def retile(ipathfmt, opathfmt, itile1=(None,None), itile2=(None,None),
otileoff=(0,0), otilenum=(None,None), ocorner=(-np.pi/2,-np.pi),
otilesize=(675,675), comm=None, verbose=False, slice=None):
"""Given a set of tiles on disk with locations ipathfmt % {"y":...,"x":...},
retile them into a new tiling and write the result to opathfmt % {"y":...,"x":...}.
The new tiling will have tile size given by otilesize[2]. Negative size means the
tiling will to down/left instead of up/right. The corner of the tiling will
be at sky coordinates ocorner[2] in radians. The new tiling will be pixel-
compatible with the input tiling - w.g. the wcs will only differ by crpix.
The output tiling will logically cover the whole sky, but only output tiles
that overlap with input tiles will actually be written. This can be modified
by using otileoff[2] and otilenum[2]. otileoff gives the tile indices of the
corner tile, while otilenum indicates the number of tiles to write."""
# Set up mpi
rank, size = (comm.rank, comm.size) if comm is not None else (0, 1)
# Expand any scalars
otilesize = np.zeros(2,int)+otilesize
otileoff = np.zeros(2,int)+otileoff
# Find the range of input tiles
itile1, itile2 = find_tile_range(ipathfmt, itile1, itile2)
# To fill in the rest of the information we need to know more
# about the input tiling, so read the first tile
ibase = enmap.read_map(ipathfmt % {"y":itile1[0],"x":itile1[1]})
if slice: ibase = eval("ibase"+slice)
itilesize = ibase.shape[-2:]
# Find the pixel position of our output corners according to the wcs.
# This is the last place we need to do a coordinate transformation.
# All the rest can be done in pure pixel logic.
pixoff = np.round(ibase.sky2pix(ocorner)).astype(int)
# Find the range of output tiles
def pix2otile(pix, ioff, osize): return (pix-ioff)/osize
otile1 = pix2otile(itile1*itilesize, pixoff, otilesize)
otile2 = pix2otile(itile2*itilesize-1, pixoff, otilesize)
otile1, otile2 = np.minimum(otile1,otile2), np.maximum(otile1,otile2)
otile2 += 1
# We can now loop over output tiles
cache = [None,None,None]
oyx = [(oy,ox) for oy in range(otile1[0],otile2[0]) for ox in range(otile1[1],otile2[1])]
for i in range(rank, len(oyx), size):
otile = np.array(oyx[i])
# Find out which input tiles overlap with this output tile.
# Our tile stretches from opix1:opix2 relative to the global input pixels
opix1 = otile*otilesize + pixoff
opix2 = (otile+1)*otilesize + pixoff
# output tiles and input tiles may increase in opposite directions
opix1, opix2 = np.minimum(opix1,opix2), np.maximum(opix1,opix2)
try: omap = read_area(ipathfmt, [opix1,opix2],itile1=itile1, itile2=itile2,cache=cache, slice=slice)
except IOError: continue
oname = opathfmt % {"y":otile[0]+otileoff[0],"x":otile[1]+otileoff[1]}
utils.mkdir(os.path.dirname(oname))
enmap.write_map(oname, omap)
if verbose: print oname
def write_map(name, map, ext="fits", merged=True):
if not merged:
# Write as individual tiles in directory of the specified name
utils.mkdir(name)
for pos, tile in zip(map.loc_pos, map.tiles):
enmap.write_map(
name + "/tile%03d_%03d.%s" % (tuple(pos) + (ext, )), tile)
else:
