From 33612e9d2a540a8e503dc96fb00f13d1b9e2ad3b Mon Sep 17 00:00:00 2001 From: Daxini Date: Tue, 30 Jun 2026 10:54:09 -0600 Subject: [PATCH 1/5] weather database access nb use local file --- .../04_weather_database_access.ipynb | 102 ++++++++---------- .../scripts/04_weather_database_access.py | 23 ++-- 2 files changed, 59 insertions(+), 66 deletions(-) diff --git a/tutorials/01_basics/04_weather_database_access.ipynb b/tutorials/01_basics/04_weather_database_access.ipynb index 7469ab8b..2f8531fb 100644 --- a/tutorials/01_basics/04_weather_database_access.ipynb +++ b/tutorials/01_basics/04_weather_database_access.ipynb @@ -50,45 +50,29 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2025-12-03T15:42:13.626699Z", - "iopub.status.busy": "2025-12-03T15:42:13.626456Z", - "iopub.status.idle": "2025-12-03T15:42:13.632347Z", - "shell.execute_reply": "2025-12-03T15:42:13.631558Z" - } - }, - "outputs": [], - "source": [ - "# if running on google colab, uncomment the next line and execute this cell to install the dependencies and prevent \"ModuleNotFoundError\" in later cells:\n", - "# !pip install pvdeg" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "execution": { - "iopub.execute_input": "2025-12-03T15:42:13.634556Z", - "iopub.status.busy": "2025-12-03T15:42:13.634241Z", - "iopub.status.idle": "2025-12-03T15:42:17.912055Z", - "shell.execute_reply": "2025-12-03T15:42:17.910698Z" + "iopub.execute_input": "2026-06-30T16:53:21.590643Z", + "iopub.status.busy": "2026-06-30T16:53:21.589455Z", + "iopub.status.idle": "2026-06-30T16:53:31.669663Z", + "shell.execute_reply": "2026-06-30T16:53:31.668144Z" }, "scrolled": true }, "outputs": [], "source": [ "import pvdeg\n", + "import json\n", "import pandas as pd" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2025-12-03T15:42:17.915654Z", - "iopub.status.busy": "2025-12-03T15:42:17.914551Z", - "iopub.status.idle": "2025-12-03T15:42:17.921986Z", - "shell.execute_reply": "2025-12-03T15:42:17.920956Z" + "iopub.execute_input": "2026-06-30T16:53:31.674429Z", + "iopub.status.busy": "2026-06-30T16:53:31.673308Z", + "iopub.status.idle": "2026-06-30T16:53:31.681145Z", + "shell.execute_reply": "2026-06-30T16:53:31.680050Z" } }, "outputs": [ @@ -97,13 +81,13 @@ "output_type": "stream", "text": [ "Working on a Windows 11\n", - "Python version 3.13.5 | packaged by Anaconda, Inc. | (main, Jun 12 2025, 16:37:03) [MSC v.1929 64 bit (AMD64)]\n", - "pvdeg version 0.5.1.dev857+g1a511e445.d20251004\n" + "Python version 3.13.13 | packaged by conda-forge | (main, Apr 8 2026, 01:56:49) [MSC v.1944 64 bit (AMD64)]\n", + "pvdeg version 0.7.2.dev86+gbddb1bdbc.d20260519\n" ] } ], "source": [ - "# This information helps with debugging and getting support :)\n", + "# This information helps with debugging and getting support\n", "import sys\n", "import platform\n", "\n", @@ -129,13 +113,13 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2025-12-03T15:42:17.959558Z", - "iopub.status.busy": "2025-12-03T15:42:17.959029Z", - "iopub.status.idle": "2025-12-03T15:42:17.966043Z", - "shell.execute_reply": "2025-12-03T15:42:17.964813Z" + "iopub.execute_input": "2026-06-30T16:53:31.730258Z", + "iopub.status.busy": "2026-06-30T16:53:31.729564Z", + "iopub.status.idle": "2026-06-30T16:53:31.738299Z", + "shell.execute_reply": "2026-06-30T16:53:31.736857Z" } }, "outputs": [], @@ -196,13 +180,13 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2025-12-03T15:42:17.969026Z", - "iopub.status.busy": "2025-12-03T15:42:17.968679Z", - "iopub.status.idle": "2025-12-03T15:42:18.182705Z", - "shell.execute_reply": "2025-12-03T15:42:18.181410Z" + "iopub.execute_input": "2026-06-30T16:53:31.741611Z", + "iopub.status.busy": "2026-06-30T16:53:31.741145Z", + "iopub.status.idle": "2026-06-30T16:53:32.000599Z", + "shell.execute_reply": "2026-06-30T16:53:31.998853Z" } }, "outputs": [ @@ -223,8 +207,6 @@ "source": [ "# Load pre-saved weather data for this tutorial\n", "# This avoids API rate limits during testing and builds\n", - "import json\n", - "\n", "weather_df = pd.read_csv(\"../data/psm4_golden.csv\", index_col=0, parse_dates=True)\n", "with open(\"../data/meta_golden.json\", \"r\") as f:\n", " meta = json.load(f)\n", @@ -274,13 +256,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2025-12-03T15:42:18.187172Z", - "iopub.status.busy": "2025-12-03T15:42:18.186692Z", - "iopub.status.idle": "2025-12-03T15:42:20.552763Z", - "shell.execute_reply": "2025-12-03T15:42:20.551416Z" + "iopub.execute_input": "2026-06-30T16:53:32.005116Z", + "iopub.status.busy": "2026-06-30T16:53:32.004526Z", + "iopub.status.idle": "2026-06-30T16:53:32.283914Z", + "shell.execute_reply": "2026-06-30T16:53:32.281909Z" } }, "outputs": [ @@ -288,13 +270,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "The array surface_tilt angle was not provided, therefore the latitude of 24.7 was used.\n", - "The estimated T₉₈ of an insulated-back module is 89.6°C. \n", - "The estimated T₉₈ of an open-rack module is 63.8°C. \n", - "Level 0 certification is valid for a standoff greather than 9.3 cm. \n", - "Level 1 certification is required for a standoff between 9.3 cm, and 3.0 cm. \n", - "Level 2 certification is required for a standoff less than 3.0 cm.\n", - "{'latitude': 24.7136, 'longitude': 46.6753, 'altitude': 646.0, 'wind_height': 10, 'Source': 'PVGIS'}\n" + "The array surface_tilt angle was not provided, therefore the latitude of 39.7 was used.\n", + "{'x_cm': 1.8, 'T98_0_C': 75.9, 'T98_inf_C': 51.6}\n", + "{'Source': 'NSRDB', 'Location ID': '479494', 'City': '-', 'State': '-', 'Country': '-', 'Clearsky DHI Units': 'w/m2', 'Clearsky DNI Units': 'w/m2', 'Clearsky GHI Units': 'w/m2', 'Dew Point Units': 'c', 'DHI Units': 'w/m2', 'DNI Units': 'w/m2', 'GHI Units': 'w/m2', 'Solar Zenith Angle Units': 'Degree', 'Temperature Units': 'c', 'Pressure Units': 'mbar', 'Relative Humidity Units': '%', 'Precipitable Water Units': 'cm', 'Wind Direction Units': 'Degrees', 'Wind Speed Units': 'm/s', 'Cloud Type -15': 'N/A', 'Cloud Type 0': 'Clear', 'Cloud Type 1': 'Probably Clear', 'Cloud Type 2': 'Fog', 'Cloud Type 3': 'Water', 'Cloud Type 4': 'Super-Cooled Water', 'Cloud Type 5': 'Mixed', 'Cloud Type 6': 'Opaque Ice', 'Cloud Type 7': 'Cirrus', 'Cloud Type 8': 'Overlapping', 'Cloud Type 9': 'Overshooting', 'Cloud Type 10': 'Unknown', 'Cloud Type 11': 'Dust', 'Cloud Type 12': 'Smoke', 'Fill Flag 0': 'N/A', 'Fill Flag 1': 'Missing Image', 'Fill Flag 2': 'Low Irradiance', 'Fill Flag 3': 'Exceeds Clearsky', 'Fill Flag 4': 'Missing CLoud Properties', 'Fill Flag 5': 'Rayleigh Violation', 'Surface Albedo Units': 'N/A', 'Version': '4.1.2.dev4+g3b38bc8.d20250228', 'latitude': 39.73, 'longitude': -105.18, 'altitude': 1876, 'tz': -7, 'wind_height': 2}\n" ] } ], @@ -304,8 +282,18 @@ "weather_id = (24.7136, 46.6753) # Riyadh, Saudi Arabia\n", "# weather_arg = {'map_variables': True}\n", "\n", - "# TMY\n", - "weather_df, meta = pvdeg.weather.get(weather_db, weather_id)\n", + "# For reproducible notebook testing, default to cached local weather/meta.\n", + "# Set USE_LIVE_PVGIS = True to fetch live PVGIS data.