def zeros(dshape, params=None):
""" Create an Array and fill it with zeros.
Parameters
----------
dshape : str, blaze.dshape instance
Specifies the datashape of the outcome object.
params : blaze.params object
Any parameter supported by the backend library.
Returns
-------
out : an Array object.
"""
if isinstance(dshape, basestring):
dshape = _dshape(dshape)
shape, dtype = to_numpy(dshape)
cparams, rootdir, format_flavor = to_cparams(params or _params())
if rootdir is not None:
carray.zeros(shape, dtype, rootdir=rootdir, cparams=cparams)
return open(rootdir)
else:
source = CArraySource(carray.zeros(shape, dtype, cparams=cparams),
params=params)
return Array(source)
def zeros(dshape, params=None):
""" Create an Array and fill it with zeros.
Parameters
----------
dshape : str, blaze.dshape instance
Specifies the datashape of the outcome object.
params : blaze.params object
Any parameter supported by the backend library.
Returns
-------
out : an Array object.
"""
if isinstance(dshape, basestring):
dshape = _dshape(dshape)
shape, dtype = to_numpy(dshape)
cparams, rootdir, format_flavor = to_cparams(params or _params())
if rootdir is not None:
carray.zeros(shape, dtype, rootdir=rootdir, cparams=cparams)
return open(rootdir)
else:
source = CArraySource(carray.zeros(shape, dtype, cparams=cparams),
params=params)
return Array(source)
def __init__(self, data=None, dshape=None, params=None):
# need at least one of the three
assert (data is not None) or (dshape is not None) or \
(params.get('storage'))
if isinstance(data, ctable):
self.ca = data
return
# Extract the relevant carray parameters from the more
# general Blaze params object.
if params:
cparams, rootdir, format_flavor = to_cparams(params)
else:
rootdir,cparams = None, None
# Extract the relevant carray parameters from the more
# general Blaze params object.
if dshape:
shape, dtype = to_numpy(dshape)
if len(data) == 0:
data = np.empty(0, dtype=dtype)
self.ca = ctable(data, rootdir=rootdir, cparams=cparams)
else:
self.ca = ctable(data, dtype=dtype, rootdir=rootdir)
else:
self.ca = ctable(data, rootdir=rootdir, cparams=cparams)
def test_not_compat():
with assert_raises(NotNumpyCompatible):
to_numpy(dshape('x, int32'))
with assert_raises(NotNumpyCompatible):
to_numpy(dshape('{1}, int32'))
with assert_raises(NotNumpyCompatible):
to_numpy(dshape('Range(0, 3), int32'))
def test_not_compat():
with assert_raises(NotNumpyCompatible):
to_numpy(dshape('x, int32'))
with assert_raises(NotNumpyCompatible):
to_numpy(dshape('{1}, int32'))
with assert_raises(NotNumpyCompatible):
to_numpy(dshape('Range(0, 3), int32'))
def broadcast(*operands):
types = [_get_datashape(op) for op in operands if op is not None]
shapes = []
for t in types:
try:
shapes.append(coretypes.extract_dims(t))
except coretypes.NotNumpyCompatible:
pass
# TODO: broadcasting
datashapes = [coretypes.to_numpy(coretypes.extract_measure(ds)) for ds in types]
type = coretypes.promote_cvals(*datashapes)
if not shapes:
return type
return DataShape(shapes[0] + (type,))
def broadcast(*operands):
types = [_get_datashape(op) for op in operands if op is not None]
shapes = []
for t in types:
try:
shapes.append(coretypes.extract_dims(t))
except coretypes.NotNumpyCompatible:
pass
# TODO: broadcasting
datashapes = [
coretypes.to_numpy(coretypes.extract_measure(ds)) for ds in types
]
type = coretypes.promote_cvals(*datashapes)
if not shapes:
return type
return DataShape(shapes[0] + (type, ))
def __init__(self, data=None, dshape=None, params=None):
# need at least one of the three
assert (data is not None) or (dshape is not None) or \
(params.get('storage'))
