def maximum_position(power_masked, kx, ky):
# estimate the maximum by parabolic->gaussian interpolation of pixels
dkx, dky = kx[0,1]-kx[0,0], ky[1,0]-ky[0,0]
iy_max, ix_max = ndimage.maximum_position(power_masked)
data_roi = power_masked.data[iy_max-1:iy_max+2, ix_max-1:ix_max+2]
x0, y0, z0 = utils.parab_interpolation(np.log(data_roi), 1, 1)
k_vec = np.array([(x0+ix_max-1)*dkx + kx[0, 0], (y0+iy_max-1)*dky + ky[0, 0]])
amp = np.exp(z0)
return k_vec, amp
def findmax(data):
i_max = data.argmax()
ix_max = int(i_max % data.shape[1])
iy_max = int(i_max / data.shape[1])
x0, y0, z0 = utils.parab_interpolation(data, ix_max, iy_max)
return np.array([kx[0]+x0*dkx, ky[0]+y0*dky])
