






from __future__ import annotations





def 				snake_case  (     lowerCamelCase				,  lowerCamelCase = None				,  lowerCamelCase = None				,  lowerCamelCase = False				,  ):




	'''simple docstring'''







	__lowercase					       =  cipher_alphabet or [chr(lowerCamelCase					) for i in range(97				,  123					)]

	# If the argument is None or the user provided an empty dictionary
	if not frequencies_dict:
		# Frequencies of letters in the english language (how much they show up)
		__lowercase					       =  {
		    """a""": 0.08497,
		    """b""": 0.01492,
		    """c""": 0.02202,
		    """d""": 0.04253,
		    """e""": 0.11162,
		    """f""": 0.02228,
		    """g""": 0.02015,
		    """h""": 0.06094,
		    """i""": 0.07546,
		    """j""": 0.00153,
		    """k""": 0.01292,
		    """l""": 0.04025,
		    """m""": 0.02406,
		    """n""": 0.06749,
		    """o""": 0.07507,
		    """p""": 0.01929,
		    """q""": 0.00095,
		    """r""": 0.07587,
		    """s""": 0.06327,
		    """t""": 0.09356,
		    """u""": 0.02758,
		    """v""": 0.00978,
		    """w""": 0.02560,
		    """x""": 0.00150,
		    """y""": 0.01994,
		    """z""": 0.00077,
		}
	else:
		# Custom frequencies dictionary
		__lowercase					       =  frequencies_dict

	if not case_sensitive:
		__lowercase					       =  ciphertext.lower()

	# Chi squared statistic values
	__lowercase					       =  {}

	# cycle through all of the shifts
	for shift in range(len(lowerCamelCase					)					):
		__lowercase					       =  """"""

		# decrypt the message with the shift
		for letter in ciphertext:
			try:
				# Try to index the letter in the alphabet
				__lowercase					       =  (alphabet_letters.index(letter.lower()					) - shift) % len(
				    lowerCamelCase					)
				decrypted_with_shift += (
				    alphabet_letters[new_key].upper()
				    if case_sensitive and letter.isupper()
				    else alphabet_letters[new_key]
				)
			except ValueError:
				# Append the character if it isn't in the alphabet
				decrypted_with_shift += letter

		__lowercase					       =  0.0

		# Loop through each letter in the decoded message with the shift
		for letter in decrypted_with_shift:
			if case_sensitive:
				__lowercase					       =  letter.lower()
				if letter in frequencies:
					# Get the amount of times the letter occurs in the message
					__lowercase					       =  decrypted_with_shift.lower().count(lowerCamelCase					)

					# Get the excepcted amount of times the letter should appear based
					# on letter frequencies
					__lowercase					       =  frequencies[letter] * occurrences

					# Complete the chi squared statistic formula
					__lowercase					       =  ((occurrences - expected) ** 2) / expected

					# Add the margin of error to the total chi squared statistic
					chi_squared_statistic += chi_letter_value
			else:
				if letter.lower() in frequencies:
					# Get the amount of times the letter occurs in the message
					__lowercase					       =  decrypted_with_shift.count(lowerCamelCase					)

					# Get the excepcted amount of times the letter should appear based
					# on letter frequencies
					__lowercase					       =  frequencies[letter] * occurrences

					# Complete the chi squared statistic formula
					__lowercase					       =  ((occurrences - expected) ** 2) / expected

					# Add the margin of error to the total chi squared statistic
					chi_squared_statistic += chi_letter_value

        # Add the data to the chi_squared_statistic_values dictionary
		__lowercase					       =  (
		    chi_squared_statistic,
		    decrypted_with_shift,
		)

	# Get the most likely cipher by finding the cipher with the smallest chi squared
	# statistic
	def chi_squared_statistic_values_sorting_key(lowerCamelCase					) -> tuple[float, str]:
		return chi_squared_statistic_values[key]

	__lowercase					       =  min(
	    lowerCamelCase				,  key=lowerCamelCase				,  )

	# Get all the data from the most likely cipher (key, decoded message)
	(
	    (
	    __lowercase						
	)       ,						(
	    __lowercase						
	)       ,												
	)					       =  chi_squared_statistic_values[most_likely_cipher]

	# Return the data on the most likely shift
	return (
	    most_likely_cipher,
	    most_likely_cipher_chi_squared_value,
	    decoded_most_likely_cipher,
	)









import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey





def 				snake_case  (     lowerCamelCase				,  lowerCamelCase				,  lowerCamelCase				,  lowerCamelCase				,  lowerCamelCase				,  lowerCamelCase					):




	'''simple docstring'''







	if (ksize % 2) == 0:
		__lowercase             =  ksize + 1
	__lowercase             =  np.zeros((ksize, ksize)				,  dtype=np.floataa					)

	# each value
	for y in range(lowerCamelCase					):
		for x in range(lowerCamelCase					):
			# distance from center
			__lowercase             =  x - ksize // 2
			__lowercase             =  y - ksize // 2

			# degree to radiant
			__lowercase             =  theta / 180 * np.pi
			__lowercase             =  np.cos(_theta					)
			__lowercase             =  np.sin(_theta					)

			# get kernel x
			__lowercase             =  cos_theta * px + sin_theta * py

			# get kernel y
			__lowercase             =  -sin_theta * px + cos_theta * py

			# fill kernel
			__lowercase             =  np.exp(
			    -(_x**2 + gamma**2 * _y**2) / (2 * sigma**2)					) * np.cos(2 * np.pi * _x / lambd + psi					)

	return gabor


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						# read original image
						__UpperCamelCase      :      List[Any]     						=						imread("""../image_data/lena.jpg""")
						# turn image in gray scale value
						__UpperCamelCase      :      Union[str, Any]     						=						cvtColor(img, COLOR_BGR2GRAY)

						# Apply multiple Kernel to detect edges
						__UpperCamelCase      :      Union[str, Any]     						=						np.zeros(gray.shape[:2])
						for theta in [0, 30, 60, 90, 120, 150]:
												__UpperCamelCase      :      Tuple     						=						gabor_filter_kernel(10, 8, theta, 10, 0, 0)
												out += filteraD(gray, CV_8UC3, kernel_aa)
						__UpperCamelCase      :      List[str]     						=						out / out.max() * 255
						__UpperCamelCase      :      List[str]     						=						out.astype(np.uinta)

						imshow("""Original""", gray)
						imshow("""Gabor filter with 20x20 mask and 6 directions""", out)

						waitKey(0)

