amplitudes = [1, 1, 1]
phs = phsTools.simulate_phs(platform, points, amplitudes)
#Apply RVP correction
phs_corr = phsTools.RVP_correct(phs, platform)
#Apply algorithm of choice to phase history data
img_bp = imgTools.backprojection(phs_corr,
platform,
img_plane,
taylor=17,
upsample=2)
N = 1000
img_DSBP = imgTools.DSBP(phs_corr,
platform,
img_plane,
center=[200, 0, 0],
size=[N, N],
n=8)
#Output image
du = img_plane['du']
dv = img_plane['dv']
#u = img_plane['u']; v = img_plane['v']
u = np.arange(-N / 2, N / 2) * du
v = np.arange(-N / 2, N / 2) * dv
extent = [u.min(), u.max(), v.min(), v.max()]
plt.subplot(1, 2, 1)
plt.title('Full Backprojection')
imgTools.imshow(img_bp[1024 - N / 2:1024 + N / 2, 1315 - N / 2:1315 + N / 2],
dB_scale=[-25, 0],
#Create image plane dictionary
img_plane = imgTools.img_plane_dict(platform,
res_factor=1.4,
upsample=True,
aspect=1.0)
#Apply algorithm of choice to phase history data
img_bp = imgTools.backprojection(phs,
platform,
img_plane,
taylor=17,
upsample=2)
N = 128
img_DSBP = imgTools.DSBP(phs,
platform,
img_plane,
center=[-15 - 0.6, 22 - 0.4, 0],
size=[N, N])
#Output image
du = img_plane['du']
dv = img_plane['dv']
#u = img_plane['u']; v = img_plane['v']
u = np.arange(-N / 2, N / 2) * du
v = np.arange(-N / 2, N / 2) * dv
extent = [u.min(), u.max(), v.min(), v.max()]
plt.subplot(1, 2, 1)
plt.title('Full Backprojection')
imgTools.imshow(img_bp[177 - N // 2:177 + N // 2, 202 - N // 2:202 + N // 2],
dB_scale=[-25, 0],