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Merge branch 'feature/parameter_limits' into develop

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Darius Arnold 2018-03-19 11:44:22 +01:00
commit aba1a16f98
2 changed files with 149 additions and 3 deletions
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pylot/core/io/default_parameters.py
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@ -1,5 +1,6 @@
#!/usr/bin/env python #!/usr/bin/env python
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import numpy as np
""" """
Default parameters used for picking Default parameters used for picking
@ -78,11 +79,15 @@ defaults = {'rootpath': {'type': str,
'vp': {'type': float, 'vp': {'type': float,
'tooltip': 'average P-wave velocity', 'tooltip': 'average P-wave velocity',
'value': 3530., 'value': 3530.,
'min': 0.,
'max': np.inf,
'namestring': 'P-velocity'}, 'namestring': 'P-velocity'},
'rho': {'type': float, 'rho': {'type': float,
'tooltip': 'average rock density [kg/m^3]', 'tooltip': 'average rock density [kg/m^3]',
'value': 2500., 'value': 2500.,
'min': 0.,
'max': np.inf,
'namestring': 'Density'}, 'namestring': 'Density'},
'Qp': {'type': (float, float), 'Qp': {'type': (float, float),
@ -94,42 +99,58 @@ defaults = {'rootpath': {'type': str,
'tooltip': 'start time [s] for calculating CF for P-picking (if TauPy:' 'tooltip': 'start time [s] for calculating CF for P-picking (if TauPy:'
' seconds relative to estimated onset)', ' seconds relative to estimated onset)',
'value': 15.0, 'value': 15.0,
'min': -np.inf,
'max': np.inf,
'namestring': 'P start'}, 'namestring': 'P start'},
'pstop': {'type': float, 'pstop': {'type': float,
'tooltip': 'end time [s] for calculating CF for P-picking (if TauPy:' 'tooltip': 'end time [s] for calculating CF for P-picking (if TauPy:'
' seconds relative to estimated onset)', ' seconds relative to estimated onset)',
'value': 60.0, 'value': 60.0,
'min': -np.inf,
'max': np.inf,
'namestring': 'P stop'}, 'namestring': 'P stop'},
'sstart': {'type': float, 'sstart': {'type': float,
'tooltip': 'start time [s] relative to P-onset for calculating CF for S-picking', 'tooltip': 'start time [s] relative to P-onset for calculating CF for S-picking',
'value': -1.0, 'value': -1.0,
'min': -np.inf,
'max': np.inf,
'namestring': 'S start'}, 'namestring': 'S start'},
'sstop': {'type': float, 'sstop': {'type': float,
'tooltip': 'end time [s] after P-onset for calculating CF for S-picking', 'tooltip': 'end time [s] after P-onset for calculating CF for S-picking',
'value': 10.0, 'value': 10.0,
'min': -np.inf,
'max': np.inf,
'namestring': 'S stop'}, 'namestring': 'S stop'},
'bpz1': {'type': (float, float), 'bpz1': {'type': (float, float),
'tooltip': 'lower/upper corner freq. of first band pass filter Z-comp. [Hz]', 'tooltip': 'lower/upper corner freq. of first band pass filter Z-comp. [Hz]',
'value': (2, 20), 'value': (2, 20),
'min': (0., 0.),
'max': (np.inf, np.inf),
'namestring': ('Z-bandpass 1', 'Lower', 'Upper')}, 'namestring': ('Z-bandpass 1', 'Lower', 'Upper')},
'bpz2': {'type': (float, float), 'bpz2': {'type': (float, float),
'tooltip': 'lower/upper corner freq. of second band pass filter Z-comp. [Hz]', 'tooltip': 'lower/upper corner freq. of second band pass filter Z-comp. [Hz]',
'value': (2, 30), 'value': (2, 30),
