Hello Thomas et al,
I have SEED data that is separated by year, month and day (rather than year
and day) – does data_structure recognise months as a value? It doesn’t
mention it in the documentation. Would it be as simple as using
“NET\STA\YEAR\NET.STA.CHAN.YEAR.MONTH.DAY” for the data structure?
Cheers
Jim
--
*Jim Whiteley*
*GW4+ DTP PhD Student*
British Geological Survey, Keyworth, Nottingham
Tel: +44(0)115 9363422 Mob: +44(0)7990 836422
*Please note, I am primarily based at BGS Keyworth*
Hello, i am a user of MSnoise. I have already confirm my email and user to become a member of the mailing list. The problem is that I do not have any password assigned so i can not enter to the MSnoise archives.
Could you be kind to give me instructions about how to get this done?
Thank you.
Good day
I need help with the following question
I am a student at a South African University and am new to MSnoise. I am
working on my thesis trying to find velocity change before and after an
earthquake. I have done cross correlation using my own code, but still need
to do the stretching method to obtain the velocity change I require. Is it
possible to use my correlations in MSNoise without the help of MySQL or
SQlite. If yes, please give me some guide line as to how to do it.
Kind regards
LINDA
Hello everyone,
I am trying to upgrade to MSNoise 1.5 but there seems to be a problem. When
I try to to a *msnoise install* or *msnoise **upgrade_db* with my current
version (1.3.1) an error occurs.
*Traceback (most recent call last):*
* File "/usr/local/anaconda/bin/msnoise", line 9, in <module>*
* load_entry_point('msnoise==0+unknown', 'console_scripts', 'msnoise')()*
* File
"/usr/local/anaconda/lib/python2.7/site-packages/msnoise/scripts/msnoise.py",
line 614, in run*
* cli(obj={})*
* File
"/usr/local/anaconda/lib/python2.7/site-packages/click-4.0-py2.7.egg/click/core.py",
line 664, in __call__*
* return self.main(*args, **kwargs)*
* File
"/usr/local/anaconda/lib/python2.7/site-packages/click-4.0-py2.7.egg/click/core.py",
line 644, in main*
* rv = self.invoke(ctx)*
* File
"/usr/local/anaconda/lib/python2.7/site-packages/click-4.0-py2.7.egg/click/core.py",
line 991, in invoke*
* return _process_result(sub_ctx.command.invoke(sub_ctx))*
* File
"/usr/local/anaconda/lib/python2.7/site-packages/click-4.0-py2.7.egg/click/core.py",
line 837, in invoke*
* return ctx.invoke(self.callback, **ctx.params)*
* File
"/usr/local/anaconda/lib/python2.7/site-packages/click-4.0-py2.7.egg/click/core.py",
line 464, in invoke*
* return callback(*args, **kwargs)*
* File
"/usr/local/anaconda/lib/python2.7/site-packages/msnoise/scripts/msnoise.py",
line 53, in admin*
* from ..msnoise_admin import main*
* File
"/usr/local/anaconda/lib/python2.7/site-packages/msnoise/msnoise_admin.py",
line 137, in <module>*
* from .api import **
* File "/usr/local/anaconda/lib/python2.7/site-packages/msnoise/api.py",
line 21, in <module>*
* from obspy.signal.invsim import cosine_taper*
*ImportError: cannot import name cosine_taper*
In fact, when I run *msnoise test* every test fails. Does anyone know what
the problem is?
Thanks in advance!
Oscar
*Pre-IAVCEI 2017 MSNoise workshop*
We are pleased to announce a *2-day MSNoise workshop* on*Saturday 12 and
Sunday 13 August 2017*, the weekend before IAVCEI 2017 in Portland!
The aim of this workshop is to demonstrate the powers and limitations of
using ambient seismic noise for seismo-volcanological studies using
continuous data, for example using ambient seismic noise
cross-correlation for computing dv/v, surface wave tomography or
microseismic activity tracking. The MSNoise package will be introduced
and then used by participants on provided demo data (from Piton de la
Fournaise volcano). New developments to MSNoise will be presented too:
an easier configuration interface, an improved pluggability and the
demonstration of external plugins currently in development (e.g. Quality
Control, Power Spectral Density, TOMO or SARA). In the framework of this
conference, we will particularly introduce the Seismic Amplitude Ratio
Analysis (SARA) that was specifically designed to track magma migration
at volcanoes using seismic data (e.g., Taisne et al., 2011).
During the first session, we will make sure everyone has the right
software and provide a refresher course on Python/ObsPy. The second
session will contain review presentations related to “the seismic
interferometry” followed by a practical using MSNoise. The last session
will specifically cover the Seimic Amplitude Ratio location technique
and the Ambient noise-based Tomography, before a MSNoise hacking session.
