X-Git-Url: https://code.communitydata.science/cdsc_reddit.git/blobdiff_plain/db53c0138ae36d4b8f75b101315651a259a89dd8..4447c60265c5c5de3281ca135461d91ab5339f03:/fit_tsne.py

diff --git a/fit_tsne.py b/fit_tsne.py
new file mode 100644
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+++ b/fit_tsne.py
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+import pyarrow
+import pandas as pd
+from numpy import random
+import numpy as np
+from sklearn.manifold import TSNE
+
+df = pd.read_feather("reddit_term_similarity_3000.feather")
+df = df.sort_values(['i','j'])
+
+n = max(df.i.max(),df.j.max())
+
+def zero_pad(grp):
+    p = grp.shape[0]
+    grp = grp.sort_values('j')
+    return np.concatenate([np.zeros(n-p),np.ones(1),np.array(grp.value)])
+
+col_names = df.sort_values('j').loc[:,['subreddit_j']].drop_duplicates()
+first_name = list(set(df.subreddit_i) - set(df.subreddit_j))[0]
+col_names = [first_name] + list(col_names.subreddit_j)
+mat = df.groupby('i').apply(zero_pad)
+mat.loc[n] = np.concatenate([np.zeros(n),np.ones(1)])
+mat = np.stack(mat)
+
+mat = mat + np.tril(mat.transpose(),k=-1)
+dist = 2*np.arccos(mat)/np.pi
+
+tsne_model = TSNE(2,learning_rate=200,perplexity=40,n_iter=5000,metric='precomputed')
+
+tsne_fit_model = tsne_model.fit(dist)
+
+tsne_fit_whole = tsne_fit_model.fit_transform(mat)
+
+plot_data = pd.DataFrame({'x':tsne_fit_whole[:,0],'y':tsne_fit_whole[:,1], 'subreddit':col_names})
+
+plot_data.to_feather("tsne_subreddit_fit.feather")