Dev pyheatdemand (#21)

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CONTRIBUTING.md

@@ -9,12 +9,14 @@ Here is how to get started.
 ### Questions
 
 For questions about PyHeatDemand (e.g. its applications, functionality, and usage), 
-please [search the existing issues for related questions](https://github.com/AlexanderJuestel/pyhheatdemand/issues).
-If your question has not already been asked, then [make a new issue](https://github.com/AlexanderJuestel/pyhheatdemand/issues/new/choose).
+
+please [search the existing issues for related questions](https://github.com/AlexanderJuestel/pyheatdemand/issues).
+If your question has not already been asked, then [make a new issue](https://github.com/AlexanderJuestel/pyheatdemand/issues/new/choose).
+
 
 ### Reporting Bugs
 
-Please report bugs on the [issue page using the bug report template](https://github.com/AlexanderJuestel/pyhheatdemand/issues/new?assignees=&labels=&template=bug_report.md&title=) and label the issue as a bug.
+Please report bugs on the [issue page using the bug report template](https://github.com/AlexanderJuestel/pyheatdemand/issues/new?assignees=&labels=&template=bug_report.md&title=) and label the issue as a bug.
 The template asks essential questions for you to answer so that we can to understand, reproduce, and fix the bug. 
 Be verbose!
 Whenever possible, provide tracebacks and/or error messages, screenshots, and sample code or other files.
@@ -23,7 +25,7 @@ Whenever possible, provide tracebacks and/or error messages, screenshots, and sa
 
 We encourage users to submit ideas for improvements to the PyHeatDemand project. For
 this please create an issue on the
- [issue page](https://github.com/AlexanderJuestel/pyhheatdemand/issues) with the *Feature 
+ [issue page](https://github.com/AlexanderJuestel/pyheatdemand/issues) with the *Feature 
  Request* template and label. Please make sure to use a descriptive title and to
  provide ample background information to help us implement that functionality
  in the future.
@@ -39,7 +41,7 @@ or anything that you think should be in the repository.
 Contributions should address an open issue (either a bug or a feature request).
 If you have found a new bug 
 or have an idea or a new feature, 
-then please [open the issue](https://github.com/AlexanderJuestel/pyhheatdemand/issues/new/choose) 
+then please [open the issue](https://github.com/AlexanderJuestel/pyheatdemand/issues/new/choose) 
 for discussion and link to that issue in your pull request.
 
 ### Python code guidelines
@@ -78,7 +80,7 @@ For all comments, follow [PEP 8](https://www.python.org/dev/peps/pep-0008/).
 ### Licensing
 
 All contributed code will be licensed under 
-[a LGPL-3 license](https://github.com/AlexanderJuestel/pyhheatdemand/blob/main/LICENSE).
+[a LGPL-3 license](https://github.com/AlexanderJuestel/pyheatdemand/blob/main/LICENSE).
 If you did not write the code yourself, 
 it is your responsibility to ensure that the existing license is compatible 
 and included in the contributed files. 
@@ -91,7 +93,7 @@ You should be familiar with `pytest` before contributing.
 Please run all tests locally before creating a pull request. 
 You can do this by running `pytest` via your terminal in your PyHeatDemand folder:
 ```bash
-cd ./path/to/pyhheatdemand
+cd ./path/to/pyheatdemand
 pytest
 ```
 All tests are located in the `test` folder and its subfolders.  
@@ -100,4 +102,4 @@ All contributed code must include test code in the pull request.
 ### Pull Requests
 
 All contributions are made via pull requests (PR's) to the main branch. 
-You must complete the checklist in the [PR template](https://github.com/AlexanderJuestel/pyhheatdemand/blob/main/PULL_REQUEST_TEMPLATE.md) before we will review the PR and consider merging your contribution.
+You must complete the checklist in the [PR template](https://github.com/AlexanderJuestel/pyheatdemand/blob/main/PULL_REQUEST_TEMPLATE.md) before we will review the PR and consider merging your contribution.

README.md

@@ -55,6 +55,9 @@ A CI is present to test the current code. It can be initiated using `pytest --co
 running the tests, `coverage report -m` can be executed to get an report on the coverage and which lines are not covered
 by the tests.
 
+## API Reference
+For creating the API reference, navigate to the `docs` folder and execute `sphinx-apidoc -o source/ ../pyheatdemand`.
+
 <a name="ref"></a>
 ## References
 

docs/source/about.rst

@@ -51,7 +51,7 @@ Resources
 * `DGE Rollout Webviewer <https://data.geus.dk/egdi/?mapname=dgerolloutwebtool#baslay=baseMapGEUS&extent=39620,-1581250,8465360,8046630&layers=dge_heat_final>`_
 
 Citing PyHeatDemand
------------
+-------------------
 If you are using **PyHeatDemand** for your scientific research, please remember to cite our work.
 
