Datasets:
Formats:
webdataset
Languages:
English
Size:
10K - 100K
Tags:
graph-neural-networks
kuramoto-oscillators
basin-stability
power-grids
physics
long-range-dependencies
License:
Update README.md
Browse files
README.md
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@@ -101,6 +101,7 @@ To load and access data conveniently, first unpack the provided `.tar` file:
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```bash
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tar -xvf num_sections_20.tar
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Then, for example, load .h5 files in Python:
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@@ -108,4 +109,5 @@ Then, for example, load .h5 files in Python:
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with h5py.File('num_sections_20/ds20/heatmap_grid_00001.h5', 'r') as f:
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basin_heatmap_node1 = np.array(f['basin_heatmap_1'])
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samples_heatmap_node1 = np.array(f['samples_heatmap_1'])
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print(basin_heatmap_node1.shape) # (20, 20)
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```bash
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tar -xvf num_sections_20.tar
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```
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Then, for example, load .h5 files in Python:
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with h5py.File('num_sections_20/ds20/heatmap_grid_00001.h5', 'r') as f:
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basin_heatmap_node1 = np.array(f['basin_heatmap_1'])
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samples_heatmap_node1 = np.array(f['samples_heatmap_1'])
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print(basin_heatmap_node1.shape) # (20, 20)
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```
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