STACK_METHOD = 'sum' # Choose either 'sum', 'product', or 'semblance'
TIME_METHOD = 'celerity' # Choose either 'celerity' or 'fdtd'
CELERITY = 320 # [m/s]
S = grid_search(processed_st=st_proc,
grid=grid,
time_method=TIME_METHOD,
starttime=STARTTIME,
endtime=ENDTIME,
stack_method=STACK_METHOD,
celerity=CELERITY)
#%% (4) Plot
from rtm import plot_time_slice, plot_record_section, get_peak_coordinates
fig_slice = plot_time_slice(S,
st_proc,
label_stations=False,
hires=False,
plot_peak=True)
time_max, y_max, x_max, _, _ = get_peak_coordinates(S, unproject=S.UTM)
fig = plot_record_section(st_proc,
origin_time=time_max,
source_location=(y_max, x_max),
plot_celerity='range',
label_waveforms=False)
fig.axes[0].set_ylim(bottom=1100) # Start at this distance (km) from source
from rtm import (plot_time_slice, plot_record_section, get_peak_coordinates,
plot_st)
import numpy as np
fig_st = plot_st(st,
filt=[FREQ_MIN, FREQ_MAX],
equal_scale=False,
remove_response=True,
label_waveforms=True)
fig_slice = plot_time_slice(S,
st_proc,
label_stations=True,
dem=dem,
plot_peak=True)
time_max, y_max, x_max, peaks, props = get_peak_coordinates(S,
global_max=False,
height=3,
min_time=2,
unproject=S.UTM)
peak_ind = np.argmax(props['peak_heights'])
fig = plot_record_section(st_proc,
origin_time=time_max[peak_ind],
source_location=(y_max[peak_ind], x_max[peak_ind]),
plot_celerity=S.celerity,
label_waveforms=True)