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Add page documenting PSM3 variable names, units, and accessibility by endpoint #11

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1 change: 1 addition & 0 deletions source/index.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -57,3 +57,4 @@ This project uses many open-source software packages, including:
pages/tmy-vs-single
pages/numerical-precision
pages/2300-artifact
pages/variables
389 changes: 389 additions & 0 deletions source/pages/variables.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "341b7567-ade5-47fb-9798-7f45c7e19b59",
"metadata": {},
"source": [
"# Variables\n",
"\n",
"This page documents several aspects of the variables available via the PSM3 API endpoints, including:\n",
"\n",
"- What variables are available at each endpoint?\n",
"- What are the request and response names for each variable?\n",
"- What units are the variable values in?"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "e8049d34-b90c-4f8f-ae9e-76458ff334c0",
"metadata": {},
"outputs": [],
"source": [
"import pvlib\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "3ed5de9c-d935-4989-b5b0-a47b77261611",
"metadata": {},
"outputs": [],
"source": [
"cases = [('TMY', 'tmy', 60), ('Hourly', 2020, 60), ('5-minute', 2020, 5)]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "63a7dda0-9ae0-49af-926d-d68335311a60",
"metadata": {},
"outputs": [],
"source": [
"units = {}\n",
"presence = {}\n",
"for label, dataset, interval in cases:\n",
" df, meta = pvlib.iotools.get_psm3(40, -80, 'DEMO_KEY', '[email protected]',\n",
" names=dataset, interval=interval,\n",
" attributes=[], # a trick to get all variables\n",
" map_variables=False, leap_day=True)\n",
" columns = df.columns[5:] # drop timestamp columns\n",
" for column in columns:\n",
" units[column] = meta.get(column + \" Units\", \"?\")\n",
" presence[label] = {column: '✓' for column in columns}"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "d40ddf73-86a5-4442-9156-fe837308879b",
"metadata": {},
"outputs": [],
"source": [
"# TODO: once pvlib 0.9.5 is released with pvlib #1648,\n",
"# determine this mapping dynamically instead of hardcoding it\n",
"\n",
"column_map = {\n",
" 'Clearsky DHI': 'clearsky_dhi',\n",
" 'Clearsky DNI': 'clearsky_dni',\n",
" 'Clearsky GHI': 'clearsky_ghi',\n",
" 'Cloud Type': 'cloud_type',\n",
" 'DHI': 'dhi',\n",
" 'DNI': 'dni',\n",
" 'Dew Point': 'dew_point',\n",
" 'Fill Flag': 'fill_flag',\n",
" 'GHI': 'ghi',\n",
" 'Global Horizontal UV Irradiance (280-400nm)': 'ghuv-280-400',\n",
" 'Global Horizontal UV Irradiance (295-385nm)': 'ghuv-295-385',\n",
" 'Precipitable Water': 'total_precipitable_water',\n",
" 'Pressure': 'surface_pressure',\n",
" 'Relative Humidity': 'relative_humidity',\n",
" 'Solar Zenith Angle': 'solar_zenith_angle',\n",
" 'Surface Albedo': 'surface_albedo',\n",
" 'Temperature': 'air_temperature',\n",
" 'Wind Direction': 'wind_direction',\n",
" 'Wind Speed': 'wind_speed'\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "f2439f4a-ff3e-4d63-9dd2-621e4119de6a",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Response Name</th>\n",
" <th>Request Name</th>\n",
" <th>Units</th>\n",
" <th>TMY</th>\n",
" <th>Hourly</th>\n",
" <th>5-minute</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Dew Point</td>\n",
" <td>dew_point</td>\n",
" <td>c</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>DHI</td>\n",
" <td>dhi</td>\n",
" <td>w/m2</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>DNI</td>\n",
" <td>dni</td>\n",
" <td>w/m2</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>GHI</td>\n",
" <td>ghi</td>\n",
