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visualuzation at scale notebook
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philipc2 committed Dec 2, 2023
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"source": [
"When working with large datasets, it's crucial to consider the performance of each visualization method. This notebook investigates the performance and data fidelity of the previously covered methods using high-resolution grids."
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"## Timing Comparison"
"The dataset used for timings and examples in this notebook were provided from the [DYAMOND Initiative](https://www.google.com/search?q=dyamond&oq=dyamond&gs_lcrp=EgZjaHJvbWUyCQgAEEUYORiABDIGCAEQIxgnMgcIAhAuGIAEMgkIAxAuGAoYgAQyCQgEEAAYChiABDIHCAUQLhiABDIHCAYQLhiABDIJCAcQABgKGIAEMgcICBAAGIAEMg8ICRAAGAoYgwEYsQMYgATSAQc5NjRqMGo0qAIAsAIA&sourceid=chrome&ie=UTF-8). \n",
"\n",
"There are four datasets, each of the same grid, but with different resolutions. The table below summarizes the scale of these datasets.\n",
"\n",
"| Element / Resolution | 30km | 15km | 7.5km | 3.75km |\n",
"|----------------------|------|-----|-------------|--------|\n",
"| Faces | 0 | 0 | 0 | 0 |\n",
"| Nodes | 0 | 0 | 0 | 0 |\n",
"\n",
"\n"
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"## Timing Comparison\n",
"\n",
"All timings were run on a single [NCAR Derecho Node](https://arc.ucar.edu/knowledge_base/74317833)"
],
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"### Data Processing (Initial Run)"
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"| Visualization Method / Grid Resolution | 30km | 15km | 7.5km | 3.75km |\n",
"|-----------------------------------------|-------------|-------------|-------------|-------------|\n",
"| Polygon Raster (Including Antimeridian) | 28.5 (1.26) | 0 | 0 | 0 |\n",
"| Polygon Raster (Excluding Antimeridian) | 1.69 (0.23) | 5.96 (0.09) | 23.1 (0.52) | 93 (1.01) |\n",
"| Point Raster | 0.13 (0.03) | 0.16 (0.01) | 0.35 (0.00) | 1.08 (0.07) |"
],
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"### Data Processing (Subsequent Runs)"
],
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