Hello Martin Gal and the rest of obspy users,
First of all thank you so much for your rapid response.
- Comments of the array,
The mean depth value of this deployment is at 4800 m, ant the data I will finally try to handle is going to be treated to avoid “tilt noise” and the microseism noise", so my idea is to reduce the overall noise to a good snr level.
As you told me I’ve been trying to plot my array response by using array_transff_freqslowness(), but something is wrong when i try to draw it.(I ve attach my script). So in your last email did you suggest that I have to plot ( sx,sy) plot and the module(s) versus frecuency right? do you have any example??
- Another good question.
there is some way in obspy to make stack, to get a beamforming seismogram ( I mean to, I have the 5 seismograms and I would like to get the coherent sum of that), this is because in the example https://docs.obspy.org/tutorial/code_snippets/beamforming_fk_analysis.html, it show a kind of vespagram more than a beamforming seismogram.
Script
import numpy as np
import matplotlib.pyplot as plt
from obspy.imaging.cm import obspy_sequential
from obspy.signal.array_analysis import array_transff_freqslowness
generate array coordinates
coords = np.array([[-10.373608,35.909685, 0.021], [-10.554655,35.594688, 0.154], [-10.988262,35.595025,0.023],[-10.988500, 36.220166,0.204], [-10.555266,36.220216,0.003]])
#coords /= 1000.
#Slowness units are in s/m ¿this is right)
#frecuency units are in Hz, limit sample frecuency/2
slim= 0.001
sxmin = -slim
sxmax = slim
symin = -slim
symax = slim
sstep = slim / 100.
flim = 25
fstep= flim / 100.
fmax=flim
fmin=0
array_transff_freqslowness(coords, slim, sstep, fmin, fmax, fstep,coordsys=‘lonlat’)
plt.pcolor(np.arange(sxmin, sxmax + sstep * 1.1, sstep) - sstep / 2.,
np.arange(symin, symax + sstep * 1.1, sstep) - sstep / 2.)
plt.colorbar()
plt.clim(vmin=0., vmax=1.)
plt.xlim(sxmin, sxmax)
plt.ylim(symin, symax)
plt.show()
I am very grateful for anyone that could help me, 