def gaussian_xy_high(x, y, dd = ddh):
cenx, ceny = angle2xy(twoTheta0, Chi0, dd = dd)
two_Theta, Chi = xy2angle(x - sizex/2 + cenx, y - sizey/2 + ceny, dd = dd)
two_theta, _chi = two_Theta * D2R, Chi * D2R
return gaussian(two_theta, _chi)
D2R = pi/180.
R2D = 180./pi
#fig = pylab.figure()
#ax = Axes3D(fig)
hklfit = np.load('hklfit.npy').item()
hklxy = np.load('hkl_xy.npy').item()
hkl = hklfit.keys()[0]
alpha = hklfit[hkl][0]
x0, y0 = hklxy[hkl]
sizex, sizey = 31, 31
himage, limage = np.zeros((sizex, sizey)), np.zeros((sizex, sizey))
twoTheta0, Chi0 = xy2angle(x0, y0)
twotheta0, chi0 = twoTheta0 * D2R, Chi0 * D2R
FWHMx, FWHMy, xi, Imax = 0.003, 0.0028, 0., 1700.
full2theta, minchi, maxchi = pi, -pi, pi
sqcosxi, sin2xi, coef = pow(cos(xi), 2), sin(2*xi), 8*log(2)
sqsinxi = 1-sqcosxi
coefx, coefy = coef/pow(FWHMx, 2), coef/pow(FWHMy, 2)
A, B, C = (sqcosxi*coefx+sqsinxi*coefy)/2, sin2xi*(coefy-coefx)/4, (sqcosxi*coefy+sqsinxi*coefx)/2
gaussian = lambda x, y: Imax*exp(-(A*(x-twotheta0)**2+2*B*(x-twotheta0)*(y-chi0)+C*(y-chi0)**2))
dd = 59.836
expe, var = np.load('exp_var.npy')[0: 2]
def gen_prototype(sizex, sizey, ddh = dd * 2, ddl = dd):