\n", + "USE_LIVE_PVGIS = False\n", + "\n", + "if USE_LIVE_PVGIS:\n", + " # TMY from live PVGIS API\n", + " weather_df, meta = pvdeg.weather.get(weather_db, weather_id)\n", + "else:\n", + " # Cached sample weather to avoid SSL/network flakiness in CI\n", + " weather_df = pd.read_csv(\"../data/psm4_golden.csv\", index_col=0, parse_dates=True)\n", + " with open(\"../data/meta_golden.json\", \"r\") as f:\n", + " meta = json.load(f)\n", "\n", "# Perform calculation\n", "res = pvdeg.standards.standoff(\n", @@ -338,7 +326,7 @@ ], "metadata": { "kernelspec": { - "display_name": "pvdeg_313", + "display_name": "pvdeg2", "language": "python", "name": "python3" }, @@ -352,7 +340,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.5" + "version": "3.13.13" } }, "nbformat": 4, diff --git a/tutorials/01_basics/scripts/04_weather_database_access.py b/tutorials/01_basics/scripts/04_weather_database_access.py index 806aa3b7..ac7a9091 100644 --- a/tutorials/01_basics/scripts/04_weather_database_access.py +++ b/tutorials/01_basics/scripts/04_weather_database_access.py @@ -31,16 +31,13 @@ # %% [markdown] # # Single location example -# %% -# if running on google colab, uncomment the next line and execute this cell to install the dependencies and prevent "ModuleNotFoundError" in later cells: -# # !pip install pvdeg - # %% import pvdeg +import json import pandas as pd # %% -# This information helps with debugging and getting support :) +# This information helps with debugging and getting support import sys import platform @@ -108,8 +105,6 @@ # %% # Load pre-saved weather data for this tutorial # This avoids API rate limits during testing and builds -import json - weather_df = pd.read_csv("../data/psm4_golden.csv", index_col=0, parse_dates=True) with open("../data/meta_golden.json", "r") as f: meta = json.load(f) @@ -158,8 +153,18 @@ weather_id = (24.7136, 46.6753) # Riyadh, Saudi Arabia # weather_arg = {'map_variables': True} -# TMY -weather_df, meta = pvdeg.weather.get(weather_db, weather_id) +# For reproducible notebook testing, default to cached local weather/meta. +# Set USE_LIVE_PVGIS = True to fetch live PVGIS data. +USE_LIVE_PVGIS = False + +if USE_LIVE_PVGIS: + # TMY from live PVGIS API + weather_df, meta = pvdeg.weather.get(weather_db, weather_id) +else: + # Cached sample weather to avoid SSL/network flakiness in CI + weather_df = pd.read_csv("../data/psm4_golden.csv", index_col=0, parse_dates=True) + with open("../data/meta_golden.json", "r") as f: + meta = json.load(f) # Perform calculation res = pvdeg.standards.standoff( From 716699aa5ab4d2b7170c8f35ecc7cd94793414a2 Mon Sep 17 00:00:00 2001 From: Daxini Date: Tue, 30 Jun 2026 14:28:19 -0600 Subject: [PATCH 2/5] update astm live demo --- .../10_workshop_demos/01_astm_live_demo.ipynb | 42 +++++++++++++------ .../scripts/01_astm_live_demo.py | 34 +++++++++++---- 2 files changed, 54 insertions(+), 22 deletions(-) diff --git a/tutorials/10_workshop_demos/01_astm_live_demo.ipynb b/tutorials/10_workshop_demos/01_astm_live_demo.ipynb index c15050f7..c8e22a60 100644 --- a/tutorials/10_workshop_demos/01_astm_live_demo.ipynb +++ b/tutorials/10_workshop_demos/01_astm_live_demo.ipynb @@ -44,7 +44,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": { "execution": { "iopub.execute_input": "2026-02-03T18:09:00.408424Z", @@ -247,7 +247,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": { "execution": { "iopub.execute_input": "2026-02-03T18:09:11.804287Z", @@ -258,15 +258,31 @@ }, "outputs": [], "source": [ - "weather_df, meta = pvlib.iotools.get_nsrdb_psm4_tmy(\n", - " latitude=33.4484,\n", - " longitude=-112.0740,\n", - " api_key=NREL_API_KEY,\n", - " email=\"silvana.ovaitt@nrel.gov\", # <-- any email works here fine\n", - " year=\"tmy\",\n", - " map_variables=True,\n", - " leap_day=False,\n", - ")" + "# For reproducible CI and offline use, default to cached weather data.\n", + "# Set USE_LIVE_NSRDB=True during workshops to make the live API call.\n", + "USE_LIVE_NSRDB = False\n", + "\n", + "if USE_LIVE_NSRDB:\n", + " weather_df, meta = pvlib.iotools.get_nsrdb_psm4_tmy(\n", + " latitude=33.4484,\n", + " longitude=-112.0740,\n", + " api_key=NREL_API_KEY,\n", + " email=\"silvana.ovaitt@nrel.gov\", # <-- any email works here fine\n", + " year=\"tmy\",\n", + " map_variables=True,\n", + " leap_day=False,\n", + " timeout=60,\n", + " )\n", + "else:\n", + " import json\n", + "\n", + " repo_root = os.path.dirname(os.path.dirname(pvdeg.__file__))\n", + " weather_path = os.path.join(repo_root, \"tutorials\", \"data\", \"psm4_golden.csv\")\n", + " meta_path = os.path.join(repo_root, \"tutorials\", \"data\", \"meta_golden.json\")\n", + "\n", + " weather_df = pd.read_csv(weather_path, index_col=0, parse_dates=True)\n", + " with open(meta_path, \"r\") as f:\n", + " meta = json.load(f)" ] }, { @@ -1033,7 +1049,7 @@ ], "metadata": { "kernelspec": { - "display_name": "pvdeg", + "display_name": "pvdeg2", "language": "python", "name": "python3" }, @@ -1047,7 +1063,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.13" } }, "nbformat": 4, diff --git a/tutorials/10_workshop_demos/scripts/01_astm_live_demo.py b/tutorials/10_workshop_demos/scripts/01_astm_live_demo.py index 00cd630d..d1134f0a 100644 --- a/tutorials/10_workshop_demos/scripts/01_astm_live_demo.py +++ b/tutorials/10_workshop_demos/scripts/01_astm_live_demo.py @@ -134,15 +134,31 @@ """ # %% -weather_df, meta = pvlib.iotools.get_nsrdb_psm4_tmy( - latitude=33.4484, - longitude=-112.0740, - api_key=NREL_API_KEY, - email="silvana.ovaitt@nrel.gov", # <-- any email works here fine - year="tmy", - map_variables=True, - leap_day=False, -) +# For reproducible CI and offline use, default to cached weather data. +# Set USE_LIVE_NSRDB=True during workshops to make the live API call. +USE_LIVE_NSRDB = False + +if USE_LIVE_NSRDB: + weather_df, meta = pvlib.iotools.get_nsrdb_psm4_tmy( + latitude=33.4484, + longitude=-112.0740, + api_key=NREL_API_KEY, + email="silvana.ovaitt@nrel.gov", # <-- any email works here fine + year="tmy", + map_variables=True, + leap_day=False, + timeout=60, + ) +else: + import json + + repo_root = os.path.dirname(os.path.dirname(pvdeg.__file__)) + weather_path = os.path.join(repo_root, "tutorials", "data", "psm4_golden.csv") + meta_path = os.path.join(repo_root, "tutorials", "data", "meta_golden.json") + + weather_df = pd.read_csv(weather_path, index_col=0, parse_dates=True) + with open(meta_path, "r") as f: + meta = json.load(f) # %% weather_df From 2c5d5d063e8f58b727305404f30913c95f96db2a Mon Sep 17 00:00:00 2001 From: Daxini Date: Wed, 1 Jul 2026 10:55:04 -0600 Subject: [PATCH 3/5] update failing notebooks custom and astm --- .../01_custom_functions_nopython.ipynb | 58 ++- .../scripts/01_custom_functions_nopython.py | 41 +- .../10_workshop_demos/01_astm_live_demo.ipynb | 491 +++++++++--------- .../scripts/01_astm_live_demo.py | 17 +- 4 files changed, 342 insertions(+), 265 deletions(-) diff --git a/tutorials/06_advanced/01_custom_functions_nopython.ipynb b/tutorials/06_advanced/01_custom_functions_nopython.ipynb index c6d2d438..b601b863 100644 --- a/tutorials/06_advanced/01_custom_functions_nopython.ipynb +++ b/tutorials/06_advanced/01_custom_functions_nopython.ipynb @@ -16,11 +16,16 @@ "iopub.status.busy": "2025-10-03T22:56:28.670787Z", "iopub.status.idle": "2025-10-03T22:56:34.487788Z", "shell.execute_reply": "2025-10-03T22:56:34.486769Z" - } + }, + "lines_to_next_cell": 2 }, "outputs": [], "source": [ + "import json\n", + "import os\n", + "\n", "import numpy as np\n", + "import pandas as pd\n", "import sympy as sp\n", "import matplotlib.pyplot as plt\n", "import pvdeg" @@ -30,9 +35,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Grabbing Weather Data from PVGIS\n", + "# Grabbing Weather Data\n", "\n", - "Use pvdeg to make an API call to PVGIS to collect location and weather data for Manhattan, NYC." + "We need a timeseries of weather data to feed into the symbolic degradation expression below.