# Extract the relevant carray parameters from the more
# general Blaze params object.
if params:
cparams, rootdir, format_flavor = to_cparams(params)
else:
rootdir,cparams = None, None
if dshape:
dtype = to_numpy(dshape)
self.ca = carray.carray(data, dtype, rootdir=rootdir)
else:
self.ca = carray.carray(data, rootdir=rootdir, cparams=cparams)
def __init__(self, data=None, dshape=None, params=None):
# need at least one of the three
assert (data is not None) or (dshape is not None) or \
(params.get('storage'))
# Extract the relevant carray parameters from the more
# general Blaze params object.
if params:
cparams, rootdir, format_flavor = to_cparams(params)
else:
rootdir, cparams = None, None
if dshape:
shape, dtype = to_numpy(dshape)
self.ca = carray.carray(data, dtype=dtype, rootdir=rootdir)
else:
self.ca = carray.carray(data, rootdir=rootdir, cparams=cparams)
self.dshape = dshape
def __init__(self, data=None, dshape=None, params=None):
""" CArray object passed directly into the constructor,
ostensibly this is just a thin wrapper that consumes a
reference.
"""
# need at least one of the three
assert (data is not None) or (dshape is not None) or (params.get("storage"))
# TODO: clean up ugly conditionals
if params:
rootdir = params.get("storage")
# compatabaility
cparams = carray.cparams(params.get("clevel"), params.get("shuffle"))
else:
rootdir = None
cparams = None
if dshape:
dtype = to_numpy(dshape)
self.ca = carray.carray(data, dtype, rootdir=rootdir)
else:
self.ca = carray.carray(data, rootdir=rootdir, cparams=cparams)
def test_dtype_compat(self):
self.assertEqual(to_numpy(blaze.int32), np.int32)
self.assertEqual(to_numpy(blaze.int64), np.int64)
self.assertEqual(to_numpy(blaze.float_), np.float_)
self.assertEqual(to_numpy(blaze.int_), np.int_)
def test_shape_compat(self):
self.assertEqual(to_numpy(dshape('1, int32')), ((1,), np.int32))
self.assertEqual(to_numpy(dshape('1, 2, int32')), ((1, 2), np.int32))
self.assertEqual(to_numpy(dshape('1, 2, 3, 4, int32')), ((1, 2, 3, 4), np.int32))
def test_dtype_compat(self):
self.assertEqual(to_numpy(blaze.int32), np.dtype(np.int32))
self.assertEqual(to_numpy(blaze.int64), np.dtype(np.int64))
self.assertEqual(to_numpy(blaze.float_), np.dtype(np.float_))
self.assertEqual(to_numpy(blaze.int_), np.dtype(np.int_))
def test_shape_compat():
to_numpy(dshape('1, int32')) == (1,), np.int32
to_numpy(dshape('1, 2, int32')) == (1, 2), np.int32
to_numpy(dshape('1, 2, 3, 4, int32')) == (1, 2, 3, 4), np.int32
def test_dtype_compat():
to_numpy(blaze.int32) == np.int32
to_numpy(blaze.int64) == np.int64
to_numpy(blaze.float_) == np.float_
to_numpy(blaze.int_) == np.int_
def test_dtype_compat():
to_numpy(blaze.int32) == np.int32
to_numpy(blaze.int64) == np.int64
to_numpy(blaze.float_) == np.float_
to_numpy(blaze.int_) == np.int_
def test_shape_compat():
to_numpy(dshape('1, int32')) == (1, ), np.int32
to_numpy(dshape('1, 2, int32')) == (1, 2), np.int32
to_numpy(dshape('1, 2, 3, 4, int32')) == (1, 2, 3, 4), np.int32
def test_shape_compat(self):
self.assertEqual(to_numpy(dshape('1, int32')), ((1,), np.int32))
self.assertEqual(to_numpy(dshape('1, 2, int32')), ((1, 2), np.int32))
self.assertEqual(to_numpy(dshape('1, 2, 3, 4, int32')), ((1, 2, 3, 4), np.int32))
