register_datasets

sofia_redux.instruments.forcast.register_datasets.register_datasets(datasets, user_shifts=None, basehead=None, refset=0, algorithm=None, initial_reference=None, missing=nan)[source]

Registers multiple sets of data to the same frame

Parameters:
datasetsarray_like of tuples

All elements are tuples. Each tuple represents a data set consisting where the elements are as follows:

  1. numpy.ndarray: image array (nrow, ncol). Image shapes are allowed to differ from others in the inputs data set.

  2. astropy.io.fits.header.Header: FITS header for the image array

  3. numpy.ndarray, optional: variance array (nrow, ncol). Used to propagate variance. Must be the same shape as the data array in the first element.

  4. numpy.ndarray, optional: normalization map (nrow, ncol) to propagate. Must be the same shape as the data array in the first element.

refsetint, optional

Index of the dataset to use as the reference. Default is the first set in the list (0).

user_shiftsarray_like of array_like, optional

User shifts if required. No shift may be represented by None. All other shifts should be supplied as (dx, dy). Length must be the same length as datasets

baseheadastropy.io.fits.header.Header, optional

FITS header to update with HISTORY messages

algorithmstr, optional

Registration and coadding algorithm. If None, defaults to the coadding algorithm determined by the drip configuration or reference header.

initial_referencearray_like, optional

An optional reference to pass if an initial shift on the reference dataset is required.

missingfloat, optional

Value with which to fill missing data points following a shift

Returns:
list of tuple

registered datasets