def test_simu():
import siddon.simu as simu
im = simu.fa.infoarrays2infoarray([simu.Image((1, 1)),])
obj = simu.Object((1, 1, 1))
im[:] = 0.
obj[:] = 1.
im2 = siddon.projector(im.copy(), obj)
assert_almost_equal(im2[0], 0.39369162)
im[:] = 1.
obj[:] = 0.
obj2 = siddon.backprojector(im, obj.copy())
assert_almost_equal(obj2[0], 0.39369162)
# object
header = {'SIMPLE':True,'BITPIX':-64,
'NAXIS1':128, 'NAXIS2':128, 'NAXIS3':128,
'CRPIX1':64., 'CRPIX2':64., 'CRPIX3':64.,
'CDELT1':0.02, 'CDELT2':0.02, 'CDELT3':0.02,
'CRVAL1':0., 'CRVAL2':0., 'CRVAL3':0.,}
obj = siddon.simu.object_from_header(header)
obj[:] = siddon.phantom.shepp_logan(obj.shape)
#obj[:] = 1.
# data
image_header = {'n_images':10,
'SIMPLE':True, 'BITPIX':-64,
'NAXIS1':128, 'NAXIS2':128,
'CRPIX1':64, 'CRPIX2':64,
'CDELT1':6e-5, 'CDELT2':6e-5,
'CRVAL1':0., 'CRVAL2':0.,
}
image_header['radius'] = 200.
data = siddon.simu.circular_trajectory_data(**image_header)
data[:] = np.zeros(data.shape)
# projection
t = time.time()
data = siddon.projector(data, obj)
print("projection time : " + str(time.time() - t))
# backprojection
t = time.time()
x0 = obj.copy()
x0[:] = 0.
x0 = siddon.backprojector(data, x0.copy())
print("backprojection time : " + str(time.time() - t))
#!/usr/bin/env python
import numpy as np
import os
import copy
import time
import siddon
import fitsarray as fa
# data
path = os.path.join(os.getenv('HOME'), 'data', '171dec08')
obsrvtry = 'STEREO_A'
time_window = ['2008-12-01T00:00:00.000', '2008-12-15T00:00:00.000']
time_step = 8 * 3600. # one image every time_step seconds
data = siddon.secchi.read_data(path, bin_factor=8,
obsrvtry=obsrvtry,
time_window=time_window,
time_step=time_step)
# cube
shape = 3 * (128,)
header = {'CRPIX1':64., 'CRPIX2':64., 'CRPIX3':64.,
'CDELT1':0.0234375, 'CDELT2':0.0234375, 'CDELT3':0.0234375,
'CRVAL1':0., 'CRVAL2':0., 'CRVAL3':0.,}
cube = fa.zeros(shape, header=header)
t = time.time()
cube = siddon.backprojector(data, cube, obstacle="sun")
print("backprojection time : " + str(time.time() - t))
def rmatvec(x):
y = fa.fitsarray_from_header(cube_header)
y[:] = 0
backprojector(x, y, obstacle=obstacle)
return y
'CRPIX1':n / 2., 'CRPIX2':n / 2., 'CRPIX3':n / 2.,
'CDELT1':1.5 / n, 'CDELT2':1.5 / n, 'CDELT3':1.5 / n,
'CRVAL1':0., 'CRVAL2':0., 'CRVAL3':0.,}
obj = siddon.simu.object_from_header(header)
#obj[:] = siddon.phantom.shepp_logan(obj.shape)
obj[:] = 1.
# data
image_header = {'n_images':60,
'SIMPLE':True, 'BITPIX':-64,
'NAXIS1':128, 'NAXIS2':128,
'CRPIX1':64, 'CRPIX2':64,
'CDELT1':6e-5, 'CDELT2':6e-5,
'CRVAL1':0., 'CRVAL2':0.,
}
image_header['radius'] = 200.
for n_images in [10, 30, 60, 120]:
print n_images
image_header['n_images'] = n_images
data = siddon.simu.circular_trajectory_data(**image_header)
data[:] = np.zeros(data.shape)
# projection
t = time.time()
data = siddon.projector(data, obj)
print("projection time : " + str(time.time() - t))
# backprojection
x0 = siddon.fa.zeros(obj.shape, header=header)
t = time.time()
x0 = siddon.backprojector(data, x0)
print("backprojection time : " + str(time.time() - t))
def rmatvec(x):
x = fa.InfoArray(data=x, header=data_header)
y = xin
y[:] = 0.
backprojector(x, y, **kwargs)
return y
