Thanks for your help Felix, with your ideas i made progresses. But the
problem isn't fixe yet. Since i have some symbolic variable such 'dx'
in my expressions, the
code's line --> 500 return eval(string, {'I': numpy.complex(0,1)})
generate this folowing error
NameError: name 'dx' is not defined
Even when i put in the begining of my function var ("dx"), the problem
stay.
Thanks again
On 14 août, 04:04, thelamecamel <thelameca...@gmail.com> wrote:
> Hi Viny,
>
> Sage's mathematica support at present seems to be geared towards
> sending data to mathematica and printing the results to the screen,
> rather than getting mathematica's results back into sage for data
> manipulation. So the going may be a little rough.
>
> Sage can convert its own arrays into mathematica's notation, e.g.
> Jason's example
> sage: b=mathematica([1,2,3])
> will create a mathematica variable representing the array {1,2,3},
> accessible from sage. I'm not sure whether you can send mathematica
> more complicated things such as functions in this fashion.
>
> Once you've got your variables into mathematica, you perform
> mathematica functions on them like so:
> sage: x = mathematica(1)
> sage: mathematica.eval('myfunc[x_,y_]:=x+y')
> sage: x.myfunc(2)
> 3
>
> It's hard to get your mathematica results back into sage for use. As
> Jason noted below, mathematica arrays with {} don't get converted back
> into sage arrays with []. There is a ticket related to the array
> problem <http://trac.sagemath.org/sage_trac/ticket/4948>, but there
> seems to be no progress on it.
>
> I gave up and rolled my own mathematica list to numpy array conversion
> - you might find it useful. I believe that using eval() is frowned
> upon for security reasons. If you want sage arrays rather than numpy
> arrays, then use sage_eval() (which is considerably slower for large
> arrays) and strip out the numpy stuff. Comments on the below code are
> welcome.
>
> import numpy
> import re
> def mma_to_numpy(mma_arr):
> """Convert mathematica array to numpy array."""
> # Convert the mathematica object to a string
> string = repr(mma_arr)
> # Convert mathematica-style {} to python style []
> string = string.replace('{','[').replace('}',']')
> # Replace mathematica's crazy exponent notation with the standard
> one
> string = string.replace('*^', 'e')
> # Delete new lines (both \n and \r\n appear sporadically)
> string = string.replace('\n', ' ').replace('\r', ' ')
> # Detect characters that should not be in an array
> if re.findall(r'[a-df-zA-HJ-Z]+', string) != []:
> raise TypeError, "Mathematica returns non-array: %s" % string
> # Read the string into numpy, interpreting I as j
> return eval(string, {'I': numpy.complex(0,1)})
>
> You use it as such:
> sage: b = mathematica([1.5,2.+3.j,3])
> sage: b
> {1.5, 2. + 3.*I, 3}
> sage: numpy.array(mma_to_numpy(b), dtype='D')
> array([ 1.5+0.j, 2.0+3.j, 3.0+0.j])
>
> Hope that this helps - there isn't much documentation on this stuff.
>
> Cheers,
> Felix
>
> On Aug 13, 8:26 pm, Viny <hje...@hotmail.com> wrote:
>
> > On 13 août, 10:47, Viny <hje...@hotmail.com> wrote:
>
> > > Hi,
>
> > > I have a problem of memory into maxima when it performs a symbolic
> > > expression of an hessian matrix. This symbolic expression of the
> > > hessian seems to be too big. My sage program is written using python.
> > > And i want to compute the hessian matrix with mathematica 6.0 in my
> > > sage file.
> > > I need to compute symbolic expresstion of the gradient and the hessian
> > > with mathematica and after compute the mathématica LinearSolve
> > > function to solve hessian^-1*grad.
> > > How to make this interface in my .sage?
> > > Please help me!!!
>
> > > I have mathematica 6.0 and sage4.0.2 in my linux 64bit system.
>
> > This is an example of the function to compute the gradient in
> > my .sage, but it doesn't work.
> > def grad(f,v):
> > return mathematica ( f ).D( [ ' v ',1] )
> > The result is {0,0} . I have another problem of format, i don't know
> > the command to change { } in () in the mathematica result {0,0}
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