# Write to a single file. This currently creates the full map
# in memory while writing. It is unclear how to avoid this
# without bypassing pyfits or becoming super-slow.
if map.comm.rank == 0:
canvas = enmap.zeros(map.shape, map.wcs, map.dtype)
else:
canvas = None
dmap2enmap(map, canvas)
if map.comm.rank == 0:
enmap.write_map(name, canvas)
parser.add_argument("-v", "--verbose", action="store_true")
parser.add_argument("-W", "--wiener", action="store_true")
parser.add_argument("-m", "--mask", type=str, default=None)
parser.add_argument("--filter-mode", type=str, default="weight")
parser.add_argument("--cg-tol", type=float, default=1e-4)
parser.add_argument("--detrend", type=int, default=1)
args = parser.parse_args()
config = jointmap.read_config(args.config)
mapinfo = jointmap.Mapset(config, args.sel)
tsize = args.tsize # pixels
pad = args.pad # pixels
dtype = np.float64
ncomp = args.ncomp
comm = mpi.COMM_WORLD
utils.mkdir(args.odir)
# Get the set of bounding boxes, after normalizing them
boxes = np.sort(np.array([d.box for d in mapinfo.datasets]), -2)
# Read the cmb power spectrum, which is an effective noise
# component. T-only
#cl_path = os.path.join(os.path.dirname(args.config),config.cl_background)
#cl_bg = powspec.read_spectrum(cl_path)[0,0]
def overlaps_any(box, refboxes):
rdec, rra = utils.moveaxis(refboxes - box[0, :], 2, 0)
wdec, wra = np.abs(box[1] - box[0])
rra -= np.floor(rra[:, 0, None] / (2 * np.pi) + 0.5) * (2 * np.pi)
for i in range(-1, 2):
parser.add_argument("-p", "--pad", type=int, default=240)
parser.add_argument("-C", "--ncomp", type=int, default=3)
parser.add_argument("-B", "--obeam", type=str, default=None)
parser.add_argument("-c", "--cont", action="store_true")
parser.add_argument("-v", "--verbose", action="store_true")
parser.add_argument("--filter-mode", type=str, default="weight")
args = parser.parse_args()
config = jointmap.read_config(args.config)
mapinfo = jointmap.Mapset(config, args.sel)
tsize = args.tsize # pixels
pad = args.pad # pixels
dtype = np.float64
ncomp = args.ncomp
comm = mpi.COMM_WORLD
utils.mkdir(args.odir)
# Get the set of bounding boxes, after normalizing them
boxes = np.sort(np.array([d.box for d in mapinfo.datasets]),-2)
# Read the cmb power spectrum, which is an effective noise
# component. T-only
#cl_path = os.path.join(os.path.dirname(args.config),config.cl_background)
#cl_bg = powspec.read_spectrum(cl_path)[0,0]
def overlaps_any(box, refboxes):
rdec, rra = utils.moveaxis(refboxes - box[0,:], 2,0)
wdec, wra = np.abs(box[1] - box[0])
rra -= np.floor(rra[:,0,None]/(2*np.pi)+0.5)*(2*np.pi)
for i in range(-1,2):
nra = rra + i*(2*np.pi)
comm = mpi.COMM_WORLD
myid = comm.rank
nproc = comm.size
filedb.init()
db = filedb.data
filelist = todinfo.get_tods(args.filelist, filedb.scans)
def compress_beam(sigma, phi):
c,s=np.cos(phi),np.sin(phi)
R = np.array([[c,-s],[s,c]])
C = np.diag(sigma**-2)
C = R.dot(C).dot(R.T)
return np.array([C[0,0],C[1,1],C[0,1]])
utils.mkdir(args.odir)
# Dump our settings
if myid == 0:
config.save(args.odir + "/config.txt")
with open(args.odir + "/args.txt","w") as f:
f.write(" ".join([pipes.quote(a) for a in sys.argv[1:]]) + "\n")
with open(args.odir + "/env.txt","w") as f:
for k,v in os.environ.items():
f.write("%s: %s\n" %(k,v))
with open(args.odir + "/ids.txt","w") as f:
for id in filelist:
f.write("%s\n" % id)
shutil.copyfile(filedb.cjoin(["root","dataset","filedb"]), args.odir + "/filedb.txt")
try: shutil.copyfile(filedb.cjoin(["root","dataset","todinfo"]), args.odir + "/todinfo.txt")
except (IOError, OSError): pass
# Set up logging
ids = ids[inds]
ifiles = [ifiles[ind] for ind in inds]
# Look for duplicates
dups = np.where(ids[1:]==ids[:-1])[0]
if len(dups) > 0:
# Get the first example
if comm.rank == 0:
print "Duplicate ids in input: " + ", ".join([ifiles[dups[0]],ifiles[dups[1]]])
comm.Finalize()
sys.exit(1)
nfile = len(ifiles)
# Make tmp directory for output
tmpdir = args.ofile + ".tmp"
tmpfmt = tmpdir + "/cut%03d.hdf"
utils.mkdir(tmpdir)
# Process each of our blocks
with h5py.File(tmpfmt % comm.rank, "w") as hfile:
