use pypsa.clustering.spatial namespace

scripts/_helpers.py

@@ -283,7 +283,7 @@ def get_aggregation_strategies(aggregation_strategies):
     # when custom values are specified in the config.
 
     import numpy as np
-    from pypsa.networkclustering import _make_consense
+    from pypsa.clustering.spatial import _make_consense
 
     bus_strategies = dict(country=_make_consense("Bus", "country"))
     bus_strategies.update(aggregation_strategies.get("buses", {}))

scripts/cluster_network.py

@@ -89,7 +89,7 @@ Description
     **Is it possible to run the model without the** ``simplify_network`` **rule?**
 
         No, the network clustering methods in the PyPSA module
-        `pypsa.networkclustering <https://github.com/PyPSA/PyPSA/blob/master/pypsa/networkclustering.py>`_
+        `pypsa.clustering.spatial <https://github.com/PyPSA/PyPSA/blob/master/pypsa/clustering/spatial.py>`_
         do not work reliably with multiple voltage levels and transformers.
 
 .. tip::
@@ -134,7 +134,7 @@ import pyomo.environ as po
 import pypsa
 import seaborn as sns
 from _helpers import configure_logging, get_aggregation_strategies, update_p_nom_max
-from pypsa.networkclustering import (
+from pypsa.clustering.spatial import (
     busmap_by_greedy_modularity,
     busmap_by_hac,
     busmap_by_kmeans,
@@ -484,7 +484,7 @@ if __name__ == "__main__":
         # Fast-path if no clustering is necessary
         busmap = n.buses.index.to_series()
         linemap = n.lines.index.to_series()
-        clustering = pypsa.networkclustering.Clustering(
+        clustering = pypsa.clustering.spatial.Clustering(
             n, busmap, linemap, linemap, pd.Series(dtype="O")
         )
     else:

scripts/simplify_network.py

@@ -95,13 +95,13 @@ import scipy as sp
 from _helpers import configure_logging, get_aggregation_strategies, update_p_nom_max
 from add_electricity import load_costs
 from cluster_network import cluster_regions, clustering_for_n_clusters
-from pypsa.io import import_components_from_dataframe, import_series_from_dataframe
-from pypsa.networkclustering import (
+from pypsa.clustering.spatial import (
     aggregategenerators,
     aggregateoneport,
     busmap_by_stubs,
     get_clustering_from_busmap,
 )
+from pypsa.io import import_components_from_dataframe, import_series_from_dataframe
 from scipy.sparse.csgraph import connected_components, dijkstra
 
 logger = logging.getLogger(__name__)