'min': (0., 0.),
'max': (np.inf, np.inf),
'namestring': ('Z-bandpass 2', 'Lower', 'Upper')}, 'namestring': ('Z-bandpass 2', 'Lower', 'Upper')},
'bph1': {'type': (float, float), 'bph1': {'type': (float, float),
'tooltip': 'lower/upper corner freq. of first band pass filter H-comp. [Hz]', 'tooltip': 'lower/upper corner freq. of first band pass filter H-comp. [Hz]',
'value': (2, 15), 'value': (2, 15),
'min': (0., 0.),
'max': (np.inf, np.inf),
'namestring': ('H-bandpass 1', 'Lower', 'Upper')}, 'namestring': ('H-bandpass 1', 'Lower', 'Upper')},
'bph2': {'type': (float, float), 'bph2': {'type': (float, float),
'tooltip': 'lower/upper corner freq. of second band pass filter z-comp. [Hz]', 'tooltip': 'lower/upper corner freq. of second band pass filter z-comp. [Hz]',
'value': (2, 20), 'value': (2, 20),
'min': (0., 0.),
'max': (np.inf, np.inf),
'namestring': ('H-bandpass 2', 'Lower', 'Upper')}, 'namestring': ('H-bandpass 2', 'Lower', 'Upper')},
'algoP': {'type': str, 'algoP': {'type': str,
@ -140,76 +161,106 @@ defaults = {'rootpath': {'type': str,
'tlta': {'type': float, 'tlta': {'type': float,
'tooltip': 'for HOS-/AR-AIC-picker, length of LTA window [s]', 'tooltip': 'for HOS-/AR-AIC-picker, length of LTA window [s]',
'value': 7.0, 'value': 7.0,
'min': 0.,
'max': np.inf,
'namestring': 'LTA window'}, 'namestring': 'LTA window'},
'hosorder': {'type': int, 'hosorder': {'type': int,
'tooltip': 'for HOS-picker, order of Higher Order Statistics', 'tooltip': 'for HOS-picker, order of Higher Order Statistics',
'value': 4, 'value': 4,
'min': 0,
'max': np.inf,
'namestring': 'HOS order'}, 'namestring': 'HOS order'},
'Parorder': {'type': int, 'Parorder': {'type': int,
'tooltip': 'for AR-picker, order of AR process of Z-component', 'tooltip': 'for AR-picker, order of AR process of Z-component',
'value': 2, 'value': 2,
'min': 0,
'max': np.inf,
'namestring': 'AR order P'}, 'namestring': 'AR order P'},
'tdet1z': {'type': float, 'tdet1z': {'type': float,
'tooltip': 'for AR-picker, length of AR determination window [s] for Z-component, 1st pick', 'tooltip': 'for AR-picker, length of AR determination window [s] for Z-component, 1st pick',
'value': 1.2, 'value': 1.2,
'min': 0.,
'max': np.inf,
'namestring': 'AR det. window Z 1'}, 'namestring': 'AR det. window Z 1'},
'tpred1z': {'type': float, 'tpred1z': {'type': float,
'tooltip': 'for AR-picker, length of AR prediction window [s] for Z-component, 1st pick', 'tooltip': 'for AR-picker, length of AR prediction window [s] for Z-component, 1st pick',
'value': 0.4, 'value': 0.4,
'min': 0.,
'max': np.inf,
'namestring': 'AR pred. window Z 1'}, 'namestring': 'AR pred. window Z 1'},
'tdet2z': {'type': float, 'tdet2z': {'type': float,
'tooltip': 'for AR-picker, length of AR determination window [s] for Z-component, 2nd pick', 'tooltip': 'for AR-picker, length of AR determination window [s] for Z-component, 2nd pick',
'value': 0.6, 'value': 0.6,
'min': 0.,
'max': np.inf,
'namestring': 'AR det. window Z 2'}, 'namestring': 'AR det. window Z 2'},
'tpred2z': {'type': float, 'tpred2z': {'type': float,
'tooltip': 'for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick', 'tooltip': 'for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick',
'value': 0.2, 'value': 0.2,
'min': 0.,
'max': np.inf,
