from pydeconv import deconv_tv_al, deconv_wiener
from utils import myconvolve, psf
if __name__ == '__main__':
#2d
from matplotlib.pyplot import imread
s = .1
x = imread("data/usaf.png")
x*= 255
h = psf(x.shape,(3.,11))
h = psf(x.shape,(5.,5.))
h2 = psf(x.shape,(11,3))
y = myconvolve(x,h)+s*np.amax(x)*np.random.uniform(0,1,x.shape)
y2 = myconvolve(x,h2)+s*np.amax(x)*np.random.uniform(0,1,x.shape)
# u = deconv_tv_al([y,y2],[h,h2])
u = deconv_tv_al(y,h,10.,1.)
from pydeconv import deconv_wiener, deconv_wiener2
from utils import myconvolve, psf
if __name__ == "__main__":
np.random.seed(0)
# 2d
from matplotlib.pyplot import imread
x = imread("data/usaf.png")
x = np.pad(x, ((256,) * 2,) * 2, mode="constant")
h = psf(x.shape, (3.0, 11))
h2 = psf(x.shape, (11, 3))
y = myconvolve(x, h) + 0.3 * np.amax(x) * np.random.uniform(0, 1, x.shape)
y2 = myconvolve(x, h2) + 0.3 * np.amax(x) * np.random.uniform(0, 1, x.shape)
u1 = deconv_wiener([y, y2], [h, h2], 1.0e-6)
u2 = deconv_wiener2([y, y2], [h2, h], 1.0e-6)
# #3d
# from spimagine import read3dTiff
#
# x = read3dTiff("data/usaf3d.tif")[100:228,100:228,100:228]
