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def | createPsf (fwhm) |
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def | transposeMaskedImage (maskedImage) |
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def | interpolateDefectList (maskedImage, defectList, fwhm, fallbackValue=None) |
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def | makeThresholdMask (maskedImage, threshold, growFootprints=1, maskName='SAT') |
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def | growMasks (mask, radius=0, maskNameList=['BAD'], maskValue="BAD") |
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def | interpolateFromMask (maskedImage, fwhm, growSaturatedFootprints=1, maskNameList=['SAT'], fallbackValue=None) |
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def | saturationCorrection (maskedImage, saturation, fwhm, growFootprints=1, interpolate=True, maskName='SAT', fallbackValue=None) |
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def | trimToMatchCalibBBox (rawMaskedImage, calibMaskedImage) |
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def | biasCorrection (maskedImage, biasMaskedImage, trimToFit=False) |
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def | darkCorrection (maskedImage, darkMaskedImage, expScale, darkScale, invert=False, trimToFit=False) |
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def | updateVariance (maskedImage, gain, readNoise) |
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def | flatCorrection (maskedImage, flatMaskedImage, scalingType, userScale=1.0, invert=False, trimToFit=False) |
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def | illuminationCorrection (maskedImage, illumMaskedImage, illumScale, trimToFit=True) |
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def | overscanCorrection (ampMaskedImage, overscanImage, fitType='MEDIAN', order=1, collapseRej=3.0, statControl=None, overscanIsInt=True) |
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def | brighterFatterCorrection (exposure, kernel, maxIter, threshold, applyGain, gains=None) |
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def | gainContext (exp, image, apply, gains=None) |
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def | attachTransmissionCurve (exposure, opticsTransmission=None, filterTransmission=None, sensorTransmission=None, atmosphereTransmission=None) |
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def | applyGains (exposure, normalizeGains=False, ptcGains=None) |
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def | widenSaturationTrails (mask) |
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def | setBadRegions (exposure, badStatistic="MEDIAN") |
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def | checkFilter (exposure, filterList, log) |
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def | getPhysicalFilter (filterLabel, log) |
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def lsst.ip.isr.isrFunctions.attachTransmissionCurve |
( |
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exposure, |
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opticsTransmission = None , |
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filterTransmission = None , |
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sensorTransmission = None , |
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atmosphereTransmission = None |
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) |
| |
Attach a TransmissionCurve to an Exposure, given separate curves for
different components.
Parameters
----------
exposure : `lsst.afw.image.Exposure`
Exposure object to modify by attaching the product of all given
``TransmissionCurves`` in post-assembly trimmed detector coordinates.
Must have a valid ``Detector`` attached that matches the detector
associated with sensorTransmission.
opticsTransmission : `lsst.afw.image.TransmissionCurve`
A ``TransmissionCurve`` that represents the throughput of the optics,
to be evaluated in focal-plane coordinates.
filterTransmission : `lsst.afw.image.TransmissionCurve`
A ``TransmissionCurve`` that represents the throughput of the filter
itself, to be evaluated in focal-plane coordinates.
sensorTransmission : `lsst.afw.image.TransmissionCurve`
A ``TransmissionCurve`` that represents the throughput of the sensor
itself, to be evaluated in post-assembly trimmed detector coordinates.
atmosphereTransmission : `lsst.afw.image.TransmissionCurve`
A ``TransmissionCurve`` that represents the throughput of the
atmosphere, assumed to be spatially constant.
Returns
-------
combined : `lsst.afw.image.TransmissionCurve`
The TransmissionCurve attached to the exposure.
Notes
-----
All ``TransmissionCurve`` arguments are optional; if none are provided, the
attached ``TransmissionCurve`` will have unit transmission everywhere.
Definition at line 700 of file isrFunctions.py.
def lsst.ip.isr.isrFunctions.brighterFatterCorrection |
( |
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exposure, |
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kernel, |
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maxIter, |
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threshold, |
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applyGain, |
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gains = None |
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) |
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Apply brighter fatter correction in place for the image.
