parser.add_argument('inputfile', metavar='inputfile', type=str, help='Input file to produce image.') args = parser.parse_args() inputfile = args.inputfile outputfile = 'four-panel-champagne.' + figformat ### Data set up. datacubes = [] vs_types = [] vsminmax = [] for i in range(4): datacubes.append(torch.CFD_Data(inputfile, axial=False)) color_maps = [] color_maps.append(hgspy.get_density_cmap()) color_maps.append(hgspy.get_water_cmap()) color_maps.append(hgspy.get_temperature_cmap()) color_maps.append(hgspy.get_par_cmap()) vs_types = [] vs_types.append(torch.VarType("nh", isLog10=datacubes[0].appropriate_to_log("nh"))) vs_types.append(torch.VarType("pre", isLog10=datacubes[1].appropriate_to_log("pre"))) vs_types.append(torch.VarType("tem", isLog10=datacubes[2].appropriate_to_log("tem"))) vs_types.append(torch.VarType("hii", isLog10=datacubes[3].appropriate_to_log("hii"))) vsminmax = [] #vsminmax.append([3.5, 4.8]) #vsminmax.append([-10, -5]) #vsminmax.append([2 , 4])
torch.set_font_sizes(fontsize) inputfile = [] inputfile.append(dir + "data2D_15.txt") inputfile.append(dir + "data2D_45.txt") inputfile.append(dir + "data2D_65.txt") outputfile = 'multi-strickland2' + '.' + figformat ### Data set up. datacubes = [] vs_types = [] vsminmax = [] color_maps = [] cmap = hgspy.get_density_cmap(isReversed=False) for i in range(3): datacubes.append(torch.CFD_Data(inputfile[i], axial=False)) color_maps.append(cmap) vs_types.append(torch.VarType(var_type, isLog10=datacubes[i].appropriate_to_log(var_type))) vsminmax.append([-1.0, 3.0]) plotparams = torch.PlotParams(datacubes, vs_types, vsminmax, True, 'linear', (3, 1), color_maps, tight=False, detail="all") ### Plotting plotter = torch.Plotter(datacubes[0].nx, datacubes[0].ny, plot_size, figformat, DPI) ### Image. grid = plotter.multi(plotparams)