vectorfieldviz
Visualization toolkit for linear vector fields defined by 2×2 and 3×3 matrices, with eigenanalysis utilities. Built on NumPy and Plotly.
Installation
pip install vectorfieldviz
Source = https://gitlab.com/algebra-done-visually/vectorfieldviz
2D
import numpy as np
from vectorfieldviz import plot_2d_vector_field, compute_eigendecomposition, plot_3d_vector_field
A = np.array([[0.0, 1.0, 1.0],
[1.0, 1.0, 1.0],
[1.0, 0.0, 0.0]])
fig = plot_3d_vector_field(A)
fig.show()
3D
import numpy as np
from vectorfieldviz import plot_2d_vector_field, compute_eigendecomposition, plot_3d_vector_field
A = np.array([[0.0, 1.0, 1.0],
[1.0, 1.0, 1.0],
[1.0, 0.0, 0.0]])
fig = plot_3d_vector_field(A)
fig.show()
Release files for vectorfieldviz 3.1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| vectorfieldviz-3.1.4.tar.gz | 8.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| vectorfieldviz-3.1.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.8 kB
Release files / vectorfieldviz-3.1.4.tar.gz
| Download URL | vectorfieldviz-3.1.4.tar.gz |
|---|---|
| Size | 8.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.9.13
|
Release files / vectorfieldviz-3.1.4-py3-none-any.whl
| Download URL | vectorfieldviz-3.1.4-py3-none-any.whl |
|---|---|
| Size | 10.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.9.13
|