Merge pull request #58 from ayan-b/full-cov

Add 100% test coverage

data/flat_triangular_mesh_no_target.txt

@@ -0,0 +1,121 @@
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gdist.pyx

@@ -170,10 +170,10 @@ def compute_gdist(numpy.ndarray[numpy.float64_t, ndim=2] vertices,
     cdef vector[unsigned] faces
 
     if source_indices is None:
-        source_indices = numpy.arange(0, dtype=numpy.int32)  # default to 0
+        source_indices = numpy.arange(1, dtype=numpy.int32)  # default to 0
     if target_indices is None:
         propagate_on_max_distance = True
-        target_indices = numpy.arange(vertices.size(), dtype=numpy.int32)
+        target_indices = numpy.arange(vertices.shape[0], dtype=numpy.int32)
 
     for k in vertices.flatten():
         points.push_back(k)

tests/test_gdist.py

@@ -71,6 +71,21 @@ def test_flat_triangular_mesh_1_indexed(self):
         )
         np.testing.assert_array_almost_equal(distance, [0.2])
 
+    def test_flat_triangular_mesh_no_target(self):
+        data = np.loadtxt("data/flat_triangular_mesh.txt", skiprows=1)
+        vertices = data[0:121].astype(np.float64)
+        triangles = data[121:].astype(np.int32)
+        source = None
+        target = None
+        distance = gdist.compute_gdist(
+            vertices,
+            triangles,
+            source,
+            target,
+        )
+        expected = np.loadtxt("data/flat_triangular_mesh_no_target.txt")
+        np.testing.assert_array_almost_equal(distance, expected)
+
     def test_hedgehog_mesh(self):
         data = np.loadtxt("data/hedgehog_mesh.txt", skiprows=1)
         vertices = data[0:300].astype(np.float64)