def findbestparams_iso(xsamples):
    """ Minimize sum of square differences of H_iso-<H_iso> for timesamples"""
    p = 0.5*np.sum(xsamples.T[3:]**2,axis=0)
    r = np.sum(xsamples.T[:3]**2,axis=0)
    return np.abs(leastsq(deltaH_iso,np.array([10.,10.]), Dfun = None , col_deriv=1,args=(p,r,))[0])
def findbestparams_iso ( xsamples ) : p = 0.5 * np . sum ( xsamples . T [ 3 : ] ** 2 , axis = 0 ) r = np . sum ( xsamples . T [ : 3 ] ** 2 , axis = 0 ) return np . abs ( leastsq ( deltaH_iso , np . array ( [ 10. , 10. ] ) , Dfun = None , col_deriv = 1 , args = ( p , r , ) ) [ 0 ] )
Minimize sum of square differences of H_iso-<H_iso> for timesamples