############################################################################### # This file is part of SWIFT. # Copyright (c) 2016 Matthieu Schaller (schaller@strw.leidenuniv.nl) # 2018 Bert Vandenbroucke (bert.vandenbroucke@gmail.com) # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License as published # by the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License # along with this program. If not, see . # ################################################################################ # Compares the swift result for the 2D spherical Sod shock with a high # resolution 2D reference result import matplotlib matplotlib.use("Agg") import matplotlib.pyplot as plt import numpy as np import scipy.stats as stats import h5py import sys # Parameters gas_gamma = 5.0 / 3.0 # Polytropic index rho_L = 1.0 # Density left state rho_R = 0.140625 # Density right state v_L = 0.0 # Velocity left state v_R = 0.0 # Velocity right state P_L = 1.0 # Pressure left state P_R = 0.1 # Pressure right state plt.style.use("../../../tools/stylesheets/mnras.mplstyle") snap = int(sys.argv[1]) # Read the simulation data sim = h5py.File("sodShock_%04d.hdf5" % snap, "r") boxSize = sim["/Header"].attrs["BoxSize"][0] time = sim["/Header"].attrs["Time"][0] scheme = sim["/HydroScheme"].attrs["Scheme"] kernel = sim["/HydroScheme"].attrs["Kernel function"] neighbours = sim["/HydroScheme"].attrs["Kernel target N_ngb"] eta = sim["/HydroScheme"].attrs["Kernel eta"] git = sim["Code"].attrs["Git Revision"] coords = sim["/PartType0/Coordinates"] x = np.sqrt((coords[:, 0] - 0.5) ** 2 + (coords[:, 1] - 0.5) ** 2) vels = sim["/PartType0/Velocities"] v = np.sqrt(vels[:, 0] ** 2 + vels[:, 1] ** 2) u = sim["/PartType0/InternalEnergies"][:] S = sim["/PartType0/Entropies"][:] P = sim["/PartType0/Pressures"][:] rho = sim["/PartType0/Densities"][:] # Bin the data rho_bin, x_bin_edge, _ = stats.binned_statistic(x, rho, statistic="mean", bins=100) x_bin = 0.5 * (x_bin_edge[1:] + x_bin_edge[:-1]) v_bin, _, _ = stats.binned_statistic(x, v, statistic="mean", bins=x_bin_edge) P_bin, _, _ = stats.binned_statistic(x, P, statistic="mean", bins=x_bin_edge) S_bin, _, _ = stats.binned_statistic(x, S, statistic="mean", bins=x_bin_edge) u_bin, _, _ = stats.binned_statistic(x, u, statistic="mean", bins=x_bin_edge) rho2_bin, _, _ = stats.binned_statistic(x, rho ** 2, statistic="mean", bins=x_bin_edge) v2_bin, _, _ = stats.binned_statistic(x, v ** 2, statistic="mean", bins=x_bin_edge) P2_bin, _, _ = stats.binned_statistic(x, P ** 2, statistic="mean", bins=x_bin_edge) S2_bin, _, _ = stats.binned_statistic(x, S ** 2, statistic="mean", bins=x_bin_edge) u2_bin, _, _ = stats.binned_statistic(x, u ** 2, statistic="mean", bins=x_bin_edge) rho_sigma_bin = np.sqrt(rho2_bin - rho_bin ** 2) v_sigma_bin = np.sqrt(v2_bin - v_bin ** 2) P_sigma_bin = np.sqrt(P2_bin - P_bin ** 2) S_sigma_bin = np.sqrt(S2_bin - S_bin ** 2) u_sigma_bin = np.sqrt(u2_bin - u_bin ** 2) ref = np.loadtxt("sodShockSpherical2D_exact.txt") # Plot