\n", + "\n", + "By default this notebook loads a cached NSRDB TMY for Miami, FL that ships with the repo (`tutorials/data/psm4_miami.csv`). This keeps the notebook reproducible in CI and works offline. Set `USE_LIVE_PVGIS = True` in the next cell to make a live PVGIS API call for Manhattan, NYC instead.\n" ] }, { @@ -44,14 +51,28 @@ "iopub.status.busy": "2025-10-03T22:56:34.490299Z", "iopub.status.idle": "2025-10-03T22:56:37.130883Z", "shell.execute_reply": "2025-10-03T22:56:37.129880Z" - } + }, + "lines_to_next_cell": 2 }, "outputs": [], "source": [ - "weather_df, meta_dict = pvdeg.weather.get(\n", - " database=\"PVGIS\",\n", - " id=(40.776676, -73.971321), # manhattan (latitude, longitude)\n", - ")" + "# For reproducible CI and offline use, default to cached weather data.\n", + "# Set USE_LIVE_PVGIS=True to fetch live PVGIS TMY for Manhattan instead.\n", + "USE_LIVE_PVGIS = False\n", + "\n", + "if USE_LIVE_PVGIS:\n", + " weather_df, meta_dict = pvdeg.weather.get(\n", + " database=\"PVGIS\",\n", + " id=(40.776676, -73.971321), # manhattan (latitude, longitude)\n", + " )\n", + "else:\n", + " repo_root = os.path.dirname(os.path.dirname(pvdeg.__file__))\n", + " weather_path = os.path.join(repo_root, \"tutorials\", \"data\", \"psm4_miami.csv\")\n", + " meta_path = os.path.join(repo_root, \"tutorials\", \"data\", \"meta_miami.json\")\n", + "\n", + " weather_df = pd.read_csv(weather_path, index_col=0, parse_dates=True)\n", + " with open(meta_path, \"r\") as f:\n", + " meta_dict = json.load(f)" ] }, { @@ -74,22 +95,23 @@ "iopub.status.busy": "2025-10-03T22:56:37.133883Z", "iopub.status.idle": "2025-10-03T22:56:37.784362Z", "shell.execute_reply": "2025-10-03T22:56:37.784362Z" - } + }, + "lines_to_next_cell": 2 }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "The array surface_tilt angle was not provided, therefore the latitude of 40.8 was used.\n", + "The array surface_tilt angle was not provided, therefore the latitude of 25.8 was used.\n", "The array azimuth was not provided, therefore an azimuth of 180.0 was used.\n", - "The array surface_tilt angle was not provided, therefore the latitude of 40.8 was used.\n", + "The array surface_tilt angle was not provided, therefore the latitude of 25.8 was used.\n", "The array azimuth was not provided, therefore an azimuth of 180.0 was used.\n" ] }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -105,16 +127,18 @@ "\n", "poa_irradiance = pvdeg.spectral.poa_irradiance(weather_df=weather_df, meta=meta_dict)\n", "\n", + "location_label = \"Manhattan\" if USE_LIVE_PVGIS else \"Miami\"\n", + "\n", "plt.figure(figsize=(10, 6))\n", "plt.subplot(1, 2, 1)\n", "plt.plot(\n", " module_temps.values\n", ") # plotting the values in order because we are using tmy data so the years are not consistent within our data\n", - "plt.title(\"TMY Module Temperature, Manhattan\")\n", + "plt.title(f\"TMY Module Temperature, {location_label}\")\n", "plt.subplot(1, 2, 2)\n", "plt.plot(poa_irradiance.values)\n", "plt.legend(poa_irradiance.columns)\n", - "plt.title(\"TML Module Irradiance, Manhattan\")\n", + "plt.title(f\"TMY Module Irradiance, {location_label}\")\n", "plt.show()" ] }, @@ -257,7 +281,7 @@ { "data": { "text/plain": [ - "np.float64(-5.890094732542499)" + "np.float64(-5.637887238640398)" ] }, "execution_count": 7, @@ -389,7 +413,7 @@ ], "metadata": { "kernelspec": { - "display_name": "pvdeg", + "display_name": "pvdeg2", "language": "python", "name": "python3" }, @@ -403,7 +427,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.9" + "version": "3.13.13" } }, "nbformat": 4, diff --git a/tutorials/06_advanced/scripts/01_custom_functions_nopython.py b/tutorials/06_advanced/scripts/01_custom_functions_nopython.py index c191930f..4412ab6b 100644 --- a/tutorials/06_advanced/scripts/01_custom_functions_nopython.py +++ b/tutorials/06_advanced/scripts/01_custom_functions_nopython.py @@ -3,21 +3,43 @@ # # %% +import json +import os + import numpy as np +import pandas as pd import sympy as sp import matplotlib.pyplot as plt import pvdeg + # %% [markdown] -# # Grabbing Weather Data from PVGIS +# # Grabbing Weather Data +# +# We need a timeseries of weather data to feed into the symbolic degradation expression below. +# +# By default this notebook loads a cached NSRDB TMY for Miami, FL that ships with the repo (`tutorials/data/psm4_miami.csv`). This keeps the notebook reproducible in CI and works offline. Set `USE_LIVE_PVGIS = True` in the next cell to make a live PVGIS API call for Manhattan, NYC instead. # -# Use pvdeg to make an API call to PVGIS to collect location and weather data for Manhattan, NYC. # %% -weather_df, meta_dict = pvdeg.weather.get( - database="PVGIS", - id=(40.776676, -73.971321), # manhattan (latitude, longitude) -) +# For reproducible CI and offline use, default to cached weather data. +# Set USE_LIVE_PVGIS=True to fetch live PVGIS TMY for Manhattan instead. +USE_LIVE_PVGIS = False + +if USE_LIVE_PVGIS: + weather_df, meta_dict = pvdeg.weather.get( + database="PVGIS", + id=(40.776676, -73.971321), # manhattan (latitude, longitude) + ) +else: + repo_root = os.path.dirname(os.path.dirname(pvdeg.__file__)) + weather_path = os.path.join(repo_root, "tutorials", "data", "psm4_miami.csv") + meta_path = os.path.join(repo_root, "tutorials", "data", "meta_miami.json") + + weather_df = pd.read_csv(weather_path, index_col=0, parse_dates=True) + with open(meta_path, "r") as f: + meta_dict = json.load(f) + # %% [markdown] # # Calculating Temperature and Irradiance @@ -33,18 +55,21 @@ poa_irradiance = pvdeg.spectral.poa_irradiance(weather_df=weather_df, meta=meta_dict) +location_label = "Manhattan" if USE_LIVE_PVGIS else "Miami" + plt.figure(figsize=(10, 6)) plt.subplot(1, 2, 1) plt.plot( module_temps.values ) # plotting the values in order because we are using tmy data so the years are not consistent within our data -plt.title("TMY Module Temperature, Manhattan") +plt.title(f"TMY Module Temperature, {location_label}") plt.subplot(1, 2, 2) plt.plot(poa_irradiance.values) plt.legend(poa_irradiance.columns) -plt.title("TML Module Irradiance, Manhattan") +plt.title(f"TMY Module Irradiance, {location_label}") plt.show() + # %% [markdown] # # Define Custom Expressions from Latex or # diff --git a/tutorials/10_workshop_demos/01_astm_live_demo.ipynb b/tutorials/10_workshop_demos/01_astm_live_demo.ipynb index c8e22a60..8bcfc35c 100644 --- a/tutorials/10_workshop_demos/01_astm_live_demo.ipynb +++ b/tutorials/10_workshop_demos/01_astm_live_demo.ipynb @@ -44,7 +44,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2026-02-03T18:09:00.408424Z", @@ -79,10 +79,10 @@ "output_type": "stream", "text": [ "Working on a Windows 11\n", - "Python version 3.13.11 | packaged by Anaconda, Inc. | (main, Dec 10 2025, 21:21:58) [MSC v.1929 64 bit (AMD64)]\n", - "Pandas version 3.0.0\n", - "pvlib version 0.14.0\n", - "pvdeg version 0.7.1.dev27+gde5391d47\n" + "Python version 3.13.13 | packaged by conda-forge | (main, Apr 8 2026, 01:56:49) [MSC v.1944 64 bit (AMD64)]\n", + "Pandas version 3.0.3\n", + "pvlib version 0.15.1\n", + "pvdeg version 0.7.2.dev86+gbddb1bdbc.d20260519\n" ] } ], @@ -199,32 +199,33 @@ "source": [ "# Fetching TMYs from the NSRDB\n", "\n", - "The NSRDB, one of many sources of weather data intended for PV modeling, is free and easy to access using pvlib. As an example, we'll fetch a TMY dataset for Phoenix, AZ at coordinates [(33.4484, -112.0740)](https://goo.gl/maps/hGV92QHCm5FHJKbf9).