Move use_taupy and taupy_model from s_parameters to p_parameters
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				| @ -226,7 +226,7 @@ def autopickstation(wfstream, pickparam, verbose=False, | ||||
| 
 | ||||
|         # for global seismology: use tau-p method for estimating travel times (needs source and station coords.) | ||||
|         # if not given: sets Lc to infinity to use full stream | ||||
|         if s_params['use_taup'] is True: | ||||
|         if p_params['use_taup'] is True: | ||||
|             Lc = np.inf | ||||
|             print('autopickstation: use_taup flag active.') | ||||
|             if not metadata[1]: | ||||
| @ -237,7 +237,7 @@ def autopickstation(wfstream, pickparam, verbose=False, | ||||
|                 station_coords = get_source_coords(parser, station_id) | ||||
|                 if station_coords and origin: | ||||
|                     source_origin = origin[0] | ||||
|                     model = TauPyModel(s_params['taup_model']) | ||||
|                     model = TauPyModel(p_params['taup_model']) | ||||
|                     arrivals = model.get_travel_times_geo( | ||||
|                         source_origin.depth, | ||||
|                         source_origin.latitude, | ||||
| @ -268,7 +268,7 @@ def autopickstation(wfstream, pickparam, verbose=False, | ||||
|         pstart = max(p_params['pstart'], 0) | ||||
|         pstop = min(p_params['pstop'], len(zdat[0])*zdat[0].stats.delta) | ||||
| 
 | ||||
|         if not s_params['use_taup'] is True or origin: | ||||
|         if p_params['use_taup'] is False or origin: | ||||
|             Lc = p_params['pstop'] - p_params['pstart'] | ||||
| 
 | ||||
|         Lwf = zdat[0].stats.endtime - zdat[0].stats.starttime | ||||
|  | ||||
| @ -1373,8 +1373,8 @@ def get_pickparams(pickparam): | ||||
|     :rtype: (dict, dict, dict, dict) | ||||
|     """ | ||||
|     # Define names of all parameters in different groups | ||||
|     p_parameter_names = 'algoP pstart pstop tlta tsnrz hosorder bpz1 bpz2 pickwinP aictsmooth tsmoothP ausP nfacP tpred1z tdet1z Parorder addnoise Precalcwin minAICPslope minAICPSNR timeerrorsP'.split(' ') | ||||
|     s_parameter_names = 'algoS sstart sstop use_taup taup_model bph1 bph2 tsnrh pickwinS tpred1h tdet1h tpred2h tdet2h Sarorder aictsmoothS tsmoothS ausS minAICSslope minAICSSNR Srecalcwin nfacS timeerrorsS zfac'.split(' ') | ||||
|     p_parameter_names = 'algoP pstart pstop use_taup taup_model tlta tsnrz hosorder bpz1 bpz2 pickwinP aictsmooth tsmoothP ausP nfacP tpred1z tdet1z Parorder addnoise Precalcwin minAICPslope minAICPSNR timeerrorsP checkwindowP minfactorP'.split(' ') | ||||
|     s_parameter_names = 'algoS sstart sstop bph1 bph2 tsnrh pickwinS tpred1h tdet1h tpred2h tdet2h Sarorder aictsmoothS tsmoothS ausS minAICSslope minAICSSNR Srecalcwin nfacS timeerrorsS zfac checkwindowS minfactorS'.split(' ') | ||||
|     first_motion_names = 'minFMSNR fmpickwin minfmweight'.split(' ') | ||||
|     signal_length_names = 'minsiglength minpercent noisefactor'.split(' ') | ||||
|     # Get list of values from pickparam by name | ||||
| @ -1388,7 +1388,7 @@ def get_pickparams(pickparam): | ||||
|     first_motion_params = dict(zip(first_motion_names, fm_parameter_values)) | ||||
|     signal_length_params = dict(zip(signal_length_names, sl_parameter_values)) | ||||
| 
 | ||||
|     s_params['use_taup'] = real_Bool(s_params['use_taup']) | ||||
|     p_params['use_taup'] = real_Bool(p_params['use_taup']) | ||||
| 
 | ||||
|     return p_params, s_params, first_motion_params, signal_length_params | ||||
| 
 | ||||
|  | ||||
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