def test_resize(self):
data = np.zeros(10)
B = DataBuffer(data=data)
data = np.zeros(20)
B.set_data(data)
assert B.nbytes == data.nbytes
assert B._need_resize is True
def test_set_data_base(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data, store=True)
B.set_data(data)
assert len(B._pending_data) == 1
def test_set_data_offset(self):
data = np.zeros(100, np.float32)
subdata = data[:10]
B = DataBuffer(data)
B.set_subdata(subdata, offset=10)
offset = B._pending_data[-1][2]
assert offset == 10*4
def test_set_data_base(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data, store=True, copy=False)
B.set_data(data)
assert len(B._pending_data) == 1
def test_invalid_view_after_set_data(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
Z = B[5:]
B.set_data(np.zeros(15, dtype=dtype))
assert Z._valid is False
def test_invalid_view_after_set_data(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
Z = B[5:]
B.set_data(np.zeros(15, dtype=dtype))
assert Z._valid is False
def test_set_data_offset(self):
data = np.zeros(100, np.float32)
subdata = data[:10]
B = DataBuffer(data)
B.set_subdata(subdata, offset=10)
last_cmd = B._context.glir.clear()[-1]
offset = last_cmd[2]
assert offset == 10*4
def test_set_data_offset(self):
data = np.zeros(100, np.float32)
subdata = data[:10]
B = DataBuffer(data)
B.set_subdata(subdata, offset=10)
last_cmd = B._glir.clear()[-1]
offset = last_cmd[2]
assert offset == 10 * 4
def test_invalid_view_after_resize(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
Y = B['position']
Z = B[5:]
B.resize_bytes(5)
assert Y._valid is False
assert Z._valid is False
def test_invalid_view_after_resize(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
Y = B['position']
Z = B[5:]
B.resize_bytes(5)
assert Y._valid is False
assert Z._valid is False
def test_set_data_base(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
B.set_data(data)
last_cmd = B._context.glir.clear()[-1]
assert last_cmd[0] == 'DATA'
# Extra kwargs are caught
self.assertRaises(TypeError, B.set_data, data, foo=4)
def test_set_data_base(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
B.set_data(data)
last_cmd = B._glir.clear()[-1]
assert last_cmd[0] == 'DATA'
# Extra kwargs are caught
self.assertRaises(TypeError, B.set_data, data, foo=4)
def test_non_contiguous_storage(self):
# Ask to have CPU storage and to use data as storage
# Not possible since data[::2] is not contiguous
data = np.ones(100, np.float32)
data_given = data[::2]
with use_log_level('warning', record=True, print_msg=False) as l:
B = DataBuffer(data_given, store=True)
assert len(l) == 1
assert B._data is not data_given
assert B.stride == 4
B = DataBuffer(data_given, store=False)
assert B._data is not data_given
assert B.stride == 4*2
def test_getitem_field(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
Z = B["position"]
assert Z.nbytes == 10 * 3 * np.dtype(np.float32).itemsize
assert Z.offset == 0
assert Z.size == 10
assert Z.itemsize == 3 * np.dtype(np.float32).itemsize
assert Z.stride == (3 + 2 + 4) * np.dtype(np.float32).itemsize
assert Z.dtype == (np.float32, 3)
Z = B["texcoord"]
assert Z.nbytes == 10 * 2 * np.dtype(np.float32).itemsize
assert Z.offset == 3 * np.dtype(np.float32).itemsize
assert Z.size == 10
assert Z.itemsize == 2 * np.dtype(np.float32).itemsize
assert Z.stride == (3 + 2 + 4) * np.dtype(np.float32).itemsize
assert Z.dtype == (np.float32, 2)
Z = B["color"]
assert Z.nbytes == 10 * 4 * np.dtype(np.float32).itemsize
assert Z.offset == (2 + 3) * np.dtype(np.float32).itemsize
assert Z.size == 10
assert Z.itemsize == 4 * np.dtype(np.float32).itemsize
assert Z.stride == (3 + 2 + 4) * np.dtype(np.float32).itemsize
assert Z.dtype == (np.float32, 4)
def test_no_resize_ellipsis(self):
data = np.zeros(10)
B = DataBuffer(data=data)
data = np.zeros(30)
# with self.assertRaises(ValueError):
# B[...] = data
self.assertRaises(ValueError, B.__setitem__, Ellipsis, data)
def test_broadcast_ellipsis(self):
data = np.zeros(10)
B = DataBuffer(data=data)
data = np.zeros(5)
B[Ellipsis] = data
glir_cmd = B._glir.clear()[-1]
assert glir_cmd[-1].shape == (10, )
def test_setitem_field_no_storage(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
self.assertRaises(ValueError, B.__setitem__, 'position', (1, 2, 3))
def test_setitem(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
B[1] = data[0]
B[-1] = data[0]
B[:5] = data[:5]
