def background_correct(data, raw_asic):
prime_asic = get_factorizable_block(raw_asic)
print "Working on block", prime_asic
block = data.matrix_copy_block(i_row=prime_asic[0],
i_column=prime_asic[1],
n_rows=prime_asic[2] - prime_asic[0],
n_columns=prime_asic[3] - prime_asic[1])
complex_data = flex.polar(block.as_double(),
flex.double(flex.grid(block.focus())))
from scitbx import fftpack
fft = fftpack.complex_to_complex_2d(block.focus())
# input data here
fft.forward(complex_data)
# your manipulation here
low_pass_filter(complex_data)
fft.backward(complex_data)
# real data
filtered_data = flex.real(complex_data) / (fft.n()[0] * fft.n()[1])
corrected_data = block - filtered_data.iround()
requested_block = data.matrix_copy_block(i_row=raw_asic[0],
i_column=raw_asic[1],
n_rows=raw_asic[2] - raw_asic[0],
n_columns=raw_asic[3] -
raw_asic[1])
requested_block.matrix_paste_block_in_place(
block=corrected_data,
i_row=prime_asic[0] - raw_asic[0],
i_column=prime_asic[1] - raw_asic[1])
return requested_block
def background_correct(data, raw_asic):
prime_asic = get_factorizable_block(raw_asic)
print "Working on block",prime_asic
block = data.matrix_copy_block(
i_row=prime_asic[0],i_column=prime_asic[1],
n_rows=prime_asic[2]-prime_asic[0],
n_columns=prime_asic[3]-prime_asic[1])
complex_data = flex.polar(block.as_double(),flex.double(flex.grid(block.focus())))
from scitbx import fftpack
fft = fftpack.complex_to_complex_2d(block.focus())
# input data here
fft.forward(complex_data)
# your manipulation here
low_pass_filter(complex_data)
fft.backward(complex_data)
# real data
filtered_data = flex.real(complex_data)/(fft.n()[0]*fft.n()[1])
corrected_data = block - filtered_data.iround()
requested_block = data.matrix_copy_block(
i_row=raw_asic[0],i_column=raw_asic[1],
n_rows=raw_asic[2]-raw_asic[0],
n_columns=raw_asic[3]-raw_asic[1])
requested_block.matrix_paste_block_in_place(
block = corrected_data,
i_row = prime_asic[0] - raw_asic[0],
i_column = prime_asic[1] - raw_asic[1]
)
return requested_block
def background_correct_padded_block(data, raw_asic): Pad = padded_unpadded(data,raw_asic) block = Pad.get_padded_input_data() complex_data = flex.polar(block.as_double(),flex.double(flex.grid(block.focus()))) from scitbx import fftpack fft = fftpack.complex_to_complex_2d(block.focus()) # input data here fft.forward(complex_data) # your manipulation here low_pass_filter(complex_data) fft.backward(complex_data) # real data filtered_data = flex.real(complex_data)/(fft.n()[0]*fft.n()[1]) # XXX change this depending on float/int data type: corrected_data = block - filtered_data.iround() return Pad.get_unpadded_result_data(corrected_data)
def background_correct_padded_block(data, raw_asic): Pad = padded_unpadded(data,raw_asic) block = Pad.get_padded_input_data() complex_data = flex.polar(block.as_double(),flex.double(flex.grid(block.focus()))) from scitbx import fftpack fft = fftpack.complex_to_complex_2d(block.focus()) # input data here fft.forward(complex_data) # your manipulation here low_pass_filter(complex_data) fft.backward(complex_data) # real data filtered_data = flex.real(complex_data)/(fft.n()[0]*fft.n()[1]) # XXX change this depending on float/int data type: corrected_data = block - filtered_data.iround() return Pad.get_unpadded_result_data(corrected_data)