Parameters
----------
exposure : `lsst.afw.image.Exposure`
Exposure to have brighter-fatter correction applied. Modified
by this method.
kernel : `numpy.ndarray`
Brighter-fatter kernel to apply.
maxIter : scalar
Number of correction iterations to run.
threshold : scalar
Convergence threshold in terms of the sum of absolute
deviations between an iteration and the previous one.
applyGain : `Bool`
If True, then the exposure values are scaled by the gain prior
to correction.
gains : `dict` [`str`, `float`]
A dictionary, keyed by amplifier name, of the gains to use.
If gains is None, the nominal gains in the amplifier object are used.
Returns
-------
diff : `float`
Final difference between iterations achieved in correction.
iteration : `int`
Number of iterations used to calculate correction.
Notes
-----
This correction takes a kernel that has been derived from flat
field images to redistribute the charge. The gradient of the
kernel is the deflection field due to the accumulated charge.
Given the original image I(x) and the kernel K(x) we can compute
the corrected image Ic(x) using the following equation:
Ic(x) = I(x) + 0.5*d/dx(I(x)*d/dx(int( dy*K(x-y)*I(y))))
To evaluate the derivative term we expand it as follows:
0.5 * ( d/dx(I(x))*d/dx(int(dy*K(x-y)*I(y)))
+ I(x)*d^2/dx^2(int(dy* K(x-y)*I(y))) )
Because we use the measured counts instead of the incident counts
we apply the correction iteratively to reconstruct the original
counts and the correction. We stop iterating when the summed
difference between the current corrected image and the one from
the previous iteration is below the threshold. We do not require
convergence because the number of iterations is too large a
computational cost. How we define the threshold still needs to be
evaluated, the current default was shown to work reasonably well
on a small set of images. For more information on the method see
DocuShare Document-19407.
The edges as defined by the kernel are not corrected because they
have spurious values due to the convolution.
Definition at line 522 of file isrFunctions.py.
def lsst.ip.isr.isrFunctions.darkCorrection |
( |
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maskedImage, |
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darkMaskedImage, |
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expScale, |
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darkScale, |
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invert = False , |
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trimToFit = False |
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) |
| |
Apply dark correction in place.
Parameters
----------
maskedImage : `lsst.afw.image.MaskedImage`
Image to process. The image is modified by this method.
darkMaskedImage : `lsst.afw.image.MaskedImage`
Dark image of the same size as ``maskedImage``.
expScale : scalar
Dark exposure time for ``maskedImage``.
darkScale : scalar
Dark exposure time for ``darkMaskedImage``.
invert : `Bool`, optional
If True, re-add the dark to an already corrected image.
trimToFit : `Bool`, optional
If True, raw data is symmetrically trimmed to match
calibration size.
Raises
------
RuntimeError
Raised if ``maskedImage`` and ``darkMaskedImage`` do not have
the same size.
Notes
-----
The dark correction is applied by calculating:
maskedImage -= dark * expScaling / darkScaling
Definition at line 300 of file isrFunctions.py.
def lsst.ip.isr.isrFunctions.flatCorrection |
( |
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maskedImage, |
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flatMaskedImage, |
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scalingType, |
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userScale = 1.0 , |
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invert = False , |
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|
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trimToFit = False |
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) |
| |
Apply flat correction in place.
Parameters
----------
maskedImage : `lsst.afw.image.MaskedImage`
Image to process. The image is modified.
flatMaskedImage : `lsst.afw.image.MaskedImage`
Flat image of the same size as ``maskedImage``
scalingType : str
Flat scale computation method. Allowed values are 'MEAN',
'MEDIAN', or 'USER'.
userScale : scalar, optional
Scale to use if ``scalingType``='USER'.
invert : `Bool`, optional
If True, unflatten an already flattened image.
trimToFit : `Bool`, optional
If True, raw data is symmetrically trimmed to match
calibration size.
Raises
------
RuntimeError
Raised if ``maskedImage`` and ``flatMaskedImage`` do not have
the same size or if ``scalingType`` is not an allowed value.
Definition at line 362 of file isrFunctions.py.
def lsst.ip.isr.isrFunctions.gainContext |
( |
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exp, |
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image, |
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apply, |
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gains = None |
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) |
| |
Context manager that applies and removes gain.
