如何将噪声存储为 python 中傅立叶变换的变量

Question

我正在尝试在 python 中执行傅立叶变换。我想知道如何将从 Fourier transformation 获得的 noise 存储为 variable?

Python代码：

import numpy as np

# Create a simple signal with two frequencies
dt = 0.001
t = np.arange(0,1,dt)
f = np.sin(2*np.pi*50*t) + np.sin(2*np.pi*120*t) # Sum of 2 frequencies
f_clean = f
noise = 2.5*np.random.randn(len(t))
f = f + noise              # Add some noise

## Compute the Fast Fourier Transform (FFT)

n = len(t)
fhat = np.fft.fft(f,n)                     # Compute the FFT
PSD = fhat * np.conj(fhat) / n             # Power spectrum (power per freq)
freq = (1/(dt*n)) * np.arange(n)           # Create x-axis of frequencies in Hz
L = np.arange(1,np.floor(n/2),dtype='int') # Only plot the first half of freqs

## Use the PSD to filter out noise
indices = PSD > 100       # Find all freqs with large power
PSDclean = PSD * indices  # Zero out all others
fhat = indices * fhat     # Zero out small Fourier coeffs. in Y
ffilt = np.fft.ifft(fhat) # Inverse FFT for filtered time signal

我尝试使用以下代码行来存储噪声值，但不确定执行此任务的语法或方法是否正确。

## To store the noise using the PSD 

low_indices = PSD < 100   # Find all freqs with small power
PSDnoise = PSD * low_indices  # zero out larger freqs
fhat_noise = low_indices * fhat

是否有更好的方法来存储这些值？

Answer 1

如果你这样做

PSDnoise = PSD * low_indices

您将有 0 个值，其中 low_indices 中有一个 False。

如果您只想将 PSD 的值保留在低于阈值的索引处，您可以使用数组索引，如下所示：

PSDnoise = PSD[low_indices]

如何将噪声存储为 python 中傅立叶变换的变量

How to store noise as a variable from the fourier transformation in python

python

fft