\n", + "The NSRDB, one of many sources of weather data intended for PV modeling, is free and easy to access using pvlib. As an example, we'll fetch a TMY dataset for Golden, CO at coordinates [(39.73, -105.18)](https://goo.gl/maps/hGV92QHCm5FHJKbf9).\n", "\n", "This function uses [`pvdeg.weather.get()`](https://pvdegradationtools.readthedocs.io/en/latest/_autosummary/pvdeg.weather.html#pvdeg.weather.get), which returns a Python dictionary of metadata and a Pandas dataframe of the timeseries weather data.\n", "\n", - "This function internally leverages [`pvlib.iotools.get_psm3()`](https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.iotools.get_psm3.html). However, for some of the NSRDB data relative humidity is not a given parameter, and `pvdeg` calculates the values from the downloaded data as an internal processing step." + "This function internally leverages [`pvlib.iotools.get_psm3()`](https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.iotools.get_psm3.html). However, for some of the NSRDB data relative humidity is not a given parameter, and `pvdeg` calculates the values from the downloaded data as an internal processing step.\n" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2026-02-03T18:09:11.781822Z", "iopub.status.busy": "2026-02-03T18:09:11.781122Z", "iopub.status.idle": "2026-02-03T18:09:11.797782Z", "shell.execute_reply": "2026-02-03T18:09:11.794972Z" - } + }, + "lines_to_next_cell": 2 }, "outputs": [ { "data": { "text/plain": [ - "\"\\nweather_db = 'PSM4'\\nweather_id = (33.4484, -112.0740)\\nweather_arg = {'api_key': NREL_API_KEY,\\n 'email': 'user@mail.com',\\n 'year': '2021',\\n 'map_variables': True,\\n 'leap_day': False}\\n\\nweather_df, meta = pvdeg.weather.get(weather_db, weather_id, **weather_arg)\\n\"" + "\"\\nweather_db = 'PSM4'\\nweather_id = (39.73, -105.18)\\nweather_arg = {'api_key': NREL_API_KEY,\\n 'email': 'user@mail.com',\\n 'year': '2021',\\n 'map_variables': True,\\n 'leap_day': False}\\n\\nweather_df, meta = pvdeg.weather.get(weather_db, weather_id, **weather_arg)\\n\"" ] }, - "execution_count": 5, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -234,7 +235,7 @@ "# The next cell performs the same request directly with PVLib.\n", "\"\"\"\n", "weather_db = 'PSM4'\n", - "weather_id = (33.4484, -112.0740)\n", + "weather_id = (39.73, -105.18)\n", "weather_arg = {'api_key': NREL_API_KEY,\n", " 'email': 'user@mail.com',\n", " 'year': '2021',\n", @@ -247,14 +248,15 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2026-02-03T18:09:11.804287Z", "iopub.status.busy": "2026-02-03T18:09:11.803228Z", "iopub.status.idle": "2026-02-03T18:09:15.349133Z", "shell.execute_reply": "2026-02-03T18:09:15.346630Z" - } + }, + "lines_to_next_cell": 2 }, "outputs": [], "source": [ @@ -264,8 +266,8 @@ "\n", "if USE_LIVE_NSRDB:\n", " weather_df, meta = pvlib.iotools.get_nsrdb_psm4_tmy(\n", - " latitude=33.4484,\n", - " longitude=-112.0740,\n", + " latitude=39.73,\n", + " longitude=-105.18,\n", " api_key=NREL_API_KEY,\n", " email=\"silvana.ovaitt@nrel.gov\", # <-- any email works here fine\n", " year=\"tmy\",\n", @@ -324,7 +326,7 @@ " Hour\n", " Minute\n", " temp_air\n", - " temp_dew\n", + " dew_point\n", " dhi\n", " dni\n", " ghi\n", @@ -332,93 +334,99 @@ " pressure\n", " wind_direction\n", " wind_speed\n", + " relative_humidity\n", " \n", " \n", " \n", " \n", - " 2010-01-01 00:30:00-07:00\n", - " 2010\n", + " 2011-01-01 00:30:00-07:00\n", + " 2011\n", " 1\n", " 1\n", " 0\n", " 30\n", - " 3.9\n", - " -7.8\n", + " -16.0\n", + " -26.6\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 982.0\n", - " 54.0\n", - " 4.6\n", + " 0.8\n", + " 794.0\n", + " 276.0\n", + " 4.0\n", + " 39.692741\n", " \n", " \n", - " 2010-01-01 01:30:00-07:00\n", - " 2010\n", + " 2011-01-01 01:30:00-07:00\n", + " 2011\n", " 1\n", " 1\n", " 1\n", " 30\n", - " 3.8\n", - " -8.1\n", + " -16.0\n", + " -26.5\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 981.0\n", - " 55.0\n", - " 4.5\n", + " 0.8\n", + " 794.0\n", + " 274.0\n", + " 4.1\n", + " 40.057183\n", " \n", " \n", - " 2010-01-01 02:30:00-07:00\n", - " 2010\n", + " 2011-01-01 02:30:00-07:00\n", + " 2011\n", " 1\n", " 1\n", " 2\n", " 30\n", - " 3.9\n", - " -8.5\n", + " -15.9\n", + " -26.2\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 981.0\n", - " 55.0\n", - " 4.2\n", + " 0.8\n", + " 795.0\n", + " 273.0\n", + " 4.1\n", + " 40.828082\n", " \n", " \n", - " 2010-01-01 03:30:00-07:00\n", - " 2010\n", + " 2011-01-01 03:30:00-07:00\n", + " 2011\n", " 1\n", " 1\n", " 3\n", " 30\n", - " 3.9\n", - " -8.8\n", + " -15.8\n", + " -26.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 981.0\n", - " 54.0\n", - " 3.9\n", + " 0.8\n", + " 795.0\n", + " 272.0\n", + " 4.1\n", + " 41.234476\n", " \n", " \n", - " 2010-01-01 04:30:00-07:00\n", - " 2010\n", + " 2011-01-01 04:30:00-07:00\n", + " 2011\n", " 1\n", " 1\n", " 4\n", " 30\n", - " 3.8\n", - " -9.1\n", + " -15.7\n", + " -25.7\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 981.0\n", - " 53.0\n", - " 3.6\n", + " 0.8\n", + " 795.0\n", + " 271.0\n", + " 4.0\n", + " 42.023356\n", " \n", " \n", " ...\n", @@ -436,138 +444,144 @@ " ...\n", " ...\n", " ...\n", + " ...\n", " \n", " \n", - " 2023-12-31 19:30:00-07:00\n", - " 2023\n", + " 2003-12-31 19:30:00-07:00\n", + " 2003\n", " 12\n", " 31\n", " 19\n", " 30\n", - " 6.8\n", - " -6.6\n", + " -15.7\n", + " -26.8\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 982.0\n", - " 30.0\n", - " 1.9\n", + " 0.8\n", + " 793.0\n", + " 284.0\n", + " 3.9\n", + " 38.014453\n", " \n", " \n", - " 2023-12-31 20:30:00-07:00\n", - " 2023\n", + " 2003-12-31 20:30:00-07:00\n", + " 2003\n", " 12\n", " 31\n", " 20\n", " 30\n", - " 6.2\n", - " -6.9\n", + " -15.6\n", + " -27.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 982.0\n", - " 39.0\n", - " 2.7\n", + " 0.8\n", + " 793.0\n", + " 282.0\n", + " 4.0\n", + " 37.015745\n", " \n", " \n", - " 2023-12-31 21:30:00-07:00\n", - " 2023\n", + " 2003-12-31 21:30:00-07:00\n", + " 2003\n", " 12\n", " 31\n", " 21\n", " 30\n", - " 5.8\n", - " -7.4\n", + " -15.5\n", + " -26.8\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 982.0\n", - " 45.0\n", - " 3.6\n", + " 0.8\n", + " 793.0\n", + " 281.0\n", + " 4.0\n", + " 37.390056\n", " \n", " \n", - " 2023-12-31 22:30:00-07:00\n", - " 2023\n", + " 2003-12-31 22:30:00-07:00\n", + " 2003\n", " 12\n", " 31\n", " 22\n", " 30\n", - " 5.0\n", - " -7.5\n", + " -15.5\n", + " -26.6\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 982.0\n", - " 50.0\n", - " 4.3\n", + " 0.8\n", + " 794.0\n", + " 280.0\n", + " 3.9\n", + " 38.080774\n", " \n", " \n", - " 2023-12-31 23:30:00-07:00\n", - " 2023\n", + " 2003-12-31 23:30:00-07:00\n", + " 2003\n", " 12\n", " 31\n", " 23\n", " 30\n", - " 4.3\n", - " -7.6\n", + " -15.8\n", + " -26.6\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 982.0\n", - " 52.0\n", - " 4.6\n", + " 0.8\n", + " 794.0\n", + " 278.0\n", + " 3.9\n", + " 39.039069\n", " \n", " \n", "\n", - "

8760 rows × 14 columns

\n", + "

8760 rows × 15 columns

