Logger.py 文件源码

def plot_norm_points(self, Inputs_N, e, Perms, scales, fig=1):
        input = Inputs_N[0][0].data.cpu().numpy()
        e = torch.sort(e, 1)[0][0].data.cpu().numpy()
        Perms = [perm[0].data.cpu().numpy() for perm in Perms]
        plt.figure(fig)
        plt.clf()
        ee = e.copy()
        for i, perm in enumerate(Perms):
            plt.subplot(1, len(Perms), i + 1)
            colors = cm.rainbow(np.linspace(0, 1, 2 ** (scales - i)))
            perm = perm[np.where(perm > 0)[0]] - 1
            points = input[perm]
            e_scale = ee[perm]
            for node in xrange(2 ** (scales - i)):
                ind = np.where(e_scale == node)[0]
                pts = points[ind]
                plt.scatter(pts[:, 0], pts[:, 1], c=colors[node])
            ee //= 2
        path = os.path.join(self.path, 'visualize_example.png')
        plt.savefig(path)