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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,145 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Data Prep" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import geopandas as gpd\n", | ||
| "import xarray as xr\n", | ||
| "import numpy as np\n", | ||
| "\n", | ||
| "# Read county shapefile, combo of state FIPS code and county FIPS code as multi-index\n", | ||
| "counties = gpd.read_file(\n", | ||
| " \"https://www2.census.gov/geo/tiger/GENZ2020/shp/cb_2020_us_county_20m.zip\"\n", | ||
| ").to_crs(\"EPSG:3395\")\n", | ||
| "counties[\"STATEFP\"] = counties.STATEFP.astype(int)\n", | ||
| "counties[\"COUNTYFP\"] = counties.COUNTYFP.astype(int)\n", | ||
| "continental = counties[\n", | ||
| " ~counties[\"STATEFP\"].isin([2, 15, 72])\n", | ||
| "] # drop Alaska, Hawaii, Puerto Rico\n", | ||
| "\n", | ||
| "# Read in saved data from xarray-water-model.py\n", | ||
| "ds = xr.open_dataset(\"mean_zwattablrt_nwm_1979_2020.nc\")\n", | ||
| "ds[\"week\"] = ds.time.dt.strftime(\"%Y-%U\")\n", | ||
| "ds = ds.groupby(\"week\").mean()\n", | ||
| "# Interpret county as combo of state FIPS code and county FIPS code\n", | ||
| "ds.coords[\"STATEFP\"] = (ds.county // 1000).astype(int)\n", | ||
| "ds.coords[\"COUNTYFP\"] = np.mod(ds.county, 1000).astype(int)\n", | ||
| "df = ds.to_dataframe().reset_index()\n", | ||
| "\n", | ||
| "# Join\n", | ||
| "merge_df = continental.merge(df, on=[\"STATEFP\", \"COUNTYFP\"])" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Make all the plots" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import matplotlib.pyplot as plt\n", | ||
| "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", | ||
| "from datetime import datetime\n", | ||
| "\n", | ||
| "day_0 = datetime.strptime(weeks[0] + \"-0\", \"%Y-%U-%w\")\n", | ||
| "weeks = merge_df.week.unique()\n", | ||
| "\n", | ||
| "for week in weeks:\n", | ||
| " fig, ax = plt.subplots(1, 1, figsize=(7.68, 4.32)) # for 3840x2160 resolution\n", | ||
| "\n", | ||
| " ax.set_axis_off()\n", | ||
| "\n", | ||
| " divider = make_axes_locatable(ax)\n", | ||
| " cax = divider.append_axes(\"bottom\", size=\"5%\", pad=0.1)\n", | ||
| "\n", | ||
| " cax.tick_params(labelsize=8)\n", | ||
| " cax.set_title(\"Depth (in meters) of the water table\", fontsize=8)\n", | ||
| "\n", | ||
| " merge_df[merge_df[\"week\"] == f\"{week}\"].plot(\n", | ||
| " column=\"zwattablrt\",\n", | ||
| " cmap=\"BrBG_r\",\n", | ||
| " vmin=0,\n", | ||
| " vmax=2,\n", | ||
| " legend=True,\n", | ||
| " ax=ax,\n", | ||
| " cax=cax,\n", | ||
| " legend_kwds={\n", | ||
| " \"orientation\": \"horizontal\",\n", | ||
| " \"ticks\": [0, 0.5, 1, 1.5, 2],\n", | ||
| " },\n", | ||
| " )\n", | ||
| "\n", | ||
| " # Add legends for memory, time, and cost\n", | ||
| " current_day = datetime.strptime(week + \"-0\", \"%Y-%U-%w\")\n", | ||
| " n_days = (current_day - day_0).days\n", | ||
| " memory = n_days * (16.88 * 1.07374) # daily memory converted to GB\n", | ||
| " cost = (n_days / 7) * 0.01124606 # weekly cost\n", | ||
| "\n", | ||
| " if memory >= 1000:\n", | ||
| " memory_string = f\"{memory/1000:.1f} TB processed, ~${cost:.2f} in cloud costs\"\n", | ||
| " else:\n", | ||
| " memory_string = f\"{memory:.0f} GB processed, ~${cost:.2f} in cloud costs\"\n", | ||
| "\n", | ||
| " plt.text(0, 1, memory_string, transform=ax.transAxes, size=9)\n", | ||
| " # convert Year - Week Number to Month - Year\n", | ||
| " date = datetime.strptime(week + \"-0\", \"%Y-%U-%w\").strftime(\"%Y %b\")\n", | ||
| " plt.text(0.85, 1, f\"{date}\", transform=ax.transAxes, size=10)\n", | ||
| " plt.savefig(f\"../../nwm-animation/3840x2160/{week}.png\", transparent=True, dpi=500)\n", | ||
| " plt.close()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Use [ffmpeg](https://ffmpeg.org/) to stitch the images together" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# ffmpeg -pattern_type glob -i '3840x2160/*.png' -r 60 -crf 18 -pix_fmt yuv420p nwm-video.mp4" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "nwm", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.10.13" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } |
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