Commit d8a622e2 authored by Oliver Zier's avatar Oliver Zier
Browse files

add 1d ppm results for evrard collapse

parent 7b3992a5
#!/usr/bin/env python3
"""
Code that plots different radial profiles for the Evrard collapse
"""
# load libraries
import sys # load sys; needed for exit codes
import numpy as np # load numpy
import h5py # load h5py; needed to read snapshots
import matplotlib
import matplotlib.pyplot as plt ## needs to be active for plotting!
import csv
matplotlib.rc_file_defaults()
FloatType = np.float64
#loads the gadget snapshot name
def load_snapshot(name):
gamma = 5./3.
try:
data = h5py.File(name, "r")
except:
print("could not open file : "+ name+" !")
exit(1)
time = FloatType(data["Header"].attrs["Time"])
Pos = np.array(data["PartType0"]["Coordinates"], dtype = FloatType)
Density = np.array(data["PartType0"]["Density"], dtype = FloatType)
Velocity = np.array(data["PartType0"]["Velocities"], dtype = FloatType)
Uthermal = np.array(data["PartType0"]["InternalEnergy"], dtype = FloatType)
radius = np.sqrt(Pos[:,0]**2 + Pos[:,1]**2 + Pos[:,2]**2)
vr = (Velocity[:,0] * Pos[:,0] + Velocity[:,1] * Pos[:,1] + Velocity[:,2] * Pos[:,2]) / radius[:]
origin_particles = np.argwhere(radius == 0.0)
vr[origin_particles] = 0
print(np.max(Density))
press = (gamma-1)*Uthermal*Density
A = press / Density**gamma
return radius,Density, vr, A, time
#bins the particle properties
def get_data_bins(radius,Density, vr, A):
number_bins = 100
min_r = 0.01
max_r = 1.0
r_bin = np.zeros(number_bins)
vr_bin = np.zeros(number_bins)
rho_bin = np.zeros(number_bins)
count_bin = np.zeros(number_bins)
entropy_bin = np.zeros(number_bins)
for i in range(radius.size):
if(radius[i] < min_r or radius[i] > max_r):
continue
bin_value = int((np.log10(radius[i] / min_r))/(np.log10(max_r/min_r)) * number_bins)
count_bin[bin_value] = count_bin[bin_value] + 1
vr_bin[bin_value] = vr_bin[bin_value] + vr[i]
rho_bin[bin_value] = rho_bin[bin_value] + Density[i]
entropy_bin[bin_value] = entropy_bin[bin_value] + A[i]
vr_bin /= count_bin
rho_bin /= count_bin
entropy_bin /= count_bin
for i in range(number_bins):
r_bin[i] = (i+0.5)* (np.log10(max_r/min_r)/number_bins) + np.log10(min_r)
r_bin[i] = 10**r_bin[i]
print(count_bin[i])
return r_bin,rho_bin, vr_bin, entropy_bin
#loads 1d ppm results
def load_ppm_result():
gamma = 5./3.
rost = 3./4./np.pi
est = 1.054811e-1 / 1.05
pst = rost*est
vst = np.sqrt(est)
rst = 1.257607
time = 0
radius = np.zeros(350)
rho = np.zeros(350)
vr = np.zeros(350)
press = np.zeros(350)
with open('ppm_profile/ppm1oaf') as csvfile:
readCSV = csv.reader(csvfile)
line = 0
for row in readCSV:
line = line+1
values = row[0].split()
if(line == 1):
time = values[1]
continue
if(line == 352):
break
radius[line -2] = float(values[1]) /rst*1e-11
rho[line -2] = float(values[2]) /rost
vr[line -2] = float(values[4]) /vst*1e-8
press[line -2] = float(values[3])/pst*1e-16
rho=rho*(3.0/(4*np.pi))
press = press*(3.0/(4*np.pi))
entropy = press / rho**gamma
return radius, rho, vr, entropy
i_file = int(sys.argv[1])
filename = 'output/snapshot_%03d.hdf5' % i_file
radius,Density, vr, A, time = load_snapshot(filename)
radius,Density, vr, A = get_data_bins(radius,Density, vr, A)
fig, ax = plt.subplots(1,3,figsize=(18,6))
ax[0].scatter(radius, Density, facecolors='none', edgecolors='b',alpha = 0.5)
ax[1].scatter(radius, vr, facecolors='none', edgecolors='b',alpha = 0.5)
ax[2].scatter(radius, A, facecolors='none', edgecolors='b',alpha = 0.5)
radius_ppm, rho_ppm, vr_ppm, entropy_ppm = load_ppm_result()
ax[0].plot(radius_ppm, rho_ppm, color="k")
ax[1].plot(radius_ppm, vr_ppm, color="k")
ax[2].plot(radius_ppm, entropy_ppm, color="k")
ax[0].set_xscale('log')
ax[1].set_xscale('log')
ax[2].set_xscale('log')
ax[0].set_yscale('log')
ax[0].set_xlim(0.01,1)
ax[1].set_xlim(0.01,1)
ax[2].set_xlim(0.01,1)
ax[0].set_ylim(0.004,700)
ax[1].set_ylim(-1.8,0)
ax[2].set_ylim(0.0,0.2)
ax[0].set_xlabel("R")
ax[1].set_xlabel("R")
ax[2].set_xlabel("R")
ax[0].set_ylabel(r"$\rho$")
ax[1].set_ylabel(r"$V_R$")
ax[2].set_ylabel(r"$P/\rho^\gamma$")
plt.tight_layout()
plt.savefig("evrard_"+str(i_file)+".eps")
plt.show()
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