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:
numpy.ndarray: image array (nrow, ncol). Image shapes are allowed to differ from others in the inputs data set.
astropy.io.fits.header.Header: FITS header for the image array
numpy.ndarray, optional: variance array (nrow, ncol). Used to propagate variance. Must be the same shape as the data array in the first element.
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