def reduce_crosscans(map_name, lowhigh='high'):
make_apex_cubes.build_cube_2014(map_name,
lowhigh=lowhigh,
posang=[50,70],
datasets=[x
for x,y in make_apex_cubes.datasets_2014.items()
if map_name in y],
extra_suffix='_lscans')
make_apex_cubes.build_cube_2014(map_name,
lowhigh=lowhigh,
posang=[140,160],
datasets=[x
for x,y in make_apex_cubes.datasets_2014.items()
if map_name in y],
extra_suffix='_bscans')
fileb = os.path.join(outdir,
'APEX_H2CO_2014_{0}_{1}_bscans.fits'.format(map_name,
lowhigh))
filel = os.path.join(outdir,
'APEX_H2CO_2014_{0}_{1}_lscans.fits'.format(map_name,
lowhigh))
cubeb = fits.getdata(fileb)
cubel = fits.getdata(filel)
assert cubeb.shape == cubel.shape
cube_comb = plait.plait_cube([cubeb,cubel], angles=[0, 90], scale=3)
header = fits.getheader(fileb)
hdu = fits.PrimaryHDU(data=cube_comb, header=header)
hdu.writeto(os.path.join(outdir, '{0}_{1}_plait.fits'.format(map_name, lowhigh)),
clobber=True)
def reduce_all_cubes_for_map(mapname, lowhigh='high', **kwargs):
for dataset,maps in make_apex_cubes.datasets_2014.items():
if mapname in maps:
date = dataset[-10:]
both_directions = True
try:
make_apex_cubes.build_cube_2014(mapname,
lowhigh=lowhigh,
posang=[50,70],
datasets=[dataset],
extra_suffix='_cal{0}_lscans'.format(date),
**kwargs)
except IndexError:
both_directions = False
try:
make_apex_cubes.build_cube_2014(mapname,
lowhigh=lowhigh,
posang=[140,160],
datasets=[dataset],
extra_suffix='_cal{0}_bscans'.format(date),
**kwargs)
except IndexError:
both_directions = False
if both_directions:
fileb = os.path.join(outdir, 'APEX_H2CO_2014_{1}_{2}_cal{0}_bscans.fits'.format(date, mapname, lowhigh))
filel = os.path.join(outdir, 'APEX_H2CO_2014_{1}_{2}_cal{0}_lscans.fits'.format(date, mapname, lowhigh))
cubeb = fits.getdata(fileb)
cubel = fits.getdata(filel)
if cubeb.shape != cubel.shape:
header = FITS_tools.fits_overlap(fileb, filel)
hdb = fits.getheader(fileb)
# Add back 3rd dimension... HACK
for key in hdb:
if key[0] == 'C' and key.strip()[-1] == '3':
header[key] = hdb[key]
FITS_tools.regrid_fits_cube(fileb, outheader=header, outfilename=fileb, clobber=True)
FITS_tools.regrid_fits_cube(filel, outheader=header, outfilename=filel, clobber=True)
cubeb = fits.getdata(fileb)
cubel = fits.getdata(filel)
if cubeb.shape != cubel.shape:
log.fatal("Cube shapes don't match: {0}, {1}".format(cubeb.shape,cubel.shape))
raise ValueError
cube_comb = plait.plait_cube([cubeb,cubel], angles=[0, 90], scale=5)
cube_comb_naive = (cubeb+cubel)/2.
