



"""simple docstring"""
import colorsys

from PIL import Image  # type: ignore


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase							) ->						float:







  '''simple docstring'''


  lowercase_								= x
  lowercase_								= y
  for step in range(__lowerCAmelCase							):  # noqa: B007
    lowercase_								= a * a - b * b + x
    lowercase_								= 2 * a * b + y
    lowercase_								= a_new

    # divergence happens for all complex number with an absolute value
    # greater than 4
    if a * a + b * b > 4:
      break
  return step / (max_step - 1)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase							) ->						tuple:







  '''simple docstring'''


  if distance == 1:
    return (0, 0, 0)
  else:
    return (2_55, 2_55, 2_55)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase							) ->						tuple:







  '''simple docstring'''


  if distance == 1:
    return (0, 0, 0)
  else:
    return tuple(round(i * 2_55							) for i in colorsys.hsv_to_rgb(__lowerCAmelCase ,  1 ,  1							)							)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase = 8_00 ,  __lowerCAmelCase = 6_00 ,  __lowerCAmelCase = -0.6 ,  __lowerCAmelCase = 0 ,  __lowerCAmelCase = 3.2 ,  __lowerCAmelCase = 50 ,  __lowerCAmelCase = True ,  ) ->						Image.Image:







  '''simple docstring'''


  lowercase_								= Image.new("""RGB""" ,  (image_width, image_height)							)
  lowercase_								= img.load()

  # loop through the image-coordinates
  for image_x in range(__lowerCAmelCase							):
    for image_y in range(__lowerCAmelCase							):
      # determine the figure-coordinates based on the image-coordinates
      lowercase_								= figure_width / image_width * image_height
      lowercase_								= figure_center_x + (image_x / image_width - 0.5) * figure_width
      lowercase_								= figure_center_y + (image_y / image_height - 0.5) * figure_height

      lowercase_								= get_distance(__lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase							)

      # color the corresponding pixel based on the selected coloring-function
      if use_distance_color_coding:
        lowercase_								= get_color_coded_rgb(__lowerCAmelCase							)
      else:
        lowercase_								= get_black_and_white_rgb(__lowerCAmelCase							)

  return img


if __name__ == "__main__":
       import doctest

       doctest.testmod()

       # colored version, full figure
       UpperCAmelCase						:		Any			= get_image()

       # uncomment for colored version, different section, zoomed in
       # img = get_image(figure_center_x = -0.6, figure_center_y = -0.4,
       # figure_width = 0.8)

       # uncomment for black and white version, full figure
       # img = get_image(use_distance_color_coding = False)

       # uncomment to save the image
       # img.save("mandelbrot.png")

       img.show()






"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase						:		Optional[Any]			= {"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		str			= [
           "WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST",
           "WavLMForAudioFrameClassification",
           "WavLMForCTC",
           "WavLMForSequenceClassification",
           "WavLMForXVector",
           "WavLMModel",
           "WavLMPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_wavlm import (
                  WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
                  WavLMForAudioFrameClassification,
                  WavLMForCTC,
                  WavLMForSequenceClassification,
                  WavLMForXVector,
                  WavLMModel,
                  WavLMPreTrainedModel,
              )

else:
       import sys

       UpperCAmelCase						:		Optional[Any]			= _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

