Merge branch 'feature/parameter_limits' into develop
This commit is contained in:
Darius Arnold
commit
aba1a16f98
@ -1,5 +1,6 @@
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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import numpy as np
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"""
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Default parameters used for picking
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@ -78,11 +79,15 @@ defaults = {'rootpath': {'type': str,
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'vp': {'type': float,
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'tooltip': 'average P-wave velocity',
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'value': 3530.,
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'min': 0.,
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'max': np.inf,
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'namestring': 'P-velocity'},
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'rho': {'type': float,
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'tooltip': 'average rock density [kg/m^3]',
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'value': 2500.,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Density'},
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'Qp': {'type': (float, float),
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@ -94,42 +99,58 @@ defaults = {'rootpath': {'type': str,
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'tooltip': 'start time [s] for calculating CF for P-picking (if TauPy:'
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' seconds relative to estimated onset)',
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'value': 15.0,
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'min': -np.inf,
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'max': np.inf,
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'namestring': 'P start'},
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'pstop': {'type': float,
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'tooltip': 'end time [s] for calculating CF for P-picking (if TauPy:'
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' seconds relative to estimated onset)',
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'value': 60.0,
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'min': -np.inf,
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'max': np.inf,
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'namestring': 'P stop'},
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'sstart': {'type': float,
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'tooltip': 'start time [s] relative to P-onset for calculating CF for S-picking',
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'value': -1.0,
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'min': -np.inf,
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'max': np.inf,
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'namestring': 'S start'},
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'sstop': {'type': float,
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'tooltip': 'end time [s] after P-onset for calculating CF for S-picking',
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'value': 10.0,
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'min': -np.inf,
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'max': np.inf,
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'namestring': 'S stop'},
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'bpz1': {'type': (float, float),
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'tooltip': 'lower/upper corner freq. of first band pass filter Z-comp. [Hz]',
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'value': (2, 20),
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'min': (0., 0.),
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'max': (np.inf, np.inf),
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'namestring': ('Z-bandpass 1', 'Lower', 'Upper')},
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'bpz2': {'type': (float, float),
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'tooltip': 'lower/upper corner freq. of second band pass filter Z-comp. [Hz]',
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'value': (2, 30),
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'min': (0., 0.),
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'max': (np.inf, np.inf),
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'namestring': ('Z-bandpass 2', 'Lower', 'Upper')},
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'bph1': {'type': (float, float),
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'tooltip': 'lower/upper corner freq. of first band pass filter H-comp. [Hz]',
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'value': (2, 15),
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'min': (0., 0.),
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'max': (np.inf, np.inf),
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'namestring': ('H-bandpass 1', 'Lower', 'Upper')},
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'bph2': {'type': (float, float),
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'tooltip': 'lower/upper corner freq. of second band pass filter z-comp. [Hz]',
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'value': (2, 20),
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'min': (0., 0.),
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'max': (np.inf, np.inf),
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'namestring': ('H-bandpass 2', 'Lower', 'Upper')},
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'algoP': {'type': str,
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@ -140,76 +161,106 @@ defaults = {'rootpath': {'type': str,
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'tlta': {'type': float,
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'tooltip': 'for HOS-/AR-AIC-picker, length of LTA window [s]',
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'value': 7.0,
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'min': 0.,
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'max': np.inf,
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'namestring': 'LTA window'},
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'hosorder': {'type': int,
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'tooltip': 'for HOS-picker, order of Higher Order Statistics',
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'value': 4,
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'min': 0,
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'max': np.inf,
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'namestring': 'HOS order'},
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'Parorder': {'type': int,
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'tooltip': 'for AR-picker, order of AR process of Z-component',
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'value': 2,
