def _deserialize_numpy_matrix(data):
if data[1] != '|O':
assert data[0].dtype == np.uint8
return np.matrix(data[0].view(descr_to_dtype(data[1])),
copy=False)
else:
return np.matrix(data[0], dtype=np.dtype(data[1]), copy=False)
def descr_to_dtype(descr):
'''
descr may be stored as dtype.descr, which is a list of
(name, format, [shape]) tuples where format may be a str or a tuple.
Offsets are not explicitly saved, rather empty fields with
name, format == '', '|Vn' are added as padding.
This function reverses the process, eliminating the empty padding fields.
'''
if isinstance(descr, str):
# No padding removal needed
return np.dtype(descr)
elif isinstance(descr, tuple):
# subtype, will always have a shape descr[1]
dt = descr_to_dtype(descr[0])
return np.dtype((dt, descr[1]))
fields = []
offset = 0
for field in descr:
if len(field) == 2:
name, descr_str = field
dt = descr_to_dtype(descr_str)
else:
name, descr_str, shape = field
dt = np.dtype((descr_to_dtype(descr_str), shape))
# Ignore padding bytes, which will be void bytes with '' as name
# Once support for blank names is removed, only "if name == ''" needed)
is_pad = (name == '' and dt.type is np.void
and dt.names is None)
if not is_pad:
fields.append((name, dt, offset))
offset += dt.itemsize
names, formats, offsets = zip(*fields)
# names may be (title, names) tuples
nametups = (n if isinstance(n, tuple) else (None, n)
for n in names)
titles, names = zip(*nametups)
return np.dtype({
'names': names,
'formats': formats,
'titles': titles,
'offsets': offsets,
'itemsize': offset
})
def _deserialize_numpy_array_list(data):
if data[1] != '|O':
assert data[0].dtype == np.uint8
return data[0].view(descr_to_dtype(data[1]))
else:
return np.array(data[0], dtype=np.dtype(data[1]))
def test_descr_to_dtype(dt):
dt1 = format.descr_to_dtype(dt.descr)
assert_equal_(dt1, dt)
arr1 = np.zeros(3, dt)
arr2 = roundtrip(arr1)
assert_array_equal(arr1, arr2)
def test_descr_to_dtype(dt):
dt1 = format.descr_to_dtype(dt.descr)
assert_equal_(dt1, dt)
arr1 = np.zeros(3, dt)
arr2 = roundtrip(arr1)
assert_array_equal(arr1, arr2)
