def test_dynd_view_of_numpy_array(self):
# Tests viewing a numpy array as a dynd.array
nonnative = self.nonnative
a = np.arange(10, dtype=np.int32)
n = nd.view(a)
self.assertEqual(nd.dtype_of(n), ndt.int32)
self.assertEqual(nd.ndim_of(n), a.ndim)
self.assertEqual(n.shape, a.shape)
self.assertEqual(n.strides, a.strides)
"""
a = np.arange(12, dtype=(nonnative + 'i4')).reshape(3,4)
n = nd.view(a)
self.assertEqual(nd.dtype_of(n), ndt.make_byteswap(ndt.int32))
self.assertEqual(nd.ndim_of(n), a.ndim)
self.assertEqual(n.shape, a.shape)
self.assertEqual(n.strides, a.strides)
"""
a = np.arange(49, dtype='i1')
a = a[1:].view(dtype=np.int32).reshape(4,3)
n = nd.view(a)
self.assertEqual(nd.dtype_of(n), ndt.make_unaligned(ndt.int32))
self.assertEqual(nd.ndim_of(n), a.ndim)
self.assertEqual(n.shape, a.shape)
self.assertEqual(n.strides, a.strides)
"""
def test_dynd_view_of_numpy_array(self):
# Tests viewing a numpy array as a dynd.array
nonnative = self.nonnative
a = np.arange(10, dtype=np.int32)
n = nd.view(a)
self.assertEqual(nd.dtype_of(n), ndt.int32)
self.assertEqual(nd.ndim_of(n), a.ndim)
self.assertEqual(n.shape, a.shape)
self.assertEqual(n.strides, a.strides)
a = np.arange(12, dtype=(nonnative + 'i4')).reshape(3,4)
n = nd.view(a)
self.assertEqual(nd.dtype_of(n), ndt.make_byteswap(ndt.int32))
self.assertEqual(nd.ndim_of(n), a.ndim)
self.assertEqual(n.shape, a.shape)
self.assertEqual(n.strides, a.strides)
a = np.arange(49, dtype='i1')
a = a[1:].view(dtype=np.int32).reshape(4,3)
n = nd.view(a)
self.assertEqual(nd.dtype_of(n), ndt.make_unaligned(ndt.int32))
self.assertEqual(nd.ndim_of(n), a.ndim)
self.assertEqual(n.shape, a.shape)
self.assertEqual(n.strides, a.strides)
a = np.arange(49, dtype='i1')
a = a[1:].view(dtype=(nonnative + 'i4')).reshape(2,2,3)
n = nd.view(a)
self.assertEqual(nd.dtype_of(n),
ndt.make_unaligned(ndt.make_byteswap(ndt.int32)))
self.assertEqual(nd.ndim_of(n), a.ndim)
self.assertEqual(n.shape, a.shape)
self.assertEqual(n.strides, a.strides)
def test_numpy_view_of_dynd_array(self):
# Tests viewing a dynd.array as a numpy array
nonnative = self.nonnative
n = nd.range(10, dtype=ndt.int32)
a = np.asarray(n)
self.assertEqual(a.dtype, np.dtype(np.int32))
self.assertTrue(a.flags.aligned)
self.assertEqual(a.ndim, nd.ndim_of(n))
self.assertEqual(a.shape, n.shape)
self.assertEqual(a.strides, n.strides)
# Make sure it's a view
a[1] = 100
self.assertEqual(nd.as_py(n[1]), 100)
n = nd.view(np.arange(12, dtype=(nonnative + 'i4')).reshape(3, 4))
a = np.asarray(n)
self.assertEqual(a.dtype, np.dtype(nonnative + 'i4'))
self.assertTrue(a.flags.aligned)
self.assertEqual(a.ndim, nd.ndim_of(n))
self.assertEqual(a.shape, n.shape)
self.assertEqual(a.strides, n.strides)
# Make sure it's a view
a[1, 2] = 100
self.assertEqual(nd.as_py(n[1, 2]), 100)
n = nd.view(
np.arange(49, dtype='i1')[1:].view(dtype=np.int32).reshape(4, 3))
a = np.asarray(n)
self.assertEqual(a.dtype, np.dtype(np.int32))
self.assertFalse(a.flags.aligned)
self.assertEqual(a.ndim, nd.ndim_of(n))
self.assertEqual(a.shape, n.shape)
self.assertEqual(a.strides, n.strides)
# Make sure it's a view
a[1, 2] = 100
self.assertEqual(nd.as_py(n[1, 2]), 100)
n = nd.view(
np.arange(49,
dtype='i1')[1:].view(dtype=(nonnative + 'i4')).reshape(
2, 2, 3))
a = np.asarray(n)
self.assertEqual(a.dtype, np.dtype(nonnative + 'i4'))
self.assertFalse(a.flags.aligned)
self.assertEqual(a.ndim, nd.ndim_of(n))
self.assertEqual(a.shape, n.shape)