for j, i in enumerate(range(comm.rank*nfile/comm.size, (comm.rank+1)*nfile/comm.size)):
ifile, id = ifiles[i], ids[i]
progress = min(comm.rank + j*comm.size, nfile-1)
print "%5d/%d %5.1f%% %s" % (progress+1, nfile, 100.0*(progress+1)/nfile, id)
dets, gain = files.read_gain(ifile)
dtype = [("det_uid","i"),("cal","f")]
res = np.zeros(len(dets),dtype)
res["det_uid"] = dets
res["cal"] = gain
hfile[id] = res
# Then concatenate them into the final file
def combine_tiles(ipathfmt,
opathfmt,
combine=2,
downsample=2,
itile1=(None, None),
itile2=(None, None),
tyflip=False,
txflip=False,
pad_to=None,
comm=None,
verbose=False):
"""Given a set of tiles on disk at locaiton ipathfmt % {"y":...,"x"...},
combine them into larger tiles, downsample and write the result to
opathfmt % {"y":...,"x":...}. x and y must be contiguous and start at 0.
reftile[2] indicates the tile coordinates of the first valid input tile.
This needs to be specified if not all tiles of the logical tiling are
physically present.
tyflip and txflip indicate if the tiles coordinate system is reversed
relative to the pixel coordinates or not."
"""
# Expand combine and downsample to 2d
combine = np.zeros(2, int) + combine
downsample = np.zeros(2, int) + downsample
if pad_to is not None:
pad_to = np.zeros(2, int) + pad_to
# Handle optional mpi
rank, size = (comm.rank, comm.size) if comm is not None else (0, 1)
# Find the range of input tiles
itile1, itile2 = find_tile_range(ipathfmt, itile1, itile2)
# Read the first tile to get its size information
ibase = enmap.read_map(ipathfmt % {"y": itile1[0], "x": itile1[1]}) * 0
# Find the set of output tiles we need to consider
otile1 = itile1 / combine
otile2 = (itile2 - 1) / combine + 1
# And loop over them
oyx = [(oy, ox) for oy in range(otile1[0], otile2[0])
for ox in range(otile1[1], otile2[1])]
for i in range(rank, len(oyx), size):
oy, ox = oyx[i]
# Read in all associated tiles into a list of lists
rows = []
for dy in range(combine[0]):
iy = oy * combine[0] + dy
if iy >= itile2[0]: continue
cols = []
for dx in range(combine[1]):
ix = ox * combine[1] + dx
if ix >= itile2[1]: continue
if iy < itile1[0] or ix < itile1[1]:
# The first tiles are missing on disk, but are
# logically a part of the tiling. Use ibase,
# which has been zeroed out.
cols.append(ibase)
else:
itname = ipathfmt % {"y": iy, "x": ix}
cols.append(enmap.read_map(itname))
if txflip: cols = cols[::-1]
rows.append(cols)
# Stack them next to each other into a big tile
if tyflip: rows = rows[::-1]
omap = enmap.tile_maps(rows)
# Downgrade if necessary
if np.any(downsample > 1):
omap = enmap.downgrade(omap, downsample)
if pad_to is not None:
# Padding happens towards the end of the tiling,
# which depends on the flip status
padding = np.array(
[[0, 0],
[pad_to[0] - omap.shape[-2], pad_to[1] - omap.shape[-1]]])
if tyflip: padding[:, 0] = padding[::-1, 0]
if txflip: padding[:, 1] = padding[::-1, 1]
omap = enmap.pad(omap, padding)
# And output
otname = opathfmt % {"y": oy, "x": ox}
utils.mkdir(os.path.dirname(otname))
enmap.write_map(otname, omap)
if verbose: print otname
parser.add_argument("-c", "--cont", action="store_true")
parser.add_argument("-P", "--npass", type=int, default=3)
parser.add_argument("--output-full-model", action="store_true")
args = parser.parse_args()
config = jointmap.read_config(args.config)
mapinfo = jointmap.Mapset(config, args.sel)
tsize = args.tsize # pixels
pad = args.pad # pixels
dtype = np.float64
ncomp = 1
comm = mpi.COMM_WORLD
signals = args.signals.split(",")
verbosity = args.verbose - args.quiet
highpass_alpha = 3
utils.mkdir(args.odir)
debug_tile = None if args.debug_tile is None else [int(w) for w in args.debug_tile.split(",")]
# Get the set of bounding boxes, after normalizing them
boxes = np.sort(np.array([d.box for d in mapinfo.datasets]),-2)
# Read the cmb power spectrum, which is an effective noise
# component. T-only
cl_path = os.path.join(os.path.dirname(args.config),config.cl_background)
cl_bg = powspec.read_spectrum(cl_path)[0,0]
