mirror of
https://github.com/Unidata/python-awips.git
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704 lines
1.1 MiB
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704 lines
1.1 MiB
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{
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"cells": [
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Python-AWIPS Tutorial Notebook"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"---\n",
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"\n",
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"\n",
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"# Objectives\n",
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"\n",
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"* Use python-awips to connect to an edex server\n",
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"* Define and filter data request for radar data\n",
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"* Plot NEXRAD 3 algorithm, precipitation, and derived products (not base data)\n",
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"\n",
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"---"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Table of Contents\n",
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"\n",
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"[1 Imports](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html#imports)<br> \n",
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"[2 EDEX Connection](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html#edex-connection)<br> \n",
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"[3 Investigate Data](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html#investigate-data)<br> \n",
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" [3.1 Available Locations](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html#available-locations)<br> \n",
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" [3.2 Available Parameters](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html#available-parameters)<br> \n",
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" [3.3 Radar Product IDs and Names](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html#radar-product-ids-and-names)<br> \n",
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"[4 Function: make_map()](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html#function-make-map)<br> \n",
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"[5 Plot the Data!](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html#plot-the-data)<br> \n",
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"[6 See Also](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html#see-also)<br> \n",
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" [6.1 Related Notebooks](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html#related-notebooks)<br> \n",
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" [6.2 Additional Documentation](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html#additional-documentation)<br> "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 1 Imports\n",
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"\n",
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"The imports below are used throughout the notebook. Note the first import is coming directly from python-awips and allows us to connect to an EDEX server. The subsequent imports are for data manipulation and visualization. "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import warnings\n",
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"from awips.dataaccess import DataAccessLayer\n",
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"import matplotlib.pyplot as plt\n",
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"import cartopy.crs as ccrs\n",
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"import numpy as np\n",
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"from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"[Top](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html)\n",
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"\n",
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"---"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 2 EDEX Connection\n",
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"\n",
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"First we establish a connection to Unidata's public EDEX server. This sets the proper server on the **DataAccessLayer**, which we will use numerous times throughout the notebook."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"DataAccessLayer.changeEDEXHost(\"edex-beta.unidata.ucar.edu\")\n",
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"request = DataAccessLayer.newDataRequest(\"radar\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"[Top](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html)\n",
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"\n",
