In the next major release of the LSST stack, the system for measuring the properties of sources will be replaced by a new one, housed mostly in the new meas_base package.  In addition to providing new Task classes and a new plugin interface for measurement algorithms, this overhaul also includes changes to the schemas of the catalogs produced by the measurement framework.  The new framework will not be entirely complete as of the next release, but it will have sufficient functionality to replace the old framework as the default.  The old system will remain available via config on the S14 final release, but will be removed entirely before the W15 release.

New Tasks

The main entry point for the new measurement framework is the new SingleFrameMeasurementTask class (in meas_base), which is intended as an almost drop-in replacement for the current SourceMeasurementTask (in meas_algorithms).  It's not drop-in replacement, because it has different plugins, a slightly different slot system, and an entirely different output schema - so we will use it everywhere SourceMeasurementTask was used before, but when changing other configuration settings from their defaults - particularly those that deal with the measurement algorithms or their outputs, you'll need to be careful to use configuration values that are consistent with the measurement tasks you're useing.  We've provided configuration instructions to make that easy, as described in the next section.

SingleFrameMeasurementTask combines the work previously done by two classes, the old SourceMeasurementTask and the C++ MeasureSources class.  It initializes the plugins (which determines the schema) in its constructor, then invokes the plugins on each source in the image, replacing neighbors with noise as it does so (this is delegated to the NoiseReplacer class, which replaces the ReplaceWithNoiseTask subtask).  Unlike SourceMeasurementTask, SingleFrameMeasurementTask does not do forced photometry (see below).  Sources are also processed in a slightly different order (see Simultaneous Multi-Object Measurement).

Reverting to the Old Framework

For the present, you will continue to support the measurement.py task in meas_algorithms.  The measurement task used by processCcd and processCoadd is controlled by configurations items in CalibrateConfig and ProcessImageConfig, and can be retargeted back to the original meas_algorithms framework using the following python code:

from lsst.meas.algorithms.measurement import SourceMeasurementTask

root.calibrate.initialMeasurement.retarget(SourceMeasurementTask)

root.calibrate.measurement.retarget(SourceMeasurementTask)

root.measurement.retarget(SourceMeasurementTask)

Please note that the old measurement task writes tables with version=0 schemas, and expects the plugins and fieldnames to use the old naming conventions.  For example, you must refer to the SdssCentroid plugin as 'centroid.sdss' and the value it stores in the output table will be afw.geom.PointD type with the name 'centroid.sdss'.  See the section Schema Changes and Versioning below.

Some care has been taken to make all of the tasks called by processImage sensitive to which measurement framework and schema version are in use, so that the pipeline will work with either measurement task.  However, the developer should be careful when accessing or adding fields to the schemas to know which measurement task and which naming conventions are in effect.  For new code, we encourage the use of the meas_base measurement framework and schema version=1 tables.

Here are some examples where you must use schema=0 names if you revert to the old framework:

NOTE:  If you are reading this document prior to the changeover to the end of Summer 14, just the opposite instructions will hold for using the New Framework.  That is, you must retarget the above 3 tasks using the SingleFrameMeasurementTask, which resides in lsst.meas.base.

Schema Changes and Versioning

The changes to afw::table's Schema objects to support the new measurement framework are handled by a new versioning mechanism, which allows the old behavior (necessary for the old framework) to coexist with the new behavior in the stack.  A Schema with version=0 corresponds to one appropriate for use with the old SourceMeasurementTask, while version>0 corresponds to SingleFrameMeasurementTask and the new forced photometry tasks.  Here are the differences between versions:

In version>0, we have stronger naming convention for fields generating by plugin algorithms, which tie the plugin name and location to its outputs.  These conventions are as follows:

Aliases and Slots

We have added an alias feature to the Schema class, via an AliasMap object it holds.  Aliases are handled simply as an extra stage in Key lookup - when a Key is requested via a string, its beginning is compared against all aliases to see if it should be replaced.  Partial replacements are allowed, but only at the beginning, and multiple replacements are not.  For example, if the AliasMap includes the mapping "slot_PsfFlux"->"base_PsfFlux", then a Key lookup on "slot_PsfFlux_flux" will resolve to "base_PsfFlux_flux", but a lookup on "r_slot_PsfFlux_flux" will not be affected.  Because Key lookup happens implicitly when getting a value from a record via string, this makes it even more important to do Key lookup once in advance rather than use a string to access the same value repeatedly.