# Read our mask. High-resolution and per-dataset masks would be handled otherwise.
# This approach only works for low-resolution masks
if config.mask_mode == "none": mask = None
elif config.mask_mode == "lowres":
if args.verbose: print("Writing %s" % ohit)
enmap.write_map(ohit, w)
# Two cases: Normal enmaps or dmaps
if not os.path.isdir(imaps[0]):
# Normal monotlithic map
coadd_maps(imaps,
ihits,
args.omap,
args.ohit,
cont=args.cont,
ncomp=args.ncomp)
else:
# Dmap. Each name is actually a directory, but they
# all have compatible tile names.
tilenames = get_tilenames(imaps[0])
utils.mkdir(args.omap)
utils.mkdir(args.ohit)
for tilename in tilenames[comm.rank::comm.size]:
timaps = ["%s/%s" % (imap, tilename) for imap in imaps]
tihits = ["%s/%s" % (ihit, tilename) for ihit in ihits]
print("%3d %s" % (comm.rank, tilename))
coadd_maps(timaps,
tihits,
args.omap + "/" + tilename,
args.ohit + "/" + tilename,
cont=args.cont,
ncomp=args.ncomp)
if args.verbose: print("Done")
res = a.copy()
res[np.isnan(res)] = 0
return res
def add_maps(imaps, omap):
if args.verbose: print "Reading %s" % imaps[0]
m = nonan(enmap.read_map(imaps[0]))*scales[0]
for scale, mif in zip(scales[1:],imaps[1:]):
if args.verbose: print "Reading %s" % mif
m += nonan(enmap.read_map(mif))*scale
if args.mean: m /= len(imaps)
if args.verbose: "Writing %s" % omap
enmap.write_map(omap, m)
def get_tilenames(dir):
return sorted([name for name in os.listdir(dir) if name.endswith(".fits") or name.endswith(".hdf")])
# Two cases: Normal enmaps or dmaps
if not os.path.isdir(args.imaps[0]):
# Normal monotlithic map
if comm.rank == 0:
add_maps(args.imaps, args.omap)
else:
# Dmap. Each name is actually a directory, but they
# all have compatible tile names.
tilenames = get_tilenames(args.imaps[0])
utils.mkdir(args.omap)
for tilename in tilenames[comm.rank::comm.size]:
timaps = ["%s/%s" % (imap,tilename) for imap in args.imaps]
print "%3d %s" % (comm.rank, tilename)
add_maps(timaps, args.omap + "/" + tilename)
if args.verbose: print"Done"
parser.add_argument("ofile")
parser.add_argument("-d", "--dets", type=str, default=None)
parser.add_argument("-D", "--absdets", type=str, default=None)
parser.add_argument("-c", "--calib", action="store_true")
parser.add_argument("-C", "--manual-calib", type=str, default=None)
parser.add_argument("--bin", type=int, default=1)
parser.add_argument("--nofft", action="store_true")
parser.add_argument("--nodeslope", action="store_true")
parser.add_argument("-F", "--fields", type=str, default=None)
args = parser.parse_args()
filedb.init()
ids = filedb.scans[args.query]
if len(ids) > 1:
# Will process multiple files
utils.mkdir(args.ofile)
for id in ids:
print id
entry = filedb.data[id]
subdets = None
absdets = None
if args.absdets is not None:
absdets = [int(w) for w in args.absdets.split(",")]
elif args.dets is not None:
subdets = [int(w) for w in args.dets.split(",")]
fields = ["gain","tconst","cut","tod","boresight"]
if args.fields: fields = args.fields.split(",")
d = actdata.read(entry, fields=fields)
if absdets: d.restrict(dets=absdets)
if subdets: d.restrict(dets=d.dets[subdets])
return 2 * h * nu**3 / c**2 / (np.exp(h * nu / k / T) - 1)
def uK2mJ(amp, b1, b2):
T0 = 2.73
