Numpy广播

2018-07-28 本文已影响0人哈哈哈哈_ad14

cs231 numpy介绍
这个定义比较准确，可以先看看这个，再看后面的例子。
Broadcasting two arrays together follows these rules:

If the arrays do not have the same rank, prepend the shape of the lower rank array with 1s until both shapes have the same length.
The two arrays are said to be compatible in a dimension if they have the same size in the dimension, or if one of the arrays has size 1 in that dimension.
The arrays can be broadcast together if they are compatible in all dimensions.
After broadcasting, each array behaves as if it had shape equal to the elementwise maximum of shapes of the two input arrays.
In any dimension where one array had size 1 and the other array had size greater than 1, the first array behaves as if it were copied along that dimension

numpy 数组广播:例子比较多
Numpy中的广播(Broadcasting):这个例子比较清晰。
a.shape得到的是(3,) b是一个浮点数，如果转换成array，则b.shape是一个()，a的1轴对齐，补齐为1，a.shape(3,1)，b对齐，则对齐也为(3,1)，然后按照一一对应的方式计算
但是这一段说的不太对，根据后面的介绍，正确流程应该是这样：