'namestring': 'AR pred. window Z 2'}, 'namestring': 'AR pred. window Z 2'},
'addnoise': {'type': float, 'addnoise': {'type': float,
'tooltip': 'add noise to seismogram for stable AR prediction', 'tooltip': 'add noise to seismogram for stable AR prediction',
'value': 0.001, 'value': 0.001,
'min': 0.,
'max': np.inf,
'namestring': 'Add noise'}, 'namestring': 'Add noise'},
'tsnrz': {'type': (float, float, float, float), 'tsnrz': {'type': (float, float, float, float),
'tooltip': 'for HOS/AR, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]', 'tooltip': 'for HOS/AR, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]',
'value': (3, 0.1, 0.5, 1.0), 'value': (3, 0.1, 0.5, 1.0),
'min': (0., 0., 0., 0.),
'max': (np.inf, np.inf, np.inf, np.inf),
'namestring': ('SNR windows P', 'Noise', 'Safety', 'Signal', 'Slope')}, 'namestring': ('SNR windows P', 'Noise', 'Safety', 'Signal', 'Slope')},
'pickwinP': {'type': float, 'pickwinP': {'type': float,
'tooltip': 'for initial AIC pick, length of P-pick window [s]', 'tooltip': 'for initial AIC pick, length of P-pick window [s]',
'value': 3.0, 'value': 3.0,
'min': 0.,
'max': np.inf,
'namestring': 'AIC window P'}, 'namestring': 'AIC window P'},
'Precalcwin': {'type': float, 'Precalcwin': {'type': float,
'tooltip': 'for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)', 'tooltip': 'for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)',
'value': 6.0, 'value': 6.0,
'min': 0.,
'max': np.inf,
'namestring': 'Recal. window P'}, 'namestring': 'Recal. window P'},
'aictsmooth': {'type': float, 'aictsmooth': {'type': float,
'tooltip': 'for HOS/AR, take average of samples for smoothing of AIC-function [s]', 'tooltip': 'for HOS/AR, take average of samples for smoothing of AIC-function [s]',
'value': 0.2, 'value': 0.2,
'min': 0.,
'max': np.inf,
'namestring': 'AIC smooth P'}, 'namestring': 'AIC smooth P'},
'tsmoothP': {'type': float, 'tsmoothP': {'type': float,
'tooltip': 'for HOS/AR, take average of samples in this time window for smoothing CF [s]', 'tooltip': 'for HOS/AR, take average of samples in this time window for smoothing CF [s]',
'value': 0.1, 'value': 0.1,
'min': 0.,
'max': np.inf,
'namestring': 'CF smooth P'}, 'namestring': 'CF smooth P'},
'ausP': {'type': float, 'ausP': {'type': float,
'tooltip': 'for HOS/AR, artificial uplift of samples (aus) of CF (P)', 'tooltip': 'for HOS/AR, artificial uplift of samples (aus) of CF (P)',
'value': 0.001, 'value': 0.001,
'min': 0.,
'max': np.inf,
'namestring': 'Artificial uplift P'}, 'namestring': 'Artificial uplift P'},
'nfacP': {'type': float, 'nfacP': {'type': float,
'tooltip': 'for HOS/AR, noise factor for noise level determination (P)', 'tooltip': 'for HOS/AR, noise factor for noise level determination (P)',
'value': 1.3, 'value': 1.3,
'min': 0.,
'max': np.inf,
'namestring': 'Noise factor P'}, 'namestring': 'Noise factor P'},
'algoS': {'type': str, 'algoS': {'type': str,
@ -220,61 +271,85 @@ defaults = {'rootpath': {'type': str,
'tdet1h': {'type': float, 'tdet1h': {'type': float,
'tooltip': 'for HOS/AR, length of AR-determination window [s], H-components, 1st pick', 'tooltip': 'for HOS/AR, length of AR-determination window [s], H-components, 1st pick',
'value': 0.8, 'value': 0.8,
'min': 0.,
'max': np.inf,
'namestring': 'AR det. window H 1'}, 'namestring': 'AR det. window H 1'},
