#
# subreddit_select = alt.selection_single(on='click',fields=['subreddit'],bind=subreddit_dropdown,name='subreddit_click')
+ base_scale = alt.Scale(scheme={"name":'category10',
+ "extent":[0,100],
+ "count":10})
+
color = alt.condition(cluster_click_select ,
- alt.Color(field='color',type='nominal',scale=alt.Scale(scheme='category10')),
+ alt.Color(field='color',type='nominal',scale=base_scale),
alt.value("lightgray"))
return chart
def assign_cluster_colors(tsne_data, clusters, n_colors, n_neighbors = 4):
+ isolate_color = 101
+
+ cluster_sizes = clusters.groupby('cluster').count()
+ singletons = set(cluster_sizes.loc[cluster_sizes.subreddit == 1].reset_index().cluster)
+
tsne_data = tsne_data.merge(clusters,on='subreddit')
centroids = tsne_data.groupby('cluster').agg({'x':np.mean,'y':np.mean})
color_assignments = np.repeat(-1,len(centroids))
for i in range(len(centroids)):
- knn = indices[i]
- knn_colors = color_assignments[knn]
- available_colors = color_ids[list(set(color_ids) - set(knn_colors))]
-
- if(len(available_colors) > 0):
- color_assignments[i] = available_colors[0]
+ if (centroids.iloc[i].name == -1) or (i in singletons):
+ color_assignments[i] = isolate_color
else:
- raise Exception("Can't color this many neighbors with this many colors")
+ knn = indices[i]
+ knn_colors = color_assignments[knn]
+ available_colors = color_ids[list(set(color_ids) - set(knn_colors))]
+ if(len(available_colors) > 0):
+ color_assignments[i] = available_colors[0]
+ else:
+ raise Exception("Can't color this many neighbors with this many colors")
centroids = centroids.reset_index()
colors = centroids.loc[:,['cluster']]
# clusters = "/gscratch/comdata/output/reddit_clustering/subreddit_author_tf_similarities_10000.feather"
tsne_data = pd.read_feather(tsne_data)
+ tsne_data = tsne_data.rename(columns={'_subreddit':'subreddit'})
clusters = pd.read_feather(clusters)
tsne_data = assign_cluster_colors(tsne_data,clusters,10,8)
- # sr_per_cluster = tsne_data.groupby('cluster').subreddit.count().reset_index()
- # sr_per_cluster = sr_per_cluster.rename(columns={'subreddit':'cluster_size'})
+ sr_per_cluster = tsne_data.groupby('cluster').subreddit.count().reset_index()
+ sr_per_cluster = sr_per_cluster.rename(columns={'subreddit':'cluster_size'})
tsne_data = tsne_data.merge(sr_per_cluster,on='cluster')