B[5:0] = data[:5] # Weird, but we apparently support this
# the below is no longer supported starting with NumPy 1.14.0
# this used to be converted to a single element array of the above
# dtype filled with 0s. This is no longer supported.
# B[1] = b'' # Gets converted into array of dtype. Lists do not work
# the below doesn't work on all systems (I guess?)
# B[1] = 0
B[1] = (
[0, 0, 0],
[0, 0],
[0, 0, 0, 0],
)
self.assertRaises(IndexError, B.__setitem__, +999, data[0])
self.assertRaises(IndexError, B.__setitem__, -999, data[0])
self.assertRaises(TypeError, B.__setitem__, [], data[0])
def test_non_contiguous_storage(self):
# Ask to have CPU storage and to use data as storage
# Not possible since data[::2] is not contiguous
data = np.ones(100, np.float32)
data_given = data[::2]
B = DataBuffer(data_given)
assert B.stride == 4 * 2
def test_setitem_broadcast(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data, store=True)
B['position'] = 1, 2, 3
assert np.allclose(data['position'].ravel(), np.resize([1, 2, 3], 30))
def test_setitem_strided(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data1 = np.zeros(10, dtype=dtype)
data2 = np.ones(10, dtype=dtype)
B = DataBuffer(data1)
s = slice(None, None, 2)
self.assertRaises(ValueError, B.__setitem__, s, data2[::2])
def test_every_two_item_no_storage(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data, store=False)
# with self.assertRaises(ValueError):
# B[::2] = data[::2]
s = slice(None, None, 2)
self.assertRaises(ValueError, B.__setitem__, s, data[::2])
def test_setitem_strided(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data1 = np.zeros(10, dtype=dtype)
data2 = np.ones(10, dtype=dtype)
B = DataBuffer(data1, store=True)
B[::2] = data2[::2]
assert np.allclose(data1['position'][::2], data2['position'][::2])
assert np.allclose(data1['texcoord'][::2], data2['texcoord'][::2])
assert np.allclose(data1['color'][::2], data2['color'][::2])
def test_setitem_half(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data1 = np.zeros(10, dtype=dtype)
data2 = np.ones(10, dtype=dtype)
B = DataBuffer(data1, store=True)
B[:5] = data2[:5]
assert np.allclose(data1['position'][:5], data2['position'][:5])
assert np.allclose(data1['texcoord'][:5], data2['texcoord'][:5])
assert np.allclose(data1['color'][:5], data2['color'][:5])
assert len(B._pending_data) == 2
def test_default_init(self):
# Check default storage and copy flags
data = np.ones(100)
B = DataBuffer(data)
assert B._store is True
assert B._copied is False
assert B.nbytes == data.nbytes
assert B.offset == 0
assert B.size == 100
assert B.itemsize == data.itemsize
assert B.stride == data.itemsize
assert B.dtype == data.dtype
def test_set_data_base_view(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data, store=True)
# set_data on field is not allowed because set_data
# can result in a buffer resize
# with self.assertRaises(ValueError):
# B['position'].set_data(data)
Z = B['position']
self.assertRaises(ValueError, Z.set_data, data)
def test_getitem_index(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
Z = B[0:1]
assert Z.nbytes == 1 * (3 + 2 + 4) * np.dtype(np.float32).itemsize
assert Z.offset == 0
assert Z.size == 1
assert Z.itemsize == (3 + 2 + 4) * np.dtype(np.float32).itemsize
assert Z.stride == (3 + 2 + 4) * np.dtype(np.float32).itemsize
assert Z.dtype == B.dtype
