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Python 3, an Illustrated Tour Transcripts

Chapter: Classes and inheritance

Lecture: Matrix Multiplication

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Pep 465 introduced what's called the matrix multiplication operator this came out in Python 3.5,

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from the pep we read: in numerical code there are two important operations, which compete for use of Python's asterisk operator

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element wise multiplication and matrix multiplication. Here's an example of doing matrix multiplication.

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If you're familiar with linear algebra, this is a common operation. Here I'm importing the numpy library and I'm creating 2 arrays

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and then I'm looping over the pairs of elements and multiplying them together and summing the result.

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This is doing what's called matrix multiplication. It gives me in this case 285 as the result. This pep introduced an operation to do that

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and we can use the @ sign around the two arrays and that also gives us the same result 285. Note that this is different than multiplication,

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if we simply multiply the array in numpy this is going to do what is called element wise multiplication

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and in that case, it will multiply every element in the array by 10, it won't do multiplication of the whole element by 10 per se.

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If you want to have a class that implements matrix multiplication you just need to implement the __matmul__ operator.

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Again, in Python, everything is an object and there are various protocols

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and if we follow certain protocols, we can take advantage of certain behavior. In this case, if we want to be able to use the @ sign

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we can Implement __matmul__. This case is pretty dumb example it simply ignores the other that's passed in there and returns 42,

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but you could do something more smart if you want to. If you're not familiar with dunder methods

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what's happening is self here would be a and b would come in as other and so inside of that method there, you could do whatever you wanted to

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with them and you could Implement that operation.