

import warnings
from collections.abc import Callable
from typing import Any

import numpy
from matplotlib import pyplot

__A   :     List[Any]      =			0.25 + 0.0j
__A   :     Any      =			-0.4 + 0.6j
__A   :     List[str]      =			-0.1 + 0.6_5_1j
__A   :     int      =			-2.0
__A   :     Optional[int]      =			56
__A   :     Optional[int]      =			2.0
__A   :     Dict      =			666
def 		SCREAMING_SNAKE_CASE__				(							_UpperCAmelCase,      _UpperCAmelCase				)					-> numpy.ndarray:



    '''simple docstring'''






    return numpy.exp(_UpperCAmelCase				) + c_parameter
def 		SCREAMING_SNAKE_CASE__				(							_UpperCAmelCase,      _UpperCAmelCase				)					-> numpy.ndarray:



    '''simple docstring'''






    return z_values * z_values + c_parameter
def 		SCREAMING_SNAKE_CASE__				(							_UpperCAmelCase,      _UpperCAmelCase				)					-> numpy.ndarray:



    '''simple docstring'''






    lowerCAmelCase				:			Union[str, Any]    			=      numpy.linspace(-window_size,      _UpperCAmelCase,      _UpperCAmelCase				)
    lowerCAmelCase				:			Optional[int]    			=      x.reshape((nb_pixels, 1)				)
    lowerCAmelCase				:			Tuple    			=      numpy.linspace(-window_size,      _UpperCAmelCase,      _UpperCAmelCase				)
    lowerCAmelCase				:			int    			=      y.reshape((1, nb_pixels)				)
    return x + 1.0j * y
def 		SCREAMING_SNAKE_CASE__				(							_UpperCAmelCase,      _UpperCAmelCase,      _UpperCAmelCase,      _UpperCAmelCase,      _UpperCAmelCase = None,      )					-> numpy.ndarray:



    '''simple docstring'''






    lowerCAmelCase				:			List[str]    			=      z_a.astype('complex64'				)
    for _ in range(_UpperCAmelCase				):
        lowerCAmelCase				:			List[Any]    			=      eval_function(_UpperCAmelCase,      _UpperCAmelCase				)
        if infinity is not None:
            numpy.nan_to_num(_UpperCAmelCase,      copy=_UpperCAmelCase,      nan=_UpperCAmelCase				)
            lowerCAmelCase				:			List[str]    			=      infinity
    return z_n
def 		SCREAMING_SNAKE_CASE__				(							_UpperCAmelCase,      _UpperCAmelCase,      _UpperCAmelCase,      _UpperCAmelCase,      )					-> None:



    '''simple docstring'''






    lowerCAmelCase				:			List[Any]    			=      (abs(_UpperCAmelCase				)).transpose()
    lowerCAmelCase				:			List[Any]    			=      abs_z_final[::-1, :]
    pyplot.matshow(abs_z_final < escape_radius				)
    pyplot.title(f"Julia set of ${function_label}$, $c={function_params}$"				)
    pyplot.show()
def 		SCREAMING_SNAKE_CASE__				(							)					-> None:



    '''simple docstring'''






    warnings.filterwarnings(
        'ignore',      category=_UpperCAmelCase,      message='overflow encountered in multiply'				)
    warnings.filterwarnings(
        'ignore',      category=_UpperCAmelCase,      message='invalid value encountered in multiply',      )
    warnings.filterwarnings(
        'ignore',      category=_UpperCAmelCase,      message='overflow encountered in absolute'				)
    warnings.filterwarnings(
        'ignore',      category=_UpperCAmelCase,      message='overflow encountered in exp'				)


if __name__ == "__main__":
 __A   :     List[Any]      =			prepare_grid(window_size, nb_pixels)

 ignore_overflow_warnings()  # See file header for explanations

 __A   :     Tuple      =			24
 __A   :     Union[str, Any]      =			2 * abs(c_cauliflower) + 1
 __A   :     Union[str, Any]      =			iterate_function(
     eval_quadratic_polynomial,
     c_cauliflower,
     nb_iterations,
     z_a,
     infinity=1.1 * escape_radius,
 )
 show_results('''z^2+c''', c_cauliflower, escape_radius, z_final)

 __A   :     Dict      =			64
 __A   :     List[str]      =			2 * abs(c_polynomial_a) + 1
 __A   :     List[Any]      =			iterate_function(
     eval_quadratic_polynomial,
     c_polynomial_a,
     nb_iterations,
     z_a,
     infinity=1.1 * escape_radius,
 )
 show_results('''z^2+c''', c_polynomial_a, escape_radius, z_final)

 __A   :     List[Any]      =			161
 __A   :     List[str]      =			2 * abs(c_polynomial_a) + 1
 __A   :     Tuple      =			iterate_function(
     eval_quadratic_polynomial,
     c_polynomial_a,
     nb_iterations,
     z_a,
     infinity=1.1 * escape_radius,
 )
 show_results('''z^2+c''', c_polynomial_a, escape_radius, z_final)

 __A   :     Tuple      =			12
 __A   :     List[str]      =			1_00_00.0
 __A   :     Optional[Any]      =			iterate_function(
     eval_exponential,
     c_exponential,
     nb_iterations,
     z_a + 2,
     infinity=1.0E10,
 )
 show_results('''e^z+c''', c_exponential, escape_radius, z_final)








__A   :     List[Any]      =			'''
# Installation de Transformers
! pip install transformers datasets
# Pour installer à partir du code source au lieu de la dernière version, commentez la commande ci-dessus et décommentez la suivante.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

__A   :     Dict      =			[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
__A   :     Tuple      =			{
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}





