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a few more typos
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philipc2 committed Dec 10, 2023
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6 changes: 3 additions & 3 deletions notebooks/03-uxarray-vis/03-polygons.ipynb
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"## Conversion Methods\n",
"UXarray represents Unstructured Grids through a set of coordinate and connectivity variables (i.e. `node_lon`, `node_lat`, `face_node_connectivity`, etc.). These variables can be manipulated to obtain our Polygons for visualuzation"
"UXarray represents Unstructured Grids through a set of coordinate and connectivity variables (i.e. `node_lon`, `node_lat`, `face_node_connectivity`, etc.). These variables need to be manipulated to obtain geometries and data structures that are compatible with visualuzation libraries (i.e. HoloViews, Datashader, Matplotlib, etc.)"
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"### Representation as a `GeoDataFrame`\n",
"\n",
"Polygons are stored in a SpatialPandas `GeoDataFrame`, which is the expected data structured by the HoloViz stack of packages for visualizing polygons.\n",
"Each face is converted into a Polygon and stored within a SpatialPandas `GeoDataFrame`, which is the expected data structured by the HoloViz stack of packages for visualizing polygons.\n",
"\n"
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"If a data variable is not face-centered, it can be manipulated to get it to map to faces. For node-centered data, as is the case with our Geoflow dataset, we can perform a nodal-average operation, which takes the average all the nodes that saddle a face and use that value to shade the polygon.\n",
"If a data variable is not face-centered, it can be manipulated to become face-centered. For node-centered data, as is the case with our Geoflow dataset, we can perform a nodal-average operation, which takes the average all the nodes that surround a face and use that value to shade the polygon.\n",
"\n",
"Here we can also see that we need to index the `time` and `meshLayers` dimensions to obtain our 1D slice of data."
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10 changes: 10 additions & 0 deletions notebooks/03-uxarray-vis/06-performance.ipynb
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