vAPE - Interactive 4D volume visualization

👉 Click to run the web app 👈

Burgers	Kuramoto–Sivashinsky	Gray-Scott

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Installation

with pip

pip install vape4d

or, alternatively, using conda

conda install conda-forge::vape4d

Usage

Viewer (jupyter notebook)

from vape4d import viewer
import numpy as np
from matplotlib import pyplot as plt

viewer(
    #[T,C,D,W,H]
    np.random.rand(1,1,32,32,32),
    plt.get_cmap("viridis"),   
)

Render Image

import numpy as np
from vape4d import diverging_alpha, render
import matplotlib.pyplot as plt

colormap = diverging_alpha(plt.get_cmap("magma"))
img = render(
        # [T,D,H,W]
        np.random.rand(2,32,32,32).astype(np.float32),
        colormap,
        0.5, # timestep
        width=1024,
        height=1024,
    )

plt.imshow(img)
plt.axis("off")

plt.savefig("test.png", bbox_inches="tight", pad_inches=0)
plt.show()

Citation

This package was developed as part of the APEBench paper (arxiv.org/abs/2411.00180) (accepted at NeurIPS 2024). If you find it useful for your research, please consider citing it:

@article{koehler2024apebench,
  title={{APEBench}: A Benchmark for Autoregressive Neural Emulators of {PDE}s},
  author={Felix Koehler and Simon Niedermayr and R{\"}udiger Westermann and Nils Thuerey},
  journal={Advances in Neural Information Processing Systems (NeurIPS)},
  volume={38},
  year={2024}
}

(Feel free to also give the project a star on GitHub if you like it.)