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GrayModelPlots.py
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GrayModelPlots.py
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import numpy as np
import matplotlib.pyplot as plt
import mpl_toolkits.mplot3d.axes3d as p3
from matplotlib.animation import FuncAnimation
from scipy import stats
import os
current_dir = os.getcwd()
def diffussive_T(T, T0, Tf, xf):
'''
Computes the steady state temperature for the diffussive regime
from the Fourier Law (Boundaries at x0=0 and xf=xf)
'''
k = (Tf - T0) / xf
return k * T + T0
def balistic_T(T0, Tf):
'''
Computes the steady state temperature for the balistic regime
from the Boltzmann Law
'''
return ((T0**4 + Tf**4)/2)**(0.25)
def get_parameters(filename):
f = open(filename, 'r')
i = 0
for line in f:
try:
cols = line.split()
if len(cols) > 0:
value = float(cols[1])
if i == 0:
Lx = value
elif i == 1:
Ly = value
elif i == 2:
Lz = value
elif i == 4:
Lx_subcell = value
elif i == 5:
Ly_subcell = value
elif i == 6:
Lz_subcell = value
elif i == 8:
T0 = value
elif i == 9:
Tf = value
elif i == 10:
Ti = value
elif i == 12:
t_MAX = value
elif i == 13:
dt = value
elif i == 15:
W = value
elif i == 16:
every_flux = value
i += 1
except:
pass
return Lx, Ly, Lz, Lx_subcell, Ly_subcell, Lz_subcell, T0, Tf, Ti, t_MAX, dt, W, every_flux
def Ballistic_regime_1D(folder):
os.chdir(current_dir + '/' + folder)
Lx, Ly, Lz, Lx_subcell, Ly_subcell, Lz_subcell, T0, Tf, Ti, t_MAX, dt, W, every_flux = get_parameters('parameters_used.txt')
print('Parameters used')
print('---------------------------------------\n')
print('Lx: ' + str(Lx))
print('Ly: ' + str(Ly))
print('Lz: ' + str(Lz) + '\n')
print('Lx_subcell: ' + str(Lx_subcell))
print('Ly_subcell: ' + str(Ly_subcell))
print('Lz_subcell: ' + str(Lz_subcell) + '\n')
print('T0: ' + str(T0))
print('Tf: ' + str(Tf))
print('Ti: ' + str(Ti) + '\n')
print('t_MAX: ' + str(t_MAX))
print('dt: ' + str(dt) + '\n')
print('W: ' + str(W))
E = np.load('Energy.npy')
N = np.load('Phonons.npy')
T_cells = np.load('Subcell_Ts.npy')
scattering_events = np.load('Scattering_events.npy')
temperatures = np.load('Temperatures.npy')
elapsed_time = np.load('Elapsed_time.npy')
print('N avg:', np.mean(N))
print('SE avg:', np.mean(scattering_events))
time = np.linspace(0, t_MAX*1e12, int(t_MAX/dt))
#Subplots
plt.figure(figsize=(10, 6))
plt.subplot(2, 2, 1)
plt.plot(time, E)
plt.title('Energy evolution')
plt.xlabel('Time [ps]')
plt.ylabel('Energy [J]')
plt.subplot(2, 2, 2)
plt.plot(time, N)
plt.title('Number of phonons evolution')
plt.xlabel('Time [ps]')
plt.ylabel('Phonons [#]')
plt.subplot(2, 2, 3)
plt.plot(time, temperatures)
plt.title('Average temperature evolution')
plt.xlabel('Time [ps]')
plt.ylabel('Temperature [K]')
plt.subplot(2, 2, 4)
plt.plot(time, scattering_events)
plt.title('Scattering events in time')
plt.xlabel('Time [ps]')
plt.ylabel('Scattering events [#]')
plt.subplots_adjust(left=0.12, bottom=0.08, right=0.9, top=0.94, wspace=0.2, hspace=0.34)
plt.show()
#T plot
plt.figure(figsize=(10, 6))
x = np.linspace(0, Lx, int(round(Lx/Lx_subcell, 0)))
