from sklearn.neighbors import NearestNeighbors
import pandas as pd
from numpy import random
+import fire
import numpy as np
def base_plot(plot_data):
tsne_data = tsne_data.merge(colors,on='cluster')
return(tsne_data)
-term_data = pd.read_feather("tsne_subreddit_fit.feather")
-clusters = pd.read_feather("term_3000_clusters.feather")
+def build_visualization(tsne_data, clusters, output):
-tsne_data = assign_cluster_colors(term_data,clusters,10,8)
+ tsne_data = pd.read_feather(tsne_data)
+ clusters = pd.read_feather(clusters)
-term_zoom_plot = zoom_plot(tsne_data)
+ tsne_data = assign_cluster_colors(tsne_data,clusters,10,8)
-term_zoom_plot.save("subreddit_terms_tsne_3000.html")
+ term_zoom_plot = zoom_plot(tsne_data)
-term_viewport_plot = viewport_plot(tsne_data)
+ term_zoom_plot.save(output)
-term_viewport_plot.save("subreddit_terms_tsne_3000_viewport.html")
+ term_viewport_plot = viewport_plot(tsne_data)
-commenter_data = pd.read_feather("tsne_author_fit.feather")
-clusters = pd.read_feather('author_3000_clusters.feather')
-commenter_data = assign_cluster_colors(commenter_data,clusters,10,8)
-commenter_zoom_plot = zoom_plot(commenter_data)
-commenter_viewport_plot = viewport_plot(commenter_data)
-commenter_zoom_plot.save("subreddit_commenters_tsne_3000.html")
-commenter_viewport_plot.save("subreddit_commenters_tsne_3000_viewport.html")
+ term_viewport_plot.save(output.replace(".html","_viewport.html"))
+
+if __name__ == "__main__":
+ fire.Fire(build_visualization)
+
+# commenter_data = pd.read_feather("tsne_author_fit.feather")
+# clusters = pd.read_feather('author_3000_clusters.feather')
+# commenter_data = assign_cluster_colors(commenter_data,clusters,10,8)
+# commenter_zoom_plot = zoom_plot(commenter_data)
+# commenter_viewport_plot = viewport_plot(commenter_data)
+# commenter_zoom_plot.save("subreddit_commenters_tsne_3000.html")
+# commenter_viewport_plot.save("subreddit_commenters_tsne_3000_viewport.html")
# chart = chart.properties(width=10000,height=10000)
# chart.save("test_tsne_whole.svg")