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"---"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 3 Investigate Data\n",
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"\n",
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"Now that we've created a new radar data request, let's take a look at what locations and parameters are available for our current request."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 3.1 Available Locations\n",
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"\n",
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"We can take a look at what \"locations\" are available for our radar request. For radar, we'll see that radar station names are returned when looking at the availalbe location names.\n",
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"\n",
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"For this example we'll use Baltimore, MD/Washington DC as our region of interest. You can easily look up other station IDs and where they are using [this NWS webpage](https://radar.weather.gov/station/KMHX/standard)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['kabr', 'kabx', 'kakq', 'kama', 'kamx', 'kapx', 'karx', 'katx', 'kbbx', 'kbgm', 'kbhx', 'kbis', 'kblx', 'kbmx', 'kbox', 'kbro', 'kbuf', 'kbyx', 'kcae', 'kcbw', 'kcbx', 'kccx', 'kcle', 'kclx', 'kcrp', 'kcxx', 'kcys', 'kdax', 'kddc', 'kdfx', 'kdgx', 'kdix', 'kdlh', 'kdmx', 'kdox', 'kdtx', 'kdvn', 'kdyx', 'keax', 'kemx', 'kenx', 'keox', 'kepz', 'kesx', 'kevx', 'kewx', 'keyx', 'kfcx', 'kfdr', 'kfdx', 'kffc', 'kfsd', 'kfsx', 'kftg', 'kfws', 'kggw', 'kgjx', 'kgld', 'kgrb', 'kgrk', 'kgrr', 'kgsp', 'kgwx', 'kgyx', 'khdc', 'khdx', 'khgx', 'khnx', 'khpx', 'khtx', 'kict', 'kicx', 'kiln', 'kilx', 'kind', 'kinx', 'kiwa', 'kiwx', 'kjax', 'kjgx', 'kjkl', 'klbb', 'klch', 'klgx', 'klnx', 'klot', 'klrx', 'klsx', 'kltx', 'klvx', 'klwx', 'klzk', 'kmaf', 'kmax', 'kmbx', 'kmhx', 'kmkx', 'kmlb', 'kmob', 'kmpx', 'kmqt', 'kmrx', 'kmsx', 'kmtx', 'kmux', 'kmvx', 'kmxx', 'knkx', 'knqa', 'koax', 'kohx', 'kokx', 'kotx', 'kpah', 'kpbz', 'kpdt', 'kpoe', 'kpux', 'krax', 'krgx', 'kriw', 'krlx', 'krtx', 'ksfx', 'ksgf', 'kshv', 'ksjt', 'ksox', 'ksrx', 'ktbw', 'ktfx', 'ktlh', 'ktlx', 'ktwx', 'ktyx', 'kudx', 'kuex', 'kvax', 'kvbx', 'kvnx', 'kvtx', 'kvwx', 'kyux', 'pabc', 'pacg', 'paec', 'pahg', 'paih', 'pakc', 'papd', 'phki', 'phkm', 'phmo', 'phwa', 'rkjk', 'rksg', 'tadw', 'tatl', 'tbna', 'tbos', 'tbwi', 'tclt', 'tcmh', 'tcvg', 'tdal', 'tday', 'tdca', 'tden', 'tdfw', 'tdtw', 'tewr', 'tfll', 'thou', 'tiad', 'tiah', 'tich', 'tids', 'tjfk', 'tjua', 'tlas', 'tlve', 'tmci', 'tmco', 'tmdw', 'tmem', 'tmia', 'tmke', 'tmsp', 'tmsy', 'tokc', 'tord', 'tpbi', 'tphl', 'tphx', 'tpit', 'trdu', 'tsdf', 'tsju', 'tslc', 'tstl', 'ttpa', 'ttul']\n"
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]
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}
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],
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"source": [
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"available_locs = DataAccessLayer.getAvailableLocationNames(request)\n",
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"available_locs.sort()\n",
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"print(available_locs)\n",
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"\n",
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"# Set our location to Baltimore (klwx)\n",
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"request.setLocationNames(\"klwx\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 3.2 Available Parameters\n",
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"\n",
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"Next, let's look at the parameters returned from the available parameters request. If we look closely, we can see that some of the parameters appear different from the others."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['134', '135', '141', '153', '154', '159', '161', '163', '165', '166', '169', '170', '172', '173', '176', '177', '32', '37', '56', '57', '58', '81', '99', 'CC', 'CZ', 'Composite Refl', 'Correlation Coeff', 'DAA', 'DHR', 'DPA', 'DPR', 'DUA', 'DVL', 'Diff Reflectivity', 'Digital Hybrid Scan Refl', 'Digital Inst Precip Rate', 'Digital Precip Array', 'Digital Vert Integ Liq', 'EET', 'Enhanced Echo Tops', 'HC', 'HHC', 'HV', 'HZ', 'Hybrid Hydrometeor Class', 'Hydrometeor Class', 'KDP', 'MD', 'ML', 'Melting Layer', 'Mesocyclone', 'OHA', 'One Hour Accum', 'One Hour Unbiased Accum', 'Reflectivity', 'SRM', 'STA', 'STI', 'Specific Diff Phase', 'Storm Rel Velocity', 'Storm Total Accum', 'Storm Track', 'User Select Accum', 'V', 'VIL', 'Velocity', 'Vert Integ Liq', 'ZDR']\n"
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]
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}
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],
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"source": [
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"availableParms = DataAccessLayer.getAvailableParameters(request)\n",
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"availableParms.sort()\n",
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"print(availableParms)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 3.3 Radar Product IDs and Names\n",
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"\n",
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"As we saw above, some parameters seem to be describing different things from the rest. The DataAccessLayer has a built in function to parse the available parameters into the separate **Product IDs** and **Product Names**. Here, we take a look at the two different arrays that are returned when parsing the *availableParms* array we just recieved in the previous code cell."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['134', '135', '141', '153', '154', '159', '161', '163', '165', '166', '169', '170', '172', '173', '176', '177', '32', '37', '56', '57', '58', '81', '99']\n",
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"['Composite Refl', 'Correlation Coeff', 'Diff Reflectivity', 'Digital Hybrid Scan Refl', 'Digital Inst Precip Rate', 'Digital Precip Array', 'Digital Vert Integ Liq', 'Enhanced Echo Tops', 'Hybrid Hydrometeor Class', 'Hydrometeor Class', 'Melting Layer', 'Mesocyclone', 'One Hour Accum', 'One Hour Unbiased Accum', 'Reflectivity', 'Specific Diff Phase', 'Storm Rel Velocity', 'Storm Total Accum', 'Storm Track', 'User Select Accum', 'Velocity', 'Vert Integ Liq']\n"
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]
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}
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],
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"source": [
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"productIDs = DataAccessLayer.getRadarProductIDs(availableParms)\n",
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"productNames = DataAccessLayer.getRadarProductNames(availableParms)\n",
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"print(productIDs)\n",
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"print(productNames)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"[Top](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html)\n",
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"\n",
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"---"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 4 Function: make_map()\n",
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"\n",
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"In order to plot more than one image, it's easiest to define common logic in a function. Here, a new function called **make_map** is defined. This function uses the [matplotlib.pyplot package (plt)](https://matplotlib.org/3.3.3/api/_as_gen/matplotlib.pyplot.html) to create a figure and axis. The coastlines (continental boundaries) are added, along with lat/lon grids."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"def make_map(bbox, projection=ccrs.PlateCarree()):\n",
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" fig, ax = plt.subplots(figsize=(16, 16),\n",
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" subplot_kw=dict(projection=projection))\n",
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" ax.set_extent(bbox)\n",
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" ax.coastlines(resolution='50m')\n",
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" gl = ax.gridlines(draw_labels=True)\n",
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" gl.top_labels = gl.right_labels = False\n",
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" gl.xformatter = LONGITUDE_FORMATTER\n",
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" gl.yformatter = LATITUDE_FORMATTER\n",
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" return fig, ax"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"[Top](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html)\n",
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"\n",
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"---"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 5 Plot the Data!\n",
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"\n",
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"Here we'll create a plot for each of the Radar Product Names from our *productNames* array from the [previous section](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html#Radar-Product-IDs-and-Names)."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"Recs : 1\n",
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"Time : 2024-05-22 21:53:42\n",
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"Name : klwx_0.0_464_464\n",
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"Prod : Composite Refl\n",
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"Range: 5.0 to 60.0 (Unit : dBZ )\n",
