'HalfSinusoidSTF': gf.HalfSinusoidSTF, 'ResonatorSTF': gf.ResonatorSTF}
def base_stf(cls, name): return cls.cls[name]()
if event.depth is None: event.depth = 0.
base_source = gf.SFSource.from_pyrocko_event(event)
stf = STFType.base_stf(self.stf_type) stf.duration = event.duration or 0.0
base_source.stf = stf
subs = dict( event_name=event.name, event_time=util.time_to_str(event.time))
problem = SFProblem( name=expand_template(self.name_template, subs), base_source=base_source, target_groups=target_groups, targets=targets, ranges=self.ranges, distance_min=self.distance_min, stf_type=self.stf_type, norm_exponent=self.norm_exponent, nthreads=self.nthreads)
return problem
Parameter('time', 's', label='Time'), Parameter('north_shift', 'm', label='Northing', **as_km), Parameter('east_shift', 'm', label='Easting', **as_km), Parameter('depth', 'm', label='Depth', **as_km), Parameter('fn', 'N', label='$F_{n}$'), Parameter('fe', 'N', label='$F_{e}$'), Parameter('fd', 'N', label='$F_{d}$')]
'HalfSinusoidSTF': [ Parameter('duration', 's', label='Duration')], 'ResonatorSTF': [ Parameter('duration', 's', label='Duration'), Parameter('frequency', 'Hz', label='Frequency')]}
Problem.__init__(self, **kwargs) self.deps_cache = {} self.problem_parameters = self.problem_parameters \ + self.problem_parameters_stf[self.stf_type] self._base_stf = STFType.base_stf(self.stf_type)
d_stf = {} for p in self.problem_parameters_stf[self.stf_type]: d_stf[p.name] = float(d[p.name])
return self._base_stf.clone(**d_stf)
d = self.get_parameter_dict(x)
p = {} for k in self.base_source.keys(): if k in d: p[k] = float( self.ranges[k].make_relative(self.base_source[k], d[k]))
source = self.base_source.clone(stf=self.get_stf(d), **p) return source
pass
return [ stf[p.name] for p in self.problem_parameters_stf[self.stf_type]]
x = num.array([ source.time - self.base_source.time, source.north_shift, source.east_shift, source.depth, source.fn, source.fe, source.fd, ] + self.pack_stf(source.stf), dtype=num.float)
return x
x = num.zeros(self.nparameters) for i in range(self.nparameters): x[i] = rstate.uniform(xbounds[i, 0], xbounds[i, 1])
return x.tolist()
return x
pass
def get_plot_classes(cls):
SFProblem SFProblemConfig '''.split() |