self.assertEqual(a.strides, n.strides)
# Make sure it's a view
a[1, 1, 1] = 100
self.assertEqual(nd.as_py(n[1, 1, 1]), 100)
def test_numpy_view_of_dynd_array(self):
# Tests viewing a dynd.array as a numpy array
nonnative = self.nonnative
n = nd.range(10, dtype=ndt.int32)
a = np.asarray(n)
self.assertEqual(a.dtype, np.dtype(np.int32))
self.assertTrue(a.flags.aligned)
self.assertEqual(a.ndim, nd.ndim_of(n))
self.assertEqual(a.shape, n.shape)
self.assertEqual(a.strides, n.strides)
# Make sure it's a view
a[1] = 100
self.assertEqual(nd.as_py(n[1]), 100)
n = nd.view(np.arange(12, dtype=(nonnative + 'i4')).reshape(3,4))
a = np.asarray(n)
self.assertEqual(a.dtype, np.dtype(nonnative + 'i4'))
self.assertTrue(a.flags.aligned)
self.assertEqual(a.ndim, nd.ndim_of(n))
self.assertEqual(a.shape, n.shape)
self.assertEqual(a.strides, n.strides)
# Make sure it's a view
a[1,2] = 100
self.assertEqual(nd.as_py(n[1,2]), 100)
n = nd.view(np.arange(49, dtype='i1')[1:].view(dtype=np.int32).reshape(4,3))
a = np.asarray(n)
self.assertEqual(a.dtype, np.dtype(np.int32))
self.assertFalse(a.flags.aligned)
self.assertEqual(a.ndim, nd.ndim_of(n))
self.assertEqual(a.shape, n.shape)
self.assertEqual(a.strides, n.strides)
# Make sure it's a view
a[1,2] = 100
self.assertEqual(nd.as_py(n[1,2]), 100)
n = nd.view(np.arange(49, dtype='i1')[1:].view(
dtype=(nonnative + 'i4')).reshape(2,2,3))
a = np.asarray(n)
self.assertEqual(a.dtype, np.dtype(nonnative + 'i4'))
self.assertFalse(a.flags.aligned)
self.assertEqual(a.ndim, nd.ndim_of(n))
self.assertEqual(a.shape, n.shape)
self.assertEqual(a.strides, n.strides)
# Make sure it's a view
a[1,1,1] = 100
self.assertEqual(nd.as_py(n[1,1,1]), 100)
def __init__(self, dyndarr, nindex):
if nindex > nd.ndim_of(dyndarr):
raise IndexError('Cannot have more indices than dimensions')
self._nindex = nindex
self._dshape = datashape.dshape(nd.dshape_of(dyndarr)).subarray(nindex)
self._c_dtype = ndt.type(str(self._dshape))
self._dyndarr = dyndarr
def __init__(self, dyndarr):
if nd.ndim_of(dyndarr) <= 0:
raise IndexError('Need at least one dimension for iteration')
self._index = 0
self._len = len(dyndarr)
self._dshape = datashape.dshape(nd.dshape_of(dyndarr)).subarray(1)
self._c_dtype = ndt.type(str(self._dshape))
self._dyndarr = dyndarr
def test_numpy_view_of_noncontig_dynd_array(self):
n = nd.range(10)[1::3]
a = np.asarray(n)
self.assertEqual(a.dtype, np.dtype('i4'))
self.assertFalse(a.flags.c_contiguous)
self.assertEqual(a.ndim, nd.ndim_of(n))
self.assertEqual(a.shape, n.shape)
self.assertEqual(a.strides, n.strides)
# Make sure it's a view as needed
a[1] = 100
self.assertEqual(nd.as_py(n[1]), 100)
def test_numpy_view_of_noncontig_dynd_array(self):
n = nd.range(10)[1::3]
a = np.asarray(n)
self.assertEqual(a.dtype, np.dtype('i4'))
self.assertFalse(a.flags.c_contiguous)
self.assertEqual(a.ndim, nd.ndim_of(n))
self.assertEqual(a.shape, n.shape)
self.assertEqual(a.strides, n.strides)
# Make sure it's a view as needed
a[1] = 100
self.assertEqual(nd.as_py(n[1]), 100)
def __init__(self, dyndarr):
if nd.ndim_of(dyndarr) <= 0:
raise IndexError('Need at least one dimension for iteration')
self._index = 0
self._len = len(dyndarr)
ds = datashape.dshape(nd.dshape_of(dyndarr))
self._dshape = ds.subarray(1)
self._c_dtype = ndt.type(str(self._dshape))
self._usebuffer = (ndt.type(str(ds)) != nd.type_of(dyndarr))
self._buffer = None
self._buffer_index = -1
self._dyndarr = dyndarr
