Fix sanity filter

convoys/regression.py

@@ -183,14 +183,14 @@ def fit(self, X, B, T, W=None):
 
         if W is None:
             W = [1] * len(X)
-        XBTW = [(x, b, t, w) for x, b, t, w in zip(X, B, T, W)
-                if t > 0 and 0 <= float(b) <= 1 and w >= 0]
-        if len(XBTW) < len(X):
-            n_removed = len(X) - len(XBTW)
+        X, B, T, W = (Z if type(Z) == numpy.ndarray else numpy.array(Z)
+                      for Z in (X, B, T, W))
+        keep_indexes = (T > 0) & (B >= 0) & (B <= 1) & (W >= 0)
+        if sum(keep_indexes) < X.shape[0]:
+            n_removed = X.shape[0] - sum(keep_indexes)
             warnings.warn('Warning! Removed %d/%d entries from inputs where '
                           'T <= 0 or B not 0/1 or W < 0' % (n_removed, len(X)))
-        X, B, T, W = (numpy.array([z[i] for z in XBTW], dtype=numpy.float32)
-                      for i in range(4))
+            X, B, T, W = (Z[keep_indexes] for Z in (X, B, T, W))
         n_features = X.shape[1]
 
         # scipy.optimize and emcee forces the the parameters to be a vector: