chore(examples): Automatic commit of example files in Markdown and Ju…

…pyter Notebook format.
RWTH-EBC · Dec 23, 2024 · e831ebf · e831ebf
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diff --git a/docs/jupyter_notebooks/e1_pull_DWD_historical_to_all_output_formats.ipynb b/docs/jupyter_notebooks/e1_pull_DWD_historical_to_all_output_formats.ipynb
@@ -20,12 +20,12 @@
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "import logging\nlogging.basicConfig(level=\"DEBUG\")\n"
+            "source": "import logging\n\nlogging.basicConfig(level=\"DEBUG\")\n"
         },
         {
             "cell_type": "markdown",
             "metadata": {},
-            "source": "Choose the project class according to the desired weather data origin.\nCheck the project classes file or the API documentation to see which classes are available.\n"
+            "source": "Choose the project class according to the desired weather data origin.\nCheck the project_class.py file or the API documentation to see which classes are available.\n[project classes](https://rwth-ebc.github.io/AixWeather//4-joss_paper//docs/code/aixweather.html#module-aixweather.project_class)\n"
         },
         {
             "cell_type": "code",
@@ -44,7 +44,7 @@
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "import datetime as dt\nDWD_pull_project = ProjectClassDWDHistorical(\n    start=dt.datetime(2022, 1, 1),\n    end=dt.datetime(2023, 1, 1),\n    station=15000,\n    # specify whether nan-values should be filled when exporting\n    fillna=True,\n    # define results path if desired\n    abs_result_folder_path=None,\n)\n"
+            "source": "import datetime as dt\n\nproject = ProjectClassDWDHistorical(\n    start=dt.datetime(2022, 1, 1),\n    end=dt.datetime(2023, 1, 1),\n    station=15000,\n    # specify whether nan-values should be filled when exporting\n    fillna=True,\n    # define results path if desired\n    abs_result_folder_path=None,\n)\n"
         },
         {
             "cell_type": "markdown",
@@ -56,7 +56,7 @@
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "DWD_pull_project.import_data()\nprint(\n    f\"\\nHow the imported data looks like:\\n{DWD_pull_project.imported_data.head()}\\n\"\n)\n"
+            "source": "project.import_data()\nprint(f\"\\nHow the imported data looks like:\\n{project.imported_data.head()}\\n\")\n"
         },
         {
             "cell_type": "markdown",
@@ -68,7 +68,7 @@
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "DWD_pull_project.data_2_core_data()\nprint(f\"\\nHow the core data looks like:\\n{DWD_pull_project.core_data.head()}\\n\")\n"
+            "source": "project.data_2_core_data()\nprint(f\"\\nHow the core data looks like:\\n{project.core_data.head()}\\n\")\n"
         },
         {
             "cell_type": "markdown",
@@ -92,7 +92,7 @@
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "plot = plot_heatmap_missing_values(DWD_pull_project.core_data)\nplot.show()\n"
+            "source": "plot = plot_heatmap_missing_values(project.core_data)\nplot.show()\n"
         },
         {
             "cell_type": "markdown",
@@ -104,7 +104,60 @@
             "execution_count": null,
             "metadata": {},
             "outputs": [],
-            "source": "DWD_pull_project.core_2_csv()\nDWD_pull_project.core_2_json()\nDWD_pull_project.core_2_pickle()\nDWD_pull_project.core_2_mos()\nDWD_pull_project.core_2_epw()\n"
+            "source": "project.core_2_csv()\nproject.core_2_json()\nproject.core_2_pickle()\nproject.core_2_mos()\nproject.core_2_epw()\n"
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": "By the way, if you want to run this with some other weather data source, here are some copy-paste snippets to get you started:\n"
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": "For DWD Forecast data\n"
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": "from aixweather.project_class import ProjectClassDWDForecast\n\nproject = ProjectClassDWDForecast(\n    station=\"06710\",  # Example station: Lausanne\n    abs_result_folder_path=None,  # Optional: specify result path\n)\n"
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": "For EPW and TRY we need to import the .epw or .dat file\nThese imports are just to create the path to the file stored in the tests folder\n"
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": "import os\nfrom aixweather import definitions\n"
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": "For EPW files\n"
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": "from aixweather.project_class import ProjectClassEPW\n\nproject = ProjectClassEPW(\n    path=os.path.join(\n        definitions.ROOT_DIR,\n        \"tests/test_files/regular_tests/EPW/test_EPW_Essen_Ladybug/input/DEU_NW_Essen_104100_TRY2035_05_Wint_BBSR.epw\",\n    ),  # Example: EPW weather file for Essen\n    abs_result_folder_path=None,\n)\n"
+        },
+        {
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": "For TRY (Test Reference Year) data\n"
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": "from aixweather.project_class import ProjectClassTRY\n\nproject = ProjectClassTRY(\n    path=os.path.join(\n        definitions.ROOT_DIR,\n        \"tests/test_files/regular_tests/TRY/test_TRY2015/input/TRY2015_507931060546_Jahr.dat\"\n    ),\n)\n"
         }
     ],
     "metadata": {

