def make_mosaic(self, block_selector=None, target_fits=None,
mosaic_key='image_path', weight_key='weight_path'):
"""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.
mosaic_key : str
MosaicDB key to save the mosaic's FITS path.
weight_key : str
MosaicDB key to save the mosaic weightmap's FITS path.
"""
mosaicDoc = self.mosaicdb.c.find_one({"_id": self.mosaic_name})
solver_cname = mosaicDoc['solver_cname']
solver_dbname = mosaicDoc['solver_dbname']
if block_selector:
block_sel = dict(block_selector)
else:
block_sel = dict(self.block_sel)
bloc_docs = self.blockdb.find_dict(block_sel)
solver = SimplexScalarOffsetSolver(dbname=solver_dbname,
cname=solver_cname,
url=self.mosaicdb.url, port=self.mosaicdb.port)
offsets = solver.find_best_offsets()
mosaic_path, mosaic_weight_path = blockmosaic.block_mosaic(bloc_docs,
offsets, self.mosaic_name, self._swarp_configs, self.workdir,
target_fits=target_fits,
delete_offset_images=True,
offset_fcn=offsettools.apply_offset,
path_key=self._image_key,
weight_key=self._weight_key)
self.mosaicdb.c.update({"_id": self.mosaic_name},
{"$set": {mosaic_key: mosaic_path,
weight_key: mosaic_weight_path}})
def _solve_offsets(self, mosaicName, solverDBName, couplings,
blockWCSs, mosaicWCS, initScale, restartScale,
fresh_start=True, n_runs=1000):
"""Use SimplexScalarOffsetSolver to derive offsets for this block."""
logPath = os.path.join(self.workdir, "%s.log" % mosaicName)
solver = SimplexScalarOffsetSolver(dbname=solverDBName,
cname=mosaicName,
url=self.mosaicdb.url, port=self.mosaicdb.port)
if fresh_start:
solver.resetdb()
initSigma, resetSigma = self._simplex_dispersion(initScale,
restartScale, couplings)
solver.multi_start(couplings, n_runs, logPath, cython=True, mp=True,
initSigma=initSigma,
restartSigma=resetSigma)
offsets = solver.find_best_offsets()
# Estimate uncertainty in the zeropoint of the sky offsets
zp_sigma = self._compute_offset_zp_sigma(offsets)
self.mosaicdb.c.update({"_id": mosaicName},
{"$set": {"offsets": offsets,
"offset_zp_sigma": zp_sigma,
"solver_cname": mosaicName,
"solver_dbname": solverDBName}})
return solver
