Merge pull request #18 from KrishnaswamyLab/dev

v0.1.9: support AnnData

.gitignore

@@ -3,6 +3,7 @@ __pycache__
 build
 dist
 *egg-info
+.coverage
 
 #syncthing
 .syncthing.*

graphtools/base.py

@@ -15,6 +15,12 @@
     # pandas not installed
     pass
 
+try:
+    import anndata
+except (ImportError, SyntaxError):
+    # anndata not installed
+    pass
+
 from .utils import (elementwise_minimum,
                     elementwise_maximum,
                     set_diagonal)
@@ -111,6 +117,13 @@ def __init__(self, data, n_pca=None, random_state=None, **kwargs):
         except NameError:
             # pandas not installed
             pass
+
+        try:
+            if isinstance(data, anndata.AnnData):
+                data = data.X
+        except NameError:
+            # anndata not installed
+            pass
         self.data = data
         self.n_pca = n_pca
         self.random_state = random_state

graphtools/version.py

@@ -1 +1 @@
-__version__ = "0.1.8.1"
+__version__ = "0.1.9"

setup.py

@@ -17,6 +17,9 @@
     'coveralls'
 ]
 
+if sys.version_info[0] == 3:
+    test_requires += ['anndata']
+
 doc_requires = [
     'sphinx',
     'sphinxcontrib-napoleon',

test/test_api.py

@@ -19,7 +19,3 @@ def test_unknown_parameter():
 @raises(ValueError)
 def test_invalid_graphtype():
     build_graph(data, graphtype='hello world')
-
-
-if __name__ == "__main__":
-    exit(nose2.run())

test/test_data.py

@@ -12,6 +12,16 @@
     squareform,
     pdist,
 )
+import warnings
+
+try:
+    import anndata
+except (ImportError, SyntaxError):
+    # python2 support is missing
+    with warnings.catch_warnings():
+        warnings.filterwarnings("always")
+        warnings.warn("Warning: failed to import anndata", ImportWarning)
+    pass
 
 #####################################################
 # Check parameters
@@ -57,6 +67,28 @@ def test_pandas_sparse_dataframe():
     assert isinstance(G.data, sp.csr_matrix)
 
 
+def test_anndata():
+    try:
+        anndata
+    except NameError:
+        # not installed
+        return
+    G = build_graph(anndata.AnnData(data))
+    assert isinstance(G, graphtools.base.BaseGraph)
+    assert isinstance(G.data, np.ndarray)
+
+
+def test_anndata_sparse():
+    try:
+        anndata
+    except NameError:
+        # not installed
+        return
+    G = build_graph(anndata.AnnData(sp.csr_matrix(data)))
+    assert isinstance(G, graphtools.base.BaseGraph)
+    assert isinstance(G.data, sp.csr_matrix)
+
+
 #####################################################
 # Check transform
 #####################################################
@@ -136,6 +168,9 @@ def test_inverse_transform_sparse_svd():
 
 def test_inverse_transform_dense_no_pca():
     G = build_graph(data, n_pca=None)
+    np.testing.assert_allclose(data[:, 5:7],
+                               G.inverse_transform(G.data_nu, columns=[5, 6]),
+                               atol=1e-12)
     assert(np.all(G.data == G.inverse_transform(G.data_nu)))
     assert_raises(ValueError, G.inverse_transform, G.data[:, 0])
     assert_raises(ValueError, G.inverse_transform, G.data[:, None, :15])
@@ -148,7 +183,3 @@ def test_inverse_transform_sparse_no_pca():
     assert_raises(ValueError, G.inverse_transform, sp.csr_matrix(G.data)[:, 0])
     assert_raises(ValueError, G.inverse_transform,
                   sp.csr_matrix(G.data)[:, :15])
-
-
-if __name__ == "__main__":
-    exit(nose2.run())

test/test_exact.py

@@ -336,7 +336,3 @@ def test_verbose():
     print()
     print("Verbose test: Exact")
     build_graph(data, decay=10, thresh=0, verbose=True)
-
-
-if __name__ == "__main__":
-    exit(nose2.run())

test/test_knn.py

@@ -171,7 +171,3 @@ def test_verbose():
     print()
     print("Verbose test: kNN")
     build_graph(data, decay=None, verbose=True)
-
-
-if __name__ == "__main__":
-    exit(nose2.run())

test/test_landmark.py

@@ -7,6 +7,7 @@
     build_graph,
     raises,
     warns,
+    generate_swiss_roll
 )
 
 
@@ -53,12 +54,12 @@ def test_landmark_knn_graph():
 
 def test_landmark_mnn_graph():
     n_landmark = 150
+    X, sample_idx = generate_swiss_roll()
     # mnn graph
-    select_idx = np.random.choice(len(data), len(data) // 5, replace=False)
-    G = build_graph(data[select_idx], n_landmark=n_landmark,
-                    thresh=1e-5, n_pca=20,
+    G = build_graph(X, n_landmark=n_landmark,
+                    thresh=1e-5, n_pca=None,
                     decay=10, knn=5, random_state=42,
-                    sample_idx=digits['target'][select_idx])
+                    sample_idx=sample_idx)
     assert(G.landmark_op.shape == (n_landmark, n_landmark))
     assert(isinstance(G, graphtools.graphs.MNNGraph))
     assert(isinstance(G, graphtools.graphs.LandmarkGraph))
@@ -76,7 +77,3 @@ def test_verbose():
     print()
     print("Verbose test: Landmark")
     build_graph(data, decay=None, n_landmark=500, verbose=True).landmark_op
-
-
-if __name__ == "__main__":
-    exit(nose2.run())

test/test_mnn.py

@@ -222,7 +222,3 @@ def test_verbose():
     build_graph(X, sample_idx=sample_idx,
                 kernel_symm='gamma', gamma=0.5,
                 n_pca=None, verbose=True)
-
-
-if __name__ == "__main__":
-    exit(nose2.run())