f01c2a4124ff6dc0843c728a546f9d9f79 | Follow Flake8 pep3101 and remove modulo formatting. ### Describe your change:
Follow Flake8 pep3101 and remove modulo formatting (replace with f-strings)
For example
```py
"Hello %s" % name
```
goes to
```py
f"Hello {name}"
```
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Three distinct points are plotted at random on a Cartesian plane,
for which -1000 ≤ x, y ≤ 1000, such that a triangle is formed.
Consider the following two triangles:
A(-340,495), B(-153,-910), C(835,-947)
X(-175,41), Y(-421,-714), Z(574,-645)
It can be verified that triangle ABC contains the origin, whereas
triangle XYZ does not.
Using triangles.txt (right click and 'Save Link/Target As...'), a 27K text
file containing the coordinates of one thousand "random" triangles, find
the number of triangles for which the interior contains the origin.
NOTE: The first two examples in the file represent the triangles in the
example given above.
"""
from __future__ import annotations
from pathlib import Path
def vector_product(point1: tuple[int, int], point2: tuple[int, int]) -> int:
"""
Return the 2-d vector product of two vectors.
>>> vector_product((1, 2), (-5, 0))
10
>>> vector_product((3, 1), (6, 10))
24
"""
return point1[0] * point2[1] - point1[1] * point2[0]
def contains_origin(x1: int, y1: int, x2: int, y2: int, x3: int, y3: int) -> bool:
"""
Check if the triangle given by the points A(x1, y1), B(x2, y2), C(x3, y3)
contains the origin.
>>> contains_origin(-340, 495, -153, -910, 835, -947)
True
>>> contains_origin(-175, 41, -421, -714, 574, -645)
False
"""
point_a: tuple[int, int] = (x1, y1)
point_a_to_b: tuple[int, int] = (x2 - x1, y2 - y1)
point_a_to_c: tuple[int, int] = (x3 - x1, y3 - y1)
a: float = -vector_product(point_a, point_a_to_b) / vector_product(
point_a_to_c, point_a_to_b
)
b: float = +vector_product(point_a, point_a_to_c) / vector_product(
point_a_to_c, point_a_to_b
)
return a > 0 and b > 0 and a + b < 1
def solution(filename: str = "p102_triangles.txt") -> int:
"""
Find the number of triangles whose interior contains the origin.
>>> solution("test_triangles.txt")
1
"""
data: str = Path(__file__).parent.joinpath(filename).read_text(encoding="utf-8")
triangles: list[list[int]] = []
for line in data.strip().split("\n"):
triangles.append([int(number) for number in line.split(",")])
ret: int = 0
triangle: list[int]
for triangle in triangles:
ret += contains_origin(*triangle)
return ret
if __name__ == "__main__":
print(f"{solution() = }")
| """
Three distinct points are plotted at random on a Cartesian plane,
for which -1000 ≤ x, y ≤ 1000, such that a triangle is formed.
Consider the following two triangles:
A(-340,495), B(-153,-910), C(835,-947)
X(-175,41), Y(-421,-714), Z(574,-645)
It can be verified that triangle ABC contains the origin, whereas
triangle XYZ does not.
Using triangles.txt (right click and 'Save Link/Target As...'), a 27K text
file containing the coordinates of one thousand "random" triangles, find
the number of triangles for which the interior contains the origin.
NOTE: The first two examples in the file represent the triangles in the
example given above.
"""
from __future__ import annotations
from pathlib import Path
def vector_product(point1: tuple[int, int], point2: tuple[int, int]) -> int:
"""
Return the 2-d vector product of two vectors.
>>> vector_product((1, 2), (-5, 0))
10
>>> vector_product((3, 1), (6, 10))
24
"""
return point1[0] * point2[1] - point1[1] * point2[0]
def contains_origin(x1: int, y1: int, x2: int, y2: int, x3: int, y3: int) -> bool:
"""
Check if the triangle given by the points A(x1, y1), B(x2, y2), C(x3, y3)
contains the origin.
>>> contains_origin(-340, 495, -153, -910, 835, -947)
True
>>> contains_origin(-175, 41, -421, -714, 574, -645)
False
"""
point_a: tuple[int, int] = (x1, y1)
point_a_to_b: tuple[int, int] = (x2 - x1, y2 - y1)
point_a_to_c: tuple[int, int] = (x3 - x1, y3 - y1)
a: float = -vector_product(point_a, point_a_to_b) / vector_product(
point_a_to_c, point_a_to_b
)
b: float = +vector_product(point_a, point_a_to_c) / vector_product(
point_a_to_c, point_a_to_b
)
return a > 0 and b > 0 and a + b < 1
def solution(filename: str = "p102_triangles.txt") -> int:
"""
Find the number of triangles whose interior contains the origin.
>>> solution("test_triangles.txt")
1
"""
data: str = Path(__file__).parent.joinpath(filename).read_text(encoding="utf-8")
triangles: list[list[int]] = []
for line in data.strip().split("\n"):
triangles.append([int(number) for number in line.split(",")])
ret: int = 0
triangle: list[int]
for triangle in triangles:
ret += contains_origin(*triangle)
return ret
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.3.0
hooks:
- id: check-executables-have-shebangs
- id: check-yaml
- id: end-of-file-fixer
types: [python]
- id: trailing-whitespace
exclude: |
(?x)^(
data_structures/heap/binomial_heap.py
)$
- id: requirements-txt-fixer
- repo: https://github.com/psf/black
rev: 22.10.0
hooks:
- id: black
- repo: https://github.com/PyCQA/isort
rev: 5.10.1
hooks:
- id: isort
args:
- --profile=black
- repo: https://github.com/asottile/pyupgrade
rev: v3.0.0
hooks:
- id: pyupgrade
args:
- --py310-plus
- repo: https://github.com/PyCQA/flake8
rev: 5.0.4
hooks:
- id: flake8 # See .flake8 for args
additional_dependencies:
- flake8-bugbear
- flake8-builtins
- flake8-comprehensions
- pep8-naming
- repo: https://github.com/pre-commit/mirrors-mypy
rev: v0.982
hooks:
- id: mypy
args:
- --ignore-missing-imports
- --install-types # See mirrors-mypy README.md
- --non-interactive
additional_dependencies: [types-requests]
- repo: https://github.com/codespell-project/codespell
rev: v2.2.1
hooks:
- id: codespell
args:
- --ignore-words-list=ans,crate,damon,fo,followings,hist,iff,mater,secant,som,sur,tim,zar
- --skip="./.*,./strings/dictionary.txt,./strings/words.txt,./project_euler/problem_022/p022_names.txt"
exclude: |
(?x)^(
strings/dictionary.txt |
strings/words.txt |
project_euler/problem_022/p022_names.txt
)$
- repo: local
hooks:
- id: validate-filenames
name: Validate filenames
entry: ./scripts/validate_filenames.py
language: script
pass_filenames: false
| repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.3.0
hooks:
- id: check-executables-have-shebangs
- id: check-yaml
- id: end-of-file-fixer
types: [python]
- id: trailing-whitespace
exclude: |
(?x)^(
data_structures/heap/binomial_heap.py
)$
- id: requirements-txt-fixer
- repo: https://github.com/psf/black
rev: 22.10.0
hooks:
- id: black
- repo: https://github.com/PyCQA/isort
rev: 5.10.1
hooks:
- id: isort
args:
- --profile=black
- repo: https://github.com/asottile/pyupgrade
rev: v3.0.0
hooks:
- id: pyupgrade
args:
- --py310-plus
- repo: https://github.com/PyCQA/flake8
rev: 5.0.4
hooks:
- id: flake8 # See .flake8 for args
additional_dependencies:
- flake8-bugbear
- flake8-builtins
- flake8-broken-line
- flake8-comprehensions
- pep8-naming
- repo: https://github.com/pre-commit/mirrors-mypy
rev: v0.982
hooks:
- id: mypy
args:
- --ignore-missing-imports
- --install-types # See mirrors-mypy README.md
- --non-interactive
additional_dependencies: [types-requests]
- repo: https://github.com/codespell-project/codespell
rev: v2.2.1
hooks:
- id: codespell
args:
- --ignore-words-list=ans,crate,damon,fo,followings,hist,iff,mater,secant,som,sur,tim,zar
- --skip="./.*,./strings/dictionary.txt,./strings/words.txt,./project_euler/problem_022/p022_names.txt"
exclude: |
(?x)^(
strings/dictionary.txt |
strings/words.txt |
project_euler/problem_022/p022_names.txt
)$
- repo: local
hooks:
- id: validate-filenames
name: Validate filenames
entry: ./scripts/validate_filenames.py
language: script
pass_filenames: false
| 1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 8: https://projecteuler.net/problem=8
Largest product in a series
The four adjacent digits in the 1000-digit number that have the greatest
product are 9 × 9 × 8 × 9 = 5832.
73167176531330624919225119674426574742355349194934
96983520312774506326239578318016984801869478851843
85861560789112949495459501737958331952853208805511
12540698747158523863050715693290963295227443043557
66896648950445244523161731856403098711121722383113
62229893423380308135336276614282806444486645238749
30358907296290491560440772390713810515859307960866
70172427121883998797908792274921901699720888093776
65727333001053367881220235421809751254540594752243
52584907711670556013604839586446706324415722155397
53697817977846174064955149290862569321978468622482
83972241375657056057490261407972968652414535100474
82166370484403199890008895243450658541227588666881
16427171479924442928230863465674813919123162824586
17866458359124566529476545682848912883142607690042
24219022671055626321111109370544217506941658960408
07198403850962455444362981230987879927244284909188
84580156166097919133875499200524063689912560717606
05886116467109405077541002256983155200055935729725
71636269561882670428252483600823257530420752963450
Find the thirteen adjacent digits in the 1000-digit number that have the
greatest product. What is the value of this product?
"""
import sys
N = """73167176531330624919225119674426574742355349194934\
96983520312774506326239578318016984801869478851843\
85861560789112949495459501737958331952853208805511\
12540698747158523863050715693290963295227443043557\
66896648950445244523161731856403098711121722383113\
62229893423380308135336276614282806444486645238749\
30358907296290491560440772390713810515859307960866\
70172427121883998797908792274921901699720888093776\
65727333001053367881220235421809751254540594752243\
52584907711670556013604839586446706324415722155397\
53697817977846174064955149290862569321978468622482\
83972241375657056057490261407972968652414535100474\
82166370484403199890008895243450658541227588666881\
16427171479924442928230863465674813919123162824586\
17866458359124566529476545682848912883142607690042\
24219022671055626321111109370544217506941658960408\
07198403850962455444362981230987879927244284909188\
84580156166097919133875499200524063689912560717606\
05886116467109405077541002256983155200055935729725\
71636269561882670428252483600823257530420752963450"""
def solution(n: str = N) -> int:
"""
Find the thirteen adjacent digits in the 1000-digit number n that have
the greatest product and returns it.
>>> solution("13978431290823798458352374")
609638400
>>> solution("13978431295823798458352374")
2612736000
>>> solution("1397843129582379841238352374")
209018880
"""
largest_product = -sys.maxsize - 1
for i in range(len(n) - 12):
product = 1
for j in range(13):
product *= int(n[i + j])
if product > largest_product:
largest_product = product
return largest_product
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 8: https://projecteuler.net/problem=8
Largest product in a series
The four adjacent digits in the 1000-digit number that have the greatest
product are 9 × 9 × 8 × 9 = 5832.
73167176531330624919225119674426574742355349194934
96983520312774506326239578318016984801869478851843
85861560789112949495459501737958331952853208805511
12540698747158523863050715693290963295227443043557
66896648950445244523161731856403098711121722383113
62229893423380308135336276614282806444486645238749
30358907296290491560440772390713810515859307960866
70172427121883998797908792274921901699720888093776
65727333001053367881220235421809751254540594752243
52584907711670556013604839586446706324415722155397
53697817977846174064955149290862569321978468622482
83972241375657056057490261407972968652414535100474
82166370484403199890008895243450658541227588666881
16427171479924442928230863465674813919123162824586
17866458359124566529476545682848912883142607690042
24219022671055626321111109370544217506941658960408
07198403850962455444362981230987879927244284909188
84580156166097919133875499200524063689912560717606
05886116467109405077541002256983155200055935729725
71636269561882670428252483600823257530420752963450
Find the thirteen adjacent digits in the 1000-digit number that have the
greatest product. What is the value of this product?
"""
import sys
N = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445244523161731856403098711121722383113"
"62229893423380308135336276614282806444486645238749"
"30358907296290491560440772390713810515859307960866"
"70172427121883998797908792274921901699720888093776"
"65727333001053367881220235421809751254540594752243"
"52584907711670556013604839586446706324415722155397"
"53697817977846174064955149290862569321978468622482"
"83972241375657056057490261407972968652414535100474"
"82166370484403199890008895243450658541227588666881"
"16427171479924442928230863465674813919123162824586"
"17866458359124566529476545682848912883142607690042"
"24219022671055626321111109370544217506941658960408"
"07198403850962455444362981230987879927244284909188"
"84580156166097919133875499200524063689912560717606"
"05886116467109405077541002256983155200055935729725"
"71636269561882670428252483600823257530420752963450"
)
def solution(n: str = N) -> int:
"""
Find the thirteen adjacent digits in the 1000-digit number n that have
the greatest product and returns it.
>>> solution("13978431290823798458352374")
609638400
>>> solution("13978431295823798458352374")
2612736000
>>> solution("1397843129582379841238352374")
209018880
"""
largest_product = -sys.maxsize - 1
for i in range(len(n) - 12):
product = 1
for j in range(13):
product *= int(n[i + j])
if product > largest_product:
largest_product = product
return largest_product
if __name__ == "__main__":
print(f"{solution() = }")
| 1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 8: https://projecteuler.net/problem=8
Largest product in a series
The four adjacent digits in the 1000-digit number that have the greatest
product are 9 × 9 × 8 × 9 = 5832.
73167176531330624919225119674426574742355349194934
96983520312774506326239578318016984801869478851843
85861560789112949495459501737958331952853208805511
12540698747158523863050715693290963295227443043557
66896648950445244523161731856403098711121722383113
62229893423380308135336276614282806444486645238749
30358907296290491560440772390713810515859307960866
70172427121883998797908792274921901699720888093776
65727333001053367881220235421809751254540594752243
52584907711670556013604839586446706324415722155397
53697817977846174064955149290862569321978468622482
83972241375657056057490261407972968652414535100474
82166370484403199890008895243450658541227588666881
16427171479924442928230863465674813919123162824586
17866458359124566529476545682848912883142607690042
24219022671055626321111109370544217506941658960408
07198403850962455444362981230987879927244284909188
84580156166097919133875499200524063689912560717606
05886116467109405077541002256983155200055935729725
71636269561882670428252483600823257530420752963450
Find the thirteen adjacent digits in the 1000-digit number that have the
greatest product. What is the value of this product?
"""
import sys
N = """73167176531330624919225119674426574742355349194934\
96983520312774506326239578318016984801869478851843\
85861560789112949495459501737958331952853208805511\
12540698747158523863050715693290963295227443043557\
66896648950445244523161731856403098711121722383113\
62229893423380308135336276614282806444486645238749\
30358907296290491560440772390713810515859307960866\
70172427121883998797908792274921901699720888093776\
65727333001053367881220235421809751254540594752243\
52584907711670556013604839586446706324415722155397\
53697817977846174064955149290862569321978468622482\
83972241375657056057490261407972968652414535100474\
82166370484403199890008895243450658541227588666881\
16427171479924442928230863465674813919123162824586\
17866458359124566529476545682848912883142607690042\
24219022671055626321111109370544217506941658960408\
07198403850962455444362981230987879927244284909188\
84580156166097919133875499200524063689912560717606\
05886116467109405077541002256983155200055935729725\
71636269561882670428252483600823257530420752963450"""
def str_eval(s: str) -> int:
"""
Returns product of digits in given string n
>>> str_eval("987654321")
362880
>>> str_eval("22222222")
256
"""
product = 1
for digit in s:
product *= int(digit)
return product
def solution(n: str = N) -> int:
"""
Find the thirteen adjacent digits in the 1000-digit number n that have
the greatest product and returns it.
