Python：如何在箭袋图轴的范围内添加第二个 "non-Nan" 条件？

Question

我想设置箭袋图轴的限制 s.t。外部使用的网格中的 NaN 不会导致我的 ax 限制在没有任何数据点的情况下不必要地过长。

我自己得到的是：

import numpy as np
pylab.xlim(np.min(Km[np.isnan(C_diff) < 0.5 ]), np.max(Km[np.isnan(C_diff) < 0.5 ]))
    #two conditions: "np.min(Cm[np.isnan(K_diff) < 0.5" on min, max (Km) are missing 

pylab.ylim(np.min(Cm[np.isnan(K_diff) < 0.5 ]), np.max(Cm[np.isnan(K_diff) < 0.5 ])) 
    #two conditions: "np.min(Km[np.isnan(K_diff) < 0.5" on min, max (Cm) are missing

为了进一步说明，我想要用 matlab 语言：

xlim([min(min(Km(real(~(isnan(K_diff))).*real(~(isnan(C_diff))) > 0.5))),
max(max(Km(real(~(isnan(K_diff))).*real(~(isnan(C_diff))) > 0.5)))]);

ylim([min(min(Cm(real(~(isnan(K_diff))).*real(~(isnan(C_diff))) > 0.5))),
max(max(Cm(real(~(isnan(K_diff))).*real(~(isnan(C_diff))) > 0.5)))]);

很高兴得到答案！提前致谢！ :)

托比亚斯

Answer 1

我想我通过以下方式修复了它：

pylab.xlim(np.min(Km[np.isnan(C_diff)^np.isnan(K_diff).all() < 0.5 ]), 
np.max(Km[np.isnan(C_diff)^np.isnan(K_diff).all() < 0.5 ]))
pylab.ylim(np.min(Cm[np.isnan(K_diff)^np.isnan(C_diff).all() < 0.5 ]),
np.max(Cm[np.isnan(K_diff)^np.isnan(C_diff).all() < 0.5 ]))

然而，从结果来看我看不出有什么不同，但这是可以通过逻辑运算符实现的。

Python：如何在箭袋图轴的范围内添加第二个 "non-Nan" 条件？

Python: How can i add a second "non-Nan"-condition to the limits of my quiver plot axis?

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