Ejemplo n.º 1
0
def get_min_gradient(image, cen, mask=None, start_exc=25):
    """Return the radial coordinate with the largest negative gradient.

    Needed for center refinement with sector or ring methods.

    Arguments:
        `image`: Image to use.
        `cen`: Tuple with the center coordinates.
        `mask`: Mask giving the pixels to be used in determination.
        `start_exc`: Number of points to exclude from the start (center) of the
            image radial gradient array
    """
    [I, n1] = c.radbin(image, cen, mask=mask)
    r = np.arange(len(I))
    yerr = np.sqrt(I)
    nzerr = yerr.copy()
    zrepl = np.abs(np.median(yerr))
    if zrepl == 0.0:
        zrepl = 1.0 # give up
    nzerr[nzerr <= 0.0] = zrepl
    sp = ip.UnivariateSpline(r, I, w=1/nzerr)
#    smoo = [ sp.derivatives(x)[0] for x in r ]
    grad = [ sp.derivatives(x)[1] for x in r ]
    gradmin = np.argmin(grad[start_exc:]) + start_exc
#    plt.plot(r, smoo, r, I, r, grad)
#    print("Min gradient: %d" % gradmin)
    return gradmin
Ejemplo n.º 2
0
 def ofun_sectors(cen):
     """Calculate two chi2s from two opposing sectors and multiply"""
     sect_cens = [0, 0.5*np.pi, np.pi, 1.5*np.pi]
     seclims = [ np.array([a - hwidth, a + hwidth])+np.pi/4.0 for a in sect_cens ]
     rints = [ c.radbin(image, cen, radrange=np.linspace(rstart,rstop), phirange=x, mask=mask)[0] for x in seclims ]
     chi2_1 = chivectors(rints[0], rints[2])
     chi2_2 = chivectors(rints[1], rints[3])
     return chi2_1*chi2_2
Ejemplo n.º 3
0
 def ofun_ringvariance(cen):
     """Calculate STD from counts in a (narrow) ring in the image"""
     [r, n] = c.radbin(image, cen, \
                 radrange=np.array([ringradius, ringradius+ringwidth]), \
                 phirange=np.linspace(0, 2*np.pi, \
                 np.floor(2*np.pi*ringradius)), mask=mask)
     r = r[r != 0]
     w = np.std(r)
     return w
Ejemplo n.º 4
0
    def ofun_ring(cen):
        """Return width of a Debye ring with the given center"""
        [r, n] = c.radbin(image, cen, peakrange, mask=mask)
        w = fwhm(x, r)
        # 2nd moment is not very stable
#        w = secondmoment(x, r)
#        print cen, w
#        sys.stdout.flush()
        return w
Ejemplo n.º 5
0
    def ofun_cylsymm(cen):
        """Calculate STD from counts in a (narrow) ring in the image"""
        R = 100
        [r, n] = c.radbin(image, cen, radrange=np.array([R,R+2]), phirange=np.linspace(0, 2*np.pi, np.floor(2*np.pi*R)), mask=mask)
        r = r[r != 0]
        w = np.std(r)
#        plt.hold(0)
#        plt.plot(r)
#        plt.show()
#        plt.waitforbuttonpress()
#        print cen, w
#        sys.stdout.flush()
        return w
Ejemplo n.º 6
0
def coordinate_test():
    m = np.zeros((9,9))
    m[0,4] = 1
    m[8,4]= 1
    m[4,0] = 1
    m[4,8]= 1
    (I,n) = r.radbin(m, (4.5, 4.5), radrange=np.arange(0,10), norm=0)
#    plt.plot(I)
#    plt.show()
#    plt.waitforbuttonpress()
#    print(I[4])
    assert(I[4] == 4.0)
    m = np.zeros((10,5))
    m[0,3] = 1
    (I,n) = r.radbin(m, (3.5, 5.5), radrange=np.arange(0,10), norm=0)
#    plt.plot(I)
#    plt.show()
    assert(I[5] == 1.0)
    I[5] = 0.0
    assert(not I.all())
    (I,n) = r.radbin(m, (3.5, 0.5), radrange=np.arange(0,10), norm=0)
    assert(I[0] == 1.0)
    I[0] = 0.0
    assert(not I.all())
Ejemplo n.º 7
0
    def ofun_sectors(cen):
        """Calculate two chi2s from two opposing sectors and multiply"""
        rstart = 120
        rstop = 220
        hwidth = 10 * (np.pi/180) # width in rads
        sect_cens = [0, 0.5*np.pi, np.pi, 1.5*np.pi]
        seclims = [ np.array([a - hwidth, a + hwidth])+np.pi/4.0 for a in sect_cens ]
        rints = [ c.radbin(image, cen, radrange=np.linspace(rstart,rstop), phirange=x, mask=mask)[0] for x in seclims ]
        chi2_1 = chivectors(rints[0], rints[2])
        chi2_2 = chivectors(rints[1], rints[3])

