diff --git a/pylot/core/pick/utils.py b/pylot/core/pick/utils.py index ea662b24..17bd3f4d 100644 --- a/pylot/core/pick/utils.py +++ b/pylot/core/pick/utils.py @@ -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'