plot_helpers.py 文件源码

python
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项目:Bayesian-Optimisation 作者: hyperc54 项目源码 文件源码
def updateInterface1D(self,solver,bbox,history,bounds):
        x = np.linspace(0, 1, 80)
        z=map(lambda y:bbox.queryAt([y]),x)
        xx=np.atleast_2d(x).T
        z_pred, sigma2_pred = solver.gp.predict(xx, eval_MSE=True)
        self.ax_scat.clear()
        self.ax_approx.clear()
        self.ax_eimap.clear()

        self.ax_scat.plot(x,np.array(z))
        self.ax_scat.scatter(np.array(history)[:,0],np.array(history)[:,1])
        self.ax_approx.plot(x,np.array(z_pred))
        self.ax_approx.fill_between(x,np.array(z_pred)+np.array(np.sqrt(sigma2_pred)),np.array(z_pred)-np.array(np.sqrt(sigma2_pred)),alpha=0.2)

        self.ax_approx.plot(x)
        target=min(np.array(history)[:,1])
        mean,variance=solver.gp.predict(xx,eval_MSE=True)
        z=(target-mean)/np.sqrt(variance)
        self.ax_approx.plot(x,np.sqrt(variance)*(z*norm.cdf(z)+norm.pdf(z)))
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