"""
largest_product = -sys.maxsize - 1
substr = n[:13]
cur_index = 13
while cur_index < len(n) - 13:
if int(n[cur_index]) >= int(substr[0]):
substr = substr[1:] + n[cur_index]
cur_index += 1
else:
largest_product = max(largest_product, str_eval(substr))
substr = n[cur_index : cur_index + 13]
cur_index += 13
return largest_product
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 8: https://projecteuler.net/problem=8
Largest product in a series
The four adjacent digits in the 1000-digit number that have the greatest
product are 9 × 9 × 8 × 9 = 5832.
73167176531330624919225119674426574742355349194934
96983520312774506326239578318016984801869478851843
85861560789112949495459501737958331952853208805511
12540698747158523863050715693290963295227443043557
66896648950445244523161731856403098711121722383113
62229893423380308135336276614282806444486645238749
30358907296290491560440772390713810515859307960866
70172427121883998797908792274921901699720888093776
65727333001053367881220235421809751254540594752243
52584907711670556013604839586446706324415722155397
53697817977846174064955149290862569321978468622482
83972241375657056057490261407972968652414535100474
82166370484403199890008895243450658541227588666881
16427171479924442928230863465674813919123162824586
17866458359124566529476545682848912883142607690042
24219022671055626321111109370544217506941658960408
07198403850962455444362981230987879927244284909188
84580156166097919133875499200524063689912560717606
05886116467109405077541002256983155200055935729725
71636269561882670428252483600823257530420752963450
Find the thirteen adjacent digits in the 1000-digit number that have the
greatest product. What is the value of this product?
"""
import sys
N = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445244523161731856403098711121722383113"
"62229893423380308135336276614282806444486645238749"
"30358907296290491560440772390713810515859307960866"
"70172427121883998797908792274921901699720888093776"
"65727333001053367881220235421809751254540594752243"
"52584907711670556013604839586446706324415722155397"
"53697817977846174064955149290862569321978468622482"
"83972241375657056057490261407972968652414535100474"
"82166370484403199890008895243450658541227588666881"
"16427171479924442928230863465674813919123162824586"
"17866458359124566529476545682848912883142607690042"
"24219022671055626321111109370544217506941658960408"
"07198403850962455444362981230987879927244284909188"
"84580156166097919133875499200524063689912560717606"
"05886116467109405077541002256983155200055935729725"
"71636269561882670428252483600823257530420752963450"
)
def str_eval(s: str) -> int:
"""
Returns product of digits in given string n
>>> str_eval("987654321")
362880
>>> str_eval("22222222")
256
"""
product = 1
for digit in s:
product *= int(digit)
return product
def solution(n: str = N) -> int:
"""
Find the thirteen adjacent digits in the 1000-digit number n that have
the greatest product and returns it.
"""
largest_product = -sys.maxsize - 1
substr = n[:13]
cur_index = 13
while cur_index < len(n) - 13:
if int(n[cur_index]) >= int(substr[0]):
substr = substr[1:] + n[cur_index]
cur_index += 1
else:
largest_product = max(largest_product, str_eval(substr))
substr = n[cur_index : cur_index + 13]
cur_index += 13
return largest_product
if __name__ == "__main__":
print(f"{solution() = }")
| 1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Information on binary shifts:
# https://docs.python.org/3/library/stdtypes.html#bitwise-operations-on-integer-types
# https://www.interviewcake.com/concept/java/bit-shift
def logical_left_shift(number: int, shift_amount: int) -> str:
"""
Take in 2 positive integers.
'number' is the integer to be logically left shifted 'shift_amount' times.
i.e. (number << shift_amount)
Return the shifted binary representation.
>>> logical_left_shift(0, 1)
'0b00'
>>> logical_left_shift(1, 1)
'0b10'
>>> logical_left_shift(1, 5)
'0b100000'
>>> logical_left_shift(17, 2)
'0b1000100'
>>> logical_left_shift(1983, 4)
'0b111101111110000'
>>> logical_left_shift(1, -1)
Traceback (most recent call last):
...
ValueError: both inputs must be positive integers
"""
if number < 0 or shift_amount < 0:
raise ValueError("both inputs must be positive integers")
binary_number = str(bin(number))
binary_number += "0" * shift_amount
return binary_number
def logical_right_shift(number: int, shift_amount: int) -> str:
"""
Take in positive 2 integers.
'number' is the integer to be logically right shifted 'shift_amount' times.
i.e. (number >>> shift_amount)
Return the shifted binary representation.
>>> logical_right_shift(0, 1)
'0b0'
>>> logical_right_shift(1, 1)
'0b0'
>>> logical_right_shift(1, 5)
'0b0'
>>> logical_right_shift(17, 2)
'0b100'
>>> logical_right_shift(1983, 4)
'0b1111011'
>>> logical_right_shift(1, -1)
Traceback (most recent call last):
...
ValueError: both inputs must be positive integers
"""
if number < 0 or shift_amount < 0:
raise ValueError("both inputs must be positive integers")
binary_number = str(bin(number))[2:]
if shift_amount >= len(binary_number):
return "0b0"
shifted_binary_number = binary_number[: len(binary_number) - shift_amount]
return "0b" + shifted_binary_number
def arithmetic_right_shift(number: int, shift_amount: int) -> str:
"""
Take in 2 integers.
'number' is the integer to be arithmetically right shifted 'shift_amount' times.
i.e. (number >> shift_amount)
Return the shifted binary representation.
>>> arithmetic_right_shift(0, 1)
'0b00'
>>> arithmetic_right_shift(1, 1)
'0b00'
>>> arithmetic_right_shift(-1, 1)
'0b11'
>>> arithmetic_right_shift(17, 2)
'0b000100'
>>> arithmetic_right_shift(-17, 2)
'0b111011'
>>> arithmetic_right_shift(-1983, 4)
'0b111110000100'
"""
if number >= 0: # Get binary representation of positive number
binary_number = "0" + str(bin(number)).strip("-")[2:]
else: # Get binary (2's complement) representation of negative number
binary_number_length = len(bin(number)[3:]) # Find 2's complement of number
binary_number = bin(abs(number) - (1 << binary_number_length))[3:]
binary_number = (
"1" + "0" * (binary_number_length - len(binary_number)) + binary_number
)
if shift_amount >= len(binary_number):
return "0b" + binary_number[0] * len(binary_number)
return (
"0b"
+ binary_number[0] * shift_amount
+ binary_number[: len(binary_number) - shift_amount]
)
if __name__ == "__main__":
import doctest
doctest.testmod()
| # Information on binary shifts:
# https://docs.python.org/3/library/stdtypes.html#bitwise-operations-on-integer-types
# https://www.interviewcake.com/concept/java/bit-shift
def logical_left_shift(number: int, shift_amount: int) -> str:
"""
Take in 2 positive integers.
'number' is the integer to be logically left shifted 'shift_amount' times.
i.e. (number << shift_amount)
Return the shifted binary representation.
>>> logical_left_shift(0, 1)
'0b00'
>>> logical_left_shift(1, 1)
'0b10'
>>> logical_left_shift(1, 5)
'0b100000'
>>> logical_left_shift(17, 2)
'0b1000100'
>>> logical_left_shift(1983, 4)
'0b111101111110000'
>>> logical_left_shift(1, -1)
Traceback (most recent call last):
...
ValueError: both inputs must be positive integers
"""
if number < 0 or shift_amount < 0:
raise ValueError("both inputs must be positive integers")
binary_number = str(bin(number))
binary_number += "0" * shift_amount
return binary_number
def logical_right_shift(number: int, shift_amount: int) -> str:
"""
Take in positive 2 integers.
'number' is the integer to be logically right shifted 'shift_amount' times.
i.e. (number >>> shift_amount)
Return the shifted binary representation.
>>> logical_right_shift(0, 1)
'0b0'
>>> logical_right_shift(1, 1)
'0b0'
>>> logical_right_shift(1, 5)
'0b0'
>>> logical_right_shift(17, 2)
'0b100'
>>> logical_right_shift(1983, 4)
'0b1111011'
>>> logical_right_shift(1, -1)
Traceback (most recent call last):
...
ValueError: both inputs must be positive integers
"""
if number < 0 or shift_amount < 0:
raise ValueError("both inputs must be positive integers")
binary_number = str(bin(number))[2:]
if shift_amount >= len(binary_number):
return "0b0"
shifted_binary_number = binary_number[: len(binary_number) - shift_amount]
return "0b" + shifted_binary_number
def arithmetic_right_shift(number: int, shift_amount: int) -> str:
"""
Take in 2 integers.
'number' is the integer to be arithmetically right shifted 'shift_amount' times.
i.e. (number >> shift_amount)
Return the shifted binary representation.
>>> arithmetic_right_shift(0, 1)
'0b00'
>>> arithmetic_right_shift(1, 1)
'0b00'
>>> arithmetic_right_shift(-1, 1)
'0b11'
>>> arithmetic_right_shift(17, 2)
'0b000100'
>>> arithmetic_right_shift(-17, 2)
'0b111011'
>>> arithmetic_right_shift(-1983, 4)
'0b111110000100'
"""
if number >= 0: # Get binary representation of positive number
binary_number = "0" + str(bin(number)).strip("-")[2:]
else: # Get binary (2's complement) representation of negative number
binary_number_length = len(bin(number)[3:]) # Find 2's complement of number
binary_number = bin(abs(number) - (1 << binary_number_length))[3:]
binary_number = (
"1" + "0" * (binary_number_length - len(binary_number)) + binary_number
)
if shift_amount >= len(binary_number):
return "0b" + binary_number[0] * len(binary_number)
return (
"0b"
+ binary_number[0] * shift_amount
+ binary_number[: len(binary_number) - shift_amount]
)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def multiplicative_persistence(num: int) -> int:
"""
Return the persistence of a given number.
https://en.wikipedia.org/wiki/Persistence_of_a_number
>>> multiplicative_persistence(217)
2
>>> multiplicative_persistence(-1)
Traceback (most recent call last):
...
ValueError: multiplicative_persistence() does not accept negative values
>>> multiplicative_persistence("long number")
Traceback (most recent call last):
...
ValueError: multiplicative_persistence() only accepts integral values
"""
if not isinstance(num, int):
raise ValueError("multiplicative_persistence() only accepts integral values")
if num < 0:
raise ValueError("multiplicative_persistence() does not accept negative values")
steps = 0
num_string = str(num)
while len(num_string) != 1:
numbers = [int(i) for i in num_string]
total = 1
for i in range(0, len(numbers)):
total *= numbers[i]
num_string = str(total)
steps += 1
return steps
def additive_persistence(num: int) -> int:
"""
Return the persistence of a given number.
https://en.wikipedia.org/wiki/Persistence_of_a_number
>>> additive_persistence(199)
3
>>> additive_persistence(-1)
Traceback (most recent call last):
...
ValueError: additive_persistence() does not accept negative values
>>> additive_persistence("long number")
Traceback (most recent call last):
...
ValueError: additive_persistence() only accepts integral values
"""
if not isinstance(num, int):
raise ValueError("additive_persistence() only accepts integral values")
if num < 0:
raise ValueError("additive_persistence() does not accept negative values")
steps = 0
num_string = str(num)
while len(num_string) != 1:
numbers = [int(i) for i in num_string]
total = 0
for i in range(0, len(numbers)):
total += numbers[i]
num_string = str(total)
steps += 1
return steps
if __name__ == "__main__":
import doctest
doctest.testmod()
| def multiplicative_persistence(num: int) -> int:
"""
Return the persistence of a given number.
https://en.wikipedia.org/wiki/Persistence_of_a_number
>>> multiplicative_persistence(217)
2
>>> multiplicative_persistence(-1)
Traceback (most recent call last):
...
ValueError: multiplicative_persistence() does not accept negative values
>>> multiplicative_persistence("long number")
Traceback (most recent call last):
...
ValueError: multiplicative_persistence() only accepts integral values
"""
if not isinstance(num, int):
raise ValueError("multiplicative_persistence() only accepts integral values")
if num < 0:
raise ValueError("multiplicative_persistence() does not accept negative values")
steps = 0
num_string = str(num)
while len(num_string) != 1:
numbers = [int(i) for i in num_string]
total = 1
for i in range(0, len(numbers)):
total *= numbers[i]
num_string = str(total)
steps += 1
return steps
def additive_persistence(num: int) -> int:
"""
Return the persistence of a given number.
https://en.wikipedia.org/wiki/Persistence_of_a_number
>>> additive_persistence(199)
3
>>> additive_persistence(-1)
Traceback (most recent call last):
...
ValueError: additive_persistence() does not accept negative values
>>> additive_persistence("long number")
Traceback (most recent call last):
...
ValueError: additive_persistence() only accepts integral values
"""
if not isinstance(num, int):
raise ValueError("additive_persistence() only accepts integral values")
if num < 0:
raise ValueError("additive_persistence() does not accept negative values")
steps = 0
num_string = str(num)
while len(num_string) != 1:
numbers = [int(i) for i in num_string]
total = 0
for i in range(0, len(numbers)):
total += numbers[i]
num_string = str(total)
steps += 1
return steps
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from json import loads
from pathlib import Path
import numpy as np
from yulewalker import yulewalk
from audio_filters.butterworth_filter import make_highpass
from audio_filters.iir_filter import IIRFilter
data = loads((Path(__file__).resolve().parent / "loudness_curve.json").read_text())
class EqualLoudnessFilter:
r"""
An equal-loudness filter which compensates for the human ear's non-linear response
to sound.
This filter corrects this by cascading a yulewalk filter and a butterworth filter.
Designed for use with samplerate of 44.1kHz and above. If you're using a lower
samplerate, use with caution.
Code based on matlab implementation at https://bit.ly/3eqh2HU
(url shortened for flake8)
Target curve: https://i.imgur.com/3g2VfaM.png
Yulewalk response: https://i.imgur.com/J9LnJ4C.png
Butterworth and overall response: https://i.imgur.com/3g2VfaM.png
Images and original matlab implementation by David Robinson, 2001
"""
def __init__(self, samplerate: int = 44100) -> None:
self.yulewalk_filter = IIRFilter(10)
self.butterworth_filter = make_highpass(150, samplerate)
# pad the data to nyquist
curve_freqs = np.array(data["frequencies"] + [max(20000.0, samplerate / 2)])
curve_gains = np.array(data["gains"] + [140])
# Convert to angular frequency
freqs_normalized = curve_freqs / samplerate * 2
# Invert the curve and normalize to 0dB
gains_normalized = np.power(10, (np.min(curve_gains) - curve_gains) / 20)
# Scipy's `yulewalk` function is a stub, so we're using the
# `yulewalker` library instead.
# This function computes the coefficients using a least-squares
# fit to the specified curve.
ya, yb = yulewalk(10, freqs_normalized, gains_normalized)
self.yulewalk_filter.set_coefficients(ya, yb)
def process(self, sample: float) -> float:
"""
Process a single sample through both filters
>>> filt = EqualLoudnessFilter()
>>> filt.process(0.0)
0.0
"""
tmp = self.yulewalk_filter.process(sample)
return self.butterworth_filter.process(tmp)
| from json import loads
from pathlib import Path
import numpy as np
from yulewalker import yulewalk
from audio_filters.butterworth_filter import make_highpass
from audio_filters.iir_filter import IIRFilter
data = loads((Path(__file__).resolve().parent / "loudness_curve.json").read_text())
class EqualLoudnessFilter:
r"""
An equal-loudness filter which compensates for the human ear's non-linear response
to sound.
This filter corrects this by cascading a yulewalk filter and a butterworth filter.
