I am trying to draw some objects with the fabulous Matplotlib package for Python. These objects consist of points implemented with plt.scatter()
and patches implemented with Poly3DCollection
. I would like to have the patches with a slight transparency so that the points and edges behind the patches can be seen.
Here the code and plot I already generated. Seems I am almost there, just missing the feature of transparency. Interestingly, if I first plot the Ploy3DCollection
and afterwards the scatter
points, the points can be seen, but not the edges.
Anyone having a suggestion for me?
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = [0, 2, 1, 1]
y = [0, 0, 1, 0]
z = [0, 0, 0, 1]
vertices = [[0, 1, 2], [0, 1, 3], [0, 2, 3], [1, 2, 3]]
tupleList = list(zip(x, y, z))
poly3d = [[tupleList[vertices[ix][iy]] for iy in range(len(vertices[0]))] for ix in range(len(vertices))]
ax.scatter(x,y,z)
ax.add_collection3d(Poly3DCollection(poly3d, facecolors='w', linewidths=1, alpha=0.5))
plt.show()
Matplotlib allows you to regulate the transparency of a graph plot using the alpha attribute. By default, alpha=1. If you would like to form the graph plot more transparent, then you'll make alpha but 1, such as 0.5 or 0.25.
Matplotlib allows you to adjust the transparency of a graph plot using the alpha attribute. If you want to make the graph plot more transparent, then you can make alpha less than 1, such as 0.5 or 0.25. If you want to make the graph plot less transparent, then you can make alpha greater than 1.
MatPlotLib with Python Create x_data and y_data(sin(x_data)), using numpy. Plot curve using x_data and y_data, with marker style and marker size. By changing the alpha, we can make it transparent to opaque.
Inmatplotlib, the plots have a parameter, alpha= to change transparency.
I made a slight modification to the OP code and got the transparency working. It appears that the facecolors argument of Poly3DCollection overrides the transparency argument, so the solution was to set the color in a separate call to either Poly3DCollection.set_color
or Poly3DCollection.set_facecolor
:
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = [0, 2, 1, 1]
y = [0, 0, 1, 0]
z = [0, 0, 0, 1]
vertices = [[0, 1, 2], [0, 1, 3], [0, 2, 3], [1, 2, 3]]
tupleList = zip(x, y, z)
poly3d = [[tupleList[vertices[ix][iy]] for iy in range(len(vertices[0]))] for ix in range(len(vertices))]
ax.scatter(x,y,z)
collection = Poly3DCollection(poly3d, linewidths=1, alpha=0.2)
face_color = [0.5, 0.5, 1] # alternative: matplotlib.colors.rgb2hex([0.5, 0.5, 1])
collection.set_facecolor(face_color)
ax.add_collection3d(collection)
plt.show()
Interestingly, if you explicitly set the edge color with collection.set_edgecolor('k')
, the edges will also honor the transparency setting.
I found a nice workaround: After plotting the data, do another plot on top with the same color and lighter line style. Instead of Poly3DCollection
I use Line3DCollection
, so no faces are plotted. The result looks very much as anticipated.
See below the new plot and the script creating it.
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d.art3d import Poly3DCollection, Line3DCollection
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = [0, 2, 1, 1]
y = [0, 0, 1, 0]
z = [0, 0, 0, 1]
vertices = [[0, 1, 2], [0, 1, 3], [0, 2, 3], [1, 2, 3]]
tupleList = list(zip(x, y, z))
poly3d = [[tupleList[vertices[ix][iy]] for iy in range(len(vertices[0]))] for ix in range(len(vertices))]
ax.scatter(x,y,z)
ax.add_collection3d(Poly3DCollection(poly3d, facecolors='w', linewidths=1, alpha=0.5))
ax.add_collection3d(Line3DCollection(poly3d, colors='k', linewidths=0.2, linestyles=':'))
plt.show()
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With