




def SCREAMING_SNAKE_CASE    (	lowercase_ = 50						)       ->	int:



       """simple docstring"""

       A__							=   [1] * (length + 1)

       for row_length in range(3			,    length + 1						):
              for block_length in range(3			,    row_length + 1						):
                     for block_start in range(row_length - block_length						):
                            ways_number[row_length] += ways_number[
                                row_length - block_start - block_length - 1
                            ]

                     ways_number[row_length] += 1

       return ways_number[length]


if __name__ == "__main__":
  print(F'''{solution() = }''')








from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np


class     UpperCamelCase_   (			UpperCAmelCase__					):

    '''simple docstring'''






    def 	SCREAMING_SNAKE_CASE							(      self				:     Optional[int] ,			UpperCAmelCase__				:     float)						->float:





           '''simple docstring'''

           return 0.0







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



       """simple docstring"""

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







def SCREAMING_SNAKE_CASE    (	lowercase_			,    lowercase_						)       ->	None:



       """simple docstring"""

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

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

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

       plt.plot(lowercase_						)
       plt.show()







def SCREAMING_SNAKE_CASE    (	lowercase_			,    lowercase_						)       ->	None:



       """simple docstring"""

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

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

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