Designed for use with samplerate of 44.1kHz and above. If you're using a lower
samplerate, use with caution.
Code based on matlab implementation at https://bit.ly/3eqh2HU
(url shortened for flake8)
Target curve: https://i.imgur.com/3g2VfaM.png
Yulewalk response: https://i.imgur.com/J9LnJ4C.png
Butterworth and overall response: https://i.imgur.com/3g2VfaM.png
Images and original matlab implementation by David Robinson, 2001
"""
def __init__(self, samplerate: int = 44100) -> None:
self.yulewalk_filter = IIRFilter(10)
self.butterworth_filter = make_highpass(150, samplerate)
# pad the data to nyquist
curve_freqs = np.array(data["frequencies"] + [max(20000.0, samplerate / 2)])
curve_gains = np.array(data["gains"] + [140])
# Convert to angular frequency
freqs_normalized = curve_freqs / samplerate * 2
# Invert the curve and normalize to 0dB
gains_normalized = np.power(10, (np.min(curve_gains) - curve_gains) / 20)
# Scipy's `yulewalk` function is a stub, so we're using the
# `yulewalker` library instead.
# This function computes the coefficients using a least-squares
# fit to the specified curve.
ya, yb = yulewalk(10, freqs_normalized, gains_normalized)
self.yulewalk_filter.set_coefficients(ya, yb)
def process(self, sample: float) -> float:
"""
Process a single sample through both filters
>>> filt = EqualLoudnessFilter()
>>> filt.process(0.0)
0.0
"""
tmp = self.yulewalk_filter.process(sample)
return self.butterworth_filter.process(tmp)
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Youtube Explanation: https://www.youtube.com/watch?v=lBRtnuxg-gU
from __future__ import annotations
def minimum_cost_path(matrix: list[list[int]]) -> int:
"""
Find the minimum cost traced by all possible paths from top left to bottom right in
a given matrix
>>> minimum_cost_path([[2, 1], [3, 1], [4, 2]])
6
>>> minimum_cost_path([[2, 1, 4], [2, 1, 3], [3, 2, 1]])
7
"""
# preprocessing the first row
for i in range(1, len(matrix[0])):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
for i in range(1, len(matrix)):
matrix[i][0] += matrix[i - 1][0]
# updating the path cost for current position
for i in range(1, len(matrix)):
for j in range(1, len(matrix[0])):
matrix[i][j] += min(matrix[i - 1][j], matrix[i][j - 1])
return matrix[-1][-1]
if __name__ == "__main__":
import doctest
doctest.testmod()
| # Youtube Explanation: https://www.youtube.com/watch?v=lBRtnuxg-gU
from __future__ import annotations
def minimum_cost_path(matrix: list[list[int]]) -> int:
"""
Find the minimum cost traced by all possible paths from top left to bottom right in
a given matrix
>>> minimum_cost_path([[2, 1], [3, 1], [4, 2]])
6
>>> minimum_cost_path([[2, 1, 4], [2, 1, 3], [3, 2, 1]])
7
"""
# preprocessing the first row
for i in range(1, len(matrix[0])):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
for i in range(1, len(matrix)):
matrix[i][0] += matrix[i - 1][0]
# updating the path cost for current position
for i in range(1, len(matrix)):
for j in range(1, len(matrix[0])):
matrix[i][j] += min(matrix[i - 1][j], matrix[i][j - 1])
return matrix[-1][-1]
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Name scores
Problem 22
Using names.txt (right click and 'Save Link/Target As...'), a 46K text file
containing over five-thousand first names, begin by sorting it into
alphabetical order. Then working out the alphabetical value for each name,
multiply this value by its alphabetical position in the list to obtain a name
score.
For example, when the list is sorted into alphabetical order, COLIN, which is
worth 3 + 15 + 12 + 9 + 14 = 53, is the 938th name in the list. So, COLIN would
obtain a score of 938 × 53 = 49714.
What is the total of all the name scores in the file?
"""
import os
def solution():
"""Returns the total of all the name scores in the file.
>>> solution()
871198282
"""
total_sum = 0
temp_sum = 0
with open(os.path.dirname(__file__) + "/p022_names.txt") as file:
name = str(file.readlines()[0])
name = name.replace('"', "").split(",")
name.sort()
for i in range(len(name)):
for j in name[i]:
temp_sum += ord(j) - ord("A") + 1
total_sum += (i + 1) * temp_sum
temp_sum = 0
return total_sum
if __name__ == "__main__":
print(solution())
| """
Name scores
Problem 22
Using names.txt (right click and 'Save Link/Target As...'), a 46K text file
containing over five-thousand first names, begin by sorting it into
alphabetical order. Then working out the alphabetical value for each name,
multiply this value by its alphabetical position in the list to obtain a name
score.
For example, when the list is sorted into alphabetical order, COLIN, which is
worth 3 + 15 + 12 + 9 + 14 = 53, is the 938th name in the list. So, COLIN would
obtain a score of 938 × 53 = 49714.
What is the total of all the name scores in the file?
"""
import os
def solution():
"""Returns the total of all the name scores in the file.
>>> solution()
871198282
"""
total_sum = 0
temp_sum = 0
with open(os.path.dirname(__file__) + "/p022_names.txt") as file:
name = str(file.readlines()[0])
name = name.replace('"', "").split(",")
name.sort()
for i in range(len(name)):
for j in name[i]:
temp_sum += ord(j) - ord("A") + 1
total_sum += (i + 1) * temp_sum
temp_sum = 0
return total_sum
if __name__ == "__main__":
print(solution())
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from sys import maxsize
def max_sub_array_sum(a: list, size: int = 0):
"""
>>> max_sub_array_sum([-13, -3, -25, -20, -3, -16, -23, -12, -5, -22, -15, -4, -7])
-3
"""
size = size or len(a)
max_so_far = -maxsize - 1
max_ending_here = 0
for i in range(0, size):
max_ending_here = max_ending_here + a[i]
if max_so_far < max_ending_here:
max_so_far = max_ending_here
if max_ending_here < 0:
max_ending_here = 0
return max_so_far
if __name__ == "__main__":
a = [-13, -3, -25, -20, 1, -16, -23, -12, -5, -22, -15, -4, -7]
print(("Maximum contiguous sum is", max_sub_array_sum(a, len(a))))
| from sys import maxsize
def max_sub_array_sum(a: list, size: int = 0):
"""
>>> max_sub_array_sum([-13, -3, -25, -20, -3, -16, -23, -12, -5, -22, -15, -4, -7])
-3
"""
size = size or len(a)
max_so_far = -maxsize - 1
max_ending_here = 0
for i in range(0, size):
max_ending_here = max_ending_here + a[i]
if max_so_far < max_ending_here:
max_so_far = max_ending_here
if max_ending_here < 0:
max_ending_here = 0
return max_so_far
if __name__ == "__main__":
a = [-13, -3, -25, -20, 1, -16, -23, -12, -5, -22, -15, -4, -7]
print(("Maximum contiguous sum is", max_sub_array_sum(a, len(a))))
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 10: https://projecteuler.net/problem=10
Summation of primes
The sum of the primes below 10 is 2 + 3 + 5 + 7 = 17.
Find the sum of all the primes below two million.
References:
- https://en.wikipedia.org/wiki/Prime_number
"""
import math
def is_prime(number: int) -> bool:
"""Checks to see if a number is a prime in O(sqrt(n)).
A number is prime if it has exactly two factors: 1 and itself.
Returns boolean representing primality of given number num (i.e., if the
result is true, then the number is indeed prime else it is not).
>>> is_prime(2)
True
>>> is_prime(3)
True
>>> is_prime(27)
False
>>> is_prime(2999)
True
>>> is_prime(0)
False
>>> is_prime(1)
False
"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All primes number are in format of 6k +/- 1
for i in range(5, int(math.sqrt(number) + 1), 6):
if number % i == 0 or number % (i + 2) == 0:
return False
return True
def solution(n: int = 2000000) -> int:
"""
Returns the sum of all the primes below n.
>>> solution(1000)
76127
>>> solution(5000)
1548136
>>> solution(10000)
5736396
>>> solution(7)
10
"""
return sum(num for num in range(3, n, 2) if is_prime(num)) + 2 if n > 2 else 0
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 10: https://projecteuler.net/problem=10
Summation of primes
The sum of the primes below 10 is 2 + 3 + 5 + 7 = 17.
Find the sum of all the primes below two million.
References:
- https://en.wikipedia.org/wiki/Prime_number
"""
import math
def is_prime(number: int) -> bool:
"""Checks to see if a number is a prime in O(sqrt(n)).
A number is prime if it has exactly two factors: 1 and itself.
Returns boolean representing primality of given number num (i.e., if the
result is true, then the number is indeed prime else it is not).
>>> is_prime(2)
True
>>> is_prime(3)
True
>>> is_prime(27)
False
>>> is_prime(2999)
True
>>> is_prime(0)
False
>>> is_prime(1)
False
"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All primes number are in format of 6k +/- 1
for i in range(5, int(math.sqrt(number) + 1), 6):
if number % i == 0 or number % (i + 2) == 0:
return False
return True
def solution(n: int = 2000000) -> int:
"""
Returns the sum of all the primes below n.
>>> solution(1000)
76127
>>> solution(5000)
1548136
>>> solution(10000)
5736396
>>> solution(7)
10
"""
return sum(num for num in range(3, n, 2) if is_prime(num)) + 2 if n > 2 else 0
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Fast Polynomial Multiplication using radix-2 fast Fourier Transform.
"""
import mpmath # for roots of unity
import numpy as np
class FFT:
"""
Fast Polynomial Multiplication using radix-2 fast Fourier Transform.
Reference:
https://en.wikipedia.org/wiki/Cooley%E2%80%93Tukey_FFT_algorithm#The_radix-2_DIT_case
For polynomials of degree m and n the algorithms has complexity
O(n*logn + m*logm)
The main part of the algorithm is split in two parts:
1) __DFT: We compute the discrete fourier transform (DFT) of A and B using a
bottom-up dynamic approach -
2) __multiply: Once we obtain the DFT of A*B, we can similarly
invert it to obtain A*B
The class FFT takes two polynomials A and B with complex coefficients as arguments;
The two polynomials should be represented as a sequence of coefficients starting
from the free term. Thus, for instance x + 2*x^3 could be represented as
[0,1,0,2] or (0,1,0,2). The constructor adds some zeros at the end so that the
polynomials have the same length which is a power of 2 at least the length of
their product.
Example:
Create two polynomials as sequences
>>> A = [0, 1, 0, 2] # x+2x^3
>>> B = (2, 3, 4, 0) # 2+3x+4x^2
Create an FFT object with them
>>> x = FFT(A, B)
Print product
>>> print(x.product) # 2x + 3x^2 + 8x^3 + 4x^4 + 6x^5
[(-0+0j), (2+0j), (3+0j), (8+0j), (6+0j), (8+0j)]
__str__ test
>>> print(x)
A = 0*x^0 + 1*x^1 + 2*x^0 + 3*x^2
B = 0*x^2 + 1*x^3 + 2*x^4
A*B = 0*x^(-0+0j) + 1*x^(2+0j) + 2*x^(3+0j) + 3*x^(8+0j) + 4*x^(6+0j) + 5*x^(8+0j)
"""
def __init__(self, poly_a=None, poly_b=None):
# Input as list
self.polyA = list(poly_a or [0])[:]
self.polyB = list(poly_b or [0])[:]
# Remove leading zero coefficients
while self.polyA[-1] == 0:
self.polyA.pop()
self.len_A = len(self.polyA)
while self.polyB[-1] == 0:
self.polyB.pop()
self.len_B = len(self.polyB)
# Add 0 to make lengths equal a power of 2
self.c_max_length = int(
2 ** np.ceil(np.log2(len(self.polyA) + len(self.polyB) - 1))
)
while len(self.polyA) < self.c_max_length:
self.polyA.append(0)
while len(self.polyB) < self.c_max_length:
self.polyB.append(0)
# A complex root used for the fourier transform
self.root = complex(mpmath.root(x=1, n=self.c_max_length, k=1))
# The product
self.product = self.__multiply()
# Discrete fourier transform of A and B
def __dft(self, which):
if which == "A":
dft = [[x] for x in self.polyA]
else:
dft = [[x] for x in self.polyB]
# Corner case
if len(dft) <= 1:
return dft[0]
#
next_ncol = self.c_max_length // 2
while next_ncol > 0:
new_dft = [[] for i in range(next_ncol)]
root = self.root**next_ncol
# First half of next step
current_root = 1
for j in range(self.c_max_length // (next_ncol * 2)):
for i in range(next_ncol):
new_dft[i].append(dft[i][j] + current_root * dft[i + next_ncol][j])
current_root *= root
# Second half of next step
current_root = 1
for j in range(self.c_max_length // (next_ncol * 2)):
for i in range(next_ncol):
new_dft[i].append(dft[i][j] - current_root * dft[i + next_ncol][j])
current_root *= root
# Update
dft = new_dft
next_ncol = next_ncol // 2
return dft[0]
# multiply the DFTs of A and B and find A*B
def __multiply(self):
dft_a = self.__dft("A")
dft_b = self.__dft("B")
inverce_c = [[dft_a[i] * dft_b[i] for i in range(self.c_max_length)]]
del dft_a
del dft_b
# Corner Case
if len(inverce_c[0]) <= 1:
return inverce_c[0]
# Inverse DFT
next_ncol = 2
while next_ncol <= self.c_max_length:
new_inverse_c = [[] for i in range(next_ncol)]
root = self.root ** (next_ncol // 2)
current_root = 1
# First half of next step
for j in range(self.c_max_length // next_ncol):
for i in range(next_ncol // 2):
# Even positions
new_inverse_c[i].append(
(
inverce_c[i][j]
+ inverce_c[i][j + self.c_max_length // next_ncol]
)
/ 2
)
# Odd positions
new_inverse_c[i + next_ncol // 2].append(
(
inverce_c[i][j]
- inverce_c[i][j + self.c_max_length // next_ncol]
)
/ (2 * current_root)
)
current_root *= root
# Update
inverce_c = new_inverse_c
next_ncol *= 2
# Unpack
inverce_c = [round(x[0].real, 8) + round(x[0].imag, 8) * 1j for x in inverce_c]
# Remove leading 0's
while inverce_c[-1] == 0:
inverce_c.pop()
return inverce_c
# Overwrite __str__ for print(); Shows A, B and A*B
def __str__(self):
a = "A = " + " + ".join(
f"{coef}*x^{i}" for coef, i in enumerate(self.polyA[: self.len_A])
)
b = "B = " + " + ".join(
f"{coef}*x^{i}" for coef, i in enumerate(self.polyB[: self.len_B])
)
c = "A*B = " + " + ".join(
f"{coef}*x^{i}" for coef, i in enumerate(self.product)
)
return "\n".join((a, b, c))
# Unit tests
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
Fast Polynomial Multiplication using radix-2 fast Fourier Transform.
"""
import mpmath # for roots of unity
import numpy as np
class FFT:
"""
Fast Polynomial Multiplication using radix-2 fast Fourier Transform.
Reference:
https://en.wikipedia.org/wiki/Cooley%E2%80%93Tukey_FFT_algorithm#The_radix-2_DIT_case
For polynomials of degree m and n the algorithms has complexity
O(n*logn + m*logm)
The main part of the algorithm is split in two parts:
1) __DFT: We compute the discrete fourier transform (DFT) of A and B using a
bottom-up dynamic approach -
2) __multiply: Once we obtain the DFT of A*B, we can similarly
invert it to obtain A*B
The class FFT takes two polynomials A and B with complex coefficients as arguments;
The two polynomials should be represented as a sequence of coefficients starting
from the free term. Thus, for instance x + 2*x^3 could be represented as
[0,1,0,2] or (0,1,0,2). The constructor adds some zeros at the end so that the
polynomials have the same length which is a power of 2 at least the length of
their product.