\n", "" ], "text/plain": [ - " Year Month Day Hour Minute temp_air temp_dew \\\n", - "2010-01-01 00:30:00-07:00 2010 1 1 0 30 3.9 -7.8 \n", - "2010-01-01 01:30:00-07:00 2010 1 1 1 30 3.8 -8.1 \n", - "2010-01-01 02:30:00-07:00 2010 1 1 2 30 3.9 -8.5 \n", - "2010-01-01 03:30:00-07:00 2010 1 1 3 30 3.9 -8.8 \n", - "2010-01-01 04:30:00-07:00 2010 1 1 4 30 3.8 -9.1 \n", - "... ... ... ... ... ... ... ... \n", - "2023-12-31 19:30:00-07:00 2023 12 31 19 30 6.8 -6.6 \n", - "2023-12-31 20:30:00-07:00 2023 12 31 20 30 6.2 -6.9 \n", - "2023-12-31 21:30:00-07:00 2023 12 31 21 30 5.8 -7.4 \n", - "2023-12-31 22:30:00-07:00 2023 12 31 22 30 5.0 -7.5 \n", - "2023-12-31 23:30:00-07:00 2023 12 31 23 30 4.3 -7.6 \n", + " Year Month Day Hour Minute temp_air \\\n", + "2011-01-01 00:30:00-07:00 2011 1 1 0 30 -16.0 \n", + "2011-01-01 01:30:00-07:00 2011 1 1 1 30 -16.0 \n", + "2011-01-01 02:30:00-07:00 2011 1 1 2 30 -15.9 \n", + "2011-01-01 03:30:00-07:00 2011 1 1 3 30 -15.8 \n", + "2011-01-01 04:30:00-07:00 2011 1 1 4 30 -15.7 \n", + "... ... ... ... ... ... ... \n", + "2003-12-31 19:30:00-07:00 2003 12 31 19 30 -15.7 \n", + "2003-12-31 20:30:00-07:00 2003 12 31 20 30 -15.6 \n", + "2003-12-31 21:30:00-07:00 2003 12 31 21 30 -15.5 \n", + "2003-12-31 22:30:00-07:00 2003 12 31 22 30 -15.5 \n", + "2003-12-31 23:30:00-07:00 2003 12 31 23 30 -15.8 \n", "\n", - " dhi dni ghi albedo pressure wind_direction \\\n", - "2010-01-01 00:30:00-07:00 0.0 0.0 0.0 0.18 982.0 54.0 \n", - "2010-01-01 01:30:00-07:00 0.0 0.0 0.0 0.18 981.0 55.0 \n", - "2010-01-01 02:30:00-07:00 0.0 0.0 0.0 0.18 981.0 55.0 \n", - "2010-01-01 03:30:00-07:00 0.0 0.0 0.0 0.18 981.0 54.0 \n", - "2010-01-01 04:30:00-07:00 0.0 0.0 0.0 0.18 981.0 53.0 \n", - "... ... ... ... ... ... ... \n", - "2023-12-31 19:30:00-07:00 0.0 0.0 0.0 0.18 982.0 30.0 \n", - "2023-12-31 20:30:00-07:00 0.0 0.0 0.0 0.18 982.0 39.0 \n", - "2023-12-31 21:30:00-07:00 0.0 0.0 0.0 0.18 982.0 45.0 \n", - "2023-12-31 22:30:00-07:00 0.0 0.0 0.0 0.18 982.0 50.0 \n", - "2023-12-31 23:30:00-07:00 0.0 0.0 0.0 0.18 982.0 52.0 \n", + " dew_point dhi dni ghi albedo pressure \\\n", + "2011-01-01 00:30:00-07:00 -26.6 0.0 0.0 0.0 0.8 794.0 \n", + "2011-01-01 01:30:00-07:00 -26.5 0.0 0.0 0.0 0.8 794.0 \n", + "2011-01-01 02:30:00-07:00 -26.2 0.0 0.0 0.0 0.8 795.0 \n", + "2011-01-01 03:30:00-07:00 -26.0 0.0 0.0 0.0 0.8 795.0 \n", + "2011-01-01 04:30:00-07:00 -25.7 0.0 0.0 0.0 0.8 795.0 \n", + "... ... ... ... ... ... ... \n", + "2003-12-31 19:30:00-07:00 -26.8 0.0 0.0 0.0 0.8 793.0 \n", + "2003-12-31 20:30:00-07:00 -27.0 0.0 0.0 0.0 0.8 793.0 \n", + "2003-12-31 21:30:00-07:00 -26.8 0.0 0.0 0.0 0.8 793.0 \n", + "2003-12-31 22:30:00-07:00 -26.6 0.0 0.0 0.0 0.8 794.0 \n", + "2003-12-31 23:30:00-07:00 -26.6 0.0 0.0 0.0 0.8 794.0 \n", "\n", - " wind_speed \n", - "2010-01-01 00:30:00-07:00 4.6 \n", - "2010-01-01 01:30:00-07:00 4.5 \n", - "2010-01-01 02:30:00-07:00 4.2 \n", - "2010-01-01 03:30:00-07:00 3.9 \n", - "2010-01-01 04:30:00-07:00 3.6 \n", - "... ... \n", - "2023-12-31 19:30:00-07:00 1.9 \n", - "2023-12-31 20:30:00-07:00 2.7 \n", - "2023-12-31 21:30:00-07:00 3.6 \n", - "2023-12-31 22:30:00-07:00 4.3 \n", - "2023-12-31 23:30:00-07:00 4.6 \n", + " wind_direction wind_speed relative_humidity \n", + "2011-01-01 00:30:00-07:00 276.0 4.0 39.692741 \n", + "2011-01-01 01:30:00-07:00 274.0 4.1 40.057183 \n", + "2011-01-01 02:30:00-07:00 273.0 4.1 40.828082 \n", + "2011-01-01 03:30:00-07:00 272.0 4.1 41.234476 \n", + "2011-01-01 04:30:00-07:00 271.0 4.0 42.023356 \n", + "... ... ... ... \n", + "2003-12-31 19:30:00-07:00 284.0 3.9 38.014453 \n", + "2003-12-31 20:30:00-07:00 282.0 4.0 37.015745 \n", + "2003-12-31 21:30:00-07:00 281.0 4.0 37.390056 \n", + "2003-12-31 22:30:00-07:00 280.0 3.9 38.080774 \n", + "2003-12-31 23:30:00-07:00 278.0 3.9 39.039069 \n", "\n", - "[8760 rows x 14 columns]" + "[8760 rows x 15 columns]" ] }, "execution_count": 7, @@ -595,12 +609,10 @@ "data": { "text/plain": [ "{'Source': 'NSRDB',\n", - " 'Location ID': '323705',\n", + " 'Location ID': '479494',\n", " 'City': '-',\n", " 'State': '-',\n", " 'Country': '-',\n", - " 'Time Zone': -7,\n", - " 'Local Time Zone': -7,\n", " 'Clearsky DHI Units': 'w/m2',\n", " 'Clearsky DNI Units': 'w/m2',\n", " 'Clearsky GHI Units': 'w/m2',\n", @@ -637,9 +649,11 @@ " 'Fill Flag 5': 'Rayleigh Violation',\n", " 'Surface Albedo Units': 'N/A',\n", " 'Version': '4.1.2.dev4+g3b38bc8.d20250228',\n", - " 'latitude': 33.45,\n", - " 'longitude': -112.06,\n", - " 'altitude': 334}" + " 'latitude': 39.73,\n", + " 'longitude': -105.18,\n", + " 'altitude': 1876,\n", + " 'tz': -7,\n", + " 'wind_height': 2}" ] }, "execution_count": 8, @@ -690,7 +704,7 @@ " Hour\n", " Minute\n", " temp_air\n", - " temp_dew\n", + " dew_point\n", " dhi\n", " dni\n", " ghi\n", @@ -698,119 +712,125 @@ " pressure\n", " wind_direction\n", " wind_speed\n", + " relative_humidity\n", " \n", " \n", " \n", " \n", - " 2010-01-01 00:30:00-07:00\n", - " 2010\n", + " 2011-01-01 00:30:00-07:00\n", + " 2011\n", " 1\n", " 1\n", " 0\n", " 30\n", - " 3.9\n", - " -7.8\n", + " -16.0\n", + " -26.6\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 982.0\n", - " 54.0\n", - " 4.6\n", + " 0.8\n", + " 794.0\n", + " 276.0\n", + " 4.0\n", + " 39.692741\n", " \n", " \n", - " 2010-01-01 01:30:00-07:00\n", - " 2010\n", + " 2011-01-01 01:30:00-07:00\n", + " 2011\n", " 1\n", " 1\n", " 1\n", " 30\n", - " 3.8\n", - " -8.1\n", + " -16.0\n", + " -26.5\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 981.0\n", - " 55.0\n", - " 4.5\n", + " 0.8\n", + " 794.0\n", + " 274.0\n", + " 4.1\n", + " 40.057183\n", " \n", " \n", - " 2010-01-01 02:30:00-07:00\n", - " 2010\n", + " 2011-01-01 02:30:00-07:00\n", + " 2011\n", " 1\n", " 1\n", " 2\n", " 30\n", - " 3.9\n", - " -8.5\n", + " -15.9\n", + " -26.2\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 981.0\n", - " 55.0\n", - " 4.2\n", + " 0.8\n", + " 795.0\n", + " 273.0\n", + " 4.1\n", + " 40.828082\n", " \n", " \n", - " 2010-01-01 03:30:00-07:00\n", - " 2010\n", + " 2011-01-01 03:30:00-07:00\n", + " 2011\n", " 1\n", " 1\n", " 3\n", " 30\n", - " 3.9\n", - " -8.8\n", + " -15.8\n", + " -26.0\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 981.0\n", - " 54.0\n", - " 3.9\n", + " 0.8\n", + " 795.0\n", + " 272.0\n", + " 4.1\n", + " 41.234476\n", " \n", " \n", - " 2010-01-01 04:30:00-07:00\n", - " 2010\n", + " 2011-01-01 04:30:00-07:00\n", + " 2011\n", " 1\n", " 1\n", " 4\n", " 30\n", - " 3.8\n", - " -9.1\n", + " -15.7\n", + " -25.7\n", " 0.0\n", " 0.0\n", " 0.0\n", - " 0.18\n", - " 981.0\n", - " 53.0\n", - " 3.6\n", + " 0.8\n", + " 795.0\n", + " 271.0\n", + " 4.0\n", + " 42.023356\n", " \n", " \n", "\n", "" ], "text/plain": [ - " Year Month Day Hour Minute temp_air temp_dew \\\n", - "2010-01-01 00:30:00-07:00 2010 1 1 0 30 3.9 -7.8 \n", - "2010-01-01 01:30:00-07:00 2010 1 1 1 30 3.8 -8.1 \n", - "2010-01-01 02:30:00-07:00 2010 1 1 2 30 3.9 -8.5 \n", - "2010-01-01 03:30:00-07:00 2010 1 1 3 30 3.9 -8.8 \n", - "2010-01-01 04:30:00-07:00 2010 1 1 4 30 3.8 -9.1 \n", + " Year Month Day Hour Minute temp_air \\\n", + "2011-01-01 00:30:00-07:00 2011 1 1 0 30 -16.0 \n", + "2011-01-01 01:30:00-07:00 2011 1 1 1 30 -16.0 \n", + "2011-01-01 02:30:00-07:00 2011 1 1 2 30 -15.9 \n", + "2011-01-01 03:30:00-07:00 2011 1 1 3 30 -15.8 \n", + "2011-01-01 04:30:00-07:00 2011 1 1 4 30 -15.7 \n", "\n", - " dhi dni ghi albedo pressure wind_direction \\\n", - "2010-01-01 00:30:00-07:00 0.0 0.0 0.0 0.18 982.0 54.0 \n", - "2010-01-01 01:30:00-07:00 0.0 0.0 0.0 0.18 981.0 55.0 \n", - "2010-01-01 02:30:00-07:00 0.0 0.0 0.0 0.18 981.0 55.0 \n", - "2010-01-01 03:30:00-07:00 0.0 0.0 0.0 0.18 981.0 54.0 \n", - "2010-01-01 04:30:00-07:00 0.0 0.0 0.0 0.18 981.0 53.0 \n", + " dew_point dhi dni ghi albedo pressure \\\n", + "2011-01-01 00:30:00-07:00 -26.6 0.0 0.0 0.0 0.8 794.0 \n", + "2011-01-01 01:30:00-07:00 -26.5 0.0 0.0 0.0 0.8 794.0 \n", + "2011-01-01 02:30:00-07:00 -26.2 0.0 0.0 0.0 0.8 795.0 \n", + "2011-01-01 03:30:00-07:00 -26.0 0.0 0.0 0.0 0.8 795.0 \n", + "2011-01-01 04:30:00-07:00 -25.7 0.0 0.0 0.0 0.8 795.0 \n", "\n", - " wind_speed \n", - "2010-01-01 00:30:00-07:00 4.6 \n", - "2010-01-01 01:30:00-07:00 4.5 \n", - "2010-01-01 02:30:00-07:00 4.2 \n", - "2010-01-01 03:30:00-07:00 3.9 \n", - "2010-01-01 04:30:00-07:00 3.6 " + " wind_direction wind_speed relative_humidity \n", + "2011-01-01 00:30:00-07:00 276.0 4.0 39.692741 \n", + "2011-01-01 01:30:00-07:00 274.0 4.1 40.057183 \n", + "2011-01-01 02:30:00-07:00 273.0 4.1 40.828082 \n", + "2011-01-01 03:30:00-07:00 272.0 4.1 41.234476 \n", + "2011-01-01 04:30:00-07:00 271.0 4.0 42.023356 " ] }, "execution_count": 9, @@ -824,19 +844,20 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2026-02-03T18:09:15.455093Z", "iopub.status.busy": "2026-02-03T18:09:15.454031Z", "iopub.status.idle": "2026-02-03T18:09:16.158228Z", "shell.execute_reply": "2026-02-03T18:09:16.155383Z" - } + }, + "lines_to_next_cell": 2 }, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -846,8 +867,9 @@ } ], "source": [ - "# Choose the date you want to plot\n", - "date = \"2010-01-01\"\n", + "# Choose the date you want to plot.\n", + "# Note: this TMY is stitched together from different years per month; July here is 2020.\n", + "date = \"2020-07-01\"\n", "mask = weather_df.index.date == pd.to_datetime(date).date()\n", "day_df = weather_df.loc[mask]\n", "\n", @@ -879,30 +901,31 @@ "name": "stdout", "output_type": "stream", "text": [ - "Index(['Year', 'Month', 'Day', 'Hour', 'Minute', 'temp_air', 'temp_dew', 'dhi',\n", - " 'dni', 'ghi', 'albedo', 'pressure', 'wind_direction', 'wind_speed'],\n", + "Index(['Year', 'Month', 'Day', 'Hour', 'Minute', 'temp_air', 'dew_point',\n", + " 'dhi', 'dni', 'ghi', 'albedo', 'pressure', 'wind_direction',\n", + " 'wind_speed', 'relative_humidity'],\n", " dtype='str')\n", - "2003-08-01 00:30:00-07:00 2023-12-31 23:30:00-07:00\n", - " Year Month Day Hour Minute temp_air temp_dew \\\n", - "2010-01-01 00:30:00-07:00 2010 1 1 0 30 3.9 -7.8 \n", - "2010-01-01 01:30:00-07:00 2010 1 1 1 30 3.8 -8.1 \n", - "2010-01-01 02:30:00-07:00 2010 1 1 2 30 3.9 -8.5 \n", - "2010-01-01 03:30:00-07:00 2010 1 1 3 30 3.9 -8.8 \n", - "2010-01-01 04:30:00-07:00 2010 1 1 4 30 3.8 -9.1 \n", + "2001-04-01 00:30:00-07:00 2020-07-31 23:30:00-07:00\n", + " Year Month Day Hour Minute temp_air \\\n", + "2011-01-01 00:30:00-07:00 2011 1 1 0 30 -16.0 \n", + "2011-01-01 01:30:00-07:00 2011 1 1 1 30 -16.0 \n", + "2011-01-01 02:30:00-07:00 2011 1 1 2 30 -15.9 \n", + "2011-01-01 03:30:00-07:00 2011 1 1 3 30 -15.8 \n", + "2011-01-01 04:30:00-07:00 2011 1 1 4 30 -15.7 \n", "\n", - " dhi dni ghi albedo pressure wind_direction \\\n", - "2010-01-01 00:30:00-07:00 0.0 0.0 0.0 0.18 982.0 54.0 \n", - "2010-01-01 01:30:00-07:00 0.0 0.0 0.0 0.18 981.0 55.0 \n", - "2010-01-01 02:30:00-07:00 0.0 0.0 0.0 0.18 981.0 55.0 \n", - "2010-01-01 03:30:00-07:00 0.0 0.0 0.0 0.18 981.0 54.0 \n", - "2010-01-01 04:30:00-07:00 0.0 0.0 0.0 0.18 981.0 53.0 \n", + " dew_point dhi dni ghi albedo pressure \\\n", + "2011-01-01 00:30:00-07:00 -26.6 0.0 0.0 0.0 0.8 794.0 \n", + "2011-01-01 01:30:00-07:00 -26.5 0.0 0.0 0.0 0.8 794.0 \n", + "2011-01-01 02:30:00-07:00 -26.2 0.0 0.0 0.0 0.8 795.0 \n", + "2011-01-01 03:30:00-07:00 -26.0 0.0 0.0 0.0 0.8 795.0 \n", + "2011-01-01 04:30:00-07:00 -25.7 0.0 0.0 0.0 0.8 795.0 \n", "\n", - " wind_speed \n", - "2010-01-01 00:30:00-07:00 4.6 \n", - "2010-01-01 01:30:00-07:00 4.5 \n", - "2010-01-01 02:30:00-07:00 4.2 \n", - "2010-01-01 03:30:00-07:00 3.9 \n", - "2010-01-01 04:30:00-07:00 3.6 \n" + " wind_direction wind_speed relative_humidity \n", + "2011-01-01 00:30:00-07:00 276.0 4.0 39.692741 \n", + "2011-01-01 01:30:00-07:00 274.0 4.1 40.057183 \n", + "2011-01-01 02:30:00-07:00 273.0 4.1 40.828082 \n", + "2011-01-01 03:30:00-07:00 272.0 4.1 41.234476 \n", + "2011-01-01 04:30:00-07:00 271.0 4.0 42.023356 \n" ] } ], @@ -924,7 +947,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 14, "metadata": { "execution": { "iopub.execute_input": "2026-02-03T18:09:16.195740Z", @@ -938,7 +961,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The array surface_tilt angle was not provided, therefore the latitude of 33.5 was used.\n", + "The array surface_tilt angle was not provided, therefore the latitude of 39.7 was used.\n", "The array azimuth was not provided, therefore an azimuth of 180.0 was used.\n" ] } @@ -949,7 +972,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 15, "metadata": { "execution": { "iopub.execute_input": "2026-02-03T18:09:16.307270Z", @@ -963,7 +986,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Minimum installation distance: 0 12.546771\n", + "Minimum installation distance: 0 1.817747\n", "Name: x, dtype: float64\n" ] } @@ -991,7 +1014,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 16, "metadata": { "execution": { "iopub.execute_input": "2026-02-03T18:09:16.328804Z", @@ -1005,7 +1028,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "The array surface_tilt angle was not provided, therefore the latitude of 33.5 was used.\n", + "The array surface_tilt angle was not provided, therefore the latitude of 39.7 was used.\n", "The array azimuth was not provided, therefore an azimuth of 180.0 was used.\n" ] } @@ -1016,7 +1039,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 17, "metadata": { "execution": { "iopub.execute_input": "2026-02-03T18:09:16.429980Z", @@ -1030,7 +1053,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Minimum installation distance: 0 12.546771\n", + "Minimum installation distance: 0 1.817747\n", "Name: x, dtype: float64\n" ] } diff --git a/tutorials/10_workshop_demos/scripts/01_astm_live_demo.py b/tutorials/10_workshop_demos/scripts/01_astm_live_demo.py index d1134f0a..d4e20a36 100644 --- a/tutorials/10_workshop_demos/scripts/01_astm_live_demo.py +++ b/tutorials/10_workshop_demos/scripts/01_astm_live_demo.py @@ -112,18 +112,19 @@ # %% [markdown] # # Fetching TMYs from the NSRDB # -# The NSRDB, one of many sources of weather data intended for PV modeling, is free and easy to access using pvlib. As an example, we'll fetch a TMY dataset for Phoenix, AZ at coordinates [(33.4484, -112.0740)](https://goo.gl/maps/hGV92QHCm5FHJKbf9). +# The NSRDB, one of many sources of weather data intended for PV modeling, is free and easy to access using pvlib. As an example, we'll fetch a TMY dataset for Golden, CO at coordinates [(39.73, -105.18)](https://goo.gl/maps/hGV92QHCm5FHJKbf9). # # This function uses [`pvdeg.weather.get()`](https://pvdegradationtools.readthedocs.io/en/latest/_autosummary/pvdeg.weather.html#pvdeg.weather.get), which returns a Python dictionary of metadata and a Pandas dataframe of the timeseries weather data. # # This function internally leverages [`pvlib.iotools.get_psm3()`](https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.iotools.get_psm3.html). However, for some of the NSRDB data relative humidity is not a given parameter, and `pvdeg` calculates the values from the downloaded data as an internal processing step. +# # %% # This cell is for documentation only and is not meant to be executed. # The next cell performs the same request directly with PVLib. """ weather_db = 'PSM4' -weather_id = (33.4484, -112.0740) +weather_id = (39.73, -105.18) weather_arg = {'api_key': NREL_API_KEY, 'email': 'user@mail.com', 'year': '2021', @@ -133,6 +134,7 @@ weather_df, meta = pvdeg.weather.get(weather_db, weather_id, **weather_arg) """ + # %% # For reproducible CI and offline use, default to cached weather data. # Set USE_LIVE_NSRDB=True during workshops to make the live API call. @@ -140,8 +142,8 @@ if USE_LIVE_NSRDB: weather_df, meta = pvlib.iotools.get_nsrdb_psm4_tmy( - latitude=33.4484, - longitude=-112.0740, + latitude=39.73, + longitude=-105.18, api_key=NREL_API_KEY, email="silvana.ovaitt@nrel.gov", # <-- any email works here fine year="tmy", @@ -160,6 +162,7 @@ with open(meta_path, "r") as f: meta = json.load(f) + # %% weather_df @@ -170,8 +173,9 @@ weather_df.head() # %% -# Choose the date you want to plot -date = "2010-01-01" +# Choose the date you want to plot. +# Note: this TMY is stitched together from different years per month; July here is 2020. +date = "2020-07-01" mask = weather_df.index.date == pd.to_datetime(date).date() day_df = weather_df.loc[mask] @@ -186,6 +190,7 @@ plt.title(f"Weather Data for {date}") plt.show() + # %% print(weather_df.columns) print(weather_df.index.min(), weather_df.index.max()) From 8671306c3dfb7d43fbd2ee20de84f6060b2a7083 Mon Sep 17 00:00:00 2001 From: Daxini Date: Wed, 1 Jul 2026 11:57:03 -0600 Subject: [PATCH 4/5] Update v0.7.2.rst --- docs/source/whatsnew/releases/v0.7.2.rst | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/docs/source/whatsnew/releases/v0.7.2.rst b/docs/source/whatsnew/releases/v0.7.2.rst index 77b50a48..683235b8 100644 --- a/docs/source/whatsnew/releases/v0.7.2.rst +++ b/docs/source/whatsnew/releases/v0.7.2.rst @@ -9,6 +9,14 @@ Documentation ------------- +Notebooks +--------- +- Make the ASTM live demo and custom-functions tutorial notebooks reproducible + offline by loading cached NSRDB TMY data (with ``USE_LIVE_*`` toggle for the + live API path), fixing ``nbval`` failures caused by stale stored outputs and + the PVGIS API being unreachable from CI. (:issue:`342`, :pull:`350`) + + Deprecations ------------- From b8a8db27d2d605ea9364ca44c2cdc4c092614e2a Mon Sep 17 00:00:00 2001 From: Daxini Date: Wed, 1 Jul 2026 14:29:01 -0600 Subject: [PATCH 5/5] Fix scenario temp --- .../04_scenario/01_scenario_temperature.ipynb | 639 +++++++++++++----- .../scripts/01_scenario_temperature.py | 40 +- 2 files changed, 482 insertions(+), 197 deletions(-) diff --git a/tutorials/04_scenario/01_scenario_temperature.ipynb b/tutorials/04_scenario/01_scenario_temperature.ipynb index db59b5fc..de61fbf7 100644 --- a/tutorials/04_scenario/01_scenario_temperature.ipynb +++ b/tutorials/04_scenario/01_scenario_temperature.ipynb @@ -12,10 +12,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T23:42:21.388783Z", - "iopub.status.busy": "2026-01-26T23:42:21.388783Z", - "iopub.status.idle": "2026-01-26T23:42:21.401177Z", - "shell.execute_reply": "2026-01-26T23:42:21.401177Z" + "iopub.execute_input": "2026-07-01T20:17:11.013935Z", + "iopub.status.busy": "2026-07-01T20:17:11.013697Z", + "iopub.status.idle": "2026-07-01T20:17:11.019554Z", + "shell.execute_reply": "2026-07-01T20:17:11.018634Z" } }, "outputs": [], @@ -29,10 +29,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T23:42:21.404728Z", - "iopub.status.busy": "2026-01-26T23:42:21.403717Z", - "iopub.status.idle": "2026-01-26T23:42:25.490141Z", - "shell.execute_reply": "2026-01-26T23:42:25.490141Z" + "iopub.execute_input": "2026-07-01T20:17:11.025233Z", + "iopub.status.busy": "2026-07-01T20:17:11.024482Z", + "iopub.status.idle": "2026-07-01T20:17:17.614401Z", + "shell.execute_reply": "2026-07-01T20:17:17.612317Z" } }, "outputs": [], @@ -46,10 +46,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T23:42:25.490141Z", - "iopub.status.busy": "2026-01-26T23:42:25.490141Z", - "iopub.status.idle": "2026-01-26T23:42:25.501048Z", - "shell.execute_reply": "2026-01-26T23:42:25.501048Z" + "iopub.execute_input": "2026-07-01T20:17:17.619281Z", + "iopub.status.busy": "2026-07-01T20:17:17.618123Z", + "iopub.status.idle": "2026-07-01T20:17:17.628056Z", + "shell.execute_reply": "2026-07-01T20:17:17.626409Z" } }, "outputs": [ @@ -58,8 +58,8 @@ "output_type": "stream", "text": [ "Working on a Windows 11\n", - "Python version 3.12.9 | packaged by Anaconda, Inc. | (main, Feb 6 2025, 18:49:16) [MSC v.1929 64 bit (AMD64)]\n", - "pvdeg version 0.5.1.dev623+g51cc68b8e.d20250905\n" + "Python version 3.13.13 | packaged by conda-forge | (main, Apr 8 2026, 01:56:49) [MSC v.1944 64 bit (AMD64)]\n", + "pvdeg version 0.7.2.dev86+gbddb1bdbc.d20260519\n" ] } ], @@ -87,10 +87,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T23:42:25.501048Z", - "iopub.status.busy": "2026-01-26T23:42:25.501048Z", - "iopub.status.idle": "2026-01-26T23:42:38.685465Z", - "shell.execute_reply": "2026-01-26T23:42:38.685465Z" + "iopub.execute_input": "2026-07-01T20:17:17.667721Z", + "iopub.status.busy": "2026-07-01T20:17:17.667230Z", + "iopub.status.idle": "2026-07-01T20:17:19.430398Z", + "shell.execute_reply": "2026-07-01T20:17:19.428865Z" } }, "outputs": [ @@ -203,10 +203,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T23:42:38.687468Z", - "iopub.status.busy": "2026-01-26T23:42:38.687468Z", - "iopub.status.idle": "2026-01-26T23:42:39.678386Z", - "shell.execute_reply": "2026-01-26T23:42:39.678386Z" + "iopub.execute_input": "2026-07-01T20:17:19.434858Z", + "iopub.status.busy": "2026-07-01T20:17:19.434281Z", + "iopub.status.idle": "2026-07-01T20:17:21.492029Z", + "shell.execute_reply": "2026-07-01T20:17:21.489689Z" } }, "outputs": [ @@ -231,13 +231,13 @@ " \n", "
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self.pipeline

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1970-01-01 12:30:00-05:0036.01717339.16676636.16436735.46469838.386368
1970-01-01 13:30:00-05:0037.93030142.47719938.09968338.24404341.502070
1970-01-01 14:30:00-05:0034.75770540.02864634.88108736.62718939.191667
1970-01-01 15:30:00-05:0030.47179635.66958330.53743633.43078835.077254
1970-01-01 16:30:00-05:0026.34035430.20317526.35521729.22039229.908870
1970-01-01 17:30:00-05:0025.12294525.31956525.12710725.22210725.289002
1970-01-01 18:30:00-05:0024.70000024.70000024.70000024.70000024.700000
1970-01-01 19:30:00-05:0024.60000024.60000024.60000024.60000024.600000
1970-01-01 20:30:00-05:0024.60000024.60000024.60000024.60000024.600000
1970-01-01 21:30:00-05:0024.50000024.50000024.50000024.50000024.500000
1970-01-01 22:30:00-05:0024.50000024.50000024.50000024.50000024.500000
1970-01-01 23:30:00-05:0024.40000024.40000024.40000024.40000024.400000
\n", + "
