

'''simple docstring'''

from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np





class 							_snake_case (       _a						):
   def     __UpperCamelCase						( self			:      Optional[Any]     ,SCREAMING_SNAKE_CASE__			:      float							):
     return 0.0





def    A_  ( snake_case      ,       snake_case ):
  SCREAMING_SNAKE_CASE:List[Any]						      =					min([-20, np.min(fft_results[1 : samplerate // 2 - 1] )] )
  SCREAMING_SNAKE_CASE:Any						      =					max([20, np.max(fft_results[1 : samplerate // 2 - 1] )] )
  return lowest, highest





def    A_  ( snake_case      ,       snake_case ):
  SCREAMING_SNAKE_CASE:str						      =					512
  SCREAMING_SNAKE_CASE:Any						      =					[1] + [0] * (size - 1)
  SCREAMING_SNAKE_CASE:Optional[int]						      =					[filter_type.process(snake_case ) for item in inputs]

  SCREAMING_SNAKE_CASE:Optional[Any]						      =					[0] * (samplerate - size)  # zero-padding
  outputs += filler
  SCREAMING_SNAKE_CASE:List[Any]						      =					np.abs(np.fft.fft(snake_case ) )
  SCREAMING_SNAKE_CASE:Dict						      =					20 * np.logaa(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
  SCREAMING_SNAKE_CASE:Optional[int]						      =					get_bounds(snake_case      ,       snake_case )
  plt.ylim(max([-80, bounds[0]] )      ,       min([80, bounds[1]] ) )
  plt.ylabel("Gain (dB)" )

  plt.plot(snake_case )
  plt.show()





def    A_  ( snake_case      ,       snake_case ):
  SCREAMING_SNAKE_CASE:List[str]						      =					512
  SCREAMING_SNAKE_CASE:int						      =					[1] + [0] * (size - 1)
  SCREAMING_SNAKE_CASE:Optional[Any]						      =					[filter_type.process(snake_case ) for item in inputs]

  SCREAMING_SNAKE_CASE:Dict						      =					[0] * (samplerate - size)  # zero-padding
  outputs += filler
  SCREAMING_SNAKE_CASE:int						      =					np.angle(np.fft.fft(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(snake_case      ,       -2 * pi ) )
  plt.show()









'''simple docstring'''

from ..utils import DummyObject, requires_backends





class 							_snake_case (       metaclass=_a						):
   _A       :     Any       =					['''torch''', '''torchsde''']
   def __init__( self			:      Any     ,*SCREAMING_SNAKE_CASE__			:      int     ,**SCREAMING_SNAKE_CASE__			:      Tuple							):
     requires_backends(self     ,["torch", "torchsde"]							)
   @classmethod
   def     __UpperCamelCase						( cls			:      Dict     ,*SCREAMING_SNAKE_CASE__			:      Dict     ,**SCREAMING_SNAKE_CASE__			:      Optional[Any]							):
     requires_backends(cls     ,["torch", "torchsde"]							)







   @classmethod
   def     __UpperCamelCase						( cls			:      List[str]     ,*SCREAMING_SNAKE_CASE__			:      int     ,**SCREAMING_SNAKE_CASE__			:      Optional[Any]							):
     requires_backends(cls     ,["torch", "torchsde"]							)