Example:
Create two polynomials as sequences
>>> A = [0, 1, 0, 2] # x+2x^3
>>> B = (2, 3, 4, 0) # 2+3x+4x^2
Create an FFT object with them
>>> x = FFT(A, B)
Print product
>>> print(x.product) # 2x + 3x^2 + 8x^3 + 4x^4 + 6x^5
[(-0+0j), (2+0j), (3+0j), (8+0j), (6+0j), (8+0j)]
__str__ test
>>> print(x)
A = 0*x^0 + 1*x^1 + 2*x^0 + 3*x^2
B = 0*x^2 + 1*x^3 + 2*x^4
A*B = 0*x^(-0+0j) + 1*x^(2+0j) + 2*x^(3+0j) + 3*x^(8+0j) + 4*x^(6+0j) + 5*x^(8+0j)
"""
def __init__(self, poly_a=None, poly_b=None):
# Input as list
self.polyA = list(poly_a or [0])[:]
self.polyB = list(poly_b or [0])[:]
# Remove leading zero coefficients
while self.polyA[-1] == 0:
self.polyA.pop()
self.len_A = len(self.polyA)
while self.polyB[-1] == 0:
self.polyB.pop()
self.len_B = len(self.polyB)
# Add 0 to make lengths equal a power of 2
self.c_max_length = int(
2 ** np.ceil(np.log2(len(self.polyA) + len(self.polyB) - 1))
)
while len(self.polyA) < self.c_max_length:
self.polyA.append(0)
while len(self.polyB) < self.c_max_length:
self.polyB.append(0)
# A complex root used for the fourier transform
self.root = complex(mpmath.root(x=1, n=self.c_max_length, k=1))
# The product
self.product = self.__multiply()
# Discrete fourier transform of A and B
def __dft(self, which):
if which == "A":
dft = [[x] for x in self.polyA]
else:
dft = [[x] for x in self.polyB]
# Corner case
if len(dft) <= 1:
return dft[0]
#
next_ncol = self.c_max_length // 2
while next_ncol > 0:
new_dft = [[] for i in range(next_ncol)]
root = self.root**next_ncol
# First half of next step
current_root = 1
for j in range(self.c_max_length // (next_ncol * 2)):
for i in range(next_ncol):
new_dft[i].append(dft[i][j] + current_root * dft[i + next_ncol][j])
current_root *= root
# Second half of next step
current_root = 1
for j in range(self.c_max_length // (next_ncol * 2)):
for i in range(next_ncol):
new_dft[i].append(dft[i][j] - current_root * dft[i + next_ncol][j])
current_root *= root
# Update
dft = new_dft
next_ncol = next_ncol // 2
return dft[0]
# multiply the DFTs of A and B and find A*B
def __multiply(self):
dft_a = self.__dft("A")
dft_b = self.__dft("B")
inverce_c = [[dft_a[i] * dft_b[i] for i in range(self.c_max_length)]]
del dft_a
del dft_b
# Corner Case
if len(inverce_c[0]) <= 1:
return inverce_c[0]
# Inverse DFT
next_ncol = 2
while next_ncol <= self.c_max_length:
new_inverse_c = [[] for i in range(next_ncol)]
root = self.root ** (next_ncol // 2)
current_root = 1
# First half of next step
for j in range(self.c_max_length // next_ncol):
for i in range(next_ncol // 2):
# Even positions
new_inverse_c[i].append(
(
inverce_c[i][j]
+ inverce_c[i][j + self.c_max_length // next_ncol]
)
/ 2
)
# Odd positions
new_inverse_c[i + next_ncol // 2].append(
(
inverce_c[i][j]
- inverce_c[i][j + self.c_max_length // next_ncol]
)
/ (2 * current_root)
)
current_root *= root
# Update
inverce_c = new_inverse_c
next_ncol *= 2
# Unpack
inverce_c = [round(x[0].real, 8) + round(x[0].imag, 8) * 1j for x in inverce_c]
# Remove leading 0's
while inverce_c[-1] == 0:
inverce_c.pop()
return inverce_c
# Overwrite __str__ for print(); Shows A, B and A*B
def __str__(self):
a = "A = " + " + ".join(
f"{coef}*x^{i}" for coef, i in enumerate(self.polyA[: self.len_A])
)
b = "B = " + " + ".join(
f"{coef}*x^{i}" for coef, i in enumerate(self.polyB[: self.len_B])
)
c = "A*B = " + " + ".join(
f"{coef}*x^{i}" for coef, i in enumerate(self.product)
)
return "\n".join((a, b, c))
# Unit tests
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """Queue represented by a Python list"""
class Queue:
def __init__(self):
self.entries = []
self.length = 0
self.front = 0
def __str__(self):
printed = "<" + str(self.entries)[1:-1] + ">"
return printed
"""Enqueues {@code item}
@param item
item to enqueue"""
def put(self, item):
self.entries.append(item)
self.length = self.length + 1
"""Dequeues {@code item}
@requirement: |self.length| > 0
@return dequeued
item that was dequeued"""
def get(self):
self.length = self.length - 1
dequeued = self.entries[self.front]
# self.front-=1
# self.entries = self.entries[self.front:]
self.entries = self.entries[1:]
return dequeued
"""Rotates the queue {@code rotation} times
@param rotation
number of times to rotate queue"""
def rotate(self, rotation):
for _ in range(rotation):
self.put(self.get())
"""Enqueues {@code item}
@return item at front of self.entries"""
def get_front(self):
return self.entries[0]
"""Returns the length of this.entries"""
def size(self):
return self.length
| """Queue represented by a Python list"""
class Queue:
def __init__(self):
self.entries = []
self.length = 0
self.front = 0
def __str__(self):
printed = "<" + str(self.entries)[1:-1] + ">"
return printed
"""Enqueues {@code item}
@param item
item to enqueue"""
def put(self, item):
self.entries.append(item)
self.length = self.length + 1
"""Dequeues {@code item}
@requirement: |self.length| > 0
@return dequeued
item that was dequeued"""
def get(self):
self.length = self.length - 1
dequeued = self.entries[self.front]
# self.front-=1
# self.entries = self.entries[self.front:]
self.entries = self.entries[1:]
return dequeued
"""Rotates the queue {@code rotation} times
@param rotation
number of times to rotate queue"""
def rotate(self, rotation):
for _ in range(rotation):
self.put(self.get())
"""Enqueues {@code item}
@return item at front of self.entries"""
def get_front(self):
return self.entries[0]
"""Returns the length of this.entries"""
def size(self):
return self.length
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def hamming_distance(string1: str, string2: str) -> int:
"""Calculate the Hamming distance between two equal length strings
In information theory, the Hamming distance between two strings of equal
length is the number of positions at which the corresponding symbols are
different. https://en.wikipedia.org/wiki/Hamming_distance
Args:
string1 (str): Sequence 1
string2 (str): Sequence 2
Returns:
int: Hamming distance
>>> hamming_distance("python", "python")
0
>>> hamming_distance("karolin", "kathrin")
3
>>> hamming_distance("00000", "11111")
5
>>> hamming_distance("karolin", "kath")
Traceback (most recent call last):
...
ValueError: String lengths must match!
"""
if len(string1) != len(string2):
raise ValueError("String lengths must match!")
count = 0
for char1, char2 in zip(string1, string2):
if char1 != char2:
count += 1
return count
if __name__ == "__main__":
import doctest
doctest.testmod()
| def hamming_distance(string1: str, string2: str) -> int:
"""Calculate the Hamming distance between two equal length strings
In information theory, the Hamming distance between two strings of equal
length is the number of positions at which the corresponding symbols are
different. https://en.wikipedia.org/wiki/Hamming_distance
Args:
string1 (str): Sequence 1
string2 (str): Sequence 2
Returns:
int: Hamming distance
>>> hamming_distance("python", "python")
0
>>> hamming_distance("karolin", "kathrin")
3
>>> hamming_distance("00000", "11111")
5
>>> hamming_distance("karolin", "kath")
Traceback (most recent call last):
...
ValueError: String lengths must match!
"""
if len(string1) != len(string2):
raise ValueError("String lengths must match!")
count = 0
for char1, char2 in zip(string1, string2):
if char1 != char2:
count += 1
return count
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Convert speed units
https://en.wikipedia.org/wiki/Kilometres_per_hour
https://en.wikipedia.org/wiki/Miles_per_hour
https://en.wikipedia.org/wiki/Knot_(unit)
https://en.wikipedia.org/wiki/Metre_per_second
"""
speed_chart: dict[str, float] = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.609344,
"knot": 1.852,
}
speed_chart_inverse: dict[str, float] = {
"km/h": 1.0,
"m/s": 0.277777778,
"mph": 0.621371192,
"knot": 0.539956803,
}
def convert_speed(speed: float, unit_from: str, unit_to: str) -> float:
"""
Convert speed from one unit to another using the speed_chart above.
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.609344,
"knot": 1.852,
>>> convert_speed(100, "km/h", "m/s")
27.778
>>> convert_speed(100, "km/h", "mph")
62.137
>>> convert_speed(100, "km/h", "knot")
53.996
>>> convert_speed(100, "m/s", "km/h")
360.0
>>> convert_speed(100, "m/s", "mph")
223.694
>>> convert_speed(100, "m/s", "knot")
194.384
>>> convert_speed(100, "mph", "km/h")
160.934
>>> convert_speed(100, "mph", "m/s")
44.704
>>> convert_speed(100, "mph", "knot")
86.898
>>> convert_speed(100, "knot", "km/h")
185.2
>>> convert_speed(100, "knot", "m/s")
51.444
>>> convert_speed(100, "knot", "mph")
115.078
"""
if unit_to not in speed_chart or unit_from not in speed_chart_inverse:
raise ValueError(
f"Incorrect 'from_type' or 'to_type' value: {unit_from!r}, {unit_to!r}\n"
f"Valid values are: {', '.join(speed_chart_inverse)}"
)
return round(speed * speed_chart[unit_from] * speed_chart_inverse[unit_to], 3)
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
Convert speed units
https://en.wikipedia.org/wiki/Kilometres_per_hour
https://en.wikipedia.org/wiki/Miles_per_hour
https://en.wikipedia.org/wiki/Knot_(unit)
https://en.wikipedia.org/wiki/Metre_per_second
"""
speed_chart: dict[str, float] = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.609344,
"knot": 1.852,
}
speed_chart_inverse: dict[str, float] = {
"km/h": 1.0,
"m/s": 0.277777778,
"mph": 0.621371192,
"knot": 0.539956803,
}
def convert_speed(speed: float, unit_from: str, unit_to: str) -> float:
"""
Convert speed from one unit to another using the speed_chart above.
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.609344,
"knot": 1.852,
>>> convert_speed(100, "km/h", "m/s")
27.778
>>> convert_speed(100, "km/h", "mph")
62.137
>>> convert_speed(100, "km/h", "knot")
53.996
>>> convert_speed(100, "m/s", "km/h")
360.0
>>> convert_speed(100, "m/s", "mph")
223.694
>>> convert_speed(100, "m/s", "knot")
194.384
>>> convert_speed(100, "mph", "km/h")
160.934
>>> convert_speed(100, "mph", "m/s")
44.704
>>> convert_speed(100, "mph", "knot")
86.898
>>> convert_speed(100, "knot", "km/h")
185.2
>>> convert_speed(100, "knot", "m/s")
51.444
>>> convert_speed(100, "knot", "mph")
115.078
"""
if unit_to not in speed_chart or unit_from not in speed_chart_inverse:
raise ValueError(
f"Incorrect 'from_type' or 'to_type' value: {unit_from!r}, {unit_to!r}\n"
f"Valid values are: {', '.join(speed_chart_inverse)}"
)
return round(speed * speed_chart[unit_from] * speed_chart_inverse[unit_to], 3)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Knight Tour Intro: https://www.youtube.com/watch?v=ab_dY3dZFHM
from __future__ import annotations
def get_valid_pos(position: tuple[int, int], n: int) -> list[tuple[int, int]]:
"""
Find all the valid positions a knight can move to from the current position.
>>> get_valid_pos((1, 3), 4)
[(2, 1), (0, 1), (3, 2)]
"""
y, x = position
positions = [
(y + 1, x + 2),
(y - 1, x + 2),
(y + 1, x - 2),
(y - 1, x - 2),
(y + 2, x + 1),
(y + 2, x - 1),
(y - 2, x + 1),
(y - 2, x - 1),
]
permissible_positions = []
for position in positions:
y_test, x_test = position
if 0 <= y_test < n and 0 <= x_test < n:
permissible_positions.append(position)
return permissible_positions
def is_complete(board: list[list[int]]) -> bool:
"""
Check if the board (matrix) has been completely filled with non-zero values.
>>> is_complete([[1]])
True
>>> is_complete([[1, 2], [3, 0]])
False
"""
return not any(elem == 0 for row in board for elem in row)
def open_knight_tour_helper(
board: list[list[int]], pos: tuple[int, int], curr: int
) -> bool:
"""
Helper function to solve knight tour problem.
"""
if is_complete(board):
return True
for position in get_valid_pos(pos, len(board)):
y, x = position
if board[y][x] == 0:
board[y][x] = curr + 1
if open_knight_tour_helper(board, position, curr + 1):
return True
board[y][x] = 0
return False
def open_knight_tour(n: int) -> list[list[int]]:
"""
Find the solution for the knight tour problem for a board of size n. Raises
ValueError if the tour cannot be performed for the given size.
>>> open_knight_tour(1)
[[1]]
>>> open_knight_tour(2)
Traceback (most recent call last):
...
ValueError: Open Kight Tour cannot be performed on a board of size 2
"""
board = [[0 for i in range(n)] for j in range(n)]
for i in range(n):
for j in range(n):
board[i][j] = 1
if open_knight_tour_helper(board, (i, j), 1):
return board
board[i][j] = 0
raise ValueError(f"Open Kight Tour cannot be performed on a board of size {n}")
if __name__ == "__main__":
import doctest
doctest.testmod()
| # Knight Tour Intro: https://www.youtube.com/watch?v=ab_dY3dZFHM
from __future__ import annotations
def get_valid_pos(position: tuple[int, int], n: int) -> list[tuple[int, int]]:
"""
Find all the valid positions a knight can move to from the current position.
>>> get_valid_pos((1, 3), 4)
[(2, 1), (0, 1), (3, 2)]
"""
y, x = position
positions = [
(y + 1, x + 2),
(y - 1, x + 2),
(y + 1, x - 2),
(y - 1, x - 2),
(y + 2, x + 1),
(y + 2, x - 1),
(y - 2, x + 1),
(y - 2, x - 1),
]
permissible_positions = []
for position in positions:
y_test, x_test = position
if 0 <= y_test < n and 0 <= x_test < n:
permissible_positions.append(position)
return permissible_positions
def is_complete(board: list[list[int]]) -> bool:
"""
Check if the board (matrix) has been completely filled with non-zero values.
>>> is_complete([[1]])
True
>>> is_complete([[1, 2], [3, 0]])
False
"""
return not any(elem == 0 for row in board for elem in row)
def open_knight_tour_helper(
board: list[list[int]], pos: tuple[int, int], curr: int
) -> bool:
"""
Helper function to solve knight tour problem.
"""
if is_complete(board):
return True
for position in get_valid_pos(pos, len(board)):
y, x = position
if board[y][x] == 0:
board[y][x] = curr + 1
if open_knight_tour_helper(board, position, curr + 1):
return True
board[y][x] = 0
return False
def open_knight_tour(n: int) -> list[list[int]]:
"""
Find the solution for the knight tour problem for a board of size n. Raises
ValueError if the tour cannot be performed for the given size.
>>> open_knight_tour(1)
[[1]]
>>> open_knight_tour(2)
Traceback (most recent call last):
...