nu = 148e9
dB = B(T0 + amp * 1e-6, nu) - B(T0, nu)
return dB * 2 * np.pi * b1 * b2 / 1e-29
def output_dummy(id):
with open(args.odir + "/samps%03d.txt" % id, "w") as ofile:
pass
utils.mkdir(args.odir)
if args.nmax > 0: groups = groups[:args.nmax]
for i in range(myid, len(groups), nproc):
if i < args.i: continue
group = groups[i]
if args.cont:
# If all our members are done, skip to next group
try:
lens = [
len(np.loadtxt(args.odir + "/samps%03d.txt" % j))
for j in group
]
if np.min(lens) >= args.nsamp:
continue
res["amplim"] = config.get("src_handling_lim")
res["srcs"] = None
srcfile = config.get("src_handling_list")
if srcfile:
res["srcs"] = pointsrcs.read(srcfile)
return res
src_handling = parse_src_handling()
filedb.init()
db = filedb.data
filelist = todinfo.get_tods(args.filelist, filedb.scans)
if args.group_tods:
filelist = scanutils.get_tod_groups(filelist)
utils.mkdir(args.odir)
root = args.odir + "/" + (args.prefix + "_" if args.prefix else "")
# Dump our settings
if comm.rank == 0:
config.save(root + "config.txt")
with open(root + "args.txt","w") as f:
argstring = " ".join([pipes.quote(a) for a in sys.argv[1:]])
f.write(argstring + "\n")
print argstring
with open(root + "env.txt","w") as f:
for k,v in os.environ.items():
f.write("%s: %s\n" %(k,v))
with open(root + "ids.txt","w") as f:
for id in filelist:
f.write("%s\n" % str(id))
parser.add_argument("-S", "--corr-spacing", type=float, default=2)
parser.add_argument("--srcsub", type=int, default=1)
parser.add_argument("-M", "--mapsub", type=str, default=None)
parser.add_argument("-I", "--inject", type=str, default=None)
parser.add_argument("--only", type=str)
parser.add_argument("--static", action="store_true")
parser.add_argument("-c", "--cont", action="store_true")
parser.add_argument("-D", "--dayerr", type=str, default="-1:1,-2:4")
parser.add_argument("--srclim-day", type=float, default=50)
# These should ideally be moved into the general tod autocuts
parser.add_argument("-a", "--asteroid-file", type=str, default=None)
parser.add_argument("--asteroid-list", type=str, default=None)
args = parser.parse_args()
comm = mpi.COMM_WORLD
utils.mkdir(args.odir)
shape, wcs = enmap.read_map_geometry(args.area)
wshape = (3, ) + shape[-2:]
dtype = np.float32 if config.get("map_bits") == 32 else np.float64
root = args.odir + "/" + (args.prefix + "_" if args.prefix else "")
sys = config.get("map_sys")
ym = utils.arcmin / utils.yr2days
# Bias source amplitudes 0.1% towards their fiducial value
amp_prior = 1e-3
dayerr = np.array([[float(w) for w in tok.split(":")]
for tok in args.dayerr.split(",")
]).T # [[x1,y1],[x2,y2]]
only = [int(word) for word in args.only.split(",")] if args.only else []
parser.add_argument("--demode", action="store_true")
parser.add_argument("--decommon", action="store_true")
parser.add_argument("-c", "--cont", action="store_true")
args = parser.parse_args()
filedb.init()
comm_world = mpi.COMM_WORLD
comm_group = comm_world.Split(comm_world.rank%args.nsub, comm_world.rank/args.nsub)
comm_sub = comm_world.Split(comm_world.rank/args.nsub, comm_world.rank%args.nsub)
ids = todinfo.get_tods(args.sel, filedb.scans)
tol = args.tol*utils.arcmin
daz = args.daz*utils.arcmin
