[MRG] Fix RCA_Supervised sklearn compat test (#198)

* FIX fix RCA_Supervised sklearn compat test

* Address #198 (review)

* Refactor comment

Author: wdevazelhes

metric_learn/rca.py

@@ -26,7 +26,9 @@
 def _chunk_mean_centering(data, chunks):
   num_chunks = chunks.max() + 1
   chunk_mask = chunks != -1
-  chunk_data = data[chunk_mask]
+  # We need to ensure the data is float so that we can substract the
+  # mean on it
+  chunk_data = data[chunk_mask].astype(float, copy=False)
   chunk_labels = chunks[chunk_mask]
   for c in xrange(num_chunks):
     mask = chunk_labels == c
@@ -98,7 +100,7 @@ def fit(self, X, chunks):
         When ``chunks[i] == -1``, point i doesn't belong to any chunklet.
         When ``chunks[i] == j``, point i belongs to chunklet j.
     """
-    X = self._prepare_inputs(X, ensure_min_samples=2)
+    X, chunks = self._prepare_inputs(X, chunks, ensure_min_samples=2)
 
     # PCA projection to remove noise and redundant information.
     if self.pca_comps is not None:
@@ -109,7 +111,6 @@ def fit(self, X, chunks):
       X_t = X - X.mean(axis=0)
       M_pca = None
 
-    chunks = np.asanyarray(chunks, dtype=int)
     chunk_mask, chunked_data = _chunk_mean_centering(X_t, chunks)
 
     inner_cov = np.atleast_2d(np.cov(chunked_data, rowvar=0, bias=1))

test/test_sklearn_compat.py

@@ -89,9 +89,15 @@ def stable_init(self, sparsity_param=0.01, num_labeled='deprecated',
     dSDML.__init__ = stable_init
     check_estimator(dSDML)
 
-  # This fails because the default num_chunks isn't data-dependent.
-  # def test_rca(self):
-  #   check_estimator(RCA_Supervised)
+  def test_rca(self):
+    def stable_init(self, num_dims=None, pca_comps=None,
+                    chunk_size=2, preprocessor=None):
+      # this init makes RCA stable for scikit-learn examples.
+      RCA_Supervised.__init__(self, num_chunks=2, num_dims=num_dims,
+                              pca_comps=pca_comps, chunk_size=chunk_size,
+                              preprocessor=preprocessor)
+    dRCA.__init__ = stable_init
+    check_estimator(dRCA)
 
 
 RNG = check_random_state(0)