无法将`scipy.interpolate.RectBivariateSpline`与`matplotlib.pyplot，plot_surface`一起使用 [英] Unable to use `scipy.interpolate.RectBivariateSpline` with `matplotlib.pyplot,plot_surface`

问题描述

我尝试构建一个最小的示例来重现我遇到的问题.请忽略随机生成的数据数组x和y.我正在将完全有意义的数据输入到plot_surface内部的zSpline调用中.您可以尝试将倒数第二行替换为-surf=ax.plot_surface(xg,yg,z,rstride=1,cstride=1,cmap=cm.coolwarm,linewidth=0.1)，其中我已将ZSpline替换为粗略数据z.这项工作向我表明，我在语法上没有弄错.

I tried building a minimal example to reproduce a problem I was having. Please ignore the randomly generated data arrays x and y. I am feeding perfectly meaningful data into the zSpline call inside plot_surface. You could try replacing the penultimate line with - surf=ax.plot_surface(xg,yg,z,rstride=1,cstride=1,cmap=cm.coolwarm,linewidth=0.1) where I have replaced the ZSpline with the coarse data z. This works which indicates to me that I am not mistaken on syntax.

我的代码是-

import numpy as np
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib.pyplot as plt
from scipy.interpolate import RectBivariateSpline

size=21
dat = np.random.randn(size, 2)
x=dat[:,0]
y=dat[:,1]
z=np.random.randn(size//3,size//3)
i=np.tile([1,2,3],size//3)
bool_dat=(i==1)
x_new=x[bool_dat]
y_new=y[bool_dat]
xi=np.linspace(x_new.min(),x_new.max(),size//3)
yi=np.linspace(y_new.min(),y_new.max(),size//3)

#print z.shape,xi.shape,yi.shape

zSpline = RectBivariateSpline(xi,yi,z)

xg,yg = np.meshgrid(xi,yi)
print zSpline(xg,yg)
fig=plt.figure()
ax=fig.gca(projection='3d')
surf=ax.plot_surface(xg,yg,zSpline(xg,yg),rstride=1,cstride=1,cmap=cm.coolwarm,linewidth=0.1)
plt.show()

我得到的错误是-

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-13-a98e6c15985e> in <module>()
     22 
     23 xg,yg = np.meshgrid(xi,yi)
---> 24 print zSpline(xg,yg)
     25 fig=plt.figure()
     26 ax=fig.gca(projection='3d')

/usr/lib/python2.7/dist-packages/scipy/interpolate/fitpack2.pyc in __call__(self, x, y, mth)
    671             z,ier = dfitpack.bispev(tx,ty,c,kx,ky,x,y)
    672             if not ier == 0:
--> 673                 raise ValueError("Error code returned by bispev: %s" % ier)
    674             return z
    675         raise NotImplementedError('unknown method mth=%s' % mth)

ValueError: Error code returned by bispev: 10

这使我相信问题在于插值例程，而不是数据/语法.关于如何进一步测试的任何建议?

Which leads me to believe that problem is with the interpolation routine and not the data/syntax. Any suggestions on how to test this further?

为了回应告诉我该问题可能来自数据类型的评论，我决定使用非随机数据进行测试.以下代码与第一个代码几乎相同-但无论如何我都会再次粘贴它.

In response to the comment that tells me that the problem is probably from the type of data, I decided to test with non-random data. the following code is almost the same as the first one - but I will paste it again anyway.

import numpy as np
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib.pyplot as plt
from scipy.interpolate import RectBivariateSpline

size=21
xi=np.linspace(-np.pi,np.pi,size)
yi=np.linspace(-np.pi,np.pi,size)

xg,yg = np.meshgrid(xi,yi)
z=np.sin(xg)*np.sin(yg) #nice and smooth function
zSpline = RectBivariateSpline(xi,yi,z,kx=2,ky=2)
fig=plt.figure()
ax=fig.gca(projection='3d')
surf=ax.plot_surface(xg,yg,z,rstride=1,cstride=1,cmap=cm.coolwarm,linewidth=0.1)
#surf=ax.plot_surface(xg,yg,zSpline(xg,yg),rstride=1,cstride=1,cmap=cm.coolwarm,linewidth=0.1)
plt.show()

这给了我下面的图像作为输出. 但是，如果使用zSpline，则会引发错误.

This gives me the following image as output. However if the zSpline is used, an error is raised.

如果我使用xg,yg = np.ogrid[-np.pi:np.pi:size*1j,-np.pi:np.pi:size*1j]而不是meshgrid，此问题将自行解决.但是我仍然不知道为什么！

The issue resolves itself if I use xg,yg = np.ogrid[-np.pi:np.pi:size*1j,-np.pi:np.pi:size*1j] instead of meshgrid. But I still do not know why!

推荐答案

请参见问题是您给样条曲线的xg和yg是2D数组，但是例程希望它们是定义网格的1D数组(即xi,yi).

The issue is that xg and yg you give to the spline are 2D arrays, but the routine expects them to be 1D arrays that define the grid (i.e. xi,yi).

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