diff --git a/python/pyspark/ml/linalg/__init__.py b/python/pyspark/ml/linalg/__init__.py
index 05c0ac862fb7f43e6529f2be6ae3fefc75c7f784..a5df727fdb4181ad5fef43a589f3a7a9c1e28792 100644
--- a/python/pyspark/ml/linalg/__init__.py
+++ b/python/pyspark/ml/linalg/__init__.py
@@ -713,7 +713,7 @@ class SparseVector(Vector):
"Indices must be of type integer, got type %s" % type(index))
if index >= self.size or index < -self.size:
- raise ValueError("Index %d out of bounds." % index)
+ raise IndexError("Index %d out of bounds." % index)
if index < 0:
index += self.size
@@ -960,10 +960,10 @@ class DenseMatrix(Matrix):
def __getitem__(self, indices):
i, j = indices
if i < 0 or i >= self.numRows:
- raise ValueError("Row index %d is out of range [0, %d)"
+ raise IndexError("Row index %d is out of range [0, %d)"
% (i, self.numRows))
if j >= self.numCols or j < 0:
- raise ValueError("Column index %d is out of range [0, %d)"
+ raise IndexError("Column index %d is out of range [0, %d)"
% (j, self.numCols))
if self.isTransposed:
@@ -1090,10 +1090,10 @@ class SparseMatrix(Matrix):
def __getitem__(self, indices):
i, j = indices
if i < 0 or i >= self.numRows:
- raise ValueError("Row index %d is out of range [0, %d)"
+ raise IndexError("Row index %d is out of range [0, %d)"
% (i, self.numRows))
if j < 0 or j >= self.numCols:
- raise ValueError("Column index %d is out of range [0, %d)"
+ raise IndexError("Column index %d is out of range [0, %d)"
% (j, self.numCols))
# If a CSR matrix is given, then the row index should be searched
diff --git a/python/pyspark/ml/tests.py b/python/pyspark/ml/tests.py
index 6886ed321ee82671947820011e77f62c8a57a523..e2335498508882b81c2382e8f83efc62fd456c6f 100755
--- a/python/pyspark/ml/tests.py
+++ b/python/pyspark/ml/tests.py
@@ -1316,7 +1316,7 @@ class VectorTests(MLlibTestCase):
self.assertEqual(sv[-3], 0.)
self.assertEqual(sv[-5], 0.)
for ind in [5, -6]:
- self.assertRaises(ValueError, sv.__getitem__, ind)
+ self.assertRaises(IndexError, sv.__getitem__, ind)
for ind in [7.8, '1']:
self.assertRaises(TypeError, sv.__getitem__, ind)
@@ -1324,11 +1324,15 @@ class VectorTests(MLlibTestCase):
self.assertEqual(zeros[0], 0.0)
self.assertEqual(zeros[3], 0.0)
for ind in [4, -5]:
- self.assertRaises(ValueError, zeros.__getitem__, ind)
+ self.assertRaises(IndexError, zeros.__getitem__, ind)
empty = SparseVector(0, {})
for ind in [-1, 0, 1]:
- self.assertRaises(ValueError, empty.__getitem__, ind)
+ self.assertRaises(IndexError, empty.__getitem__, ind)
+
+ def test_sparse_vector_iteration(self):
+ self.assertListEqual(list(SparseVector(3, [], [])), [0.0, 0.0, 0.0])
+ self.assertListEqual(list(SparseVector(5, [0, 3], [1.0, 2.0])), [1.0, 0.0, 0.0, 2.0, 0.0])
def test_matrix_indexing(self):
mat = DenseMatrix(3, 2, [0, 1, 4, 6, 8, 10])
@@ -1337,6 +1341,9 @@ class VectorTests(MLlibTestCase):
for j in range(2):
self.assertEqual(mat[i, j], expected[i][j])
+ for i, j in [(-1, 0), (4, 1), (3, 4)]:
+ self.assertRaises(IndexError, mat.__getitem__, (i, j))
+
def test_repr_dense_matrix(self):
mat = DenseMatrix(3, 2, [0, 1, 4, 6, 8, 10])
self.assertTrue(
@@ -1408,6 +1415,9 @@ class VectorTests(MLlibTestCase):
self.assertEqual(expected[i][j], sm1[i, j])
self.assertTrue(array_equal(sm1.toArray(), expected))
+ for i, j in [(-1, 1), (4, 3), (3, 5)]:
+ self.assertRaises(IndexError, sm1.__getitem__, (i, j))