" <td>w/m2</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Surface Albedo</td>\n",
" <td>surface_albedo</td>\n",
" <td>N/A</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Pressure</td>\n",
" <td>surface_pressure</td>\n",
" <td>mbar</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Temperature</td>\n",
" <td>air_temperature</td>\n",
" <td>c</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Wind Direction</td>\n",
" <td>wind_direction</td>\n",
" <td>Degrees</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Wind Speed</td>\n",
" <td>wind_speed</td>\n",
" <td>m/s</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Clearsky DHI</td>\n",
" <td>clearsky_dhi</td>\n",
" <td>w/m2</td>\n",
" <td></td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Clearsky DNI</td>\n",
" <td>clearsky_dni</td>\n",
" <td>w/m2</td>\n",
" <td></td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Clearsky GHI</td>\n",
" <td>clearsky_ghi</td>\n",
" <td>w/m2</td>\n",
" <td></td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Cloud Type</td>\n",
" <td>cloud_type</td>\n",
" <td>?</td>\n",
" <td></td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Fill Flag</td>\n",
" <td>fill_flag</td>\n",
" <td>?</td>\n",
" <td></td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>Relative Humidity</td>\n",
" <td>relative_humidity</td>\n",
" <td>%</td>\n",
" <td></td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Solar Zenith Angle</td>\n",
" <td>solar_zenith_angle</td>\n",
" <td>Degree</td>\n",
" <td></td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>Precipitable Water</td>\n",
" <td>total_precipitable_water</td>\n",
" <td>cm</td>\n",
" <td></td>\n",
" <td>✓</td>\n",
" <td>✓</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>Global Horizontal UV Irradiance (280-400nm)</td>\n",
" <td>ghuv-280-400</td>\n",
" <td>?</td>\n",
" <td></td>\n",
" <td>✓</td>\n",
" <td></td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>Global Horizontal UV Irradiance (295-385nm)</td>\n",
" <td>ghuv-295-385</td>\n",
" <td>?</td>\n",
" <td></td>\n",
" <td>✓</td>\n",
" <td></td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Response Name Request Name \\\n",
"0 Dew Point dew_point \n",
"1 DHI dhi \n",
"2 DNI dni \n",
"3 GHI ghi \n",
"4 Surface Albedo surface_albedo \n",
"5 Pressure surface_pressure \n",
"6 Temperature air_temperature \n",
"7 Wind Direction wind_direction \n",
"8 Wind Speed wind_speed \n",
"9 Clearsky DHI clearsky_dhi \n",
"10 Clearsky DNI clearsky_dni \n",
"11 Clearsky GHI clearsky_ghi \n",
"12 Cloud Type cloud_type \n",
"13 Fill Flag fill_flag \n",
"14 Relative Humidity relative_humidity \n",
"15 Solar Zenith Angle solar_zenith_angle \n",
"16 Precipitable Water total_precipitable_water \n",
"17 Global Horizontal UV Irradiance (280-400nm) ghuv-280-400 \n",
"18 Global Horizontal UV Irradiance (295-385nm) ghuv-295-385 \n",
"\n",
" Units TMY Hourly 5-minute \n",
"0 c ✓ ✓ ✓ \n",
"1 w/m2 ✓ ✓ ✓ \n",
"2 w/m2 ✓ ✓ ✓ \n",
"3 w/m2 ✓ ✓ ✓ \n",
"4 N/A ✓ ✓ ✓ \n",
"5 mbar ✓ ✓ ✓ \n",
"6 c ✓ ✓ ✓ \n",
"7 Degrees ✓ ✓ ✓ \n",
"8 m/s ✓ ✓ ✓ \n",
"9 w/m2 ✓ ✓ \n",
"10 w/m2 ✓ ✓ \n",
"11 w/m2 ✓ ✓ \n",
"12 ? ✓ ✓ \n",
"13 ? ✓ ✓ \n",
"14 % ✓ ✓ \n",
"15 Degree ✓ ✓ \n",
"16 cm ✓ ✓ \n",
"17 ? ✓ \n",
"18 ? ✓ "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.concat([\n",
" pd.Series({v: column_map[v] for v in units}, name='Request Name'),\n",
" pd.Series(units, name='Units'),\n",
" pd.DataFrame(presence).fillna(\"\"),\n",
"], axis=1).rename_axis(index='Response Name').reset_index()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "79915e61-6b9b-405d-a737-828ac117ac5f",
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.10.4"
}
},
"nbformat": 4,
"nbformat_minor": 5
}