On Wed, Jan 27, 2016 at 9:12 AM, Mirmojtaba Gharibi <mojtaba.gharibi@gmail.com> wrote:

MATLAB has a built-in easy way of achieving component-wise operation and I think Python would benefit from that without use of libraries such as numpy.

I've always thought there should be a component-wise operations in Python. The wlay to do it now is somthing like:

[i + j for i,j in zip(a,b)]

is really pretty darn wordy, compared to :

a_numpy_array + another_numpy array

(similar in matlab).

But maybe an operator is the way to do it. But it was long ago decide dnot to introduce a full set of extra operators, alla matlab:

etc....

rather, it was realized that for numpy, which does element-wise operations be default, matrix multiplication was really the only non-elementwise operation widely used, so the new @ operator was added.

And we're kind of stuck --even if we added a full set, then in numpy, the regular operators would be element wise, but for built-in Python sequences, the special ones would be elementwise -- really confusing!

if you really want this, I'd make your own sequences that re-define the operators.

Or just use Numpy... you can use object arrays if you want to handle non-numeric values:

In [4]: a1 = np.array(["this", "that"], dtype=object)

In [5]: a2 = np.array(["some", "more"], dtype=object)

In [6]: a1 + a2

Out[6]: array(['thissome', 'thatmore'], dtype=object)

-CHB

Christopher Barker, Ph.D.
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