diff --git a/docs/source/examples/e1_pull_DWD_historical_to_all_output_formats.md b/docs/source/examples/e1_pull_DWD_historical_to_all_output_formats.md
@@ -11,11 +11,13 @@ Enable logging, this is just to get more feedback through the terminal
 
 ```python
 import logging
+
 logging.basicConfig(level="DEBUG")
 ```
 
 Choose the project class according to the desired weather data origin.
-Check the project classes file or the API documentation to see which classes are available.
+Check the project_class.py file or the API documentation to see which classes are available.
+[project classes](https://rwth-ebc.github.io/AixWeather//4-joss_paper//docs/code/aixweather.html#module-aixweather.project_class)
 
 ```python
 from aixweather.project_class import ProjectClassDWDHistorical
@@ -26,7 +28,8 @@ For this, we use the datetime module to specify dates.
 
 ```python
 import datetime as dt
-DWD_pull_project = ProjectClassDWDHistorical(
+
+project = ProjectClassDWDHistorical(
     start=dt.datetime(2022, 1, 1),
     end=dt.datetime(2023, 1, 1),
     station=15000,
@@ -40,17 +43,15 @@ DWD_pull_project = ProjectClassDWDHistorical(
 Step 1: Import historical weather from the DWD open access database
 
 ```python
-DWD_pull_project.import_data()
-print(
-    f"\nHow the imported data looks like:\n{DWD_pull_project.imported_data.head()}\n"
-)
+project.import_data()
+print(f"\nHow the imported data looks like:\n{project.imported_data.head()}\n")
 ```
 
 Step 2: Convert this imported data to the core format
 
 ```python
-DWD_pull_project.data_2_core_data()
-print(f"\nHow the core data looks like:\n{DWD_pull_project.core_data.head()}\n")
+project.data_2_core_data()
+print(f"\nHow the core data looks like:\n{project.core_data.head()}\n")
 ```
 
 You may optionally also use data quality check utils, like:
@@ -62,16 +63,64 @@ from aixweather.data_quality_checks import plot_heatmap_missing_values
 Plot data quality
 
 ```python
-plot = plot_heatmap_missing_values(DWD_pull_project.core_data)
+plot = plot_heatmap_missing_values(project.core_data)
 plot.show()
 ```
 
 Step 3: Convert this core data to an output data format of your choice
 
 ```python
-DWD_pull_project.core_2_csv()
-DWD_pull_project.core_2_json()
-DWD_pull_project.core_2_pickle()
-DWD_pull_project.core_2_mos()
-DWD_pull_project.core_2_epw()
+project.core_2_csv()
+project.core_2_json()
+project.core_2_pickle()
+project.core_2_mos()
+project.core_2_epw()
+```
+
+By the way, if you want to run this with some other weather data source, here are some copy-paste snippets to get you started:
+
+For DWD Forecast data
+
+```python
+from aixweather.project_class import ProjectClassDWDForecast
+
+project = ProjectClassDWDForecast(
+    station="06710",  # Example station: Lausanne
+    abs_result_folder_path=None,  # Optional: specify result path
+)
+```
+
+For EPW and TRY we need to import the .epw or .dat file
+These imports are just to create the path to the file stored in the tests folder
+
+```python
+import os
+from aixweather import definitions
+```
+
+For EPW files
+
+```python
+from aixweather.project_class import ProjectClassEPW
+
+project = ProjectClassEPW(
+    path=os.path.join(
+        definitions.ROOT_DIR,
+        "tests/test_files/regular_tests/EPW/test_EPW_Essen_Ladybug/input/DEU_NW_Essen_104100_TRY2035_05_Wint_BBSR.epw",
+    ),  # Example: EPW weather file for Essen
+    abs_result_folder_path=None,
+)
+```
+
+For TRY (Test Reference Year) data
+
+```python
+from aixweather.project_class import ProjectClassTRY
+
+project = ProjectClassTRY(
+    path=os.path.join(
+        definitions.ROOT_DIR,
+        "tests/test_files/regular_tests/TRY/test_TRY2015/input/TRY2015_507931060546_Jahr.dat"
+    ),
+)
 ```