XRF_Alignment/phase_calculator.py at master · licode/XRF_Alignment · GitHub

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"""
calculate phase by given phase gradient
"""
import numpy as np

def reconstruct_phase(gx, gy):
    """
    reconstruct the final phase image using gx and gy
    gx: differential phase gradient in x
    gy: differential phase gradient in y
    """

    gx = np.array(gx)
    gy = np.array(gy)

    shapev = gy.shape
    print "shape is", shapev
    row = shapev[0]
    column = shapev[1]
    totalnum = row*column

    dx = 0.2  # in um
    dy = 0.2

    w = 1 # Weighting parameter
    tx = np.fft.fftshift(np.fft.fft2(gx))
    ty = np.fft.fftshift(np.fft.fft2(gy))


    c = np.arange(totalnum, dtype=complex).reshape(row, column)


    for i in range(row):
        for j in range(column):
            kappax = 2 * np.pi * (j+1-(np.floor(column/2.0)+1)) / (column*dx)
            kappay = 2 * np.pi * (i+1-(np.floor(row/2.0)+1)) / (row*dy)
            if kappax == 0 and kappay == 0:
                c[i, j] = 0
            else:
                cTemp = -1j * (kappax*tx[i][j]+w*kappay*ty[i][j]) / (kappax**2 + w*kappay**2)
                c[i, j] = cTemp

    padv1 = row*2
    padv2 = column*2
    c_new = np.zeros([row+2*padv1,column+2*padv2], dtype=complex)

    #c_new[padv1:-padv1, padv2:-padv2] = c
    c_new = c
    c_new = np.fft.ifftshift(c_new)
    phi = np.fft.ifft2(c_new)
    phi = phi.real
    #imsave(namephi, self.phi)

    return phi