def _copy(self, self_ref, other_ref):
if (len(other_ref) <= len(self_ref)):
from pycuda.elementwise import get_copy_kernel
func = get_copy_kernel(self.dtype, other_ref.dtype)
func.prepared_async_call(self_ref._grid, self_ref._block, None,
self_ref.gpudata, other_ref.gpudata,
self_ref.mem_size)
else:
raise RuntimeError("The arrays must the same length")
def _copy(self, self_ref, other_ref):
if (len(other_ref) <= len(self_ref)) :
from pycuda.elementwise import get_copy_kernel
func = get_copy_kernel(self.dtype, other_ref.dtype)
func.prepared_async_call(self_ref._grid, self_ref._block, None,
self_ref.gpudata, other_ref.gpudata,
self_ref.mem_size)
else:
raise RuntimeError("The arrays must the same length")
def astype(self, dtype, stream=None):
if dtype == self.dtype:
return self
result = self._new_like_me(dtype=dtype)
func = elementwise.get_copy_kernel(dtype, self.dtype)
func.set_block_shape(*self._block)
func.prepared_async_call(self._grid, stream, result.gpudata,
self.gpudata, self.mem_size)
return result
def astype(self, dtype, stream=None):
if dtype == self.dtype:
return self
result = self._new_like_me(dtype=dtype)
func = elementwise.get_copy_kernel(dtype, self.dtype)
func.set_block_shape(*self._block)
func.prepared_async_call(self._grid, stream,
result.gpudata, self.gpudata,
self.mem_size)
return result
def astype(self, dtype, stream=None):
if not self.flags.forc:
raise RuntimeError("only contiguous arrays may " "be used as arguments to this operation")
if dtype == self.dtype:
return self
result = self._new_like_me(dtype=dtype)
func = elementwise.get_copy_kernel(dtype, self.dtype)
func.prepared_async_call(self._grid, self._block, stream, result.gpudata, self.gpudata, self.mem_size)
return result
def astype(self, dtype, stream=None):
if not self.flags.forc:
raise RuntimeError("only contiguous arrays may "
"be used as arguments to this operation")
if dtype == self.dtype:
return self
result = self._new_like_me(dtype=dtype)
func = elementwise.get_copy_kernel(dtype, self.dtype)
func.prepared_async_call(self._grid, self._block, stream,
result.gpudata, self.gpudata, self.mem_size)
return result
def __setitem__(self, index, other):
if isinstance(other, Array):
if self.kind is 'real' and other.kind is 'complex':
raise ValueError('Cannot set real value with complex')
if isinstance(index, slice):
self_ref = self._data[index]
other_ref = other._data
else:
self_ref = self._data[index:index + 1]
other_ref = other._data
if type(self._data) is _numpy.ndarray:
self_ref[:] = other_ref[:]
elif _pycbc.HAVE_CUDA and type(self._data) is _cudaarray.GPUArray:
if (len(other_ref) <= len(self_ref)):
from pycuda.elementwise import get_copy_kernel
func = get_copy_kernel(self.dtype, other.dtype)
func.prepared_async_call(self_ref._grid, self_ref._block,
None, self_ref.gpudata,
other_ref.gpudata,
self_ref.mem_size)
else:
raise RuntimeError("The arrays must the same length")
elif _pycbc.HAVE_OPENCL and type(self._data) is _openclarray.Array:
raise NotImplementedError
elif type(other) in _ALLOWED_SCALARS:
if isinstance(index, slice):
self[index].fill(other)
else:
self[index:index + 1].fill(other)
else:
raise TypeError('Can only copy data from another Array')