fr., 03.09.2010 kl. 11.27 +0530, skrev Rahul Siddharthan:
> Aaron, Chris,
> Thanks for the replies!
>
> Aaron wrote:
> > This is great. SymPy code is *MUCH* easier to read than some lisp, in my
> > opinion.
>
> So far, yes and no. The main thing is that I needed to implement
> structured "tuples" as defined in SICM, and functions that take tuples
> as arguments, and derivatives/partial derivatives of those functions.
> I defined my own class for those things, but with higher-order
> functions (functions that return functions, which is done all the time
> in SICM) it gets a bit inelegant. Still, I think most of the
> infrastructure is done: I will put up what I have, and ask about
> prettyfication, shortly.
>
> Chris wrote:
>
> > what you could try doing is "masking" the derivatives--replace them
> > with symbols of your own
>
> That's exactly what I ended up doing, but in a much more longwinded
> way than what you wrote.
>
> The other issue that came up is, I see from the archives, again a
> known problem: if I want to define multiplication for "tuples", a
> multiplication of a tuple by a scalar (on the left or the right) is
> the tuple of each component multiplied by the scalar. I define the
> __mul__ and __rmul__ methods, but __rmul__ fails to get called when
> the scalar is a sympy object, because scalar defines a __mul__ that
> can handle other sympy objects and I get, eg,
> r * (1,2)
> instead of
> (r, 2*r)
> (I am using the Basic class for my tuples). If I don't know that r is
> a scalar, of course, the first answer is right and the second need not
> be right. But even when r is a sympified number, it fails to expand:
>
> a = up(1,2) # (up and down are tuple-generating functions in my library)
> b = 3
> b*a
> (output)=> (3, 6) (desired answer)
> b = sympify(3)
> b*a
> (output)=> 3⋅(1, 2) (not the desired answer!)
>
> I am currently using the workaround of unsympifying all numbers...
In the current master branch you can use the _op_priority class
attribute to make sure your own __mul__() overrides the default. You
could do it like this:
from sympy.core.containers import Tuple
from sympy.core.expr import Expr
class ET(Tuple, Expr):
_op_priority = 20
def __mul__(self, other):
other = sympify(other)
if other.is_Atom:
return ET(*[a*other for a in self.args])
def __rmul__(self, other):
other = sympify(other)
if other.is_Atom:
return ET(*[other*a for a in self.args])
Using this class in isympy, I get:
In [1]: t = ET(x,y,z)
In [2]: x*t
Out[2]: ET(x**2, x*y, x*z)
In [3]: t*x
Out[3]: ET(x**2, x*y, x*z)
Øyvind
>
> Rahul
>
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