#Average for each subcell in equilibrium
average_T_cells = []
desv_std = []
desv_std_neg = []
equil = 7500
for i in range(int(round(Lx/Lx_subcell, 0))):
average_T_cells.append(np.nanmean(T_cells[equil : , i]))
desv_std.append(np.nanstd(T_cells[equil : , i, 0, 0]))
desv_std_neg.append(-np.nanstd(T_cells[equil : , i, 0, 0]))
max_errror = np.max(desv_std)
y_balistic = np.linspace(balistic_T(float(T_cells[-1][0]), float(T_cells[-1][-1])), balistic_T(float(T_cells[-1][0]), float(T_cells[-1][-1])), len(x))
print('Max error:', max_errror)
total_avg_T = np.nanmean(T_cells[equil:])
plt.plot(x, average_T_cells, ls='', color='r', marker='x', label='Average cell temperature')
#plt.plot(x, T_cells[0][:, int(Ly / 2), int(Lz/2)], ls='-', color='c', marker='*', label='T at %.2f ps' % float(time[1]))
#plt.plot(x, T_cells[1000][:, int(Ly / 2), int(Lz/2)], ls='-', color='r', marker='^', label='T at %.2f ns' % float(time[1000] * 1e-3))
#plt.plot(x, T_cells[5000][:, int(Ly / 2), int(Lz/2)], ls='-', color='b', marker='o', label='T at %.2f ns' % float(time[5000]* 1e-3))
plt.plot(x, T_cells[-1][:, int(Ly / 2), int(Lz/2)], ls='-', color='g', marker='s', label='T at %.2f ns' % float(time[-1] * 1e-3))
plt.plot(x, desv_std + y_balistic, ls='--', color='b', label='Standard Deviation')
plt.plot(x, desv_std_neg + y_balistic, ls='--', color='b')
plt.plot(x, np.linspace(balistic_T(float(T_cells[-1][0]), float(T_cells[-1][-1])),
balistic_T(float(T_cells[-1][0]), float(T_cells[-1][-1])), len(x)), ls='--', color='k', label='Ballistic regime')
plt.plot(x, diffussive_T(x, float(T_cells[-1][0]), float(T_cells[-1][-1]), Lx), color='k', label='Diffusive regime')
plt.title('Domain temperature evolution')
plt.xlabel('Domain length [m]')
plt.ylabel('Temperature [K]')
plt.legend()
plt.show()
def Diffusive_regime_1D(folder_filename):
os.chdir(current_dir + '/' + folder_filename)
Lx, Ly, Lz, Lx_subcell, Ly_subcell, Lz_subcell, T0, Tf, Ti, t_MAX, dt, W, every_flux = get_parameters('parameters_used.txt')
print('Parameters used')
print('---------------------------------------\n')
print('Lx: ' + str(Lx))
print('Ly: ' + str(Ly))
print('Lz: ' + str(Lz) + '\n')
print('Lx_subcell: ' + str(Lx_subcell))
print('Ly_subcell: ' + str(Ly_subcell))
print('Lz_subcell: ' + str(Lz_subcell) + '\n')
print('T0: ' + str(T0))
print('Tf: ' + str(Tf))
print('Ti: ' + str(Ti) + '\n')
print('t_MAX: ' + str(t_MAX))
print('dt: ' + str(dt) + '\n')
print('W: ' + str(W))
time = np.linspace(0, t_MAX*1e12, int(t_MAX/dt))
E = np.load('Energy.npy')
N = np.load('Phonons.npy')
T_cells = np.load('Subcell_Ts.npy')
scattering_events = np.load('Scattering_events.npy')
temperatures = np.load('Temperatures.npy')
print('N avg:', np.mean(N))
print('SE avg:', np.mean(scattering_events))
#Subplots
plt.figure(figsize=(10, 6))
plt.subplot(2, 2, 1)
plt.plot(time, E)
plt.title('Energy evolution')
plt.xlabel('Time [ps]')
plt.ylabel('Energy [J]')
plt.subplot(2, 2, 2)
plt.plot(time, N)
plt.ticklabel_format(axis='y', style='scientific', scilimits=(-2,2))
plt.title('Number of phonons evolution')
plt.xlabel('Time [ps]')
plt.ylabel('Phonons [#]')
plt.subplot(2, 2, 3)
