Merge branch 'dev_landmark' into dev

graphtools/graphs.py

@@ -445,6 +445,20 @@ def transitions(self):
             self.build_landmark_op()
             return self._transitions
 
+    def _landmarks_to_data(self):
+        landmarks = np.unique(self._clusters)
+        if sparse.issparse(self.kernel):
+            pmn = sparse.vstack(
+                [sparse.csr_matrix(self.kernel[self._clusters == i, :].sum(
+                    axis=0)) for i in landmarks])
+        else:
+            pmn = np.array([np.sum(self.kernel[self._clusters == i, :], axis=0)
+                            for i in landmarks])
+        return pmn
+
+    def _data_transitions(self):
+        return normalize(self._landmarks_to_data(), 'l1', axis=1)
+
     def build_landmark_op(self):
         """Build the landmark operator
 
@@ -469,17 +483,11 @@ def build_landmark_op(self):
         self._clusters = kmeans.fit_predict(
             self.diff_op.dot(VT.T))
         # some clusters are not assigned
-        landmarks = np.unique(self._clusters)
         tasklogger.log_complete("KMeans")
 
         # transition matrices
-        if is_sparse:
-            pmn = sparse.vstack(
-                [sparse.csr_matrix(self.kernel[self._clusters == i, :].sum(
-                    axis=0)) for i in landmarks])
-        else:
-            pmn = np.array([np.sum(self.kernel[self._clusters == i, :], axis=0)
-                            for i in landmarks])
+        pmn = self._landmarks_to_data()
+
         # row normalize
         pnm = pmn.transpose()
         pmn = normalize(pmn, norm='l1', axis=1)
@@ -594,7 +602,8 @@ class TraditionalGraph(DataGraph):
         All affinities below `thresh` will be set to zero in order to save
         on time and memory constraints.
 
-    precomputed : {'distance', 'affinity', 'adjacency', `None`}, optional (default: `None`)
+    precomputed : {'distance', 'affinity', 'adjacency', `None`},
+        optional (default: `None`)
         If the graph is precomputed, this variable denotes which graph
         matrix is provided as `data`.
         Only one of `precomputed` and `n_pca` can be set.

test/load_tests/__init__.py

@@ -10,7 +10,22 @@
 
 import nose2
 from nose.tools import raises, assert_raises, make_decorator
-warnings.filterwarnings("error")
+
+
+def reset_warnings():
+    warnings.resetwarnings()
+    warnings.simplefilter("error")
+    ignore_numpy_warning()
+
+
+def ignore_numpy_warning():
+    warnings.filterwarnings(
+        "ignore", category=PendingDeprecationWarning,
+        message="the matrix subclass is not the recommended way to represent "
+        "matrices or deal with linear algebra ")
+
+
+reset_warnings()
 
 global digits
 global data
@@ -65,9 +80,11 @@ def decorate(func):
 
         def newfunc(*arg, **kw):
             with warnings.catch_warnings(record=True) as w:
-                warnings.filterwarnings("always")
+                warnings.resetwarnings()
+                warnings.simplefilter("always")
+                ignore_numpy_warning()
                 func(*arg, **kw)
-                warnings.filterwarnings("error")
+                reset_warnings()
             try:
                 for warn in w:
                     raise warn.category