IsrStatisticsTask¶
- class lsst.ip.isr.IsrStatisticsTask(statControl=None, **kwargs)¶
Bases:
Task
Task to measure arbitrary statistics on ISR processed exposures.
The goal is to wrap a number of optional measurements that are useful for calibration production and detector stability.
Methods Summary
copyCalibDistributionStatistics
(inputExp, ...)Copy calibration statistics for this exposure.
Empty (clear) the metadata for this Task and all sub-Tasks.
Get metadata for all tasks.
Get the task name as a hierarchical name including parent task names.
getName
()Get the name of the task.
Get a dictionary of all tasks as a shallow copy.
makeField
(doc)Make a
lsst.pex.config.ConfigurableField
for this task.makeKernel
(kernelSize)Make a boxcar smoothing kernel.
makeSubtask
(name, **keyArgs)Create a subtask as a new instance as the
name
attribute of this task.measureAmpCorrelations
(inputExp, overscanResults)Measure correlations between amplifier segments.
measureBanding
(inputExp, overscans)Task to measure banding statistics.
measureBiasShifts
(inputExp, overscanResults)Measure number of bias shifts from overscan data.
measureCti
(inputExp, overscans, gains)Task to measure CTI statistics.
measureDivisaderoStatistics
(inputExp, **kwargs)Measure Max Divisadero Tearing effect per amp.
measureProjectionStatistics
(inputExp, overscans)Task to measure metrics from image slicing.
run
(inputExp[, ptc, overscanResults])Task to run arbitrary statistics.
timer
(name[, logLevel])Context manager to log performance data for an arbitrary block of code.
Methods Documentation
- copyCalibDistributionStatistics(inputExp, **kwargs)¶
Copy calibration statistics for this exposure.
- getFullMetadata() 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.
- metadata
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”.
- fullName
- getName() str ¶
Get the name of the task.
- Returns:
- taskName
str
Name of the task.
- taskName
See also
getFullName
Get the full name of the task.
- getTaskDict() dict[str, weakref.ReferenceType[lsst.pipe.base.task.Task]] ¶
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.
- taskDict
- classmethod makeField(doc: str) ConfigurableField ¶
Make a
lsst.pex.config.ConfigurableField
for this task.- Parameters:
- doc
str
Help text for the field.
- doc
- Returns:
- configurableField
lsst.pex.config.ConfigurableField
A
ConfigurableField
for this task.
- configurableField
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")
- static makeKernel(kernelSize)¶
Make a boxcar smoothing kernel.
- Parameters:
- kernelSize
int
Size of the kernel in pixels.
- kernelSize
- Returns:
- kernel
np.array
Kernel for boxcar smoothing.
- kernel
- makeSubtask(name: str, **keyArgs: Any) 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
.
- name
Notes
The subtask must be defined by
Task.config.name
, an instance ofConfigurableField
orRegistryField
.
- measureAmpCorrelations(inputExp, overscanResults)¶
Measure correlations between amplifier segments.
- Parameters:
- inputExp
lsst.afw.image.Exposure
Exposure to measure.
- overscans
list
[lsst.pipe.base.Struct
] List of overscan results. Expected fields are:
imageFit
Value or fit subtracted from the amplifier image data (scalar or
lsst.afw.image.Image
).overscanFit
Value or fit subtracted from the overscan image data (scalar or
lsst.afw.image.Image
).overscanImage
Image of the overscan region with the overscan correction applied (
lsst.afw.image.Image
). This quantity is used to estimate the amplifier read noise empirically.
- inputExp
- Returns:
Notes
Based on eo_pipe implementation: https://github.com/lsst-camera-dh/eo_pipe/blob/main/python/lsst/eo/pipe/raft_level_correlations.py # noqa: E501 W505
- measureBanding(inputExp, overscans)¶
Task to measure banding statistics.
- Parameters:
- inputExp
lsst.afw.image.Exposure
Exposure to measure.
- overscans
list
[lsst.pipe.base.Struct
] List of overscan results. Expected fields are:
imageFit
Value or fit subtracted from the amplifier image data (scalar or
lsst.afw.image.Image
).overscanFit
Value or fit subtracted from the overscan image data (scalar or
lsst.afw.image.Image
).overscanImage
Image of the overscan region with the overscan correction applied (
lsst.afw.image.Image
). This quantity is used to estimate the amplifier read noise empirically.
- inputExp
- Returns:
- measureBiasShifts(inputExp, overscanResults)¶
Measure number of bias shifts from overscan data.
