QuickFrameMeasurementTask

class lsst.pipe.tasks.quickFrameMeasurement.QuickFrameMeasurementTask(config, *, display=None, **kwargs)

Bases: lsst.pipe.base.Task

WARNING: An experimental new task with changable API! Do not rely on yet!

This task finds the centroid of the brightest source in a given CCD-image and returns its centroid and a rough estimate of the seeing/PSF.

It is designed for speed, such that it can be used in observing scripts to provide pointing offsets, allowing subsequent pointings to place a source at an exact pixel position.

The approach taken here is deliberately sub-optimal in the detection and measurement sense, with all optimisation being done for speed and robustness of the result.

A small set of unit tests exist for this task, which run automatically if afwdata is setup. These, however, are stricky unit tests, and will not catch algorithmic regressions. TODO: DM-29038 exists to merge a regression real test which runs against 1,000 LATISS images, but is therefore slow and requires access to the data.

Parameters:
config : lsst.pipe.tasks.quickFrameMeasurement.QuickFrameMeasurementTaskConfig

Configuration class for the QuickFrameMeasurementTask.

display : lsst.afw.display.Display, optional

The display to use for showing the images, detections and centroids.

Returns:
result : lsst.pipe.base.Struct

Return strucure containing whether the task was successful, the main source’s centroid, its the aperture fluxes, the ixx and iyy of the source, and the median ixx, iyy of the detections in the exposure. See run() method for further details.

Raises:
This task should never raise, as the run() method is enclosed in an
except Exception block, so that it will never fail during observing.
Failure modes should be limited to returning a return Struct() with the same
structure as the success case, with all value set to np.nan but with
result.success=False.

Methods Summary

checkResult(exp, centroid, srcNum, percentile) Perform a final check that centroid location is actually bright.
detectObjectsInExp(exp, nSigma, nPixMin[, grow]) Run a very basic but fast threshold-based object detection on an exposure Return the footPrintSet for the objects in a postISR exposure.
emptyMetadata() Empty (clear) the metadata for this Task and all sub-Tasks.
getAllSchemaCatalogs() Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
getFullMetadata() Get metadata for all tasks.
getFullName() Get the task name as a hierarchical name including parent task names.
getName() Get the name of the task.
getSchemaCatalogs() Get the schemas generated by this task.
getTaskDict() Get a dictionary of all tasks as a shallow copy.
makeField(doc) Make a lsst.pex.config.ConfigurableField for this task.
makeSubtask(name, **keyArgs) Create a subtask as a new instance as the name attribute of this task.
run(exp, *[, donutDiameter, doDisplay]) Calculate position, flux and shape of the brightest star in an image.
timer(name, logLevel) Context manager to log performance data for an arbitrary block of code.

Methods Documentation

static checkResult(exp, centroid, srcNum, percentile)

Perform a final check that centroid location is actually bright.

Parameters:
exp : lsst.afw.image.Exposure

The exposure on which to operate

centroid : tuple of float

Location of the centroid in pixel coordinates

scrNum : int

Number of the source in the source catalog. Only used if the check is failed, for debug purposes.

percentile : float

Image’s percentile above which the pixel containing the centroid must be in order to pass the check.

Raises:
ValueError

Raised if the centroid’s pixel is not above the percentile threshold

static detectObjectsInExp(exp, nSigma, nPixMin, grow=0)

Run a very basic but fast threshold-based object detection on an exposure Return the footPrintSet for the objects in a postISR exposure.

Parameters:
exp : lsst.afw.image.Exposure

Image in which to detect objects.

nSigma : float

nSigma above image’s stddev at which to set the detection threshold.

nPixMin : int

Minimum number of pixels for detection.

grow : int

Grow the detected footprint by this many pixels.

Returns:
footPrintSet : lsst.afw.detection.FootprintSet

FootprintSet containing the detections.

emptyMetadata() → None

Empty (clear) the metadata for this Task and all sub-Tasks.

getAllSchemaCatalogs() → Dict[str, Any]

Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.

Returns:
schemacatalogs : dict

Keys are butler dataset type, values are a empty catalog (an instance of the appropriate lsst.afw.table Catalog type) for all tasks in the hierarchy, from the top-level task down through all subtasks.

Notes

This method may be called on any task in the hierarchy; it will return the same answer, regardless.

