def busmap_by_spectral_clustering(network, n_clusters, **kwds):
if find_spec('sklearn') is None:
raise ModuleNotFoundError(
"Optional dependency 'sklearn' not found."
"Install via 'conda install -c conda-forge scikit-learn' "
"or 'pip install scikit-learn'")
from sklearn.cluster import spectral_clustering as sk_spectral_clustering
weight = {
"Line":
network.lines.s_max_pu * network.lines.s_nom.clip(.1) /
abs(network.lines.r + 1j * network.lines.x),
"Link":
network.links.p_max_pu * network.links.p_nom.clip(.1)
}
A = network.adjacency_matrix(branch_components=["Line", "Link"],
weights=weight)
# input arg for spectral clustering must be symmetric, but A is directed. use A+A.T:
return pd.Series(sk_spectral_clustering(A + A.T,
n_clusters=n_clusters).astype(str),
index=network.buses.index)
def busmap_by_spectral_clustering(network, n_clusters, **kwds):
lines = network.lines.loc[:,['bus0', 'bus1']].assign(weight=1./network.lines.x).set_index(['bus0','bus1'])
G = OrderedGraph()
G.add_nodes_from(network.buses.index)
G.add_edges_from((u,v,dict(weight=w)) for (u,v),w in lines.itertuples())
return pd.Series(sk_spectral_clustering(nx.adjacency_matrix(G), n_clusters, **kwds) + 1,
index=network.buses.index)
def busmap_by_spectral_clustering(network, n_clusters, **kwds):
lines = network.lines.loc[:,['bus0', 'bus1']].assign(weight=1./network.lines.x).set_index(['bus0','bus1'])
G = OrderedGraph()
G.add_nodes_from(network.buses.index)
G.add_edges_from((u,v,dict(weight=w)) for (u,v),w in lines.itertuples())
return pd.Series(sk_spectral_clustering(nx.adjacency_matrix(G), n_clusters, **kwds) + 1,
index=network.buses.index)
def busmap_by_spectral_clustering(network, n_clusters, **kwds):
lines = network.lines.loc[:,['bus0', 'bus1']].assign(weight=network.lines.num_parallel).set_index(['bus0','bus1'])
lines.weight+=0.1
G = nx.Graph()
G.add_nodes_from(network.buses.index)
G.add_edges_from((u,v,dict(weight=w)) for (u,v),w in lines.itertuples())
return pd.Series(list(map(str,sk_spectral_clustering(nx.adjacency_matrix(G), n_clusters, **kwds) + 1)),
index=network.buses.index)
def busmap_by_spectral_clustering(network, n_clusters, **kwds):
if find_spec('sklearn') is None:
raise ModuleNotFoundError(
"Optional dependency 'sklearn' not found."
"Install via 'conda install -c conda-forge scikit-learn' "
"or 'pip install scikit-learn'")
from sklearn.cluster import spectral_clustering as sk_spectral_clustering
lines = network.lines.loc[:, ['bus0', 'bus1']].assign(
weight=network.lines.num_parallel).set_index(['bus0', 'bus1'])
lines.weight += 0.1
G = nx.Graph()
G.add_nodes_from(network.buses.index)
G.add_edges_from(
(u, v, dict(weight=w)) for (u, v), w in lines.itertuples())
return pd.Series(list(
map(
str,
sk_spectral_clustering(nx.adjacency_matrix(G), n_clusters, **kwds)
+ 1)),
index=network.buses.index)
