fmda/visualizations.ipynb

   1 {
   2  "cells": [
   3   {
   4    "cell_type": "code",
   5    "execution_count": null,
   6    "id": "dd71eb39-f938-440e-99a8-3dc02ee55102",
   7    "metadata": {},
   8    "outputs": [],
   9    "source": [
  10     "from utils import read_pkl\n",
  11     "from data_funcs import combine_nested\n",
  12     "import pandas as pd\n",
  13     "import matplotlib.pyplot as plt\n",
  14     "import plotly.express as px\n",
  15     "import plotly.graph_objects as go\n",
  16     "import numpy as np\n",
  17     "from mpl_toolkits.basemap import Basemap\n",
  18     "from matplotlib.patches import Polygon\n",
  19     "import os.path as osp"
  20    ]
  21   },
  22   {
  23    "cell_type": "code",
  24    "execution_count": null,
  25    "id": "f8ac5c75-a590-4dae-8a5f-737c8833af1e",
  26    "metadata": {},
  27    "outputs": [],
  28    "source": []
  29   },
  30   {
  31    "cell_type": "code",
  32    "execution_count": null,
  33    "id": "4197b2ae-d8e3-4878-b87b-795f7622c753",
  34    "metadata": {},
  35    "outputs": [],
  36    "source": [
  37     "# dat = read_pkl(\"train.pkl\")\n",
  38     "dat = read_pkl(\"data/fmda_rocky_202403-05_f05.pkl\")"
  39    ]
  40   },
  41   {
  42    "cell_type": "code",
  43    "execution_count": null,
  44    "id": "28dcf75e-2fad-4fc5-8deb-354f1e31a472",
  45    "metadata": {},
  46    "outputs": [],
  47    "source": [
  48     "dat['CPTC2_202403'].keys()"
  49    ]
  50   },
  51   {
  52    "cell_type": "code",
  53    "execution_count": null,
  54    "id": "d28d3760-92ad-4e14-90fd-69020c2c4b56",
  55    "metadata": {},
  56    "outputs": [],
  57    "source": [
  58     "# NW GACC\n",
  59     "bbox = [37, -111, 46, -95]"
  60    ]
  61   },
  62   {
  63    "cell_type": "code",
  64    "execution_count": null,
  65    "id": "189ab08a-06f5-4758-8d9f-ee95e5cafa70",
  66    "metadata": {},
  67    "outputs": [],
  68    "source": [
  69     "data = []\n",
  70     "for key in dat:\n",
  71     "    loc_data = dat[key]['loc']\n",
  72     "    data.append([loc_data['STID'], loc_data['lat'], loc_data['lon']])\n",
  73     "\n",
  74     "df = pd.DataFrame(data, columns=['STID', 'lat', 'lon'])\n",
  75     "df"
  76    ]
  77   },
  78   {
  79    "cell_type": "code",
  80    "execution_count": null,
  81    "id": "4c04a46d-7096-4fad-8c20-807e409f8f80",
  82    "metadata": {},
  83    "outputs": [],
  84    "source": [
  85     "def make_st_map_interactive(df):\n",
  86     "    fig = go.Figure(go.Scattermapbox(\n",
  87     "        lat=df['lat'],\n",
  88     "        lon=df['lon'],\n",
  89     "        mode='markers',\n",
  90     "        marker=go.scattermapbox.Marker(\n",
  91     "            size=10,\n",
  92     "            opacity=0.7,\n",
  93     "        ),\n",
  94     "        text=df['STID'],\n",
  95     "        name='',\n",
  96     "        showlegend=False  # Turn off legend\n",
  97     "    ))\n",
  98     "\n",
  99     "    # Add Points\n",
 100     "    center_lon=df['lon'].median()\n",
 101     "    center_lat=df['lat'].median()\n",
 102     "    fig.update_layout(\n",
 103     "        mapbox_style=\"open-street-map\",\n",
 104     "        mapbox_center=dict(lat=center_lat, lon=center_lon)\n",
 105     "    )\n",
 106     "    # Add Lines for Bounding Box\n",
 107     "    \n",
 108     "    fig.add_trace(go.Scattermapbox(\n",
 109     "        mode=\"lines\",\n",
 110     "        lon=[df['lon'].min(), df['lon'].min(), df['lon'].max(), df['lon'].max(), df['lon'].min()],\n",
 111     "        lat=[df['lat'].min(), df['lat'].max(), df['lat'].max(), df['lat'].min(), df['lat'].min()],\n",
 112     "        marker=dict(size=5, color=\"black\"),\n",
 113     "        line=dict(width=1.5, color=\"black\"),\n",
 114     "        showlegend=False\n",
 115     "    ))\n",
 116     "    \n",
 117     "    fig.update_layout(\n",
 118     "        margin={\"r\":0,\"t\":0,\"l\":0,\"b\":0},\n",
 119     "        mapbox_zoom =5,\n",
 120     "        mapbox_center={\"lat\": np.median(df.lat), \"lon\": np.median(df.lon)},  # Center the map on desired location\n",
 121     "        width=1000,\n",
 122     "        height=800\n",
 123     "    )\n",
 124     "    return fig"
 125    ]