ValueError: Open Kight Tour cannot be performed on a board of size 2
"""
board = [[0 for i in range(n)] for j in range(n)]
for i in range(n):
for j in range(n):
board[i][j] = 1
if open_knight_tour_helper(board, (i, j), 1):
return board
board[i][j] = 0
raise ValueError(f"Open Kight Tour cannot be performed on a board of size {n}")
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Description
The Koch snowflake is a fractal curve and one of the earliest fractals to
have been described. The Koch snowflake can be built up iteratively, in a
sequence of stages. The first stage is an equilateral triangle, and each
successive stage is formed by adding outward bends to each side of the
previous stage, making smaller equilateral triangles.
This can be achieved through the following steps for each line:
1. divide the line segment into three segments of equal length.
2. draw an equilateral triangle that has the middle segment from step 1
as its base and points outward.
3. remove the line segment that is the base of the triangle from step 2.
(description adapted from https://en.wikipedia.org/wiki/Koch_snowflake )
(for a more detailed explanation and an implementation in the
Processing language, see https://natureofcode.com/book/chapter-8-fractals/
#84-the-koch-curve-and-the-arraylist-technique )
Requirements (pip):
- matplotlib
- numpy
"""
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
VECTOR_1 = numpy.array([0, 0])
VECTOR_2 = numpy.array([0.5, 0.8660254])
VECTOR_3 = numpy.array([1, 0])
INITIAL_VECTORS = [VECTOR_1, VECTOR_2, VECTOR_3, VECTOR_1]
# uncomment for simple Koch curve instead of Koch snowflake
# INITIAL_VECTORS = [VECTOR_1, VECTOR_3]
def iterate(initial_vectors: list[numpy.ndarray], steps: int) -> list[numpy.ndarray]:
"""
Go through the number of iterations determined by the argument "steps".
Be careful with high values (above 5) since the time to calculate increases
exponentially.
>>> iterate([numpy.array([0, 0]), numpy.array([1, 0])], 1)
[array([0, 0]), array([0.33333333, 0. ]), array([0.5 , \
0.28867513]), array([0.66666667, 0. ]), array([1, 0])]
"""
vectors = initial_vectors
for _ in range(steps):
vectors = iteration_step(vectors)
return vectors
def iteration_step(vectors: list[numpy.ndarray]) -> list[numpy.ndarray]:
"""
Loops through each pair of adjacent vectors. Each line between two adjacent
vectors is divided into 4 segments by adding 3 additional vectors in-between
the original two vectors. The vector in the middle is constructed through a
60 degree rotation so it is bent outwards.
>>> iteration_step([numpy.array([0, 0]), numpy.array([1, 0])])
[array([0, 0]), array([0.33333333, 0. ]), array([0.5 , \
0.28867513]), array([0.66666667, 0. ]), array([1, 0])]
"""
new_vectors = []
for i, start_vector in enumerate(vectors[:-1]):
end_vector = vectors[i + 1]
new_vectors.append(start_vector)
difference_vector = end_vector - start_vector
new_vectors.append(start_vector + difference_vector / 3)
new_vectors.append(
start_vector + difference_vector / 3 + rotate(difference_vector / 3, 60)
)
new_vectors.append(start_vector + difference_vector * 2 / 3)
new_vectors.append(vectors[-1])
return new_vectors
def rotate(vector: numpy.ndarray, angle_in_degrees: float) -> numpy.ndarray:
"""
Standard rotation of a 2D vector with a rotation matrix
(see https://en.wikipedia.org/wiki/Rotation_matrix )
>>> rotate(numpy.array([1, 0]), 60)
array([0.5 , 0.8660254])
>>> rotate(numpy.array([1, 0]), 90)
array([6.123234e-17, 1.000000e+00])
"""
theta = numpy.radians(angle_in_degrees)
c, s = numpy.cos(theta), numpy.sin(theta)
rotation_matrix = numpy.array(((c, -s), (s, c)))
return numpy.dot(rotation_matrix, vector)
def plot(vectors: list[numpy.ndarray]) -> None:
"""
Utility function to plot the vectors using matplotlib.pyplot
No doctest was implemented since this function does not have a return value
"""
# avoid stretched display of graph
axes = plt.gca()
axes.set_aspect("equal")
# matplotlib.pyplot.plot takes a list of all x-coordinates and a list of all
# y-coordinates as inputs, which are constructed from the vector-list using
# zip()
x_coordinates, y_coordinates = zip(*vectors)
plt.plot(x_coordinates, y_coordinates)
plt.show()
if __name__ == "__main__":
import doctest
doctest.testmod()
processed_vectors = iterate(INITIAL_VECTORS, 5)
plot(processed_vectors)
| """
Description
The Koch snowflake is a fractal curve and one of the earliest fractals to
have been described. The Koch snowflake can be built up iteratively, in a
sequence of stages. The first stage is an equilateral triangle, and each
successive stage is formed by adding outward bends to each side of the
previous stage, making smaller equilateral triangles.
This can be achieved through the following steps for each line:
1. divide the line segment into three segments of equal length.
2. draw an equilateral triangle that has the middle segment from step 1
as its base and points outward.
3. remove the line segment that is the base of the triangle from step 2.
(description adapted from https://en.wikipedia.org/wiki/Koch_snowflake )
(for a more detailed explanation and an implementation in the
Processing language, see https://natureofcode.com/book/chapter-8-fractals/
#84-the-koch-curve-and-the-arraylist-technique )
Requirements (pip):
- matplotlib
- numpy
"""
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
VECTOR_1 = numpy.array([0, 0])
VECTOR_2 = numpy.array([0.5, 0.8660254])
VECTOR_3 = numpy.array([1, 0])
INITIAL_VECTORS = [VECTOR_1, VECTOR_2, VECTOR_3, VECTOR_1]
# uncomment for simple Koch curve instead of Koch snowflake
# INITIAL_VECTORS = [VECTOR_1, VECTOR_3]
def iterate(initial_vectors: list[numpy.ndarray], steps: int) -> list[numpy.ndarray]:
"""
Go through the number of iterations determined by the argument "steps".
Be careful with high values (above 5) since the time to calculate increases
exponentially.
>>> iterate([numpy.array([0, 0]), numpy.array([1, 0])], 1)
[array([0, 0]), array([0.33333333, 0. ]), array([0.5 , \
0.28867513]), array([0.66666667, 0. ]), array([1, 0])]
"""
vectors = initial_vectors
for _ in range(steps):
vectors = iteration_step(vectors)
return vectors
def iteration_step(vectors: list[numpy.ndarray]) -> list[numpy.ndarray]:
"""
Loops through each pair of adjacent vectors. Each line between two adjacent
vectors is divided into 4 segments by adding 3 additional vectors in-between
the original two vectors. The vector in the middle is constructed through a
60 degree rotation so it is bent outwards.
>>> iteration_step([numpy.array([0, 0]), numpy.array([1, 0])])
[array([0, 0]), array([0.33333333, 0. ]), array([0.5 , \
0.28867513]), array([0.66666667, 0. ]), array([1, 0])]
"""
new_vectors = []
for i, start_vector in enumerate(vectors[:-1]):
end_vector = vectors[i + 1]
new_vectors.append(start_vector)
difference_vector = end_vector - start_vector
new_vectors.append(start_vector + difference_vector / 3)
new_vectors.append(
start_vector + difference_vector / 3 + rotate(difference_vector / 3, 60)
)
new_vectors.append(start_vector + difference_vector * 2 / 3)
new_vectors.append(vectors[-1])
return new_vectors
def rotate(vector: numpy.ndarray, angle_in_degrees: float) -> numpy.ndarray:
"""
Standard rotation of a 2D vector with a rotation matrix
(see https://en.wikipedia.org/wiki/Rotation_matrix )
>>> rotate(numpy.array([1, 0]), 60)
array([0.5 , 0.8660254])
>>> rotate(numpy.array([1, 0]), 90)
array([6.123234e-17, 1.000000e+00])
"""
theta = numpy.radians(angle_in_degrees)
c, s = numpy.cos(theta), numpy.sin(theta)
rotation_matrix = numpy.array(((c, -s), (s, c)))
return numpy.dot(rotation_matrix, vector)
def plot(vectors: list[numpy.ndarray]) -> None:
"""
Utility function to plot the vectors using matplotlib.pyplot
No doctest was implemented since this function does not have a return value
"""
# avoid stretched display of graph
axes = plt.gca()
axes.set_aspect("equal")
# matplotlib.pyplot.plot takes a list of all x-coordinates and a list of all
# y-coordinates as inputs, which are constructed from the vector-list using
# zip()
x_coordinates, y_coordinates = zip(*vectors)
plt.plot(x_coordinates, y_coordinates)
plt.show()
if __name__ == "__main__":
import doctest
doctest.testmod()
processed_vectors = iterate(INITIAL_VECTORS, 5)
plot(processed_vectors)
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Problem 28
Url: https://projecteuler.net/problem=28
Statement:
Starting with the number 1 and moving to the right in a clockwise direction a 5
by 5 spiral is formed as follows:
21 22 23 24 25
20 7 8 9 10
19 6 1 2 11
18 5 4 3 12
17 16 15 14 13
It can be verified that the sum of the numbers on the diagonals is 101.
What is the sum of the numbers on the diagonals in a 1001 by 1001 spiral formed
in the same way?
"""
from math import ceil
def solution(n: int = 1001) -> int:
"""Returns the sum of the numbers on the diagonals in a n by n spiral
formed in the same way.
>>> solution(1001)
669171001
>>> solution(500)
82959497
>>> solution(100)
651897
>>> solution(50)
79697
>>> solution(10)
537
"""
total = 1
for i in range(1, int(ceil(n / 2.0))):
odd = 2 * i + 1
even = 2 * i
total = total + 4 * odd**2 - 6 * even
return total
if __name__ == "__main__":
import sys
if len(sys.argv) == 1:
print(solution())
else:
try:
n = int(sys.argv[1])
print(solution(n))
except ValueError:
print("Invalid entry - please enter a number")
| """
Problem 28
Url: https://projecteuler.net/problem=28
Statement:
Starting with the number 1 and moving to the right in a clockwise direction a 5
by 5 spiral is formed as follows:
21 22 23 24 25
20 7 8 9 10
19 6 1 2 11
18 5 4 3 12
17 16 15 14 13
It can be verified that the sum of the numbers on the diagonals is 101.
What is the sum of the numbers on the diagonals in a 1001 by 1001 spiral formed
in the same way?
"""
from math import ceil
def solution(n: int = 1001) -> int:
"""Returns the sum of the numbers on the diagonals in a n by n spiral
formed in the same way.
>>> solution(1001)
669171001
>>> solution(500)
82959497
>>> solution(100)
651897
>>> solution(50)
79697
>>> solution(10)
537
"""
total = 1
for i in range(1, int(ceil(n / 2.0))):
odd = 2 * i + 1
even = 2 * i
total = total + 4 * odd**2 - 6 * even
return total
if __name__ == "__main__":
import sys
if len(sys.argv) == 1:
print(solution())
else:
try:
n = int(sys.argv[1])
print(solution(n))
except ValueError:
print("Invalid entry - please enter a number")
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from collections.abc import Callable
class Heap:
"""
A generic Heap class, can be used as min or max by passing the key function
accordingly.
"""
def __init__(self, key: Callable | None = None) -> None:
# Stores actual heap items.
self.arr: list = []
# Stores indexes of each item for supporting updates and deletion.
self.pos_map: dict = {}
# Stores current size of heap.
self.size = 0
# Stores function used to evaluate the score of an item on which basis ordering
# will be done.
self.key = key or (lambda x: x)
def _parent(self, i: int) -> int | None:
"""Returns parent index of given index if exists else None"""
return int((i - 1) / 2) if i > 0 else None
def _left(self, i: int) -> int | None:
"""Returns left-child-index of given index if exists else None"""
left = int(2 * i + 1)
return left if 0 < left < self.size else None
def _right(self, i: int) -> int | None:
"""Returns right-child-index of given index if exists else None"""
right = int(2 * i + 2)
return right if 0 < right < self.size else None
def _swap(self, i: int, j: int) -> None:
"""Performs changes required for swapping two elements in the heap"""
# First update the indexes of the items in index map.
self.pos_map[self.arr[i][0]], self.pos_map[self.arr[j][0]] = (
self.pos_map[self.arr[j][0]],
self.pos_map[self.arr[i][0]],
)
# Then swap the items in the list.
self.arr[i], self.arr[j] = self.arr[j], self.arr[i]
def _cmp(self, i: int, j: int) -> bool:
"""Compares the two items using default comparison"""
return self.arr[i][1] < self.arr[j][1]
def _get_valid_parent(self, i: int) -> int:
"""
Returns index of valid parent as per desired ordering among given index and
both it's children
"""
left = self._left(i)
right = self._right(i)
valid_parent = i
if left is not None and not self._cmp(left, valid_parent):
valid_parent = left
if right is not None and not self._cmp(right, valid_parent):
valid_parent = right
return valid_parent
def _heapify_up(self, index: int) -> None:
"""Fixes the heap in upward direction of given index"""
parent = self._parent(index)
while parent is not None and not self._cmp(index, parent):
self._swap(index, parent)
index, parent = parent, self._parent(parent)
def _heapify_down(self, index: int) -> None:
"""Fixes the heap in downward direction of given index"""
valid_parent = self._get_valid_parent(index)
while valid_parent != index:
self._swap(index, valid_parent)
index, valid_parent = valid_parent, self._get_valid_parent(valid_parent)
def update_item(self, item: int, item_value: int) -> None:
"""Updates given item value in heap if present"""
if item not in self.pos_map:
return
index = self.pos_map[item]
self.arr[index] = [item, self.key(item_value)]
# Make sure heap is right in both up and down direction.
# Ideally only one of them will make any change.
self._heapify_up(index)
self._heapify_down(index)
def delete_item(self, item: int) -> None:
"""Deletes given item from heap if present"""
if item not in self.pos_map:
return
index = self.pos_map[item]
del self.pos_map[item]
self.arr[index] = self.arr[self.size - 1]
self.pos_map[self.arr[self.size - 1][0]] = index
self.size -= 1
# Make sure heap is right in both up and down direction. Ideally only one
# of them will make any change- so no performance loss in calling both.
if self.size > index:
self._heapify_up(index)
self._heapify_down(index)
def insert_item(self, item: int, item_value: int) -> None:
"""Inserts given item with given value in heap"""
arr_len = len(self.arr)
if arr_len == self.size:
self.arr.append([item, self.key(item_value)])
else:
self.arr[self.size] = [item, self.key(item_value)]
self.pos_map[item] = self.size
self.size += 1
self._heapify_up(self.size - 1)
def get_top(self) -> tuple | None:
"""Returns top item tuple (Calculated value, item) from heap if present"""
return self.arr[0] if self.size else None
def extract_top(self) -> tuple | None:
"""
Return top item tuple (Calculated value, item) from heap and removes it as well
if present
"""
top_item_tuple = self.get_top()
if top_item_tuple:
self.delete_item(top_item_tuple[0])
return top_item_tuple
def test_heap() -> None:
"""
>>> h = Heap() # Max-heap
>>> h.insert_item(5, 34)
>>> h.insert_item(6, 31)
>>> h.insert_item(7, 37)
>>> h.get_top()
[7, 37]
>>> h.extract_top()
[7, 37]
>>> h.extract_top()
[5, 34]
>>> h.extract_top()
[6, 31]
>>> h = Heap(key=lambda x: -x) # Min heap
>>> h.insert_item(5, 34)
>>> h.insert_item(6, 31)
>>> h.insert_item(7, 37)
>>> h.get_top()
[6, -31]
>>> h.extract_top()
[6, -31]
>>> h.extract_top()
[5, -34]
>>> h.extract_top()
[7, -37]
>>> h.insert_item(8, 45)
>>> h.insert_item(9, 40)
>>> h.insert_item(10, 50)
>>> h.get_top()
[9, -40]
>>> h.update_item(10, 30)
>>> h.get_top()
[10, -30]
>>> h.delete_item(10)
>>> h.get_top()
[9, -40]
"""
pass
if __name__ == "__main__":
import doctest
doctest.testmod()
| from collections.abc import Callable
class Heap:
"""
A generic Heap class, can be used as min or max by passing the key function
accordingly.
