Python 为什么scipy.griddata返回带有'；立方'；如果输入为'；价值观'；纳南？

我想使用

scipy.griddata

对包含一些

nan

值的数组执行立方插值。但是，只要

values

参数中存在单个

nan

，返回的插值将仅填充

nan

。使用“最近”或“线性”插值方法时，情况并非如此

这种行为的原因是什么？是否有一种简单的方法可以忽略

值

输入中的NAN

这是一个最小的工作示例，改编自：

---

解决方案是在插入数据之前，从

点和
值的输入数组中删除所有
nan
numpy
可以有效地用于此操作：

import numpy as np

def func(x, y):
    return x*(1-x)*np.cos(4*np.pi*x) * np.sin(4*np.pi*y**2)**2

grid_x, grid_y = np.mgrid[0:1:10j, 0:1:10j]
points = np.random.rand(100, 2)
values = func(points[:,0], points[:,1])

values[0]=np.nan # now add a single nan value to the array

#Find all the indexes where there is no nan neither in values nor in points.
nonanindex=np.invert(np.isnan(points[:,0]))*np.invert(np.isnan(points[:,1]))*np.invert(np.isnan(values))

#Remove the nan using fancy indexing. griddata can now properly interpolate. The result will have nan only on the edges of the array
from scipy.interpolate import griddata
grid_z2 = riddata(np.stack((points[nonanindex,0],points[nonanindex,1]),axis=1), values[nonanindex], (grid_x, grid_y), method='cubic')

虽然这解决了问题，但我还没有回答为什么griddata函数的这个问题只出现在三次插值中

import numpy as np

def func(x, y):
    return x*(1-x)*np.cos(4*np.pi*x) * np.sin(4*np.pi*y**2)**2

grid_x, grid_y = np.mgrid[0:1:10j, 0:1:10j]
points = np.random.rand(100, 2)
values = func(points[:,0], points[:,1])

values[0]=np.nan # now add a single nan value to the array

#Find all the indexes where there is no nan neither in values nor in points.
nonanindex=np.invert(np.isnan(points[:,0]))*np.invert(np.isnan(points[:,1]))*np.invert(np.isnan(values))

#Remove the nan using fancy indexing. griddata can now properly interpolate. The result will have nan only on the edges of the array
from scipy.interpolate import griddata
grid_z2 = riddata(np.stack((points[nonanindex,0],points[nonanindex,1]),axis=1), values[nonanindex], (grid_x, grid_y), method='cubic')