+import fire
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'])
+similarities = "term_similarities_10000.feather"
-n = max(df.i.max(),df.j.max())
+def fit_tsne(similarities, output, learning_rate=750, perplexity=50, n_iter=10000, early_exaggeration=20):
+ '''
+ similarities: feather file with a dataframe of similarity scores
+ learning_rate: parameter controlling how fast the model converges. Too low and you get outliers. Too high and you get a ball.
+ perplexity: number of neighbors to use. the default of 50 is often good.
-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)])
+ '''
+ df = pd.read_feather(similarities)
-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)
+ n = df.shape[0]
+ mat = np.array(df.drop('subreddit',1),dtype=np.float64)
+ mat[range(n),range(n)] = 1
+ mat[mat > 1] = 1
+ dist = 2*np.arccos(mat)/np.pi
+ tsne_model = TSNE(2,learning_rate=750,perplexity=50,n_iter=10000,metric='precomputed',early_exaggeration=20,n_jobs=-1)
+ tsne_fit_model = tsne_model.fit(dist)
-mat = mat + np.tril(mat.transpose(),k=-1)
-dist = 2*np.arccos(mat)/np.pi
+ tsne_fit_whole = tsne_fit_model.fit_transform(dist)
-tsne_model = TSNE(2,learning_rate=750,perplexity=50,n_iter=10000,metric='precomputed',early_exaggeration=20,n_jobs=-1)
+ plot_data = pd.DataFrame({'x':tsne_fit_whole[:,0],'y':tsne_fit_whole[:,1], 'subreddit':df.subreddit})
-tsne_fit_model = tsne_model.fit(dist)
+ plot_data.to_feather(output)
-tsne_fit_whole = tsne_fit_model.fit_transform(dist)
-
-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")
+if __name__ == "__main__":
+ fire.Fire(fit_tsne)
projects / cdsc_reddit.git / commitdiff