def from_memoryview(cls, mview: memoryview) -> VT:
"""Create an R vector/array from a memoryview.
The memoryview must be contiguous, and the C representation
for the vector must be compatible between R and Python. If
not the case, a :class:`ValueError` exception with will be
raised."""
if not embedded.isready():
raise embedded.RNotReadyError('Embedded R is not ready to use.')
if not mview.contiguous:
raise ValueError('The memory view must be contiguous.')
if not cls._check_C_compatible(mview):
cls._raise_incompatible_C_size(mview)
r_vector = None
n = len(mview)
with memorymanagement.rmemory() as rmemory:
r_vector = rmemory.protect(
openrlib.rlib.Rf_allocVector(
cls._R_TYPE, n)
)
dest_ptr = cls._R_GET_PTR(r_vector)
src_ptr = _rinterface.ffi.from_buffer(mview)
nbytes = n * mview.itemsize
_rinterface.ffi.memmove(dest_ptr, src_ptr, nbytes)
return r_vector
def from_memoryview(cls, mview: memoryview) -> VT:
"""Create an R vector/array from a memoryview.
The memoryview must be contiguous, and the C representation
for the vector must be compatible between R and Python. If
not the case, a :class:`ValueError` exception with will be
raised."""
if not embedded.isready():
raise embedded.RNotReadyError('Embedded R is not ready to use.')
if not mview.contiguous:
raise ValueError('The memory view must be contiguous.')
if mview.itemsize != cls._R_SIZEOF_ELT:
msg = (
'Incompatible C type sizes. '
'The R array type is {r_size} bytes '
'while the Python array type is {py_size} '
'bytes.'
.format(r_size=cls._R_SIZEOF_ELT,
py_size=mview.itemsize)
)
raise ValueError(msg)
r_vector = None
n = len(mview)
with memorymanagement.rmemory() as rmemory:
r_vector = rmemory.protect(
openrlib.rlib.Rf_allocVector(
cls._R_TYPE, n)
)
dest_ptr = cls._R_GET_PTR(r_vector)
src_ptr = _rinterface.ffi.from_buffer(mview)
nbytes = n * mview.itemsize
_rinterface.ffi.memmove(dest_ptr, src_ptr, nbytes)
return r_vector
def from_iterable(cls,
iterable,
populate_func=None,
set_elt=None,
cast_value=None) -> VT:
"""Create an R vector/array from an iterable."""
if not embedded.isready():
raise embedded.RNotReadyError('Embedded R is not ready to use.')
if populate_func is None:
populate_func = _populate_r_vector
if set_elt is None:
set_elt = cls._R_SET_VECTOR_ELT
if cast_value is None:
cast_value = cls._CAST_IN
n = len(iterable)
with memorymanagement.rmemory() as rmemory:
r_vector = rmemory.protect(
openrlib.rlib.Rf_allocVector(cls._R_TYPE, n))
populate_func(iterable, r_vector, set_elt, cast_value)
return r_vector