Here's a short comment: using Idx(n+1) seems to work a little better
for me, since I've noticed that if I use Idx(n) with a very
complicated expression, there is a possibility of terms with (n+1)
indices ending up on the same side as the (n) indices.
That sounds like a bug. Can you give a specific example of an
expression that does that?
Aaron Meurer
Sure, I can attempt to give an example. I've been unable to reproduce
this behavior with a simple expression, so I am pasting below the full
expression that I've been using. Of course, it may be something that
I'm doing wrong, so I'm reluctant to cry wolf. But in a similar
fashion to working with a building, if the pipes are a bit leaky,
perhaps a small patch job would be beneficial if warranted.
Okay, here is a test program with a much simpler expression. The output
of the program shows what I suspect to be right and wrong behavior. The
questioned behavior seems to occur when two indexed terms are multiplied
together:
This appears to be wrong:
(p[1, 2, 1 + n], -p[1, 2, n] + p[2, 2, n]*p[1, 2, 1 + n])
This appears to be right:
(-p[1, 2, n], p[2, 2, n]*p[1, 2, 1 + n] + p[1, 2, 1 + n])
Nicholas
#begin sample code
from sympy import *
from sympy.tensor import Indexed, Idx, IndexedBase
from sympy.matrices import *
p = IndexedBase('p')
var('deltax deltay delta deltat A B')
i,j,n = symbols('i j n', integer = True)
def test_as_independent(expr):
expr0 = expr.lhs - expr.rhs
expr1 = expr0.as_independent(*filter(lambda t: t.args[-1] ==
Idx(n), expr0.atoms(Indexed) ) )
print 'This appears to be wrong: '
print expr1
print 'This appears to be right: '
expr2 = expr0.as_independent(*filter(lambda t: t.args[-1] ==
Idx(n+1), expr0.atoms(Indexed) ) )
print expr2
def run_scheme():
expr1 = Eq( p[1,2,n+1] + p[2,2,n]*p[1,2,n+1], p[1,2,n])
test_as_independent(expr1)
def main():
run_scheme()
if __name__ == "__main__":
main()
# end sample code
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