#        print(cen, chi2_1, chi2_2)
#        sys.stdout.flush()
#        plt.hold(0)
#        plt.plot(rints[0], 'b')
#        plt.hold(1)
#        plt.plot(rints[2], 'b')
#        plt.plot(rints[1], 'r')
#        plt.plot(rints[3], 'r')
#        plt.waitforbuttonpress()

        return chi2_1*chi2_2
Ejemplo n.º 8
0
def centerfit_peakwidth(image, startcen=None, peakrange=None, baseline=None, mask=None, plotit=False):
    """Return center from an image with a ring.

    Minimizes the width of the peak obtained from radial averaging
    in the given range as a function of the center position."""

    if peakrange is None:
        raise ValueError("peakrange must be supplied")

    if startcen is None:
        startcen = get_im_max(image)

    [r1, n1] = c.radbin(image, startcen, peakrange, mask=mask)
    if baseline == None:
        baseline = r1.min()
    x = np.arange(peakrange.size - 1)
    if(plotit):
        plt.hold(0)
        plt.plot(x, r1)
        plt.show()
#        plt.waitforbuttonpress()


    def ofun_ring(cen):
        """Return width of a Debye ring with the given center"""
        [r, n] = c.radbin(image, cen, peakrange, mask=mask)
        w = fwhm(x, r)
        # 2nd moment is not very stable
#        w = secondmoment(x, r)
#        print cen, w
#        sys.stdout.flush()
        return w

    def ofun_cylsymm(cen):
        """Calculate STD from counts in a (narrow) ring in the image"""
        R = 100
        [r, n] = c.radbin(image, cen, radrange=np.array([R,R+2]), phirange=np.linspace(0, 2*np.pi, np.floor(2*np.pi*R)), mask=mask)
        r = r[r != 0]
        w = np.std(r)
#        plt.hold(0)
#        plt.plot(r)
#        plt.show()
#        plt.waitforbuttonpress()
#        print cen, w
#        sys.stdout.flush()
        return w


    def ofun_sectors(cen):
        """Calculate two chi2s from two opposing sectors and multiply"""
        rstart = 120
        rstop = 220
        hwidth = 10 * (np.pi/180) # width in rads
        sect_cens = [0, 0.5*np.pi, np.pi, 1.5*np.pi]
        seclims = [ np.array([a - hwidth, a + hwidth])+np.pi/4.0 for a in sect_cens ]
        rints = [ c.radbin(image, cen, radrange=np.linspace(rstart,rstop), phirange=x, mask=mask)[0] for x in seclims ]
        chi2_1 = chivectors(rints[0], rints[2])
        chi2_2 = chivectors(rints[1], rints[3])

#        print(cen, chi2_1, chi2_2)
#        sys.stdout.flush()
#        plt.hold(0)
#        plt.plot(rints[0], 'b')
#        plt.hold(1)
#        plt.plot(rints[2], 'b')
#        plt.plot(rints[1], 'r')
#        plt.plot(rints[3], 'r')
#        plt.waitforbuttonpress()

        return chi2_1*chi2_2


    optcen = optim.fmin(ofun_sectors, startcen, disp=True)
    [r2, n2] = c.radbin(image, optcen, peakrange, mask=mask)
    if(plotit):
        plt.plot(x, r1, x, r2)
        plt.show()
    return optcen