How to Find Local Maxima and Minima in a 1D Numpy Array?

Utilizing Numpy's SciPy Module to Locate Local Maxima and Minima in a 1D Numpy Array

Seeking a Numpy or SciPy module function capable of identifying local maxima and minima within a 1D Numpy array, we can explore a proven solution employed within the Numpy distribution.

Solution Using SciPy's Extrema Detection Functions

For instances where your SciPy installation is version 0.11 or later, you can leverage the argrelextrema function:

import numpy as np
from scipy.signal import argrelextrema

x = np.random.random(12)

# Detect local maxima
maxima_indices = argrelextrema(x, np.greater)

# Detect local minima
minima_indices = argrelextrema(x, np.less)

This script generates arrays containing the indices of local maxima or minima. To retrieve the corresponding values, utilize:

maxima_values = x[maxima_indices[0]]
minima_values = x[minima_indices[0]]

Alternative Options from SciPy.Signal

SciPy.signal also offers dedicated functions for handling max and min detection:

• argrelmax: Locates local maxima
• argrelmin: Locates local minima

Employ these methods for specific extraction of maxima or minima.

Example Output

For the example array [0.56660112, 0.76309473, 0.69597908, 0.38260156, 0.24346445, 0.56021785, 0.24109326, 0.41884061, 0.35461957, 0.54398472, 0.59572658, 0.92377974], the output indices of local maxima and minima are:

• Maxima: [1, 5, 7]
• Minima: [4, 6, 8]

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