The alias system is available for both version 0 and version > 0 tables, and is now used to define the slot mechanism in SourceTable/SourceRecord/SourceCatalog in both cases; each slot corresponds to a predefined field name prefix that is mapped to an actual measurement via an alias.  These predefined names are the name of the slot, starting with a capital letter (e.g. "PsfFlux", "Centroid"), prefixed with "slot_" (or "slot." for version 0).  For instance, a typical AliasMap containing slot definitions would have the following mappings for version 1:

Slot definitions are now persisted simply as aliases, with slots saved via older versions of the stack translated into aliases when read from disk.  Changing one of these aliases in an AliasMap attached to a SourceTable will notify the table that slots have changed and the cached Keys that correspond to them must be updated (in fact, the old slot definers, such as SourceTable::definePsfFlux() are now implemented by simply changing the alias and letting the notification callback do its work).

Note that this means that slot values can now be accessed via string, just like any normal measurement.

Forced Photometry

The new measurement framework adds several new Task classes for forced photometry, including the capability to perform forced photometry on coadds (long present on the HSC fork of the codebase but absent on the LSST side).  The new Tasks are:

More information on forced photometry can be found in the Doxygen documentation for the meas_base package.

Simultaneous Multi-Object Measurement

While the old SourceMeasurementTask processed sources in the order set by the catalog it was given, SingleFrameMeasurementTask and ForcedMeasurementTask instead iterate over deblend families; within each family, the children are processed individually first, followed by the parent.  After the individual source measurements, plugins are then given an opportunity to measure all the children at once at once, using an interface that was not present in the old framework, using the same pixel values used in the parent measurement but writing outputs to per-child records.  This allows us to support plugins that fit multiple objects simultaneously (possibly using the earlier non-simultaneous measurements as input).

This will likely provide the easiest route to properly-deblended forced photometry; rather than attempt to transform deblender outputs from frame to frame, or rely on a full, multi-epoch deblender, we can simply fit families simultaneously in forced mode.  This does not, of course, address the problem of consistent multi-band detection or deblending.

Currently we have no plugins that use this API.  Of our current algorithms, only the PSF flux and the galaxy model flux are likely to ever be usable in this mode.

Python and C++ Measurement Plugins

While the new framework allows plugins to be written in Python, we expect that essentially all production plugins will be implemented in C++.  As a result, we've put much more effort into reducing the amount of boilerplate necessary to implement a C++ plugin (see the meas_base Doxygen documentation) than we have into reducing boilerplate for pure-Python plugins.  Even so, we're not entirely happy with this C++ interface, and plan to investigate some alternate designs in W15.  We also plan (in W15) to give the pure-Python plugin-writing experience much more attention - while the Python plugin interface itself will not change, we plan to add helper classes that will make it easier to implement new plugins.

Error-Handling and Diagnostics

One of the main areas we hope to improve on in the new framework is in the handling of errors in measurement algorithms.  Our first goal in this area is to ensure that no errors go unreported in detail: known failure modes should be reported as problem-specific flags, and any unexpected exception should result in a warning-level log message that would enable the problem to be tracked down as a bug.  These known failures are indicated by throwing an instance of lsst.meas.base.MeasurementError, which stores information about a problem-specific flag that should be set.  All other exceptions that propagate up to the measurement task will be logged as warnings.  For configuration errors that affect all sources to be measured on an exposure (i.e. running an algorithm that requires a Psf on an Exposure with no Psf), we will also provide custom exceptions that will be treated as fatal by the measurement framework (see ).

For measurements accessed via slots, however, problem-specific flags are not available, and the user is forced to rely only on the "general failure" flag that is common to all algorithms.  This flag is often ambiguous, however, as it is used both when an algorithm has completely failed and has no valid output, and when a more minor error occurred that yields a valid but slightly less trustworthy result (for example, the SdssShape algorithm typically uses Gaussian-weighted moments, but can fall back to unweighted moments).  To address this, we plan to add a "general suspect" flag to all algorithms and the slot system, in addition to the "general failure" flag.  The failure flag (likely renamed to "*_flag_failed" from simply "*_flag") will be used to indicate a complete failure, and the new "suspect" flag ("*_flag_suspect").  This is slated for .

Missing Features and Known Problems

For issues that we expect to complete in S15, please consult  and .  These include reimplementing aperture corrections, removing now-deprecated afw::table features, and reimplemented database ingest.