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 edf, _, eBins = da.get_edf(args.decond)[0:3] DI, _, _, fit = da.get_diffusion(decond_D)[0:4] edD, _, _, eBins_edD = da.get_decD(decond_D, da.DecType.energy)[0:4] edf_edD = da.get_edf(decond_D)[0] sig_IL, _, eBins_sig = da.get_ec_dec_energy(decond_ecdec)[0:3] eBins /= da.const.calorie eBins_edD /= da.const.calorie eBins_sig /= da.const.calorie edf *= da.const.angstrom**3 * da.const.calorie edf_edD *= da.const.angstrom**3 * da.const.calorie DI /= da.const.angstrom**2 / da.const.pico edD /= da.const.angstrom**2 / da.const.pico numPlots = 3 fig, axs = plt.subplots(numPlots, 1, sharex=False, figsize=figsize3)
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, nonlocal_ref=nonlocal_ref, avewidth=avewidth)) print() print("({})".format(sig_unit)) print("=======================================") print("{:<10} {:<}".format('local', str(sig_local[fitkey]))) print("{:<10} {:<}".format('nonlocal', str(sig_nonlocal[fitkey]))) print()
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] smallRegion = []
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 edf, _, eBins = da.get_edf(args.decond)[0:3] DI, _, _, fit = da.get_diffusion(decond_D)[0:4] edD, _, _, eBins_edD = da.get_decD(decond_D, da.DecType.energy)[0:4] edf_edD = da.get_edf(decond_D)[0] sig_I, _, sig_IL, _, eBins_sig = da.get_ec_dec_energy(decond_ecdec, sep_nonlocal=True, threshold=0)[0:5] eBins /= da.const.calorie eBins_edD /= da.const.calorie eBins_sig /= da.const.calorie edf *= da.const.angstrom**3 * da.const.calorie edf_edD *= da.const.angstrom**3 * da.const.calorie DI /= da.const.angstrom**2 / da.const.pico edD /= da.const.angstrom**2 / da.const.pico numPlots = 3 fig, axs = plt.subplots(numPlots, 1, sharex=False, figsize=figsize3)