ValueError: operands could not be broadcast together with shapes、numpy广播错误

问题

# 不符合numpy的广播规则，触发了计算错误。两个向量或者矩阵维度不同，没法进行按位的运算；

M = np.ones((3, 2))
a = np.arange(3)M+a

解决方案

#查看np.newaxis进行维度扩增后的shape

a[:, np.newaxis].shape

(3, 1)

# 使用np.newaxis进行维度扩增，之后就符合了numpy的广播规则，就可以进行运算

M + a[:, np.newaxis]

array([[ 1.,  1.],[ 2.,  2.],[ 3.,  3.]])

还要注意，虽然我们在这里一直关注+运算符，但这些广播规则适用于任何二进制UFUNC。例如，下面是logaddexp(a，b)函数，它计算log(exp(a)+exp(b))的精度比简单方法高。

np.logaddexp(M, a[:, np.newaxis])******************************************************************************array([[ 1.31326169,  1.31326169],[ 1.69314718,  1.69314718],[ 2.31326169,  2.31326169]])

完整错误日志

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-219-f2cda6cbe81d> in <module>2 a = np.arange(3)3
----> 4 M+aValueError: operands could not be broadcast together with shapes (3,2) (3,)

参考：Computation on Arrays: Broadcasting

参考：Python Data Science Handbook

参考：Numpy的广播机制

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ValueError: operands could not be broadcast together with shapes、numpy广播错误

ValueError: operands could not be broadcast together with shapes、numpy广播错误

问题

解决方案

完整错误日志

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