'tpred1h': {'type': float, 'tpred1h': {'type': float,
'tooltip': 'for HOS/AR, length of AR-prediction window [s], H-components, 1st pick', 'tooltip': 'for HOS/AR, length of AR-prediction window [s], H-components, 1st pick',
'value': 0.4, 'value': 0.4,
'min': 0.,
'max': np.inf,
'namestring': 'AR pred. window H 1'}, 'namestring': 'AR pred. window H 1'},
'tdet2h': {'type': float, 'tdet2h': {'type': float,
'tooltip': 'for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick', 'tooltip': 'for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick',
'value': 0.6, 'value': 0.6,
'min': 0.,
'max': np.inf,
'namestring': 'AR det. window H 2'}, 'namestring': 'AR det. window H 2'},
'tpred2h': {'type': float, 'tpred2h': {'type': float,
'tooltip': 'for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick', 'tooltip': 'for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick',
'value': 0.3, 'value': 0.3,
'min': 0.,
'max': np.inf,
'namestring': 'AR pred. window H 2'}, 'namestring': 'AR pred. window H 2'},
'Sarorder': {'type': int, 'Sarorder': {'type': int,
'tooltip': 'for AR-picker, order of AR process of H-components', 'tooltip': 'for AR-picker, order of AR process of H-components',
'value': 4, 'value': 4,
'min': 0,
'max': np.inf,
'namestring': 'AR order S'}, 'namestring': 'AR order S'},
'Srecalcwin': {'type': float, 'Srecalcwin': {'type': float,
'tooltip': 'for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)', 'tooltip': 'for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)',
'value': 5.0, 'value': 5.0,
'min': 0.,
'max': np.inf,
'namestring': 'Recal. window S'}, 'namestring': 'Recal. window S'},
'pickwinS': {'type': float, 'pickwinS': {'type': float,
'tooltip': 'for initial AIC pick, length of S-pick window [s]', 'tooltip': 'for initial AIC pick, length of S-pick window [s]',
'value': 3.0, 'value': 3.0,
'min': 0.,
'max': np.inf,
'namestring': 'AIC window S'}, 'namestring': 'AIC window S'},
'tsnrh': {'type': (float, float, float, float), 'tsnrh': {'type': (float, float, float, float),
'tooltip': 'for ARH/AR3, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]', 'tooltip': 'for ARH/AR3, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]',
'value': (2, 0.2, 1.5, 0.5), 'value': (2, 0.2, 1.5, 0.5),
'min': (0., 0., 0., 0.),
'max': (np.inf, np.inf, np.inf, np.inf),
'namestring': ('SNR windows S', 'Noise', 'Safety', 'Signal', 'Slope')}, 'namestring': ('SNR windows S', 'Noise', 'Safety', 'Signal', 'Slope')},
'aictsmoothS': {'type': float, 'aictsmoothS': {'type': float,
'tooltip': 'for AIC-picker, take average of samples in this time window for smoothing of AIC-function [s]', 'tooltip': 'for AIC-picker, take average of samples in this time window for smoothing of AIC-function [s]',
'value': 0.5, 'value': 0.5,
'min': 0.,
'max': np.inf,
'namestring': 'AIC smooth S'}, 'namestring': 'AIC smooth S'},
'tsmoothS': {'type': float, 'tsmoothS': {'type': float,
'tooltip': 'for AR-picker, take average of samples for smoothing CF [s] (S)', 'tooltip': 'for AR-picker, take average of samples for smoothing CF [s] (S)',
'value': 0.7, 'value': 0.7,
'min': 0.,
'max': np.inf,
'namestring': 'CF smooth S'}, 'namestring': 'CF smooth S'},
'ausS': {'type': float, 'ausS': {'type': float,
'tooltip': 'for HOS/AR, artificial uplift of samples (aus) of CF (S)', 'tooltip': 'for HOS/AR, artificial uplift of samples (aus) of CF (S)',
