lineStyle = ['--'] * numIonTypes + ['-'] * numIonTypePairs
if (args.decond_D is None):
decond_D = [args.decond]
else:
decond_D = args.decond_D
if len(decond_D) > 1:
assert(sdD_plot_list is not None)
assert(len(sdD_plot_list) == len(decond_D))
if (args.decond_decqnt is None):
decond_decqnt = args.decond
else:
decond_decqnt = args.decond_decqnt
g, rBins, rBins_unit = da.get_rdf(args.decond)[0:3]
DI, _, DI_unit, fit = da.get_D(decond_D[0])[0:4]
sdD_list = []
rBins_sdD_list = []
g_sdD_list = []
print("fitting range: {}".format(fit[fitkey]))
for file in decond_D:
_sdD, _, _, _rBins_sdD = da.get_decD(file, da.DecType.spatial)[0:4]
sdD_list.append(_sdD)
rBins_sdD_list.append(_rBins_sdD)
g_sdD_list.append(da.get_rdf(file)[0])
sigI, sig_unit, rBins_sigI, _, _, _, sig_local, sig_nonlocal = (
da.get_decqnt_sd(decond_decqnt, sep_nonlocal=sep_nonlocal,
if (args.custom):
mpl.rcParams['axes.color_cycle'] = color
fitKey = 0
if (args.decond_D is None):
decond_D = args.decond
else:
decond_D = args.decond_D
if (args.decond_ecdec is None):
decond_ecdec = args.decond
else:
decond_ecdec = args.decond_ecdec
g, rBins = da.get_rdf(args.decond)[0:2]
DI, _, _, fit = da.get_diffusion(decond_D)[0:4]
sdD, _, _, rBins_sdD = da.get_decD(decond_D, da.DecType.spatial)[0:4]
g_sdD = da.get_rdf(decond_D)[0]
sigI, _, rBins_sigI = da.get_ec_dec(decond_ecdec, da.DecType.spatial)[0:3]
rBins /= da.const.angstrom
rBins_sdD /= da.const.angstrom
rBins_sigI /= da.const.angstrom
DI /= da.const.angstrom**2 / da.const.pico
sdD /= da.const.angstrom**2 / da.const.pico
numPlots = 3
halfCellIndex = rBins.size / np.sqrt(3)
halfCellLength = rBins[halfCellIndex]
if (args.custom):
mpl.rcParams['axes.color_cycle'] = color
fitKey = 0
if (args.decond_D is None):
decond_D = args.decond
else:
decond_D = args.decond_D
if (args.decond_ecdec is None):
decond_ecdec = args.decond
else:
decond_ecdec = args.decond_ecdec
g, rBins = da.get_rdf(args.decond)[0:2]
DI, _, _, fit = da.get_diffusion(decond_D)[0:4]
sdD, _, _, rBins_sdD = da.get_decD(decond_D, da.DecType.spatial)[0:4]
g_sdD = da.get_rdf(decond_D)[0]
sigI, _, rBins_sigI = da.get_ec_dec(decond_ecdec, da.DecType.spatial)[0:3]
rBins /= da.const.angstrom
rBins_sdD /= da.const.angstrom
rBins_sigI /= da.const.angstrom
DI /= da.const.angstrom**2 / da.const.pico
sdD /= da.const.angstrom**2 / da.const.pico
numPlots = 3
halfCellIndex = rBins.size / np.sqrt(3)
halfCellLength = rBins[halfCellIndex]
threshold = 0
cnum = 31
with h5py.File(args.corrData, 'r') as f:
timeLags = f['timeLags'][...]
volume = f['volume'][...]
numMol = f['numMol'][...]
numIonTypes = numMol.size
numIonTypePairs = (numIonTypes * (numIonTypes + 1)) // 2
decgrp = f[da.DecType.spatial.value]
rBins = decgrp['decBins'][...] # nm
rBins *= da.const.nano / da.const.angstrom # AA
sdCorr = decgrp['decCorr'][...] # nm^2 / ps^2
sdCorr *= (da.const.nano / da.const.angstrom)**2 # AA^2 / ps^2
g = da.get_rdf(args.corrData)[0]
# validate arguments
if (args.custom):
assert (len(label) == numIonTypes)
else:
label = ['{}'.format(i + 1) for i in range(numIonTypes)]
label += ['-'.join(l) for l in it.combinations_with_replacement(label, 2)]
# plot sdCorr
rc = {
'font': {
'size': 46,
'family': 'serif',
'serif': 'Times'
threshold = 0
cnum = 31
with h5py.File(args.corrData, 'r') as f:
timeLags = f['timeLags'][...]
volume = f['volume'][...]
numMol = f['numMol'][...]
numIonTypes = numMol.size
numIonTypePairs = (numIonTypes*(numIonTypes+1)) // 2
decgrp = f[da.DecType.spatial.value]
rBins = decgrp['decBins'][...] # nm
rBins *= da.const.nano / da.const.angstrom # AA
sdCorr = decgrp['decCorr'][...] # nm^2 / ps^2
sdCorr *= (da.const.nano / da.const.angstrom)**2 # AA^2 / ps^2
g = da.get_rdf(args.corrData)[0]
# validate arguments
if (args.custom):
assert(len(label) == numIonTypes)
else:
label = ['{}'.format(i+1) for i in range(numIonTypes)]
label += ['-'.join(l) for l in it.combinations_with_replacement(label, 2)]
# plot sdCorr
rc = {'font': {'size': 46,
'family': 'serif',
'serif': 'Times'},
'text': {'usetex': True},
'legend': {'fontsize': 46},
