

import colorsys

from PIL import Image  # type: ignore


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		float ,   _SCREAMING_SNAKE_CASE					:		float ,   _SCREAMING_SNAKE_CASE					:		int       ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						x
    SCREAMING_SNAKE_CASE_									=						y
    for step in range(_SCREAMING_SNAKE_CASE       ):  # noqa: B007
        SCREAMING_SNAKE_CASE_									=						a * a - b * b + x
        SCREAMING_SNAKE_CASE_									=						2 * a * b + y
        SCREAMING_SNAKE_CASE_									=						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 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		float       ):





    """simple docstring"""


    if distance == 1:
        return (0, 0, 0)
    else:
        return (255, 255, 255)


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		float       ):





    """simple docstring"""


    if distance == 1:
        return (0, 0, 0)
    else:
        return tuple(round(i * 255       ) for i in colorsys.hsv_to_rgb(_SCREAMING_SNAKE_CASE ,   1 ,   1       )       )


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		int = 800 ,   _SCREAMING_SNAKE_CASE					:		int = 600 ,   _SCREAMING_SNAKE_CASE					:		float = -0.6 ,   _SCREAMING_SNAKE_CASE					:		float = 0 ,   _SCREAMING_SNAKE_CASE					:		float = 3.2 ,   _SCREAMING_SNAKE_CASE					:		int = 50 ,   _SCREAMING_SNAKE_CASE					:		bool = True ,   ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						Image.new('RGB' ,   (image_width, image_height)       )
    SCREAMING_SNAKE_CASE_									=						img.load()

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

            SCREAMING_SNAKE_CASE_									=						get_distance(_SCREAMING_SNAKE_CASE ,   _SCREAMING_SNAKE_CASE ,   _SCREAMING_SNAKE_CASE       )

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

    return img


if __name__ == "__main__":
       import doctest

       doctest.testmod()

       # colored version, full figure
       UpperCamelCase__  :      List[str]			=    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()





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCamelCase__  :      Any			=    {
    "configuration_mvp": ["MVP_PRETRAINED_CONFIG_ARCHIVE_MAP", "MvpConfig", "MvpOnnxConfig"],
    "tokenization_mvp": ["MvpTokenizer"],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__  :      Optional[int]			=    ["MvpTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__  :      str			=    [
           "MVP_PRETRAINED_MODEL_ARCHIVE_LIST",
           "MvpForCausalLM",
           "MvpForConditionalGeneration",
           "MvpForQuestionAnswering",
           "MvpForSequenceClassification",
           "MvpModel",
           "MvpPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
       from .tokenization_mvp import MvpTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_mvp_fast import MvpTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_mvp import (
                  MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  MvpForCausalLM,
                  MvpForConditionalGeneration,
                  MvpForQuestionAnswering,
                  MvpForSequenceClassification,
                  MvpModel,
                  MvpPreTrainedModel,
              )

else:
       import sys

       UpperCamelCase__  :      Dict			=    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