'value': 0.9, 'value': 0.9,
'min': 0.,
'max': np.inf,
'namestring': 'Artificial uplift S'}, 'namestring': 'Artificial uplift S'},
'nfacS': {'type': float, 'nfacS': {'type': float,
'tooltip': 'for AR-picker, noise factor for noise level determination (S)', 'tooltip': 'for AR-picker, noise factor for noise level determination (S)',
'value': 1.5, 'value': 1.5,
'min': 0.,
'max': np.inf,
'namestring': 'Noise factor S'}, 'namestring': 'Noise factor S'},
'minfmweight': {'type': int, 'minfmweight': {'type': int,
@ -285,103 +360,143 @@ defaults = {'rootpath': {'type': str,
'minFMSNR': {'type': float, 'minFMSNR': {'type': float,
'tooltip': 'miniumum required SNR for first-motion determination', 'tooltip': 'miniumum required SNR for first-motion determination',
'value': 2., 'value': 2.,
'min': 0.,
'max': np.inf,
'namestring': 'Min SNR'}, 'namestring': 'Min SNR'},
'fmpickwin': {'type': float, 'fmpickwin': {'type': float,
'tooltip': 'pick window [s] around P onset for calculating zero crossings', 'tooltip': 'pick window [s] around P onset for calculating zero crossings',
'value': 0.2, 'value': 0.2,
'min': 0.,
'max': np.inf,
'namestring': 'Zero crossings window'}, 'namestring': 'Zero crossings window'},
'timeerrorsP': {'type': (float, float, float, float), 'timeerrorsP': {'type': (float, float, float, float),
'tooltip': 'discrete time errors [s] corresponding to picking weights [0 1 2 3] for P', 'tooltip': 'discrete time errors [s] corresponding to picking weights [0 1 2 3] for P',
'value': (0.01, 0.02, 0.04, 0.08), 'value': (0.01, 0.02, 0.04, 0.08),
'min': (0., 0., 0., 0.),
'max': (np.inf, np.inf, np.inf, np.inf),
'namestring': ('Time errors P', '0', '1', '2', '3')}, 'namestring': ('Time errors P', '0', '1', '2', '3')},
'timeerrorsS': {'type': (float, float, float, float), 'timeerrorsS': {'type': (float, float, float, float),
'tooltip': 'discrete time errors [s] corresponding to picking weights [0 1 2 3] for S', 'tooltip': 'discrete time errors [s] corresponding to picking weights [0 1 2 3] for S',
'value': (0.04, 0.08, 0.16, 0.32), 'value': (0.04, 0.08, 0.16, 0.32),
'min': (0., 0., 0., 0.),
'max': (np.inf, np.inf, np.inf, np.inf),
'namestring': ('Time errors S', '0', '1', '2', '3')}, 'namestring': ('Time errors S', '0', '1', '2', '3')},
'minAICPslope': {'type': float, 'minAICPslope': {'type': float,
'tooltip': 'below this slope [counts/s] the initial P pick is rejected', 'tooltip': 'below this slope [counts/s] the initial P pick is rejected',
'value': 0.8, 'value': 0.8,
'min': 0.,
'max': np.inf,
'namestring': 'Min. slope P'}, 'namestring': 'Min. slope P'},
'minAICPSNR': {'type': float, 'minAICPSNR': {'type': float,
'tooltip': 'below this SNR the initial P pick is rejected', 'tooltip': 'below this SNR the initial P pick is rejected',
'value': 1.1, 'value': 1.1,
'min': 0.,
'max': np.inf,
'namestring': 'Min. SNR P'}, 'namestring': 'Min. SNR P'},
'minAICSslope': {'type': float, 'minAICSslope': {'type': float,
'tooltip': 'below this slope [counts/s] the initial S pick is rejected', 'tooltip': 'below this slope [counts/s] the initial S pick is rejected',
'value': 1., 'value': 1.,
'min': 0.,
'max': np.inf,
'namestring': 'Min. slope S'}, 'namestring': 'Min. slope S'},
