Hi, On 1 November 2011 11:26, a.lwtzky <[email protected]> wrote:
> 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) > This is correct behavior. I you want to get a minimal dtype (some sort of int) then a quick hack is to use lambdify(), e.g.: In [1]: a = Matrix([[1, 2], [3, 4]]) In [2]: f = lambdify((), a, 'numpy') In [3]: f() Out[3]: [[1 2] [3 4]] In [4]: _.dtype Out[4]: int64 f is a zero argument Python's native lambda with NumPy's data types. Downcasting should work and would be a preferred solution, but it fails due to a bug in SymPy: In [5]: import numpy as np In [6]: b = np.array(a) In [7]: b.astype(int) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) /home/mateusz/repo/git/sympy/<ipython-input-7-523ae7d433be> in <module>() ----> 1 b.astype(int) TypeError: long() argument must be a string or a number, not 'Integer' For some reason NumPy uses long() when int dtype is give and currently in SymPy: In [8]: int(Integer(10)) Out[8]: 10 In [9]: long(Integer(10)) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) /home/mateusz/repo/git/sympy/<ipython-input-9-5db2e38df86b> in <module>() ----> 1 long(Integer(10)) TypeError: long() argument must be a string or a number, not 'Integer' > 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 > > > > > -- > > > You received this message because you are subscribed to the Google > Groups > > > "sympy" group. > > > To post to this group, send email to [email protected]. > > > To unsubscribe from this group, send email to > > > [email protected]. > > > For more options, visit this group at > > >http://groups.google.com/group/sympy?hl=en. > > > > Mateusz > > -- > You received this message because you are subscribed to the Google Groups > "sympy" group. > To post to this group, send email to [email protected]. > To unsubscribe from this group, send email to > [email protected]. > For more options, visit this group at > http://groups.google.com/group/sympy?hl=en. > > Mateusz -- You received this message because you are subscribed to the Google Groups "sympy" group. 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