def make_filename(self, filename, jones_label=None):
"""
Helper method: expands full filename a from templated filename. This uses the standard
str.format() function, passing in self.global_options, as well as JONES=jones_label, as keyword
arguments. This allows for filename templates that include strings from the global options
dictionary, e.g. "{data[ms]}-ddid{sel[ddid]}".
Args:
filename (str):
the templated filename
jones_label (str, optional):
Jones matrix label, overrides self.jones_label if specified.
Returns:
str:
Expanded filename
"""
return expand_templated_name(filename,
JONES=jones_label or self.jones_label)
def __init__(self, gmfactory, ifrgain_opts, compute=True):
"""
Initializes the IFR-based gains machinery.
Args:
gmfactory: a GainMachine Factory is used to manage the solution databases
ifrgain_opts: dict of options
compute: if False, gains are not computed even if options ask them to
"""
from cubical.main import expand_templated_name
self.gmfactory = gmfactory
load_from = expand_templated_name(ifrgain_opts['load-from'])
save_to = expand_templated_name(ifrgain_opts['save-to'])
self._ifrgains_per_chan = ifrgain_opts['per-chan']
self._ifrgain = None
self._nfreq = gmfactory.grid["freq"]
nfreq, nant, ncorr = [
len(gmfactory.grid[axis]) for axis in ("freq", "ant", "corr")
]
if load_from:
filename = load_from
print(ModColor.Str(
"applying baseline-based corrections (BBCs) from {}".format(
filename),
col="green"),
file=log(0))
if "//" in filename:
filename, prefix = filename.rsplit("//", 1)
else:
filename, prefix = filename, "BBC"
parm = param_db.load(filename).get(prefix)
if parm is None:
print(ModColor.Str(" no solutions for '{}' in {}".format(
prefix, filename)),
file=log(0))
else:
self._ifrgain = parm.reinterpolate(
freq=gmfactory.grid["freq"]).filled()
if tuple(self._ifrgain.shape) != (nfreq, nant, nant, ncorr,
ncorr):
print(ModColor.Str(
" invalid BBC shape {}, will ignore".format(
self._ifrgain.shape)),
file=log(0))
self._ifrgain = None
else:
print(" loaded per-channel BBCs of shape {}".format(
filename, self._ifrgain.shape),
file=log(0))
if not self._ifrgains_per_chan:
print(" using one mean value across band",
file=log(0))
self._ifrgain[np.newaxis,
...] = self._ifrgain.mean(axis=0)
# reset off-diagonal values, if needed
if ifrgain_opts["apply-2x2"]:
print(ModColor.Str(
" using full 2x2 BBCs. You'd better know what you're doing!",
col="green"),
file=log(0))
else:
self._ifrgain[..., (0, 1), (1, 0)] = 1
print(" using parallel-hand BBCs only", file=log(0))
if save_to and compute:
self._compute_2x2 = ifrgain_opts["compute-2x2"]
# setup axes for IFR-based gains
axes = ["freq", "ant1", "ant2", "corr1", "corr2"]
# define the ifrgain parameter
self._save_filename = save_to
parm = gmfactory.define_param(self._save_filename,
"BBC",
1 + 0j,
axes,
interpolation_axes=["freq"])
self._ifrgains_grid = {
axis: parm.grid[i]
for i, axis in enumerate(axes)
}
# initialize accumulators for M.D^H and D.D^H terms
self._mdh_sum = np.ma.zeros(parm.shape,
gmfactory.ctype,
fill_value=0)
self._ddh_sum = np.ma.zeros(parm.shape,
gmfactory.ctype,
fill_value=0)
#
print(
"will compute & save suggested baseline-based corrections (BBCs) to {}"
.format(self._save_filename),
file=log(0))
print(
" (these can optionally be applied in a subsequent CubiCal run)",
file=log(0))
else:
self._ifrgains_grid = None