"""
def __init__(self, key: Callable | None = None) -> None:
# Stores actual heap items.
self.arr: list = []
# Stores indexes of each item for supporting updates and deletion.
self.pos_map: dict = {}
# Stores current size of heap.
self.size = 0
# Stores function used to evaluate the score of an item on which basis ordering
# will be done.
self.key = key or (lambda x: x)
def _parent(self, i: int) -> int | None:
"""Returns parent index of given index if exists else None"""
return int((i - 1) / 2) if i > 0 else None
def _left(self, i: int) -> int | None:
"""Returns left-child-index of given index if exists else None"""
left = int(2 * i + 1)
return left if 0 < left < self.size else None
def _right(self, i: int) -> int | None:
"""Returns right-child-index of given index if exists else None"""
right = int(2 * i + 2)
return right if 0 < right < self.size else None
def _swap(self, i: int, j: int) -> None:
"""Performs changes required for swapping two elements in the heap"""
# First update the indexes of the items in index map.
self.pos_map[self.arr[i][0]], self.pos_map[self.arr[j][0]] = (
self.pos_map[self.arr[j][0]],
self.pos_map[self.arr[i][0]],
)
# Then swap the items in the list.
self.arr[i], self.arr[j] = self.arr[j], self.arr[i]
def _cmp(self, i: int, j: int) -> bool:
"""Compares the two items using default comparison"""
return self.arr[i][1] < self.arr[j][1]
def _get_valid_parent(self, i: int) -> int:
"""
Returns index of valid parent as per desired ordering among given index and
both it's children
"""
left = self._left(i)
right = self._right(i)
valid_parent = i
if left is not None and not self._cmp(left, valid_parent):
valid_parent = left
if right is not None and not self._cmp(right, valid_parent):
valid_parent = right
return valid_parent
def _heapify_up(self, index: int) -> None:
"""Fixes the heap in upward direction of given index"""
parent = self._parent(index)
while parent is not None and not self._cmp(index, parent):
self._swap(index, parent)
index, parent = parent, self._parent(parent)
def _heapify_down(self, index: int) -> None:
"""Fixes the heap in downward direction of given index"""
valid_parent = self._get_valid_parent(index)
while valid_parent != index:
self._swap(index, valid_parent)
index, valid_parent = valid_parent, self._get_valid_parent(valid_parent)
def update_item(self, item: int, item_value: int) -> None:
"""Updates given item value in heap if present"""
if item not in self.pos_map:
return
index = self.pos_map[item]
self.arr[index] = [item, self.key(item_value)]
# Make sure heap is right in both up and down direction.
# Ideally only one of them will make any change.
self._heapify_up(index)
self._heapify_down(index)
def delete_item(self, item: int) -> None:
"""Deletes given item from heap if present"""
if item not in self.pos_map:
return
index = self.pos_map[item]
del self.pos_map[item]
self.arr[index] = self.arr[self.size - 1]
self.pos_map[self.arr[self.size - 1][0]] = index
self.size -= 1
# Make sure heap is right in both up and down direction. Ideally only one
# of them will make any change- so no performance loss in calling both.
if self.size > index:
self._heapify_up(index)
self._heapify_down(index)
def insert_item(self, item: int, item_value: int) -> None:
"""Inserts given item with given value in heap"""
arr_len = len(self.arr)
if arr_len == self.size:
self.arr.append([item, self.key(item_value)])
else:
self.arr[self.size] = [item, self.key(item_value)]
self.pos_map[item] = self.size
self.size += 1
self._heapify_up(self.size - 1)
def get_top(self) -> tuple | None:
"""Returns top item tuple (Calculated value, item) from heap if present"""
return self.arr[0] if self.size else None
def extract_top(self) -> tuple | None:
"""
Return top item tuple (Calculated value, item) from heap and removes it as well
if present
"""
top_item_tuple = self.get_top()
if top_item_tuple:
self.delete_item(top_item_tuple[0])
return top_item_tuple
def test_heap() -> None:
"""
>>> h = Heap() # Max-heap
>>> h.insert_item(5, 34)
>>> h.insert_item(6, 31)
>>> h.insert_item(7, 37)
>>> h.get_top()
[7, 37]
>>> h.extract_top()
[7, 37]
>>> h.extract_top()
[5, 34]
>>> h.extract_top()
[6, 31]
>>> h = Heap(key=lambda x: -x) # Min heap
>>> h.insert_item(5, 34)
>>> h.insert_item(6, 31)
>>> h.insert_item(7, 37)
>>> h.get_top()
[6, -31]
>>> h.extract_top()
[6, -31]
>>> h.extract_top()
[5, -34]
>>> h.extract_top()
[7, -37]
>>> h.insert_item(8, 45)
>>> h.insert_item(9, 40)
>>> h.insert_item(10, 50)
>>> h.get_top()
[9, -40]
>>> h.update_item(10, 30)
>>> h.get_top()
[10, -30]
>>> h.delete_item(10)
>>> h.get_top()
[9, -40]
"""
pass
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Author: Abhijeeth S
import math
def res(x, y):
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.log10(x)
else:
if x == 0: # 0 raised to any number is 0
return 0
elif y == 0:
return 1 # any number raised to 0 is 1
if __name__ == "__main__": # Main function
# Read two numbers from input and typecast them to int using map function.
# Here x is the base and y is the power.
prompt = "Enter the base and the power separated by a comma: "
x1, y1 = map(int, input(prompt).split(","))
x2, y2 = map(int, input(prompt).split(","))
# We find the log of each number, using the function res(), which takes two
# arguments.
res1 = res(x1, y1)
res2 = res(x2, y2)
# We check for the largest number
if res1 > res2:
print("Largest number is", x1, "^", y1)
elif res2 > res1:
print("Largest number is", x2, "^", y2)
else:
print("Both are equal")
| # Author: Abhijeeth S
import math
def res(x, y):
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.log10(x)
else:
if x == 0: # 0 raised to any number is 0
return 0
elif y == 0:
return 1 # any number raised to 0 is 1
if __name__ == "__main__": # Main function
# Read two numbers from input and typecast them to int using map function.
# Here x is the base and y is the power.
prompt = "Enter the base and the power separated by a comma: "
x1, y1 = map(int, input(prompt).split(","))
x2, y2 = map(int, input(prompt).split(","))
# We find the log of each number, using the function res(), which takes two
# arguments.
res1 = res(x1, y1)
res2 = res(x2, y2)
# We check for the largest number
if res1 > res2:
print("Largest number is", x1, "^", y1)
elif res2 > res1:
print("Largest number is", x2, "^", y2)
else:
print("Both are equal")
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from __future__ import annotations
def modular_division(a: int, b: int, n: int) -> int:
"""
Modular Division :
An efficient algorithm for dividing b by a modulo n.
GCD ( Greatest Common Divisor ) or HCF ( Highest Common Factor )
Given three integers a, b, and n, such that gcd(a,n)=1 and n>1, the algorithm should
return an integer x such that 0≤x≤n−1, and b/a=x(modn) (that is, b=ax(modn)).
Theorem:
a has a multiplicative inverse modulo n iff gcd(a,n) = 1
This find x = b*a^(-1) mod n
Uses ExtendedEuclid to find the inverse of a
>>> modular_division(4,8,5)
2
>>> modular_division(3,8,5)
1
>>> modular_division(4, 11, 5)
4
"""
assert n > 1 and a > 0 and greatest_common_divisor(a, n) == 1
(d, t, s) = extended_gcd(n, a) # Implemented below
x = (b * s) % n
return x
def invert_modulo(a: int, n: int) -> int:
"""
This function find the inverses of a i.e., a^(-1)
>>> invert_modulo(2, 5)
3
>>> invert_modulo(8,7)
1
"""
(b, x) = extended_euclid(a, n) # Implemented below
if b < 0:
b = (b % n + n) % n
return b
# ------------------ Finding Modular division using invert_modulo -------------------
def modular_division2(a: int, b: int, n: int) -> int:
"""
This function used the above inversion of a to find x = (b*a^(-1))mod n
>>> modular_division2(4,8,5)
2
>>> modular_division2(3,8,5)
1
>>> modular_division2(4, 11, 5)
4
"""
s = invert_modulo(a, n)
x = (b * s) % n
return x
def extended_gcd(a: int, b: int) -> tuple[int, int, int]:
"""
Extended Euclid's Algorithm : If d divides a and b and d = a*x + b*y for integers x
and y, then d = gcd(a,b)
>>> extended_gcd(10, 6)
(2, -1, 2)
>>> extended_gcd(7, 5)
(1, -2, 3)
** extended_gcd function is used when d = gcd(a,b) is required in output
"""
assert a >= 0 and b >= 0
if b == 0:
d, x, y = a, 1, 0
else:
(d, p, q) = extended_gcd(b, a % b)
x = q
y = p - q * (a // b)
assert a % d == 0 and b % d == 0
assert d == a * x + b * y
return (d, x, y)
def extended_euclid(a: int, b: int) -> tuple[int, int]:
"""
Extended Euclid
>>> extended_euclid(10, 6)
(-1, 2)
>>> extended_euclid(7, 5)
(-2, 3)
"""
if b == 0:
return (1, 0)
(x, y) = extended_euclid(b, a % b)
k = a // b
return (y, x - k * y)
def greatest_common_divisor(a: int, b: int) -> int:
"""
Euclid's Lemma : d divides a and b, if and only if d divides a-b and b
Euclid's Algorithm
>>> greatest_common_divisor(7,5)
1
Note : In number theory, two integers a and b are said to be relatively prime,
mutually prime, or co-prime if the only positive integer (factor) that divides
both of them is 1 i.e., gcd(a,b) = 1.
>>> greatest_common_divisor(121, 11)
11
"""
if a < b:
a, b = b, a
while a % b != 0:
a, b = b, a % b
return b
if __name__ == "__main__":
from doctest import testmod
testmod(name="modular_division", verbose=True)
testmod(name="modular_division2", verbose=True)
testmod(name="invert_modulo", verbose=True)
testmod(name="extended_gcd", verbose=True)
testmod(name="extended_euclid", verbose=True)
testmod(name="greatest_common_divisor", verbose=True)
| from __future__ import annotations
def modular_division(a: int, b: int, n: int) -> int:
"""
Modular Division :
An efficient algorithm for dividing b by a modulo n.
GCD ( Greatest Common Divisor ) or HCF ( Highest Common Factor )
Given three integers a, b, and n, such that gcd(a,n)=1 and n>1, the algorithm should
return an integer x such that 0≤x≤n−1, and b/a=x(modn) (that is, b=ax(modn)).
Theorem:
a has a multiplicative inverse modulo n iff gcd(a,n) = 1
This find x = b*a^(-1) mod n
Uses ExtendedEuclid to find the inverse of a
>>> modular_division(4,8,5)
2
>>> modular_division(3,8,5)
1
>>> modular_division(4, 11, 5)
4
"""
assert n > 1 and a > 0 and greatest_common_divisor(a, n) == 1
(d, t, s) = extended_gcd(n, a) # Implemented below
x = (b * s) % n
return x
def invert_modulo(a: int, n: int) -> int:
"""
This function find the inverses of a i.e., a^(-1)
>>> invert_modulo(2, 5)
3
>>> invert_modulo(8,7)
1
"""
(b, x) = extended_euclid(a, n) # Implemented below
if b < 0:
b = (b % n + n) % n
return b
# ------------------ Finding Modular division using invert_modulo -------------------
def modular_division2(a: int, b: int, n: int) -> int:
"""
This function used the above inversion of a to find x = (b*a^(-1))mod n
>>> modular_division2(4,8,5)
2
>>> modular_division2(3,8,5)
1
>>> modular_division2(4, 11, 5)
4
"""
s = invert_modulo(a, n)
x = (b * s) % n
return x
def extended_gcd(a: int, b: int) -> tuple[int, int, int]:
"""
Extended Euclid's Algorithm : If d divides a and b and d = a*x + b*y for integers x
and y, then d = gcd(a,b)
>>> extended_gcd(10, 6)
(2, -1, 2)
>>> extended_gcd(7, 5)
(1, -2, 3)
** extended_gcd function is used when d = gcd(a,b) is required in output
"""
assert a >= 0 and b >= 0
if b == 0:
d, x, y = a, 1, 0
else:
(d, p, q) = extended_gcd(b, a % b)
x = q
y = p - q * (a // b)
assert a % d == 0 and b % d == 0
assert d == a * x + b * y
return (d, x, y)
def extended_euclid(a: int, b: int) -> tuple[int, int]:
"""
Extended Euclid
>>> extended_euclid(10, 6)
(-1, 2)
>>> extended_euclid(7, 5)
(-2, 3)
"""
if b == 0:
return (1, 0)
(x, y) = extended_euclid(b, a % b)
k = a // b
return (y, x - k * y)
def greatest_common_divisor(a: int, b: int) -> int:
"""
Euclid's Lemma : d divides a and b, if and only if d divides a-b and b
Euclid's Algorithm
>>> greatest_common_divisor(7,5)
1
Note : In number theory, two integers a and b are said to be relatively prime,
mutually prime, or co-prime if the only positive integer (factor) that divides
both of them is 1 i.e., gcd(a,b) = 1.
>>> greatest_common_divisor(121, 11)
11
"""
if a < b:
a, b = b, a
while a % b != 0:
a, b = b, a % b
return b
if __name__ == "__main__":
from doctest import testmod
testmod(name="modular_division", verbose=True)
testmod(name="modular_division2", verbose=True)
testmod(name="invert_modulo", verbose=True)
testmod(name="extended_gcd", verbose=True)
testmod(name="extended_euclid", verbose=True)
testmod(name="greatest_common_divisor", verbose=True)
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import cv2
import numpy as np
"""
Harris Corner Detector
https://en.wikipedia.org/wiki/Harris_Corner_Detector
"""
class HarrisCorner:
def __init__(self, k: float, window_size: int):
"""
k : is an empirically determined constant in [0.04,0.06]
window_size : neighbourhoods considered
"""
if k in (0.04, 0.06):
self.k = k
self.window_size = window_size
else:
raise ValueError("invalid k value")
def __str__(self) -> str:
return f"Harris Corner detection with k : {self.k}"
def detect(self, img_path: str) -> tuple[cv2.Mat, list[list[int]]]:
"""
Returns the image with corners identified
img_path : path of the image
output : list of the corner positions, image
"""
img = cv2.imread(img_path, 0)
h, w = img.shape
corner_list: list[list[int]] = []
color_img = img.copy()
color_img = cv2.cvtColor(color_img, cv2.COLOR_GRAY2RGB)
dy, dx = np.gradient(img)
ixx = dx**2
iyy = dy**2
ixy = dx * dy
k = 0.04
offset = self.window_size // 2
for y in range(offset, h - offset):
for x in range(offset, w - offset):
wxx = ixx[
y - offset : y + offset + 1, x - offset : x + offset + 1
].sum()
wyy = iyy[
y - offset : y + offset + 1, x - offset : x + offset + 1
].sum()
wxy = ixy[
y - offset : y + offset + 1, x - offset : x + offset + 1
].sum()
det = (wxx * wyy) - (wxy**2)
trace = wxx + wyy
r = det - k * (trace**2)
# Can change the value
if r > 0.5:
corner_list.append([x, y, r])
color_img.itemset((y, x, 0), 0)
color_img.itemset((y, x, 1), 0)
color_img.itemset((y, x, 2), 255)
return color_img, corner_list
if __name__ == "__main__":
edge_detect = HarrisCorner(0.04, 3)
color_img, _ = edge_detect.detect("path_to_image")
cv2.imwrite("detect.png", color_img)
| import cv2
import numpy as np
"""
Harris Corner Detector
https://en.wikipedia.org/wiki/Harris_Corner_Detector
"""
class HarrisCorner:
def __init__(self, k: float, window_size: int):
"""
k : is an empirically determined constant in [0.04,0.06]
window_size : neighbourhoods considered
"""
if k in (0.04, 0.06):
self.k = k
self.window_size = window_size
else:
raise ValueError("invalid k value")
def __str__(self) -> str:
return f"Harris Corner detection with k : {self.k}"
def detect(self, img_path: str) -> tuple[cv2.Mat, list[list[int]]]:
"""
Returns the image with corners identified
img_path : path of the image
output : list of the corner positions, image
"""
img = cv2.imread(img_path, 0)
h, w = img.shape
corner_list: list[list[int]] = []
color_img = img.copy()
color_img = cv2.cvtColor(color_img, cv2.COLOR_GRAY2RGB)
dy, dx = np.gradient(img)
ixx = dx**2
iyy = dy**2
ixy = dx * dy
k = 0.04
offset = self.window_size // 2
for y in range(offset, h - offset):
for x in range(offset, w - offset):
wxx = ixx[
y - offset : y + offset + 1, x - offset : x + offset + 1
].sum()
wyy = iyy[
y - offset : y + offset + 1, x - offset : x + offset + 1
].sum()
wxy = ixy[
y - offset : y + offset + 1, x - offset : x + offset + 1
].sum()
det = (wxx * wyy) - (wxy**2)
trace = wxx + wyy
r = det - k * (trace**2)
# Can change the value
if r > 0.5:
corner_list.append([x, y, r])
color_img.itemset((y, x, 0), 0)
color_img.itemset((y, x, 1), 0)
color_img.itemset((y, x, 2), 255)
return color_img, corner_list
if __name__ == "__main__":
edge_detect = HarrisCorner(0.04, 3)
color_img, _ = edge_detect.detect("path_to_image")
cv2.imwrite("detect.png", color_img)
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Compression
Data compression is everywhere, you need it to store data without taking too much space.
