Map balmorel plotting tool (#27)

* First draft of the map plot tool * Updates : - fix line width problem - add background colormap * Adjust scales for pie plotting * Fixing the legend * Code clearing * code clearing * Ioannis map function deleted * Put possibility to have a personalized geofile again * Fix some coordinates issues * Fix generation_show option issue * Fix savefig issue * Documentation * cartopy * Added option to color countries * Added bioconda * Trying pip instead * Uploading pybalmorel 0.5.0 to PyPI * Added gams system directory to function * New upload --------- Co-authored-by: mathias157 <mathiasros@gmail.com>
balmorelcommunity · Jan 20, 2025 · 7af371f · 7af371f
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diff --git a/docs/conf.py b/docs/conf.py
@@ -1,7 +1,7 @@
 project = "pybalmorel"
 copyright = "2024, Mathias Berg Rosendal, Théodore Le Nalinec"
 author = "Mathias Berg Rosendal, Théodore Le Nalinec"
-release = "0.4.5"
+release = "0.5.1"
 
 exclude_patterns = ["_build", "Thumbs.db", ".DS_Store", ".testenv", ".testenv/**"]
 

diff --git a/docs/examples.md b/docs/examples.md
@@ -5,6 +5,7 @@ The following notebooks can also be downloaded:
 - [Pre-Processing](https://github.com/Mathias157/pybalmorel/blob/master/examples/PreProcessing.ipynb)
 - [Execution](https://github.com/Mathias157/pybalmorel/blob/master/examples/Execution.ipynb)
 - [Post-Processing](https://github.com/Mathias157/pybalmorel/blob/master/examples/PostProcessing.ipynb)
+- [Post_Processing Map]((https://github.com/Mathias157/pybalmorel/blob/master/examples/PostProcessing_map.ipynb))
 
 
 ```{toctree}

diff --git a/docs/examples/postprocessing.md b/docs/examples/postprocessing.md
@@ -30,6 +30,15 @@ model.results.plot_map(model.results.sc[0], 'electricity', 2050)
 model.results.plot_profile('heat', 2050, model.results.sc[1])
 ```
 
+For more information about the map plotting please look here :
+
+```{toctree}
+:maxdepth: 1
+:hidden:
+
+postprocessing_map.md
+```
+
 ## Getting Specific Results
 The `model.results` is actually a `MainResults` class. The example below illustrates how to get specific results using that class.
 

