IsrMock¶

class lsst.ip.isr.IsrMock(**kwargs)¶

Bases: lsst.pipe.base.Task

Class to generate consistent mock images for ISR testing.

ISR testing currently relies on one-off fake images that do not accurately mimic the full set of detector effects. This class uses the test camera/detector/amplifier structure defined in lsst.afw.cameraGeom.testUtils to avoid making the test data dependent on any of the actual obs package formats.

Methods Summary

`amplifierAddCT`(ampDataSource, ampDataTarget, …)	Add a scaled copy of an amplifier to another, simulating crosstalk.
`amplifierAddFringe`(amp, ampData, scale[, x0, y0])	Add a fringe-like ripple pattern to an amplifier’s image data.
`amplifierAddNoise`(ampData, mean, sigma)	Add Gaussian noise to an amplifier’s image data.
`amplifierAddSource`(ampData, scale, x0, y0)	Add a single Gaussian source to an amplifier.
`amplifierAddYGradient`(ampData, start, end)	Add a y-axis linear gradient to an amplifier’s image data.
`amplifierMultiplyFlat`(amp, ampData, fracDrop)	Multiply an amplifier’s image data by a flat-like pattern.
`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.
`getCamera`()	Construct a test camera object.
`getExposure`()	Construct a test exposure.
`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.
`getWcs`()	Construct a dummy WCS object.
`localCoordToExpCoord`(ampData, x, y)	Convert between a local amplifier coordinate and the full exposure coordinate.
`makeBfKernel`()	Generate a simple Gaussian brighter-fatter kernel.
`makeCrosstalkCoeff`()	Generate the simulated crosstalk coefficients.
`makeData`()	Generate simulated ISR data.
`makeDefectList`()	Generate a simple single-entry defect list.
`makeField`(doc)	Make a `lsst.pex.config.ConfigurableField` for this task.
`makeImage`()	Generate a simulated ISR image.
`makeSubtask`(name, **keyArgs)	Create a subtask as a new instance as the `name` attribute of this task.
`makeTransmissionCurve`()	Generate a simulated flat transmission curve.
`run`()	Generate a mock ISR product, and return it.
`timer`(name, logLevel)	Context manager to log performance data for an arbitrary block of code.

Methods Documentation

amplifierAddCT(ampDataSource, ampDataTarget, scale)¶

Add a scaled copy of an amplifier to another, simulating crosstalk.

This method operates in the amplifier coordinate frame.

Parameters:	ampDataSource : `lsst.afw.image.ImageF` Amplifier image to add scaled copy from. ampDataTarget : `lsst.afw.image.ImageF` Amplifier image to add scaled copy to. scale : `float` Flux scale of the copy to add to the target.

Notes

This simulates simple crosstalk between amplifiers.

amplifierAddFringe(amp, ampData, scale, x0=100, y0=0)¶

Add a fringe-like ripple pattern to an amplifier’s image data.

Parameters:	amp : `AmpInfoRecord` Amplifier to operate on. Needed for amp<->exp coordinate transforms. ampData : `lsst.afw.image.ImageF` Amplifier image to operate on. scale : `numpy.array` or `float` Peak intensity scaling for the ripple. x0 : `numpy.array` or `float`, optional Fringe center y0 : `numpy.array` or `float`, optional Fringe center

Notes

This uses an offset sinc function to generate a ripple pattern. True fringes have much finer structure, but this pattern should be visually identifiable. The (x, y) coordinates are in the frame of the amplifier, and (u, v) in the frame of the full trimmed image.

amplifierAddNoise(ampData, mean, sigma)¶

Add Gaussian noise to an amplifier’s image data.

This method operates in the amplifier coordinate frame.

Parameters:	ampData : `lsst.afw.image.ImageF` Amplifier image to operate on. mean : `float` Mean value of the Gaussian noise. sigma : `float` Sigma of the Gaussian noise.

amplifierAddSource(ampData, scale, x0, y0)¶

Add a single Gaussian source to an amplifier.

This method operates in the amplifier coordinate frame.

Parameters:	ampData : `lsst.afw.image.ImageF` Amplifier image to operate on. scale : `float` Peak flux of the source to add. x0 : `float` X-coordinate of the source peak. y0 : `float` Y-coordinate of the source peak.

amplifierAddYGradient(ampData, start, end)¶

Add a y-axis linear gradient to an amplifier’s image data.

This method operates in the amplifier coordinate frame.

