"""simple docstring"""
import cva
import numpy as np

from digital_image_processing.filters.convolve import img_convolve
from digital_image_processing.filters.sobel_filter import sobel_filter

lowercase__   			=      180







def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )      ->Union[str, Any]:
  a__:	List[str]     				=      k_size // 2
  a__				,       a__:	Union[str, Any]     				=      np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
  a__:	Tuple     				=      (
      1
      / (2 * np.pi * sigma)
      * np.exp(-(np.square(_SCREAMING_SNAKE_CASE  ) + np.square(_SCREAMING_SNAKE_CASE  )) / (2 * np.square(_SCREAMING_SNAKE_CASE  ))  )
  )
  return g







def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )      ->Optional[int]:
  a__:	Union[str, Any]     				=      np.zeros(_SCREAMING_SNAKE_CASE  )

  for row in range(1						,	image_shape[0] - 1  ):
    for col in range(1						,	image_shape[1] - 1  ):
      a__:	int     				=      gradient_direction[row, col]

      if (
          0 <= direction < PI / 8
          or 15 * PI / 8 <= direction <= 2 * PI
          or 7 * PI / 8 <= direction <= 9 * PI / 8
      ):
        a__:	List[Any]     				=      sobel_grad[row, col - 1]
        a__:	Any     				=      sobel_grad[row, col + 1]
        if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
          a__:	Optional[Any]     				=      sobel_grad[row, col]

      elif (
          PI / 8 <= direction < 3 * PI / 8
          or 9 * PI / 8 <= direction < 11 * PI / 8
      ):
        a__:	Optional[int]     				=      sobel_grad[row + 1, col - 1]
        a__:	int     				=      sobel_grad[row - 1, col + 1]
        if sobel_grad[row, col] >= sw and sobel_grad[row, col] >= ne:
          a__:	int     				=      sobel_grad[row, col]

      elif (
          3 * PI / 8 <= direction < 5 * PI / 8
          or 11 * PI / 8 <= direction < 13 * PI / 8
      ):
        a__:	List[Any]     				=      sobel_grad[row - 1, col]
        a__:	List[str]     				=      sobel_grad[row + 1, col]
        if sobel_grad[row, col] >= n and sobel_grad[row, col] >= s:
          a__:	List[str]     				=      sobel_grad[row, col]

      elif (
          5 * PI / 8 <= direction < 7 * PI / 8
          or 13 * PI / 8 <= direction < 15 * PI / 8
      ):
        a__:	Tuple     				=      sobel_grad[row - 1, col - 1]
        a__:	str     				=      sobel_grad[row + 1, col + 1]
        if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
          a__:	Optional[Any]     				=      sobel_grad[row, col]

  return destination







def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )      ->Any:
  for row in range(1						,	image_shape[0] - 1  ):
    for col in range(1						,	image_shape[1] - 1  ):
      if destination[row, col] >= threshold_high:
        a__:	Union[str, Any]     				=      strong
      elif destination[row, col] <= threshold_low:
        a__:	Dict     				=      0
      else:
        a__:	int     				=      weak







def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )      ->int:
  for row in range(1						,	image_shape[0]  ):
    for col in range(1						,	image_shape[1]  ):
      if destination[row, col] == weak:
        if 255 in (
            destination[row, col + 1],
            destination[row, col - 1],
            destination[row - 1, col],
            destination[row + 1, col],
            destination[row - 1, col - 1],
            destination[row + 1, col - 1],
            destination[row - 1, col + 1],
            destination[row + 1, col + 1],
        ):
          a__:	Optional[int]     				=      strong
        else:
          a__:	List[str]     				=      0







def 		__a  (      _SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE=15						,	_SCREAMING_SNAKE_CASE=30						,	_SCREAMING_SNAKE_CASE=128						,	_SCREAMING_SNAKE_CASE=255  )      ->Tuple:
  # gaussian_filter
  a__:	Union[str, Any]     				=      img_convolve(_SCREAMING_SNAKE_CASE						,	gen_gaussian_kernel(9						,	sigma=1.4  )  )
  # get the gradient and degree by sobel_filter
  a__				,       a__:	Optional[int]     				=      sobel_filter(_SCREAMING_SNAKE_CASE  )
  a__:	Optional[Any]     				=      PI + np.radadeg(_SCREAMING_SNAKE_CASE  )

  a__:	Tuple     				=      suppress_non_maximum(image.shape						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )

  detect_high_low_threshold(
      image.shape						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )

  track_edge(image.shape						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE						,	_SCREAMING_SNAKE_CASE  )

  return destination


if __name__ == "__main__":
 # read original image in gray mode
 lowercase__   			=      cva.imread(r'../image_data/lena.jpg', 0)
 # canny edge detection
 lowercase__   			=      canny(lena)
 cva.imshow('canny', canny_destination)
 cva.waitKey(0)










from dataclasses import dataclass

UpperCamelCase											=      '''0.1'''
UpperCamelCase											=      '''Lucia Harcekova'''




