Difference between numpy.array shape (R, 1) and (R,)

Question

In numpy, some of the operations return in shape (R, 1) but some return (R,). This will make matrix multiplication more tedious since

Answer 1

The difference between (R,) and (1,R) is literally the number of indices that you need to use. ones((1,R)) is a 2-D array that happens to have only one row. ones(R) is a vector. Generally if it doesn't make sense for the variable to have more than one row/column, you should be using a vector, not a matrix with a singleton dimension.

For your specific case, there are a couple of options:

1) Just make the second argument a vector. The following works fine:

    np.dot(M[:,0], np.ones(R))

2) If you want matlab like matrix operations, use the class matrix instead of ndarray. All matricies are forced into being 2-D arrays, and operator * does matrix multiplication instead of element-wise (so you don't need dot). In my experience, this is more trouble that it is worth, but it may be nice if you are used to matlab.