def autocorr_h5(h5name, directory, fields):
# TODO: merge this with spectrum.spectra_h5
import tables
from visualization import h5_gen
from itertools import izip
dta = tables.openFile(h5name, mode='r')
try:
os.makedirs(directory)
except OSError:
pass
field_gens = [h5_gen(dta, field) for field in fields]
for h5arrs in izip(*field_gens):
name = h5arrs[0].name
title = '%s autocorrelation' % name
fname = os.path.join(directory, name)
plot_multi(h5arrs, fields, title, fname)
# for field in fields:
# for h5arr in h5_gen(dta, field):
# arr = h5arr.read()
# arr -= arr.mean()
# name = "%s%s" % (field, h5arr.name)
# title = "%s autocorrelation" % (name,)
# name = os.path.join(directory, name)
# savefig_ac(arr, title, fname=name)
# del arr
dta.close()
def spectra_h5(h5name, directory):
import tables
from visualization import h5_gen
dta = tables.openFile(h5name, mode='r')
rho_s2 = dta.root.sim_params._v_attrs.RHO_S2
def itr(gen):
for x in gen:
yield x.data()
cdens = h5_gen(dta, 'cden')
cpsis = h5_gen(dta, 'cpsi')
cvors = h5_gen(dta, 'cvor')
npoints = 256
from itertools import izip
try:
os.makedirs(directory)
except OSError:
pass
for (cpsi, cvor, cden) in izip(cpsis, cvors, cdens):
arrs = [cpsi.read(), cvor.read(), cden.read()]
for arr in arrs:
arr.dtype = np.complex64
arrs = [np.transpose(arr) for arr in arrs]
nx = arrs[0].shape[0]
czeros = np.zeros((nx,1), dtype=np.complex64)
arrs = [np.hstack([arr, czeros]) for arr in arrs]
name = os.path.join(directory, cpsi.name)
assert cpsi.name == cvor.name == cden.name
spectra_plot(*arrs, rho_s2=rho_s2, npoints=npoints, name=name, title=name)
dta.close()
