# Array response (questions )

Hello Martin Gal and the rest of obspy users,

First of all thank you so much for your rapid response.

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??

1. 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,