- Parameters:
- inputExp
lsst.afw.image.Exposure
Exposure to measure.
- overscans
list
[lsst.pipe.base.Struct
] List of overscan results. Expected fields are:
imageFit
Value or fit subtracted from the amplifier image data (scalar or
lsst.afw.image.Image
).overscanFit
Value or fit subtracted from the overscan image data (scalar or
lsst.afw.image.Image
).overscanImage
Image of the overscan region with the overscan correction applied (
lsst.afw.image.Image
). This quantity is used to estimate the amplifier read noise empirically.
- inputExp
- Returns:
Notes
Based on eop_pipe implementation: https://github.com/lsst-camera-dh/eo_pipe/blob/main/python/lsst/eo/pipe/biasShiftsTask.py # noqa: E501 W505
- measureCti(inputExp, overscans, gains)¶
Task to measure CTI statistics.
- Parameters:
- inputExp
lsst.afw.image.Exposure
Exposure to measure.
- overscans
list
[lsst.pipe.base.Struct
] List of overscan results. Expected fields are:
imageFit
Value or fit subtracted from the amplifier image data (scalar or
lsst.afw.image.Image
).overscanFit
Value or fit subtracted from the overscan image data (scalar or
lsst.afw.image.Image
).overscanImage
Image of the overscan region with the overscan correction applied (
lsst.afw.image.Image
). This quantity is used to estimate the amplifier read noise empirically.
- gains
dict
[str
float
] Dictionary of per-amplifier gains, indexed by amplifier name.
- inputExp
- Returns:
- measureDivisaderoStatistics(inputExp, **kwargs)¶
Measure Max Divisadero Tearing effect per amp.
- Parameters:
- inputExp
lsst.afw.image.Exposure
Exposure to measure. Usually a flat.
- **kwargs
The flat will be selected from here.
- inputExp
- Returns:
- outputStats
dict
[str
, [dict
[str
,float
]]] Dictionary of measurements, keyed by amplifier name and statistics segment. Measurements include
DIVISADERO_PROFILE: Robust mean of rows between divisaderoProjection<Maximum|Minumum> on readout edge of ccd normalized by a linear fit to the same rows.
DIVISADERO_MAX_PAIR: Tuple of maximum of the absolute values of the DIVISADERO_PROFILE, for number of pixels (specified by divisaderoNumImpactPixels on left and right side of amp.
DIVISADERO_MAX: Maximum of the absolute values of the the DIVISADERO_PROFILE, for the divisaderoNumImpactPixels on boundaries of neighboring amps (including the pixels in those neighborboring amps).
- outputStats
- measureProjectionStatistics(inputExp, overscans)¶
Task to measure metrics from image slicing.
- Parameters:
- inputExp
lsst.afw.image.Exposure
Exposure to measure.
- overscans
list
[lsst.pipe.base.Struct
] List of overscan results. Expected fields are:
imageFit
Value or fit subtracted from the amplifier image data (scalar or
lsst.afw.image.Image
).overscanFit
Value or fit subtracted from the overscan image data (scalar or
lsst.afw.image.Image
).overscanImage
Image of the overscan region with the overscan correction applied (
lsst.afw.image.Image
). This quantity is used to estimate the amplifier read noise empirically.
- inputExp
- Returns:
- run(inputExp, ptc=None, overscanResults=None, **kwargs)¶
Task to run arbitrary statistics.
The statistics should be measured by individual methods, and add to the dictionary in the return struct.
- Parameters:
- inputExp
lsst.afw.image.Exposure
The exposure to measure.
- ptc
lsst.ip.isr.PtcDataset
, optional A PTC object containing gains to use.
- overscanResults
list
[lsst.pipe.base.Struct
], optional List of overscan results. Expected fields are:
imageFit
Value or fit subtracted from the amplifier image data (scalar or
lsst.afw.image.Image
).overscanFit
Value or fit subtracted from the overscan image data (scalar or
lsst.afw.image.Image
).overscanImage
Image of the overscan region with the overscan correction applied (
lsst.afw.image.Image
). This quantity is used to estimate the amplifier read noise empirically.
- **kwargs
Keyword arguments. Calibrations being passed in should have an entry here.
- inputExp
- Returns:
- resultStruct
lsst.pipe.base.Struct
Contains the measured statistics as a dict stored in a field named
results
.
- resultStruct
- Raises:
- RuntimeError
Raised if the amplifier gains could not be found.