header = fits.getheader(fileb)
fits.PrimaryHDU(data=cube_comb,
header=header).writeto(os.path.join(outdir, '{1}_{2}_cal{0}_plait.fits'.format(date, mapname, lowhigh)),
clobber=True)
def reduce_all_cubes_for_map(mapname, lowhigh='high', **kwargs):
for dataset, maps in make_apex_cubes.datasets_2014.items():
if mapname in maps:
date = dataset[-10:]
both_directions = True
try:
make_apex_cubes.build_cube_2014(
mapname,
lowhigh=lowhigh,
posang=[50, 70],
datasets=[dataset],
extra_suffix='_cal{0}_lscans'.format(date),
**kwargs)
except IndexError:
both_directions = False
try:
make_apex_cubes.build_cube_2014(
mapname,
lowhigh=lowhigh,
posang=[140, 160],
datasets=[dataset],
extra_suffix='_cal{0}_bscans'.format(date),
**kwargs)
except IndexError:
both_directions = False
if both_directions:
fileb = os.path.join(
outdir, 'APEX_H2CO_2014_{1}_{2}_cal{0}_bscans.fits'.format(
date, mapname, lowhigh))
filel = os.path.join(
outdir, 'APEX_H2CO_2014_{1}_{2}_cal{0}_lscans.fits'.format(
date, mapname, lowhigh))
cubeb = fits.getdata(fileb)
cubel = fits.getdata(filel)
if cubeb.shape != cubel.shape:
header = FITS_tools.fits_overlap(fileb, filel)
hdb = fits.getheader(fileb)
# Add back 3rd dimension... HACK
for key in hdb:
if key[0] == 'C' and key.strip()[-1] == '3':
header[key] = hdb[key]
FITS_tools.regrid_fits_cube(fileb,
outheader=header,
outfilename=fileb,
clobber=True)
FITS_tools.regrid_fits_cube(filel,
outheader=header,
outfilename=filel,
clobber=True)
cubeb = fits.getdata(fileb)
cubel = fits.getdata(filel)
if cubeb.shape != cubel.shape:
log.fatal("Cube shapes don't match: {0}, {1}".format(
cubeb.shape, cubel.shape))
raise ValueError
cube_comb = plait.plait_cube([cubeb, cubel],
angles=[0, 90],
scale=5)
cube_comb_naive = (cubeb + cubel) / 2.
header = fits.getheader(fileb)
fits.PrimaryHDU(data=cube_comb,
header=header).writeto(os.path.join(
outdir, '{1}_{2}_cal{0}_plait.fits'.format(
date, mapname, lowhigh)),
clobber=True)
'MAP_003',
lowhigh='high',
posang=[140, 160],
datasets=[
x for x, y in make_apex_cubes.datasets_2014.items() if 'MAP_003' in y
],
extra_suffix='_bscans')
fileb = os.path.join(outdir, 'APEX_H2CO_2014_MAP_003_high_bscans.fits')
filel = os.path.join(outdir, 'APEX_H2CO_2014_MAP_003_high_lscans.fits')
cubeb = fits.getdata(fileb)
cubel = fits.getdata(filel)
assert cubeb.shape == cubel.shape
cube_comb = plait.plait_cube([cubeb, cubel], angles=[0, 90], scale=5)
cube_comb_naive = (cubeb + cubel) / 2.
