These highlights cover the final 3 days of the LSST 2016 Project and Community Workshop.
Senior management were involved in the Joint Status Review for some of that time.
Accomplishments
- A hack session at LSST 2016 focused on migrating our tests to a form that would make them runnable by
py.test
(following the developer guidelines and the instructions in SQR-012). We also took the opportunity to clean up asserts in the test code to use modern idioms. Progress can be tracked on the Confluence page. Test suites modernized this week:pipe_base
(DM-7232),meas_astrom
(DM-3904),daf_butlerUtils
(DM-7230),obs_test
(DM-7244),coadd_utils
(DM-7258),coadd_chisquared
(DM-7261),meas_algorithms
(DM-7248),ctrl_provenance
(DM-7269),ctrl_events
(DM-7252),sphgeom
(DM-7315),ip_diffim
(DM-7320),meas_extensions_photometryKron
(DM-7329),meas_extensions_simpleShape
(DM-7332),meas_deblender
(DM-7347),pex_policy
(DM-7312),meas_extensions_psfex
(DM-7343),meas_extensions_shapeHSM
(DM-7344). - Significant progress has been made on Python 3 support. Details on current progress can be found on Confluence. Ported to Python 3 this week:
skypix
(DM-7249),geom
(DM-7243),daf_butlerUtils
(DM-7247),shapelet
(DM-7256),obs_test
(DM-7244),pipe_base
(DM-7245),coadd_utils
(DM-7258),coadd_chisquared
(DM-7261),ctrl_provenance
(DM-7269),meas_base
(DM-7262),db
(DM-7253),cat
(DM-7260),display_ds9
(DM-7250) - New testing asserts were added to the
utils
package. (DM-7267)
Documentation
- Draft Report: Data Backbone Scenario: Ceph (DM-7322)
Presentations
- DM Plans for Blended Objects by @jbosch.
- DM Documentation by @jsick.
- Real-World Testing of LSST-DM with Hyper Suprime-Cam by @price.
- DM In-Depth: Level 1 by @ctslater.
- State of the Level 2 Pipelines by @jbosch.
- Science User Interface and Tools: Status by @davidciardi and @xiuqin.
- Alert streams and the LSST filtering service by @connolly.
- DM Considerations for Deep Drilling by @gpdf.
RFC Activity
-
RFC-215: PROPOSED Disallow executable tests due to
#!/usr/bin/env python
problems on OS X - RFC-214: ADOPTED Use numpydoc and reStructuredText for Python docstrings.