new spatial clustering method: modularity

envs/environment.yaml

@@ -10,7 +10,6 @@ dependencies:
   - python>=3.8
   - pip
 
-  - pypsa>=0.19.1
   - atlite>=0.2.6
   - dask
 
@@ -55,5 +54,6 @@ dependencies:
   - tabula-py
 
   - pip:
+    - git+https://github.com/pypsa/pypsa.git#egg=pypsa
     - vresutils>=0.3.1
     - tsam>=1.1.0

scripts/cluster_network.py

@@ -138,7 +138,8 @@ import seaborn as sns
 from functools import reduce
 
 from pypsa.networkclustering import (busmap_by_kmeans, busmap_by_spectral_clustering,
-                                     busmap_by_hac, _make_consense, get_clustering_from_busmap)
+                                     busmap_by_hac, busmap_by_greedy_modularity,
+                                     _make_consense, get_clustering_from_busmap)
 
 import warnings
 warnings.filterwarnings(action='ignore', category=UserWarning)
@@ -326,6 +327,8 @@ def busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights=None, algori
             return prefix + busmap_by_louvain(reduce_network(n, x), n_clusters[x.name], **algorithm_kwds)
         elif algorithm == "hac":
             return prefix + busmap_by_hac(n, n_clusters[x.name], buses_i=x.index, feature=feature.loc[x.index])
+        elif algorithm == "modularity":
+            return prefix + busmap_by_greedy_modularity(n, n_clusters[x.name], buses_i=x.index)
         else:
             raise ValueError(f"`algorithm` must be one of 'kmeans', 'hac', 'spectral' or 'louvain'. Is {algorithm}.")