plt.plot(time, temperatures)
plt.title('Average temperature evolution')
plt.xlabel('Time [ps]')
plt.ylabel('Temperature [K]')
plt.subplot(2, 2, 4)
plt.plot(time, scattering_events)
plt.ticklabel_format(axis='y', style='scientific', scilimits=(-2,2))
plt.title('Scattering events in time')
plt.xlabel('Time [ps]')
plt.ylabel('Scattering events [#]')
plt.subplots_adjust(left=0.12, bottom=0.08, right=0.9, top=0.94, wspace=0.2, hspace=0.34)
plt.show()
#T plot
plt.figure(figsize=(10, 6))
x = np.linspace(0, Lx, int(round(Lx/Lx_subcell, 0)))
#Average for each subcell in equilibrium
average_T_cells = []
desv_std = []
desv_std_neg = []
equil = 2000
for i in range(int(round(Lx/Lx_subcell, 0))):
average_T_cells.append(np.nanmean(T_cells[equil : , i, 0, 0]))
desv_std.append(np.nanstd(T_cells[equil : , i, 0, 0]))
desv_std_neg.append(-np.nanstd(T_cells[equil : , i, 0, 0]))
max_errror = np.max(desv_std)
print('Max error:', max_errror)
#markerfacecolor='None'
plt.plot(x, average_T_cells, ls='', color='r', marker='x', label='Average cell temperature')
plt.plot(x, desv_std + diffussive_T(x, float(T_cells[-1][0]), float(T_cells[-1][-1]), Lx), ls='-', color='b', label='Standard Deviation')
plt.plot(x, desv_std_neg + diffussive_T(x, float(T_cells[-1][0]), float(T_cells[-1][-1]), Lx), ls='-', color='b')
#plt.plot(x, T_cells[1000][:, int(Ly / 2), int(Lz/2)], ls='-', color='r', marker='^', label='T at %.2f ns' % float(time[1000]*1e-3))
#plt.plot(x, T_cells[2000][:, int(Ly / 2), int(Lz/2)], ls='-', color='b', marker='o', label='T at %.2f ns' % float(time[2000]*1e-3))
plt.plot(x, T_cells[-1][:, int(Ly / 2), int(Lz/2)], ls='-', color='g', marker='s', label='T at %.2f ns' % float(time[-1]*1e-3))
plt.plot(x, np.linspace(balistic_T(float(T_cells[-1][0]), float(T_cells[-1][-1])),
balistic_T(float(T_cells[-1][0]), float(T_cells[-1][-1])), len(x)), ls='--', color='k', label='Ballistic regime')
plt.plot(x, diffussive_T(x, float(T_cells[-1][0]), float(T_cells[-1][-1]), Lx), color='k', label='Diffusive regime')
plt.title('Domain temperature evolution')
plt.xlabel('Domain length [m]')
plt.ylabel('Temperature [K]')
plt.legend()
plt.show()
def all_plots(folder):
os.chdir(current_dir + '/' + folder)
Lx, Ly, Lz, Lx_subcell, Ly_subcell, Lz_subcell, T0, Tf, Ti, t_MAX, dt, W, every_flux = get_parameters('parameters_used.txt')
print('Parameters used')
print('---------------------------------------\n')
print('Lx: ' + str(Lx))
print('Ly: ' + str(Ly))
print('Lz: ' + str(Lz) + '\n')
print('Lx_subcell: ' + str(Lx_subcell))
print('Ly_subcell: ' + str(Ly_subcell))
print('Lz_subcell: ' + str(Lz_subcell) + '\n')
print('T0: ' + str(T0))
print('Tf: ' + str(Tf))
print('Ti: ' + str(Ti) + '\n')
print('t_MAX: ' + str(t_MAX))
print('dt: ' + str(dt) + '\n')
print('W: ' + str(W))
print('Every_flux: ' + str(every_flux))
E = np.load('Energy.npy')
N = np.load('Phonons.npy')
T_cells = np.load('Subcell_Ts.npy')
scattering_events = np.load('Scattering_events.npy')
temperatures = np.load('Temperatures.npy')
elapsed_time = np.load('Elapsed_time.npy')
flux = np.load('Flux.npy')
time = np.linspace(0, t_MAX*1e12, int(round(t_MAX/dt, 0)))