the interesting quantities plt.figure(figsize=(7, 7 / 1.6)) line_color = "C4" binned_color = "C2" binned_marker_size = 4 scatter_props = dict( marker=".", ms=1, markeredgecolor="none", alpha=0.5, zorder=-1, rasterized=True, linestyle="none", ) errorbar_props = dict(color=binned_color, ms=binned_marker_size, fmt=".", lw=1.2) # Velocity profile -------------------------------- plt.subplot(231) plt.plot(x, v, **scatter_props) plt.plot(ref[:, 0], ref[:, 2], color=line_color, alpha=0.8, lw=1.2) plt.errorbar(x_bin, v_bin, yerr=v_sigma_bin, **errorbar_props) plt.xlabel("${\\rm{Radius}}~r$", labelpad=0) plt.ylabel("${\\rm{Velocity}}~v_r$", labelpad=0) # Density profile -------------------------------- plt.subplot(232) plt.plot(x, rho, **scatter_props) plt.plot(ref[:, 0], ref[:, 1], color=line_color, alpha=0.8, lw=1.2) plt.errorbar(x_bin, rho_bin, yerr=rho_sigma_bin, **errorbar_props) plt.xlabel("${\\rm{Radius}}~r$", labelpad=0) plt.ylabel("${\\rm{Density}}~\\rho$", labelpad=0) # Pressure profile -------------------------------- plt.subplot(233) plt.plot(x, P, **scatter_props) plt.plot(ref[:, 0], ref[:, 3], color=line_color, alpha=0.8, lw=1.2) plt.errorbar(x_bin, P_bin, yerr=P_sigma_bin, **errorbar_props) plt.xlabel("${\\rm{Radius}}~r$", labelpad=0) plt.ylabel("${\\rm{Pressure}}~P$", labelpad=0) # Internal energy profile ------------------------- plt.subplot(234) plt.plot(x, u, **scatter_props) plt.plot( ref[:, 0], ref[:, 3] / ref[:, 1] / (gas_gamma - 1.0), color=line_color, alpha=0.8, lw=1.2, ) plt.errorbar(x_bin, u_bin, yerr=u_sigma_bin, **errorbar_props) plt.xlabel("${\\rm{Radius}}~r$", labelpad=0) plt.ylabel("${\\rm{Internal~Energy}}~u$", labelpad=0) # Entropy profile --------------------------------- plt.subplot(235) plt.plot(x, S, **scatter_props) plt.plot( ref[:, 0], ref[:, 3] / ref[:, 1] ** gas_gamma, color=line_color, alpha=0.8, lw=1.2 ) plt.errorbar(x_bin, S_bin, yerr=S_sigma_bin, **errorbar_props) plt.xlabel("${\\rm{Radius}}~r$", labelpad=0) plt.ylabel("${\\rm{Entropy}}~S$", labelpad=0) # Information ------------------------------------- plt.subplot(236, frameon=False) text_fontsize = 5 plt.text( -0.45, 0.9, "Sod shock with $\\gamma=%.3f$ in 2D at $t=%.2f$" % (gas_gamma, time), fontsize=text_fontsize, ) plt.text( -0.45, 0.8, "Left:~~ $(P_L, \\rho_L, v_L) = (%.3f, %.3f, %.3f)$" % (P_L, rho_L, v_L), fontsize=text_fontsize, ) plt.text( -0.45, 0.7, "Right: $(P_R, \\rho_R, v_R) = (%.3f, %.3f, %.3f)$" % (P_R, rho_R, v_R), fontsize=text_fontsize, ) plt.plot([-0.45, 0.1], [0.62, 0.62], "k-", lw=1) plt.text(-0.45, 0.5, "$SWIFT$ %s" % git.decode("utf-8"), fontsize=text_fontsize) plt.text(-0.45, 0.4, scheme.decode("utf-8"), fontsize=text_fontsize) plt.text(-0.45, 0.3, kernel.decode("utf-8"), fontsize=text_fontsize) plt.text( -0.45, 0.2, "$%.2f$ neighbours ($\\eta=%.3f$)" % (neighbours, eta), fontsize=text_fontsize, ) plt.xlim(-0.5, 0.5) plt.ylim(0, 1) plt.xticks([]) plt.yticks([]) plt.tight_layout() plt.savefig("SodShock.png", dpi=200)