'minAICSSNR': {'type': float, 'minAICSSNR': {'type': float,
'tooltip': 'below this SNR the initial S pick is rejected', 'tooltip': 'below this SNR the initial S pick is rejected',
'value': 1.5, 'value': 1.5,
'min': 0.,
'max': np.inf,
'namestring': 'Min. SNR S'}, 'namestring': 'Min. SNR S'},
'minsiglength': {'type': float, 'minsiglength': {'type': float,
'tooltip': 'length of signal part for which amplitudes must exceed noiselevel [s]', 'tooltip': 'length of signal part for which amplitudes must exceed noiselevel [s]',
'value': 1., 'value': 1.,
'min': 0.,
'max': np.inf,
'namestring': 'Min. signal length'}, 'namestring': 'Min. signal length'},
'noisefactor': {'type': float, 'noisefactor': {'type': float,
'tooltip': 'noiselevel*noisefactor=threshold', 'tooltip': 'noiselevel*noisefactor=threshold',
'value': 1.0, 'value': 1.0,
'min': 0.,
'max': np.inf,
'namestring': 'Noise factor'}, 'namestring': 'Noise factor'},
'minpercent': {'type': float, 'minpercent': {'type': float,
'tooltip': 'required percentage of amplitudes exceeding threshold', 'tooltip': 'required percentage of amplitudes exceeding threshold',
'value': 10., 'value': 10.,
'min': 0.,
'max': np.inf,
'namestring': 'Min amplitude [%]'}, 'namestring': 'Min amplitude [%]'},
'zfac': {'type': float, 'zfac': {'type': float,
'tooltip': 'P-amplitude must exceed at least zfac times RMS-S amplitude', 'tooltip': 'P-amplitude must exceed at least zfac times RMS-S amplitude',
'value': 1.5, 'value': 1.5,
'min': 0.,
'max': np.inf,
'namestring': 'Z factor'}, 'namestring': 'Z factor'},
'mdttolerance': {'type': float, 'mdttolerance': {'type': float,
'tooltip': 'maximum allowed deviation of P picks from median [s]', 'tooltip': 'maximum allowed deviation of P picks from median [s]',
'value': 6.0, 'value': 6.0,
'min': 0.,
'max': np.inf,
'namestring': 'Median tolerance'}, 'namestring': 'Median tolerance'},
'wdttolerance': {'type': float, 'wdttolerance': {'type': float,
'tooltip': 'maximum allowed deviation from Wadati-diagram', 'tooltip': 'maximum allowed deviation from Wadati-diagram',
'value': 1.0, 'value': 1.0,
'min': 0.,
'max': np.inf,
'namestring': 'Wadati tolerance'}, 'namestring': 'Wadati tolerance'},
'jackfactor': {'type': float, 'jackfactor': {'type': float,
'tooltip': 'pick is removed if the variance of the subgroup with the pick removed is larger than the mean variance of all subgroups times safety factor', 'tooltip': 'pick is removed if the variance of the subgroup with the pick removed is larger than the mean variance of all subgroups times safety factor',
'value': 5.0, 'value': 5.0,
'namestring': 'Jackknife safety factor'}, 'min': 0.,
'max': np.inf,
'namestring': 'Jackknife safety factor'},
'WAscaling': {'type': (float, float, float), 'WAscaling': {'type': (float, float, float),
'tooltip': 'Scaling relation (log(Ao)+Alog(r)+Br+C) of Wood-Anderson amplitude Ao [nm] \ 'tooltip': 'Scaling relation (log(Ao)+Alog(r)+Br+C) of Wood-Anderson amplitude Ao [nm] \
If zeros are set, original Richter magnitude is calculated!', If zeros are set, original Richter magnitude is calculated!',
'value': (0., 0., 0.), 'value': (0., 0., 0.),
'min': (0., 0., 0.),
'max': (np.inf, np.inf, np.inf),
'namestring': ('Wood-Anderson scaling', '', '', '')}, 'namestring': ('Wood-Anderson scaling', '', '', '')},