time_flux = np.linspace(0, t_MAX*1e12, int(round(t_MAX/(dt * every_flux))))
#Subplots
plt.figure(figsize=(10, 6))
plt.subplot(2, 2, 1)
plt.plot(time, E)
plt.title('Energy evolution')
plt.xlabel('Time [ps]')
plt.ylabel('Energy [J]')
plt.subplot(2, 2, 2)
plt.plot(time, N)
plt.title('Number of phonons evolution')
plt.xlabel('Time [ps]')
plt.ylabel('Phonons [#]')
plt.subplot(2, 2, 3)
plt.plot(time, temperatures)
plt.title('Average temperature evolution')
plt.xlabel('Time [ps]')
plt.ylabel('Temperature [K]')
plt.subplot(2, 2, 4)
plt.plot(time, scattering_events)
plt.title('Scattering events in time')
plt.xlabel('Time [ps]')
plt.ylabel('Scattering events [#]')
plt.subplots_adjust(left=0.12, bottom=0.08, right=0.9, top=0.94, wspace=0.2, hspace=0.34)
plt.show()
#T plot
plt.figure(figsize=(10, 6))
x = np.linspace(0, Lx, int(round(Lx/Lx_subcell, 0)))
#Average for each subcell in equilibrium
average_T_cells = []
equil = 500
for i in range(int(round(Lx/Lx_subcell, 0))):
average_T_cells.append(np.nanmean(T_cells[equil : , i]))
total_avg_T = np.nanmean(T_cells[equil:])
plt.plot(x, average_T_cells, ls='-', color='k', marker='s', label='Average cell T %.2f' % total_avg_T)
#plt.plot(x, T_cells[0][:, int(Ly / 2), int(Lz/2)], ls='-', color='c', marker='*', label='T at %.2f ps' % float(time[1]))
#plt.plot(x, T_cells[1000][:, int(Ly / 2), int(Lz/2)], ls='-', color='r', marker='^', label='T at %.2f ps' % float(time[1000]))
#plt.plot(x, T_cells[5000][:, int(Ly / 2), int(Lz/2)], ls='-', color='b', marker='o', label='T at %.2f ps' % float(time[5000]))
plt.plot(x, T_cells[-1][:, int(Ly / 2), int(Lz/2)], ls='-', color='g', marker='s', label='T at %.2f ns' % float(time[-1] * 1e-3))
plt.plot(x, np.linspace(balistic_T(float(T_cells[-1][0]), float(T_cells[-1][-1])),
balistic_T(float(T_cells[-1][0]), float(T_cells[-1][-1])), len(x)), ls='--', color='k', label='Ballistic regime')
plt.plot(x, diffussive_T(x, float(T_cells[-1][0]), float(T_cells[-1][-1]), Lx), color='k', label='Diffusive regime')
plt.title('Domain temperature evolution')
plt.xlabel('Domain length [m]')
plt.ylabel('Temperature [K]')
plt.legend()
plt.show()
plt.plot(time_flux, flux, ls='--', color='c', label='')
plt.title('Flux')
plt.show()
plt.plot(time, elapsed_time, ls='', marker='x', color='g')
slope, intercept, r_value, p_value, std_error = stats.linregress(time, elapsed_time)
y_regre = np.array(time) * slope + intercept
plt.plot(time, y_regre, color='r', label='y=%.2fx+%.2f' % (slope, intercept))
plt.title('Elapsed time')
plt.legend()
plt.show()
def plots_restart(folder, t_max):
os.chdir(current_dir + '/' + folder)
Lx, Ly, Lz, Lx_subcell, Ly_subcell, Lz_subcell, T0, Tf, Ti, t_MAX, dt, W, every_flux = get_parameters('parameters_used.txt')
print('Parameters used')
print('---------------------------------------\n')
print('Lx: ' + str(Lx))
print('Ly: ' + str(Ly))
print('Lz: ' + str(Lz) + '\n')
print('Lx_subcell: ' + str(Lx_subcell))
print('Ly_subcell: ' + str(Ly_subcell))
print('Lz_subcell: ' + str(Lz_subcell) + '\n')
print('T0: ' + str(T0))
print('Tf: ' + str(Tf))
print('Ti: ' + str(Ti) + '\n')
print('t_MAX: ' + str(t_MAX))
