def resample_buf(data, new_shape):
"""resamples d"""
d1_g = OCLArray.from_array(data)
d2_g = OCLArray.empty(new_shape, data.dtype)
if data.dtype.type == np.float32:
im = OCLImage.empty(data.shape[::1], dtype=np.float32)
elif data.dtype.type == np.complex64:
im = OCLImage.empty(data.shape[::1], dtype=np.float32, num_channels=2)
im.copy_buffer(d1_g)
d2_g.copy_image_resampled(im)
return d2_g.get()
def transfer(data):
"""transfers data"""
d1_g = OCLArray.from_array(data)
d2_g = OCLArray.empty_like(data)
if data.dtype.type == np.float32:
im = OCLImage.empty(data.shape[::1], dtype=np.float32)
elif data.dtype.type == np.complex64:
im = OCLImage.empty(data.shape[::1], dtype=np.float32, num_channels=2)
im.copy_buffer(d1_g)
d2_g.copy_image(im)
return d2_g.get()
def transfer(data):
"""transfers data"""
d1_g = OCLArray.from_array(data)
d2_g = OCLArray.empty_like(data)
if data.dtype.type == np.float32:
im = OCLImage.empty(data.shape[::1],dtype = np.float32)
elif data.dtype.type == np.complex64:
im = OCLImage.empty(data.shape[::1],dtype = np.float32, num_channels=2)
im.copy_buffer(d1_g)
d2_g.copy_image(im)
return d2_g.get()
def resample_buf(data, new_shape):
"""resamples d"""
d1_g = OCLArray.from_array(data)
d2_g = OCLArray.empty(new_shape,data.dtype)
if data.dtype.type == np.float32:
im = OCLImage.empty(data.shape[::1],dtype = np.float32)
elif data.dtype.type == np.complex64:
im = OCLImage.empty(data.shape[::1],dtype = np.float32, num_channels=2)
im.copy_buffer(d1_g)
d2_g.copy_image_resampled(im)
return d2_g.get()
def _setup_gpu(self):
dev = get_device()
self._queue = dev.queue
self._ctx = dev.context
prog = OCLProgram(absPath("kernels/bpm_3d_kernels.cl"))
# the buffers/ images
Nx, Ny = self.simul_xy
Nx0, Ny0 = self.shape[:2]
self._plan = fft_plan((Ny, Nx), **self.fftplan_kwargs)
self._buf_plane = OCLArray.empty((Ny, Nx), np.complex64)
self._buf_H = OCLArray.empty((Ny, Nx), np.complex64)
self._img_xy = OCLImage.empty((Ny, Nx),
dtype=np.float32,
num_channels=2)
# buffer for the weighted dn average
self.intens_g = OCLArray.empty((1, Ny, Nx), dtype=Bpm3d._real_type)
self.intens_dn_g = OCLArray.empty((1, Ny, Nx), dtype=Bpm3d._real_type)
self.intens_sum_g = OCLArray.zeros((), dtype=Bpm3d._real_type)
self.intens_dn_sum_g = OCLArray.zeros((), dtype=Bpm3d._real_type)
# the kernels
self._kernel_compute_propagator = prog.compute_propagator
self._kernel_compute_propagator.set_scalar_arg_dtypes((None, ) +
(np.float32, ) *
5)
self._kernel_compute_propagator_buf = prog.compute_propagator_buf
self._kernel_compute_propagator_buf.set_scalar_arg_dtypes(
(None, ) + (np.float32, ) * 5 + (None, ) * 2)
self._kernel_mult_complex = prog.mult
self._kernel_im_to_buf_field = prog.img_to_buf_field
self._kernel_im_to_buf_intensity = prog.img_to_buf_intensity
self._kernel_im_to_im_intensity = prog.img_to_img_intensity
self._kernel_buf_to_buf_field = prog.buf_to_buf_field
self._kernel_buf_to_buf_intensity = prog.buf_to_buf_intensity
self._kernel_mult_dn_img_float = prog.mult_dn_image
self._kernel_mult_dn_buf_float = prog.mult_dn
self._kernel_mult_dn_img_complex = prog.mult_dn_image_complex
self._kernel_mult_dn_buf_complex = prog.mult_dn_complex
self._kernel_mult_dn_img_float_local = prog.mult_dn_image_local
self._kernel_mult_dn_buf_float_local = prog.mult_dn_local
self._kernel_mult_dn_img_complex_local = prog.mult_dn_image_complex_local
self._kernel_mult_dn_buf_complex_local = prog.mult_dn_complex_local
self._kernel_reduction = OCLMultiReductionKernel(
np.float32,
neutral="0",
