




from __future__ import annotations

from collections.abc import Iterator
from typing import Any


class        UpperCamelCase_					:

    '''simple docstring'''






    def __init__(    self   :			Tuple      ,				UpperCAmelCase__   :			Any)		->str:





           '''simple docstring'''

           A__   				=					data
           A__   				=					None


class        UpperCamelCase_					:

    '''simple docstring'''






    def __init__(    self   :			int)		->Any:





           '''simple docstring'''

           A__   				=					None
           A__   				=					None


    def __iter__(    self   :			Union[str, Any])		->Iterator[Any]:





           '''simple docstring'''

           A__   				=					self.head
           while self.head:
                  yield node.data
                  A__   				=					node.next
                  if node == self.head:
                         break


    def __len__(    self   :			Any)		->int:





           '''simple docstring'''

           return sum(1 for _ in self)


    def __repr__(    self   :			Optional[Any])		->Optional[int]:





           '''simple docstring'''

           return "->".join(str(UpperCAmelCase__) for item in iter(self))


    def  SCREAMING_SNAKE_CASE							(    self   :			List[str]      ,				UpperCAmelCase__   :			Any)		->None:





           '''simple docstring'''

           self.insert_nth(len(self)      ,				UpperCAmelCase__)


    def  SCREAMING_SNAKE_CASE							(    self   :			List[Any]      ,				UpperCAmelCase__   :			Any)		->None:





           '''simple docstring'''

           self.insert_nth(0      ,				UpperCAmelCase__)


    def  SCREAMING_SNAKE_CASE							(    self   :			Optional[Any]      ,				UpperCAmelCase__   :			int      ,				UpperCAmelCase__   :			Any)		->None:





           '''simple docstring'''

           if index < 0 or index > len(self):
                  raise IndexError('''list index out of range.''')
           A__   				=					Node(UpperCAmelCase__)
           if self.head is None:
                  A__   				=					new_node  # first node points itself
                  A__   				=					A__   				=					new_node
           elif index == 0:  # insert at head
                  A__   				=					self.head
                  A__   				=					A__   				=					new_node
           else:
                  A__   				=					self.head
                  for _ in range(index - 1):
                         A__   				=					temp.next
                  A__   				=					temp.next
                  A__   				=					new_node
                  if index == len(self) - 1:  # insert at tail
                         A__   				=					new_node


    def  SCREAMING_SNAKE_CASE							(    self   :			Tuple)		->int:





           '''simple docstring'''

           return self.delete_nth(0)


    def  SCREAMING_SNAKE_CASE							(    self   :			List[str])		->Any:





           '''simple docstring'''

           return self.delete_nth(len(self) - 1)


    def  SCREAMING_SNAKE_CASE							(    self   :			Optional[int]      ,				UpperCAmelCase__   :			int = 0)		->Any:





           '''simple docstring'''

           if not 0 <= index < len(self):
                  raise IndexError('''list index out of range.''')
           A__   				=					self.head
           if self.head == self.tail:  # just one node
                  A__   				=					A__   				=					None
           elif index == 0:  # delete head node
                  A__   				=					self.tail.next.next
                  A__   				=					self.head.next
           else:
                  A__   				=					self.head
                  for _ in range(index - 1):
                         A__   				=					temp.next
                  A__   				=					temp.next
                  A__   				=					temp.next.next
                  if index == len(self) - 1:  # delete at tail
                         A__   				=					temp
           return delete_node.data





    def  SCREAMING_SNAKE_CASE							(    self   :			int)		->bool:





           '''simple docstring'''

           return len(self) == 0







def SCREAMING_SNAKE_CASE       ( )     -> None:



       """simple docstring"""

       A__   				=					CircularLinkedList()
       assert len(lowercase_		) == 0
       assert circular_linked_list.is_empty() is True
       assert str(lowercase_		) == ""

