问题描述
抱歉问了这么长的问题，也许有一个快速的解决方案，但我一直无法弄清楚。我有 3 个不同的数据集，其中包含 x 和 y 数据点，如下所示：
line1_x = [277.75,287.68,308.77,322.23,342.98,363.99,387.59,396.83,401.52,405.78,408.30,408.06,406.94,406.11,403.46,401.14,397.28,394.04,390.62,386.99,384.31,380.41,375.85,372.25,368.35,364.86,363.01,361.84,361.85,363.79,366.25,368.94,371.58,376.11,380.97,387.33,391.61,392.36,373.35,350.68]
line1_y = [806.00,779.43,713.71,731.96,701.13,621.68,525.04,490.21,467.48,455.57,445.59,440.54,436.74,432.71,434.32,438.06,449.00,462.25,476.56,493.43,514.02,538.52,570.87,614.20,664.00,708.06,750.61,786.38,814.16,834.67,853.45,864.71,872.50,882.23,893.28,907.94,922.18,931.05,950.03,1085.45]
line2_x = [443.98,442.71,441.24,437.57,427.09,417.82,418.20,418.14,417.76,414.84,411.93,408.14,404.29,402.48,400.63,398.01,394.43,392.05,391.69,391.06,388.61,384.59,378.93,374.67,372.82,371.07,370.50,370.96,372.11,374.10,377.05,381.65,385.54,388.72,389.27,389.00,389.71,391.49,392.60,385.89,384.39,361.87]
line2_y = [299.48,317.04,338.92,360.55,405.99,451.64,493.67,516.66,530.73,540.62,548.90,553.39,555.65,559.21,564.41,571.17,577.56,585.31,592.54,606.96,626.18,651.76,679.82,710.62,744.39,774.02,802.14,829.54,849.98,865.51,879.94,894.02,903.30,910.80,918.08,926.39,935.80,947.09,955.08,965.04,1076.83,1110.45]
line3_x = [302.52,313.15,340.68,352.96,364.85,378.51,407.05,437.33,453.73,462.99,467.79,470.68,472.10,473.56,473.49,472.72,471.14,468.91,467.76,466.58,463.90,460.31,457.23,453.48,448.68,443.65,438.08,433.63,429.14,424.09,418.62,415.17,414.60,417.55,422.72,429.17,436.35,443.75,450.29,455.66,459.26,461.39,462.30,463.23,469.86,435.97]
line3_y = [794.42,809.18,782.48,761.93,771.51,776.51,689.07,560.78,531.03,524.44,518.59,516.73,514.03,511.97,511.63,518.31,532.60,549.91,563.77,582.81,601.98,617.95,628.03,640.11,658.30,703.00,730.40,754.16,776.00,800.85,824.39,844.47,856.76,866.70,875.72,884.18,892.66,903.61,912.93,922.55,928.60,932.00,952.27,1029.70,1065.12]
这个数据集是一个点序列，所以时间和位置很重要，这就是为什么不能简单地将点添加到较小的数据集中并计算平均值。我一直在尝试对数据进行插值，以便所有插值线具有相同的距离，然后使用它来计算插值线的每个步骤的平均值。数据如下所示：
我使用 interp1d 函数使用 3 个数据集的最小 y 和最大 y 计算插值：
interpolated_y = np.linspace(minimum_y,maximum_y,num=100,endpoint=True)
interpolated_x = interp1d(line1_y,line1_x,fill_value="extrapolate")(interpolated_y)
它们看起来像这样：
这很好，因为所有线的内插点的步骤之间的所有距离都相同，并且内插点的数量完全相同，但是如果我用它来计算内插步骤之间的平均值，我就输了关于起点的信息，即我无法计算起点之间的平均值。
我的问题是：如何对 3 个数据集进行插值，以使每个数据集具有相同数量的插值点，并且每个数据集的点之间距离相同？，并且插值应从起点开始并以正确的方式继续方向。对于数据集较小的情况，应该进行外推。
或者，考虑到这些点是时间序列点，是否有另一种方法来计算它们的平均值？
解决方法
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