Esempio n. 1
0
    files = glob(args.glob)
elif args.files:
    files = args.files
else:
    sys.exit("Must specify either --glob or --files")

#Because we are impatient and want to compute statistics before all the jobs are finished,
# there may be some directories that do not have a flatchains.hdf5 file
flatchainList = []
for file in files:
    try:
        # If we've specified HDF5, use h5read
        # If we've specified csv, use csvread
        root, ext = os.path.splitext(file)
        if ext == ".hdf5":
            flatchainList.append(utils.h5read(file, args.burn, args.thin))
        elif ext == ".csv":
            flatchainList.append(utils.csvread(file, args.burn, args.thin))
    except OSError as e:
        print("{} does not exist, skipping. Or error {}".format(file, e))

print("Using a total of {} flatchains".format(len(flatchainList)))

if args.cat:
    assert len(flatchainList) > 1, "If concatenating samples, must provide more than one flatchain"
    utils.cat_list(args.output, flatchainList)

# Assume that if we are using either args.chain, or args.triangle, we are only suppling one
# chain, since these commands don't make sense otherwise.
if args.chain:
    assert len(flatchainList) == 1, "If plotting Markov Chain, only specify one flatchain"
Esempio n. 2
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from Starfish import utils

# Determine all of the orders we will be fitting
spectra = Starfish.data["files"]
orders = Starfish.data["orders"]

for spectrum_id in range(len(spectra)):
    for order in orders:

        npoly = Starfish.config["cheb_degree"]

        if order == orders[-1]:
            # Use cheb degree - 1 for the last order
            npoly -= 1

        fname_phi = Starfish.specfmt.format(spectrum_id, order) + "phi.json"
        phi = PhiParam.load(fname_phi)

        fname_mc = args.rundir + "/" + Starfish.specfmt.format(
            spectrum_id, order) + "/mc.hdf5"
        flatchain = utils.h5read(fname_mc)

        pars = flatchain[-1, :]

        phi.cheb = pars[:npoly]
        phi.sigAmp = float(pars[npoly])
        phi.logAmp = float(pars[npoly + 1])
        phi.l = float(pars[npoly + 2])

        phi.save()
Esempio n. 3
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# from http://www.astropython.org/snippet/2009/10/chdir-context-manager
@contextlib.contextmanager
def chdir(dirname=None):
    curdir = os.getcwd()
    try:
        if dirname is not None:
            os.chdir(dirname)
        yield
    finally:
        os.chdir(curdir)


paths = glob("s*o*/mc.hdf5")

if args.triangle:
    flatchain = utils.h5read("mc.hdf5", args.burn)
    utils.plot(flatchain, base="")

    cmd = [
        "chain.py", "--files", "mc.hdf5", "-t", "--burn",
        "{}".format(args.burn)
    ]

    for path in paths:
        dirname, fname = path.split("/")

        # CD to this directory using context managers
        with chdir(dirname):
            subprocess.call(cmd)

if args.chain:
Esempio n. 4
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# from http://www.astropython.org/snippet/2009/10/chdir-context-manager
@contextlib.contextmanager
def chdir(dirname=None):
  curdir = os.getcwd()
  try:
    if dirname is not None:
      os.chdir(dirname)
    yield
  finally:
    os.chdir(curdir)


paths = glob("s*o*/mc.hdf5")

if args.triangle:
    flatchain = utils.h5read("mc.hdf5", args.burn)
    utils.plot(flatchain, base="")

    cmd = ["chain.py",  "--files", "mc.hdf5", "-t", "--burn", "{}".format(args.burn)]

    for path in paths:
        dirname, fname = path.split("/")

        # CD to this directory using context managers
        with chdir(dirname):
            subprocess.call(cmd)



if args.chain:
    flatchain = utils.h5read("mc.hdf5", args.burn)
Esempio n. 5
0
from Starfish import utils

# Determine all of the orders we will be fitting
spectra = Starfish.data["files"]
orders = Starfish.data["orders"]


for spectrum_id in range(len(spectra)):
    for order in orders:

        npoly = Starfish.config["cheb_degree"]

        if order == orders[-1]:
            # Use cheb degree - 1 for the last order
            npoly -= 1

        fname_phi = Starfish.specfmt.format(spectrum_id, order) + "phi.json"
        phi = PhiParam.load(fname_phi)

        fname_mc = args.rundir + "/" + Starfish.specfmt.format(spectrum_id, order) + "/mc.hdf5"
        flatchain = utils.h5read(fname_mc)

        pars = flatchain[-1,:]

        phi.cheb = pars[:npoly]
        phi.sigAmp = float(pars[npoly])
        phi.logAmp = float(pars[npoly + 1])
        phi.l = float(pars[npoly + 2])

        phi.save()
Esempio n. 6
0
    files = glob(args.glob)
elif args.files:
    files = args.files
else:
    sys.exit("Must specify either --glob or --files")

#Because we are impatient and want to compute statistics before all the jobs are finished,
# there may be some directories that do not have a flatchains.hdf5 file
flatchainList = []
for file in files:
    try:
        # If we've specified HDF5, use h5read
        # If we've specified csv, use csvread
        root, ext = os.path.splitext(file)
        if ext == ".hdf5":
            flatchainList.append(utils.h5read(file, args.burn, args.thin))
        elif ext == ".csv":
            flatchainList.append(utils.csvread(file, args.burn, args.thin))
    except OSError as e:
        print("{} does not exist, skipping. Or error {}".format(file, e))

print("Using a total of {} flatchains".format(len(flatchainList)))

if args.cat:
    assert len(
        flatchainList
    ) > 1, "If concatenating samples, must provide more than one flatchain"
    utils.cat_list(args.output, flatchainList)

# Assume that if we are using either args.chain, or args.triangle, we are only suppling one
# chain, since these commands don't make sense otherwise.