###############################################################################
# This file is part of SWIFT.
# Copyright (c) 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 <http://www.gnu.org/licenses/>.
#
##############################################################################

import matplotlib

matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
from scipy import stats
import h5py
import sys

# Parameters
gamma = 5.0 / 3.0  # Polytropic index
rhoL = 1.0  # Initial density in the non vacuum state
vL = 0.0  # Initial velocity in the non vacuum state
PL = 1.0  # Initial pressure in the non vacuum state
rhoR = 0.0  # Initial vacuum density
vR = 0.0  # Initial vacuum velocity
PR = 0.0  # Initial vacuum pressure

plt.style.use("../../../tools/stylesheets/mnras.mplstyle")

snap = int(sys.argv[1])

# Open the file and read the relevant data
file = h5py.File("vacuum_{0:04d}.hdf5".format(snap), "r")
coords = file["/PartType0/Coordinates"]
x = np.sqrt(
    (coords[:, 0] - 0.5) ** 2 + (coords[:, 1] - 0.5) ** 2 + (coords[:, 2] - 0.5) ** 2
)
rho = file["/PartType0/Densities"][:]
vels = file["/PartType0/Velocities"]
v = np.sqrt(vels[:, 0] ** 2 + vels[:, 1] ** 2 + vels[:, 2] ** 2)
u = file["/PartType0/InternalEnergies"][:]
S = file["/PartType0/Entropies"][:]
P = file["/PartType0/Pressures"][:]
time = file["/Header"].attrs["Time"][0]

scheme = file["/HydroScheme"].attrs["Scheme"]
kernel = file["/HydroScheme"].attrs["Kernel function"]
neighbours = file["/HydroScheme"].attrs["Kernel target N_ngb"][0]
eta = file["/HydroScheme"].attrs["Kernel eta"][0]
git = file["Code"].attrs["Git Revision"]

# Bin the data values
# We let scipy choose the bins and then reuse them for all other quantities
rho_bin, x_bin_edge, _ = stats.binned_statistic(x, rho, statistic="mean", bins=50)
rho2_bin, _, _ = stats.binned_statistic(x, rho ** 2, statistic="mean", bins=x_bin_edge)
rho_sigma_bin = np.sqrt(rho2_bin - rho_bin ** 2)

v_bin, _, _ = stats.binned_statistic(x, v, statistic="mean", bins=x_bin_edge)
v2_bin, _, _ = stats.binned_statistic(x, v ** 2, statistic="mean", bins=x_bin_edge)
v_sigma_bin = np.sqrt(v2_bin - v_bin ** 2)

P_bin, _, _ = stats.binned_statistic(x, P, statistic="mean", bins=x_bin_edge)
P2_bin, _, _ = stats.binned_statistic(x, P ** 2, statistic="mean", bins=x_bin_edge)
P_sigma_bin = np.sqrt(P2_bin - P_bin ** 2)

u_bin, _, _ = stats.binned_statistic(x, u, statistic="mean", bins=x_bin_edge)
u2_bin, _, _ = stats.binned_statistic(x, u ** 2, statistic="mean", bins=x_bin_edge)
u_sigma_bin = np.sqrt(u2_bin - u_bin ** 2)

S_bin, _, _ = stats.binned_statistic(x, S, statistic="mean", bins=x_bin_edge)
S2_bin, _, _ = stats.binned_statistic(x, S ** 2, statistic="mean", bins=x_bin_edge)
S_sigma_bin = np.sqrt(S2_bin - S_bin ** 2)

x_bin = 0.5 * (x_bin_edge[1:] + x_bin_edge[:-1])

ref = np.loadtxt("vacuumSpherical3D_exact.txt")

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)
plt.xlim(0.0, 0.4)
plt.ylim(-0.1, 3.2)

# 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)
plt.xlim(0.0, 0.4)

# 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)
plt.xlim(0.0, 0.4)

# Internal energy profile
plt.subplot(234)
plt.plot(x, u, **scatter_props)
plt.plot(
    ref[:, 0],
    ref[:, 3] / ref[:, 1] / (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)
plt.xlim(0.0, 0.4)

# Entropy profile
plt.subplot(235)
plt.plot(x, S, **scatter_props)
plt.plot(ref[:, 0], ref[:, 3] / ref[:, 1] ** 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)
plt.xlim(0.0, 0.4)
plt.ylim(0.0, 4.0)

# Run information
plt.subplot(236, frameon=False)

text_fontsize = 5

plt.text(
    -0.45,
    0.9,
    "Vacuum test with $\\gamma={0:.3f}$ in 3D at $t = {1:.2f}$".format(gamma, time),
    fontsize=text_fontsize,
)
plt.text(
    -0.45,
    0.8,
    "Left: $(P_L, \\rho_L, v_L) = ({0:.3f}, {1:.3f}, {2:.3f})$".format(PL, rhoL, vL),
    fontsize=text_fontsize,
)
plt.text(
    -0.45,
    0.7,
    "Right: $(P_R, \\rho_R, v_R) = ({0:.3f}, {1:.3f}, {2:.3f})$".format(PR, rhoR, vR),
    fontsize=text_fontsize,
)
plt.plot([-0.45, 0.1], [0.62, 0.62], "k-", lw=1)
plt.text(-0.45, 0.5, "$SWIFT$ {0}".format(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,
    "${0:.2f}$ neighbours ($\\eta={1:.3f}$)".format(neighbours, eta),
    fontsize=text_fontsize,
)
plt.xlim(-0.5, 0.5)
plt.ylim(0.0, 1.0)
plt.xticks([])
plt.yticks([])

plt.tight_layout()

plt.savefig("Vacuum.png", dpi=200)