def test_structured_init(self):
# Check structured type
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
assert B.nbytes == data.nbytes
assert B.offset == 0
assert B.size == 10
assert B.itemsize == data.itemsize
assert B.stride == data.itemsize
assert B.dtype == data.dtype
def test_getitem(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
assert B[1].dtype == dtype
assert B[1].size == 1
assert B[-1].dtype == dtype
assert B[-1].size == 1
self.assertRaises(IndexError, B.__getitem__, +999)
self.assertRaises(IndexError, B.__getitem__, -999)
def test_default_init(self):
# Check default storage and copy flags
data = np.ones(100)
B = DataBuffer(data)
assert B.nbytes == data.nbytes
assert B.offset == 0
assert B.size == 100
assert B.itemsize == data.itemsize
assert B.stride == data.itemsize
assert B.dtype == data.dtype
# Given data must be actual numeric data
self.assertRaises(TypeError, DataBuffer, 'this is not nice data')
def test_setitem_half(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data1 = np.zeros(10, dtype=dtype)
data2 = np.ones(10, dtype=dtype)
B = DataBuffer(data1)
B._glir.clear()
B[:5] = data2[:5]
glir_cmds = B._glir.clear()
assert len(glir_cmds) == 1
set_data = glir_cmds[0][-1]
assert np.allclose(set_data['position'], data2['position'][:5])
assert np.allclose(set_data['texcoord'][:5], data2['texcoord'][:5])
assert np.allclose(set_data['color'][:5], data2['color'][:5])
def test_setitem(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
B[1] = data[0]
B[-1] = data[0]
B[:5] = data[:5]
B[5:0] = data[:5] # Weird, but we apparently support this
B[1] = b'' # Gets conveted into array of dtype. Lists do not work
self.assertRaises(IndexError, B.__setitem__, +999, data[0])
self.assertRaises(IndexError, B.__setitem__, -999, data[0])
self.assertRaises(TypeError, B.__setitem__, [], data[0])
def test_init_view(self):
data = np.zeros(10)
B = DataBuffer(data=data)
V = DataBufferView(B, 1)
assert V.size == 1
V = DataBufferView(B, slice(0, 5))
assert V.size == 5
V = DataBufferView(B, slice(5, 0))
assert V.size == 5
V = DataBufferView(B, Ellipsis)
assert V.size == 10
self.assertRaises(TypeError, DataBufferView, B, [])
self.assertRaises(ValueError, DataBufferView, B, slice(0, 10, 2))
def test_getitem_index(self):
dtype = np.dtype([('position', np.float32, 3),
('texcoord', np.float32, 2),
('color', np.float32, 4)])
data = np.zeros(10, dtype=dtype)
B = DataBuffer(data)
Z = B[0:1]
assert Z.base == B
assert Z.id == B.id
assert Z.nbytes == 1 * (3 + 2 + 4) * np.dtype(np.float32).itemsize
assert Z.offset == 0
assert Z.size == 1
assert Z.itemsize == (3 + 2 + 4) * np.dtype(np.float32).itemsize
assert Z.stride == (3 + 2 + 4) * np.dtype(np.float32).itemsize
assert Z.dtype == B.dtype
assert 'DataBufferView' in repr(Z)
# There's a few things we cannot do with a view
self.assertRaises(RuntimeError, Z.set_data, data)
self.assertRaises(RuntimeError, Z.set_subdata, data)
self.assertRaises(RuntimeError, Z.resize_bytes, 20)
self.assertRaises(RuntimeError, Z.__getitem__, 3)
self.assertRaises(RuntimeError, Z.__setitem__, 3, data)
def test_resize(self):
data = np.zeros(10)
B = DataBuffer(data=data)
data = np.zeros(20)
B.set_data(data)
assert B.nbytes == data.nbytes
def test_no_storage_copy(self):
data = np.ones(100, np.float32)
B = DataBuffer(data, store=False)
assert B.data is None
assert B.stride == 4
