Some fixing and documentation

balmorelcommunity · Jan 30, 2025 · 38a5adf · 38a5adf
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diff --git a/docs/postprocessing/map_plotting.md b/docs/postprocessing/map_plotting.md
@@ -9,118 +9,152 @@ res = MainResults(files=['MainResults_Example1.gdx', 'MainResults_Example2.gdx',
 
 ## 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.
+The map plotting tool only needs 2 arguments to work. One has to select the **scenario** (see scenarios importation in [this section](postprocessing.md)), and the **year**. \
+With those two arguments, the map of Europe is plotted with the countries inside the model in beige and the countries outside of the model in grey. \
+To plot the transmission lines and the generation information, one has to set the parameters **lines**, **generation**, and **commodity** (*Electricity* or *Hydrogen*). \
+Please note that lines and generation can also be plotted alone but that **commodity is always necessary if one of them is used.**
 
 
 ```python
-fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity')
+fig, ax = res.plot_map(scenario='SC3', year=2050)
 ```
 
-![png](../img/PostProcessing_map_files/PostProcessing_map_4_3.png)
+![png](../img/PostProcessing_map_files/MapPlotting_4_2.png)
 
 
 ```python
-fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Hydrogen')
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='Capacity', generation='Capacity')
 ```
 
-![png](../img/PostProcessing_map_files/PostProcessing_map_5_2.png)
+![png](../img/PostProcessing_map_files/MapPlotting_5_2.png)
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Hydrogen', lines='Capacity')
+```
+
+![png](../img/PostProcessing_map_files/MapPlotting_6_2.png)
 
 
-## Selecting a different transmission information
+## Selecting different transmission and generation 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.
+The option **generation** allows to plot different generation information amongst *Capacity*, *Production*, *ProductionTime*. \
+Please note that for *FlowTime*, *UtilizationTime* and *ProductionTime*, it is possible to select a specific **S** and **T**. \
+If one wants the lines commodity and the generation commodity to be different, they can use the **generation_commodity** option.
 
 
 ```python
-fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='Capacity', generation='Capacity')
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowYear', generation='Production')
 ```
 
-![png](../img/PostProcessing_map_files/PostProcessing_map_7_2.png)
+![png](../img/PostProcessing_map_files/MapPlotting_8_2.png)
 
 
 ```python
-fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowTime', generation='Production', S='S08', T='T076')
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowTime', generation='ProductionTime', S='S08', T='T076')
 ```
 
-![png](../img/PostProcessing_map_files/PostProcessing_map_8_2.png)
+![png](../img/PostProcessing_map_files/MapPlotting_9_2.png)
 
 
 ```python
-fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowYear', generation='Production', generation_show=False)
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Hydrogen', generation_commodity='Electricity', lines='UtilizationYear', generation='Production')
 ```
 
-![png](../img/PostProcessing_map_files/PostProcessing_map_9_2.png)
+![png](../img/PostProcessing_map_files/MapPlotting_10_2.png)
 
 
+## Background information
+
+Using the option **background**, it is possible to plot an additional information that colors the countries. For now *H2 Storage*, *Elec Storage*, *Elec Net Export* and *H2 Net Export* have been implemented. \
+It is possible to personalize the background scale with the option **background_scale** and **background_scale_tick** as in the examples below (both can be used at the same time).
+
+
 ```python
-fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='UtilizationTime', generation='Production')
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='Capacity', generation='Capacity', 
+                       background="Elec Storage")
 ```
-    
-![png](../img/PostProcessing_map_files/PostProcessing_map_10_2.png)
+
+![png](../img/PostProcessing_map_files/MapPlotting_12_3.png)
 
 
 ```python
-fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='UtilizationYear', generation='Production')
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Hydrogen', lines='Capacity', generation='Capacity', 
+                       background="H2 Storage", background_scale = [0,25])
 ```
 
-![png](../img/PostProcessing_map_files/PostProcessing_map_11_2.png)
-
+![png](../img/PostProcessing_map_files/MapPlotting_13_3.png)
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowYear', generation='Production', 
+                       background="Elec Net Export", background_scale_tick = 20)
+```
 
+![png](../img/PostProcessing_map_files/MapPlotting_14_3.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.
+## Size of the elements and legend 
+
+The size of the lines and pie charts is function of the options **line_width_cat** and **pie_radius_cat** and can be selected amongst *log*, *linear*, and *cluster*. (log is the default one) \
+While *log* and *linear* are computing the sizes based on maximum and minimum values (those values can be changed), *cluster* needs the input of cluster values and cluster widths/radius to work (see example below). \
+The size of the lines and the pie charts in the legend is automatic but one can choose to personalized them with **line_legend_cluster_values** and **pie_legend_cluster_values**. \
+Please note that if *cluster* is choosed as category, then the legend will used those categories. The width of the lines is in point and the radius of the pie chart in data unit. \
+It is also possible to change the legend of the pie charts and to select either *TECH_TYPE* or *FFF* to be plotted with the option **generation_var**.
 
