def update_models(self, model, vpvs):
logger.debug('### Found new chain model')
vp, vs, dep = Model.get_stepmodel(model, vpvs=vpvs, mantle=self.mantle)
self.vs_step = np.roll(self.vs_step, -1, axis=0) # rolling up models
nantmp = np.ones(self.modellength) * np.nan
nantmp[:vs.size] = vs
self.vs_step[-1] = nantmp
self.dep_step = np.roll(self.dep_step, -1, axis=0) # rolling up models
nantmp = np.ones(self.modellength) * np.nan
nantmp[:dep.size] = dep
self.dep_step[-1] = nantmp
vp, vs, h = Model.get_vp_vs_h(model, vpvs=vpvs, mantle=self.mantle)
ymod = self.compute_synth(h, vs, vp)
for i, tline in enumerate(self.targetlines):
if tline is not None:
tline.set_ydata(ymod[i])
# # create LineCollection
segments = [
np.column_stack([x, y])
for x, y in zip(self.vs_step, self.dep_step)
]
self.modelcollection.set_segments(segments)
a = np.repeat(([0, 1], ), self.capacity, axis=0)
b = np.array([[v] * 2 for v in self.vpvss])
segments = [np.column_stack([x, y]) for x, y in zip(b, a)]
self.vpvscollection.set_segments(segments)
def update_chain(self):
print('New chain index:', self.chainidx)
# if new chain is chosen
self.modelmatrix, self.likes, self.noises, self.vpvss = self.chainarrays[
self.chainidx]
nantmp = np.ones(self.modellength) * np.nan
# reset vs and dep matrix to nan
self.vs_step = np.ones((self.capacity, self.modellength)) * np.nan
self.dep_step = np.ones((self.capacity, self.modellength)) * np.nan
for i, model in enumerate(self.modelmatrix):
# if nan model, the first element is also nan !
if ~np.isnan(model[0]):
vp, vs, dep = Model.get_stepmodel(model,
vpvs=self.vpvss[i],
mantle=self.mantle)
dep[-1] = self.priors['z'][-1] * 1.5
self.vs_step = np.roll(self.vs_step, -1,
axis=0) # rolling up models
vs = nantmp[:vs.size] = vs
self.vs_step[-1][:vs.size] = vs
self.dep_step = np.roll(self.dep_step, -1,
axis=0) # rolling up models
dep = nantmp[:dep.size] = dep
self.dep_step[-1][:dep.size] = dep
# update title
self.axes[0].set_title('Chain %d' % self.chainidx)
lastmodel = model
lastvpvs = self.vpvss[-1]
# immediately update data fit lines
vp, vs, h = Model.get_vp_vs_h(lastmodel,
vpvs=lastvpvs,
mantle=self.mantle)
ymod = self.compute_synth(h, vs, vp)
for i, tline in enumerate(self.targetlines):
if tline is not None:
tline.set_ydata(ymod[i])
# # create LineCollection and update velocity models
segments = [
np.column_stack([x, y])
for x, y in zip(self.vs_step, self.dep_step)
]
self.modelcollection.set_segments(segments)
self.likeline.set_ydata(self.likes)
self.axes[3].set_ylim(
[np.nanmin(self.likes) * 0.999,
np.nanmax(self.likes) * 1.001])
# vpvs
a = np.repeat(([0, 1], ), self.capacity, axis=0)
b = np.array([[v] * 2 for v in self.vpvss])
segments = [np.column_stack([x, y]) for x, y in zip(b, a)]
self.vpvscollection.set_segments(segments)
for i, sline in enumerate(self.sigmalines):
if sline is not None:
ref = self.targetrefs[i]
idx = self.targetrefs.index(ref)
sline.set_ydata(self.noises.T[1::2][idx])
self.axes[4].set_ylim([
np.nanmin(self.noises.T[1::2]) * 0.98,
np.nanmax(self.noises.T[1::2]) * 1.02
])
self.fig.canvas.draw_idle()
