lsst.ip.isr.linearize.LinearizePolynomial Class Reference

Inheritance diagram for lsst.ip.isr.linearize.LinearizePolynomial:

Public Member Functions
	__call__ (self, image, **kwargs)

Static Public Attributes
str	LinearityType = "Polynomial"

Detailed Description

Correct non-linearity with a polynomial mode.

.. code-block::

    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.

Definition at line 620 of file linearize.py.

Member Function Documentation

__call__()

lsst.ip.isr.linearize.LinearizePolynomial.__call__	(		self,
			image,
		**	kwargs )

Correct non-linearity.

Parameters
----------
image : `lsst.afw.image.Image`
    Image to be corrected
kwargs : `dict`
    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
-------
output : `tuple` [`bool`, `int`]
    If true, a correction was applied successfully.  The
    integer indicates the number of pixels that were
    uncorrectable by being out of range.

Reimplemented from lsst.ip.isr.linearize.LinearizeBase.

Definition at line 640 of file linearize.py.

    def __call__(self, image, **kwargs):
        """Correct non-linearity.
 
        Parameters
        ----------
        image : `lsst.afw.image.Image`
            Image to be corrected
        kwargs : `dict`
            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
        -------
        output : `tuple` [`bool`, `int`]
            If true, a correction was applied successfully.  The
            integer indicates the number of pixels that were
            uncorrectable by being out of range.
        """
        if not np.any(np.isfinite(kwargs['coeffs'])):
            return False, 0
        if not np.any(kwargs['coeffs']):
            return False, 0
 
        ampArray = image.getArray()
        correction = np.zeros_like(ampArray)
        for order, coeff in enumerate(kwargs['coeffs'], start=2):
            correction += coeff * np.power(ampArray, order)
        ampArray += correction
 
        return True, 0
 
 

Member Data Documentation

LinearityType

str lsst.ip.isr.linearize.LinearizePolynomial.LinearityType = "Polynomial"

static

Definition at line 638 of file linearize.py.

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The documentation for this class was generated from the following file:

• /j/snowflake/release/lsstsw/stack/lsst-scipipe-8.0.0/Linux64/ip_isr/g02d81e74bb+fa3a7a026e/python/lsst/ip/isr/linearize.py