diff --git a/docs/examples/postprocessing_map.md b/docs/examples/postprocessing_map.md
@@ -0,0 +1,161 @@
+# Pybalmorel for map plotting
+
+This notebook provide examples on how to use the pybalmorel post processing map plotting tool. 
+
+```python
+### Loading scenarios
+res = MainResults(files=['MainResults_Example1.gdx', 'MainResults_Example2.gdx', 'MainResults_Example3.gdx'], paths='files', scenario_names=['SC1', 'SC2', 'SC3'])
+```
+
+## Basic map plotting
+
+The map plotting tool only needs 3 arguments to work. One has to select the **scenario** (see scenarios importation in [this section](postprocessing.md)), the **year** and the **commodity** shown on both the lines and the generation capacity. \
+For now, electricity and hydrogen can be selected as commodities. If the information are available in the gdx results file, it should work.
+
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity')
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_4_3.png)
+
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Hydrogen')
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_5_2.png)
+
+
+## Selecting a different transmission information
+
+The option **lines** allows to plot different transmission line information amongst *Capacity*, *FlowYear*, *FlowTime*, *UtilizationYear*, *UtilizationTime*. \
+Please note that for *FlowTime* and *UtilizationTime*, it is possible to select a specific **S** and **T** to select a specific simulation time. \
+It is also possible to select with **generation** the generation information plotted amongst *Capacity* and *Production*. It is also possible to desactivate pie charts with *generation_show* option.
+
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='Capacity', generation='Capacity')
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_7_2.png)
+
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowTime', generation='Production', S='S08', T='T076')
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_8_2.png)
+
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowYear', generation='Production', generation_show=False)
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_9_2.png)
+
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='UtilizationTime', generation='Production')
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_10_2.png)
+
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='UtilizationYear', generation='Production')
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_11_2.png)
+
+
+
+## Background information and legend selection
+
+Using the option **background**, it is possible to plot an additional information that colors the countries. For now *H2 Storage* and *Elec Storage* have been implemented. \
+It is also possible to change the legend of the pie charts and to select either *TECH_TYPE* or *FFF* to be plotted.
+
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowYear', generation='Capacity', background="Elec Storage", generation_var='TECH_TYPE')
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_13_2.png)
+
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowYear', generation='Capacity', background="H2 Storage", generation_var='FFF')
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_14_2.png)
+
+
+## Geofile input and coordinates issues
+
+Using the option **path_to_geofile**, it is possible to use a personalized map file with a specific column (option *geo_file_region_column*) with the name of the regions in your Balmorel file. \
+When using this option, the coordinates are set automatically as the border of the map plus an offset that can be modified with the option *coordinates_geofile_offset*. \
+It is also possible to choose to plot only Denmark by setting *choosen_map_coordinates* as "DK" (if you only have data for denmark, please use it) or to select specific coordinates with *map_coordinates*. \
+Please note that when modifying all of this, you will have trouble with the size of the pie charts that are defined in data values. You will need to modify those to have something that you like. \
+**For now, the legend is only working for the EU coordinates (in the case of having data for all EU) !!**
+
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', path_to_geofile="../../../examples/files/Geofile_Example.geojson")
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_16_4.png)
+
+
+```python
+fig, ax = res.plot_map(scenario='SC1', year=2050, commodity='Electricity', lines='Capacity')
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_17_2.png)
+
+
+```python
+fig, ax = res.plot_map(scenario='SC1', year=2050, commodity='Electricity', lines='Capacity', choosen_map_coordinates="DK")
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_18_2.png)
+
+
+
+## Additional options
+
+There is a large number of additional options available and the detailed can be found in the function's help below :
+
+
+```python
+help(res.plot_map)
+```
+
+Let's review some examnples :
+
+```python
+# If you want to show the value of the lines and not the arrows
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='UtilizationYear', generation='Capacity',
+                       line_label_show=True, line_flow_show=False)
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_21_3.png)
+
+
+```python
+# If you want to clusterize the pie charts and/or the lines and not plot the smaller ones
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowYear', generation='Capacity',
+                       line_width_cat='cluster', pie_radius_cat='cluster', line_show_min=1)
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_22_2.png)
+
+
+```python
+# If you want to specified the colors of things
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowYear', generation='Capacity',
+                       background_color='blue', regions_model_color='green', regions_ext_color='red', line_color='black')
+```
+
+![png](../img/PostProcessing_map_files/PostProcessing_map_23_2.png)
+
+
diff --git a/docs/get_started/installation.md b/docs/get_started/installation.md
@@ -19,8 +19,10 @@ dependencies:
   - geopandas>=1.0.1
   - ipywidgets>=8.1.3
   - ipykernel>=6.29.5
+  - cartopy>=0.24.1
   - pip
   - pip:
-    - pybalmorel==0.4.5
+    - pybalmorel==0.5.1
+    - cartopy>=0.24.1
 ```
 
diff --git a/docs/img/PostProcessing_map_files/PostProcessing_map_10_2.png b/docs/img/PostProcessing_map_files/PostProcessing_map_10_2.png
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diff --git a/docs/img/PostProcessing_map_files/PostProcessing_map_17_2.png b/docs/img/PostProcessing_map_files/PostProcessing_map_17_2.png
diff --git a/docs/img/PostProcessing_map_files/PostProcessing_map_18_2.png b/docs/img/PostProcessing_map_files/PostProcessing_map_18_2.png
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diff --git a/docs/img/PostProcessing_map_files/PostProcessing_map_23_2.png b/docs/img/PostProcessing_map_files/PostProcessing_map_23_2.png
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diff --git a/docs/img/PostProcessing_map_files/PostProcessing_map_7_2.png b/docs/img/PostProcessing_map_files/PostProcessing_map_7_2.png
diff --git a/docs/img/PostProcessing_map_files/PostProcessing_map_8_2.png b/docs/img/PostProcessing_map_files/PostProcessing_map_8_2.png
diff --git a/docs/img/PostProcessing_map_files/PostProcessing_map_9_2.png b/docs/img/PostProcessing_map_files/PostProcessing_map_9_2.png
diff --git a/environment.yaml b/environment.yaml
@@ -12,4 +12,5 @@ dependencies:
   - pytest=8.3.3
   - pip
   - pip:
-    - pybalmorel==0.4.5
+    - pybalmorel==0.5.1
+    - cartopy>=0.24.1