本文介绍了缺少值的pcolormesh?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有3个一维ndarray:x,y,z
I have 3 1-D ndarrays: x, y, z
和以下代码:
import numpy as np
import matplotlib.pyplot as plt
import scipy.interpolate as spinterp
## define data
npoints = 50
xreg = np.linspace(x.min(),x.max(),npoints)
yreg = np.linspace(y.min(),y.max(),npoints)
X,Y = np.meshgrid(xreg,yreg)
Z = spinterp.griddata(np.vstack((x,y)).T,z,(X,Y),
method='linear').reshape(X.shape)
## plot
plt.close()
ax = plt.axes()
col = ax.pcolormesh(X,Y,Z.T)
plt.draw()
我的图空白了,我怀疑是因为方法='linear'插值是用nans出来的.我试过转换为带掩码的数组,但无济于事-情节仍然是空白.你能告诉我我做错了什么吗?谢谢.
My plot comes out blank, and I suspect it is because the method='linear' interpolation comes out with nans. I've tried converting to a masked array, but to no avail - plot is still blank. Can you tell me what I am doing wrong? Thanks.
推荐答案
知道了.这似乎是回旋的,但这是解决方案:
Got it. This seems round-about, but this was the solution:
import numpy.ma as ma
Zm = ma.masked_where(np.isnan(Z),Z)
plt.pcolormesh(X,Y,Zm.T)
如果Z矩阵包含nan
,则它必须是pcolormesh
的掩码数组,必须使用ma.masked_where
或
If the Z matrix contains nan
's, it has to be a masked array for pcolormesh
, which has to be created with ma.masked_where
, or, alternatively,
Zm = ma.array(Z,mask=np.isnan(Z))
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