Coverage for python/lsst/meas/base/pluginsBase.py : 64%

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# This file is part of meas_base. # # Developed for the LSST Data Management System. # This product includes software developed by the LSST Project # (https://www.lsst.org). # See the COPYRIGHT file at the top-level directory of this distribution # for details of code ownership. # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see <https://www.gnu.org/licenses/>.
""" Base class measurement plugin config classes.
Notes ----- Most derived classes will want to set defaults that make sense for the plugin type. """
""" Base class for measurement plugins.
This is the base class for `SingleFramePlugin` and `ForcedPlugin`; derived classes should inherit from one of those.
Parameters ---------- config : `BasePluginConfig` Plugin configuration. name : `str` Plugin name. logName : `str` Logger name.
Notes ----- Relative execution orders are defined by a series of named constants defined in this class: plugins with a lower execution number are run first.
This approach was chosen instead of a full graph-based analysis of dependencies because algorithm dependencies are usually both quite simple and entirely substitutable: an algorithm that requires a centroid can typically make use of any centroid algorithms outputs. That makes it relatively easy to figure out the correct value to use for any particular algorithm. """
"""Order for algorithms which require only Footprint and Peaks (`float`).
Notes ----- Algorithms with this execution order include centroids. """
"""Order for algorithms which require a centroid (`float`).
Notes ----- These algorithms may refer assume that `getCentroid` will return a good centroid, and that a Footprint and its Peaks are available. """
"""Order for algorithms which require a shape and a centroid (`float`).
Notes ----- These algorithms may assume that both `getCentroid` and `getShape` will return good values, and that a Footprint and its Peaks are available. """
"""Order for algorithms which require shape, centroid and flux (`float`).
Notes ----- These algorithms may assume that `getCentroid` and `getShape` will return good values, that flux has been measured, and that and that a Footprint and its Peaks are available. """
"""Order for catalog calculation plugins.
Notes ----- These plugins only operate on catalogs; they may not access pixel values. """
"""Plugin configuration information (`lsst.pex.config.Config`). """
def getExecutionOrder(cls): """Get the relative execution order of this plugin.
Must be reimplemented as a class method by concrete derived classes. """ raise NotImplementedError("All plugins must implement getExecutionOrder()")
object.__init__(self) self.config = config self.name = name self.logName = logName
return self.logName
"""Record a failure of the `measure` or `measureN` method.
Parameters ---------- measRecord : `lsst.afw.table.SourceRecord` Table record describing the source being measured. error : `MeasurementError`, optional Only provided if the measurement failed due to a `MeasurementError` being raised; otherwise, will be `None`.
Notes ----- When the plugin raises an exception, framework will call `BasePlugin.fail` to allow the plugin to set its failure flag field(s). When `BasePlugin.measureN` raises an exception, `BasePlugin.fail` will be called repeatedly with all the records that were being measured.
If the exception is an `MeasurementError`, it will be passed as the error argument; in all other cases the error argument will be `None`, and the failure will be logged by the measurement framework as a warning.
""" traceback.print_exc() message = ("The algorithm '%s' thinks it cannot fail, but it did; " "please report this as a bug (the full traceback is above)." % (self.__class__.__name__,)) raise NotImplementedError(message)
def getTransformClass(): """Get the measurement transformation appropriate to this plugin.
This returns a subclass of `transforms.MeasurementTransform`, which may be instantiated with details of the algorithm configuration and then called with information about calibration and WCS to convert from raw measurement quantities to calibrated units. Calibrated data is then provided in a separate output table.
Notes ----- By default, we copy everything from the input to the output without transformation. """ return PassThroughTransform |