


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


_SCREAMING_SNAKE_CASE      :			Optional[List[str]]      				=   None
_SCREAMING_SNAKE_CASE      :			List[str]      				=   "<" 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
_SCREAMING_SNAKE_CASE      :			Dict      				=   [
    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"""

    __magic_name__        =		True
    __magic_name__        =		None
    # Automatically constructed
    __magic_name__        =		'PIL.Image.Image'
    __magic_name__        =		pa.struct({'bytes': pa.binary(), 'path': pa.string()}     )
    __magic_name__        =		field(default='Image'	, init=snake_case__	, repr=snake_case__     )
    def __call__(	self   ):
         return self.pa_type
    def 		a_      (	self      , __snake_case   ):
         if config.PIL_AVAILABLE:
              import PIL.Image
         else:
              raise ImportError('''To support encoding images, please install \'Pillow\'.'''   )

         if isinstance(__snake_case      , __snake_case   ):
              snake_case					=    np.array(__snake_case   )

         if isinstance(__snake_case      , __snake_case   ):
              return {"path": value, "bytes": None}
         elif isinstance(__snake_case      , __snake_case   ):
              return {"path": None, "bytes": value}
         elif isinstance(__snake_case      , np.ndarray   ):
              # convert the image array to PNG/TIFF bytes
              return encode_np_array(__snake_case   )
         elif isinstance(__snake_case      , PIL.Image.Image   ):
              # convert the PIL image to bytes (default format is PNG/TIFF)
              return encode_pil_image(__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      , __snake_case      , __snake_case=None   ):
         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					=    {}

         snake_case			,  snake_case					=    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(__snake_case   ):
                        snake_case					=    PIL.Image.open(__snake_case   )
                   else:
                        snake_case					=    path.split('''::'''   )[-1]
                        try:
                             snake_case					=    string_to_dict(__snake_case      , config.HUB_DATASETS_URL   )['''repo_id''']
                             snake_case					=    token_per_repo_id.get(__snake_case   )
                        except ValueError:
                             snake_case					=    None
                        with xopen(__snake_case      , '''rb'''      , use_auth_token=__snake_case   ) as f:
                             snake_case					=    BytesIO(f.read()   )
                        snake_case					=    PIL.Image.open(bytes_   )
         else:
              snake_case					=    PIL.Image.open(BytesIO(bytes_   )   )
         image.load()  # to avoid "Too many open files" errors
         return image
    def 		a_      (	self   ):
         from .features import Value

         return (
             self
             if self.decode
             else {
                 "bytes": Value('''binary'''   ),
                 "path": Value('''string'''   ),
             }
         )
    def 		a_      (	self      , __snake_case   ):
         if pa.types.is_string(storage.type   ):
              snake_case					=    pa.array([None] * len(__snake_case   )      , type=pa.binary()   )
              snake_case					=    pa.StructArray.from_arrays([bytes_array, storage]      , ['''bytes''', '''path''']      , mask=storage.is_null()   )
         elif pa.types.is_binary(storage.type   ):
              snake_case					=    pa.array([None] * len(__snake_case   )      , type=pa.string()   )
              snake_case					=    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					=    storage.field('''bytes'''   )
              else:
                   snake_case					=    pa.array([None] * len(__snake_case   )      , type=pa.binary()   )
              if storage.type.get_field_index('''path'''   ) >= 0:
                   snake_case					=    storage.field('''path'''   )
              else:
                   snake_case					=    pa.array([None] * len(__snake_case   )      , type=pa.string()   )
              snake_case					=    pa.StructArray.from_arrays([bytes_array, path_array]      , ['''bytes''', '''path''']      , mask=storage.is_null()   )
         elif pa.types.is_list(storage.type   ):
              snake_case					=    pa.array(
                  [encode_np_array(np.array(__snake_case   )   )['''bytes'''] if arr is not None else None for arr in storage.to_pylist()]      , type=pa.binary()      , )
              snake_case					=    pa.array([None] * len(__snake_case   )      , type=pa.string()   )
              snake_case					=    pa.StructArray.from_arrays(
                  [bytes_array, path_array]      , ['''bytes''', '''path''']      , mask=bytes_array.is_null()   )
         return array_cast(__snake_case      , self.pa_type   )




    def 		a_      (	self      , __snake_case   ):

