

'''simple docstring'''


import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import numpy as np
import pyarrow as pa

from .. import config
from ..download.streaming_download_manager import xopen
from ..table import array_cast
from ..utils.file_utils import is_local_path
from ..utils.py_utils import first_non_null_value, no_op_if_value_is_null, string_to_dict


if TYPE_CHECKING:
					import PIL.Image

					from .features import FeatureType


lowerCAmelCase__    :							Optional[List[str]]					    =    None
lowerCAmelCase__    :							List[Any]					    =    '''<''' if sys.byteorder == '''little''' else '''>'''
# Origin: https://github.com/python-pillow/Pillow/blob/698951e19e19972aeed56df686868f1329981c12/src/PIL/Image.py#L3126 minus "|i1" which values are not preserved correctly when saving and loading an image
lowerCAmelCase__    :							int					    =    [
    np.dtype("""|b1"""),
    np.dtype("""|u1"""),
    np.dtype("""<u2"""),
    np.dtype(""">u2"""),
    np.dtype("""<i2"""),
    np.dtype(""">i2"""),
    np.dtype("""<u4"""),
    np.dtype(""">u4"""),
    np.dtype("""<i4"""),
    np.dtype(""">i4"""),
    np.dtype("""<f4"""),
    np.dtype(""">f4"""),
    np.dtype("""<f8"""),
    np.dtype(""">f8"""),
]




@dataclass
class      a      :






						"""simple docstring"""




						__UpperCAmelCase        =     True
						__UpperCAmelCase        =     None
						# Automatically constructed
						__UpperCAmelCase        =     "PIL.Image.Image"
						__UpperCAmelCase        =     pa.struct({"""bytes""": pa.binary(), """path""": pa.string()}							)
						__UpperCAmelCase        =     field(default="""Image"""      ,      init=__a      ,      repr=__a							)







						def __call__(				self       :   Union[str, Any]	):



								'''simple docstring'''



								return self.pa_type







						def    __magic_name__				(				self       :   Any      ,      snake_case_       :   Union[str, Any]	):



								'''simple docstring'''



								if config.PIL_AVAILABLE:
										import PIL.Image
								else:
										raise ImportError('''To support encoding images, please install \'Pillow\'.'''	)

								if isinstance(_lowerCamelCase      ,      _lowerCamelCase	):
										snake_case__    :							Any							    =	np.array(_lowerCamelCase	)

								if isinstance(_lowerCamelCase      ,      _lowerCamelCase	):
										return {"path": value, "bytes": None}
								elif isinstance(_lowerCamelCase      ,      _lowerCamelCase	):
										return {"path": None, "bytes": value}
								elif isinstance(_lowerCamelCase      ,      np.ndarray	):
										# convert the image array to PNG/TIFF bytes
										return encode_np_array(_lowerCamelCase	)
								elif isinstance(_lowerCamelCase      ,      PIL.Image.Image	):
										# convert the PIL image to bytes (default format is PNG/TIFF)
										return encode_pil_image(_lowerCamelCase	)
								elif value.get('''path'''	) is not None and os.path.isfile(value['''path''']	):
										# we set "bytes": None to not duplicate the data if they're already available locally
										return {"bytes": None, "path": value.get('''path'''	)}
								elif value.get('''bytes'''	) is not None or value.get('''path'''	) is not None:
										# store the image bytes, and path is used to infer the image format using the file extension
										return {"bytes": value.get('''bytes'''	), "path": value.get('''path'''	)}
								else:
										raise ValueError(
										    F"""An image sample should have one of \'path\' or \'bytes\' but they are missing or None in {value}."""	)







						def    __magic_name__				(				self       :   Tuple      ,      snake_case_       :   Tuple      ,      snake_case_       :   Any=None	):



