inital commit of similarity functions

src/pg/sql/80_similarity_rank.sql

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+CREATE OR REPLACE FUNCTION cdb_SimilarityRank(cartodb_id numeric, query string)
+returns TABLE (cartodb_id NUMERIC, similarity NUMERIC)
+as $$
+  from crankshaft.similarity import similarity_rank
+  return similarity_rank(cartodb_id, query)
+$$ LANGUAGE plpythonu
+
+CREATE OR REPLACE FUNCTION cdb_MostSimilar(cartodb_id numeric, query string ,matches numeric)
+returns TABLE (cartodb_id NUMERIC, similarity NUMERIC)
+as $$
+  from crankshaft.similarity import most_similar
+  return most_similar(matches, query)
+$$ LANGUAGE plpythonu

src/py/crankshaft/crankshaft/similarity/__init__.py

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+from similarity import * 

src/py/crankshaft/crankshaft/similarity/similarity.py

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+from sklearn.neighbors import BallTree
+import numpy as np
+import plpy
+
+def similarity_rank(target_cartodb_id, query):
+    data = plpy.execute(query)    
+    features, target = extract_features_target(data,target_cartodb_id)
+    tree = train(features)
+    dist, ind  = tree.query(target, k=len(data))
+    cartodb_ids  = [ dist[ind]['cartodb_id'] for index in ind ]
+    return cartodb_ids, dist
+
+def most_similar(matches,query):
+    data = plpy.execute(query)    
+    features, _ = extract_features_target(data)
+    tree = train(features)
+    results = []
+    for i in features:
+        target = features
+        dist,ind = tree.query(target, k=matches)
+        cartodb_ids  = [ dist[ind]['cartodb_id'] for index in ind ]
+        results.append(cartodb_ids)
+    return cartodb_ids, results
+    
+def train(features):
+    normed_features  = normalize_features(featuers)
+    normed_target    = normalize_features([target])
+    tree = BallTree(normed_features, leaf_size=2)
+    return tree
+    
+def normalize_features(features):
+    maxes = features.max(axis=0)
+    mins  = features.min(axis=0)
+    return (features - mins)/(maxes-mins)
+    
+def extract_features_target:(data, target_cartodb_id=None):
+    target = None
+    for row in data:
+        data.keys().difference(['the_geom', 'the_geom_webmercator','cartodb_id'])
+        if data['cartodb_id'] == target_cartodb_id
+            target = data.values()
+    return np.array(data), np.array(target)
+