MSNoise 1.6.3

bugfix the hanning - hann scipy change

MSNoise 1.6.2

Bugfix the changes in pandas indexing

MSNoise 1.6.1

Bugfix and compatibility with latest SciPy (fftpack/fft renaming).

MSNoise 1.6

More than 2 years after the last major release (MSNoise 1.5) I’m proud to announce the new MSNoise 1.6. It is a major release, with a massive amount of work since the last one: in GitHub numbers , it’s over 190 commits and over 4000 lines of code and documentation changed or added!

End of summer is also a very special period for MSNoise, as it has been 9 years since Corentin contacted Florent and that I immediately started working on this package. 2010-2019. Nine years. Wow. MSNoise has now a few thousand lines of code and more than 100 pages of documentation, it is widely used and scientists around the globe use it and even make super cool publications out of their results! So proud!

MSNoise 1.6 introduces a series of new features :

• The workflow has been rewritten to create “job types” per step, making it easier for users to reset a jobs before a specific step.
• This and other smaller adaptations to the code allows to run MSNoise more efficiently, e.g. on a HPC.
• The components to compute can be defined for “single-station” and “cross-station” independently.
• The compute_cc step has been completely rewritten to be much, much faster.
• A new db top level command, which among others include dump and import commands for handling the tables from the database.
• A new Interaction Examples & Gallery section of the documentation in order to demonstrate how users can interact with the MSNoise API, e.g. for creating custom plots.

As always, this version has benefited from outputs/ideas/pull requests/questions from several users/friends.

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 70 publications using MSNoise! That’s the best validation of our project ever and it has doubled since last release!!

Thomas

Full release notes for 1.6: http://msnoise.org/doc/releasenotes/msnoise-1.6.html

MSNoise 1.5.1

This is a bugfix release.

• MAJOR: revert scipy's next_fast_len in MWCS for nextpow2 (needs more work, but this restores the expected original behaviour of the spectral smoother)
• MAJOR: When used with different filters, the AC whitening occured on the same trace, not its copy, leading to wrong spectra. (see #105)
• allow 'intervals" to be float, not only ints

MSNoise 1.5

About 1 year after the last major release (MSNoise 1.4) we are proud to announce the new MSNoise 1.5. It is a major release, with a massive amount of work since the last one: in GitHub numbers , it’s over 140 commits and about 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 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.

Thomas, Corentin and others

Bugfix release

• Typos
• Hardcode version to prevent pypi errors
• dynamic loading of CDN or local jquery
• fixed raw_input vs input (Py2 vs Py3)

MSNoise 1.4

Just over a year after the last major release (MSNoise 1.3) we are proud to announce the new MSNoise 1.4. It is a major release, with a massive amount of work since the last one: in GitHub numbers , it’s over 110 commits and about 5500 new lines of code and documentation added!

MSNoise 1.4 introduces four major new features : a new ultra-intuitive web-based admin interface, the support for plugins and extensions, the phase weighted stack and the instrument response removal. It also brings the possibility to parallel/thread process the cross-correlation and the MWCS steps. MSNoise is now “tested” automatically on Linux (thanks to TravisCI) & Windows (thanks to Appveyor), for Python versions 2.7, 3.4 and 3.5. Yes, MSNoise is Python 3 compatible !!!

This version has benefited from outputs/ideas/pull requests/questions from several users/friends:

• Carmelo Sammarco
• Esteban Chaves
• Lion Krisher
• Tobias Megies
• Clare Donaldson
• Aurélien Mordret
• Raphaël De Plaen
• Lukas E. Preiswerk
• 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 12 publications using MSNoise ! That’s the best validation of our project ever ! See the full list on the MSNoise website.

Thomas

Bugfix in the new_jobs command

This is a bugfix release.

When running the new_jobs procedure, the jobs are "inserted" in the database, even if they already existed (they should be "updated"). This is because of the complete rewrite of the code to optimize the operation.

As this optimization is mostly useful upon first run, I've added a parameter --init to the command. If provided, the "massive insert" procedure is used, if not, then the classic "insert or update if existing" is used.

So, upon first run : msnoise new_jobs --init
And afterwards (in cron, e.g.): ``msnoise new_jobs`

Users who have already run MSNoise 1.3 on their archive need to clean the jobs table in the database. The buggy jobs are those "CC" jobs which are still marked "I"n progress after the compute_cc procedure, and with a "lastmod" = "NULL". They can be easily identified and removed.

a classic SQL command would be:

DELETE from jobs WHERE lastmod is NULL;

MSNoise 1.3

Release type: Major.
....................................................................
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!)!