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
请参见文档.
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).
这篇关于无法将`scipy.interpolate.RectBivariateSpline`与`matplotlib.pyplot，plot_surface`一起使用的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！