def _process_data(input_task, output_task, sinograms, slices):
import ufo.numpy as unp
num_sinograms, num_projections, width = sinograms.shape
for i in range(num_sinograms):
if i == 0:
data = unp.empty_like(sinograms[i, :, :])
else:
data = input_task.get_input_buffer()
# Set host array pointer and use that as first input
data.set_host_array(sinograms[i, :, :].__array_interface__['data'][0],
False)
input_task.release_input_buffer(data)
# Get last output and copy result back into NumPy buffer
data = output_task.get_output_buffer()
array = unp.asarray(data)
frm = int(array.shape[0] / 2 - width / 2)
to = int(array.shape[0] / 2 + width / 2)
slices[i, :, :] = array[frm:to, frm:to]
output_task.release_output_buffer(data)
input_task.stop()
def _process_data(input_task, output_task, sinograms, slices):
import ufo.numpy as unp
num_sinograms, num_projections, width = sinograms.shape
for i in range(num_sinograms):
if i == 0:
data = unp.empty_like(sinograms[i, :, :])
else:
data = input_task.get_input_buffer()
# Set host array pointer and use that as first input
data.set_host_array(
sinograms[i, :, :].__array_interface__['data'][0], False)
input_task.release_input_buffer(data)
# Get last output and copy result back into NumPy buffer
data = output_task.get_output_buffer()
array = unp.asarray(data)
frm = int(array.shape[0] / 2 - width / 2)
to = int(array.shape[0] / 2 + width / 2)
slices[i, :, :] = array[frm:to, frm:to]
output_task.release_output_buffer(data)
input_task.stop()