




from collections.abc import Callable

import numpy as np







def lowerCamelCase__       (      _lowercase			,						_lowercase			,						_lowercase			,						_lowercase			,						_lowercase				):

     '''simple docstring'''


     UpperCAmelCase_      :							int       =      int(np.ceil((x_end - xa) / step_size				)				)
     UpperCAmelCase_      :							Tuple       =      np.zeros((n + 1,)				)
     UpperCAmelCase_      :							Optional[Any]       =      ya
     UpperCAmelCase_      :							Dict       =      xa

     for k in range(_lowercase				):
          UpperCAmelCase_      :							str       =      y[k] + step_size * ode_func(_lowercase			,						y[k]				)
          UpperCAmelCase_      :							str       =      y[k] + (
              (step_size / 2) * (ode_func(_lowercase			,						y[k]				) + ode_func(x + step_size			,						_lowercase				))
          )
          x += step_size

     return y


if __name__ == "__main__":
     import doctest

     doctest.testmod()





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


__a          =			None
__a          =			'<' 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
__a          =			[
    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"""





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





    def __call__(				self  )			->		Optional[Any]:
         return self.pa_type





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE  )			->		dict:
         if config.PIL_AVAILABLE:
              import PIL.Image
         else:
              raise ImportError('''To support encoding images, please install \'Pillow\'.'''  )

         if isinstance(_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  ):
              UpperCAmelCase_      :							Optional[int]       =      np.array(_SCREAMING_SNAKE_CASE  )

         if isinstance(_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  ):
              return {"path": value, "bytes": None}
         elif isinstance(_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE  ):
              return {"path": None, "bytes": value}
         elif isinstance(_SCREAMING_SNAKE_CASE       ,np.ndarray  ):
              # convert the image array to PNG/TIFF bytes
              return encode_np_array(_SCREAMING_SNAKE_CASE  )
         elif isinstance(_SCREAMING_SNAKE_CASE       ,PIL.Image.Image  ):
              # convert the PIL image to bytes (default format is PNG/TIFF)
              return encode_pil_image(_SCREAMING_SNAKE_CASE  )
         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 							a__				(				self       ,_SCREAMING_SNAKE_CASE       ,_SCREAMING_SNAKE_CASE=None  )			->		"PIL.Image.Image":
         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:
              UpperCAmelCase_      :							str       =      {}

         UpperCAmelCase_,   UpperCAmelCase_      :							List[str]       =      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(_SCREAMING_SNAKE_CASE  ):
                        UpperCAmelCase_      :							int       =      PIL.Image.open(_SCREAMING_SNAKE_CASE  )
                   else:
                        UpperCAmelCase_      :							int       =      path.split('''::'''  )[-1]
                        try:
                             UpperCAmelCase_      :							str       =      string_to_dict(_SCREAMING_SNAKE_CASE       ,config.HUB_DATASETS_URL  )['''repo_id''']
                             UpperCAmelCase_      :							Optional[Any]       =      token_per_repo_id.get(_SCREAMING_SNAKE_CASE  )
                        except ValueError:
                             UpperCAmelCase_      :							Any       =      None
                        with xopen(_SCREAMING_SNAKE_CASE       ,'''rb'''       ,use_auth_token=_SCREAMING_SNAKE_CASE  ) as f:
                             UpperCAmelCase_      :							List[str]       =      BytesIO(f.read()  )
                        UpperCAmelCase_      :							Optional[int]       =      PIL.Image.open(bytes_  )
         else:
              UpperCAmelCase_      :							Dict       =      PIL.Image.open(BytesIO(bytes_  )  )
         image.load()  # to avoid "Too many open files" errors
         return image





    def 							a__				(				self  )			->		Union["FeatureType", Dict[str, "FeatureType"]]:
         from .features import Value

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





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





    def 							a__				(				self       ,_SCREAMING_SNAKE_CASE  )			->		pa.StructArray:

         @no_op_if_value_is_null
         def path_to_bytes(_SCREAMING_SNAKE_CASE  ):
              with xopen(_SCREAMING_SNAKE_CASE       ,'''rb'''  ) as f:
                   UpperCAmelCase_      :							List[Any]       =      f.read()
              return bytes_

         UpperCAmelCase_      :							Dict       =      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()       ,)
         UpperCAmelCase_      :							Union[str, Any]       =      pa.array(
             [os.path.basename(_SCREAMING_SNAKE_CASE  ) if path is not None else None for path in storage.field('''path'''  ).to_pylist()]       ,type=pa.string()       ,)
         UpperCAmelCase_      :							Tuple       =      pa.StructArray.from_arrays([bytes_array, path_array]       ,['''bytes''', '''path''']       ,mask=bytes_array.is_null()  )
         return array_cast(_SCREAMING_SNAKE_CASE       ,self.pa_type  )







def lowerCamelCase__       (      ):

     '''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()
          UpperCAmelCase_      :							Optional[Any]       =      list(set(PIL.Image.OPEN.keys()				) & set(PIL.Image.SAVE.keys()				)				)
     return _IMAGE_COMPRESSION_FORMATS







def lowerCamelCase__       (      _lowercase				):

     '''simple docstring'''


     UpperCAmelCase_      :							Optional[int]       =      BytesIO()
     if image.format in list_image_compression_formats():
          UpperCAmelCase_      :							List[str]       =      image.format
     else:
          UpperCAmelCase_      :							int       =      '''PNG''' if image.mode in ['''1''', '''L''', '''LA''', '''RGB''', '''RGBA'''] else '''TIFF'''
     image.save(_lowercase			,						format=_lowercase				)
     return buffer.getvalue()







def lowerCamelCase__       (      _lowercase				):

     '''simple docstring'''


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







def lowerCamelCase__       (      _lowercase				):

     '''simple docstring'''


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

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

     UpperCAmelCase_      :							Optional[int]       =      None

     # Multi-channel array case (only np.dtype("|u1") is allowed)
     if array.shape[2:]:
          UpperCAmelCase_      :							str       =      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:
          UpperCAmelCase_      :							Dict       =      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:
               UpperCAmelCase_      :							Optional[int]       =      dtype_byteorder + dtype_kind + str(_lowercase				)
               UpperCAmelCase_      :							Dict       =      np.dtype(_lowercase				)
               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}'''				)
     UpperCAmelCase_      :							Dict       =      PIL.Image.fromarray(array.astype(_lowercase				)				)
     return {"path": None, "bytes": image_to_bytes(_lowercase				)}







def lowerCamelCase__       (      _lowercase				):

     '''simple docstring'''


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

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