 .. code::

pyheatdemand/processing.py

@@ -188,15 +188,15 @@ def create_outline(gdf: gpd.GeoDataFrame) -> gpd.GeoDataFrame:
 
 
 def calculate_hd(hd_gdf: gpd.GeoDataFrame,
-                 mask_gdf: gpd.GeoDataFrame,
+                 mask_gdf: Union[gpd.GeoDataFrame, Polygon],
                  hd_data_column: str = ''):
     """Calculate Heat Demand.
 
     Parameters
     __________
         hd_gdf : gpd.GeoDataFrame
             Heat demand data as GeoDataFrame.
-        mask_gdf : gpd.GeoDataFrame
+        mask_gdf : Union[gpd.GeoDataFrame, shapely.geometry.Polygon]
             Mask for the output Heat Demand Data.
         hd_data_column : str
             Name of the column that contains the Heat Demand Data, e.g. ``hd_data_column='HD'``.
@@ -224,6 +224,11 @@ def calculate_hd(hd_gdf: gpd.GeoDataFrame,
 
     """
 
+    # Converting Shapely Polygon to GeoDataFrame
+    if isinstance(mask_gdf, Polygon):
+        mask_gdf = gpd.GeoDataFrame(geometry=[mask_gdf],
+                                    crs=hd_gdf.crs)
+
     # Checking that the hd_gdf is of type GeoDataFrame
     if not isinstance(hd_gdf, gpd.GeoDataFrame):
         raise TypeError('The heat demand gdf must be provided as GeoDataFrame')
@@ -244,34 +249,41 @@ def calculate_hd(hd_gdf: gpd.GeoDataFrame,
     if mask_gdf.crs != hd_gdf.crs:
         hd_gdf = hd_gdf.to_crs(mask_gdf.crs)
 
+    # Exploding MultiPolygons
     if any(shapely.get_type_id(hd_gdf.geometry) == 6):
         hd_gdf = hd_gdf.explode(index_parts=True).reset_index(drop=True)
 
+    # Assigning area to Polygons
     if all(shapely.get_type_id(hd_gdf.geometry) == 3):
         # Assigning area of original geometries to GeoDataFrame
         hd_gdf['area'] = hd_gdf.area
 
+    # Assigning lengths to LineStrings
     elif all(shapely.get_type_id(hd_gdf.geometry) == 1):
         # Assigning length of original geometries to GeoDataFrame
         hd_gdf['length'] = hd_gdf.length
 
     # Overlaying Heat Demand Data with Mask
     overlay = gpd.overlay(df1=hd_gdf,
                           df2=mask_gdf)
+
+    # Calculate HD for Polygons
     if all(shapely.get_type_id(hd_gdf.geometry) == 3):
         # Assigning area of splitted geometries to GeoDataFrame
         overlay['area_new'] = overlay.area
 
         # Calculating the share of the original Heat Demand for each splitted geometry
         overlay['HD'] = overlay[hd_data_column] * overlay['area_new'] / overlay['area']
 
+    #  Calculate HD for LineStrings
     elif all(shapely.get_type_id(hd_gdf.geometry) == 1):
         # Assigning length of splitted geometries to GeoDataFrame
         overlay['length_new'] = overlay.length
 
         # Calculating the share of the original Heat Demand for each splitted geometry
         overlay['HD'] = overlay[hd_data_column] * overlay['length_new'] / overlay['length']
 
+    # Calculate HD for Points
     elif all(shapely.get_type_id(hd_gdf.geometry) == 0):
         overlay['HD'] = overlay[hd_data_column]
 

test/test_processing.py

@@ -154,6 +154,13 @@ def test_calculate_hd(mask_gdf, hd_gdf):
     assert isinstance(gdf_hd, gpd.GeoDataFrame)
     assert gdf_hd.crs == hd_gdf.crs
 
+    gdf_hd = calculate_hd(hd_gdf=hd_gdf,
+                          mask_gdf=mask_gdf.iloc[0].geometry,
+                          hd_data_column='WOHNGEB_WB')
+
+    assert isinstance(gdf_hd, gpd.GeoDataFrame)
+    assert gdf_hd.crs == hd_gdf.crs
+
 
 @pytest.mark.parametrize('mask_gdf',
                          [gpd.read_file('data/Interreg_NWE_mask_500m_EPSG3034.shp')])