find_edges.py

#!/usr/bin/env python3

import numpy as np

import matplotlib.pyplot as plt

np.set_printoptions(threshold=np.inf)


def main():
    threshold = 0.5
    samples = np.random.standard_normal((10000,))

    # Get a boolean array for all samples higher or lower than the threshold
    low_samples = samples < threshold
    high_samples = samples >= threshold

    # Compute the rising edge and falling edges by comparing the current value to the next with
    # the boolean operator & (if both are true the result is true) and converting this to an index
    # into the current array
    rising_edge_idx = np.nonzero(low_samples[:-1] & np.roll(high_samples, -1)[:-1])[0]
    falling_edge_idx = np.nonzero(high_samples[:-1] & np.roll(low_samples, -1)[:-1])[0]

    rising_edge_diff = np.diff(rising_edge_idx)
    pulse_widths = rising_edge_idx - falling_edge_idx


    # Plot the signal and mark rising edges in red and falling edges in yellow
    plt.plot(samples, alpha=0.5)
    for re in rising_edge_idx:
        plt.axvspan(re, re+1, color='red', alpha=0.5)

    for fe in falling_edge_idx:
        plt.axvspan(fe, fe+1, color='yellow', alpha=0.5)
    plt.show()


if __name__ == "__main__":
    exit(not main())