completition of Docstring
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				| @ -6,11 +6,15 @@ import numpy as np | ||||
| 
 | ||||
| def crosscorrsingle(wf1, wf2, taumax): | ||||
|     ''' | ||||
| 
 | ||||
|     :param Wx: | ||||
|     :param Wy: | ||||
|     :param taumax: | ||||
|     :return: | ||||
|     Calculates the crosscorrelation between two waveforms with a defined maximum timedifference. | ||||
|     :param wf1: first waveformdata | ||||
|     :type wf1: list | ||||
|     :param wf2: second waveformdata | ||||
|     :type wf2: list | ||||
|     :param taumax: maximum time difference between waveforms | ||||
|     :type taumax: positive integer | ||||
|     :return: returns the crosscorrelation funktion 'c' and the lagvector 'l' | ||||
|     :rtype: c and l are lists | ||||
|     ''' | ||||
|     N = len(wf1) | ||||
|     c = np.zeros(2 * taumax - 1) | ||||
| @ -83,10 +87,13 @@ def wfscrosscorr(weights, wfs, taumax): | ||||
| 
 | ||||
|     SWB 26.01.2010 as arranged with Thomas Meier and Monika Bischoff | ||||
| 
 | ||||
|     :param weights: | ||||
|     :param wfs: | ||||
|     :param taumax: | ||||
|     :return: | ||||
|     :param weights: weighting factors for the single components | ||||
|     :type weights: tuple | ||||
|     :param wfs: tuple of `~numpy.array` object containing waveform data | ||||
|     :type wfs: tuple | ||||
|     :param taumax: maximum time difference | ||||
|     :type taumax: positive integer | ||||
|     :return: returns cross correlation function normalized by the waveform energy | ||||
|     ''' | ||||
| 
 | ||||
|     ccnorm = 0. | ||||
|  | ||||
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