								'''simple docstring'''



								if not self.decode:
										raise RuntimeError('''Decoding is disabled for this feature. Please use Image(decode=True) instead.'''	)

								if config.PIL_AVAILABLE:
										import PIL.Image
								else:
										raise ImportError('''To support decoding images, please install \'Pillow\'.'''	)

								if token_per_repo_id is None:
										snake_case__    :							Dict							    =	{}

								snake_case__    ,							snake_case__    :							Dict							    =	value['''path'''], value['''bytes''']
								if bytes_ is None:
										if path is None:
												raise ValueError(F"""An image should have one of \'path\' or \'bytes\' but both are None in {value}."""	)
										else:
												if is_local_path(_lowerCamelCase	):
														snake_case__    :							Optional[int]							    =	PIL.Image.open(_lowerCamelCase	)
												else:
														snake_case__    :							Dict							    =	path.split('''::'''	)[-1]
														try:
																snake_case__    :							List[str]							    =	string_to_dict(_lowerCamelCase      ,      config.HUB_DATASETS_URL	)['''repo_id''']
																snake_case__    :							List[str]							    =	token_per_repo_id.get(_lowerCamelCase	)
														except ValueError:
																snake_case__    :							List[Any]							    =	None
														with xopen(_lowerCamelCase      ,      '''rb'''      ,      use_auth_token=_lowerCamelCase	) as f:
																snake_case__    :							Any							    =	BytesIO(f.read()	)
														snake_case__    :							Optional[int]							    =	PIL.Image.open(bytes_	)
								else:
										snake_case__    :							List[Any]							    =	PIL.Image.open(BytesIO(bytes_	)	)
								image.load()  # to avoid "Too many open files" errors
								return image







						def    __magic_name__				(				self       :   Any	):



								'''simple docstring'''



								from .features import Value

								return (
								    self
								    if self.decode
								    else {
								        "bytes": Value('''binary'''	),
								        "path": Value('''string'''	),
								    }
								)







						def    __magic_name__				(				self       :   List[str]      ,      snake_case_       :   Dict	):



								'''simple docstring'''



								if pa.types.is_string(storage.type	):
										snake_case__    :							Union[str, Any]							    =	pa.array([None] * len(_lowerCamelCase	)      ,      type=pa.binary()	)
										snake_case__    :							int							    =	pa.StructArray.from_arrays([bytes_array, storage]      ,      ['''bytes''', '''path''']      ,      mask=storage.is_null()	)
								elif pa.types.is_binary(storage.type	):
										snake_case__    :							Optional[int]							    =	pa.array([None] * len(_lowerCamelCase	)      ,      type=pa.string()	)
										snake_case__    :							List[Any]							    =	pa.StructArray.from_arrays([storage, path_array]      ,      ['''bytes''', '''path''']      ,      mask=storage.is_null()	)
								elif pa.types.is_struct(storage.type	):
										if storage.type.get_field_index('''bytes'''	) >= 0:
												snake_case__    :							List[Any]							    =	storage.field('''bytes'''	)
										else:
												snake_case__    :							str							    =	pa.array([None] * len(_lowerCamelCase	)      ,      type=pa.binary()	)
										if storage.type.get_field_index('''path'''	) >= 0:
												snake_case__    :							Union[str, Any]							    =	storage.field('''path'''	)
										else:
												snake_case__    :							int							    =	pa.array([None] * len(_lowerCamelCase	)      ,      type=pa.string()	)
										snake_case__    :							Optional[int]							    =	pa.StructArray.from_arrays([bytes_array, path_array]      ,      ['''bytes''', '''path''']      ,      mask=storage.is_null()	)
								elif pa.types.is_list(storage.type	):
										snake_case__    :							int							    =	pa.array(
										    [encode_np_array(np.array(_lowerCamelCase	)	)['''bytes'''] if arr is not None else None for arr in storage.to_pylist()]      ,      type=pa.binary()      ,      )
										snake_case__    :							Union[str, Any]							    =	pa.array([None] * len(_lowerCamelCase	)      ,      type=pa.string()	)
										snake_case__    :							Union[str, Any]							    =	pa.StructArray.from_arrays(
										    [bytes_array, path_array]      ,      ['''bytes''', '''path''']      ,      mask=bytes_array.is_null()	)
								return array_cast(_lowerCamelCase      ,      self.pa_type	)







						def    __magic_name__				(				self       :   List[str]      ,      snake_case_       :   Optional[int]	):



