在Python中简化半日志图中的步骤

Question

我知道平滑曲线上有许多不同的线程，最著名的是this one。我尝试了此线程中的建议，但未成功（Savitzky-Golay，移动框，LOWESS，样条插值，来自scipy.ndimage的高斯滤波器...）。这是我的问题。我有一些数据点，如下图所示。它们实际上是离散的点，但是如果我将它们连接起来，则更容易看到我的观点。 我想简化步骤。有趣的是，您的眼睛和大脑会立即知道该怎么做。不幸的是，这不适用于我的计算机。 Scipy的Savitzky-Golay滤波器重现了这些步骤，我能找到的最佳解决方法是使用样条插值，然后再加上Savitzky-Golay滤波器。对于样条插值，我采用了x值的对数以使其在数值上没有问题。尽管结果仍然不能令人满意...边缘明显分开，最终曲线不平滑。我设置了不同的曲线以获得更好的可见性 如果有帮助，这里是原始数据数组：

x_vals = np.concatenate([np.linspace(0.1,1,50),np.linspace(2,10,50),np.linspace(20,100,50),np.linspace(200,1000,50)])

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