lsst.pipe.tasks g14a832a312+311607e4ab
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Classes | Functions
lsst.pipe.tasks.computeExposureSummaryStats Namespace Reference

Classes

class  ComputeExposureSummaryStatsConfig
 
class  ComputeExposureSummaryStatsTask
 

Functions

 maximum_nearest_psf_distance (image_mask, psf_cat, sampling=8, bad_mask_bits=["BAD", "CR", "INTRP", "SAT", "SUSPECT", "NO_DATA", "EDGE"])
 
 psf_trace_radius_delta (image_mask, image_psf, sampling=96, bad_mask_bits=["BAD", "CR", "INTRP", "SAT", "SUSPECT", "NO_DATA", "EDGE"])
 

Function Documentation

◆ maximum_nearest_psf_distance()

lsst.pipe.tasks.computeExposureSummaryStats.maximum_nearest_psf_distance ( image_mask,
psf_cat,
sampling = 8,
bad_mask_bits = ["BAD", "CR", "INTRP", "SAT", "SUSPECT", "NO_DATA", "EDGE"] )
Compute the maximum distance of an unmasked pixel to its nearest PSF.

Parameters
----------
image_mask : `lsst.afw.image.Mask`
    The mask plane associated with the exposure.
psf_cat : `lsst.afw.table.SourceCatalog` or `astropy.table.Table`
    Catalog containing only the stars used in the PSF modeling.
sampling : `int`
    Sampling rate in each dimension to create the grid of points on which
    to evaluate the distance to the nearest PSF star. The tradeoff is
    between adequate sampling versus speed.
bad_mask_bits : `list` [`str`]
    Mask bits required to be absent for a pixel to be considered
    "unmasked".

Returns
-------
max_dist_to_nearest_psf : `float`
    The maximum distance (in pixels) of an unmasked pixel to its nearest
    PSF model star.

Definition at line 604 of file computeExposureSummaryStats.py.

◆ psf_trace_radius_delta()

lsst.pipe.tasks.computeExposureSummaryStats.psf_trace_radius_delta ( image_mask,
image_psf,
sampling = 96,
bad_mask_bits = ["BAD", "CR", "INTRP", "SAT", "SUSPECT", "NO_DATA", "EDGE"] )
Compute the delta between the maximum and minimum model PSF trace radius
values evaluated on a grid of points lying in the unmasked region of the
image.

Parameters
----------
image_mask : `lsst.afw.image.Mask`
    The mask plane associated with the exposure.
image_psf : `lsst.afw.detection.Psf`
    The PSF model associated with the exposure.
sampling : `int`
    Sampling rate in each dimension to create the grid of points at which
    to evaluate ``image_psf``s trace radius value. The tradeoff is between
    adequate sampling versus speed.
bad_mask_bits : `list` [`str`]
    Mask bits required to be absent for a pixel to be considered
    "unmasked".

Returns
-------
psf_trace_radius_delta : `float`
    The delta (in pixels) between the maximum and minimum model PSF trace
    radius values evaluated on the x,y-grid subsampled on the unmasked
    detector pixels by a factor of ``sampling``.  If any model PSF trace
    radius value on the grid evaluates to NaN, then NaN is returned
    immediately.

Definition at line 651 of file computeExposureSummaryStats.py.