from matplotlib.gridspec import GridSpec import matplotlib.pyplot as plt import numpy as np from plotting.paramplotter import ParamPlotter from dataset import Dataset import datasets.peakstransfer as transfer fig = plt.figure(figsize=[8, 6]) gs = GridSpec(1, 1) ax = fig.add_subplot(gs[0, 0]) dataset = Dataset(1, 1) splineInterval = np.array([0.0, 1.0]) t = transfer.createTransferFunction() p = ParamPlotter(ax, splineInterval, precision=1000) cax = p.plotScalarField(dataset.rho, t) ax.set_aspect('equal') cbar = fig.colorbar(cax, ticks=[0.0, 1.0]) cbar.ax.set_yticklabels(['0.0', '1.0']) # Workaround for the ticks being converted to integers cbar.solids.set_edgecolor('face') # Removes buggy lines in vector graphics fig.tight_layout() plt.savefig("output/vg/scalartransfer.pdf", format="pdf", transparent=True)
import matplotlib.pyplot as plt import numpy as np from plotting.paramplotter import ParamPlotter from dataset import Dataset def transfer(x): return np.array([x, x, x, 1.0]) fig = plt.figure(figsize=[6, 6]) dataset = Dataset(1, 1) splineInterval = np.array([0.0, 1.0]) p = ParamPlotter(plt, splineInterval) p.plotScalarField(dataset.rho, transfer) fig.tight_layout() plt.savefig("output/vg/scalar.pdf", format="pdf", transparent=True)