dtype = np.float32 if config.get("map_bits") == 32 else np.float64
tods_per_map = args.group
utils.mkdir(args.odir)
root = args.odir + "/" + (args.prefix + "_" if args.prefix else "")
# Set up logging
utils.mkdir(root + "log")
logfile = root + "log/log%03d.txt" % comm_world.rank
log_level = log.verbosity2level(config.get("verbosity"))
L = log.init(level=log_level, file=logfile, rank=comm_world.rank, shared=False)
# Run through all tods to determine the scanning patterns
L.info("Detecting scanning patterns")
boxes = np.zeros([len(ids),2,2])
for ind in range(comm_world.rank, len(ids), comm_world.size):
id = ids[ind]
entry = filedb.data[id]
try:
d = actdata.read(entry, ["boresight","tconst","cut","cut_noiseest"])
ifiles = [ifiles[ind] for ind in inds]
# Look for duplicates
dups = np.where(ids[1:] == ids[:-1])[0]
if len(dups) > 0:
# Get the first example
if comm.rank == 0:
print "Duplicate ids in input: " + ", ".join(
[ifiles[dups[0]], ifiles[dups[1]]])
comm.Finalize()
sys.exit(1)
nfile = len(ifiles)
# Make tmp directory for output
tmpdir = args.ofile + ".tmp"
tmpfmt = tmpdir + "/cut%03d.hdf"
utils.mkdir(tmpdir)
# Process each of our blocks
with h5py.File(tmpfmt % comm.rank, "w") as hfile:
for j, i in enumerate(
range(comm.rank * nfile / comm.size,
(comm.rank + 1) * nfile / comm.size)):
ifile, id = ifiles[i], ids[i]
progress = min(comm.rank + j * comm.size, nfile - 1)
print "%5d/%d %5.1f%% %s" % (progress + 1, nfile, 100.0 *
(progress + 1) / nfile, id)
dets, gain = files.read_gain(ifile)
dtype = [("det_uid", "i"), ("cal", "f")]
res = np.zeros(len(dets), dtype)
res["det_uid"] = dets
res["cal"] = gain
def output(res, dir):
utils.mkdir(dir)
for i, (tqu, teb, desc) in enumerate(zip(res.tqu, res.teb, res.desc)):
enmap.write_map("%s/%02d_%s_tqu.hdf" % (dir,i+1,desc), tqu)
enmap.write_map("%s/%02d_%s_teb.hdf" % (dir,i+1,desc), teb)
def mkoutdir(outdir):
if comm.Get_rank() == 0:
utils.mkdir(outdir)
parser.add_argument("--ndet", type=int, default=0)
args = parser.parse_args()
precon = config.get("map_precon")
dtype = np.float32 if config.get("map_bits") == 32 else np.float64
comm = mpi4py.MPI.COMM_WORLD
myid = comm.rank
nproc = comm.size
nmax = config.get("map_cg_nmax")
db = filedb.ACTFiles(config.get("filedb"))
filelist = todinfo.get_tods(args.filelist, config.get("todinfo"))
area = enmap.read_map(args.area)
area = enmap.zeros((args.ncomp, ) + area.shape[-2:], area.wcs, dtype)
utils.mkdir(args.odir)
root = args.odir + "/" + (args.prefix + "_" if args.prefix else "")
# Dump our settings
if myid == 0:
config.save(root + "config.txt")
with open(root + "args.txt", "w") as f:
f.write(" ".join([pipes.quote(a) for a in sys.argv[1:]]) + "\n")
with open(root + "env.txt", "w") as f:
for k, v in os.environ.items():
f.write("%s: %s\n" % (k, v))
with open(root + "ids.txt", "w") as f:
for id in filelist:
f.write("%s\n" % id)
shutil.copyfile(config.get("filedb"), root + "filedb.txt")
# Set up logging
def build_single(ifile, srcs, beam, ofile, mask_level=0, apod_size=16):
imap = enmap.read_map(ifile)
omap, oslice = pointsrcs.sim_srcs(imap.shape[-2:],
imap.wcs,
srcs,
beam,
return_padded=True)
if mask_level:
mask = omap > mask_level
omap = 1 - np.cos(
np.minimum(1,
ndimage.distance_transform_edt(1 - mask) / 16.0) *
