pwtools.signal.find_peaks

pwtools.signal.find_peaks(y, x=None, k=3, spread=2, ymin=None)[source]

Simple peak finding algorithm.

Find all peaks where y > ymin. If x given, also extract peak maxima positions by fitting a spline of order k to each found peak. To find minima, just use -y.

Parameters:

  • y (1d array_like) – data with peaks

  • x (1d array_like, optional, len(y)) – x axis

  • k (int) – order of spline

  • spread (int) – Use 2*spread+1 points around each peak to fit a spline. Note that we need 2*spread+1 > k.

  • ymin (float, optional) – Find all peaks above that value.

Returns:

  • idx0, pos0

  • idx0 (indices of peaks from finite diffs, each peak is at x[idx0[i]])

  • pos0 (refined x-positions of peaks if x given, else None)

Examples

>>> from pwtools.signal import gauss, find_peaks
>>> from pwtools import num
>>> x=linspace(0,10,300); y=0.2*gauss(x-0.5,.1) + gauss(x-2,.1) + 0.7*gauss(x-3,0.1) + gauss(x-6,1)
>>> # ymin=0.4: ignore first peak at x=0.5
>>> find_peaks(y,x, ymin=0.4)
([60, 90, 179], [2.000231296097065, 3.0007122565950572, 5.999998055132549])
>>> idx0, pos0=find_peaks(y,x, ymin=0.4)
>>> spl=num.Spline(x,y)
>>> plot(x,y)
>>> for x0 in pos0:
...    plot([x0], [spl(x0)], 'ro')