# energyRa[:,1] : time
# energyRa[:,2] : energy flowing across the domain borders
# energyRa[:,3] : energy used for phase transition
# energyRa[:,4] : energy for the internal energy
energyRa = np.loadtxt(energyRa_filename)
plt.close("all")
plt.rc('text', usetex=True)
plt.rc('font', family='serif')
fig = plt.figure(figsize=(8,6))
ax = fig.add_subplot(111)
style = ['s-','-','o-']
width = 3
for i in range(0,len(style)):
grayscale_value = 0.1 + 0.9*(float(i)/float(len(style)-1))
plt.plot(
energyRa[:,1],
energyRa[:,2+i],
style[i],
linewidth=width,
color=grayscale_to_RGB(grayscale_value))
plt.show()
def create_mass_graph(simDirs,
legend='None',
width=3,
xlabel='',
ylabel='',
show=True,
figPath='',
add_zoom_above=False,
add_linear_interpolation=True,
borders_linear_interpolation='None',
step=1,
legendLoc='lower right',
styleDashed=False,
xlim='None',
ylim='None'):
'''
@description: create a graph with the vapor mass
as function of time for different contact angles
'''
growthRate='None'
plt.close("all")
plt.rc('text', usetex=True)
plt.rc('font', family='serif')
fig = plt.figure(figsize=(8,6))
# plot the mass as function of time
# as the main plot
ax = fig.add_subplot(111)
ini_time = [100.,0.]
ini_mass = [0.,0.]
start_i = np.empty([len(simDirs)])
end_i = np.empty([len(simDirs)])
max_mass = 0.0
for i in range(0,len(simDirs)):
mass = np.loadtxt(os.path.join(simDirs[i],'mass.txt'))
max_mass = max(max_mass,max(mass[:,2]))
# determine the last relevant step: timestep!=0
start_i[i]=0
for j in range(0,len(mass[:,0])):
if(mass[j,2]>0.0):
start_i[i]=j
break
end_i[i]=len(mass[:,0])-1
for j in range(int(start_i[i]),len(mass[:,0])):
if(mass[j,0]==0.0):
end_i[i]=j-1
break
# extract the initial time when
# the bubble appears
for j in range(0,len(mass[:,0])):
if(mass[j,2]>0.0):
ini_time[0] = min(ini_time[0],mass[j,1])
ini_time[1] = max(ini_time[1],mass[j,1])
ini_mass[0] = min(ini_mass[0],mass[j,2])
ini_mass[1] = max(ini_mass[1],mass[j,2])
break
# plot the mass as function
# of time on the main graph
if(styleDashed):
grayscale_value = 0.2+ 0.8*float((i-i%2)/2.0)/float(len(simDirs)/2.0)
else:
grayscale_value = 0.2+ 0.8*float(i)/float(len(simDirs))
if(styleDashed):
if(i%2==0):
style='-'
else:
style='--'
else:
style='-'
plt.plot(mass[0:end_i[i]:step,1],
mass[0:end_i[i]:step,2],
style,
linewidth=width,
color=grayscale_to_RGB(grayscale_value))
ax.set_xlabel(r''+xlabel)
ax.set_ylabel(r''+ylabel)
# extract the linear growth rate
if(add_linear_interpolation):
growthRate = []
if(borders_linear_interpolation!='None'):
for i in range(0,len(simDirs)):
mass = np.loadtxt(os.path.join(simDirs[i],'mass.txt'))
for j in range(0,len(borders_linear_interpolation[i])):
i1 = borders_linear_interpolation[i][j][0]
i2 = borders_linear_interpolation[i][j][1]
xi = mass[i1:i2,1]
A = np.array([xi, np.ones(len(xi))])
yi = mass[i1:i2,2]
pi = np.linalg.lstsq(A.T,yi)[0] #least square approximation
xi = mass[i1-5:i2+5,1]
line = pi[0]*xi + pi[1]
if(len(borders_linear_interpolation[i])>1 and j==0):
style = '--'
else:
style ='-'
growthRate.append(pi[0])
