Merge branch 'main' of https://github.com/gcrsef-gang/the-rebalancing…

…-act into main

.gitignore

@@ -19,3 +19,6 @@ examples/*.png
 NC_ensemble_10000
 
 debug.py
+
+maryland
+new_hampshire

rba/district_quantification.py

@@ -77,7 +77,9 @@ def quantify_districts(graph_file, district_file, difference_file, verbose=False
     with open(graph_file, "r") as f:
         graph_json = json.load(f)
     graph = nx.readwrite.json_graph.adjacency_graph(graph_json)
-    districts = load_districts(graph, district_file)
+    # districts = load_districts(graph, district_file)
+    with open(district_file, "r") as f:
+        districts = json.load(f)
 
     with open(difference_file, "r") as f:
         supercommunity_output = json.load(f)  # Contains strings as keys.

rba/ensemble.py

@@ -444,7 +444,6 @@ def ensemble_analysis(graph_file, difference_file, vra_config_file, num_steps, n
 
     if optimize_vis:
         output_dir = vis_dir
-
     # Save a histogram of statewide scores.
     plt.hist(scores_df["state_gerry_score"], bins=30)
     plt.axvline(scores_df["state_gerry_score"].mean(), color='k', linestyle='dashed', linewidth=1)
@@ -466,7 +465,7 @@ def get_z_score(precinct, metric):
             districts_assignment[node] = district
     districts_partition = Partition(graph, assignment=districts_assignment)
 
-    _, ax = plt.subplots(figsize=(60, 30))
+    _, ax = plt.subplots(figsize=(12.8, 9.6))
     visualize_gradient_geopandas(
         sorted_node_names,
         get_value=partial(get_z_score, metric="score"),