megies on fdsn_raspi_url
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megies on fdsn_raspi_url
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if key == 'NOTE':
try:
value = [cleanup_and_decode_string(line)
for line in value.split(self.line_terminator)
if line]
except:
value = ''
else:
value = cleanup_and_decode_string(value)
Hello, I'm trying to process seismic data from MASW using the SWPROCESS library, it intrinsically uses some obspy libraries. Following the tutorial on the page, which loads a series of .dat data in SEG2 format separated by offset, I am not successful in inverting my data. I've already tried to use my data in SEG2, SEGY and SU format and still no success. With that, my last attempt was to try with the SEG2 format named the same as the one in the tutorial. However, I get the following error:
# Path (relative or full) to a folder containing the data files. Data files must be in either the SEG2 and/or SU data format.
path_to_folder = "data/wghs/"
set0 = [f"{path_to_folder}{x}.dat" for x in range(6, 7)]
fnames_set = [set0]
print(fnames_set)
for set_number, fnames in enumerate(fnames_set):
print(f" set{set_number} includes {len(fnames)} files from {fnames[0]} to {fnames[-1]}")
names = None
workflow = "time-domain"
transform = "fdbf"
fmin, fmax = 3, 100
vmin, vmax, nvel, vspace = 100, 500, 400, "linear"
fdbf_weighting = "sqrt"
fdbf_steering = "cylindrical"
snr = True
noise_begin, noise_end = -0.5, 0.
signal_begin, signal_end = 0., 0.5
%matplotlib qt5
settings = swprocess.Masw.create_settings_dict(workflow=workflow,
trim=trim, trim_begin=trim_begin, trim_end=trim_end,
mute=mute, method=method, window_kwargs=window_kwargs,
transform=transform, fmin=fmin, fmax=fmax, pad=pad, df=df,
vmin=vmin, vmax=vmax, nvel=nvel, vspace=vspace,
weighting=fdbf_weighting, steering=fdbf_steering,
snr=snr, noise_begin=noise_begin, noise_end=noise_end,
signal_begin=signal_begin, signal_end=signal_end,
pad_snr = pad_snr, df_snr=df_snr)
start = time.perf_counter()
wavefieldtransforms = []
for fnames in fnames_set:
wavefieldtransforms.append(swprocess.Masw.run(fnames=fnames, settings=settings))
print(wavefieldtransforms)
end = time.perf_counter()
print(f"Elapsed Time (s): {round(end-start,2)}")
From that I get the following error:
Could anyone help me to solve this problem? I would be extremely grateful!
I am trying to analyse daily seismic recordings near a river to capture signals associated with river processes. It is new for me, and not sure if I am doing things right. I cut the signal in 6 hours windows and tried to plot spectrogram/PSD (not sure of the difference between Spectro and PSD).
Here is the basic python script I used.
import numpy as np
import matplotlib.pyplot as plt
import obspy
from obspy import read
st = read("WU.JSP2.00.ELZ.D.2022.231.000002.SAC_6h")
print(st)
tr=st[0]
print(tr.stats)
sps =int(st[0].stats.sampling_rate)
st.plot()
fig = plt.figure()
ax1 = fig.add_axes([0.1, 0.75, 0.7, 0.2]) #[left bottom width height]
ax2 = fig.add_axes([0.1, 0.1, 0.7, 0.60], sharex=ax1)
ax3 = fig.add_axes([0.83, 0.1, 0.03, 0.6])
t = np.arange(tr.stats.npts) / tr.stats.sampling_rate
ax1.plot(t, tr.copy().data, 'k')
tr.spectrogram(wlen =2sps, per_lap=0.95, dbscale=True, log=True,cmap="rainbow")
st = read("WU.JSP2.00.ELZ.D.2022.231.000002.SAC_12h")
print(st)
tr=st[0]
print(tr.stats)
sps =int(st[0].stats.sampling_rate)
st.plot()
fig = plt.figure()
ax1 = fig.add_axes([0.1, 0.75, 0.7, 0.2]) #[left bottom width height]
ax2 = fig.add_axes([0.1, 0.1, 0.7, 0.60], sharex=ax1)
ax3 = fig.add_axes([0.83, 0.1, 0.03, 0.6])
t = np.arange(tr.stats.npts) / tr.stats.sampling_rate
ax1.plot(t, tr.copy().data, 'k')
tr.spectrogram(wlen =2sps, per_lap=0.95, dbscale=True, log=True,cmap="rainbow")
I don't know how to include the colour scale too. Any advice will be great.
Thx.
We would like to inform you about a public beta release of a new FDSNWS station service at the Italian EIDA node (@INGV). This new services implementation should remove some important performance limitation of the currently used version. The service is available at the following URL: https://webservices.ingv.it/beta/fdsnws/station/1/.
We also would very much appreciate any feedback, bug reports or other comments, in order to catch any issue before the production release occurs which is planned within the next few weeks. Thanks!