plt.plot(xi,line,'r',linestyle=style)
print("%40s | growthrate: %3.2e" % (os.path.basename(os.path.dirname(simDirs[i])), pi[0]))
else:
for i in range(0,len(simDirs)):
mass = np.loadtxt(os.path.join(simDirs[i],'mass.txt'))
xi = mass[int(start_i[i]):int(end_i[i]),1]
A = np.array([xi, np.ones(len(xi))])
yi = mass[int(start_i[i]):int(end_i[i]),2]
pi = np.linalg.lstsq(A.T,yi)[0] #least square approximation
line = pi[0]*xi + pi[1]
plt.plot(xi,line,'r-')
print("%40s | growthrate: %3.2e" % (os.path.basename(os.path.dirname(simDirs[i])), pi[0]))
growthRate.append(pi[0])
if(add_zoom_above):
ax.set_ylim(0.0,max_mass*(1.0+0.2))
else:
ax.set_ylim(0.0,max_mass)
if(xlim!='None'):
ax.set_xlim(xlim[0],xlim[1])
if(ylim!='None'):
ax.set_ylim(ylim[0],ylim[1])
if(legend!='None'):
plt.legend(legend,loc=legendLoc)
# add a zoom where the initial bubble appears
# on the lower right part of the plot
if(add_zoom_above):
ax_x_lim = ax.get_xlim()
ax_y_lim = ax.get_ylim()
border = 0.2*(ini_time[1]-ini_time[0])
ini_time[0]-= border
ini_time[1]+= border
ini_mass[0] = ini_mass[0]*(1.-0.1)
ini_mass_tmp = ini_mass[0]+(ini_time[1]-ini_time[0])*(ax_y_lim[1]-ax_y_lim[0])/(ax_x_lim[1]-ax_x_lim[0])
width = 0.5
height_p = width*((ini_mass_tmp-ini_mass[0])/(ax_y_lim[1]-ax_y_lim[0]))/((ini_time[1]-ini_time[0])/(ax_x_lim[1]-ax_x_lim[0]))
height = 0.2
ini_mass_tmp = height/height_p*ini_mass_tmp
if(ini_mass_tmp>ini_mass[1]):
ini_mass[1] = ini_mass_tmp
ax_zoom = plt.axes([.15, .65, width, height]) #, axisbg='y')
for i in range(0,len(simDirs)):
mass = np.loadtxt(os.path.join(simDirs[i],'mass.txt'))
grayscale_value = 0.2+ 0.8*float(i)/float(len(simDirs))
p = ax_zoom.plot(mass[0:end_i[i]:step,1],
mass[0:end_i[i]:step,2],
'+-',
linewidth=5*width,
color=grayscale_to_RGB(grayscale_value))
plt.setp(ax_zoom, xticks=[], yticks=[])
ax_zoom.set_xlim(ini_time[0],ini_time[1])
ax_zoom.set_ylim(ini_mass[0],ini_mass[1])
if(show):
plt.show()
plt.close()
if(not figPath==''):
plt.savefig(figPath)
return growthRate,
def create_growthrate_graph(heatFlux,
growthRate,
width=3,
xlabel='',
ylabel='',
show=True,
legend='None',
xlim='None',
ylim='None'):
'''
@description: draw a graph with the mass growth rate
as a function of the heat flux
'''
# open new figure for the mass growth rate
plt.close("all")
plt.rc('text', usetex=True)
plt.rc('font', family='serif')
fig = plt.figure(figsize=(8,6))
ax = fig.add_subplot(111)
# plot the mass growth rate
plt.plot(heatFlux,
growthRate,
'o',
linewidth=width,
color=grayscale_to_RGB(0.8))
ax.set_xlabel(r''+xlabel)
ax.set_ylabel(r''+ylabel)
# add the linear interpolation
xi = np.array(heatFlux)
A = np.array([xi, np.ones(len(xi))])
yi = np.array(growthRate)
pi = np.linalg.lstsq(A.T,yi)[0] #least square approximation
xi = np.insert(xi,0,0.0)
xi = np.append(xi,0.11)
line = pi[0]*xi + pi[1]
plt.plot(xi,line,'r-')
plt.plot([-pi[1]/pi[0]],[0.0],'rs')
plt.plot([0.0,0.11],[0.0,0.0],'k--')
print 'equivalent_latent_heat: ', pi[0]
print 'equivalent_temperature: ', 1.0 - (pi[0]/15.08)**2
# graph properties
if(xlim!='None'):
ax.set_xlim(xlim[0],xlim[1])
if(ylim!='None'):