" + ], + "text/plain": [ + " sapm_1 pvsyst_1 sapm_2 sapm_3 \\\n", + "1970-01-01 00:30:00-05:00 24.100000 24.100000 24.100000 24.100000 \n", + "1970-01-01 01:30:00-05:00 24.100000 24.100000 24.100000 24.100000 \n", + "1970-01-01 02:30:00-05:00 24.000000 24.000000 24.000000 24.000000 \n", + "1970-01-01 03:30:00-05:00 24.000000 24.000000 24.000000 24.000000 \n", + "1970-01-01 04:30:00-05:00 24.000000 24.000000 24.000000 24.000000 \n", + "1970-01-01 05:30:00-05:00 23.900000 23.900000 23.900000 23.900000 \n", + "1970-01-01 06:30:00-05:00 24.000000 24.000000 24.000000 24.000000 \n", + "1970-01-01 07:30:00-05:00 27.565173 25.680763 27.609768 25.351273 \n", + "1970-01-01 08:30:00-05:00 30.664107 29.424296 30.749572 28.055360 \n", + "1970-01-01 09:30:00-05:00 37.165736 35.939976 37.348417 32.527241 \n", + "1970-01-01 10:30:00-05:00 38.435542 39.348967 38.632696 34.996477 \n", + "1970-01-01 11:30:00-05:00 38.956198 41.350708 39.151817 36.773449 \n", + "1970-01-01 12:30:00-05:00 36.017173 39.166766 36.164367 35.464698 \n", + "1970-01-01 13:30:00-05:00 37.930301 42.477199 38.099683 38.244043 \n", + "1970-01-01 14:30:00-05:00 34.757705 40.028646 34.881087 36.627189 \n", + "1970-01-01 15:30:00-05:00 30.471796 35.669583 30.537436 33.430788 \n", + "1970-01-01 16:30:00-05:00 26.340354 30.203175 26.355217 29.220392 \n", + "1970-01-01 17:30:00-05:00 25.122945 25.319565 25.127107 25.222107 \n", + "1970-01-01 18:30:00-05:00 24.700000 24.700000 24.700000 24.700000 \n", + "1970-01-01 19:30:00-05:00 24.600000 24.600000 24.600000 24.600000 \n", + "1970-01-01 20:30:00-05:00 24.600000 24.600000 24.600000 24.600000 \n", + "1970-01-01 21:30:00-05:00 24.500000 24.500000 24.500000 24.500000 \n", + "1970-01-01 22:30:00-05:00 24.500000 24.500000 24.500000 24.500000 \n", + "1970-01-01 23:30:00-05:00 24.400000 24.400000 24.400000 24.400000 \n", + "\n", + " pvsyst_2 \n", + "1970-01-01 00:30:00-05:00 24.100000 \n", + "1970-01-01 01:30:00-05:00 24.100000 \n", + "1970-01-01 02:30:00-05:00 24.000000 \n", + "1970-01-01 03:30:00-05:00 24.000000 \n", + "1970-01-01 04:30:00-05:00 24.000000 \n", + "1970-01-01 05:30:00-05:00 23.900000 \n", + "1970-01-01 06:30:00-05:00 24.000000 \n", + "1970-01-01 07:30:00-05:00 25.611306 \n", + "1970-01-01 08:30:00-05:00 29.169925 \n", + "1970-01-01 09:30:00-05:00 35.319977 \n", + "1970-01-01 10:30:00-05:00 38.540204 \n", + "1970-01-01 11:30:00-05:00 40.435961 \n", + "1970-01-01 12:30:00-05:00 38.386368 \n", + "1970-01-01 13:30:00-05:00 41.502070 \n", + "1970-01-01 14:30:00-05:00 39.191667 \n", + "1970-01-01 15:30:00-05:00 35.077254 \n", + "1970-01-01 16:30:00-05:00 29.908870 \n", + "1970-01-01 17:30:00-05:00 25.289002 \n", + "1970-01-01 18:30:00-05:00 24.700000 \n", + "1970-01-01 19:30:00-05:00 24.600000 \n", + "1970-01-01 20:30:00-05:00 24.600000 \n", + "1970-01-01 21:30:00-05:00 24.500000 \n", + "1970-01-01 22:30:00-05:00 24.500000 \n", + "1970-01-01 23:30:00-05:00 24.400000 " + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -1531,15 +1807,16 @@ "t0 = datetime.datetime(1970, 1, 1, 0, 0)\n", "tf = datetime.datetime(1970, 1, 1, 23, 59)\n", "\n", - "# Get the first function result dynamically\n", - "function_ids = [key[1] for key in scene_temp.results.keys() if key[0] == \"function\"]\n", - "if function_ids:\n", - " temp_df = scene_temp.extract(\n", - " (\"function\", function_ids[0]), tmy=True, start_time=t0, end_time=tf\n", - " )\n", - " display(temp_df)\n", - "else:\n", - " print(\"No function results found\")" + "# scene_temp.results is keyed by module_name, whose values are dicts keyed by\n", + "# job_id. Grab the first job_id from any module to use as the ('function', ...)\n", + "# target for extract/plot.\n", + "first_module_results = next(iter(scene_temp.results.values()))\n", + "first_job_id = next(iter(first_module_results.keys()))\n", + "\n", + "temp_df = scene_temp.extract(\n", + " (\"function\", first_job_id), tmy=True, start_time=t0, end_time=tf\n", + ")\n", + "display(temp_df)" ] }, { @@ -1547,34 +1824,44 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T23:42:39.696743Z", - "iopub.status.busy": "2026-01-26T23:42:39.696743Z", - "iopub.status.idle": "2026-01-26T23:42:39.703802Z", - "shell.execute_reply": "2026-01-26T23:42:39.703802Z" - } + "iopub.execute_input": "2026-07-01T20:17:21.775811Z", + "iopub.status.busy": "2026-07-01T20:17:21.775286Z", + "iopub.status.idle": "2026-07-01T20:17:22.349400Z", + "shell.execute_reply": "2026-07-01T20:17:22.347800Z" + }, + "lines_to_next_cell": 2 }, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "No function results found\n" - ] + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,\n", + " )" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "# Get the first function result dynamically for plotting\n", - "function_ids = [key[1] for key in scene_temp.results.keys() if key[0] == \"function\"]\n", - "if function_ids:\n", - " scene_temp.plot(\n", - " (\"function\", function_ids[0]),\n", - " tmy=True,\n", - " start_time=t0,\n", - " end_time=tf,\n", - " title=\"single day cell temperature\",\n", - " )\n", - "else:\n", - " print(\"No function results found\")" + "scene_temp.plot(\n", + " (\"function\", first_job_id),\n", + " tmy=True,\n", + " start_time=t0,\n", + " end_time=tf,\n", + " title=\"single day cell temperature\",\n", + ")" ] }, { @@ -1589,10 +1876,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2026-01-26T23:42:39.703802Z", - "iopub.status.busy": "2026-01-26T23:42:39.703802Z", - "iopub.status.idle": "2026-01-26T23:42:41.299654Z", - "shell.execute_reply": "2026-01-26T23:42:41.299654Z" + "iopub.execute_input": "2026-07-01T20:17:22.352617Z", + "iopub.status.busy": "2026-07-01T20:17:22.352195Z", + "iopub.status.idle": "2026-07-01T20:17:23.658044Z", + "shell.execute_reply": "2026-07-01T20:17:23.655899Z" } }, "outputs": [ @@ -2165,7 +2452,7 @@ ], "metadata": { "kernelspec": { - "display_name": "pvdeg", + "display_name": "pvdeg2", "language": "python", "name": "python3" }, @@ -2179,7 +2466,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.9" + "version": "3.13.13" } }, "nbformat": 4, diff --git a/tutorials/04_scenario/scripts/01_scenario_temperature.py b/tutorials/04_scenario/scripts/01_scenario_temperature.py index 562449ba..e3e27fc9 100644 --- a/tutorials/04_scenario/scripts/01_scenario_temperature.py +++ b/tutorials/04_scenario/scripts/01_scenario_temperature.py @@ -121,29 +121,27 @@ t0 = datetime.datetime(1970, 1, 1, 0, 0) tf = datetime.datetime(1970, 1, 1, 23, 59) -# Get the first function result dynamically -function_ids = [key[1] for key in scene_temp.results.keys() if key[0] == "function"] -if function_ids: - temp_df = scene_temp.extract( - ("function", function_ids[0]), tmy=True, start_time=t0, end_time=tf - ) - display(temp_df) -else: - print("No function results found") +# scene_temp.results is keyed by module_name, whose values are dicts keyed by +# job_id. Grab the first job_id from any module to use as the ('function', ...) +# target for extract/plot. +first_module_results = next(iter(scene_temp.results.values())) +first_job_id = next(iter(first_module_results.keys())) + +temp_df = scene_temp.extract( + ("function", first_job_id), tmy=True, start_time=t0, end_time=tf +) +display(temp_df) + # %% -# Get the first function result dynamically for plotting -function_ids = [key[1] for key in scene_temp.results.keys() if key[0] == "function"] -if function_ids: - scene_temp.plot( - ("function", function_ids[0]), - tmy=True, - start_time=t0, - end_time=tf, - title="single day cell temperature", - ) -else: - print("No function results found") +scene_temp.plot( + ("function", first_job_id), + tmy=True, + start_time=t0, + end_time=tf, + title="single day cell temperature", +) + # %% [markdown] # # Create a Copy of a Scenario