def test_flux_calib_corr(datadir, plot=False):
"""
Test the handling of the flux calibration
"""
filename = datadir.join("test_sensitivity_cube.fits").strpath
#filename = datadir.join("test.fits").strpath
fcalib_corr = datadir.join("polyvals.txt").strpath
wavelengths = [3500.0, 5500.0]
alphas = [-3.5, -3.5]
scube = SensitivityCube.from_file(filename, wavelengths, alphas)
scube_corr1 = SensitivityCube.from_file(filename, wavelengths, alphas)
scube_corr1.apply_flux_recalibration(
1.0, flux_calib_correction_file=fcalib_corr)
# The aper_corr should be multiplied though in the cubes
ratio = scube.sigmas.filled() / scube_corr1.sigmas.filled()
if plot:
import matplotlib.pyplot as plt
ra, dec, wls = scube.wcs.wcs_pix2world(0, 0,
range(scube.sigmas.shape[0]), 0)
plt.plot(wls,
(scube.f50vals[:, 10, 10] - scube_corr1.sigmas[:, 10, 10]) /
scube.sigmas[:, 10, 10])
plt.show()
# Check something happened
assert ratio != pytest.approx(1.0)
def sensitivity_cube(datadir):
""" A sensitivity cube to add or read"""
filename = datadir.join("test_sensitivity_cube.fits").strpath
wavelengths = [3500.0, 5500.0]
alphas = [-3.5, -3.5]
return SensitivityCube.from_file(filename, wavelengths, alphas)
def test_aper_corr(datadir, aper_corr):
"""
Test the handling of the aperture
correction
"""
filename = datadir.join("test_sensitivity_cube.fits").strpath
wavelengths = [3500.0, 5500.0]
alphas = [-3.5, -3.5]
scube = SensitivityCube.from_file(filename,
wavelengths,
alphas,
aper_corr=aper_corr)
scube_corr1 = SensitivityCube.from_file(filename,
wavelengths,
alphas,
aper_corr=1.0)
# The aper_corr should be multiplied though in the cubes
ratio = scube.sigmas.filled() / scube_corr1.sigmas.filled()
assert ratio == pytest.approx(aper_corr)
def test_completeness_func(datadir, flux, model, sncut, expected):
"""
Test that a value is returned
"""
filename = datadir.join("test_sensitivity_cube.fits").strpath
wavelengths = [3500.0, 5500.0]
alphas = [-3.5, -3.5]
if model == "hdr1":
scube = SensitivityCube.from_file(filename,
wavelengths,
alphas,
nsigma=1.0,
flim_model=model,
aper_corr=None)
else:
scube = SensitivityCube.from_file(filename,
wavelengths,
alphas,
nsigma=1.0,
flim_model=model)
c = scube.return_completeness(flux, 161.4201, 50.8822, 3478, sncut)
assert c == pytest.approx(expected)
def add_sensitivity_cube_to_hdf5(args=None):
"""
Command line tool to add a sensitivity cube(s)
to an HDF5 containter
"""
import argparse
parser = argparse.ArgumentParser(
description="Add sensitivty cubes to HDF5 container",
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
parser.add_argument(
"--regex",
default=".*(2[0-9]{7}v[0-9]{3})_[0-9]{3}_([0-9]{3})",
help="""Regex with two capture groups, the first for datevshot the second
for IFU slot""",
)
parser.add_argument("--append", action="store_true", help="Append to existing HDF5")
parser.add_argument(
"--alpha", type=float, help="Alpha for Fleming function", default=-3.5
)
parser.add_argument(
"fits_files",
type=str,
nargs="+",
help="Files to add, filename must follow convention set out in --regex option",
)
parser.add_argument("hdf5_out", type=str, help="HDF5 container to add to")
opts = parser.parse_args(args=args)
if opts.append:
hdfcont = SensitivityCubeHDF5Container(opts.hdf5_out, mode="a")
else:
hdfcont = SensitivityCubeHDF5Container(opts.hdf5_out, mode="w")
# Compile the regex so it's faster
regex = compile(opts.regex)
for fn in opts.fits_files:
m = regex.match(fn)
datevshot = m.group(1)
ifuslot = m.group(2)
_logger.info(
"Inserting {:s} with dateshot {:s} and IFU slot {:s}".format(
fn, datevshot, ifuslot
)
)
scube = SensitivityCube.from_file(
fn, [3500.0, 5500.0], [opts.alpha, opts.alpha]
)
hdfcont.add_sensitivity_cube("virus_" + datevshot, "ifuslot_" + ifuslot, scube)
hdfcont.close()
def collapse_datacubes_command(args=None):
"""
Produce combined flux limit versus
wavelength estimates for sensitivity
cubes passed on command line
"""
import argparse
# Command line options
parser = argparse.ArgumentParser(description="""
Collapse the RA and DEC of a single or
set of sensitivity cube(s) to
produce one file of 50% flux limit versus
wavelength.
""")
parser.add_argument("--plot",
type=str,
help="Filename for optional plot",
default="")
parser.add_argument(
"--fmin",
help="Minimum flux to consider when interpolating for 50% limit",
type=float,
default=1e-17)
parser.add_argument(
"--fmax",
help="""Maximum flux to consider when interpolating for 50% limit.
Regions not 99% at this flux ignored!""",
type=float,
default=1e-15)
parser.add_argument(
"--nbins",
help=
"Number of flux bin to use when interpolating to measure 50% limit",
type=int,
default=100)
parser.add_argument(
"--alpha",
help="The alpha of the Fleming function fit (default=-3.5)",
default=-3.5,
type=float)
parser.add_argument(
"scubes",
nargs='+',
help="The sensitivity cube(s) you want to collapse and combine")
parser.add_argument("output", help="(Ascii) file to output to", type=str)
opts = parser.parse_args(args=args)
# Stores a list of the completeness versus flux and lambda for
# all the cubes
compl_cube_list = []
# Flux bins to compute completeness in
fluxes = linspace(opts.fmin, opts.fmax, opts.nbins)
# A list of the number of good pixels in each cube as
# a function of wavelength
npixes_list = []
for cube_name in opts.scubes:
# Currently fix the alpha versus wavelength
tscube = SensitivityCube.from_file(cube_name, [3500.0, 5500.0],
[opts.alpha, opts.alpha])
lambda_, npix, compls = return_spatially_collapsed_cube(tscube, fluxes)
compl_cube_list.append(compls)
npixes_list.append(npix)
# Produce a combined cube of completness versus flux and lambda,
# weighted by the number of good pixels in each cube
combined_cube = compl_cube_list[0] * npixes_list[0]
for npix, compl_cube in zip(npixes_list[1:], compl_cube_list[1:]):
combined_cube += npix * compl_cube
# This should give the correct completeness versus lambda and flux, ignoring empty pixels
combined_cube /= sum(array(npixes_list), axis=0)
# This should give is the 50% flux limits and the new alpha values
f50vals, alphas = compute_new_fleming_fits(lambda_, fluxes, combined_cube)
if opts.plot:
plot_collapsed_cube(f50vals, alphas, lambda_, fluxes, combined_cube,
opts.plot)
# Write out
table = Table([lambda_, f50vals, alphas],
names=["wavelength", "f50", "alpha"])
table.write(opts.output, format="ascii")