[Term Entry] Python Scipy Function: find_peaks()

content/scipy/concepts/scipy-signal/terms/find-peaks/find-peaks.md

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+---
+Title: '.find_peaks()'
+Description: 'Finds the indices of local maxima (peaks) in a 1D signal array based on specified conditions.'
+Subjects:
+  - 'Machine Learning'
+  - 'Data Visualization'
+Tags:
+  - 'Scikit-learn'
+  - 'Machine Learning'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/computer-science'
+---
+
+In SciPy, the **`.find_peaks()`** function identifies the indices of local maxima (peaks) in a 1D signal array based on specified conditions.
+
+## Syntax
+
+```pseudo
+scipy.signal.find_peaks(x, height=None, threshold=None, distance=None, prominence=None, width=None, wlen=None, rel_height=0.5, plateau_size=None)
+```
+
+- `x`: The input data in which to search for peaks.
+- `height` (Optional): Specifies the required height of peaks.
+- `threshold` (Optional): The vertical distance to the neighboring samples.
+- `distance` (Optional): Minimum horizontal distance (in samples) between neighboring peaks.
+- `prominence` (Optional): Minimum prominence of peaks.
+- `width` (Optional): Required width of peaks in samples.
+- `wlen` (Optional): Used for calculating the prominence of peaks; specifies the size of the window.
+- `rel_height` (Otional): Used for measuring the width at relative height.
+- `plateau_size` (Optional): Specifies the size of flat peaks (plateaus).
+
+## Example
+
+The following example showcases the `.find_peaks()` function:
+
+```py
+import numpy as np
+from scipy.signal import find_peaks
+
+# Create a signal with some peaks
+signal = np.array([1, 2, 3, 4, 5, 4, 3, 2, 1])
+
+# Find the peaks in the signal
+peaks, _ = find_peaks(signal)
+
+# Print the indices of the peaks
+print(peaks)
+```
+
+The code above generates the following output:
+
+```shell
+[4]
+```