 126   },
 127   {
 128    "cell_type": "code",
 129    "execution_count": null,
 130    "id": "1fd6cfd9-8ce5-44a8-a618-fc06ba898666",
 131    "metadata": {},
 132    "outputs": [],
 133    "source": [
 134     "make_st_map_interactive(df)"
 135    ]
 136   },
 137   {
 138    "cell_type": "code",
 139    "execution_count": null,
 140    "id": "39374ba7-e4fb-4a7d-a9b0-7bca76e2f950",
 141    "metadata": {},
 142    "outputs": [],
 143    "source": [
 144     "st = \"TGSK1_202403\""
 145    ]
 146   },
 147   {
 148    "cell_type": "code",
 149    "execution_count": null,
 150    "id": "62053cfb-d882-4044-90c5-38165572596e",
 151    "metadata": {},
 152    "outputs": [],
 153    "source": [
 154     "fig, ax = plt.subplots()\n",
 155     "plt.title(f\"RAWS Station {st}\")\n",
 156     "ax.plot(dat[st]['RAWS']['fm'][0:500], linestyle='-',c='#468a29',label='FMC Observed')\n",
 157     "plt.legend(loc='upper right')\n",
 158     "ax.set_ylabel(\"Fuel Moisture Content (%)\")\n",
 159     "ax.set_xlabel(\"Hour\")\n",
 160     "plt.savefig(\"outputs/fmc_plot2.png\")\n",
 161     "# Increase the thickness of the axis borders\n",
 162     "ax.spines['top'].set_linewidth(1.5)\n",
 163     "ax.spines['bottom'].set_linewidth(1.5)\n",
 164     "ax.spines['left'].set_linewidth(1.5)\n",
 165     "ax.spines['right'].set_linewidth(1.5)\n",
 166     "\n",
 167     "# plt.savefig(\"outputs/fmc_plot2.png\")"
 168    ]
 169   },
 170   {
 171    "cell_type": "markdown",
 172    "id": "d9aba79a-70b0-4fdb-aeaf-bc593daa0bda",
 173    "metadata": {},
 174    "source": [
 175     "## Plot Tif Files Remotely"
 176    ]
 177   },
 178   {
 179    "cell_type": "code",
 180    "execution_count": null,
 181    "id": "6e5ce074-d1c6-4521-857e-d31aec07f88b",
 182    "metadata": {},
 183    "outputs": [],
 184    "source": [
 185     "url = \"https://demo.openwfm.org/web/data/fmda/tif/20210428/\"\n",
 186     "tif_files = [\"hrrr.t00z.wrfprsf00.629.tif\", \"hrrr.t00z.wrfprsf01.629.tif\",\n",
 187     "            \"hrrr.t00z.wrfprsf03.629.tif\", \"hrrr.t00z.wrfprsf06.629.tif\"]"
 188    ]
 189   },
 190   {
 191    "cell_type": "code",
 192    "execution_count": null,
 193    "id": "0d5d84da-39ce-46b6-ade1-5afb774e9159",
 194    "metadata": {},
 195    "outputs": [],
 196    "source": [
 197     "import rasterio\n",
 198     "from rasterio.plot import show\n",
 199     "import matplotlib.pyplot as plt"
 200    ]
 201   },
 202   {
 203    "cell_type": "code",
 204    "execution_count": null,
 205    "id": "08d8d690-fdaa-479f-a597-77f2fa4aace9",
 206    "metadata": {},
 207    "outputs": [],
 208    "source": [
 209     "with rasterio.open(osp.join(url, tif_files[0])) as dataset:\n",
 210     "    # Plot the dataset\n",
 211     "    fig, ax = plt.subplots()\n",
 212     "    show(dataset, ax=ax)\n",
 213     "    plt.show()    "
 214    ]
 215   },
 216   {
 217    "cell_type": "code",
 218    "execution_count": null,
 219    "id": "7cfd568d-30d9-4a0a-b83a-9b500fced3b4",
 220    "metadata": {},
 221    "outputs": [],
 222    "source": [
 223     "with rasterio.open(osp.join(url, tif_files[2])) as dataset:\n",
 224     "    # Plot the dataset\n",
 225     "    fig, ax = plt.subplots()\n",
 226     "    show(dataset, ax=ax)\n",
 227     "    plt.show()    "
 228    ]
 229   },
 230   {
 231    "cell_type": "code",
 232    "execution_count": null,
 233    "id": "1ca98402-5fa4-4383-8798-969db67f7352",
 234    "metadata": {},
 235    "outputs": [],
 236    "source": []
 237   },
 238   {
 239    "cell_type": "code",
 240    "execution_count": null,
 241    "id": "86d94b91-fbb4-47fb-bba0-e41551f361b5",
 242    "metadata": {},
 243    "outputs": [],
 244    "source": []
 245   }
 246  ],
 247  "metadata": {
 248   "kernelspec": {
 249    "display_name": "Python 3 (ipykernel)",
 250    "language": "python",
 251    "name": "python3"
 252   },
 253   "language_info": {
 254    "codemirror_mode": {
 255     "name": "ipython",
 256     "version": 3
 257    },
 258    "file_extension": ".py",
 259    "mimetype": "text/x-python",
 260    "name": "python",
 261    "nbconvert_exporter": "python",
 262    "pygments_lexer": "ipython3",
 263    "version": "3.12.5"
 264   }
 265  },
 266  "nbformat": 4,
 267  "nbformat_minor": 5
 268 }