deeplearning/modulus/modulus-core-v021/_modules/modulus/utils/graphcast/icospheres.html

Core v0.2.1

Source code for modulus.utils.graphcast.icospheres

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# Licensed under the Apache License, Version 2.0 (the "License");
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#     http://www.apache.org/licenses/LICENSE-2.0
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import numpy as np
import json

try:
    import pymesh
except ImportError:
    Warning("pymesh is not installed. Please install it to use icosphere.")

# TODO apply a transformation to make faces parallel to ploes


[docs]def generate_and_save_icospheres( save_path: str = "icospheres.json", level: int = 6 ) -> None: # pragma: no cover """enerate icospheres from level 0 to 6 (inclusive) and save them to a json file. Parameters ---------- path : str Path to save the json file. """ radius = 1 center = np.array((0, 0, 0)) icospheres = {"vertices": [], "faces": []} # Generate icospheres from level 0 to 6 (inclusive) for order in range(level + 1): icosphere = pymesh.generate_icosphere(radius, center, refinement_order=order) icospheres["order_" + str(order) + "_vertices"] = icosphere.vertices icospheres["order_" + str(order) + "_faces"] = icosphere.faces icosphere.add_attribute("face_centroid") icospheres[ "order_" + str(order) + "_face_centroid" ] = icosphere.get_face_attribute("face_centroid") # save icosphere vertices and faces to a json file icospheres_dict = { key: (value.tolist() if isinstance(value, np.ndarray) else value) for key, value in icospheres.items() } with open(save_path, "w") as f: json.dump(icospheres_dict, f)

if __name__ == "__main__": generate_and_save_icospheres(level=6)

© Copyright 2023, NVIDIA Modulus Team. Last updated on Sep 21, 2023.