How To’s

Reprocess data

When starting to use MSNoise, one will most probably need to re-run different parts of the Workflow more than one time. By default, MSNoise is designed to only process “what’s new”, which is antagonistic to what is wanted. Hereafter, we present cases that will cover most of the re-run techniques:

When adding a new filter

If new filter are added to the filters list in the Configurator, one has to reprocess all CC jobs, but not for filters already existing. The recipe is:

  • Add a new filter, be sure to mark ‘used’=1
  • Set all other filters ‘used’ value to 0
  • Redefine the flag of the CC jobs, from ‘D’one to ‘T’odo with the following:
  • Run msnoise reset CC --all
  • Run msnoise compute_cc
  • Run next commands if needed (stack, mwcs, dtt)
  • Set back the other filters ‘used’ value to 1

The compute_cc will only compute the CC’s for the new filter(s) and output the results in the STACKS/ folder, in a subfolder named by a formatted integer from the filter ID. For example: STACKS/01 for ‘filter id’=1, STACKS/02 for ‘filter id’=2, etc.

When changing the REF

When changing the REF, the REF stack has to be re-computed:

msnoise stack -r -i 999 will ensure all jobs marked done in the last 999 days are checked for modification. The REF will then be re-output.

When changing the MWCS parameters

If the MWCS parameters are changed in the database, all MWCS jobs need to be reprocessed.

msnoise reset DTT --all

msnoise compute_mwcs

shoud do the trick.

When changing the dt/t parameters

msnoise compute_dtt -i 999 will ensure all MWCS jobs marked done in the last 999 days are checked for modification.

Define one’s own data structure of the waveform archive

The file contains the known data archive formats. If another data format needs to be defined, it will be done in the file in the current project folder:

See also

Check the “Populate Station Table” step in the <no title>.

How to have MSNoise work with 2+ data structures at the same time

Not yet implemented.

How to duplicate/dump the MSNoise configuration

Not yet implemented.

Testing the Dependencies

Once installed, you should be able to import the python packages in a python console. MSNoise comes with a little script called that can be useful to check if you have all the required packages (+ some extras).

The usage is such:

$ msnoise bugreport -h

usage: msnoise bugreport [-h] [-s] [-m] [-e] [-a]

Helps determining what didn't work

optional arguments:
  -h, --help     show this help message and exit
  -s, --sys      Outputs System info
  -m, --modules  Outputs Python Modules Presence/Version
  -e, --env      Outputs System Environment Variables
  -a, --all      Outputs all of the above

On my Windows machine, the execution of

$ msnoise bugreport -s -m

results in:

************* Computer Report *************

Intel64 Family 6 Model 42 Stepping 7, GenuineIntel

Python: 2.7.5 |Anaconda 1.7.0 (64-bit)| (default, Jul  1 2013, 12:37:52) [MSC v.1500 64 bit (AMD64)]


[X] numpy: 1.7.1
[X] scipy: 0.12.0
[X] pandas: 0.12.0
[X] matplotlib: 1.3.0
[X] statsmodels: 0.5.0
[X] sqlalchemy: 0.8.2
[X] traitsui: 4.3.0
[X] traits: 4.3.0
[X] enable: 4.3.0
[X] scikits.samplerate: present (no version)
[X] obspy: present (no version)
[X] sphinx: 1.1.3
[X] jinja2: 2.7.1

Backends: (at least one is required)
[X] wx:
[ ] PyQt4: not found
[X] PySide: 1.2.1

Not required, just checking:
[X] setuptools: 0.6
[X] reportlab:  $Id$
[X] configobj: 4.7.2
[X] pkg_resources: present (no version)
[ ] paramiko: not found
[X] ctypes: 1.1.0
[X] pyparsing: 1.5.6
[X] distutils: 2.7.5
[X] IPython: 1.0.0
[X] vtk: present (no version)

The [X] marks the presence of the module. In the case above, PyQt4 is missing, but that’s not a problem because wx or PySide are present, so traitsui has a backend to render the GUI for the Configurator. The “not-required” packages are checked for information, those packages can be useful for reporting / hacking / rendering the data.

To install a missing package, for example obspy, use the pip command:

$ pip install obspy