print('dt: ' + str(dt) + '\n')
print('W: ' + str(W))
print('Every_flux: ' + str(every_flux))
E = np.load('Energy.npy')
N = np.load('Phonons.npy')
T_cells = np.load('Subcell_Ts.npy')
scattering_events = np.load('Scattering_events.npy')
temperatures = np.load('Temperatures.npy')
elapsed_time = np.load('Elapsed_time.npy')
flux = np.load('Flux.npy')
time = np.linspace(0, len(E), len(E))
time_flux = np.linspace(0, len(flux), len(flux))
#Subplots
plt.figure(figsize=(10, 6))
plt.subplot(2, 2, 1)
plt.plot(time, E)
plt.title('Energy evolution')
plt.xlabel('Time [ps]')
plt.ylabel('Energy [J]')
plt.subplot(2, 2, 2)
plt.plot(time, N)
plt.title('Number of phonons evolution')
plt.xlabel('Time [ps]')
plt.ylabel('Phonons [#]')
plt.subplot(2, 2, 3)
plt.plot(time, temperatures)
plt.title('Average temperature evolution')
plt.xlabel('Time [ps]')
plt.ylabel('Temperature [K]')
plt.subplot(2, 2, 4)
plt.plot(time, scattering_events)
plt.title('Scattering events in time')
plt.xlabel('Time [ps]')
plt.ylabel('Scattering events [#]')
plt.subplots_adjust(left=0.12, bottom=0.08, right=0.9, top=0.94, wspace=0.2, hspace=0.34)
plt.show()
#T plot
plt.figure(figsize=(10, 6))
x = np.linspace(0, Lx, int(round(Lx/Lx_subcell, 0)))
#Average for each subcell in equilibrium
average_T_cells = []
equil = 7500
for i in range(int(round(Lx/Lx_subcell, 0))):
average_T_cells.append(np.nanmean(T_cells[equil : , i]))
total_avg_T = np.nanmean(T_cells[equil:])
plt.plot(x, average_T_cells, ls='-', color='k', marker='s', label='Average cell T %.2f' % total_avg_T)
plt.plot(x, T_cells[0][:, int(Ly / 2), int(Lz/2)], ls='-', color='c', marker='*', label='T at %.2f ps' % float(time[1]))
#plt.plot(x, T_cells[1000][:, int(Ly / 2), int(Lz/2)], ls='-', color='r', marker='^', label='T at %.2f ps' % float(time[1000]))
#plt.plot(x, T_cells[5000][:, int(Ly / 2), int(Lz/2)], ls='-', color='b', marker='o', label='T at %.2f ps' % float(time[5000]))
plt.plot(x, T_cells[-1][:, int(Ly / 2), int(Lz/2)], ls='-', color='g', marker='s', label='T at %.2f ns' % float(time[-1] * 1e-3))
plt.plot(x, np.linspace(balistic_T(float(T_cells[-1][0]), float(T_cells[-1][-1])),
balistic_T(float(T_cells[-1][0]), float(T_cells[-1][-1])), len(x)), ls='--', color='k', label='Ballistic regime')
plt.plot(x, diffussive_T(x, float(T_cells[-1][0]), float(T_cells[-1][-1]), Lx), color='k', label='Diffusive regime')
plt.title('Domain temperature evolution')
plt.xlabel('Domain length [m]')
plt.ylabel('Temperature [K]')
plt.legend()
plt.show()
print('\n\nAvg_flux:', np.nanmean(flux))
plt.plot(time_flux, flux, ls='--', color='c', label='')
plt.title('Flux')
plt.show()
plt.plot(time, elapsed_time, ls='', marker='x', color='g')
slope, intercept, r_value, p_value, std_error = stats.linregress(time, elapsed_time)
y_regre = np.array(time) * slope + intercept
plt.plot(time, y_regre, color='r', label='y=%.2fx+%.2f' % (slope, intercept))
plt.title('Elapsed time')
plt.legend()
plt.show()
########################
# UNCOMMENT TO USE #
########################
#Ballistic_regime_1D('OUTPUTS')
#Diffusive_regime_1D('OUTPUTS')
#all_plots('OUTPUTS')
#plots_restart('restart_1000' 1000)