Difference between revisions of "Staff Priorities - Masha"

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=== Yesterday ===
 
=== Yesterday ===
* Tagged official CSEP V15.10.0 release, built RPMs
+
* CSEP V15.10.0 release: could not install on csep-op due to the nightly processing still running
* 'pandas' data analysis Python package for optimized file IO functionality: problems reading forecast from gzip archive, but 10x faster to read forecast from ASCII format file.
+
** Tested NZ image successfully
 +
* Updated/checked David Jackson's email on CSEP lists
 +
* Read papers for the CSEP status meeting on Wednesday
 +
* 'pandas' data analysis Python package for optimized file IO functionality: problems reading forecast from gzip archive because of storing original filename as part of the archive
 
* Re-run test case using best available catalog for Canterbury experiment with zero days of delay for providing slip models to the forecasts:
 
* Re-run test case using best available catalog for Canterbury experiment with zero days of delay for providing slip models to the forecasts:
 
** Generating one-month and one-day forecasts
 
** Generating one-month and one-day forecasts
Line 10: Line 13:
 
* Install and test CSEP V15.10.0 on csep-op
 
* Install and test CSEP V15.10.0 on csep-op
 
* Read papers for the CSEP status meeting on Wednesday
 
* Read papers for the CSEP status meeting on Wednesday
* Re-run test case using best available catalog for Canterbury experiment using zero days delay for providing slip models to the forecasts:
+
* 'pandas' data analysis Python package for reading forecast from gzip archive file:
 +
** tested with iPython that adding data extraction from archive adds only 100ms to 500ms to read data with Pandas vs. 3.5s to load data with numpy.loadtxt
 +
** post question to user group if can load data directly with Pandas when filename is stored within archive
 +
* Re-run test case using best available catalog for Canterbury experiment with zero days of delay for providing slip models to the forecasts:
 
** Generating one-month and one-day forecasts
 
** Generating one-month and one-day forecasts
* 'pandas' data analysis Python package for reading forecast from gzip archive file without extracting data first
 
  
 
'''Blocked''': No
 
'''Blocked''': No

Revision as of 21:08, 13 October 2015

Current Activities

Yesterday

  • CSEP V15.10.0 release: could not install on csep-op due to the nightly processing still running
    • Tested NZ image successfully
  • Updated/checked David Jackson's email on CSEP lists
  • Read papers for the CSEP status meeting on Wednesday
  • 'pandas' data analysis Python package for optimized file IO functionality: problems reading forecast from gzip archive because of storing original filename as part of the archive
  • Re-run test case using best available catalog for Canterbury experiment with zero days of delay for providing slip models to the forecasts:
    • Generating one-month and one-day forecasts

Today

  • Install and test CSEP V15.10.0 on csep-op
  • Read papers for the CSEP status meeting on Wednesday
  • 'pandas' data analysis Python package for reading forecast from gzip archive file:
    • tested with iPython that adding data extraction from archive adds only 100ms to 500ms to read data with Pandas vs. 3.5s to load data with numpy.loadtxt
    • post question to user group if can load data directly with Pandas when filename is stored within archive
  • Re-run test case using best available catalog for Canterbury experiment with zero days of delay for providing slip models to the forecasts:
    • Generating one-month and one-day forecasts

Blocked: No

Followups:

  • With John Y.:
    • csep-op: Added my email to recipients list for Oceanic Transform Faults status email, got email sent to my account, but not to the mailing list.

TODO

  • Trac ticket #353: Optimize RELM N-test by avoiding event to bin look up when masking bit is set for the whole forecast

CSEP

EEW

Responsiblities