scalarmosaicfactory API Reference
Make mosaics using scalar sky offsets.
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class skyoffset.scalarmosaicfactory.ScalarMosaicFactory(mosaic_name, block_sel, blockdb, mosaicdb, workdir, swarp_configs=None)[source]
Pipeline class for solving scalar sky offsets between overlapping images
and producing a mosaic.
| Parameters: | mosaic_name : str
Name of the mosaic being generated.
block_sel : dict
A MongoDB selector for blocks in the BlockDB.
blockdb : skyoffset.imagedb.MosaicDB instance
A MosaicDB database containing blocks, the component images that
will be mosaiced together.
mosaicdb : skyoffset.imagedb.MosaicDB instance
A MosaicDB database where the final mosaic will be stored.
workdir : str
Directory where the mosaic will be created. This directory will
be created if necessary.
swarp_configs : dict
A dictionary of configurations to pass to
moastro.astromatic.Swarp.
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make_mosaic(block_selector=None, target_fits=None)[source]
Swarp a mosaic using the optimal sky offsets.
The mosaic can be made anytime once entries are added
to the solver’s collection. This is because we initialize
a SimplexScalarOffsetSolver that re-generates the list of best
offsets from the collection of solver documents.
| Parameters: | block_selector : dict
An alternative MongoDB block selector (used instead of the one
specific during instance initialization). This can be useful
for building a mosaic with a subset of the blocks.
target_fits : str
Set to the path of a FITS file that will be used to define the
output frame of the block. The output blocks will then correspond
pixel-to-pixel. Note that both blocks should already be resampled
into the same pixel space.
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make_noisemap(block_selector=None)[source]
Make a Gaussian sigma noise map, propagating those from stacks.
| Parameters: | block_selector : dict
An alternative MongoDB block selector (used instead of the one
specific during instance initialization). This can be useful
for building a mosaic with a subset of the blocks.
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make_tiff()[source]
Render a tiff image of this block.
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solve_offsets(solver_dbname, solver_cname, n_runs=1000, dbmeta=None, reset_couplings=False, fresh_start=True, init_scale=5.0, restart_scale=2.0)[source]
Pipeline for solving the scalar sky offsets between a set of
blocks.
| Parameters: | solver_dbname : str
Name of the MongoDB database where results from sky offset
optimization are persisted.
solver_cname : str
Name of the MongoDB collection where results from sky offset
optimization are persisted.
n_runs : int
Number of optimizations to start; the sky offsets from the best
optimization run are chosen.
init_scale : float
Sets dispersion of initial guesses sky offsets as a fraction of
the block difference dispersion.
restart_scale : float
Sets dispersion of sky offset simplex re-inflation as a fraction of
the block difference dispersion after an optimization as converged.
dbmeta : dict
Arbitrary metadata to store in the mosaic’s MongoDB document.
reset_couplings : bool
If True, then the couplings (differences) between blocks
will be recomputed.
fresh_start : bool
If True, then previous optimization runs for this mosaic
will be deleted from the sky offset solver MongoDB collection.
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subsample_mosaic(pixel_scale=1.0, fluxscale=True)[source]
Subsamples the existing mosaic.