I would make `arr.T2` the same as `np.atleast_2d(arr).T`. So a 1D array would act as a row vector, since that is already the convention for coercing 1D arrays to 2D.
On Tue, Apr 5, 2016 at 10:49 PM, Juan Nunez-Iglesias <jni.s...@gmail.com> wrote: > Todd, > > Would you consider a 1D array to be a row vector or a column vector for > the purposes of transposition? The "correct" answer is not clear to me. > > Juan. > > On Wed, Apr 6, 2016 at 12:26 PM, Alan Isaac <alan.is...@gmail.com> wrote: > >> On 4/5/2016 10:11 PM, Todd wrote: >> >>> When you try to transpose a 1D array, it does nothing. This is the >>> correct behavior, since it transposing a 1D array is meaningless. >>> However, this can often lead to unexpected errors since this is rarely >>> what you want. You can convert the array to 2D, using `np.atleast_2d` >>> or `arr[None]`, but this makes simple linear algebra computations more >>> difficult. >>> >>> I propose adding an argument to transpose, perhaps called `expand` or >>> `expanddim`, which if `True` (it is `False` by default) will force the >>> array to be at least 2D. A shortcut property, `ndarray.T2`, would be >>> the same as `ndarray.transpose(True)`. >>> >> >> >> >> Use `dot`. E.g., >> m.dot(a) >> >> hth, >> Alan Isaac >> >> >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> https://mail.scipy.org/mailman/listinfo/numpy-discussion >> > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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