+
# Test conversion to dense and sparse.
smnew = sm1.toDense().toSparse()
self.assertEqual(sm1.numRows, smnew.numRows)
diff --git a/python/pyspark/mllib/linalg/__init__.py b/python/pyspark/mllib/linalg/__init__.py
index 9672dbde823f2fc360283a8cac30f43997419410..d37e715c8d8ec5d5adf6639ba350eda2d64bbf0f 100644
--- a/python/pyspark/mllib/linalg/__init__.py
+++ b/python/pyspark/mllib/linalg/__init__.py
@@ -802,7 +802,7 @@ class SparseVector(Vector):
"Indices must be of type integer, got type %s" % type(index))
if index >= self.size or index < -self.size:
- raise ValueError("Index %d out of bounds." % index)
+ raise IndexError("Index %d out of bounds." % index)
if index < 0:
index += self.size
@@ -1115,10 +1115,10 @@ class DenseMatrix(Matrix):
def __getitem__(self, indices):
i, j = indices
if i < 0 or i >= self.numRows:
- raise ValueError("Row index %d is out of range [0, %d)"
+ raise IndexError("Row index %d is out of range [0, %d)"
% (i, self.numRows))
if j >= self.numCols or j < 0:
- raise ValueError("Column index %d is out of range [0, %d)"
+ raise IndexError("Column index %d is out of range [0, %d)"
% (j, self.numCols))
if self.isTransposed:
@@ -1245,10 +1245,10 @@ class SparseMatrix(Matrix):
def __getitem__(self, indices):
i, j = indices
if i < 0 or i >= self.numRows:
- raise ValueError("Row index %d is out of range [0, %d)"
+ raise IndexError("Row index %d is out of range [0, %d)"
% (i, self.numRows))
if j < 0 or j >= self.numCols:
- raise ValueError("Column index %d is out of range [0, %d)"
+ raise IndexError("Column index %d is out of range [0, %d)"
% (j, self.numCols))
# If a CSR matrix is given, then the row index should be searched
diff --git a/python/pyspark/mllib/tests.py b/python/pyspark/mllib/tests.py
index 3f3dfd186c10d6a51c3f57946b54a580baa8c889..c519883cdd73bf7db45f285405a4cc56bdf4e51d 100644
--- a/python/pyspark/mllib/tests.py
+++ b/python/pyspark/mllib/tests.py
@@ -260,7 +260,7 @@ class VectorTests(MLlibTestCase):
self.assertEqual(sv[-3], 0.)
self.assertEqual(sv[-5], 0.)
for ind in [5, -6]:
- self.assertRaises(ValueError, sv.__getitem__, ind)
+ self.assertRaises(IndexError, sv.__getitem__, ind)
for ind in [7.8, '1']:
self.assertRaises(TypeError, sv.__getitem__, ind)
@@ -268,11 +268,15 @@ class VectorTests(MLlibTestCase):
self.assertEqual(zeros[0], 0.0)
self.assertEqual(zeros[3], 0.0)
for ind in [4, -5]:
- self.assertRaises(ValueError, zeros.__getitem__, ind)
+ self.assertRaises(IndexError, zeros.__getitem__, ind)
empty = SparseVector(0, {})
for ind in [-1, 0, 1]:
- self.assertRaises(ValueError, empty.__getitem__, ind)
+ self.assertRaises(IndexError, empty.__getitem__, ind)
+
+ def test_sparse_vector_iteration(self):
+ self.assertListEqual(list(SparseVector(3, [], [])), [0.0, 0.0, 0.0])
+ self.assertListEqual(list(SparseVector(5, [0, 3], [1.0, 2.0])), [1.0, 0.0, 0.0, 2.0, 0.0])
def test_matrix_indexing(self):
mat = DenseMatrix(3, 2, [0, 1, 4, 6, 8, 10])
@@ -281,6 +285,9 @@ class VectorTests(MLlibTestCase):
for j in range(2):
self.assertEqual(mat[i, j], expected[i][j])
+ for i, j in [(-1, 0), (4, 1), (3, 4)]:
+ self.assertRaises(IndexError, mat.__getitem__, (i, j))
+
def test_repr_dense_matrix(self):
mat = DenseMatrix(3, 2, [0, 1, 4, 6, 8, 10])
self.assertTrue(
@@ -352,6 +359,9 @@ class VectorTests(MLlibTestCase):
self.assertEqual(expected[i][j], sm1[i, j])
self.assertTrue(array_equal(sm1.toArray(), expected))
+ for i, j in [(-1, 1), (4, 3), (3, 5)]:
+ self.assertRaises(IndexError, sm1.__getitem__, (i, j))
+
# Test conversion to dense and sparse.
smnew = sm1.toDense().toSparse()
self.assertEqual(sm1.numRows, smnew.numRows)