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"Size : (464, 464)\n",
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"\n"
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]
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},
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{
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"data": {
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"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x1152 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"No levels found for Correlation Coeff\n",
|
||
|
|
"No levels found for Diff Reflectivity\n",
|
||
|
|
"\n",
|
||
|
|
"Recs : 1\n",
|
||
|
|
"Time : 2024-05-22 21:57:59\n",
|
||
|
|
"Name : klwx_0.0_230_360_0.0_359.0\n",
|
||
|
|
"Prod : Digital Hybrid Scan Refl\n",
|
||
|
|
"Range: -16.0 to 57.0 (Unit : dBZ )\n",
|
||
|
|
"Size : (230, 360)\n",
|
||
|
|
"\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x1152 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"\n",
|
||
|
|
"Recs : 1\n",
|
||
|
|
"Time : 2024-05-22 21:57:59\n",
|
||
|
|
"Name : klwx_0.0_920_360_0.0_359.0\n",
|
||
|
|
"Prod : Digital Inst Precip Rate\n",
|
||
|
|
"Range: 7.0555557e-09 to 4.0117888e-05 (Unit : m*sec^-1 )\n",
|
||
|
|
"Size : (920, 360)\n",
|
||
|
|
"\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x1152 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"\n",
|
||
|
|
"Recs : 1\n",
|
||
|
|
"Time : 2024-05-22 21:57:59\n",
|
||
|
|
"Name : klwx_0.0_13_13\n",
|
||
|
|
"Prod : Digital Precip Array\n",
|
||
|
|
"Range: -60.0 to 690.0 (Unit : count )\n",
|
||
|
|
"Size : (13, 13)\n",
|
||
|
|
"\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x1152 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"\n",
|
||
|
|
"Recs : 1\n",
|
||
|
|
"Time : 2024-05-22 21:53:42\n",
|
||
|
|
"Name : klwx_0.0_460_360_0.0_359.0\n",
|
||
|
|
"Prod : Digital Vert Integ Liq\n",
|
||
|
|
"Range: 0.0 to 46.34034 (Unit : kg*m^-2 )\n",
|
||
|
|
"Size : (460, 360)\n",
|
||
|
|
"\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
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|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x1152 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
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|
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},
|
||
|
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"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"\n",
|
||
|
|
"Recs : 1\n",
|
||
|
|
"Time : 2024-05-22 21:53:42\n",
|
||
|
|
"Name : klwx_0.0_346_360_0.0_359.0\n",
|
||
|
|
"Prod : Enhanced Echo Tops\n",
|
||
|
|
"Range: nan to nan (Unit : m )\n",
|
||
|
|
"Size : (346, 360)\n",
|
||
|
|
"\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
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"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x1152 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"\n",
|
||
|
|
"Recs : 1\n",
|
||
|
|
"Time : 2024-05-22 21:57:59\n",
|
||
|
|
"Name : klwx_0.0_920_360_0.0_359.0\n",
|
||
|
|
"Prod : Hybrid Hydrometeor Class\n",
|
||
|
|
"Range: 1.0 to 10.0 (Unit : count )\n",
|
||
|
|
"Size : (920, 360)\n",
|
||
|
|
"\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x1152 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"No levels found for Hydrometeor Class\n",
|
||
|
|
"No levels found for Melting Layer\n",
|
||
|
|
"\n",
|
||
|
|
"Recs : 0\n",
|
||
|
|
"\n",
|
||
|
|
"Recs : 1\n",
|
||
|
|
"Time : 2024-05-22 21:57:59\n",
|
||
|
|
"Name : klwx_0.0_115_360_359.0_359.0\n",
|
||
|
|
"Prod : One Hour Accum\n",
|
||
|
|
"Range: 0.0 to 0.0254 (Unit : m )\n",
|
||
|
|
"Size : (115, 360)\n",
|
||
|
|
"\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x1152 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"\n",
|
||
|
|
"Recs : 1\n",
|
||
|
|
"Time : 2024-05-22 21:57:59\n",
|
||
|
|
"Name : klwx_0.0_920_360_0.0_359.0\n",
|
||
|
|
"Prod : One Hour Unbiased Accum\n",
|
||
|
|
"Range: 2.54e-05 to 0.030784799 (Unit : m )\n",
|
||
|
|
"Size : (920, 360)\n",
|
||
|
|
"\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x1152 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"No levels found for Reflectivity\n",
|
||
|
|
"No levels found for Specific Diff Phase\n",
|
||
|
|
"No levels found for Storm Rel Velocity\n",
|
||
|
|
"\n",
|
||
|
|
"Recs : 1\n",
|
||
|
|
"Time : 2024-05-22 21:57:59\n",
|
||
|
|
"Name : klwx_0.0_920_360_0.0_359.0\n",
|
||
|
|
"Prod : Storm Total Accum\n",
|
||
|
|
"Range: 0.000254 to 0.051054 (Unit : m )\n",
|
||
|
|
"Size : (920, 360)\n",
|
||
|
|
"\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x1152 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"\n",
|
||
|
|
"Recs : 0\n",
|
||
|
|
"No levels found for User Select Accum\n",
|
||
|
|
"No levels found for Velocity\n",
|
||
|
|
"\n",
|
||
|
|
"Recs : 1\n",
|
||
|
|
"Time : 2024-05-22 21:57:59\n",
|
||
|
|
"Name : klwx_0.0_116_116\n",
|
||
|
|
"Prod : Vert Integ Liq\n",
|
||
|
|
"Range: 1.0 to 45.0 (Unit : kg*m^-2 )\n",
|
||
|
|
"Size : (116, 116)\n",
