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When I multiply an nxn matrix by a nx1 vector, I get back a nested vector. How do I avoid this or how do I recover the vector.

Examples:

Using @ operator

A = np.matrix([[1,4,3],[2,2,1],[5,4,2]]) v = np.array([1,2,3]) A @ v => RuntimeError: Iterator automatic output has an array subtype which changed the dimensions of the output

Using np.dot

np.dot(A,v) => matrix([[18,9,19]])

Here the vector is nested and is a matrix of shape (3,1). I just want a vector of length 3 (i.e. of shape (3,))

If I had declared the matrix as an array, using the @ operator would've worked just fine, but I can't do this for this homework exercise.

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  • np.matrix is ALWAYS 2d. And these math operations using np.matrix return np.matrix, even if the other argument is ndarray. You can use .A1 to return a 1d ndarray from a np.matrix: np.dot(A,v).A1. Commented Nov 2, 2018 at 6:51
  • Why is this homework assignment forcing you to use np.matrix? Read the docs. Developers would like us to stop using it. I"m closing this because the matrix to array conversion has already been covered. Commented Nov 2, 2018 at 6:53
  • Thanks! The object I given work with is a matrix. I don't know why, since they expect us to produce an array Commented Nov 2, 2018 at 7:02
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