LinearizePolynomial

class lsst.ip.isr.LinearizePolynomial

Bases: LinearizeBase

Correct non-linearity with a polynomial mode.

corrImage = uncorrImage + sum_i c_i uncorrImage^(2 + i)

where c_i are the linearity coefficients for each amplifier. Lower order coefficients are not included as they duplicate other calibration parameters:

k0

A coefficient multiplied by uncorrImage**0 is equivalent to bias level. Irrelevant for correcting non-linearity.

k1

A coefficient multiplied by uncorrImage**1 is proportional to the gain. Not necessary for correcting non-linearity.

Attributes Summary

LinearityType

Methods Summary

__call__(image, **kwargs)

Correct non-linearity.

Attributes Documentation

LinearityType = 'Polynomial'

Methods Documentation

__call__(image, **kwargs)

Correct non-linearity.

Parameters:

imagelsst.afw.image.Image

Image to be corrected

kwargsdict

Dictionary of parameter keywords:

coeffs

Coefficient vector (list or numpy.array). If the order of the polynomial is n, this list should have a length of n-1 (“k0” and “k1” are not needed for the correction).

log

Logger to handle messages (logging.Logger).

Returns:

outputtuple [bool, int]

If true, a correction was applied successfully. The integer indicates the number of pixels that were uncorrectable by being out of range.