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'min': 0,
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'max': np.inf,
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'namestring': 'AR order P'},
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'tdet1z': {'type': float,
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'tooltip': 'for AR-picker, length of AR determination window [s] for Z-component, 1st pick',
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'value': 1.2,
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'min': 0.,
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'max': np.inf,
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'namestring': 'AR det. window Z 1'},
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'tpred1z': {'type': float,
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'tooltip': 'for AR-picker, length of AR prediction window [s] for Z-component, 1st pick',
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'value': 0.4,
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'min': 0.,
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'max': np.inf,
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'namestring': 'AR pred. window Z 1'},
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'tdet2z': {'type': float,
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'tooltip': 'for AR-picker, length of AR determination window [s] for Z-component, 2nd pick',
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'value': 0.6,
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'min': 0.,
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'max': np.inf,
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'namestring': 'AR det. window Z 2'},
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'tpred2z': {'type': float,
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'tooltip': 'for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick',
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'value': 0.2,
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'min': 0.,
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'max': np.inf,
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'namestring': 'AR pred. window Z 2'},
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'addnoise': {'type': float,
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'tooltip': 'add noise to seismogram for stable AR prediction',
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'value': 0.001,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Add noise'},
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'tsnrz': {'type': (float, float, float, float),
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'tooltip': 'for HOS/AR, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]',
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'value': (3, 0.1, 0.5, 1.0),
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'min': (0., 0., 0., 0.),
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'max': (np.inf, np.inf, np.inf, np.inf),
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'namestring': ('SNR windows P', 'Noise', 'Safety', 'Signal', 'Slope')},
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'pickwinP': {'type': float,
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'tooltip': 'for initial AIC pick, length of P-pick window [s]',
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'value': 3.0,
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'min': 0.,
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'max': np.inf,
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'namestring': 'AIC window P'},
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'Precalcwin': {'type': float,
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'tooltip': 'for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)',
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'value': 6.0,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Recal. window P'},
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'aictsmooth': {'type': float,
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'tooltip': 'for HOS/AR, take average of samples for smoothing of AIC-function [s]',
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'value': 0.2,
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'min': 0.,
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'max': np.inf,
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'namestring': 'AIC smooth P'},
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'tsmoothP': {'type': float,
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'tooltip': 'for HOS/AR, take average of samples in this time window for smoothing CF [s]',
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'value': 0.1,
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'min': 0.,
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'max': np.inf,
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'namestring': 'CF smooth P'},
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'ausP': {'type': float,
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'tooltip': 'for HOS/AR, artificial uplift of samples (aus) of CF (P)',
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'value': 0.001,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Artificial uplift P'},
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'nfacP': {'type': float,
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'tooltip': 'for HOS/AR, noise factor for noise level determination (P)',
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'value': 1.3,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Noise factor P'},
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'algoS': {'type': str,
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@ -220,61 +271,85 @@ defaults = {'rootpath': {'type': str,
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'tdet1h': {'type': float,
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'tooltip': 'for HOS/AR, length of AR-determination window [s], H-components, 1st pick',
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'value': 0.8,
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'min': 0.,
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'max': np.inf,
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'namestring': 'AR det. window H 1'},
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'tpred1h': {'type': float,
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'tooltip': 'for HOS/AR, length of AR-prediction window [s], H-components, 1st pick',
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'value': 0.4,
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'min': 0.,
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'max': np.inf,
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'namestring': 'AR pred. window H 1'},
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'tdet2h': {'type': float,
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'tooltip': 'for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick',
