def make_lib(R=1000, wmin=1e3, wmax=1e4, velocity=True,
dirname='./', name='ckc14_new', **extras):
"""Make a new downsampled CKC library, with the desired resolution
in the desired wavelength range. This makes both binary files
(one for each metallicity) and a wavelength file, suitable for use
in FSPS. It also makes an hdf5 file.
This is deprecated in favor of make_lib_byz below
"""
downsample = utils.read_and_downsample_spectra
if not os.path.exists(dirname):
os.makedirs(dirname)
outwave, outres = utils.construct_outwave(R, wmin, wmax,
velocity=velocity)
wave = np.concatenate(outwave)
spectra = downsample(outwave, outres, velocity=velocity,
write_binary=True,
binout=dirname+'{0}_z{{0}}.spectra.bin'.format(name))
with open(dirname+'{0}.lambda'.format(name), 'w') as f:
for w in np.concatenate(outwave):
f.write('{0:15.4f}\n'.format(w))
params = utils.spec_params(expanded=True)
with h5py.File(dirname + '{0}.h5'.format(name), 'x') as f:
dspec = f.create_dataset("spectra", data=spectra)
dwave = f.create_dataset("wavelengths", data=wave)
dpar = f.create_dataset("parameters", data=params)
def make_lib_flatfull(R=1000, wmin=1e3, wmax=1e4, velocity=True,
h5name='data/h5/ckc14_fsps.flat.h5',
outfile='ckc14_new.flat.h5', **extras):
"""Make a new downsampled CKC library, with the desired resolution
in the desired wavelength range. This makes an hdf5 file with the
downsampled spectra.
:param R:
Desired resolution in the interval (wmin, wmax) *not including
the native CKC resolution*, in terms of
lambda/sigma_lambda. Ouside this interval the resolution will
be 100.
:param h5name:
Full path to the *flat* version of the HDF file containing the
full CKC grid.
:param outfile:
Full path to the output h5 filename. Note that this will be a
*flat* spectral file, suitable for use with StarBasis()
"""
h5fullflat = h5name
from utils import downsample_onespec as downsample
# Get the output wavelength grid as segments
outwave, outres = utils.construct_outwave(R, wmin, wmax,
velocity=velocity)
wave = np.concatenate(outwave)
with h5py.File(h5fullflat, "r") as full:
# Full wavelength vector and number of spectra
fwave = np.array(full["wavelengths"])
nspec = full["parameters"].shape[0]
with h5py.File(outfile, "w") as newf:
# store the output wavelength vector
newf.create_dataset("wavelengths", data=wave)
# copy the spectral parameters over
full.copy("parameters", newf)
# create an array to hold the new spectra.
news = newf.create_dataset("spectra", data=np.ones([nspec, len(wave)]) * 1e-33)
# loop over the old spectra
for i in xrange(nspec):
s = np.array(full["spectra"][i, :])
# monitor progress
if np.mod(i , np.int(nspec/10)) == 0:
print("doing {0} of {1} spectra".format(i, nspec))
# don't convolve empty spectra
if s.max() < 1e-32:
continue
# Actually do the convolution
lores = downsample(fwave, s, outwave, outres,
velocity=velocity)
news[i, :] = np.concatenate(lores)
# flush to disk so you can read the file and monitor
# progress in another python instance, and if
# something dies you don't totally lose the data
if np.mod(i , np.int(nspec/10)) == 0:
newf.flush()
def make_lib_byz(R=1000, wmin=1e3, wmax=1e4, velocity=True,
dirname='./', name='ckc14_new', **extras):
"""Make a new downsampled CKC library, with the desired resolution
in the desired wavelength range. This makes both binary files
(one for each metallicity) and a wavelength file, suitable for use
in FSPS. It also makes an hdf5 file with the downsampled spectra.
"""
downsample = utils.read_and_downsample_onez
# set up output names, directories, and files
if not os.path.exists(dirname):
os.makedirs(dirname)
binout = dirname+'{0}_z{{0}}.spectra.bin'.format(name)
wout = dirname+'{0}.lambda'.format(name)
with h5py.File(dirname + '{0}.h5'.format(name), 'x') as f:
spgr = f.create_group("spectra")
# Get the output wavelength grid, write to hdf5 and a file
outwave, outres = utils.construct_outwave(R, wmin, wmax,
velocity=velocity)
wave = np.concatenate(outwave)
dwave = f.create_dataset("wavelengths", data=wave)
with open(wout, 'w') as wf:
for w in np.concatenate(outwave):
wf.write('{0:15.4f}\n'.format(w))
# Parameters
params = utils.spec_params(expanded=True)
dpar = f.create_dataset("parameters", data=params)
zlegend, logg, logt = utils.spec_params()
# Get the spectra for each z binary file
zlist = ['{0:06.4f}'.format(z) for z in zlegend]
for z in zlist:
print('doing z={}'.format(z))
zspec = downsample(z, outwave, outres, binout=binout,
write_binary=True, velocity=velocity)
zd = spgr.create_dataset('z{0}'.format(z), data=zspec)
f.flush()