Python编程-numpy polyfit说NAN [英] Python programming - numpy polyfit saying NAN

问题描述

我编写的一个非常简单的代码有一些问题.我有4组数据，并想使用numpy polyfit生成多项式最佳拟合线.使用polyfit时，列表中的3个产生数字，但是使用polyfit时，第三个数据集产生NAN.下面是代码和打印输出.有任何想法吗?

I am having some issues with a pretty simple code I have written. I have 4 sets of data, and want to generate polynomial best fit lines using numpy polyfit. 3 of the lists yield numbers when using polyfit, but the third data set yields NAN when using polyfit. Below is the code and the print out. Any ideas?

代码:

ind_1=np.array(ind_1, np.float)

dep_1=np.array(dep_1, np.float)

x_1=np.arange(min(ind_1)-1, max(ind_1)+1, .01)

ind_2=np.array(ind_2, np.float)

dep_2=np.array(dep_2, np.float)

x_2=np.arange(min(ind_2)-1, max(ind_2)+1, .01)

ind_3=np.array(ind_3, np.float)

dep_3=np.array(dep_3, np.float)

x_3=np.arange(min(ind_3)-1, max(ind_3)+1, .01)

ind_4=np.array(ind_4, np.float)

dep_4=np.array(dep_4, np.float)

x_4=np.arange(min(ind_4)-1, max(ind_4)+1, .01)

下面将打印出上面生成的数组以及polyfit列表的内容，这些内容通常是多项式方程的系数，但是对于下面的第三种情况，所有polyfit的内容都将打印为NAN

print(ind_1)

print(dep_1)

print(np.polyfit(ind_1,dep_1,2))

print(ind_2)

print(dep_2)

print(np.polyfit(ind_2,dep_2,2))

print(ind_3)

print(dep_3)

print(np.polyfit(ind_3,dep_3,2))

print(ind_4)

print(dep_4)

print(np.polyfit(ind_4,dep_4,2))

打印出:

[ 1.405  1.871  2.713 ...,  5.367  5.404  2.155]

[ 0.274  0.07   0.043 ...,  0.607  0.614  0.152]

[ 0.01391925 -0.00950728  0.14803846]

[ 0.9760001  2.067      8.8       ...,  1.301      1.625      2.007    ]

[ 0.219      0.05       0.9810001 ...,  0.163      0.161      0.163    ]

[ 0.00886807 -0.00868727  0.17793324]

[ 1.143      0.9120001  2.162     ...,  2.915      2.865      2.739    ]

[ 0.283  0.3    0.27  ...,  0.227  0.213  0.161]

[ nan  nan  nan]

[ 0.167  0.315  1.938 ...,  2.641  1.799  2.719]

[ 0.6810001  0.7140001  0.309     ...,  0.283      0.313      0.251    ]

[ 0.00382331  0.00222269  0.16940372]

为什么第三种情况的polyfit常数列为NAN?所有数据集都具有相同类型的数据，并且所有代码都是一致的.请帮忙.

Why are the polyfit constants from the third case listed as NAN? All the data sets have same type of data, and all of the code is consistent. Please help.

推荐答案

只需查看您的数据即可.发生这种情况是因为您在dep_3中有一个NaN(元素713).您可以确保只在适合的情况下使用有限值，如下所示:

Just looked at your data. This is happening because you have a NaN in dep_3 (element 713). You can make sure that you only use finite values in the fit like this:

idx = np.isfinite(ind_3) & np.isfinite(dep_3)
print(np.polyfit(ind_3[idx], dep_3[idx], 2))

对于在大型数据集中查找不良值，numpy使其非常容易.您可以找到这样的索引:

As for finding for bad values in large datasets, numpy makes that really easy. You can find the indices like this:

print(np.where(~np.isfinite(dep_3)))

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