         @no_op_if_value_is_null
         def path_to_bytes(__snake_case   ):
              with xopen(__snake_case      , '''rb'''   ) as f:
                   snake_case					=    f.read()
              return bytes_

         snake_case					=    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					=    pa.array(
             [os.path.basename(__snake_case   ) if path is not None else None for path in storage.field('''path'''   ).to_pylist()]      , type=pa.string()      , )
         snake_case					=    pa.StructArray.from_arrays([bytes_array, path_array]      , ['''bytes''', '''path''']      , mask=bytes_array.is_null()   )
         return array_cast(__snake_case      , self.pa_type   )






def       UpperCAmelCase__						():



     """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(set(PIL.Image.OPEN.keys()    ) & set(PIL.Image.SAVE.keys()    )    )
     return _IMAGE_COMPRESSION_FORMATS
def       UpperCAmelCase__						(UpperCamelCase_    ):



     """simple docstring"""






     snake_case					=    BytesIO()
     if image.format in list_image_compression_formats():
          snake_case					=    image.format
     else:
          snake_case					=    '''PNG''' if image.mode in ['''1''', '''L''', '''LA''', '''RGB''', '''RGBA'''] else '''TIFF'''
     image.save(UpperCamelCase_							,format=UpperCamelCase_    )
     return buffer.getvalue()
def       UpperCAmelCase__						(UpperCamelCase_    ):



     """simple docstring"""






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



     """simple docstring"""






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

     snake_case					=    array.dtype
     snake_case					=    dtype.byteorder if dtype.byteorder != '''=''' else _NATIVE_BYTEORDER
     snake_case					=    dtype.kind
     snake_case					=    dtype.itemsize

     snake_case					=    None

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

def       UpperCAmelCase__						(UpperCamelCase_    ):



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








from __future__ import annotations

from scipy.special import comb  # type: ignore

class   A__ :







    """simple docstring"""

    def __init__(	self      , __snake_case   ):
         snake_case					=    list_of_points
         # Degree determines the flexibility of the curve.
         # Degree = 1 will produce a straight line.
         snake_case					=    len(__snake_case   ) - 1
    def 		a_      (	self      , __snake_case   ):
         assert 0 <= t <= 1, "Time t must be between 0 and 1."
         snake_case					=    []
         for i in range(len(self.list_of_points   )   ):
              # basis function for each i
              output_values.append(
                  comb(self.degree      , __snake_case   ) * ((1 - t) ** (self.degree - i)) * (t**i)   )
         # the basis must sum up to 1 for it to produce a valid Bezier curve.
         assert round(sum(__snake_case   )      , 5   ) == 1
         return output_values
    def 		a_      (	self      , __snake_case   ):
         assert 0 <= t <= 1, "Time t must be between 0 and 1."

         snake_case					=    self.basis_function(__snake_case   )
         snake_case					=    0.0
         snake_case					=    0.0
         for i in range(len(self.list_of_points   )   ):
              # For all points, sum up the product of i-th basis function and i-th point.
              x += basis_function[i] * self.list_of_points[i][0]
              y += basis_function[i] * self.list_of_points[i][1]
         return (x, y)




    def 		a_      (	self      , __snake_case = 0.01   ):
         from matplotlib import pyplot as plt  # type: ignore

         snake_case					=    []  # x coordinates of points to plot
         snake_case					=    []  # y coordinates of points to plot

         snake_case					=    0.0
         while t <= 1:
              snake_case					=    self.bezier_curve_function(__snake_case   )
              to_plot_x.append(value[0]   )
              to_plot_y.append(value[1]   )
              t += step_size

         snake_case					=    [i[0] for i in self.list_of_points]
         snake_case					=    [i[1] for i in self.list_of_points]

         plt.plot(
             __snake_case      , __snake_case      , color='''blue'''      , label='''Curve of Degree ''' + str(self.degree   )      , )
         plt.scatter(__snake_case      , __snake_case      , color='''red'''      , label='''Control Points'''   )
         plt.legend()
         plt.show()


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 BezierCurve([(1, 2), (3, 5)]).plot_curve()  # degree 1
 BezierCurve([(0, 0), (5, 5), (5, 0)]).plot_curve()  # degree 2
 BezierCurve([(0, 0), (5, 5), (5, 0), (2.5, -2.5)]).plot_curve()  # degree 3