ax.set_ylim(ylim[0],ylim[1])
if(legend!='None'):
plt.legend(legend,loc=legendLoc)
# show the graph
if(show):
plt.show()
def create_temperature_graph(simDirs,
legend='None',
width=3,
xlabel='',
ylabel='',
show=True,
figPath='',
borders='None',
legendLoc='lower right',
xlim='None',
ylim='None'):
'''
@description: create a graph with the temperature
at the interface for different conditions
'''
# figure initialization
plt.close("all")
plt.rc('text', usetex=True)
plt.rc('font', family='serif')
fig = plt.figure(figsize=(8,6))
ax = fig.add_subplot(111)
for i in range(0,len(simDirs)):
temperature = np.loadtxt(os.path.join(simDirs[i],'temperature.txt'))
# data plotted
if(borders!='None'):
i_start = borders[i][0]
i_end = borders[i][1]
else:
for j in range(0,len(temperature[:,0])):
if(temperature[j,1]>0):
i_start = j
break
for j in range(len(temperature[:,0])-1,0,-1):
if(temperature[j,1]>0):
i_end = j
break
# color
grayscale_value = 0.2+ 0.8*float(i)/float(len(simDirs))
# plot
plt.plot(temperature[i_start:i_end,1],
temperature[i_start:i_end,2],
'-',
linewidth=width,
color=grayscale_to_RGB(grayscale_value))
ax.set_xlabel(r''+xlabel)
ax.set_ylabel(r''+ylabel)
# graph properties
if(xlim!='None'):
ax.set_xlim(xlim[0],xlim[1])
if(ylim!='None'):
ax.set_ylim(ylim[0],ylim[1])
if(legend!='None'):
plt.legend(legend,loc=legendLoc)
# show the graph
if(show):
plt.show()
def create_nucleation_time_graph(dirs,
velocities,
styles,
legend='None',
legendLoc='lower right',
width=3,
xlabel='$v$',
ylabel='$t_n$',
bothDirs=False,
show=True):
'''
@description: create a graph with the nucleation times
for different velocities and fluxes
- dirs : 2D array containing the directory paths
- styles : array with the style corresponding to dirs[i]
- leg : legend for dirs[i]
- width : width of the lines
- xlabel : xlabel for the plot
- ylabel : ylabel for the plot
- show : show the plot at the end
'''
plt.close("all")
plt.rc('text', usetex=True)
plt.rc('font', family='serif')
fig = plt.figure(figsize=(8,6))
ax = fig.add_subplot(111)
i=0
for simDirs,simVelocities,simStyle in zip(dirs,velocities,styles):
# determine the color for the plot
if(bothDirs):
grayscale_value = 0.2+ 0.8*float(i%(len(dirs)/2))/float(len(dirs)/2)
else:
grayscale_value = 0.2+ 0.8*float(i)/float(len(dirs))
simColor = grayscale_to_RGB(grayscale_value)
# array containing the data at fixed flux
x_data = []
y_data = []
for simDir,simVelocity in zip(simDirs,simVelocities):
# get the nucleation time and mass
mass = np.loadtxt(os.path.join(simDir,'contours','mass.txt'))
for j in range(0,len(mass[:,0])):
if(mass[j,2]>0):
nucleation_time = mass[j,1]
nucleation_mass = mass[j,2]
break
# extract the velocity corresponding to the directory
# it is simVelocity
# create the corresponding database for plotting
x_data.append(simVelocity)
y_data.append(nucleation_time)
# plot the data
plt.plot(x_data,
y_data,
simStyle,
linewidth=width,
color=simColor)
i+=1
ax.set_xlabel(r''+xlabel)
ax.set_ylabel(r''+ylabel)
if(legend!='None'):
plt.legend(legend,loc=legendLoc)
if(show):
plt.show()
plt.close()
