directory = './data/Sandia/'
# Import phase history and create platform dictionary
[phs, platform] = phsRead.Sandia(directory)
# Correct for reisdual video phase
phs_corr = phsTools.RVP_correct(phs, platform)
# Import image plane dictionary from './parameters/img_plane'
img_plane = imgTools.img_plane_dict(platform,
res_factor=1.0,
n_hat=platform['n_hat'])
# Apply polar format algorithm to phase history data
# (Other options not available since platform position is unknown)
img_pf = imgTools.polar_format(phs_corr, platform, img_plane, taylor=30)
# Degrade image with random 10th order polynomial phase
coeff = (np.random.rand(10) - 0.5) * img_pf.shape[0]
x = np.linspace(-1, 1, img_pf.shape[0])
y = np.poly1d(coeff)(x)
slope, intercept, r_value, p_value, std_err = linregress(x, y)
line = slope * x + np.mean(y)
y = y - line
ph_err = np.tile(np.array([y]).T, (1, img_pf.shape[1]))
img_err = sig.ft(sig.ift(img_pf, ax=0) * np.exp(1j * ph_err), ax=0)
# Autofocus image
print('autofocusing')
img_af, af_ph = imgTools.autoFocus2(img_err, win='auto')
# img_af, af_ph = imgTools.autoFocus2(img_err, win = 0, win_params = [500,0.8])
#Create platform dictionary
platform = plat_dict()
#Create image plane dictionary
img_plane = imgTools.img_plane_dict(platform)
#Simulate phase history, if needed
##############################################################################
nsamples = platform['nsamples']
npulses = platform['npulses']
x = img_plane['u']; y = img_plane['v']
points = [[0,0,0],
[0,-100,0],
[200,0,0]]
amplitudes = [1,1,1]
phs = phsTools.simulate_phs(platform, points, amplitudes)
##############################################################################
#Apply RVP correction
phs_corr = phsTools.RVP_correct(phs, platform)
#Demodulate phase history with constant reference, if needed
phs_fixed = phsTools.phs_to_const_ref(phs_corr, platform, upchirp = 1)
#Apply algorithm of choice to phase history data
img_pf = imgTools.polar_format(phs_corr, platform, img_plane, taylor = 43)
#img_wk = imgTools.omega_k(phs_fixed, platform, taylor = 43, upsample = 2)
#img_bp = imgTools.backprojection(phs_corr, platform, img_plane, taylor = 0, upsample = 2)
#Output image
plt.imshow(np.abs(img_pf))
[phs, platform] = phsRead.AFRL(directory, start_az, n_az=1)
# Create subapertures with angle less than 360 to use polar format algorithm
phs_list, plat_list = imgTools.subaperture(phs,
platform,
angle=15,
keep_R_c=False)
# Or compare to using backprojection on the same (keep_R_c can be true or false with bp)
#phs_list,plat_list=imgTools.subaperture(phs,platform,angle=15,keep_R_c=True)
print(len(phs_list))
images = []
#######
for i in range(len(phs_list)):
checkme = True if i == 0 else False
lil_img_plane=imgTools.img_plane_dict(plat_list[i],checkme=checkme,numPixels=160,\
length=22,force_xy=True)
img = imgTools.polar_format(phs_list[i],
plat_list[i],
lil_img_plane,
taylor=20,
prnt=False)
#img = imgTools.backprojection(phs_list[i], plat_list[i], lil_img_plane, taylor = 20,prnt=False)
images.append(img)
for image in images:
plt.figure()
imgTools.imshow(image, dB_scale=[-15, 0])
plt.title('')
