Merge branch 'develop' of 134.147.164.251:/data/git/pylot into develop
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				| @ -507,6 +507,7 @@ def wadaticheck(pickdic, dttolerance, iplot): | ||||
|         checkedSPtimes = [] | ||||
|         # calculate deviations from Wadati regression | ||||
|         ii = 0 | ||||
|         ibad = 0 | ||||
|         for key in pickdic: | ||||
|             if pickdic[key].has_key('SPt'): | ||||
|                 wddiff = abs(pickdic[key]['SPt'] - wdfit[ii]) | ||||
| @ -517,6 +518,7 @@ def wadaticheck(pickdic, dttolerance, iplot): | ||||
|                     # (not used anymore) | ||||
|                     marker = 'badWadatiCheck' | ||||
|                     pickdic[key]['S']['weight'] = 9 | ||||
|                     ibad += 1 | ||||
|                 else: | ||||
|                     marker = 'goodWadatiCheck' | ||||
|                     checkedPpick =  UTCDateTime(pickdic[key]['P']['mpp']) | ||||
| @ -536,6 +538,7 @@ def wadaticheck(pickdic, dttolerance, iplot): | ||||
|         	# calculate vp/vs ratio after check | ||||
|         	cvpvsr = p2[0] + 1 | ||||
|         	print 'wadaticheck: Average Vp/Vs ratio after check:', cvpvsr | ||||
|                 print 'wadatacheck: Skipped %d S pick(s).' % ibad  | ||||
|         else: | ||||
|                 print '###############################################' | ||||
|         	print 'wadatacheck: Not enough checked S-P times available!' | ||||
| @ -696,7 +699,7 @@ def checkPonsets(pickdic, dttolerance, iplot): | ||||
|     # these picks did not pass jackknife test | ||||
|     badjk = np.where(PHI_pseudo > 2 * xjack) | ||||
|     badjkstations = np.array(stations)[badjk] | ||||
|     print 'checkPonsets: %d picks did not pass jackknife test!' % len(badjkstations) | ||||
|     print 'checkPonsets: %d pick(s) did not pass jackknife test!' % len(badjkstations) | ||||
| 
 | ||||
|     # calculate median from these picks | ||||
|     pmedian = np.median(np.array(Ppicks)[ij]) | ||||
| @ -708,8 +711,8 @@ def checkPonsets(pickdic, dttolerance, iplot): | ||||
|     goodstations = np.array(stations)[igood] | ||||
|     badstations = np.array(stations)[ibad] | ||||
| 
 | ||||
|     print 'checkPonsets: %d picks deviate too much from median!' % len(ibad) | ||||
|     print 'checkPonsets: Skipped %d P onsets out of %d' % (len(badstations) \ | ||||
|     print 'checkPonsets: %d pick(s) deviate too much from median!' % len(ibad) | ||||
|     print 'checkPonsets: Skipped %d P pick(s) out of %d' % (len(badstations) \ | ||||
|             + len(badjkstations), len(stations)) | ||||
| 
 | ||||
|     goodmarker = 'goodPonsetcheck' | ||||
|  | ||||
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