'magscaling': {'type': (float, float), 'magscaling': {'type': (float, float),
'tooltip': 'Scaling relation for derived local magnitude [a*Ml+b]. \ 'tooltip': 'Scaling relation for derived local magnitude [a*Ml+b]. \
If zeros are set, no scaling of network magnitude is applied!', If zeros are set, no scaling of network magnitude is applied!',
'value': (0., 0.), 'value': (0., 0.),
'min': (0., 0.),
'max': (np.inf, np.inf),
'namestring': ('Local mag. scaling', '', '')}, 'namestring': ('Local mag. scaling', '', '')},
'minfreq': {'type': (float, float), 'minfreq': {'type': (float, float),
'tooltip': 'Lower filter frequency [P, S]', 'tooltip': 'Lower filter frequency [P, S]',
'value': (1.0, 1.0), 'value': (1.0, 1.0),
'min': (0., 0.),
'max': (np.inf, np.inf),
'namestring': ('Lower freq.', 'P', 'S')}, 'namestring': ('Lower freq.', 'P', 'S')},
'maxfreq': {'type': (float, float), 'maxfreq': {'type': (float, float),
'tooltip': 'Upper filter frequency [P, S]', 'tooltip': 'Upper filter frequency [P, S]',
'value': (10.0, 10.0), 'value': (10.0, 10.0),
'min': (0., 0.),
'max': (np.inf, np.inf),
'namestring': ('Upper freq.', 'P', 'S')}, 'namestring': ('Upper freq.', 'P', 'S')},
'filter_order': {'type': (int, int), 'filter_order': {'type': (int, int),
'tooltip': 'filter order [P, S]', 'tooltip': 'filter order [P, S]',
'value': (2, 2), 'value': (2, 2),
'min': (0, 0),
'max': (np.inf, np.inf),
'namestring': ('Order', 'P', 'S')}, 'namestring': ('Order', 'P', 'S')},
'filter_type': {'type': (str, str), 'filter_type': {'type': (str, str),

31
pylot/core/io/inputs.py
View File

@ -93,6 +93,11 @@ class PylotParameter(object):
return None return None
def __setitem__(self, key, value): def __setitem__(self, key, value):
try:
value = self.check_range(value, self.__defaults[key]['max'], self.__defaults[key]['min'])
except KeyError:
# no min/max values in defaults
pass
self.__parameter[key] = value self.__parameter[key] = value
def __delitem__(self, key): def __delitem__(self, key):
@ -190,6 +195,32 @@ class PylotParameter(object):
all_names += self.get_special_para_names()['quality'] all_names += self.get_special_para_names()['quality']
return all_names return all_names
@staticmethod
def check_range(value, max_value, min_value):
"""
Check if value is within the min/max values defined in default_parameters. Works for tuple and scalar values.
:param value: Value to be checked against min/max range
:param max_value: Maximum allowed value, tuple or scalar
:param min_value: Minimum allowed value, tuple or scalar
:return: value tuple/scalar clamped to the valid range
>>> checkRange(-5, 10, 0)
0
>>> checkRange((-5., 100.), (10., 10.), (0., 0.))
(0.0, 10.0)
"""
try:
# Try handling tuples by comparing their elements
comparisons = [(a > b) for a, b in zip(value, max_value)]
if True in comparisons:
value = tuple(max_value[i] if comp else value[i] for i, comp in enumerate(comparisons))
comparisons = [(a < b) for a, b in zip(value, min_value)]
if True in comparisons:
value = tuple(min_value[i] if comp else value[i] for i, comp in enumerate(comparisons))
except TypeError:
value = max(min_value, min(max_value, value))
return value
def checkValue(self, param, value): def checkValue(self, param, value):
""" """
Check type of value against expected type of param. Check type of value against expected type of param.