Plaid datasets
Collection
A collection of datasets of physics problems, easily convertible in [PLAID](https://plaid-lib.readthedocs.io/) format
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15 items
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Updated
sample
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"gASV8gIAAAAAAAB9lCiMDm1lc2hfYmFzZV9uYW1llIwEQmFzZZSMDm1lc2hfem9uZV9uYW1llIwEWm9uZZSMBm1lc2hlc5R9lCi(...TRUNCATED) |
"gASV8gIAAAAAAAB9lCiMDm1lc2hfYmFzZV9uYW1llIwEQmFzZZSMDm1lc2hfem9uZV9uYW1llIwEWm9uZZSMBm1lc2hlc5R9lCi(...TRUNCATED) |
"gASV8gIAAAAAAAB9lCiMDm1lc2hfYmFzZV9uYW1llIwEQmFzZZSMDm1lc2hfem9uZV9uYW1llIwEWm9uZZSMBm1lc2hlc5R9lCi(...TRUNCATED) |
"gASV8gIAAAAAAAB9lCiMDm1lc2hfYmFzZV9uYW1llIwEQmFzZZSMDm1lc2hfem9uZV9uYW1llIwEWm9uZZSMBm1lc2hlc5R9lCi(...TRUNCATED) |
"gASV8gIAAAAAAAB9lCiMDm1lc2hfYmFzZV9uYW1llIwEQmFzZZSMDm1lc2hfem9uZV9uYW1llIwEWm9uZZSMBm1lc2hlc5R9lCi(...TRUNCATED) |
"gASV8gIAAAAAAAB9lCiMDm1lc2hfYmFzZV9uYW1llIwEQmFzZZSMDm1lc2hfem9uZV9uYW1llIwEWm9uZZSMBm1lc2hlc5R9lCi(...TRUNCATED) |
"gASV8gIAAAAAAAB9lCiMDm1lc2hfYmFzZV9uYW1llIwEQmFzZZSMDm1lc2hfem9uZV9uYW1llIwEWm9uZZSMBm1lc2hlc5R9lCi(...TRUNCATED) |
"gASV8gIAAAAAAAB9lCiMDm1lc2hfYmFzZV9uYW1llIwEQmFzZZSMDm1lc2hfem9uZV9uYW1llIwEWm9uZZSMBm1lc2hlc5R9lCi(...TRUNCATED) |
"gASV8gIAAAAAAAB9lCiMDm1lc2hfYmFzZV9uYW1llIwEQmFzZZSMDm1lc2hfem9uZV9uYW1llIwEWm9uZZSMBm1lc2hlc5R9lCi(...TRUNCATED) |
"gASV8gIAAAAAAAB9lCiMDm1lc2hfYmFzZV9uYW1llIwEQmFzZZSMDm1lc2hfem9uZV9uYW1llIwEWm9uZZSMBm1lc2hlc5R9lCi(...TRUNCATED) |
This dataset contains a single huggingface split, named 'all_samples'.
The samples contains a single huggingface feature, named called "sample".
Samples are instances of plaid.containers.sample.Sample. Mesh objects included in samples follow the CGNS standard, and can be converted in Muscat.Containers.Mesh.Mesh.
Example of commands:
import pickle
from datasets import load_dataset
from plaid.containers.sample import Sample
# Load the dataset
dataset = load_dataset("chanel/dataset", split="all_samples")
# Get the first sample of the first split
split_names = list(dataset.description["split"].keys())
ids_split_0 = dataset.description["split"][split_names[0]]
sample_0_split_0 = dataset[ids_split_0[0]]["sample"]
plaid_sample = Sample.model_validate(pickle.loads(sample_0_split_0))
print("type(plaid_sample) =", type(plaid_sample))
print("plaid_sample =", plaid_sample)
# Get a field from the sample
field_names = plaid_sample.get_field_names()
field = plaid_sample.get_field(field_names[0])
print("field_names[0] =", field_names[0])
print("field.shape =", field.shape)
# Get the mesh and convert it to Muscat
from Muscat.Bridges import CGNSBridge
CGNS_tree = plaid_sample.get_mesh()
mesh = CGNSBridge.CGNSToMesh(CGNS_tree)
print(mesh)
This dataset contains 2D dynamic non-linear structural mechanics with a non-linear non-local constitutive law.
The variablity in the samples is the geometry (mesh). Outputs of interest are 3 transient fields: x and y components of the displacement at the nodes and the erosion status at the elements.
Dataset created using the PLAID library and datamodel, version 0.1.