header = fits.getheader(fileb)
fits.PrimaryHDU(data=cube_comb,
header=header).writeto(os.path.join('MAP_003_high_plait.fits'),
clobber=True)
fits.PrimaryHDU(data=cube_comb_naive,
header=header).writeto(os.path.join(outdir,
'MAP_003_high_naive.fits'),
clobber=True)
fits.PrimaryHDU(data=cube_comb_naive - cube_comb,
header=header).writeto(os.path.join(outdir,
'MAP_003_high_diff.fits'),
clobber=True)
paths.april2014path,
'APEX_H2CO_2014_MAP_006_{0}_cal2014-05-30_lscans.fits'.format(
lowhigh)))
cube730b = fits.getdata(
os.path.join(
paths.april2014path,
'APEX_H2CO_2014_MAP_006_{0}_cal2014-07-31_bscans.fits'.format(
lowhigh)))
cube730l = fits.getdata(
os.path.join(
paths.april2014path,
'APEX_H2CO_2014_MAP_006_{0}_cal2014-07-30_lscans.fits'.format(
lowhigh)))
cube730comb = plait.plait_cube([cube730b, cube730l],
angles=[0, 90],
scale=5)
cube530comb = plait.plait_cube([cube530b, cube530l],
angles=[0, 90],
scale=5)
import pylab as pl
fig2 = pl.figure(2)
fig2.clf()
ax2 = fig2.gca()
ax2.grid()
data = []
for threshold in np.logspace(-0.6, 1.1, 10):
mask = (cube530comb > threshold) & (cube730comb > threshold)
if not np.any(mask):
make_apex_cubes.build_cube_2014('MAP_003',
lowhigh='high',
posang=[140,160],
datasets=[x
for x,y in make_apex_cubes.datasets_2014.items()
if 'MAP_003' in y],
extra_suffix='_bscans')
fileb = os.path.join(outdir, 'APEX_H2CO_2014_MAP_003_high_bscans.fits')
filel = os.path.join(outdir, 'APEX_H2CO_2014_MAP_003_high_lscans.fits')
cubeb = fits.getdata(fileb)
cubel = fits.getdata(filel)
assert cubeb.shape == cubel.shape
cube_comb = plait.plait_cube([cubeb,cubel], angles=[0, 90], scale=5)
cube_comb_naive = (cubeb+cubel)/2.
header = fits.getheader(fileb)
fits.PrimaryHDU(data=cube_comb, header=header).writeto(os.path.join('MAP_003_high_plait.fits'), clobber=True)
fits.PrimaryHDU(data=cube_comb_naive, header=header).writeto(os.path.join(outdir, 'MAP_003_high_naive.fits'), clobber=True)
fits.PrimaryHDU(data=cube_comb_naive-cube_comb, header=header).writeto(os.path.join(outdir, 'MAP_003_high_diff.fits'), clobber=True)
import pylab as pl
pl.figure(1, figsize=(12,12))
pl.clf()
for ii,scale in enumerate((1,5,10)):
cube_comb = plait.plait_cube([cubeb,cubel], angles=[0, 90], scale=scale)
integ_plait = cube_comb[900:990,:,:].mean(axis=0)
integ_naive = cube_comb_naive[900:990,:,:].mean(axis=0)
integ_plait = cube_comb[2515:2605,:,:].mean(axis=0)
hd = fits.getheader(fn1)
# Add back 3rd dimension... HACK
for key in hd:
if key[0] == 'C' and key.strip()[-1] == '3':
header[key] = hd[key]
for fn in files:
FITS_tools.regrid_fits_cube(fn, outheader=header, outfilename=fn, clobber=True)
cube530b = fits.getdata(os.path.join(paths.april2014path, 'APEX_H2CO_2014_MAP_006_{0}_cal2014-05-30_bscans.fits'.format(lowhigh)))
cube530l = fits.getdata(os.path.join(paths.april2014path, 'APEX_H2CO_2014_MAP_006_{0}_cal2014-05-30_lscans.fits'.format(lowhigh)))
cube730b = fits.getdata(os.path.join(paths.april2014path, 'APEX_H2CO_2014_MAP_006_{0}_cal2014-07-31_bscans.fits'.format(lowhigh)))
cube730l = fits.getdata(os.path.join(paths.april2014path, 'APEX_H2CO_2014_MAP_006_{0}_cal2014-07-30_lscans.fits'.format(lowhigh)))
cube730comb = plait.plait_cube([cube730b,cube730l], angles=[0, 90], scale=5)
cube530comb = plait.plait_cube([cube530b,cube530l], angles=[0, 90], scale=5)
import pylab as pl
fig2 = pl.figure(2)
fig2.clf()
ax2 = fig2.gca()
ax2.grid()
data = []
for threshold in np.logspace(-0.6,1.1,10):
mask = (cube530comb>threshold)&(cube730comb>threshold)
if not np.any(mask):
log.info("Skip threshold {0} for {1} because no data".format(threshold, lowhigh))
continue
