三次样条内存错误

在具有 4GB 内存的计算机上，这种简单的插值会导致内存错误：

（基于：http://docs.scipy.org/doc/scipy/reference/tutorial/interpolate.html http://docs.scipy.org/doc/scipy/reference/tutorial/interpolate.html)

import numpy as np
from scipy.interpolate import interp1d

x = np.linspace(0, 10, 80000)
y = np.cos(-x**2/8.0)
f2 = interp1d(x, y, kind='cubic')

我考虑过将数据切成块，但是有没有一种方法可以在不需要这么多内存的情况下执行三次样条插值？ 为什么它甚至会陷入困境？

如果您在错误发生时查看回溯，您将看到类似以下内容：

---------------------------------------------------------------------------
MemoryError                               Traceback (most recent call last)
<ipython-input-4-1e538e8d766e> in <module>()
----> 1 f2 = interp1d(x, y, kind='cubic')

/home/warren/local_scipy/lib/python2.7/site-packages/scipy/interpolate/interpolate.py in __init__(self, x, y, kind, axis, copy, bounds_error, fill_value)
    390         else:
    391             minval = order + 1
--> 392             self._spline = splmake(x, y, order=order)
    393             self._call = self.__class__._call_spline
    394 

/home/warren/local_scipy/lib/python2.7/site-packages/scipy/interpolate/interpolate.py in splmake(xk, yk, order, kind, conds)
   1754 
   1755     # the constraint matrix
-> 1756     B = _fitpack._bsplmat(order, xk)
   1757     coefs = func(xk, yk, order, conds, B)
   1758     return xk, coefs, order

MemoryError: 

失败的功能是scipy.interpolate._fitpack._bsplmat(order, xk)。该函数创建一个 64 位浮点数的二维数组，其形状(len(xk), len(xk) + order - 1)。就您而言，该大小超过 51GB。

代替interp1d， 看看InterpolatedUnivariateSpline http://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.InterpolatedUnivariateSpline.html为你工作。例如，

import numpy as np
from scipy.interpolate import InterpolatedUnivariateSpline

x = np.linspace(0, 10, 80000)
y = np.cos(-x**2/8.0)
f2 = InterpolatedUnivariateSpline(x, y, k=3)

我没有遇到内存错误。