python – Scipy leastsq()函数开销

我正在使用scipy cookbook中给出的代码来解决这个问题：

def gaussian(height,center_x,center_y,width_x,width_y):
           """Returns a gaussian function with the given parameters"""
        width_x = float(width_x)
        width_y = float(width_y)
        return lambda x,y: height*exp(
                    -(((center_x-x)/width_x)**2+((center_y-y)/width_y)**2)/2)


def moments(data):
    """Returns (height,x,y,width_y)
    the gaussian parameters of a 2D distribution by calculating its
    moments """
    total = data.sum()
    X,Y = indices(data.shape)
    x = (X*data).sum()/total
    y = (Y*data).sum()/total
    col = data[:,int(y)]
    width_x = sqrt(abs((arange(col.size)-y)**2*col).sum()/col.sum())
    row = data[int(x),:]
    width_y = sqrt(abs((arange(row.size)-x)**2*row).sum()/row.sum())
    height = data.max()
    return height,width_y


def fitgaussian(data):
    """Returns (height,width_y)
    the gaussian parameters of a 2D distribution found by a fit"""
    params = moments(data)
    errorfunction = lambda p: ravel(gaussian(*p)(*indices(data.shape)) -
                                 data)
    p,success = optimize.leastsq(errorfunction,params,maxfev=50,ftol=1.49012e-05)
    return p

我能够通过组合errorfunction()和gaussian()函数将执行时间缩短一半,因此每次leastsq()调用errorfunction()时都会有一个函数调用而不是两个函数调用.

这让我相信大多数剩余的执行时间都花费在函数调用开销上,因为leastsq()算法调用了errorfunction().

有没有办法减少这个函数调用开销？我很茫然,因为leastsq()将一个函数作为输入.

如果我的描述令人困惑,我提前道歉,我是一名训练有素的机械工程师,我正在学习Python.如果有任何其他有用的信息,请告诉我.