def xminmax(self, traces):
return trace.minmaxtime(traces, key=self.map_xscaling)
def call(self):
self.cleanup()
viewer = self.get_viewer()
if viewer.lowpass is None or viewer.highpass is None:
self.fail('highpass and lowpass in viewer must be set!')
traces = []
for trs in self.chopper_selected_traces(fallback=True):
for tr in trs:
tr.downsample_to(1/20.)
tr.lowpass(4, viewer.lowpass)
tr.highpass(4, viewer.highpass)
traces.extend(trs)
if not traces:
self.fail('no traces selected')
tmin, tmax = trace.minmaxtime(traces, key=lambda x: None)[None]
try:
obspy_traces = [ p2o_trace(tr, viewer.get_station(viewer.station_key(tr)) ) for tr in traces ]
except KeyError:
self.fail('station information missing')
st = stream.Stream(traces=obspy_traces)
smax = 0.5
# Execute sonic
kwargs = dict(
# slowness grid: X min, X max, Y min, Y max, Slow Step
sll_x=-smax, slm_x=smax, sll_y=-smax, slm_y=smax, sl_s=smax/20.,
# sliding window properties
win_len=5.0, win_frac=0.1,
# frequency properties
frqlow=viewer.highpass, frqhigh=viewer.lowpass, prewhiten=0,
# restrict output
semb_thres=-1.0e9, vel_thres=-1.0e9, verbose=True, timestamp='mlabday',
stime=UTCDateTime(tmin), etime=UTCDateTime(tmax)
)
#out = sonic(st, **kwargs)
out = array_analysis.array_processing(st, **kwargs)
cmap = cm.hot_r
pi = np.pi
#
# make output human readable, adjust backazimuth to values between 0 and 360
t, rel_power, abs_power, baz, slow = out.T
baz[baz < 0.0] += 360.
# choose number of fractions in plot (desirably 360 degree/N is an integer!)
N = int(self.numberOfFraction)
abins = np.arange(N + 1) * 360. / N
sbins = np.linspace(0., smax, N + 1)
# sum rel power in bins given by abins and sbins
hist, baz_edges, sl_edges = np.histogram2d(baz, slow,
bins=[abins, sbins], weights=rel_power)
# transform to gradient
baz_edges = baz_edges / 180 * np.pi
# add polar and colorbar axes
fig = self.pylab(get='figure')
cax = fig.add_axes([0.85, 0.2, 0.05, 0.5])
ax = fig.add_axes([0.10, 0.1, 0.70, 0.7], polar=True)
dh = abs(sl_edges[1] - sl_edges[0])
dw = abs(baz_edges[1] - baz_edges[0])
# circle through backazimuth
for i, row in enumerate(hist):
bars = ax.bar(left=(pi / 2 - (i + 1) * dw) * np.ones(N),
height=dh * np.ones(N),
width=dw, bottom=dh * np.arange(N),
color=cmap(row / hist.max()))
ax.set_xticks([pi / 2, 0, 3. / 2 * pi, pi])
ax.set_xticklabels(['N', 'E', 'S', 'W'])
# set slowness limits
ax.set_ylim(0., smax)
ColorbarBase(cax, cmap=cmap,
norm=Normalize(vmin=hist.min(), vmax=hist.max()))
