On Thu, Feb 17, 2011 at 8:35 AM, Chris Smith <[email protected]> wrote:
> Ronan Lamy wrote:
>> Le mercredi 16 février 2011 à 22:24 -0800, Ondrej Certik a écrit :
>>> 2) NumPy array()
>>>
>>> So that you can use syntax like:
>>>
>>> xdata = array([1, 2, 3, 4, 5])
>>> ydata = xdata ** 2
>>> data2 = array([xdata, 1.5 * ydata])
>>>
>>> which just works in Mathematica (it's in the core language).
>>>
>>
>> I don't really see the point of having this in sympy. Which actual
>> problems does it solve?
>
> It's just sugar, and I think that's what is meant by "it just works". I'm
> guessing the above means the following in python:
>
> ydata = [xi**2 for xi in xdata]
> data2 = zip(xdata, [yi*1.5 for yi in ydata])
Well, this is what it means:
In [1]: from numpy import array
In [2]: xdata = array([1, 2, 3, 4, 5])
In [3]: ydata = xdata ** 2
In [4]: data2 = array([xdata, 1.5 * ydata])
In [5]: data2
Out[5]:
array([[ 1. , 2. , 3. , 4. , 5. ],
[ 1.5, 6. , 13.5, 24. , 37.5]])
Btw, we already have a similar concept in SymPy: Matrix. But it
represents a math matrix and that's it. I think we need an array
concept as well.
Ronan --- the actual problem that it solves is that in Mathematica,
people do use the syntactic sugar for arrays. So I would like to use
the same thing in SymPy. Which I can, using numpy, but as I said,
sometimes numpy is not available, and I want this to always work.
Ondrej
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