|
||
|
|
"\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1152x1152 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {
|
||
|
|
"needs_background": "light"
|
||
|
|
},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"# suppress a few warnings that come from plotting\n",
|
||
|
|
"warnings.filterwarnings(\"ignore\",category =RuntimeWarning)\n",
|
||
|
|
"warnings.filterwarnings(\"ignore\",category =UserWarning)\n",
|
||
|
|
"\n",
|
||
|
|
"# Cycle through all of the products to try and plot each one\n",
|
||
|
|
"for prod in productNames:\n",
|
||
|
|
" \n",
|
||
|
|
" request.setParameters(prod)\n",
|
||
|
|
" availableLevels = DataAccessLayer.getAvailableLevels(request)\n",
|
||
|
|
" \n",
|
||
|
|
" # Check the available levels, if there are none, then skip this product\n",
|
||
|
|
" if availableLevels:\n",
|
||
|
|
" request.setLevels(availableLevels[0])\n",
|
||
|
|
" else:\n",
|
||
|
|
" print(\"No levels found for \" + prod)\n",
|
||
|
|
" continue\n",
|
||
|
|
"\n",
|
||
|
|
" cycles = DataAccessLayer.getAvailableTimes(request, True)\n",
|
||
|
|
" times = DataAccessLayer.getAvailableTimes(request)\n",
|
||
|
|
"\n",
|
||
|
|
" if times:\n",
|
||
|
|
" print()\n",
|
||
|
|
" response = DataAccessLayer.getGridData(request, [times[-1]])\n",
|
||
|
|
" print(\"Recs : \", len(response))\n",
|
||
|
|
" \n",
|
||
|
|
" if response:\n",
|
||
|
|
" grid = response[0]\n",
|
||
|
|
" else:\n",
|
||
|
|
" continue\n",
|
||
|
|
" data = grid.getRawData()\n",
|
||
|
|
" lons, lats = grid.getLatLonCoords()\n",
|
||
|
|
" \n",
|
||
|
|
" print('Time :', str(grid.getDataTime()))\n",
|
||
|
|
" flat = np.ndarray.flatten(data)\n",
|
||
|
|
" print('Name :', str(grid.getLocationName()))\n",
|
||
|
|
" print('Prod :', str(grid.getParameter()))\n",
|
||
|
|
" print('Range:' , np.nanmin(flat), \" to \", np.nanmax(flat), \" (Unit :\", grid.getUnit(), \")\")\n",
|
||
|
|
" print('Size :', str(data.shape))\n",
|
||
|
|
" print()\n",
|
||
|
|
"\n",
|
||
|
|
" cmap = plt.get_cmap('rainbow')\n",
|
||
|
|
" bbox = [lons.min()-0.5, lons.max()+0.5, lats.min()-0.5, lats.max()+0.5]\n",
|
||
|
|
" fig, ax = make_map(bbox=bbox)\n",
|
||
|
|
" cs = ax.pcolormesh(lons, lats, data, cmap=cmap)\n",
|
||
|
|
" cbar = fig.colorbar(cs, extend='both', shrink=0.5, orientation='horizontal')\n",
|
||
|
|
" cbar.set_label(grid.getParameter() +\" \" + grid.getLevel() + \" \" \\\n",
|
||
|
|
" + grid.getLocationName() + \" (\" + prod + \"), (\" + grid.getUnit() + \") \" \\\n",
|
||
|
|
" + \"valid \" + str(grid.getDataTime().getRefTime()))\n",
|
||
|
|
" plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"[Top](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html)\n",
|
||
|
|
"\n",
|
||
|
|
"---"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## 6 See Also\n",
|
||
|
|
"\n",
|
||
|
|
"\n",
|
||
|
|
"### 6.1 Related Notebooks\n",
|
||
|
|
"\n",
|
||
|
|
"* [Grid Levels and Parameters](https://unidata.github.io/python-awips/examples/generated/Grid_Levels_and_Parameters.html)\n",
|
||
|
|
"\n",
|
||
|
|
"\n",
|
||
|
|
"### 6.2 Additional Documentation\n",
|
||
|
|
"\n",
|
||
|
|
"**python-awips**\n",
|
||
|
|
"\n",
|
||
|
|
"- [DataAccessLayer.changeEDEXHost()](http://unidata.github.io/python-awips/api/DataAccessLayer.html#awips.dataaccess.DataAccessLayer.changeEDEXHost)\n",
|
||
|
|
"- [DataAccessLayer.newDataRequest()](http://unidata.github.io/python-awips/api/DataAccessLayer.html#awips.dataaccess.DataAccessLayer.newDataRequest)\n",
|
||
|
|
"- [DataAccessLayer.getRadarProductIDs()](http://unidata.github.io/python-awips/api/DataAccessLayer.html#awips.dataaccess.DataAccessLayer.getRadarProductIDs)\n",
|
||
|
|
"- [DataAccessLayer.getRadarProductNames()](http://unidata.github.io/python-awips/api/DataAccessLayer.html#awips.dataaccess.DataAccessLayer.getRadarProductNames)\n",
|
||
|
|
"\n",
|
||
|
|
"**matplotlib**\n",
|
||
|
|
"\n",
|
||
|
|
"- [matplotlib.pyplot()](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.html)\n",
|
||
|
|
"- [matplotlib.pyplot.axes()](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.axes.html)\n",
|
||
|
|
"- [matplotlib.pyplot.figure()](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.figure.html)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"[Top](https://unidata.github.io/python-awips/examples/generated/NEXRAD_Level3_Radar.html)\n",
|
||
|
|
"\n",
|
||
|
|
"---"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "Python 3 (ipykernel)",
|
||
|
|
"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": "3.13.1"
|
||
|
|
},
|
||
|
|
"toc": {
|
||
|
|
"base_numbering": 1,
|
||
|
|
"nav_menu": {},
|
||
|
|
"number_sections": false,
|
||
|
|
"sideBar": false,
|
||
|
|
"skip_h1_title": true,
|
||
|
|
"title_cell": "Table of Contents",
|
||
|
|
"title_sidebar": "Contents",
|
||
|
|
"toc_cell": false,
|
||
|
|
"toc_position": {},
|
||
|
|
"toc_section_display": false,
|
||
|
|
"toc_window_display": false
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 4
|
||
|
|
}
|