

import enum
import os
from hashlib import shaaaa
from typing import Optional

from .. import config
from .logging import get_logger


__UpperCAmelCase    				=     get_logger(__name__)





class A__    ( enum.Enum ):



 """simple docstring"""







 _lowercase     :					Dict      =						'''all_checks'''
 _lowercase     :					Optional[int]      =						'''basic_checks'''
 _lowercase     :					str      =						'''no_checks'''





class A__    ( __a ):



 """simple docstring"""












class A__    ( __a ):



 """simple docstring"""












class A__    ( __a ):



 """simple docstring"""












class A__    ( __a ):



 """simple docstring"""














def 	_snake_case		(    SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE=None				)       ->      Optional[Any]:

     """simple docstring"""







     if expected_checksums is None:
          logger.info("Unable to verify checksums."				)
          return
     if len(set(snake_case__				) - set(snake_case__				)				) > 0:
          raise ExpectedMoreDownloadedFiles(str(set(snake_case__				) - set(snake_case__				)				)				)
     if len(set(snake_case__				) - set(snake_case__				)				) > 0:
          raise UnexpectedDownloadedFile(str(set(snake_case__				) - set(snake_case__				)				)				)
     _lowerCAmelCase   :					Dict        =    [url for url in expected_checksums if expected_checksums[url] != recorded_checksums[url]]
     _lowerCAmelCase   :					Any        =    """ for """ + verification_name if verification_name is not None else """"""
     if len(snake_case__				) > 0:
          raise NonMatchingChecksumError(
              f'''Checksums didn\'t match{for_verification_name}:\n'''
              f'''{bad_urls}\n'''
              "Set `verification_mode='no_checks'` to skip checksums verification and ignore this error"				)
     logger.info("All the checksums matched successfully" + for_verification_name				)





class A__    ( __a ):



 """simple docstring"""












class A__    ( __a ):



 """simple docstring"""












class A__    ( __a ):



 """simple docstring"""












class A__    ( __a ):



 """simple docstring"""














def 	_snake_case		(    SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE				)       ->      Dict:

     """simple docstring"""







     if expected_splits is None:
          logger.info("Unable to verify splits sizes."				)
          return
     if len(set(snake_case__				) - set(snake_case__				)				) > 0:
          raise ExpectedMoreSplits(str(set(snake_case__				) - set(snake_case__				)				)				)
     if len(set(snake_case__				) - set(snake_case__				)				) > 0:
          raise UnexpectedSplits(str(set(snake_case__				) - set(snake_case__				)				)				)
     _lowerCAmelCase   :					Optional[Any]        =    [
         {"""expected""": expected_splits[name], """recorded""": recorded_splits[name]}
         for name in expected_splits
         if expected_splits[name].num_examples != recorded_splits[name].num_examples
     ]
     if len(snake_case__				) > 0:
          raise NonMatchingSplitsSizesError(str(snake_case__				)				)
     logger.info("All the splits matched successfully."				)







def 	_snake_case		(    SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE = True				)       ->      Optional[int]:

     """simple docstring"""







     if record_checksum:
          _lowerCAmelCase   :					int        =    shaaaa()
          with open(snake_case__		,							"rb"				) as f:
               for chunk in iter(lambda: f.read(1 << 20				)		,							B""				):
                    m.update(snake_case__				)
               _lowerCAmelCase   :					List[str]        =    m.hexdigest()
     else:
          _lowerCAmelCase   :					List[Any]        =    None
     return {"num_bytes": os.path.getsize(snake_case__				), "checksum": checksum}







def 	_snake_case		(    SCREAMING_SNAKE_CASE				)       ->      Optional[Any]:

     """simple docstring"""







     if dataset_size and config.IN_MEMORY_MAX_SIZE:
          return dataset_size < config.IN_MEMORY_MAX_SIZE
     else:
          return False





from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np





class A__    ( A ):



 """simple docstring"""







 def    __magic_name__       (		self :	List[Any]     ,						A_ :	float       ):






      '''simple docstring'''




      return 0.0







def 	_snake_case		(    SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE				)       ->      tuple[int | float, int | float]:

     """simple docstring"""







     _lowerCAmelCase   :					Union[str, Any]        =    min([-20, np.min(fft_results[1 : samplerate // 2 - 1]				)]				)
     _lowerCAmelCase   :					Optional[Any]        =    max([20, np.max(fft_results[1 : samplerate // 2 - 1]				)]				)
     return lowest, highest







def 	_snake_case		(    SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE				)       ->      None:

     """simple docstring"""







     _lowerCAmelCase   :					Any        =    512
     _lowerCAmelCase   :					Tuple        =    [1] + [0] * (size - 1)
     _lowerCAmelCase   :					Optional[Any]        =    [filter_type.process(SCREAMING_SNAKE_CASE				) for item in inputs]

     _lowerCAmelCase   :					Dict        =    [0] * (samplerate - size)  # zero-padding
     outputs += filler
     _lowerCAmelCase   :					Dict        =    np.abs(np.fft.fft(SCREAMING_SNAKE_CASE				)				)
     _lowerCAmelCase   :					str        =    20 * np.logaa(SCREAMING_SNAKE_CASE				)

     # Frequencies on log scale from 24 to nyquist frequency
     plt.xlim(24		,							samplerate / 2 - 1				)
     plt.xlabel("Frequency (Hz)"				)
     plt.xscale("log"				)

     # Display within reasonable bounds
     _lowerCAmelCase   :					Tuple        =    get_bounds(SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE				)
     plt.ylim(max([-80, bounds[0]]				)		,							min([80, bounds[1]]				)				)
     plt.ylabel("Gain (dB)"				)

     plt.plot(SCREAMING_SNAKE_CASE				)
     plt.show()







def 	_snake_case		(    SCREAMING_SNAKE_CASE		,							SCREAMING_SNAKE_CASE				)       ->      None:

     """simple docstring"""







     _lowerCAmelCase   :					Tuple        =    512
     _lowerCAmelCase   :					Tuple        =    [1] + [0] * (size - 1)
     _lowerCAmelCase   :					Dict        =    [filter_type.process(SCREAMING_SNAKE_CASE				) for item in inputs]

     _lowerCAmelCase   :					Tuple        =    [0] * (samplerate - size)  # zero-padding
     outputs += filler
     _lowerCAmelCase   :					Tuple        =    np.angle(np.fft.fft(SCREAMING_SNAKE_CASE				)				)

     # Frequencies on log scale from 24 to nyquist frequency
     plt.xlim(24		,							samplerate / 2 - 1				)
     plt.xlabel("Frequency (Hz)"				)
     plt.xscale("log"				)

     plt.ylim(-2 * pi		,							2 * pi				)
     plt.ylabel("Phase shift (Radians)"				)
     plt.plot(np.unwrap(SCREAMING_SNAKE_CASE		,							-2 * pi				)				)
     plt.show()