								'''simple docstring'''



								@no_op_if_value_is_null
								def path_to_bytes(snake_case_       :   Dict	):
										with xopen(_lowerCamelCase      ,      '''rb'''	) as f:
												snake_case__    :							Union[str, Any]							    =	f.read()
										return bytes_

								snake_case__    :							List[str]							    =	pa.array(
								    [
								        (path_to_bytes(x['''path''']	) if x['''bytes'''] is None else x['''bytes''']) if x is not None else None
								        for x in storage.to_pylist()
								    ]      ,      type=pa.binary()      ,      )
								snake_case__    :							List[str]							    =	pa.array(
								    [os.path.basename(_lowerCamelCase	) if path is not None else None for path in storage.field('''path'''	).to_pylist()]      ,      type=pa.string()      ,      )
								snake_case__    :							Any							    =	pa.StructArray.from_arrays([bytes_array, path_array]      ,      ['''bytes''', '''path''']      ,      mask=bytes_array.is_null()	)
								return array_cast(_lowerCamelCase      ,      self.pa_type	)





def 						_a							(					):

		"""simple docstring"""

		if config.PIL_AVAILABLE:
				import PIL.Image
		else:
				raise ImportError('''To support encoding images, please install \'Pillow\'.'''  )

		global _IMAGE_COMPRESSION_FORMATS
		if _IMAGE_COMPRESSION_FORMATS is None:
				PIL.Image.init()
				snake_case__    :							List[Any]							    =	list(set(PIL.Image.OPEN.keys()  ) & set(PIL.Image.SAVE.keys()  )  )
		return _IMAGE_COMPRESSION_FORMATS




def 						_a							(					__lowerCAmelCase		:   "PIL.Image.Image"  ):

		"""simple docstring"""

		snake_case__    :							Dict							    =	BytesIO()
		if image.format in list_image_compression_formats():
				snake_case__    :							Any							    =	image.format
		else:
				snake_case__    :							Any							    =	'''PNG''' if image.mode in ['''1''', '''L''', '''LA''', '''RGB''', '''RGBA'''] else '''TIFF'''
		image.save(__snake_case ,				format=__snake_case  )
		return buffer.getvalue()




def 						_a							(					__lowerCAmelCase		:   "PIL.Image.Image"  ):

		"""simple docstring"""

		if hasattr(__snake_case ,				'''filename'''  ) and image.filename != "":
				return {"path": image.filename, "bytes": None}
		else:
				return {"path": None, "bytes": image_to_bytes(__snake_case  )}




def 						_a							(					__lowerCAmelCase		:   np.ndarray  ):

		"""simple docstring"""

		if config.PIL_AVAILABLE:
				import PIL.Image
		else:
				raise ImportError('''To support encoding images, please install \'Pillow\'.'''  )

		snake_case__    :							Optional[int]							    =	array.dtype
		snake_case__    :							str							    =	dtype.byteorder if dtype.byteorder != '''=''' else _NATIVE_BYTEORDER
		snake_case__    :							Any							    =	dtype.kind
		snake_case__    :							List[str]							    =	dtype.itemsize

