FitTanSipWcsTask¶
FitTanSipWcsTask
Fit a TAN-SIP WCS given a list of reference object/source
matches.
Processing summary¶
Measure the distortions in an image plane and express them a SIP polynomials.
Given a list of matching sources between a catalog and an image, and a linear Wcs that describes the mapping from pixel space in the image and ra/dec space in the catalog, calculate discrepancies between the two and compute SIP distortion polynomials to describe the discrepancy.
SIP polynomials are defined in Shupe at al. (2005) ASPC 347 491.
Note that the SIP standard insists (although it is only mentioned obliquely between Eqns 3 and 4) that the lowest three terms in the distortion polynomials be zero (A00, A10, A01, B00, etc.). To achieve this, we need to adjust the values of CD and CRPIX from the input wcs. This may not be the behavior you expect.
Python API summary¶
from lsst.meas.astrom.fitTanSipWcs import FitTanSipWcsTask
-
class
(config=None, name=None, parentTask=None, log=None)FitTanSipWcsTask
Fit a TAN-SIP WCS given a list of reference object/source matches
...
-
attribute
config
Access configuration fields and retargetable subtasks.
See also
See the FitTanSipWcsTask
API reference for complete details.
Retargetable subtasks¶
No subtasks.
Configuration fields¶
maxScatterArcsec¶
- Default
10
- Field type
float
RangeField
- Range
- [0,inf)
numIter¶
- Default
3
- Field type
int
RangeField
- Range
- [1,inf)
rejSigma¶
- Default
3.0
- Field type
float
RangeField
- Range
- [0.0,inf)
Examples¶
See lsst.pipe.tasks.photoCal.PhotoCalTask
.. note:: Pipe task will require conversion before this link is usable.
Debugging¶
FitTanSipWcsTask does not support any debug variables.