reduce_expr="a+b",
map_exprs=["a[i]", "b[i]"],
arguments="__global float *a, __global float *b")
self._fill_propagator(self.n0)
def resample_img(data, new_shape):
"""resamples d"""
d1_g = OCLImage.from_array(data)
d2_g = OCLImage.empty(new_shape,np.float32,num_channels = 2 if np.iscomplexobj(data) else 1)
d2_g.copy_image_resampled(d1_g)
return d2_g.get()
def resample_img(data, new_shape):
"""resamples d"""
d1_g = OCLImage.from_array(data)
d2_g = OCLImage.empty(new_shape,
np.float32,
num_channels=2 if np.iscomplexobj(data) else 1)
d2_g.copy_image_resampled(d1_g)
return d2_g.get()
def _setup_gpu(self):
dev = get_device()
self._queue = dev.queue
self._ctx = dev.context
prog = OCLProgram(absPath("kernels/bpm_3d_kernels.cl"))
# the buffers/ images
Nx, Ny = self.simul_xy
Nx0, Ny0 = self.shape[:2]
self._plan = fft_plan((Ny, Nx), **self.fftplan_kwargs)
self._buf_plane = OCLArray.empty((Ny, Nx), np.complex64)
self._buf_H = OCLArray.empty((Ny, Nx), np.complex64)
self._img_xy = OCLImage.empty((Ny, Nx), dtype=np.float32, num_channels=2)
# buffer for the weighted dn average
self.intens_g = OCLArray.empty((1, Ny, Nx), dtype=Bpm3d._real_type)
self.intens_dn_g = OCLArray.empty((1, Ny, Nx), dtype=Bpm3d._real_type)
self.intens_sum_g = OCLArray.zeros((), dtype=Bpm3d._real_type)
self.intens_dn_sum_g = OCLArray.zeros((), dtype=Bpm3d._real_type)
# the kernels
self._kernel_compute_propagator = prog.compute_propagator
self._kernel_compute_propagator.set_scalar_arg_dtypes((None,)+(np.float32,)*5)
self._kernel_compute_propagator_buf = prog.compute_propagator_buf
self._kernel_compute_propagator_buf.set_scalar_arg_dtypes((None,)+(np.float32,)*5+(None,)*2)
self._kernel_mult_complex = prog.mult
self._kernel_im_to_buf_field = prog.img_to_buf_field
self._kernel_im_to_buf_intensity = prog.img_to_buf_intensity
self._kernel_im_to_im_intensity = prog.img_to_img_intensity
self._kernel_buf_to_buf_field = prog.buf_to_buf_field
self._kernel_buf_to_buf_intensity = prog.buf_to_buf_intensity
self._kernel_mult_dn_img_float = prog.mult_dn_image
self._kernel_mult_dn_buf_float = prog.mult_dn
self._kernel_mult_dn_img_complex = prog.mult_dn_image_complex
self._kernel_mult_dn_buf_complex = prog.mult_dn_complex
self._kernel_mult_dn_img_float_local = prog.mult_dn_image_local
self._kernel_mult_dn_buf_float_local = prog.mult_dn_local
self._kernel_mult_dn_img_complex_local = prog.mult_dn_image_complex_local
self._kernel_mult_dn_buf_complex_local = prog.mult_dn_complex_local
self._kernel_reduction = OCLMultiReductionKernel(np.float32,
neutral="0", reduce_expr="a+b",
map_exprs=["a[i]", "b[i]"],
arguments="__global float *a, __global float *b")
self._fill_propagator(self.n0)
def __init__(self, *args, **kwargs):
kwargs["enforce_subsampled"] = True
super(Bpm3d_img, self).__init__(*args, **kwargs)
self._is_subsampled = True
self.result_im = OCLImage.empty(self.shape[::-1], dtype=np.float32)
def set_shape(self, dataShape):
if self.isGPU:
self.dataImg = OCLImage.empty(dataShape[::-1], dtype=self.dtype)
else:
raise NotImplementedError("TODO")
def image_create_write(data):
im = OCLImage.empty(data.shape, data.dtype)
im.write_array(data)
assert np.allclose(data, im.get())
def image_create_write(data):
im = OCLImage.empty(data.shape,data.dtype)
im.write_array(data)
assert np.allclose(data,im.get())
def __init__(self, *args, **kwargs):
kwargs["enforce_subsampled"] = True
super(Bpm3d_img, self).__init__(*args, **kwargs)
self._is_subsampled = True
self.result_im = OCLImage.empty(self.shape[::-1], dtype=np.float32)