		snake_case__    :							Dict							    =	None

		# Multi-channel array case (only np.dtype("|u1") is allowed)
		if array.shape[2:]:
				snake_case__    :							Union[str, Any]							    =	np.dtype('''|u1'''  )
				if dtype_kind not in ["u", "i"]:
						raise TypeError(
						    F"""Unsupported array dtype {dtype} for image encoding. Only {dest_dtype} is supported for multi-channel arrays."""  )
				if dtype is not dest_dtype:
						warnings.warn(F"""Downcasting array dtype {dtype} to {dest_dtype} to be compatible with \'Pillow\'"""  )
    # Exact match
		elif dtype in _VALID_IMAGE_ARRAY_DTPYES:
				snake_case__    :							Optional[int]							    =	dtype
		else:  # Downcast the type within the kind (np.can_cast(from_type, to_type, casting="same_kind") doesn't behave as expected, so do it manually)
				while dtype_itemsize >= 1:
						snake_case__    :							List[Any]							    =	dtype_byteorder + dtype_kind + str(__snake_case  )
						snake_case__    :							List[Any]							    =	np.dtype(__snake_case  )
						if dest_dtype in _VALID_IMAGE_ARRAY_DTPYES:
								warnings.warn(F"""Downcasting array dtype {dtype} to {dest_dtype} to be compatible with \'Pillow\'"""  )
								break
						else:
								dtype_itemsize //= 2

		if dest_dtype is None:
				raise TypeError(
				    F"""Cannot convert dtype {dtype} to a valid image dtype. Valid image dtypes: {_VALID_IMAGE_ARRAY_DTPYES}"""  )
		snake_case__    :							Tuple							    =	PIL.Image.fromarray(array.astype(__snake_case  )  )
		return {"path": None, "bytes": image_to_bytes(__snake_case  )}





def 						_a							(					__lowerCAmelCase		:   Union[List[str], List[dict], List[np.ndarray], List["PIL.Image.Image"]]  ):

		"""simple docstring"""

		if config.PIL_AVAILABLE:
				import PIL.Image
		else:
				raise ImportError('''To support encoding images, please install \'Pillow\'.'''  )

		if objs:
				snake_case__    ,							snake_case__    :							Union[str, Any]							    =	first_non_null_value(__snake_case  )
				if isinstance(__snake_case ,				__snake_case  ):
						return [{"path": obj, "bytes": None} if obj is not None else None for obj in objs]
				if isinstance(__snake_case ,				np.ndarray  ):
						snake_case__    :							List[Any]							    =	no_op_if_value_is_null(__snake_case  )
						return [obj_to_image_dict_func(__snake_case  ) for obj in objs]
				elif isinstance(__snake_case ,				PIL.Image.Image  ):
						snake_case__    :							List[str]							    =	no_op_if_value_is_null(__snake_case  )
						return [obj_to_image_dict_func(__snake_case  ) for obj in objs]
				else:
						return objs
		else:
				return objs




'''simple docstring'''

import colorsys

from PIL import Image  # type: ignore



def snake_case_      (					__snake_case  :							float	,   __snake_case  :							float	,   __snake_case  :							int)			->					float:
   lowerCAmelCase_			=      x
   lowerCAmelCase_			=      y
   for step in range(__snake_case):  # noqa: B007
      lowerCAmelCase_			=      a * a - b * b + x
      lowerCAmelCase_			=      2 * a * b + y
      lowerCAmelCase_			=      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 snake_case_      (					__snake_case  :							float)			->					tuple:
   if distance == 1:
      return (0, 0, 0)
   else:
      return (255, 255, 255)



def snake_case_      (					__snake_case  :							float)			->					tuple:
   if distance == 1:
      return (0, 0, 0)
   else:
      return tuple(round(i * 255) for i in colorsys.hsv_to_rgb(__snake_case	,   1	,   1))



def snake_case_      (					__snake_case  :							int = 800	,   __snake_case  :							int = 600	,   __snake_case  :							float = -0.6	,   __snake_case  :							float = 0	,   __snake_case  :							float = 3.2	,   __snake_case  :							int = 50	,   __snake_case  :							bool = True	,   )			->					Image.Image:
   lowerCAmelCase_			=      Image.new('''RGB'''	,   (image_width, image_height))
   lowerCAmelCase_			=      img.load()

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

         lowerCAmelCase_			=      get_distance(__snake_case	,   __snake_case	,   __snake_case)

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

   return img


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 # colored version, full figure
 A_     :						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()