Parameters:	ampData : `lsst.afw.image.ImageF` Amplifier image to operate on. start : `float` Start value of the gradient (at y=0). end : `float` End value of the gradient (at y=ymax).

amplifierMultiplyFlat(amp, ampData, fracDrop, u0=100.0, v0=100.0)¶

Multiply an amplifier’s image data by a flat-like pattern.

Parameters:	amp : `lsst.afw.ampInfo.AmpInfoRecord` Amplifier to operate on. Needed for amp<->exp coordinate transforms. ampData : `lsst.afw.image.ImageF` Amplifier image to operate on. fracDrop : `float` Fractional drop from center to edge of detector along x-axis. u0 : `float` Peak location in detector coordinates. v0 : `float` Peak location in detector coordinates.

Notes

This uses a 2-d Gaussian to simulate an illumination pattern that falls off towards the edge of the detector. The (x, y) coordinates are in the frame of the amplifier, and (u, v) in the frame of the full trimmed image.

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.

getCamera()¶

Construct a test camera object.

Returns:	camera : `lsst.afw.cameraGeom.camera` Test camera.

getExposure()¶

Construct a test exposure.

The test exposure has a simple WCS set, as well as a list of unlikely header keywords that can be removed during ISR processing to exercise that code.

Returns:	exposure : `lsst.afw.exposure.Exposure` Construct exposure containing masked image of the appropriate size.

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

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.

getWcs()¶

Construct a dummy WCS object.

Taken from the deprecated ip_isr/examples/exampleUtils.py.

This is not guaranteed, given the distortion and pixel scale listed in the afwTestUtils camera definition.

Returns:	wcs : `lsst.afw.geom.SkyWcs` Test WCS transform.

localCoordToExpCoord(ampData, x, y)¶

Convert between a local amplifier coordinate and the full exposure coordinate.

Parameters:	ampData : `lsst.afw.image.ImageF` Amplifier image to use for conversions. x : `int` X-coordinate of the point to transform. y : `int` Y-coordinate of the point to transform.
Returns:	u : `int` Transformed x-coordinate. v : `int` Transformed y-coordinate.

Notes

The output is transposed intentionally here, to match the internal transpose between numpy and afw.image coordinates.

makeBfKernel()¶

Generate a simple Gaussian brighter-fatter kernel.

Returns:	kernel : `numpy.ndarray` Simulated brighter-fatter kernel.

makeCrosstalkCoeff()¶

Generate the simulated crosstalk coefficients.

Returns:	coeffs : `numpy.ndarray` Simulated crosstalk coefficients.

makeData()¶

Generate simulated ISR data.

Currently, only the class defined crosstalk coefficient matrix, brighter-fatter kernel, a constant unity transmission curve, or a simple single-entry defect list can be generated.

Returns:	dataProduct : Simulated ISR data product.

makeDefectList()¶

Generate a simple single-entry defect list.

Returns:	defectList : `lsst.meas.algorithms.Defects` Simulated defect list

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")

makeImage()¶

Generate a simulated ISR image.

Returns:	exposure : `lsst.afw.image.Exposure` or `dict` Simulated ISR image data.

Notes

This method currently constructs a “raw” data image by:

Generating a simulated sky with noise
Adding a single Gaussian “star”
Adding the fringe signal
Multiplying the frame by the simulated flat
Adding dark current (and noise)
Adding a bias offset (and noise)
Adding an overscan gradient parallel to the pixel y-axis
Simulating crosstalk by adding a scaled version of each amplifier to each other amplifier.

The exposure with image data constructed this way is in one of three formats.

A single image, with overscan and prescan regions retained
A single image, with overscan and prescan regions trimmed
A dict, containing the amplifer data indexed by the amplifier name.

The nonlinearity, CTE, and brighter fatter are currently not implemented.

Note that this method generates an image in the reverse direction as the ISR processing, as the output image here has had a series of instrument effects added to an idealized exposure.

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.

makeTransmissionCurve()¶

Generate a simulated flat transmission curve.

Returns:	transmission : `lsst.afw.image.TransmissionCurve` Simulated transmission curve.

run()¶

Generate a mock ISR product, and return it.

Returns:	image : `lsst.afw.image.Exposure` Simulated ISR image with signals added. dataProduct : Simulated ISR data products. None : Returned if no valid configuration was found.
Raises:	RuntimeError Raised if both doGenerateImage and doGenerateData are specified.

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.

Navigation

IsrMock¶