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'value': 0.6,
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'min': 0.,
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'max': np.inf,
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'namestring': 'AR det. window H 2'},
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'tpred2h': {'type': float,
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'tooltip': 'for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick',
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'value': 0.3,
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'min': 0.,
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'max': np.inf,
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'namestring': 'AR pred. window H 2'},
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'Sarorder': {'type': int,
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'tooltip': 'for AR-picker, order of AR process of H-components',
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'value': 4,
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'min': 0,
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'max': np.inf,
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'namestring': 'AR order S'},
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'Srecalcwin': {'type': float,
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'tooltip': 'for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)',
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'value': 5.0,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Recal. window S'},
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'pickwinS': {'type': float,
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'tooltip': 'for initial AIC pick, length of S-pick window [s]',
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'value': 3.0,
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'min': 0.,
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'max': np.inf,
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'namestring': 'AIC window S'},
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'tsnrh': {'type': (float, float, float, float),
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'tooltip': 'for ARH/AR3, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]',
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'value': (2, 0.2, 1.5, 0.5),
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'min': (0., 0., 0., 0.),
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'max': (np.inf, np.inf, np.inf, np.inf),
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'namestring': ('SNR windows S', 'Noise', 'Safety', 'Signal', 'Slope')},
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'aictsmoothS': {'type': float,
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'tooltip': 'for AIC-picker, take average of samples in this time window for smoothing of AIC-function [s]',
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'value': 0.5,
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'min': 0.,
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'max': np.inf,
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'namestring': 'AIC smooth S'},
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'tsmoothS': {'type': float,
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'tooltip': 'for AR-picker, take average of samples for smoothing CF [s] (S)',
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'value': 0.7,
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'min': 0.,
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'max': np.inf,
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'namestring': 'CF smooth S'},
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'ausS': {'type': float,
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'tooltip': 'for HOS/AR, artificial uplift of samples (aus) of CF (S)',
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'value': 0.9,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Artificial uplift S'},
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'nfacS': {'type': float,
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'tooltip': 'for AR-picker, noise factor for noise level determination (S)',
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'value': 1.5,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Noise factor S'},
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'minfmweight': {'type': int,
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@ -285,103 +360,143 @@ defaults = {'rootpath': {'type': str,
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'minFMSNR': {'type': float,
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'tooltip': 'miniumum required SNR for first-motion determination',
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'value': 2.,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Min SNR'},
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'fmpickwin': {'type': float,
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'tooltip': 'pick window [s] around P onset for calculating zero crossings',
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'value': 0.2,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Zero crossings window'},
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'timeerrorsP': {'type': (float, float, float, float),
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'tooltip': 'discrete time errors [s] corresponding to picking weights [0 1 2 3] for P',
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'value': (0.01, 0.02, 0.04, 0.08),
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'min': (0., 0., 0., 0.),
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'max': (np.inf, np.inf, np.inf, np.inf),
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'namestring': ('Time errors P', '0', '1', '2', '3')},
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'timeerrorsS': {'type': (float, float, float, float),
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'tooltip': 'discrete time errors [s] corresponding to picking weights [0 1 2 3] for S',
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'value': (0.04, 0.08, 0.16, 0.32),
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'min': (0., 0., 0., 0.),
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'max': (np.inf, np.inf, np.inf, np.inf),
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'namestring': ('Time errors S', '0', '1', '2', '3')},
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'minAICPslope': {'type': float,
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'tooltip': 'below this slope [counts/s] the initial P pick is rejected',
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'value': 0.8,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Min. slope P'},
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'minAICPSNR': {'type': float,
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'tooltip': 'below this SNR the initial P pick is rejected',
