MSNoise 1.3¶
Release date: 20 March 2015
Release type: major
Release notes:
Introduction¶
8 months after the last bugfix release (MSNoise 1.2.5), and 17 months after the last major release (MSNoise 1.2) we are proud to announce the new MSNoise 1.3. It is a major release, with a massive amount of work since the last release: in GitHub numbers , it’s over 100 commits and about 3500 new lines of code and documentation added ! MSNoise 1.3 introduces a brand new way of executing the workflow. The workflow in itself doesn’t change, so experienced users as well as new users reading the SRL publication will find their way easily!
MSNoise is now a Python Package, allowing a single (and easy) install for
all your projects and/or all users using pip
. The new top-level msnoise
command contains all the steps of the workflow, plus new additions, as the very
useful reset
command to easily mark all jobs “T”odo. The msnoise plot
command group which includes seven plots, all directly callable from the command
line, without needing to hack/edit the source codes. About hacking: MSNoise has
now a proper documented API which allows pythonistas to write their own plots,
computation steps, …, while interacting with the database and the data
archive! The “dynamic time lag” allows to use parts of the coda that is
dependent from the interstation distance (provided station coordinates are
defined).
Finally, MSNoise is now tested and automatically checked by Travis-CI!
This version has benefited from outputs/ideas/pull requests/questions from several users:
Rebecca Kramer
Carmelo Sammarco
Oscar Alberto Castro Artola
Kasper van Wijk
Kohtaro R. Araragi
Esteban Chaves
Adrian Shelley
Weston Thelen
Robert Abbott
Jean Battaglia
Sébastien Carniato
Xiao Wang
Lion Krisher
Tobias Megies
all participants to the 2014 Pre-AGU MSNoise workshop
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!)!
Thomas Lecocq & Corentin Caudron
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.
MSNoise is a real Python Package¶
This is probably the most important change since the original release of MSNoise 1.0 (August 2013), it represents a massive amount of work since the last release (1.2.5 in June 2014), and is probably the most needed by users! In GitHub numbers , it’s over 100 commits and about 3500 new lines of code (and of documentation!) added !
In practice, what does change ?
MSNoise is installable using
pip
oreasy_install
, soon usingconda
MSNoise is installed in the common “site-package/” folder of one’s python install.
Once installed, it is available for all users, all projects.
It allows updating MSNoise for all projects at once.
It removes all python files from project folders, which is much cleaner.
MSNoise being installed in the standard lib directories means it shouldn’t
write or output anything in those folders. To facilitate the launch of commnands
a new top level msnoise
command has been created, and should be available
right after installing.
msnoise
is now a top-level command¶
Users of MSNoise will have to change the way they call the steps, i.e.:
python s000_installer.py
becomesmsnoise install
python s001_configurator.py
becomesmsnoise config
python s002_populate_station_table.py
becomesmsnoise populate
python s01_scan_archive.py
becomesmsnoise scan_archive
python s02_new_jobs.py
becomesmsnoise new_jobs
python s03_compute_cc.py
becomesmsnoise compute_cc
python s04_stack.py
becomesmsnoise stack
python s05_compute_mwcs.py
becomesmsnoise compute_mwcs
python s06_compute_dtt.py
becomesmsnoise compute_dtt
All the commands are visible using the --help
argument:
msnoise --help
Usage: msnoise-script.py [OPTIONS] COMMAND [ARGS]...
Options:
-t, --threads INTEGER Number of threads to use (only affects modules that
are designed to do parallel processing)
--help Show this message and exit.
Commands:
bugreport This command launches the Bug Report script.
compute_cc Computes the CC jobs (based on the "New Jobs"...
compute_dtt Computes the dt/t jobs based on the new MWCS...
compute_mwcs Computes the MWCS based on the new stacked...
compute_stretching [experimental] Computes the stretching based...
config This command launches the Configurator.
info Outputs general information about the current...
install This command launches the installer.
ipython Launches an ipython notebook in the current...
new_jobs Determines if new CC jobs are to be defined
plot Top level command to trigger different plots
populate Rapidly scan the archive filenames and find...
reset Resets the job to "T"odo.
scan_archive Scan the archive and insert into the Data...
stack Stacks the [REF] and/or [MOV] windows
test Runs the test suite, should be executed in an...
upgrade_db Upgrade the database from pre-1.3 to MSNoise...
The parameters/arguments of each command are explained using its own --help
, for example:
msnoise reset --help
Usage: msnoise-script.py reset [OPTIONS] JOBTYPE
Resets the job to "T"odo. ARG is [CC] or [DTT]. By default only resets
jobs "I"n progress. --all resets all jobs, whatever the flag value
Options:
-a, --all Reset all jobs
--help Show this message and exit.
The description of each step has been updated in the documentation.
msnoise plot
: Plotting made easy¶
As explained above, msnoise
is a top level command available in your
command prompt. MSNoise 1.3 includes several plots which are available using the
msnoise plot
command. See Plotting to view all plots!
All the available plots are listed using the --help
argument:
msnoise plot --help
Usage: msnoise-script.py plot [OPTIONS] COMMAND [ARGS]...
Top level command to trigger different plots
Options:
--help Show this message and exit.
Commands:
ccftime Plots the dv/v (parses the dt/t results)
data_availability Plots the Data Availability vs time
distance Plots the REFs of all pairs vs distance
dvv Plots the dv/v (parses the dt/t results)
interferogram Plots the interferogram between sta1 and sta2...
mwcs Plots the mwcs results between sta1 and sta2...
station_map Plots the station map (very basic)
Same as above, sub-commands have their own --help
:
msnoise plot interferogram --help
Usage: [OPTIONS] STA1 STA2 [EXTRA_ARGS]...