Either the compression lose some data (then we talk about lossy compression, such as .jpg) or it does not (and then it is lossless compression, such as .png)
Lossless compression is mainly used for archive purpose as it allow storing data without losing information about the file archived. On the other hand, lossy compression is used for transfer of file where quality isn't necessarily what is required (i.e: images on Twitter).
* <https://www.sciencedirect.com/topics/computer-science/compression-algorithm>
* <https://en.wikipedia.org/wiki/Data_compression>
* <https://en.wikipedia.org/wiki/Pigeonhole_principle>
| # Compression
Data compression is everywhere, you need it to store data without taking too much space.
Either the compression lose some data (then we talk about lossy compression, such as .jpg) or it does not (and then it is lossless compression, such as .png)
Lossless compression is mainly used for archive purpose as it allow storing data without losing information about the file archived. On the other hand, lossy compression is used for transfer of file where quality isn't necessarily what is required (i.e: images on Twitter).
* <https://www.sciencedirect.com/topics/computer-science/compression-algorithm>
* <https://en.wikipedia.org/wiki/Data_compression>
* <https://en.wikipedia.org/wiki/Pigeonhole_principle>
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 2: https://projecteuler.net/problem=2
Even Fibonacci Numbers
Each new term in the Fibonacci sequence is generated by adding the previous
two terms. By starting with 1 and 2, the first 10 terms will be:
1, 2, 3, 5, 8, 13, 21, 34, 55, 89, ...
By considering the terms in the Fibonacci sequence whose values do not exceed
four million, find the sum of the even-valued terms.
References:
- https://en.wikipedia.org/wiki/Fibonacci_number
"""
import math
from decimal import Decimal, getcontext
def solution(n: int = 4000000) -> int:
"""
Returns the sum of all even fibonacci sequence elements that are lower
or equal to n.
>>> solution(10)
10
>>> solution(15)
10
>>> solution(2)
2
>>> solution(1)
0
>>> solution(34)
44
>>> solution(3.4)
2
>>> solution(0)
Traceback (most recent call last):
...
ValueError: Parameter n must be greater than or equal to one.
>>> solution(-17)
Traceback (most recent call last):
...
ValueError: Parameter n must be greater than or equal to one.
>>> solution([])
Traceback (most recent call last):
...
TypeError: Parameter n must be int or castable to int.
>>> solution("asd")
Traceback (most recent call last):
...
TypeError: Parameter n must be int or castable to int.
"""
try:
n = int(n)
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int.")
if n <= 0:
raise ValueError("Parameter n must be greater than or equal to one.")
getcontext().prec = 100
phi = (Decimal(5) ** Decimal(0.5) + 1) / Decimal(2)
index = (math.floor(math.log(n * (phi + 2), phi) - 1) // 3) * 3 + 2
num = Decimal(round(phi ** Decimal(index + 1))) / (phi + 2)
total = num // 2
return int(total)
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 2: https://projecteuler.net/problem=2
Even Fibonacci Numbers
Each new term in the Fibonacci sequence is generated by adding the previous
two terms. By starting with 1 and 2, the first 10 terms will be:
1, 2, 3, 5, 8, 13, 21, 34, 55, 89, ...
By considering the terms in the Fibonacci sequence whose values do not exceed
four million, find the sum of the even-valued terms.
References:
- https://en.wikipedia.org/wiki/Fibonacci_number
"""
import math
from decimal import Decimal, getcontext
def solution(n: int = 4000000) -> int:
"""
Returns the sum of all even fibonacci sequence elements that are lower
or equal to n.
>>> solution(10)
10
>>> solution(15)
10
>>> solution(2)
2
>>> solution(1)
0
>>> solution(34)
44
>>> solution(3.4)
2
>>> solution(0)
Traceback (most recent call last):
...
ValueError: Parameter n must be greater than or equal to one.
>>> solution(-17)
Traceback (most recent call last):
...
ValueError: Parameter n must be greater than or equal to one.
>>> solution([])
Traceback (most recent call last):
...
TypeError: Parameter n must be int or castable to int.
>>> solution("asd")
Traceback (most recent call last):
...
TypeError: Parameter n must be int or castable to int.
"""
try:
n = int(n)
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int.")
if n <= 0:
raise ValueError("Parameter n must be greater than or equal to one.")
getcontext().prec = 100
phi = (Decimal(5) ** Decimal(0.5) + 1) / Decimal(2)
index = (math.floor(math.log(n * (phi + 2), phi) - 1) // 3) * 3 + 2
num = Decimal(round(phi ** Decimal(index + 1))) / (phi + 2)
total = num // 2
return int(total)
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Problem 78
Url: https://projecteuler.net/problem=78
Statement:
Let p(n) represent the number of different ways in which n coins
can be separated into piles. For example, five coins can be separated
into piles in exactly seven different ways, so p(5)=7.
OOOOO
OOOO O
OOO OO
OOO O O
OO OO O
OO O O O
O O O O O
Find the least value of n for which p(n) is divisible by one million.
"""
import itertools
def solution(number: int = 1000000) -> int:
"""
>>> solution(1)
1
>>> solution(9)
14
>>> solution()
55374
"""
partitions = [1]
for i in itertools.count(len(partitions)):
item = 0
for j in itertools.count(1):
sign = -1 if j % 2 == 0 else +1
index = (j * j * 3 - j) // 2
if index > i:
break
item += partitions[i - index] * sign
item %= number
index += j
if index > i:
break
item += partitions[i - index] * sign
item %= number
if item == 0:
return i
partitions.append(item)
return 0
if __name__ == "__main__":
import doctest
doctest.testmod()
print(f"{solution() = }")
| """
Problem 78
Url: https://projecteuler.net/problem=78
Statement:
Let p(n) represent the number of different ways in which n coins
can be separated into piles. For example, five coins can be separated
into piles in exactly seven different ways, so p(5)=7.
OOOOO
OOOO O
OOO OO
OOO O O
OO OO O
OO O O O
O O O O O
Find the least value of n for which p(n) is divisible by one million.
"""
import itertools
def solution(number: int = 1000000) -> int:
"""
>>> solution(1)
1
>>> solution(9)
14
>>> solution()
55374
"""
partitions = [1]
for i in itertools.count(len(partitions)):
item = 0
for j in itertools.count(1):
sign = -1 if j % 2 == 0 else +1
index = (j * j * 3 - j) // 2
if index > i:
break
item += partitions[i - index] * sign
item %= number
index += j
if index > i:
break
item += partitions[i - index] * sign
item %= number
if item == 0:
return i
partitions.append(item)
return 0
if __name__ == "__main__":
import doctest
doctest.testmod()
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Description :
Newton's second law of motion pertains to the behavior of objects for which
all existing forces are not balanced.
The second law states that the acceleration of an object is dependent upon two variables
- the net force acting upon the object and the mass of the object.
The acceleration of an object depends directly
upon the net force acting upon the object,
and inversely upon the mass of the object.
As the force acting upon an object is increased,
the acceleration of the object is increased.
As the mass of an object is increased, the acceleration of the object is decreased.
Source: https://www.physicsclassroom.com/class/newtlaws/Lesson-3/Newton-s-Second-Law
Formulation: Fnet = m • a
Diagrammatic Explanation:
Forces are unbalanced
|
|
|
V
There is acceleration
/\
/ \
/ \
/ \
/ \
/ \
/ \
__________________ ____ ________________
|The acceleration | |The acceleration |
|depends directly | |depends inversely |
|on the net Force | |upon the object's |
|_________________| |mass_______________|
Units:
1 Newton = 1 kg X meters / (seconds^2)
How to use?
Inputs:
___________________________________________________
|Name | Units | Type |
|-------------|-------------------------|-----------|
|mass | (in kgs) | float |
|-------------|-------------------------|-----------|
|acceleration | (in meters/(seconds^2)) | float |
|_____________|_________________________|___________|
Output:
___________________________________________________
|Name | Units | Type |
|-------------|-------------------------|-----------|
|force | (in Newtons) | float |
|_____________|_________________________|___________|
"""
def newtons_second_law_of_motion(mass: float, acceleration: float) -> float:
"""
>>> newtons_second_law_of_motion(10, 10)
100
>>> newtons_second_law_of_motion(2.0, 1)
2.0
"""
force = float()
try:
force = mass * acceleration
except Exception:
return -0.0
return force
if __name__ == "__main__":
import doctest
# run doctest
doctest.testmod()
# demo
mass = 12.5
acceleration = 10
force = newtons_second_law_of_motion(mass, acceleration)
print("The force is ", force, "N")
| """
Description :
Newton's second law of motion pertains to the behavior of objects for which
all existing forces are not balanced.
The second law states that the acceleration of an object is dependent upon two variables
- the net force acting upon the object and the mass of the object.
The acceleration of an object depends directly
upon the net force acting upon the object,
and inversely upon the mass of the object.
As the force acting upon an object is increased,
the acceleration of the object is increased.
As the mass of an object is increased, the acceleration of the object is decreased.
Source: https://www.physicsclassroom.com/class/newtlaws/Lesson-3/Newton-s-Second-Law
Formulation: Fnet = m • a
Diagrammatic Explanation:
Forces are unbalanced
|
|
|
V
There is acceleration
/\
/ \
/ \
/ \
/ \
/ \
/ \
__________________ ____ ________________
|The acceleration | |The acceleration |
|depends directly | |depends inversely |
|on the net Force | |upon the object's |
|_________________| |mass_______________|
Units:
1 Newton = 1 kg X meters / (seconds^2)
How to use?
Inputs:
___________________________________________________
|Name | Units | Type |
|-------------|-------------------------|-----------|
|mass | (in kgs) | float |
|-------------|-------------------------|-----------|
|acceleration | (in meters/(seconds^2)) | float |
|_____________|_________________________|___________|
Output:
___________________________________________________
|Name | Units | Type |
|-------------|-------------------------|-----------|
|force | (in Newtons) | float |
|_____________|_________________________|___________|
"""
def newtons_second_law_of_motion(mass: float, acceleration: float) -> float:
"""
>>> newtons_second_law_of_motion(10, 10)
100
>>> newtons_second_law_of_motion(2.0, 1)
2.0
"""
force = float()
try:
force = mass * acceleration
except Exception:
return -0.0
return force
if __name__ == "__main__":
import doctest
# run doctest
doctest.testmod()
# demo
mass = 12.5
acceleration = 10
force = newtons_second_law_of_motion(mass, acceleration)
print("The force is ", force, "N")
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 129: https://projecteuler.net/problem=129
A number consisting entirely of ones is called a repunit. We shall define R(k) to be
a repunit of length k; for example, R(6) = 111111.
Given that n is a positive integer and GCD(n, 10) = 1, it can be shown that there
always exists a value, k, for which R(k) is divisible by n, and let A(n) be the least
such value of k; for example, A(7) = 6 and A(41) = 5.
The least value of n for which A(n) first exceeds ten is 17.
Find the least value of n for which A(n) first exceeds one-million.
"""
def least_divisible_repunit(divisor: int) -> int:
"""
Return the least value k such that the Repunit of length k is divisible by divisor.
>>> least_divisible_repunit(7)
6
>>> least_divisible_repunit(41)
5
>>> least_divisible_repunit(1234567)
34020
"""
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
repunit = 1
repunit_index = 1
while repunit:
repunit = (10 * repunit + 1) % divisor
repunit_index += 1
return repunit_index
def solution(limit: int = 1000000) -> int:
"""
Return the least value of n for which least_divisible_repunit(n)
first exceeds limit.
>>> solution(10)
17
>>> solution(100)
109
>>> solution(1000)
1017
"""
divisor = limit - 1
if divisor % 2 == 0:
divisor += 1
while least_divisible_repunit(divisor) <= limit:
divisor += 2
return divisor
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 129: https://projecteuler.net/problem=129
A number consisting entirely of ones is called a repunit. We shall define R(k) to be
a repunit of length k; for example, R(6) = 111111.
Given that n is a positive integer and GCD(n, 10) = 1, it can be shown that there
always exists a value, k, for which R(k) is divisible by n, and let A(n) be the least
such value of k; for example, A(7) = 6 and A(41) = 5.
The least value of n for which A(n) first exceeds ten is 17.
Find the least value of n for which A(n) first exceeds one-million.
"""
def least_divisible_repunit(divisor: int) -> int:
"""
Return the least value k such that the Repunit of length k is divisible by divisor.
>>> least_divisible_repunit(7)
6
>>> least_divisible_repunit(41)
5
>>> least_divisible_repunit(1234567)
34020
"""
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
repunit = 1
repunit_index = 1
while repunit:
repunit = (10 * repunit + 1) % divisor
repunit_index += 1
return repunit_index
def solution(limit: int = 1000000) -> int:
"""
Return the least value of n for which least_divisible_repunit(n)
first exceeds limit.
>>> solution(10)
17
>>> solution(100)
109
>>> solution(1000)
1017
"""
divisor = limit - 1
if divisor % 2 == 0:
divisor += 1
while least_divisible_repunit(divisor) <= limit:
divisor += 2
return divisor
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
* Author: Manuel Di Lullo (https://github.com/manueldilullo)
* Description: Random graphs generator.
Uses graphs represented with an adjacency list.
