Simplify BRP plots

burggraaff · Sep 5, 2024 · 93311a4 · 93311a4
1 parent 88b0319
commit 93311a4
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Showing 3 changed files with 11 additions and 5 deletions.
diff --git a/demo.ipynb b/demo.ipynb
@@ -154,7 +154,7 @@
    "outputs": [],
    "source": [
     "# Plot\n",
-    "fpcup.plotting.brp_map(brp, column=\"crop_species\", title=\"Selected crop types\", colour_dict=fpcup.plotting.brp_crops_colours)"
+    "fpcup.plotting.brp_map_crop(brp)"
    ]
   },
   {
@@ -175,7 +175,7 @@
    "source": [
     "# Plot\n",
     "province = fpcup.geo.process_input_province(\"Zuid-Holland\") \n",
-    "fpcup.plotting.brp_map(brp, province=province, column=\"crop_species\", title=\"Selected crop types\", colour_dict=fpcup.plotting.brp_crops_colours)"
+    "fpcup.plotting.brp_map_crop(brp, province=province)"
    ]
   },
   {

diff --git a/fpcup/plotting/brp.py b/fpcup/plotting/brp.py
@@ -1,6 +1,8 @@
 """
 Functions for plotting BRP data.
 """
+from functools import partial
+
 import geopandas as gpd
 
 from matplotlib import pyplot as plt, patches as mpatches
@@ -134,6 +136,10 @@ def brp_map(data: gpd.GeoDataFrame, column: str, *,
     plt.close()
 
 
+brp_map_category = partial(brp_map, column="category", title="Land usage", colour_dict=brp_categories_colours)
+brp_map_crop = partial(brp_map, column="crop_species", title="Selected crop types", colour_dict=brp_crops_colours)
+
+
 def brp_crop_map_split(data: gpd.GeoDataFrame, column: str="crop_species", *,
                        province: Province=NETHERLANDS, crops: Iterable[str]=brp_crops_colours.keys(),
                        figsize=(14, 3.5), shape=(1, 5), title: Optional[str]=None, saveto: Optional[PathOrStr]=None, **kwargs) -> None:

diff --git a/process_brp.py b/process_brp.py
@@ -41,7 +41,7 @@
     fpcup.plotting.brp_histogram(brp, column="category", title=filestem, top5=False, saveto=args.results_dir/f"brp{year}-hist_categories.pdf")
 
     for province in fpcup.geo.iterate_over_locations():
-        fpcup.plotting.brp_map(brp, column="category", province=province, title=f"Land usage in {province}\n{filestem}", colour_dict=fpcup.plotting.brp_categories_colours, saveto=args.results_dir/f"brp{year}-map_categories-{province.abbreviation}.pdf")
+        fpcup.plotting.brp_map_category(brp, province=province, saveto=args.results_dir/f"brp{year}-map_categories-{province.abbreviation}.pdf")
 
 # Select cropland
 brp_agro = brp.loc[brp["category"] == "cropland"].drop(columns=["category"])
@@ -71,9 +71,9 @@
 # Show the distribution across the country
 if args.plots:
     for province in fpcup.geo.iterate_over_locations():
-        fpcup.plotting.brp_map(brp_fpcup, column="crop_species", province=province, title=f"Selected crop types in {province}\n{filestem}", colour_dict=fpcup.plotting.brp_crops_colours, saveto=args.results_dir/f"brp{year}-map_crops-filtered-{province.abbreviation}.pdf")
+        fpcup.plotting.brp_map_crop(brp_fpcup, province=province, saveto=args.results_dir/f"brp{year}-map_crops-filtered-{province.abbreviation}.pdf")
 
-        fpcup.plotting.brp_crop_map_split(brp_fpcup, column="crop_species", province=province, title=f"Selected crop types in {province} from {filestem}", saveto=args.results_dir/f"brp{year}-map_crops-individual-{province.abbreviation}.pdf")
+        fpcup.plotting.brp_crop_map_split(brp_fpcup, province=province, title=f"Selected crop types in {province} from {filestem}", saveto=args.results_dir/f"brp{year}-map_crops-individual-{province.abbreviation}.pdf")
 
 # Add centroid coordinates in WGS84 for WOFOST
 coordinates = brp_fpcup.centroid.to_crs("WGS84")