CODEWITHSUNDEEP
python-3.xnumpymatplotlib
IRobo
IRobo

Reputation: 23

ValueError: Invalid RGBA argument. Why it can be? How can I fix it?

I'm trying to create a simple cube following this code:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np


# Create axis
axes = [5,5,5]

# Create Data
data = np.ones(axes, dtype=np.bool)

# Controll Tranperency
alpha = 0.9

# Control colour RGBA colour
colors = np.empty(axes + [4], dtype=np.float32)

colors[0] = [1, 0, 0, alpha] # red
colors[1] = [0, 1, 0, alpha] # green
colors[2] = [0, 0, 1, alpha] # blue
colors[3] = [1, 1, 0, alpha] # yellow
colors[4] = [1, 1, 1, alpha] # grey

# Plot figure
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

# Voxels are used for customizations of sizes, positions, and colors.
ax.voxels(data, facecolors=colors, edgecolors='grey')
plt.show()

It works well. But when I change axes = [10, 10, 10], here is the code:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np


# Create axis
axes = [10, 10, 10]

# Create Data
data = np.ones(axes, dtype=np.bool)

# Controll Tranperency
alpha = 0.9

# Control colour RGBA colour
colors = np.empty(axes + [4], dtype=np.float32)

colors[0] = [1, 0, 0, alpha] # red
colors[1] = [0, 1, 0, alpha] # green
colors[2] = [0, 0, 1, alpha] # blue
colors[3] = [1, 1, 0, alpha] # yellow
colors[4] = [1, 1, 1, alpha] # grey

# Plot figure
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

# Voxels are used for customizations of sizes, positions, and colors.
ax.voxels(data, facecolors=colors, edgecolors='grey')
plt.show()

sometimes it works, sometimes it doesn't, and throw the error: ValueError: Invalid RGBA argument: 4.435719e+27. The same error when I remove dtype in data = np.ones(axes, type=np.bool). Now I am unable to debug the Invalid RGBA argument because I don't understand what is causing the error. I read this, but it seems that error about invalid shape, not invalid value.

Why can this error happen? How can I fix it? Thank you very much.

Upvotes: 2

Views: 4527

Answers (1)

Ofer Sadan
Ofer Sadan

Reputation: 11992

You're getting this error because np.empty created basically randomly filled arrays (sometimes uses empty memory space, which is why it sometimes will work for you). This isn't a problem with axes = [5, 5, 5] because you're filling out proper RGBA values when you assign colors, but with bigger axes it wont work as well.

Look at the result of printing colors when axes is [5, 5, 5] vs. the times it doesn't work for you with [10, 10, 10]

To fix: use np.zeros instead of np.empty to make sure zeros is what you get for missing values:

axes = [10, 10, 10]
colors = np.zeros(axes + [4], dtype=np.float32)

Upvotes: 3

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