


'''simple docstring'''






import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image

from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_processing.dithering import burkes as bs
from digital_image_processing.edge_detection import canny
from digital_image_processing.filters import convolve as conv
from digital_image_processing.filters import gaussian_filter as gg
from digital_image_processing.filters import local_binary_pattern as lbp
from digital_image_processing.filters import median_filter as med
from digital_image_processing.filters import sobel_filter as sob
from digital_image_processing.resize import resize as rs

a_					:    Dict          =    imread(R"digital_image_processing/image_data/lena_small.jpg")
a_					:    Union[str, Any]          =    cvtColor(img, COLOR_BGR2GRAY)






def 	_A				()   ->  List[str]:




     '''simple docstring'''



     _a			      =							cn.convert_to_negative(__UpperCamelCase		)
     # assert negative_img array for at least one True
     assert negative_img.any()






def 	_A				()   ->  Tuple:




     '''simple docstring'''



     with Image.open('digital_image_processing/image_data/lena_small.jpg'		) as img:
          # Work around assertion for response
          assert str(cc.change_contrast(__UpperCamelCase				,						1_10		)		).startswith(
              '<PIL.Image.Image image mode=RGB size=100x100 at'		)






def 	_A				()   ->  Optional[int]:




     '''simple docstring'''



     _a			      =							canny.gen_gaussian_kernel(9				,						sigma=1.4		)
     # Assert ambiguous array
     assert resp.all()






def 	_A				()   ->  Any:




     '''simple docstring'''



     _a			      =							imread('digital_image_processing/image_data/lena_small.jpg'				,						0		)
     # assert ambiguous array for all == True
     assert canny_img.all()
     _a			      =							canny.canny(__UpperCamelCase		)
     # assert canny array for at least one True
     assert canny_array.any()






def 	_A				()   ->  List[str]:




     '''simple docstring'''



     assert gg.gaussian_filter(__UpperCamelCase				,						5				,						sigma=0.9		).all()






def 	_A				()   ->  Optional[int]:




     '''simple docstring'''



     _a			      =							array([[0.2_5, 0.5, 0.2_5], [0.5, -3, 0.5], [0.2_5, 0.5, 0.2_5]]		)
     _a			      =							conv.img_convolve(__UpperCamelCase				,						__UpperCamelCase		).astype(__UpperCamelCase		)
     assert res.any()






def 	_A				()   ->  Any:




     '''simple docstring'''



     assert med.median_filter(__UpperCamelCase				,						3		).any()






def 	_A				()   ->  Optional[Any]:




     '''simple docstring'''



     _a      ,   _a			      =							sob.sobel_filter(__UpperCamelCase		)
     assert grad.any() and theta.any()






def 	_A				()   ->  Dict:




     '''simple docstring'''



     _a			      =							sp.make_sepia(__UpperCamelCase				,						20		)
     assert sepia.all()






def 	_A				(lowerCAmelCase__  :Optional[Any] = "digital_image_processing/image_data/lena_small.jpg"		)   ->  Optional[int]:




     '''simple docstring'''



     _a			      =							bs.Burkes(imread(__UpperCamelCase				,						1		)				,						1_20		)
     burkes.process()
     assert burkes.output_img.any()






def 	_A				(lowerCAmelCase__  :List[Any] = "digital_image_processing/image_data/lena_small.jpg"				,						)   ->  Optional[int]:




     '''simple docstring'''



     _a			      =							rs.NearestNeighbour(imread(__UpperCamelCase				,						1		)				,						4_00				,						2_00		)
     nn.process()
     assert nn.output.any()






def 	_A				()   ->  List[str]:




     '''simple docstring'''



     _a			      =							'digital_image_processing/image_data/lena.jpg'

     # Reading the image and converting it to grayscale.
     _a			      =							imread(__UpperCamelCase				,						0		)

     # Test for get_neighbors_pixel function() return not None
     _a			      =							0
     _a			      =							0
     _a			      =							image[x_coordinate][y_coordinate]

     _a			      =							lbp.get_neighbors_pixel(
         __UpperCamelCase				,						__UpperCamelCase				,						__UpperCamelCase				,						__UpperCamelCase		)

     assert neighbors_pixels is not None

     # Test for local_binary_pattern function()
     # Create a numpy array as the same height and width of read image
     _a			      =							np.zeros((image.shape[0], image.shape[1])		)

     # Iterating through the image and calculating the local binary pattern value
     # for each pixel.
     for i in range(0				,						image.shape[0]		):
          for j in range(0				,						image.shape[1]		):
               _a			      =							lbp.local_binary_value(__UpperCamelCase				,						__UpperCamelCase				,						__UpperCamelCase		)

     assert lbp_image.any()





'''simple docstring'''






import numpy as np
import qiskit






def 	_A				(lowerCAmelCase__  :int = 8				,						lowerCAmelCase__  :int | None = None		)   ->  str:




     '''simple docstring'''



     _a			      =							np.random.default_rng(seed=lowerCAmelCase__		)

     # Roughly 25% of the qubits will contribute to the key.
     # So we take more than we need.
     _a			      =							6 * key_len
     # Measurement basis for Alice's qubits.
     _a			      =							rng.integers(2				,						size=lowerCAmelCase__		)
     # The set of states Alice will prepare.
     _a			      =							rng.integers(2				,						size=lowerCAmelCase__		)
     # Measurement basis for Bob's qubits.
     _a			      =							rng.integers(2				,						size=lowerCAmelCase__		)

     # Quantum Circuit to simulate BB84
     _a			      =							qiskit.QuantumCircuit(lowerCAmelCase__				,						name='BB84'		)

     # Alice prepares her qubits according to rules above.
     for index, _ in enumerate(lowerCAmelCase__		):
          if alice_state[index] == 1:
               bbaa_circ.x(lowerCAmelCase__		)
          if alice_basis[index] == 1:
               bbaa_circ.h(lowerCAmelCase__		)
     bbaa_circ.barrier()

     # Bob measures the received qubits according to rules above.
     for index, _ in enumerate(lowerCAmelCase__		):
          if bob_basis[index] == 1:
               bbaa_circ.h(lowerCAmelCase__		)

     bbaa_circ.barrier()
     bbaa_circ.measure_all()

     # Simulate the quantum circuit.
     _a			      =							qiskit.Aer.get_backend('aer_simulator'		)
     # We only need to run one shot because the key is unique.
     # Multiple shots will produce the same key.
     _a			      =							qiskit.execute(lowerCAmelCase__				,						lowerCAmelCase__				,						shots=1				,						seed_simulator=lowerCAmelCase__		)
     # Returns the result of measurement.
     _a			      =							job.result().get_counts(lowerCAmelCase__		).most_frequent()

     # Extracting the generated key from the simulation results.
     # Only keep measurement results where Alice and Bob chose the same basis.
     _a			      =							''.join(
         [
             result_bit
             for alice_basis_bit, bob_basis_bit, result_bit in zip(
                 lowerCAmelCase__				,						lowerCAmelCase__				,						lowerCAmelCase__		)
             if alice_basis_bit == bob_basis_bit
         ]		)

     # Get final key. Pad with 0 if too short, otherwise truncate.
     _a			      =							gen_key[:key_len] if len(lowerCAmelCase__		) >= key_len else gen_key.ljust(lowerCAmelCase__				,						'0'		)
     return key


if __name__ == "__main__":
 print(f'''The generated key is : {bbaa(8, seed=0)}''')
 from doctest import testmod

 testmod()