URL: https://en.wikipedia.org/wiki/Random_graph
"""
import random
def random_graph(
vertices_number: int, probability: float, directed: bool = False
) -> dict:
"""
Generate a random graph
@input: vertices_number (number of vertices),
probability (probability that a generic edge (u,v) exists),
directed (if True: graph will be a directed graph,
otherwise it will be an undirected graph)
@examples:
>>> random.seed(1)
>>> random_graph(4, 0.5)
{0: [1], 1: [0, 2, 3], 2: [1, 3], 3: [1, 2]}
>>> random.seed(1)
>>> random_graph(4, 0.5, True)
{0: [1], 1: [2, 3], 2: [3], 3: []}
"""
graph: dict = {i: [] for i in range(vertices_number)}
# if probability is greater or equal than 1, then generate a complete graph
if probability >= 1:
return complete_graph(vertices_number)
# if probability is lower or equal than 0, then return a graph without edges
if probability <= 0:
return graph
# for each couple of nodes, add an edge from u to v
# if the number randomly generated is greater than probability probability
for i in range(vertices_number):
for j in range(i + 1, vertices_number):
if random.random() < probability:
graph[i].append(j)
if not directed:
# if the graph is undirected, add an edge in from j to i, either
graph[j].append(i)
return graph
def complete_graph(vertices_number: int) -> dict:
"""
Generate a complete graph with vertices_number vertices.
@input: vertices_number (number of vertices),
directed (False if the graph is undirected, True otherwise)
@example:
>>> print(complete_graph(3))
{0: [1, 2], 1: [0, 2], 2: [0, 1]}
"""
return {
i: [j for j in range(vertices_number) if i != j] for i in range(vertices_number)
}
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
* Author: Manuel Di Lullo (https://github.com/manueldilullo)
* Description: Random graphs generator.
Uses graphs represented with an adjacency list.
URL: https://en.wikipedia.org/wiki/Random_graph
"""
import random
def random_graph(
vertices_number: int, probability: float, directed: bool = False
) -> dict:
"""
Generate a random graph
@input: vertices_number (number of vertices),
probability (probability that a generic edge (u,v) exists),
directed (if True: graph will be a directed graph,
otherwise it will be an undirected graph)
@examples:
>>> random.seed(1)
>>> random_graph(4, 0.5)
{0: [1], 1: [0, 2, 3], 2: [1, 3], 3: [1, 2]}
>>> random.seed(1)
>>> random_graph(4, 0.5, True)
{0: [1], 1: [2, 3], 2: [3], 3: []}
"""
graph: dict = {i: [] for i in range(vertices_number)}
# if probability is greater or equal than 1, then generate a complete graph
if probability >= 1:
return complete_graph(vertices_number)
# if probability is lower or equal than 0, then return a graph without edges
if probability <= 0:
return graph
# for each couple of nodes, add an edge from u to v
# if the number randomly generated is greater than probability probability
for i in range(vertices_number):
for j in range(i + 1, vertices_number):
if random.random() < probability:
graph[i].append(j)
if not directed:
# if the graph is undirected, add an edge in from j to i, either
graph[j].append(i)
return graph
def complete_graph(vertices_number: int) -> dict:
"""
Generate a complete graph with vertices_number vertices.
@input: vertices_number (number of vertices),
directed (False if the graph is undirected, True otherwise)
@example:
>>> print(complete_graph(3))
{0: [1, 2], 1: [0, 2], 2: [0, 1]}
"""
return {
i: [j for j in range(vertices_number) if i != j] for i in range(vertices_number)
}
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| B64_CHARSET = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def base64_encode(data: bytes) -> bytes:
"""Encodes data according to RFC4648.
The data is first transformed to binary and appended with binary digits so that its
length becomes a multiple of 6, then each 6 binary digits will match a character in
the B64_CHARSET string. The number of appended binary digits would later determine
how many "=" signs should be added, the padding.
For every 2 binary digits added, a "=" sign is added in the output.
We can add any binary digits to make it a multiple of 6, for instance, consider the
following example:
"AA" -> 0010100100101001 -> 001010 010010 1001
As can be seen above, 2 more binary digits should be added, so there's 4
possibilities here: 00, 01, 10 or 11.
That being said, Base64 encoding can be used in Steganography to hide data in these
appended digits.
>>> from base64 import b64encode
>>> a = b"This pull request is part of Hacktoberfest20!"
>>> b = b"https://tools.ietf.org/html/rfc4648"
>>> c = b"A"
>>> base64_encode(a) == b64encode(a)
True
>>> base64_encode(b) == b64encode(b)
True
>>> base64_encode(c) == b64encode(c)
True
>>> base64_encode("abc")
Traceback (most recent call last):
...
TypeError: a bytes-like object is required, not 'str'
"""
# Make sure the supplied data is a bytes-like object
if not isinstance(data, bytes):
raise TypeError(
f"a bytes-like object is required, not '{data.__class__.__name__}'"
)
binary_stream = "".join(bin(byte)[2:].zfill(8) for byte in data)
padding_needed = len(binary_stream) % 6 != 0
if padding_needed:
# The padding that will be added later
padding = b"=" * ((6 - len(binary_stream) % 6) // 2)
# Append binary_stream with arbitrary binary digits (0's by default) to make its
# length a multiple of 6.
binary_stream += "0" * (6 - len(binary_stream) % 6)
else:
padding = b""
# Encode every 6 binary digits to their corresponding Base64 character
return (
"".join(
B64_CHARSET[int(binary_stream[index : index + 6], 2)]
for index in range(0, len(binary_stream), 6)
).encode()
+ padding
)
def base64_decode(encoded_data: str) -> bytes:
"""Decodes data according to RFC4648.
This does the reverse operation of base64_encode.
We first transform the encoded data back to a binary stream, take off the
previously appended binary digits according to the padding, at this point we
would have a binary stream whose length is multiple of 8, the last step is
to convert every 8 bits to a byte.
>>> from base64 import b64decode
>>> a = "VGhpcyBwdWxsIHJlcXVlc3QgaXMgcGFydCBvZiBIYWNrdG9iZXJmZXN0MjAh"
>>> b = "aHR0cHM6Ly90b29scy5pZXRmLm9yZy9odG1sL3JmYzQ2NDg="
>>> c = "QQ=="
>>> base64_decode(a) == b64decode(a)
True
>>> base64_decode(b) == b64decode(b)
True
>>> base64_decode(c) == b64decode(c)
True
>>> base64_decode("abc")
Traceback (most recent call last):
...
AssertionError: Incorrect padding
"""
# Make sure encoded_data is either a string or a bytes-like object
if not isinstance(encoded_data, bytes) and not isinstance(encoded_data, str):
raise TypeError(
"argument should be a bytes-like object or ASCII string, not "
f"'{encoded_data.__class__.__name__}'"
)
# In case encoded_data is a bytes-like object, make sure it contains only
# ASCII characters so we convert it to a string object
if isinstance(encoded_data, bytes):
try:
encoded_data = encoded_data.decode("utf-8")
except UnicodeDecodeError:
raise ValueError("base64 encoded data should only contain ASCII characters")
padding = encoded_data.count("=")
# Check if the encoded string contains non base64 characters
if padding:
assert all(
char in B64_CHARSET for char in encoded_data[:-padding]
), "Invalid base64 character(s) found."
else:
assert all(
char in B64_CHARSET for char in encoded_data
), "Invalid base64 character(s) found."
# Check the padding
assert len(encoded_data) % 4 == 0 and padding < 3, "Incorrect padding"
if padding:
# Remove padding if there is one
encoded_data = encoded_data[:-padding]
binary_stream = "".join(
bin(B64_CHARSET.index(char))[2:].zfill(6) for char in encoded_data
)[: -padding * 2]
else:
binary_stream = "".join(
bin(B64_CHARSET.index(char))[2:].zfill(6) for char in encoded_data
)
data = [
int(binary_stream[index : index + 8], 2)
for index in range(0, len(binary_stream), 8)
]
return bytes(data)
if __name__ == "__main__":
import doctest
doctest.testmod()
| B64_CHARSET = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def base64_encode(data: bytes) -> bytes:
"""Encodes data according to RFC4648.
The data is first transformed to binary and appended with binary digits so that its
length becomes a multiple of 6, then each 6 binary digits will match a character in
the B64_CHARSET string. The number of appended binary digits would later determine
how many "=" signs should be added, the padding.
For every 2 binary digits added, a "=" sign is added in the output.
We can add any binary digits to make it a multiple of 6, for instance, consider the
following example:
"AA" -> 0010100100101001 -> 001010 010010 1001
As can be seen above, 2 more binary digits should be added, so there's 4
possibilities here: 00, 01, 10 or 11.
That being said, Base64 encoding can be used in Steganography to hide data in these
appended digits.
>>> from base64 import b64encode
>>> a = b"This pull request is part of Hacktoberfest20!"
>>> b = b"https://tools.ietf.org/html/rfc4648"
>>> c = b"A"
>>> base64_encode(a) == b64encode(a)
True
>>> base64_encode(b) == b64encode(b)
True
>>> base64_encode(c) == b64encode(c)
True
>>> base64_encode("abc")
Traceback (most recent call last):
...
TypeError: a bytes-like object is required, not 'str'
"""
# Make sure the supplied data is a bytes-like object
if not isinstance(data, bytes):
raise TypeError(
f"a bytes-like object is required, not '{data.__class__.__name__}'"
)
binary_stream = "".join(bin(byte)[2:].zfill(8) for byte in data)
padding_needed = len(binary_stream) % 6 != 0
if padding_needed:
# The padding that will be added later
padding = b"=" * ((6 - len(binary_stream) % 6) // 2)
# Append binary_stream with arbitrary binary digits (0's by default) to make its
# length a multiple of 6.
binary_stream += "0" * (6 - len(binary_stream) % 6)
else:
padding = b""
# Encode every 6 binary digits to their corresponding Base64 character
return (
"".join(
B64_CHARSET[int(binary_stream[index : index + 6], 2)]
for index in range(0, len(binary_stream), 6)
).encode()
+ padding
)
def base64_decode(encoded_data: str) -> bytes:
"""Decodes data according to RFC4648.
This does the reverse operation of base64_encode.
We first transform the encoded data back to a binary stream, take off the
previously appended binary digits according to the padding, at this point we
would have a binary stream whose length is multiple of 8, the last step is
to convert every 8 bits to a byte.
>>> from base64 import b64decode
>>> a = "VGhpcyBwdWxsIHJlcXVlc3QgaXMgcGFydCBvZiBIYWNrdG9iZXJmZXN0MjAh"
>>> b = "aHR0cHM6Ly90b29scy5pZXRmLm9yZy9odG1sL3JmYzQ2NDg="
>>> c = "QQ=="
>>> base64_decode(a) == b64decode(a)
True
>>> base64_decode(b) == b64decode(b)
True
>>> base64_decode(c) == b64decode(c)
True
>>> base64_decode("abc")
Traceback (most recent call last):
...
AssertionError: Incorrect padding
"""
# Make sure encoded_data is either a string or a bytes-like object
if not isinstance(encoded_data, bytes) and not isinstance(encoded_data, str):
raise TypeError(
"argument should be a bytes-like object or ASCII string, not "
f"'{encoded_data.__class__.__name__}'"
)
# In case encoded_data is a bytes-like object, make sure it contains only
# ASCII characters so we convert it to a string object
if isinstance(encoded_data, bytes):
try:
encoded_data = encoded_data.decode("utf-8")
except UnicodeDecodeError:
raise ValueError("base64 encoded data should only contain ASCII characters")
padding = encoded_data.count("=")
# Check if the encoded string contains non base64 characters
if padding:
assert all(
char in B64_CHARSET for char in encoded_data[:-padding]
), "Invalid base64 character(s) found."
else:
assert all(
char in B64_CHARSET for char in encoded_data
), "Invalid base64 character(s) found."
# Check the padding
assert len(encoded_data) % 4 == 0 and padding < 3, "Incorrect padding"
if padding:
# Remove padding if there is one
encoded_data = encoded_data[:-padding]
binary_stream = "".join(
bin(B64_CHARSET.index(char))[2:].zfill(6) for char in encoded_data
)[: -padding * 2]
else:
binary_stream = "".join(
bin(B64_CHARSET.index(char))[2:].zfill(6) for char in encoded_data
)
data = [
int(binary_stream[index : index + 8], 2)
for index in range(0, len(binary_stream), 8)
]
return bytes(data)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 1: https://projecteuler.net/problem=1
Multiples of 3 and 5
If we list all the natural numbers below 10 that are multiples of 3 or 5,
we get 3, 5, 6 and 9. The sum of these multiples is 23.
Find the sum of all the multiples of 3 or 5 below 1000.
"""
def solution(n: int = 1000) -> int:
"""
This solution is based on the pattern that the successive numbers in the
series follow: 0+3,+2,+1,+3,+1,+2,+3.
Returns the sum of all the multiples of 3 or 5 below n.
>>> solution(3)
0
>>> solution(4)
3
>>> solution(10)
23
>>> solution(600)
83700
"""
total = 0
num = 0
while 1:
num += 3
if num >= n:
break
total += num
num += 2
if num >= n:
break
total += num
num += 1
if num >= n:
break
total += num
num += 3
if num >= n:
break
total += num
num += 1
if num >= n:
break
total += num
num += 2
if num >= n:
break
total += num
num += 3
if num >= n:
break
total += num
return total
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 1: https://projecteuler.net/problem=1
Multiples of 3 and 5
If we list all the natural numbers below 10 that are multiples of 3 or 5,
we get 3, 5, 6 and 9. The sum of these multiples is 23.
Find the sum of all the multiples of 3 or 5 below 1000.
"""
def solution(n: int = 1000) -> int:
"""
This solution is based on the pattern that the successive numbers in the
series follow: 0+3,+2,+1,+3,+1,+2,+3.
Returns the sum of all the multiples of 3 or 5 below n.
>>> solution(3)
0
>>> solution(4)
3
>>> solution(10)
23
>>> solution(600)
83700
"""
total = 0
num = 0
while 1:
num += 3
if num >= n:
break
total += num
num += 2
if num >= n:
break
total += num
num += 1
if num >= n:
break
total += num
num += 3
if num >= n:
break
total += num
num += 1
if num >= n:
break
total += num
num += 2
if num >= n:
break
total += num
num += 3
if num >= n:
break
total += num
return total
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 7,338 | Add `flake8-broken-line` to `pre-commit` | ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| CaedenPH | "2022-10-16T19:46:34Z" | "2022-10-16T19:50:48Z" | b5b1eb2f00f942955217ef6968fe8016476690ba | 6d20e2b750839d978873f6a89ce6d844ba3cc0b8 | Add `flake8-broken-line` to `pre-commit`. ### Describe your change:
Add `flake8-broken-line` to `pre-commit` and fix errors
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### Checklist:
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Finding longest distance in Directed Acyclic Graph using KahnsAlgorithm
def longest_distance(graph):
indegree = [0] * len(graph)
queue = []
long_dist = [1] * len(graph)
for values in graph.values():
for i in values:
indegree[i] += 1
for i in range(len(indegree)):
if indegree[i] == 0:
queue.append(i)
while queue:
vertex = queue.pop(0)
for x in graph[vertex]:
indegree[x] -= 1
if long_dist[vertex] + 1 > long_dist[x]:
long_dist[x] = long_dist[vertex] + 1
if indegree[x] == 0:
queue.append(x)
print(max(long_dist))
# Adjacency list of Graph
graph = {0: [2, 3, 4], 1: [2, 7], 2: [5], 3: [5, 7], 4: [7], 5: [6], 6: [7], 7: []}
longest_distance(graph)
| # Finding longest distance in Directed Acyclic Graph using KahnsAlgorithm
def longest_distance(graph):
indegree = [0] * len(graph)
queue = []
long_dist = [1] * len(graph)
for values in graph.values():
for i in values:
indegree[i] += 1
for i in range(len(indegree)):
if indegree[i] == 0:
queue.append(i)
while queue:
vertex = queue.pop(0)
for x in graph[vertex]:
indegree[x] -= 1
if long_dist[vertex] + 1 > long_dist[x]:
long_dist[x] = long_dist[vertex] + 1
if indegree[x] == 0:
queue.append(x)
print(max(long_dist))
# Adjacency list of Graph
graph = {0: [2, 3, 4], 1: [2, 7], 2: [5], 3: [5, 7], 4: [7], 5: [6], 6: [7], 7: []}
longest_distance(graph)
| -1 |
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