update to new pypsa and scipy version

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/add_electricity.py

@@ -644,7 +644,7 @@ def attach_OPSD_renewables(n, tech_map):
         buses = n.buses.loc[gens.bus.unique()]
         gens_per_bus = gens.groupby("bus").p_nom.count()
 
-        caps = map_country_bus(df.query("Fueltype == @fueltype"), buses)
+        caps = map_country_bus(df.query("Fueltype == @fueltype and lat == lat"), buses)
         caps = caps.groupby(["bus"]).Capacity.sum()
         caps = caps / gens_per_bus.reindex(caps.index, fill_value=1)
 

scripts/cluster_network.py

@@ -89,7 +89,7 @@
     **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 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 @@ def plot_busmap_for_n_clusters(n, n_clusters, fn=None):
         # 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 @@
 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__)

scripts/solve_network.py

@@ -235,8 +235,7 @@ def add_CCL_constraints(n, config):
     p_nom = n.model["Generator-p_nom"]
 
     gens = n.generators.query("p_nom_extendable").rename_axis(index="Generator-ext")
-    grouper = [gens.bus.map(n.buses.country), gens.carrier]
-    grouper = xr.DataArray(pd.MultiIndex.from_arrays(grouper), dims=["Generator-ext"])
+    grouper = pd.concat([gens.bus.map(n.buses.country), gens.carrier])
     lhs = p_nom.groupby(grouper).sum().rename(bus="country")
 
     minimum = xr.DataArray(agg_p_nom_minmax["min"].dropna()).rename(dim_0="group")