The default implementation should always suffice. If your subtask uses schemas the override Task.getSchemaCatalogs, not this method.

getFullMetadata() → lsst.pipe.base._task_metadata.TaskMetadata

Get metadata for all tasks.

Returns:
metadata : TaskMetadata

The keys are the full task name. Values are metadata for the top-level task and all subtasks, sub-subtasks, etc.

Notes

The returned metadata includes timing information (if @timer.timeMethod is used) and any metadata set by the task. The name of each item consists of the full task name with . replaced by :, followed by . and the name of the item, e.g.:

topLevelTaskName:subtaskName:subsubtaskName.itemName

using : in the full task name disambiguates the rare situation that a task has a subtask and a metadata item with the same name.

getFullName() → str

Get the task name as a hierarchical name including parent task names.

Returns:
fullName : str

The full name consists of the name of the parent task and each subtask separated by periods. For example:

  • The full name of top-level task “top” is simply “top”.
  • The full name of subtask “sub” of top-level task “top” is “top.sub”.
  • The full name of subtask “sub2” of subtask “sub” of top-level task “top” is “top.sub.sub2”.
getName() → str

Get the name of the task.

Returns:
taskName : str

Name of the task.

See also

getFullName
getSchemaCatalogs() → Dict[str, Any]

Get the schemas generated by this task.

Returns:
schemaCatalogs : dict

Keys are butler dataset type, values are an empty catalog (an instance of the appropriate lsst.afw.table Catalog type) for this task.

See also

Task.getAllSchemaCatalogs

Notes

Warning

Subclasses that use schemas must override this method. The default implementation returns an empty dict.

This method may be called at any time after the Task is constructed, which means that all task schemas should be computed at construction time, not when data is actually processed. This reflects the philosophy that the schema should not depend on the data.

Returning catalogs rather than just schemas allows us to save e.g. slots for SourceCatalog as well.

getTaskDict() → Dict[str, weakref]

Get a dictionary of all tasks as a shallow copy.

Returns:
taskDict : dict

Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc.

classmethod makeField(doc: str) → lsst.pex.config.configurableField.ConfigurableField

Make a lsst.pex.config.ConfigurableField for this task.

Parameters:
doc : str

Help text for the field.

Returns:
configurableField : lsst.pex.config.ConfigurableField

A ConfigurableField for this task.

Examples

Provides a convenient way to specify this task is a subtask of another task.

Here is an example of use:

class OtherTaskConfig(lsst.pex.config.Config):
    aSubtask = ATaskClass.makeField("brief description of task")
makeSubtask(name: str, **keyArgs) → None

Create a subtask as a new instance as the name attribute of this task.

Parameters:
name : str

Brief name of the subtask.

keyArgs

Extra keyword arguments used to construct the task. The following arguments are automatically provided and cannot be overridden:

  • “config”.
  • “parentTask”.

Notes

The subtask must be defined by Task.config.name, an instance of ConfigurableField or RegistryField.

run(exp, *, donutDiameter=None, doDisplay=False)

Calculate position, flux and shape of the brightest star in an image.

Given an an assembled (and at least minimally ISRed exposure), quickly and robustly calculate the centroid of the brightest star in the image.

Parameters:
exp : lsst.afw.image.Exposure

The exposure in which to find and measure the brightest star.

donutDiameter : int or float, optional

The expected diameter of donuts in pixels for use in the centre of mass centroid measurement. If None is provided, the config option is used.

doDisplay : bool

Display the image and found sources. A diplay object must have been passed to the task constructor.

Returns:
result : lsst.pipe.base.Struct
Struct containing:

Whether the task ran successfully and found the object (bool) The object’s centroid (float, float) The object’s ixx, iyy (float, float) The object’s 70 pixel aperture flux (float) The object’s 25 pixel aperture flux (float) The images’s median ixx, iyy (float, float)

If unsuccessful, the success field is False and all other results are np.nan of the expected shape.

Notes

Because of this task’s involvement in observing scripts, the run method should never raise. Failure modes are noted by returning a Struct with the same structure as the success case, with all value set to np.nan and result.success=False.

timer(name: str, logLevel: int = 10) → Iterator[None]

Context manager to log performance data for an arbitrary block of code.

Parameters:
name : str

Name of code being timed; data will be logged using item name: Start and End.

logLevel

A logging level constant.

See also

timer.logInfo

Examples

Creating a timer context:

with self.timer("someCodeToTime"):
    pass  # code to time