vs = [nh, tem, L, dt]
for i in range(3):
vs[i] = cfd.safe_log10(vs[i])
vsminmax = [[-0.87, 6.89],
[None, None],
[None, None],
[0, 20]]
### Plotting
plotter = TorchPlotter(cfd, plot_size=5, figformat=fformat, dpi=300)
### Interpolation set up.
vsi = []
for i in range(4):
vsi.append(cfd.interpolate(vs[i], 'nearest'))
vsminmax[i][0] = (vs[i].min() if vsminmax[i][0] == None else vsminmax[i][0])
vsminmax[i][1] = (vsi[i].max() if vsminmax[i][1] == None else vsminmax[i][1])
### Image.
vs_types = ['nH', 'energy', 'lambda', 'dtcool']
grid = plotter.twobytwo(vs_types, vsi, vsminmax, hgspy.get_green_map(), detail="all")
for i in range(4):
for axis in ['top','bottom','left','right']:
grid[i].spines[axis].set_linewidth(0.5)
grid.cbar_axes[i].spines[axis].set_linewidth(0.5)
grid.cbar_axes[0].set_xlabel(r"$\mathregular{log_{10}(n_H}$ / $\mathregular{cm^{-3})}$")
grid.cbar_axes[1].set_xlabel(r"$\mathregular{log_{10}(E}$ / $\mathregular{ergs.cm^{-3})}$")
grid.cbar_axes[2].set_xlabel(r"$\mathregular{log_{10}(\Lambda}$ / $\mathregular{ergs.s^{-1}.cm^{3})}$")
grid.cbar_axes[3].set_xlabel(r"$\mathregular{dt}$ / $\mathregular{yrs}$")
args = parser.parse_args()
input_dir = args.input_dir
if not input_dir.endswith('/'):
input_dir += '/'
input_regex = input_dir + '*.txt'
time = []
radius = []
for inputfile in glob.iglob(input_regex):
### Data set up.
torchData = TorchCFD(inputfile, axial=True)
den = torchData.get_var('den')
deni = torchData.interpolate(den, 'nearest')
### Find bubble radius.
index = 0
max_den = 0
for i in range(11, torchData.nx):
if deni[i,0] > max_den:
index = i
max_den = deni[i,0]
time.append(t)
radius.append(torchData.xi[0, index])
zipped = zip(time, radius)
zipped.sort()
time, radius = zip(*zipped)