*Day 1:*
* 09.30 – 10.00: Welcome
* 10.00 – 11.00: Installation “party”
* 11.00 – 12.30: Refresher course on Python/ObsPy (version 1.0 & new
features)
* 12.30 – 13.30: Lunch (not provided)
* 13.30 – 15.30: Introduction on Noise – What is Noise? How do we use
it? Cross-Correlation? dv/v? – MSNoise general introduction
* 15.30 – 18.00: MSNoise practical
*Day 2:*
* 09.30 – 10.00: Welcome
* 10.00 – 12.00: Noise-based studies (SARA, TOMO)
* 13.30 – 16.00: Advanced MSNoise Practical (Jupyter notebooks, API, etc)
Because of high organisational costs, we can’t afford to organise this
workshop for free. We have fixed the fee to 230 USD per person. Payments
will be done online directly while registering for the IAVCEI meeting.
To ensure the quality of the experience for everyone, we will not accept
more than 30 participants. Each participant is required to have a
sufficiently decent (and fast!) laptop with software requirements
installed beforehand (instructions will follow). Participants are not
expected to be Python experts at all, but having a little experience in
programming will be useful.
*Information on MSNoise:* MSNoise is the first complete software package
for extracting signal from noise. MSNoise is a fully-integrated solution
that automatically scans data archives and determines which jobs need to
be done whenever the scheduled task is executed (http://www.msnoise.org).
*Registration:* Via the IAVCEI meeting registration page.
*Worth reading:* Lecocq, Thomas, Corentin Caudron, et Florent Brenguier
(2014), MSNoise, a Python Package for Monitoring Seismic Velocity
Changes Using Ambient Seismic Noise, /Seismological Research Letters/,
/85/(3), 715‑726, doi:10.1785/0220130073
<http://srl.geoscienceworld.org/content/85/3/715.full>.
http://srl.geoscienceworld.org/content/85/3/715.full And the release
notes of the latest versions (please read 1.4
<http://msnoise.org/doc/releasenotes/msnoise-1.4.html> and 1.5
<http://msnoise.org/doc/releasenotes/msnoise-1.5.html>).
Thomas Lecocq & Corentin Caudron
--
Dr. Thomas Lecocq
Geologist - Seismologist
Seismology - Gravimetry
Royal Observatory of Belgium
*
* * * * *
* * * *
---------
http://www.seismology.behttp://msnoise.orghttp://twitter.com/#!/Seismologie_behttps://www.facebook.com/seismologie.be
Dear community,
About 1 year after the last major release (MSNoise 1.4
<http://msnoise.org/doc/releasenotes/msnoise-1.4.html>) we are proud to
announce the new MSNoise 1.5
<http://msnoise.org/doc/releasenotes/msnoise-1.5.html#>. It is a *major*
release, with a massive amount of work since the last one: in GitHub
numbers
<https://github.com/ROBelgium/MSNoise/graphs/contributors?from=2016-06-02&to…>
, it’s over 120 commits and over 2500 lines of code and documentation
changed or added!
MSNoise 1.5 introduces a series of *new features* :
* We have started to move core math functions to ObsPy, currently the
only one ready is linear_regression, a function I wrote to remove
the dependency to |statsmodels|, required to move mwcs to ObsPy later.
* The preprocessing routine has been isolated, rewritten and
optimized. It is now a standalone script, callable by plugins. It
returns a Stream object with all the data needed for the analysis.
* This change in preprocessing was done mostly to allow
cross-component, auto- correlation and cross-correlation, with or
without rotation, to be done with the same code. CC, SC and AC are
now supported in MSNoise with proper whitening (possible to disable
spectral whitening for specific cases).
* This documentation is now available in PDF
<http://msnoise.org/doc/MSNoise.pdf> too (easier for offline usage)
and it also includes a new tutorial for setting up the MySQL server
and Workbench.
* Last but not least: MSNoise is “tested” automatically on Linux
(thanks to TravisCI) & Windows (thanks to Appveyor), for Python
versions 2.7 and 3.5. With MSNoise 1.5 we also added the MacOSX
tests on TravisCI. With these tests, we can guarantee MSNoise works
on different platforms and Anaconda (or miniconda) python versions.
This version has benefited from outputs/ideas/pull requests/questions
from several users/friends (listed alphabetically):
* Raphael De Plaen
* Clare Donaldson
* Robert Green
* Aurelien Mordret
* Lukas Preiswerk
* The participants to the NERC MSNoise Liverpool Workshop in January 2017
* all others (don’t be mad :-) )
Thanks to all for using MSNoise, and please, let us know why/how you use
it (and please cite it!)!
To date, we found/are aware of 25 publications using MSNoise ! That’s
the best validation of our project ever ! See the full list on the
MSNoise website <http://www.msnoise.org/they-cite-msnoise/>.
/Thomas, Corentin and others/
------------------------------------------------------------------------
PS: if you use MSNoise for your research and prepare publications,
*please consider citing it*:
*Lecocq, T., C. Caudron, et F. Brenguier (2014)*, MSNoise, a Python
Package for Monitoring Seismic Velocity Changes Using Ambient Seismic
Noise, /Seismological Research Letters/, 85(3), 715‑726,
doi:10.1785/0220130073.
--
Dr. Thomas Lecocq
Geologist - Seismologist
Seismology - Gravimetry
Royal Observatory of Belgium
*
* * * * *
* * * *
---------
http://www.seismology.behttp://msnoise.orghttp://twitter.com/#!/Seismologie_behttps://www.facebook.com/seismologie.be