Plots the interferogram between sta1 and sta2 (parses the CCFs)
STA1 and STA2 must be provided with this format: NET.STA !
Options:
-f, --filterid INTEGER Filter ID
-c, --comp TEXT Components (ZZ, ZR,...)
-m, --mov_stack INTEGER Mov Stack to read from disk
-s, --show BOOLEAN Show interactively?
-o, --outfile TEXT Output filename (?=auto)
-r, --refilter TEXT Refilter CCFs before plotting (e.g. 4:8 for
filtering CCFs between 4.0 and 8.0 Hz. This will
update the plot title.
--help Show this message and exit.
New functionality: Dynamic time lags¶
As before, the dt/t is determined as the slope of the delays vs time lags.
the slope is calculated a weighted linear regression (WLS) through selected
points.
The selection of points is first based on the time lag criteria.
The minimum time lag can either be defined absolutely or dynamically.
When dtt_lag
is set to “dynamic” in the database, the inter-station
distance is used to determine the minimum time lag. This lag is calculated from
the distance and a velocity configured (dtt_v
). The velocity is determined
by the user so that the minlag doesn’t include the ballistic waves. For example
if ballistic waves are visible with a velocity of 2 km/s, one could configure
dtt_v=1.0.
This way, if stations are located 15 km apart, the minimum lag time will be
set to 15 s. The dtt_width
determines the width of the lag window used. A
value of 30.0 means the process will use time lags between 15 and 45 s in the
example above, on both sides if configured (dtt_sides
), or only causal or
acausal parts of the CCF.
Note
It seems obvious that these parameters are frequency-dependent, but they are currently common for all filters !
New parameters have been added to the configuration:
dtt_lag
: How is the lag window defined [dynamic]/static (default=static)dtt_v
: If dtt_lag=dynamic: what velocity to use to avoid ballistic waves [1.0]km/s (default=1.0)dtt_minlag
: If dtt_lag=static: min lag time (default=5.0)dtt_width
: Width of the time lag window [30]s (default=30.0)dtt_sides
: Which sides to use [both]/left/right (default=both)dtt_mincoh
: Minimum coherence on dt measurement, MWCS points with values lower than that will not be used in the WLS (default=0.65)dtt_maxerr
: Maximum error on dt measurement, MWCS points with values larger than that will not be used in the WLS (default=0.1)dtt_maxdt
: Maximum dt values, MWCS points with values larger than that will not be used in the WLS (default=0.1)
See also
The description of the Compute dt/t step in the workflow.
Math updates & bugfixes¶
Some improvements to the maths have been done for MSNoise 1.3:
whiten
: the symmetric hermitian was not properly defined and could lead to a 1 sample shift in the negative frequencies.compute_cc
: it is now possible to define an overlap of the windowscompute_cc
: settingwindsorizing
to-1
now computes the 1-bit normalization of the trace. Reminder:0
: no normalization,N
: N*rms clipping.mwcs
: the tapering of the windowed CCF has been improved in order to optimize the calculation for the center of the window.
Performance improvements¶
Improvements in terms of performances have also been done for MSNoise 1.3:
new_jobs
: the procedure has been completely rewritten and should be a lot faster, certainly for large (to very-large) archives and/or number of days.keep_all
: if set toY
(=True) in the config, all CCF are now stored in a single HDF5 file, which makes it much nicer to backup/transfer/delete.compute_cc
: if only ZZ components are to be computed, the whitened windows are pre-computed, which makes the process faster. This could lead to memory issues if the job contains a lot of stations, a lot of filters are configured and a large number of windows.compute_mwcs
: The procedure updates the jobs all at once, which brings a big gain in transaction time.
MSNoise has a proper API: Hacking MSNoise¶
The former database_tools.py
has been renamed to api.py
and all the
functions are now documented (in MSNoise API) so they can be used from the
console or from custom scripts.
Using the msnoise ipython
command, one triggers the start of an IPython
notebook in the current project folder. Once in a new notebook, one could
from msnoise.api import connect, get_config
session = connect()
print get_config(session, "mov_stack")
to get the current configuration of the mov_stack
parameter ! Enjoy Hacking!
MSNoise is tested¶
UnitTests are now defined for some (not all, yet) MSNoise functions, and most of
the workflow is tested automatically by launching msnoise test
in a new
folder.
This will allow contributors to easily know the code they want to be merged in the next versions of MSNoise doesn’t break anything. Travis-CI runs automatically on every push or pull request made on GitHub.
Upgrading an existing project to MSNoise 1.3¶
Some users will want to keep their current project without recomputing everything. This requires:
adding a few configuration parameters to the database
modifying the structure of the
jobs
table.
Running the following command will do both parts for MySQL and only the first part for SQLite:
msnoise upgrade_db
The second part is a little different if you are using SQLite as it
can’t be done automatically. This is because SQLite doesn’t support “ALTER”
commands. Ultimately we want the jobs.type
to be renamed to
jobs.jobtype
. You will have to do this operation manually:
Open SQLite database browser (SQLiteManager extension for Firefox, for example)
Open the msnoise.sqlite file
Select the jobs table
Edit the
type
field and rename it tojobtype
Ignore the warnings (it should work, although it could fail!)
Close the database
A note on parallel processing¶
Although the msnoise
command accepts the
-t INTEGER
argument to launch a number of threads in parallel, it currently
only works with scan_archive
: msnoise -t 4 scan_archive
will run the
scan on four folders in parallel. For the other steps, one has still to run
multiple commands in a console. This should change in the future.