'''simple docstring'''

from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np





class 							lowercase						(						__lowerCamelCase ):


   def __UpperCAmelCase       (   self				:	Optional[int]   ,		__lowerCAmelCase				:	float)      ->					float:
         return 0.0




def __a (	__lowerCamelCase			:						np.ndarray ,		__lowerCamelCase			:						int				)	->							tuple[int | float, int | float]:
      '''simple docstring'''


      lowercase_     =      min([-20, np.min(fft_results[1 : samplerate // 2 - 1]				)]				)
      lowercase_     =      max([20, np.max(fft_results[1 : samplerate // 2 - 1]				)]				)
      return lowest, highest


def __a (	__lowerCamelCase			:						FilterType ,		__lowerCamelCase			:						int				)	->							None:
      '''simple docstring'''


      lowercase_     =      512
      lowercase_     =      [1] + [0] * (size - 1)
      lowercase_     =      [filter_type.process(__lowerCamelCase				) for item in inputs]

      lowercase_     =      [0] * (samplerate - size)  # zero-padding
      outputs += filler
      lowercase_     =      np.abs(np.fft.fft(__lowerCamelCase				)				)
      lowercase_     =      20 * np.logaa(__lowerCamelCase				)

      # 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
      lowercase_     =      get_bounds(__lowerCamelCase ,		__lowerCamelCase				)
      plt.ylim(max([-80, bounds[0]]				) ,		min([80, bounds[1]]				)				)
      plt.ylabel("Gain (dB)"				)

      plt.plot(__lowerCamelCase				)
      plt.show()






def __a (	__lowerCamelCase			:						FilterType ,		__lowerCamelCase			:						int				)	->							None:
      '''simple docstring'''


      lowercase_     =      512
      lowercase_     =      [1] + [0] * (size - 1)
      lowercase_     =      [filter_type.process(__lowerCamelCase				) for item in inputs]

      lowercase_     =      [0] * (samplerate - size)  # zero-padding
      outputs += filler
      lowercase_     =      np.angle(np.fft.fft(__lowerCamelCase				)				)

      # 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(__lowerCamelCase ,		-2 * pi				)				)
      plt.show()







'''simple docstring'''

# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

lowerCAmelCase_ : Dict						  =      TypeVar("T")





class 							lowercase						(						Generic[T] ):


   def __init__(   self				:	int   ,		__lowerCAmelCase				:	bool = True)      ->					None:
         lowercase_     =      {}  # dictionary of lists
         lowercase_     =      directed


   def __UpperCAmelCase       (   self				:	int   ,		__lowerCAmelCase				:	T   ,		__lowerCAmelCase				:	T)      ->					GraphAdjacencyList[T]:

         if not self.directed:  # For undirected graphs
               # if both source vertex and destination vertex are both present in the
               # adjacency list, add destination vertex to source vertex list of adjacent
               # vertices and add source vertex to destination vertex list of adjacent
               # vertices.
               if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                     self.adj_list[source_vertex].append(__lowerCAmelCase)
                     self.adj_list[destination_vertex].append(__lowerCAmelCase)
               # if only source vertex is present in adjacency list, add destination vertex
               # to source vertex list of adjacent vertices, then create a new vertex with
               # destination vertex as key and assign a list containing the source vertex
               # as it's first adjacent vertex.
               elif source_vertex in self.adj_list:
                     self.adj_list[source_vertex].append(__lowerCAmelCase)
                     lowercase_     =      [source_vertex]
               # if only destination vertex is present in adjacency list, add source vertex
               # to destination vertex list of adjacent vertices, then create a new vertex
               # with source vertex as key and assign a list containing the source vertex
               # as it's first adjacent vertex.
               elif destination_vertex in self.adj_list:
                     self.adj_list[destination_vertex].append(__lowerCAmelCase)
                     lowercase_     =      [destination_vertex]
               # if both source vertex and destination vertex are not present in adjacency
               # list, create a new vertex with source vertex as key and assign a list
               # containing the destination vertex as it's first adjacent vertex also
               # create a new vertex with destination vertex as key and assign a list
               # containing the source vertex as it's first adjacent vertex.
               else:
                     lowercase_     =      [destination_vertex]
                     lowercase_     =      [source_vertex]
         else:  # For directed graphs
               # if both source vertex and destination vertex are present in adjacency
               # list, add destination vertex to source vertex list of adjacent vertices.
               if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                     self.adj_list[source_vertex].append(__lowerCAmelCase)
               # if only source vertex is present in adjacency list, add destination
               # vertex to source vertex list of adjacent vertices and create a new vertex
               # with destination vertex as key, which has no adjacent vertex
               elif source_vertex in self.adj_list:
                     self.adj_list[source_vertex].append(__lowerCAmelCase)
                     lowercase_     =      []
               # if only destination vertex is present in adjacency list, create a new
               # vertex with source vertex as key and assign a list containing destination
               # vertex as first adjacent vertex
               elif destination_vertex in self.adj_list:
                     lowercase_     =      [destination_vertex]
               # if both source vertex and destination vertex are not present in adjacency
               # list, create a new vertex with source vertex as key and a list containing
               # destination vertex as it's first adjacent vertex. Then create a new vertex
               # with destination vertex as key, which has no adjacent vertex
               else:
                     lowercase_     =      [destination_vertex]
                     lowercase_     =      []

         return self


   def __repr__(   self				:	str)      ->					str:
         return pformat(self.adj_list)