np.pi)
omap = enmap.samewcs(omap, imap)
omap = omap[oslice]
enmap.write_map(ofile, omap)
if os.path.isdir(args.ifile):
utils.mkdir(args.ofile)
ifiles = sorted(glob.glob(args.ifile + "/tile*.fits"))[::-1]
for ind in range(comm.rank, len(ifiles), comm.size):
ifile = ifiles[ind]
print(ifile)
ofile = args.ofile + "/" + os.path.basename(ifile)
build_single(ifile, srcs, beam, ofile, args.mask, args.apod)
else:
print(args.ifile)
build_single(args.ifile, srcs, beam, args.ofile, args.mask, args.apod)
comm = mpi.COMM_WORLD
myid = comm.rank
nproc = comm.size
filedb.init()
db = filedb.data
filelist = todinfo.get_tods(args.filelist, filedb.scans)
def compress_beam(sigma, phi):
c,s=np.cos(phi),np.sin(phi)
R = np.array([[c,-s],[s,c]])
C = np.diag(sigma**-2)
C = R.dot(C).dot(R.T)
return np.array([C[0,0],C[1,1],C[0,1]])
utils.mkdir(args.odir)
# Dump our settings
if myid == 0:
config.save(args.odir + "/config.txt")
with open(args.odir + "/args.txt","w") as f:
f.write(" ".join([pipes.quote(a) for a in sys.argv[1:]]) + "\n")
with open(args.odir + "/env.txt","w") as f:
for k,v in os.environ.items():
f.write("%s: %s\n" %(k,v))
with open(args.odir + "/ids.txt","w") as f:
for id in filelist:
f.write("%s\n" % id)
shutil.copyfile(filedb.cjoin(["root","dataset","filedb"]), args.odir + "/filedb.txt")
try: shutil.copyfile(filedb.cjoin(["root","dataset","todinfo"]), args.odir + "/todinfo.txt")
except IOError: pass
# Set up logging
parser.add_argument(
"--max-sens",
type=float,
default=20,
help=
"Reject detectors more than this times more sensitive than the median at any of the indicated frequencies. Set to 0 to disable."
)
parser.add_argument("--full-stats", action="store_true")
args = parser.parse_args()
comm = mpi.COMM_WORLD
srate = 400.
fmax = srate / 2
ndet = 32 * 33
utils.mkdir(args.odir)
tmp = [[float(tok) for tok in word.split(":")] for word in args.f.split(",")]
bins = np.array([[t[0] - t[1] / 2, t[0] + t[1] / 2] for t in tmp])
rate = [float(w) for w in args.R.split(":")]
filedb.init()
ids = filedb.scans[args.sel]
ntod = len(ids)
cuts = np.zeros([ntod, ndet], dtype=np.uint8)
stats = None
if args.full_stats: stats = np.zeros([ntod, ndet, 4])
for si in range(comm.rank, ntod, comm.size):
try:
id = ids[si]
srcdata = np.array([ra*u.degree, dec*u.degree, amp, omg, phi, D])
# if only one source is specified, make sure it has a shape
# compatible with multiple sources
if len(srcdata.shape) == 1: srcdata = srcdata[:, None]
return srcdata
filedb.init()
db = filedb.scans.select(args.sel)
ids = db.ids
sys = args.sys
dtype = np.float32
verbose = args.verbose - args.quiet
down = config.get("downsample")
poly_pad = 3*u.degree
bounds = db.data["bounds"]
u.mkdir(args.odir)
# load source information
srcdata = read_srcs(args.catalog)
srcpos, amps, omg, phi, D = srcdata[:2], srcdata[2], srcdata[3], srcdata[4], srcdata[5]
if len(srcpos.shape) == 1: srcpos = srcpos[:,None]
# Which sources pass our requirements?
base_sids = set(range(amps.size))
if args.minamp is not None:
base_sids &= set(np.where(amps > args.minamp)[0])
if args.srcs is not None:
selected = [int(w) for w in args.srcs.split(",")]
base_sids &= set(selected)
base_sids = list(base_sids)
for ind in range(len(ids)):