Parameters
----------
exp : `lsst.afw.image.Exposure`
Exposure to apply/remove gain.
image : `lsst.afw.image.Image`
Image to apply/remove gain.
apply : `Bool`
If True, apply and remove the amplifier gain.
gains : `dict` [`str`, `float`]
A dictionary, keyed by amplifier name, of the gains to use.
If gains is None, the nominal gains in the amplifier object are used.
Yields
------
exp : `lsst.afw.image.Exposure`
Exposure with the gain applied.
Definition at line 648 of file isrFunctions.py.
def lsst.ip.isr.isrFunctions.overscanCorrection |
( |
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ampMaskedImage, |
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overscanImage, |
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fitType = 'MEDIAN' , |
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order = 1 , |
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collapseRej = 3.0 , |
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statControl = None , |
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|
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overscanIsInt = True |
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) |
| |
Apply overscan correction in place.
Parameters
----------
ampMaskedImage : `lsst.afw.image.MaskedImage`
Image of amplifier to correct; modified.
overscanImage : `lsst.afw.image.Image` or `lsst.afw.image.MaskedImage`
Image of overscan; modified.
fitType : `str`
Type of fit for overscan correction. May be one of:
- ``MEAN``: use mean of overscan.
- ``MEANCLIP``: use clipped mean of overscan.
- ``MEDIAN``: use median of overscan.
- ``MEDIAN_PER_ROW``: use median per row of overscan.
- ``POLY``: fit with ordinary polynomial.
- ``CHEB``: fit with Chebyshev polynomial.
- ``LEG``: fit with Legendre polynomial.
- ``NATURAL_SPLINE``: fit with natural spline.
- ``CUBIC_SPLINE``: fit with cubic spline.
- ``AKIMA_SPLINE``: fit with Akima spline.
order : `int`
Polynomial order or number of spline knots; ignored unless
``fitType`` indicates a polynomial or spline.
statControl : `lsst.afw.math.StatisticsControl`
Statistics control object. In particular, we pay attention to
``numSigmaClip``.
overscanIsInt : `bool`
Treat the overscan region as consisting of integers, even if it's been
converted to float. E.g. handle ties properly.
Returns
-------
result : `lsst.pipe.base.Struct`
Result struct with components:
- ``imageFit``: Value(s) removed from image (scalar or
`lsst.afw.image.Image`)
- ``overscanFit``: Value(s) removed from overscan (scalar or
`lsst.afw.image.Image`)
- ``overscanImage``: Overscan corrected overscan region
(`lsst.afw.image.Image`)
Raises
------
RuntimeError
Raised if ``fitType`` is not an allowed value.
Notes
-----
The ``ampMaskedImage`` and ``overscanImage`` are modified, with the fit
subtracted. Note that the ``overscanImage`` should not be a subimage of
the ``ampMaskedImage``, to avoid being subtracted twice.
Debug plots are available for the SPLINE fitTypes by setting the
`debug.display` for `name` == "lsst.ip.isr.isrFunctions". These
plots show the scatter plot of the overscan data (collapsed along
the perpendicular dimension) as a function of position on the CCD
(normalized between +/-1).
Definition at line 444 of file isrFunctions.py.
def lsst.ip.isr.isrFunctions.saturationCorrection |
( |
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maskedImage, |
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|
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saturation, |
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|
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fwhm, |
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|
|
growFootprints = 1 , |
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|
|
interpolate = True , |
|
|
|
maskName = 'SAT' , |
|
|
|
fallbackValue = None |
|
) |
| |
Mark saturated pixels and optionally interpolate over them
Parameters
----------
maskedImage : `lsst.afw.image.MaskedImage`
Image to process.
saturation : scalar
Saturation level used as the detection threshold.
fwhm : scalar
FWHM of double Gaussian smoothing kernel.
growFootprints : scalar, optional
Number of pixels to grow footprints of detected regions.
interpolate : Bool, optional
If True, saturated pixels are interpolated over.
maskName : str, optional
Mask plane name.
fallbackValue : scalar, optional
Value of last resort for interpolation.
Definition at line 191 of file isrFunctions.py.