make tests pass

graphtools/graphs.py

@@ -64,24 +64,25 @@ class kNNGraph(DataGraph):
     def __init__(self, data, knn=5, decay=None,
                  bandwidth=None, distance='euclidean',
                  thresh=1e-4, n_pca=None, **kwargs):
-        self.knn = knn
-        self.decay = decay
-        self.bandwidth = bandwidth
-        self.distance = distance
-        self.thresh = thresh
 
         if decay is not None and thresh <= 0:
             raise ValueError("Cannot instantiate a kNNGraph with `decay=None` "
                              "and `thresh=0`. Use a TraditionalGraph instead.")
         if knn > data.shape[0]:
             warnings.warn("Cannot set knn ({k}) to be greater than "
-                          "data.shape[0] ({n}). Setting knn={n}".format(
+                          "n_samples ({n}). Setting knn={n}".format(
                               k=knn, n=data.shape[0]))
+            knn = data.shape[0]
         if n_pca is None and data.shape[1] > 500:
             warnings.warn("Building a kNNGraph on data of shape {} is "
                           "expensive. Consider setting n_pca.".format(
                               data.shape), UserWarning)
 
+        self.knn = knn
+        self.decay = decay
+        self.bandwidth = bandwidth
+        self.distance = distance
+        self.thresh = thresh
         super().__init__(data, n_pca=n_pca, **kwargs)
 
     def get_params(self):
@@ -232,7 +233,7 @@ def build_kernel_to_data(self, Y, knn=None, bandwidth=None):
             bandwidth = self.bandwidth
         if knn > self.data.shape[0]:
             warnings.warn("Cannot set knn ({k}) to be greater than "
-                          "data.shape[0] ({n}). Setting knn={n}".format(
+                          "n_samples ({n}). Setting knn={n}".format(
                               k=knn, n=self.data.shape[0]))
 
         Y = self._check_extension_shape(Y)
@@ -675,15 +676,20 @@ def __init__(self, data,
                  n_pca=None,
                  thresh=1e-4,
                  precomputed=None, **kwargs):
+        if decay is None and precomputed not in ['affinity', 'adjacency']:
+            # decay high enough is basically a binary kernel
+            raise ValueError("`decay` must be provided for a TraditionalGraph"
+                             ". For kNN kernel, use kNNGraph.")
         if precomputed is not None and n_pca is not None:
             # the data itself is a matrix of distances / affinities
             n_pca = None
             warnings.warn("n_pca cannot be given on a precomputed graph."
                           " Setting n_pca=None", RuntimeWarning)
-        if decay is None and precomputed not in ['affinity', 'adjacency']:
-            # decay high enough is basically a binary kernel
-            raise ValueError("`decay` must be provided for a TraditionalGraph"
-                             ". For kNN kernel, use kNNGraph.")
+        if knn > data.shape[0]:
+            warnings.warn("Cannot set knn ({k}) to be greater than or equal to"
+                          " n_samples ({n}). Setting knn={n}".format(
+                              k=knn, n=data.shape[0] - 1))
+            knn = data.shape[0] - 1
         if precomputed is not None:
             if precomputed not in ["distance", "affinity", "adjacency"]:
                 raise ValueError("Precomputed value {} not recognized. "

test/test_api.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 from load_tests import (
     nose2,
     data,

test/test_data.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 from load_tests import (
     np,
     sp,

test/test_exact.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 from load_tests import (
     graphtools,
     np,
@@ -83,6 +84,15 @@ def test_duplicate_data():
                 thresh=0)
 
 
+@warns(UserWarning)
+def test_k_too_large():
+    build_graph(data,
+                n_pca=20,
+                decay=10,
+                knn=len(data) + 1,
+                thresh=0)
+
+
 #####################################################
 # Check kernel
 #####################################################

test/test_knn.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 from load_tests import (
     graphtools,
     np,

test/test_landmark.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 from load_tests import (
     graphtools,
     np,
@@ -43,7 +44,7 @@ def test_landmark_exact_graph():
     assert(isinstance(G, graphtools.graphs.TraditionalGraph))
     assert(isinstance(G, graphtools.graphs.LandmarkGraph))
     assert(G.transitions.shape == (data.shape[0], n_landmark))
-    assert(G.clusters.shape == data.shape[0])
+    assert(G.clusters.shape == (data.shape[0],))
     assert(len(np.unique(G.clusters)) <= n_landmark)
     signal = np.random.normal(0, 1, [n_landmark, 10])
     interpolated_signal = G.interpolate(signal)
@@ -72,7 +73,7 @@ def test_landmark_mnn_graph():
                     thresh=1e-5, n_pca=None,
                     decay=10, knn=5, random_state=42,
                     sample_idx=sample_idx)
-    assert(G.clusters.shape == data.shape[0])
+    assert(G.clusters.shape == (X.shape[0],))
     assert(G.landmark_op.shape == (n_landmark, n_landmark))
     assert(isinstance(G, graphtools.graphs.MNNGraph))
     assert(isinstance(G, graphtools.graphs.LandmarkGraph))

test/test_mnn.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 from load_tests import (
     graphtools,
     np,