studysv.py 文件源码

def analyseparamsneighbourhood(svdata, params, includejumps, randomstate):
    parameterndarray = transformparameterndarray(np.array(params), includejumps)
    offsets = np.linspace(-.5, .5, 10)
    for dimension in range(params.dimensioncount):
        xs, ys = [], []
        parametername = params.getdimensionname(dimension)
        print('Perturbing %s...' % parametername)
        for offset in offsets:
            newparameterndarray = np.copy(parameterndarray)
            newparameterndarray[dimension] += offset
            xs.append(inversetransformparameterndarray(newparameterndarray, includejumps)[dimension])
            y = runsvljparticlefilter(svdata, sv.Params(*inversetransformparameterndarray(newparameterndarray, includejumps)), randomstate).stochfilter.loglikelihood
            ys.append(y)
        fig = plt.figure()
        plot = fig.add_subplot(111)
        plot.plot(xs, ys)
        plot.axvline(x=inversetransformparameterndarray(parameterndarray, includejumps)[dimension], color='red')
        plot.set_xlabel(parametername)
        plot.set_ylabel('loglikelihood')
        plt.show()