More tests for sparse indexing.

theano/sparse/tests/test_basic.py

@@ -930,7 +930,11 @@ def test_size():
         check()
 
 
-def test_GetItem2D():
+class Test_getitem(unittest.TestCase):
+    def setUp(self):
+        self.rng = numpy.random.RandomState(utt.fetch_seed())
+
+    def test_GetItem2D(self):
         sparse_formats = ('csc', 'csr')
         for format in sparse_formats:
             x = theano.sparse.matrix(format, name='x')
@@ -945,7 +949,7 @@ def test_GetItem2D():
             p = 10
             q = 15
 
-        vx = as_sparse_format(numpy.random.binomial(1, 0.5, (100, 100)),
+            vx = as_sparse_format(self.rng.binomial(1, 0.5, (100, 100)),
                                   format).astype(theano.config.floatX)
             #mode_no_debug = theano.compile.mode.get_default_mode()
             #if isinstance(mode_no_debug, theano.compile.DebugMode):
@@ -1016,8 +1020,46 @@ def test_GetItem2D():
             assert r9.shape == t9.shape
             assert numpy.all(r9.toarray() == t9.toarray())
 
-
-def test_GetItemScalar():
+            #-----------------------------------------------------------
+            # Test mixing None and variables
+            f10 = theano.function([x, a, b], x[:a, :b])
+            r10 = f10(vx, p, q)
+            t10 = vx[:p, :q]
+            assert r10.shape == t10.shape
+            assert numpy.all(r10.toarray() == t10.toarray())
+
+            f11 = theano.function([x, a], x[:,a:])
+            r11 = f11(vx, p)
+            t11 = vx[:, p:]
+            assert r11.shape == t11.shape
+            assert numpy.all(r11.toarray() == t11.toarray())
+
+            #------------------------------------------------------------
+            # Invalid things
+            # The syntax is a bit awkward because assertRaises forbids
+            # the [] shortcut for getitem.
+            # x[a:b] is not accepted because we don't have sparse vectors
+            self.assertRaises(NotImplementedError,
+                    x.__getitem__, (slice(a, b), c))
+
+            # x[a:b:step, c:d] is not accepted because scipy silently drops
+            # the step (!)
+            self.assertRaises(ValueError,
+                    x.__getitem__, (slice(a, b, -1), slice(c, d)))
+            self.assertRaises(ValueError,
+                    x.__getitem__, (slice(a, b), slice(c, d, 2)))
+
+            # Advanced indexing is not supported
+            self.assertRaises(ValueError,
+                    x.__getitem__, (tensor.ivector('l'), slice(a, b)))
+
+            # Indexing with random things is not supported either
+            self.assertRaises(ValueError,
+                    x.__getitem__, slice(tensor.fscalar('f'), None))
+            self.assertRaises(ValueError,
+                    x.__getitem__, (slice(None), slice([1,3,4], None)))
+
+    def test_GetItemScalar(self):
         sparse_formats = ('csc', 'csr')
         for format in sparse_formats:
             x = theano.sparse.csc_matrix('x')
@@ -1027,7 +1069,7 @@ def test_GetItemScalar():
             m = 50
             n = 50
 
-        vx = as_sparse_format(numpy.random.binomial(1, 0.5, (100, 100)),
+            vx = as_sparse_format(self.rng.binomial(1, 0.5, (100, 100)),
                                  format).astype(theano.config.floatX)
 
             f1 = theano.function([x, a, b], x[a, b])