autowisp.magnitude_fitting.linear module

Class Inheritance Diagram

Implement magnitude fitting using linear regression.

class autowisp.magnitude_fitting.linear.LinearMagnitudeFit(*, config, **kwargs)

Bases: MagnitudeFit

Differential photometry correction using linear regression.

__call__(*args, **kwargs)

Delay creating of fit terms to avoid pickling.

__init__(*, config, **kwargs)

Initialize a magnitude fitting object using linear least squares.

Parameters:

config –

An object with attributes configuring how to perform magnitude fitting. It should provide at least the arguments required by the parent class and the following:

• correction_parametrization: As string that expands to the terms to include in the magnitude fitting correction.

• max_mag_err: The largest the formal magnitude error is allowed to be before the source is excluded.

• noise_offset: Additional offset to format magnitude error estimates when they are used to determine the fitting weights.

• error_avg: See same name argument to autowisp.fit_expression.iterative_fit().

• rej_level: See same name argument to autowisp.fit_expression.iterative_fit().

• max_rej_iter: See same name argument to autowisp.fit_expression.iterative_fit().

Returns:

None

_compute_mag_offset(phot_fit_results, fit_base, header)

Evaluate the magfit correction at the image centre for a median star.

Builds a synthetic source whose per-field values are the median of fit_base, then overrides x and y with the image centre (NAXIS1/2, NAXIS2/2). The correction is evaluated by dotting the fit coefficients with the resulting predictors, and the median across fit groups is returned.