Open
Description
Issue
While plotting an np.ndarray of type fp64, it is not displayed.
It is so funny that we could reproduce it only for one specific array.
Thigs that make the script work:
- If we add epsilon (as in the commented line), then the pointcloud is displayed properly.
- If we cast to fp32 it works.
- If we add a small value (0.000000000001 for example), it works.
Things that doesn't work:
- If we add or substract big values, like 0.4, 1 or 2, it doesn't work
- If we substract epsilon, it doesn't work
- if we add numbers larger than 0.000000000001, it doesnt' work even if tehy are small (0.000001 for example)
Environment
We tried this (and reproduced in at least 2 computers) with numpy 1.26.3 and plotly 5.18.0 on ubuntu 22
import numpy as np
import plotly.graph_objects as go
init = np.array(
[
[
-0.063,
-0.063,
0.0,
],
[
-0.063,
-0.021,
0.0,
],
[
-0.063,
0.021,
0.0,
],
[
-0.063,
0.063,
0.0,
],
[
-0.021,
-0.021,
0.0,
],
[
-0.021,
-0.063,
0.0,
],
[
-0.021,
0.021,
0.0,
],
[
-0.021,
0.063,
0.0,
],
[
0.021,
-0.063,
0.0,
],
[
0.021,
-0.021,
0.0,
],
[
0.021,
0.021,
0.0,
],
[
0.021,
0.063,
0.0,
],
[
0.063,
-0.063,
0.0,
],
[
0.063,
-0.021,
0.0,
],
[
0.063,
0.021,
0.0,
],
[
0.063,
0.063,
0.0,
],
]
)
rot_mat = [
[4.93038066e-32, -1.00000000e00, 2.22044605e-16],
[2.22044605e-16, 2.22044605e-16, 1.00000000e00],
[-1.00000000e00, 0.00000000e00, 2.22044605e-16],
]
transformed = (rot_mat @ init.T).T + np.array([0.5, 0.5, 0.5])
x, y, z = 0, 1, 2
idx = list(transformed.shape).index(3)
if idx < 0:
raise ValueError("Array must be [X,Y,Z] x N")
elif idx == 1:
array = transformed.transpose()
default_kwargs = dict(
mode="markers",
marker=dict(size=3, color="black"),
)
print(array.dtype)
# array[y]+=np.finfo(np.float64).eps
print(array.dtype)
print(array)
plot = go.Scatter3d(x=array[x], y=array[y], z=array[z], **default_kwargs)
default_kwargs = dict(
scene=dict(
xaxis=dict(title="X", range=[0, 2]),
yaxis=dict(title="Y", range=[0, 2]),
zaxis=dict(title="Z", range=[0, 2]),
),
)
layout = go.Layout(**default_kwargs)
fig = go.Figure(data=plot, layout=layout)
fig.show()
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