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suggestions by coroa and fneum

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This commit is contained in:
martacki 2022-03-17 17:38:30 +01:00
parent 3e07fdfd54
commit 4c1c5e3a4e
1 changed files with 21 additions and 21 deletions
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42
scripts/cluster_network.py
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@ -189,28 +189,20 @@ def get_feature_for_hac(n, buses_i=None, feature=None):
if feature.split('-')[1] == 'cap':
feature_data = pd.DataFrame(index=buses_i, columns=carriers)
for carrier in carriers:
try:
# without simpl wildcard (bus names are "X X"):
feature_data[carrier] = (n.generators_t.p_max_pu.filter(like=carrier).mean()
.rename(index=lambda x: x.split(' ')[0]))
except:
# with simpl wildcard (bus names are "X X X"):
feature_data[carrier] = (n.generators_t.p_max_pu.filter(like=carrier).mean()
.rename(index=lambda x: x.split(' ')[0] + ' ' + x.split(' ')[1]))
gen_i = n.generators.query("carrier == @carrier").index
attach = n.generators_t.p_max_pu[gen_i].mean().rename(index = n.generators.loc[gen_i].bus)
feature_data[carrier] = attach
if feature.split('-')[1] == 'time':
feature_data = pd.DataFrame(columns=buses_i)
for carrier in carriers:
try:
# without simpl wildcard (bus names are "X X"):
feature_data = feature_data.append(n.generators_t.p_max_pu.filter(like=carrier)
.rename(columns=lambda x: x.split(' ')[0]))[buses_i]
except:
# with simpl wildcard (bus names are "X X X"):
feature_data = feature_data.append(n.generators_t.p_max_pu.filter(like=carrier)
.rename(columns=lambda x: x.split(' ')[0] + ' ' + x.split(' ')[1]))[buses_i]
gen_i = n.generators.query("carrier == @carrier").index
attach = n.generators_t.p_max_pu[gen_i].rename(columns = n.generators.loc[gen_i].bus)
feature_data = pd.concat([feature_data, attach], axis=0)[buses_i]
feature_data = feature_data.T
feature_data.columns = feature_data.columns.astype(str) # timestamp raises error in sklearn>=v1.2
# timestamp raises error in sklearn >= v1.2:
feature_data.columns = feature_data.columns.astype(str)
feature_data = feature_data.fillna(0)
@ -283,16 +275,24 @@ def busmap_for_n_clusters(n, n_clusters, solver_name, focus_weights=None, algori
m.links = m.links.query("bus0 in @m.buses.index and bus1 in @m.buses.index")
_, labels = csgraph.connected_components(m.adjacency_matrix(), directed=False)
component = pd.Series(labels, index=m.buses.index)
component_sizes = component.value_counts()
if len(component_sizes)>1:
disconnected_bus = component[component==component_sizes[component_sizes==component_sizes.min()].index[0]].index
neighbor_bus = n.lines.query("bus0 in @disconnected_bus or bus1 in @disconnected_bus").iloc[0][['bus0','bus1']]
disconnected_bus = component[component==component_sizes.index[-1]].index[0]
neighbor_bus = (
n.lines.query("bus0 == @disconnected_bus or bus1 == @disconnected_bus")
.iloc[0][['bus0', 'bus1']]
)
new_country = list(set(n.buses.loc[neighbor_bus].country)-set([country]))[0]
logger.info(f"overwriting country `{country}` of bus `{disconnected_bus}` to new country `{new_country}`, "
"because it is disconnected from its inital inter-country transmission grid.")
logger.info(
f"overwriting country `{country}` of bus `{disconnected_bus}` "
f"to new country `{new_country}`, because it is disconnected "
"from its inital inter-country transmission grid."
)
n.buses.at[disconnected_bus, "country"] = new_country
return n