@dataclass
class 	lowerCamelCase__				:
      lowerCamelCase_							:   int
      lowerCamelCase_							:   int
      lowerCamelCase_							:   str






      def __repr__(self					:    Tuple		)       ->   str:


       """simple docstring"""






       return f'({self.offset}, {self.length}, {self.indicator})'




class 	lowerCamelCase__				:






      def __init__(self					:    Optional[int]		,		_snake_case					:    int = 13		,		_snake_case					:    int = 6		)       ->   None:


       """simple docstring"""






       lowerCamelCase_							:    Any							=     window_size
       lowerCamelCase_							:    List[str]							=     lookahead_buffer_size
       lowerCamelCase_							:    Optional[int]							=     self.window_size - self.lookahead_buffer_size






      def      UpperCAmelCase_     (self					:    Tuple		,		_snake_case					:    str		)       ->   list[Token]:


       """simple docstring"""






       lowerCamelCase_							:    Optional[Any]							=     []
       lowerCamelCase_							:    List[str]							=     ''

       # while there are still characters in text to compress
       while text:
        # find the next encoding phrase
        # - triplet with offset, length, indicator (the next encoding character)
        lowerCamelCase_							:    List[Any]							=     self._find_encoding_token(_snake_case		,		_snake_case		)

        # update the search buffer:
        # - add new characters from text into it
        # - check if size exceed the max search buffer size, if so, drop the
        #   oldest elements
        search_buffer += text[: token.length + 1]
        if len(_snake_case		) > self.search_buffer_size:
         lowerCamelCase_							:    int							=     search_buffer[-self.search_buffer_size :]

        # update the text
        lowerCamelCase_							:    str							=     text[token.length + 1 :]

        # append the token to output
        output.append(_snake_case		)

       return output






      def      UpperCAmelCase_     (self					:    Tuple		,		_snake_case					:    list[Token]		)       ->   str:


       """simple docstring"""






       lowerCamelCase_							:    Optional[Any]							=     ''

       for token in tokens:
        for _ in range(token.length		):
         output += output[-token.offset]
        output += token.indicator

       return output






      def      UpperCAmelCase_     (self					:    Dict		,		_snake_case					:    str		,		_snake_case					:    str		)       ->   Token:


       """simple docstring"""






       if not text:
        raise ValueError('We need some text to work with.'		)

       # Initialise result parameters to default values
       lowerCamelCase_		,      lowerCamelCase_							:    List[str]							=     0, 0

       if not search_buffer:
        return Token(_snake_case		,		_snake_case		,		text[length]		)

       for i, character in enumerate(_snake_case		):
        lowerCamelCase_							:    Union[str, Any]							=     len(_snake_case		) - i
        if character == text[0]:
         lowerCamelCase_							:    str							=     self._match_length_from_index(_snake_case		,		_snake_case		,		0		,		_snake_case		)
         # if the found length is bigger than the current or if it's equal,
         # which means it's offset is smaller: update offset and length
         if found_length >= length:
          lowerCamelCase_		,      lowerCamelCase_							:    str							=     found_offset, found_length

       return Token(_snake_case		,		_snake_case		,		text[length]		)






      def      UpperCAmelCase_     (self					:    Any		,		_snake_case					:    str		,		_snake_case					:    str		,		_snake_case					:    int		,		_snake_case					:    int		)       ->   int:


       """simple docstring"""






       if not text or text[text_index] != window[window_index]:
        return 0
       return 1 + self._match_length_from_index(
           _snake_case		,		window + text[text_index]		,		text_index + 1		,		window_index + 1		)


if __name__ == "__main__":
       from doctest import testmod

       testmod()
       # Initialize compressor class
       UpperCamelCase											=      LZaaCompressor(window_size=1_3, lookahead_buffer_size=6)

       # Example
       UpperCamelCase											=      '''cabracadabrarrarrad'''
       UpperCamelCase											=      lzaa_compressor.compress(TEXT)
       print(lzaa_compressor.compress('''ababcbababaa'''))
       UpperCamelCase											=      lzaa_compressor.decompress(compressed_text)
       assert decompressed_text == TEXT, "The LZ77 algorithm returned the invalid result."
