stdfilt

Introduction

stdfilt is a Python function that performs standard deviation filtering on 1d or 2d arrays.

This function computes the standard deviation of a specified window size of elements in the input array and replaces the central element with this computed value. This process is repeated for all the elements in the input array, except for the outermost elements where the window size exceeds the available elements.

stdfilt can be used in a variety of applications, including image processing, signal processing, and data analysis.

Usage

To use stdfilt, you must first import it from the appropriate module. Here's an example:

from scipy.ndimage import generic_filter
from numpy import ndarray

def stdfilt(arr: ndarray, window_size: int) -> ndarray:
    def std_filter(values):
        return values.std()

    return generic_filter(arr, std_filter, size=window_size)

stdfilt takes two arguments: arr, the input 1d or 2d array to be filtered, and window_size, the size of the window over which to compute the standard deviation. The function returns a filtered array with the same shape and datatype as the input array.

Here's an example of how to use stdfilt to filter a Noisy Sine Wave:

import numpy as np
import matplotlib.pyplot as plt

# Generate a noisy sine wave signal
time = np.arange(0, 10, 0.1)
amplitude = np.sin(time)
noisy_amplitude = amplitude + 0.5*np.random.randn(len(time))

# Apply stdfilt to the noisy signal
filtered_amplitude = stdfilt(noisy_amplitude, 5)

# Plot the noisy and filtered signals
plt.plot(time, noisy_amplitude, label='Noisy Wave', color='red')
plt.plot(time, filtered_amplitude, label='Filtered Wave', color='blue')
plt.legend()
plt.show()

This code generates the following plot:

Conclusion

In conclusion, stdfilt is a simple and powerful tool for performing standard deviation filtering on 1d and 2d arrays. Its ease of use and versatility make it a valuable asset for any Python developer working with image processing, signal processing, or data analysis.