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)