Does np.dot automatically transpose vectors?

Question

I am trying to calculate the first and second order moments for a portfolio of stocks (i.e. expected return and standard deviation).

expected_returns_annual         


        

Answer 1

In NumPy, a transpose .T reverses the order of dimensions, which means that it doesn't do anything to your one-dimensional array weights.

This is a common source of confusion for people coming from Matlab, in which one-dimensional arrays do not exist. See Transposing a NumPy Array for some earlier discussion of this.

np.dot(x,y) has complicated behavior on higher-dimensional arrays, but its behavior when it's fed two one-dimensional arrays is very simple: it takes the inner product. If we wanted to get the equivalent result as a matrix product of a row and column instead, we'd have to write something like

np.asscalar(x @ y[:, np.newaxis])

adding a trailing dimension to y to turn it into a "column", multiplying, and then converting our one-element array back into a scalar. But np.dot(x,y) is much faster and more efficient, so we just use that.

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Edit: actually, this was dumb on my part. You can, of course, just write matrix multiplication x @ y to get equivalent behavior to np.dot for one-dimensional arrays, as tel's excellent answer points out.