From 9279c7f0276504bb6fe3ec788d96e97b0722909e Mon Sep 17 00:00:00 2001
From: Jonas Hoersch <jonas@chaoflow.net>
Date: Wed, 20 Feb 2019 19:06:48 +0100
Subject: [PATCH] solve_network: Remove hard-coded solver fallback in
 `busmap_for_n_clusters`

Necessary for when `clustering_for_n_clusters` is used from the simplify_network
rule.

Fixes #12
---
 scripts/cluster_network.py  | 15 ++++++---------
 scripts/simplify_network.py |  7 +++----
 2 files changed, 9 insertions(+), 13 deletions(-)

diff --git a/scripts/cluster_network.py b/scripts/cluster_network.py
index e04cbe6d..7fb339fc 100644
--- a/scripts/cluster_network.py
+++ b/scripts/cluster_network.py
@@ -93,7 +93,7 @@ def distribute_clusters(n, n_clusters, solver_name=None):
 
     return pd.Series(m.n.get_values(), index=L.index).astype(int)
 
-def busmap_for_n_clusters(n, n_clusters, algorithm="kmeans", **algorithm_kwds):
+def busmap_for_n_clusters(n, n_clusters, solver_name, algorithm="kmeans", **algorithm_kwds):
     if algorithm == "kmeans":
         algorithm_kwds.setdefault('n_init', 1000)
         algorithm_kwds.setdefault('max_iter', 30000)
@@ -101,11 +101,6 @@ def busmap_for_n_clusters(n, n_clusters, algorithm="kmeans", **algorithm_kwds):
 
     n.determine_network_topology()
 
-    if 'snakemake' in globals():
-        solver_name = snakemake.config['solving']['solver']['name']
-    else:
-        solver_name = "gurobi"
-
     n_clusters = distribute_clusters(n, n_clusters, solver_name=solver_name)
 
     def reduce_network(n, buses):
@@ -140,7 +135,8 @@ def plot_busmap_for_n_clusters(n, n_clusters=50):
     del cs, cr
 
 def clustering_for_n_clusters(n, n_clusters, aggregate_carriers=None,
-                              line_length_factor=1.25, potential_mode='simple', algorithm="kmeans"):
+                              line_length_factor=1.25, potential_mode='simple',
+                              solver_name="cbc", algorithm="kmeans"):
 
     if potential_mode == 'simple':
         p_nom_max_strategy = np.sum
@@ -151,7 +147,7 @@ def clustering_for_n_clusters(n, n_clusters, aggregate_carriers=None,
                              "but is '{}'".format(potential_mode))
 
     clustering = get_clustering_from_busmap(
-        n, busmap_for_n_clusters(n, n_clusters, algorithm),
+        n, busmap_for_n_clusters(n, n_clusters, solver_name, algorithm),
         bus_strategies=dict(country=_make_consense("Bus", "country")),
         aggregate_generators_weighted=True,
         aggregate_generators_carriers=aggregate_carriers,
@@ -233,7 +229,8 @@ if __name__ == "__main__":
                                              for tech in renewable_carriers]))
         clustering = clustering_for_n_clusters(n, n_clusters, aggregate_carriers,
                                                line_length_factor=line_length_factor,
-                                               potential_mode=potential_mode)
+                                               potential_mode=potential_mode,
+                                               solver_name=snakemake.config['solving']['solver']['name'])
 
     clustering.network.export_to_netcdf(snakemake.output.network)
     with pd.HDFStore(snakemake.output.clustermaps, mode='w') as store:
diff --git a/scripts/simplify_network.py b/scripts/simplify_network.py
index ba8f9bac..e419989a 100644
--- a/scripts/simplify_network.py
+++ b/scripts/simplify_network.py
@@ -21,9 +21,7 @@ from six.moves import reduce
 
 import pypsa
 from pypsa.io import import_components_from_dataframe, import_series_from_dataframe
-from pypsa.networkclustering import (busmap_by_stubs, busmap_by_kmeans,
-                                     _make_consense, get_clustering_from_busmap,
-                                     aggregategenerators, aggregateoneport)
+from pypsa.networkclustering import busmap_by_stubs, aggregategenerators, aggregateoneport
 
 from cluster_network import clustering_for_n_clusters, cluster_regions
 from add_electricity import load_costs
@@ -254,7 +252,8 @@ def cluster(n, n_clusters):
     potential_mode = (consense(pd.Series([snakemake.config['renewable'][tech]['potential']
                                             for tech in renewable_carriers]))
                         if len(renewable_carriers) > 0 else 'conservative')
-    clustering = clustering_for_n_clusters(n, n_clusters, potential_mode=potential_mode)
+    clustering = clustering_for_n_clusters(n, n_clusters, potential_mode=potential_mode,
+                                           solver_name=snakemake.config['solving']['solver']['name'])
 
     return clustering.network, clustering.busmap