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'value': 1.1,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Min. SNR P'},
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'minAICSslope': {'type': float,
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'tooltip': 'below this slope [counts/s] the initial S pick is rejected',
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'value': 1.,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Min. slope S'},
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'minAICSSNR': {'type': float,
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'tooltip': 'below this SNR the initial S pick is rejected',
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'value': 1.5,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Min. SNR S'},
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|
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'minsiglength': {'type': float,
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'tooltip': 'length of signal part for which amplitudes must exceed noiselevel [s]',
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'value': 1.,
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'min': 0.,
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'max': np.inf,
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'namestring': 'Min. signal length'},
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|
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'noisefactor': {'type': float,
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'tooltip': 'noiselevel*noisefactor=threshold',
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'value': 1.0,
|
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'min': 0.,
|
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'max': np.inf,
|
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'namestring': 'Noise factor'},
|
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|
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'minpercent': {'type': float,
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'tooltip': 'required percentage of amplitudes exceeding threshold',
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'value': 10.,
|
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'min': 0.,
|
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'max': np.inf,
|
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'namestring': 'Min amplitude [%]'},
|
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|
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'zfac': {'type': float,
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'tooltip': 'P-amplitude must exceed at least zfac times RMS-S amplitude',
|
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'value': 1.5,
|
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'min': 0.,
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'max': np.inf,
|
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'namestring': 'Z factor'},
|
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|
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'mdttolerance': {'type': float,
|
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'tooltip': 'maximum allowed deviation of P picks from median [s]',
|
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'value': 6.0,
|
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'min': 0.,
|
||||
'max': np.inf,
|
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'namestring': 'Median tolerance'},
|
||||
|
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'wdttolerance': {'type': float,
|
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'tooltip': 'maximum allowed deviation from Wadati-diagram',
|
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'value': 1.0,
|
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'min': 0.,
|
||||
'max': np.inf,
|
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'namestring': 'Wadati tolerance'},
|
||||
|
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'jackfactor': {'type': float,
|
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'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',
|
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'value': 5.0,
|
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'namestring': 'Jackknife safety factor'},
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'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',
|
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'value': 5.0,
|
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'min': 0.,
|
||||
'max': np.inf,
|
||||
'namestring': 'Jackknife safety factor'},
|
||||
|
||||
'WAscaling': {'type': (float, float, float),
|
||||
'tooltip': 'Scaling relation (log(Ao)+Alog(r)+Br+C) of Wood-Anderson amplitude Ao [nm] \
|
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If zeros are set, original Richter magnitude is calculated!',
|
||||
'value': (0., 0., 0.),
|
||||
'min': (0., 0., 0.),
|
||||
'max': (np.inf, np.inf, np.inf),
|
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'namestring': ('Wood-Anderson scaling', '', '', '')},
|
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|
||||
'magscaling': {'type': (float, float),
|
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'tooltip': 'Scaling relation for derived local magnitude [a*Ml+b]. \
|
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If zeros are set, no scaling of network magnitude is applied!',
|
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'value': (0., 0.),
|
||||
'min': (0., 0.),
|
||||
'max': (np.inf, np.inf),
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||||
'namestring': ('Local mag. scaling', '', '')},
|
||||
|
||||
'minfreq': {'type': (float, float),
|
||||
'tooltip': 'Lower filter frequency [P, S]',
|
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'value': (1.0, 1.0),
|
||||
'min': (0., 0.),
|
||||
'max': (np.inf, np.inf),
|
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'namestring': ('Lower freq.', 'P', 'S')},
|
||||
|
||||
'maxfreq': {'type': (float, float),
|
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'tooltip': 'Upper filter frequency [P, S]',
|
||||
'value': (10.0, 10.0),
|
||||
'min': (0., 0.),
|
||||
'max': (np.inf, np.inf),
|
||||
'namestring': ('Upper freq.', 'P', 'S')},
|
||||
|
||||
'filter_order': {'type': (int, int),
|
||||
'tooltip': 'filter order [P, S]',
|
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'value': (2, 2),
|
||||
'min': (0, 0),
|
||||
'max': (np.inf, np.inf),
|
||||
'namestring': ('Order', 'P', 'S')},
|
||||
|
||||
'filter_type': {'type': (str, str),
|
||||
|
||||
@ -93,6 +93,11 @@ class PylotParameter(object):
|
||||
return None
|
||||
|
||||
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
|
||||
|
||||
def __delitem__(self, key):
|
||||
@ -190,6 +195,32 @@ class PylotParameter(object):
|
||||
all_names += self.get_special_para_names()['quality']
|
||||
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):
|
||||
"""
|
||||
Check type of value against expected type of param.
|
||||
|
||||
Loading…
Reference in New Issue
Block a user