def RenormalizeFunction(func, z_min, z_max):
"""
It re-normalizes the Function in the new limits (z_min,z_max).
We assume that region of the function definition will be cut not extended.
"""
spline = SplineCH()
spline.compile(func)
integrator = GaussLegendreIntegrator(500)
integrator.setLimits(z_min, z_max)
integral = integrator.integral(spline)
n_points = func.getSize()
step = (z_max - z_min) / (n_points - 1)
new_func = Function()
for i in range(n_points):
x = z_min + step * i
y = spline.getY(x) / integral
new_func.add(x, y)
new_func.setConstStep(1)
return new_func
f.add(x,y) f.dump() spline = SplineCH() spline.compile(f) spline.dump() print "================" n = 100 step = 0.8*(f.getMaxX() - f.getMinX())/(n-1) y_dev_max = 0. yp_dev_max = 0. for j in range(n): x = f.getMinX() + j*step y = FF(x) yp = FFP(x) ys = math.fabs(spline.getY(x) - y) yps = math.fabs(spline.getYP(x) - yp) if(y_dev_max < ys): #print "debug x=",x," dev y=",ys," y=",y y_dev_max = ys if(yp_dev_max < yps): #print "debug x=",x," dev yp=",yps," yp=",yp yp_dev_max = yps print " deviation y max =",y_dev_max print " deviation yp max =",yp_dev_max