Revert "COSMIT skip some repeated computations in k-means"

This reverts commit e3583da,
except for a typo fix.

Fixes scikit-learn#3039.

Author: larsmans

sklearn/cluster/k_means_.py

@@ -840,20 +840,22 @@ def _mini_batch_step(X, x_squared_norms, centers, counts,
         # Reassign clusters that have very low counts
         to_reassign = np.logical_or(
             (counts <= 1), counts <= reassignment_ratio * counts.max())
-        n_reassigns = min(to_reassign.sum(), X.shape[0])
-        if n_reassigns:
+        number_of_reassignments = to_reassign.sum()
+        if number_of_reassignments:
             # Pick new clusters amongst observations with probability
             # proportional to their closeness to their center.
             # Flip the ordering of the distances.
             distances -= distances.max()
             distances *= -1
-            rand_vals = random_state.rand(n_reassigns)
+            rand_vals = random_state.rand(number_of_reassignments)
             rand_vals *= distances.sum()
             new_centers = np.searchsorted(distances.cumsum(),
                                           rand_vals)
             if verbose:
-                print("[MiniBatchKMeans] Reassigning %i cluster centers."
-                      % n_reassigns)
+                n_reassigns = to_reassign.sum()
+                if n_reassigns:
+                    print("[MiniBatchKMeans] Reassigning %i cluster centers."
+                          % n_reassigns)
 
             if sp.issparse(X) and not sp.issparse(centers):
                 assign_rows_csr(X, new_centers, np.where(to_reassign)[0],