import numpy as np

def mean_power(x_blocks):
    return np.sqrt(np.mean(x_blocks**2, axis=-1))

def power(x_blocks):
    return np.sqrt(np.sum(x_blocks**2, axis=-1))

def mean_energy(x_blocks):
    return np.mean(x_blocks**2, axis=-1)

def energy(x_blocks):
    return np.sum(x_blocks**2, axis=-1)

if __name__ == '__main__':

    import matplotlib.pyplot as plt
    from files import load_wav
    from analysis import split_to_blocks

    def analyze_mean_energy(file, block_size=1024):
        x, fs = load_wav(file)
        blocks, t = split_to_blocks(x, block_size)
        y = mean_energy(blocks)
        plt.semilogy(t, y)
        plt.ylim(0, 1)


import numpy as np


def mean_power(x_blocks):
    return np.sqrt(np.mean(x_blocks**2, axis=-1))

def power(x_blocks):
    return np.sqrt(np.sum(x_blocks**2, axis=-1))

def mean_energy(x_blocks):
    return np.mean(x_blocks**2, axis=-1)

def energy(x_blocks):
    return np.sum(x_blocks**2, axis=-1)

Put the code into a comment as an example usage.
Put the code into a comment as an example usage.

+ 
  import numpy as np
+ 
  
  def mean_power(x_blocks):
      return np.sqrt(np.mean(x_blocks**2, axis=-1))
  
  def power(x_blocks):
      return np.sqrt(np.sum(x_blocks**2, axis=-1))
  
  def mean_energy(x_blocks):
      return np.mean(x_blocks**2, axis=-1)
  
  def energy(x_blocks):
      return np.sum(x_blocks**2, axis=-1)
  
- if __name__ == '__main__':
- 
-     import matplotlib.pyplot as plt
-     from files import load_wav
-     from analysis import split_to_blocks
- 
-     def analyze_mean_energy(file, block_size=1024):
-         x, fs = load_wav(file)
-         blocks, t = split_to_blocks(x, block_size)
-         y = mean_energy(blocks)
-         plt.semilogy(t, y)
-         plt.ylim(0, 1)
- 
Put the code into a comment as an example usage.
## Code Before:
import numpy as np

def mean_power(x_blocks):
    return np.sqrt(np.mean(x_blocks**2, axis=-1))

def power(x_blocks):
    return np.sqrt(np.sum(x_blocks**2, axis=-1))

def mean_energy(x_blocks):
    return np.mean(x_blocks**2, axis=-1)

def energy(x_blocks):
    return np.sum(x_blocks**2, axis=-1)

if __name__ == '__main__':

    import matplotlib.pyplot as plt
    from files import load_wav
    from analysis import split_to_blocks

    def analyze_mean_energy(file, block_size=1024):
        x, fs = load_wav(file)
        blocks, t = split_to_blocks(x, block_size)
        y = mean_energy(blocks)
        plt.semilogy(t, y)
        plt.ylim(0, 1)

## Instruction:
Put the code into a comment as an example usage.
## Code After:

import numpy as np


def mean_power(x_blocks):
    return np.sqrt(np.mean(x_blocks**2, axis=-1))

def power(x_blocks):
    return np.sqrt(np.sum(x_blocks**2, axis=-1))

def mean_energy(x_blocks):
    return np.mean(x_blocks**2, axis=-1)

def energy(x_blocks):
    return np.sum(x_blocks**2, axis=-1)