       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(lowercase_		) == i
              circular_linked_list.insert_nth(lowercase_				,       i + 1		)
       assert str(lowercase_		) == "->".join(str(lowercase_		) for i in range(1				,       6		)		)

       circular_linked_list.insert_tail(6		)
       assert str(lowercase_		) == "->".join(str(lowercase_		) for i in range(1				,       7		)		)
       circular_linked_list.insert_head(0		)
       assert str(lowercase_		) == "->".join(str(lowercase_		) for i in range(0				,       7		)		)

       assert circular_linked_list.delete_front() == 0
       assert circular_linked_list.delete_tail() == 6
       assert str(lowercase_		) == "->".join(str(lowercase_		) for i in range(1				,       6		)		)
       assert circular_linked_list.delete_nth(2		) == 3

       circular_linked_list.insert_nth(2				,       3		)
       assert str(lowercase_		) == "->".join(str(lowercase_		) for i in range(1				,       6		)		)

       assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
  import doctest

  doctest.testmod()








# Logistic Regression from scratch

# In[62]:

# In[63]:

# importing all the required libraries

import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets







def SCREAMING_SNAKE_CASE       ( lowercase_		)     -> Dict:



       """simple docstring"""

       return 1 / (1 + np.exp(-z		))







def SCREAMING_SNAKE_CASE       ( lowercase_				,       lowercase_		)     -> Optional[int]:



       """simple docstring"""

       return (-y * np.log(lowercase_		) - (1 - y) * np.log(1 - h		)).mean()







def SCREAMING_SNAKE_CASE       ( lowercase_				,       lowercase_				,       lowercase_		)     -> int:



       """simple docstring"""

       A__   				=					np.dot(lowercase_				,       lowercase_		)
       return np.sum(y * scores - np.log(1 + np.exp(lowercase_		)		)		)







def SCREAMING_SNAKE_CASE       ( lowercase_				,       lowercase_				,       lowercase_				,       lowercase_=70_000		)     -> Dict:



       """simple docstring"""

       A__   				=					np.zeros(x.shape[1]		)

       for iterations in range(lowercase_		):
              A__   				=					np.dot(lowercase_				,       lowercase_		)
              A__   				=					sigmoid_function(lowercase_		)
              A__   				=					np.dot(x.T				,       h - y		) / y.size
              A__   				=					theta - alpha * gradient  # updating the weights
              A__   				=					np.dot(lowercase_				,       lowercase_		)
              A__   				=					sigmoid_function(lowercase_		)
              A__   				=					cost_function(lowercase_				,       lowercase_		)
              if iterations % 100 == 0:
                     print(f"""loss: {j} \t"""		)  # printing the loss after every 100 iterations
       return theta


# In[68]:

if __name__ == "__main__":
  _lowerCamelCase			:	str							 =     datasets.load_iris()
  _lowerCamelCase			:	Any							 =     iris.data[:, :2]
  _lowerCamelCase			:	Dict							 =     (iris.target != 0) * 1

  _lowerCamelCase			:	Union[str, Any]							 =     0.1
  _lowerCamelCase			:	Tuple							 =     logistic_reg(alpha, x, y, max_iterations=70000)
  print("""theta: """, theta)  # printing the theta i.e our weights vector







  def SCREAMING_SNAKE_CASE       ( lowercase_		)     -> List[Any]:



         """simple docstring"""

         return sigmoid_function(
             np.dot(lowercase_				,       lowercase_		)		)  # predicting the value of probability from the logistic regression algorithm

  plt.figure(figsize=(10, 6))
  plt.scatter(x[y == 0][:, 0], x[y == 0][:, 1], color="""b""", label="""0""")
  plt.scatter(x[y == 1][:, 0], x[y == 1][:, 1], color="""r""", label="""1""")
  ((_lowerCamelCase) ,    (_lowerCamelCase))			:	int							 =     (x[:, 0].min(), x[:, 0].max())
  ((_lowerCamelCase) ,    (_lowerCamelCase))			:	Union[str, Any]							 =     (x[:, 1].min(), x[:, 1].max())
  ((_lowerCamelCase) ,    (_lowerCamelCase))			:	List[Any]							 =     np.meshgrid(np.linspace(xa_min, xa_max), np.linspace(xa_min, xa_max))
  _lowerCamelCase			:	str							 =     np.c_[xxa.ravel(), xxa.ravel()]
  _lowerCamelCase			:	Tuple							 =     predict_prob(grid).reshape(xxa.shape)
  plt.contour(xxa, xxa, probs, [0.5], linewidths=1, colors="""black""")

  plt.legend()
  plt.show()


