源代码位置和向量化数组操作的说明 [英] Source code location and explanation of vectorized array operations

问题描述

我正在尝试查找包含基本矢量化数组操作的NumPy .c文件.例如，当您对诸如a + 5的数组进行标量加法或执行诸如a.sum()的聚合之类的简单操作时，我想知道运行什么代码段.我相信ndarray对象在这里声明.

I am trying to locate the NumPy .c file that contains basic vectorized array operations. For instance, I'd like to know what piece of code runs when you do something simple like a scalar addition to an array like a + 5 or perform an aggregation like a.sum(). I believe the ndarray object gets declared here.

我还想知道是否有任何线性代数库(例如BLAS或LAPACK)与这些基本算术运算有关?代码是否像在C数组上进行for循环一样简单，还是计算机以某种神奇的方式对连续数组进行基本操作而没有for循环?

I'd also like to know if any of the linear algebra libraries like BLAS or LAPACK are involved with these basic arithmetic operations? Is the code as simple as a for-loop iterating over a C array or is there some magical way that computers do basic operations on contiguous arrays without for-loops?

推荐答案

大多数内容都在 numpy/core/src/umath/loops.c.src .这是NumPy用来生成很多非常相似的C函数的模板文件.不涉及BLAS或LAPACK调用.

Most of that stuff is in numpy/core/src/umath/loops.c.src. This is a template file NumPy uses to generate lots and lots of very similar C functions. No BLAS or LAPACK calls are involved.

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