Hi Mateusz,
True, but the dtype of this numpy array is object, which is unsuitable
e.g. for numerical ODE solver.
Try:
In [1] : a = Matrix([[1, 2], [3, 4]])
In [2]: type(a.tolist()[0][0])
Out[13]: <class 'sympy.core.numbers.One'>
same with the numpy array:
array([[1, 2],
[3, 4]], dtype=object)
I've got the pypy version of sympy which is 0.7.1. Has the behavior
anything changed here?
Thanks for your help anyway,
Andy
On 1 Nov., 18:10, Mateusz Paprocki <[email protected]> wrote:
> Hi,
>
> On 1 November 2011 09:36, a.lwtzky <[email protected]> wrote:
>
>
>
>
>
>
>
>
>
> > Dear everyone,
>
> > I was wondering if there is a function in sympy that converts a
> > sympy.Matrix to a list of lists of python standard types. For example
> > if you have
> > >>> m = matrices.Matrix([[2,0],[0,2]])
>
> > it would be nice to have a function <f> that returns:
> > >>> res = <f>(m)
> > [[2,0],[0,2]]
> > >>> type(res)
> > list
> > >>> type(res[0][0])
> > int # or float or whatever seems appropriate.
>
> > as an alternative: return a 2D numpy array of integers/floats... But
> > this brings probably unnecessary dependencies to numpy. And if the
> > user really wants to have a numpy.array, he/she could just use
> > np.asarray(res).
>
> You can create an array from a matrix and convert a matrix to a list of
> lists, e.g.:
>
> In [1]: import numpy as np
>
> In [2]: a = Matrix([[1, 2], [3, 4]])
>
> In [3]: a
> Out[3]:
> ⎡1 2⎤
> ⎢ ⎥
> ⎣3 4⎦
>
> In [4]: a.tolist()
> Out[4]: [[1, 2], [3, 4]]
>
> In [5]: np.array(a)
> Out[5]:
> [[1 2]
> [3 4]]
>
> This is for git version of SymPy, but should work for older versions too.
>
>
>
>
>
>
>
>
>
>
>
> > I spent a couple of hours in order to find a (simple) solution for
> > this.
> > A similar idea was presented here:
>
> >http://weekinpse.wordpress.com/2010/01/06/how-to-convert-a-sympy-matr...
> > This subject has already been discussed in sympy IRC channel with
> > ronan (thanks again).
>
> > -> Motivation - Use case
> > I would like to use numpy and sympy in the same project. Use sympy to
> > solve a ODE system symbolically, get its jacobian, the jacobian's
> > eigenvectors at a critical point and so on. Then use this information
> > to plot it (with matplotlib) together with other functions, further
> > investigate it's properties (for example integrate it numerically with
> > numpy - plot the trajectories) and so on.
>
> > -> suggestions
> > It doesn't seem to be too bad implementing something like this. The
> > solution of hdahlol can be found at the link (see above).
> > ronan thought about something like:
> > def <f>(m):
> > arr = np.asarray(map(int, m.mat)) # or float...
> > arr.shape = m.shape
> > return arr
>
> > But both of us agreed that using m.mat is pretty ugly at this point.
> > And it does explicitly take use of numpy. Of course there is a way to
> > copy value by value - but this might result in terribly slow code
> > without benefit.
>
> > In case a value can't be converted to standard types (for example a
> > variable x) the function could just throw an exception or leave the
> > sympy.object in the list and let the user care about this case.
>
> > I would really appreciate help in this question.
>
> > Thanks, Andy
>
> > --
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>
> Mateusz
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