seg1d.algorithm.get_peaks

seg1d.algorithm.get_peaks(x, minC=0.7, dst=None)

Peak Detection

Find the peaks of a data array with a minimum value of a peak and an optional distance parameter.

Relies on scipy.signal.find_peaks

Parameters:

xDict[int,List[float]]

{scale:  [correlations] }

Returns:

n x 3 array

sorted by highest to lowest correlation of form [ scale, correlation , peak index ]

Other Parameters:  

minCfloat, optional

-1 to 1

dstreal, optional

int or float

See also

combine_corr

(input for this function)

uniques

(takes the return of this function)

Examples

>>> import numpy as np
>>> import seg1d.algorithm as alg

>>> # convenience function for generating wave
>>> def s(f1, f2, f3): return np.sin( np.linspace(f1, f2, f3) )

Define some scales that have correlations

>>> x = { 10: s(-np.pi*1, np.pi*1, 10), 20: s(-np.pi*2, np.pi*2, 10) }

Query the peaks in the data

>>> np.around(alg.get_peaks(x), decimals=7)
array([[10.       ,  0.9848078,  7.       ],
       [20.       ,  0.9848078,  1.       ],
       [20.       ,  0.8660254,  6.       ]])

Define a minimum for the peak

>>> np.around(alg.get_peaks(x,minC = 0.9), decimals=7)
array([[10.       ,  0.9848078,  7.       ],
       [20.       ,  0.9848078,  1.       ]])