 
 ```python
-fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowYear', generation='Capacity', background="Elec Storage", generation_var='TECH_TYPE')
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='Capacity', generation='Capacity', generation_var='TECH_TYPE',
+                       line_width_cat = 'linear', pie_radius_cat = 'linear')
 ```
-
-![png](../img/PostProcessing_map_files/PostProcessing_map_13_2.png)
-
+
+![png](../img/PostProcessing_map_files/MapPlotting_16_2.png)
 
 ```python
-fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowYear', generation='Capacity', background="H2 Storage", generation_var='FFF')
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='Capacity', generation='Capacity', generation_var='FFF',
+                       line_legend_cluster_values=[10, 20, 50, 75], pie_legend_cluster_values=[10, 100, 300, 500])
 ```
-
-![png](../img/PostProcessing_map_files/PostProcessing_map_14_2.png)
+
+![png](../img/PostProcessing_map_files/MapPlotting_17_2.png)
+
+```python
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='Capacity', generation='Capacity',
+                       line_width_cat = 'cluster', line_cluster_values = [5, 10, 40, 80], line_cluster_widths = [0.5, 2, 5, 12],
+                       pie_radius_cat = 'cluster', pie_cluster_values = [50, 100, 300, 500], pie_cluster_radius = [0.2, 0.5, 1, 1.5])
+```
+
+![png](../img/PostProcessing_map_files/MapPlotting_18_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*. \
+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. \
+Please note that when modifying all of this, you will have trouble with the size of the lines and 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)
+![png](../img/PostProcessing_map_files/MapPlotting_20_2.png)
 
 
 ```python
-fig, ax = res.plot_map(scenario='SC1', year=2050, commodity='Electricity', lines='Capacity')
+fig, ax = res.plot_map(scenario='SC1', year=2050, commodity='Electricity', lines='Capacity', generation='Capacity')
 ```
 
-![png](../img/PostProcessing_map_files/PostProcessing_map_17_2.png)
+![png](../img/PostProcessing_map_files/MapPlotting_21_2.png)
 
 
 ```python
-fig, ax = res.plot_map(scenario='SC1', year=2050, commodity='Electricity', lines='Capacity', choosen_map_coordinates="DK")
+fig, ax = res.plot_map(scenario='SC1', year=2050, commodity='Electricity', lines='Capacity', generation='Capacity', choosen_map_coordinates="DK")
 ```
 
-![png](../img/PostProcessing_map_files/PostProcessing_map_18_2.png)
+![png](../img/PostProcessing_map_files/MapPlotting_22_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 :
@@ -137,25 +171,28 @@ Let's review some examnples :
 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)
-
 
+![png](../img/PostProcessing_map_files/MapPlotting_25_2.png)
+
 ```python
-# If you want to clusterize the pie charts and/or the lines and not plot the smaller ones
+# If you want to not plot the smaller lines and pies you can define a minimum value
 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)
+                       line_show_min=10, pie_show_min=50)
 ```
 
-![png](../img/PostProcessing_map_files/PostProcessing_map_22_2.png)
+![png](../img/PostProcessing_map_files/MapPlotting_26_2.png)
 
-
 ```python
-# If you want to specified the colors of things
+# If you want to specified the colors of different things on the graph
 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)
+![png](../img/PostProcessing_map_files/MapPlotting_27_2.png)
 
-
+```python
+# If you want to specify the colors used for the different countries, using a csv file (this coloring has the priority on everything) 
+fig, ax = res.plot_map(scenario='SC3', year=2050, commodity='Electricity', lines='FlowYear', generation='Production',
+                       countries_colors_path = "../../../examples/files/countries_colors_example.csv")
+```
+![png](../img/PostProcessing_map_files/MapPlotting_28_2.png)
diff --git a/examples/MapPlotting.ipynb b/examples/MapPlotting.ipynb
diff --git a/src/pybalmorel/classes.py b/src/pybalmorel/classes.py
@@ -189,7 +189,6 @@ def plot_map(self,
             generation (str, optional): Generation information plots on the countries. Choose from ['Capacity', 'Production', 'ProductionTime].
             background (str, optional): Background information to be shown on the map. Choose from ['H2 Storage', 'Elec Storage']. Defaults to 'None'.
             save_fig (bool, optional): Save the figure or not. Defaults to False.
-            system_directory (str, optional): GAMS system directory. Default does NOT WORK! Need to make some if statements so it's not specified if not specified
             path_to_geofile (str, optional): Path to a personalized geofile. Defaults to None.
             geo_file_region_column (str, optional): Column name of the region names in the geofile. Defaults to 'id'.
             Structural additional options:
@@ -236,7 +235,7 @@ def plot_map(self,
                     **pie_legend_cluster_radius (list, optional) = The legend capacity grouping if a specific legend is needed. Is handled automatically if not defined. Not used if cat is 'cluster'. 
                 Background options :
                     **background_scale (list, optional) : Scale used for the background coloring. Defaults to (0, Max value found in results).
-                    **background_legend_tick (int, optional) : A tick every x units in the background legend. Defaults to 2.
+                    **background_scale_tick (int, optional) : A tick every x units in the background legend. Defaults to 2.
             Colors additional options:
                 **background_color (str, optional): Background color of the map. Defaults to 'white'.
                 **regions_ext_color (str, optional): Color of regions outside the model. Defaults to '#d3d3d3'.