- Add three new content types: SIM SEA, EPHIN housekeeping, and CPE.
- Numerous infrastructure improvements in ingest and update process.
- Use weighted mean and stddev for calculating stats.
- Use float64 to accumulate sum for computing stats mean.
- Rebuild stats files for the full mission.
- Fix bug that number of samples for daily stats was incorrect.
- Add notes and regression testing code for re-building stats files.
- This release fixes issues #38, #39, and #41.
- Add
MSID.interpolate()
method which is likeMSIDset.interpolate()
- Speed up
interpolate()
methods using the newSka.Numpy.interpolate
. - Add
MSIDset.filter_bad_times()
method that applies the bad times filter to all MSIDs in a set. - Speed up filter_bad_times() by using a single mask array over all bad time filters.
- Add some unit / regression tests.
- Fix MSID.raw_vals() so it handles state codes with different lengths
- Fix problem in iplot where units not tied to fetched MSID
- Add units to DEA housekeeping MSIDs
- Make it possible to reliably use the import mechanism to select different unit systems within the same script or Python process with no interactions.
- Improve tutorial documentation
- Modify PCAD derived parameters to use only predictive ephemeris
- Redefine DP_ROLL_FSS and DP_PITCH_FSS to improve accuracy
- Allow for filter_bad_times to function for data that have already been filtered.
A number of major new features are available in the release 0.16 of the Ska engineering archive:
- Built-in plotting capability and an interactive plot browser that allows arbitrary zooming and panning. See tutorial sections: Plotting time data (http://goo.gl/6tGNZ) and Interactive plotting (http://goo.gl/2dG4c)
- Support for plotting state-valued MSIDs and for accessing the raw count values. See: State valued MSIDs (http://goo.gl/9R0Tz)
- Support for accessing Telemetry Database attributes related to an MSID. See: Telemetry database (http://goo.gl/pPo0s)
- PCAD derived parameters (main code from A. Arvai). See: Derived PCAD parameters (http://goo.gl/iKDUK)
- MSIDset.interpolate() now behaves more intuitively. This was done
by making the
times
attribute of interpolated MSIDs correspond to the new (linearly-spaced) interpolated times. Previously times was set to the nearest-neighbor times, which is not generally useful. See #20 and Interpolation (http://goo.gl/5U5Kp)
- Fixed problem where Msidset fails for 5min and daily values.
Minor updates and bug fixes:
- Change max_gap for ACISDEAHK from 3600 to 10000 sec
- Add midvals attr for stat fetch
- Fix ss_vector() to use quaternion midvals and handle missing telemetry
- Fix typo in fetch.logical_intervals
- Explicitly set --data-root when calling update_archive.py in task_schedule.cfg
Version 0.13 of the Ska.engineering archive contains a number of new features:
Support for derived parameter pseudo-MSIDs. Currently there are number of thermal values and ACIS power values.
Two new fetch.MSID methods:
- logical_intervals() returns contiguous intervals during which a logical expression is true.
- state_intervals() determines contiguous intervals during which the MSID value is unchanged.
Two new classes fetch.Msid and fetch.Msidset. These are just like fetch.MSID or fetch.MSIDset except that filter_bad=True by default. You can use the new classes just like before but you'll always only get good data values.
Changed definition of the "vals" attribute for '5min' and 'daily' stat values so "vals" is now the sames as "means". Previously the "vals" attribute for a statistics fetch was the exact telemetry value at the interval midpoint. This quantity is not that useful and prone to errors since one frequently does things like:
dat = fetch.MSID('tephin', '2011:150', stat='5min') plot_cxctime(dat.times, dat.vals)
Caching of previously fetched data values. This is disabled by default but used for telemetry and derived parameter ingest. In certain circumstances caching can be useful.
New function for truncating the engineering archive at a certain date. This is useful for fixing the database in the event of a corruption.