I have a function of a few variables that is the result of some
symbolic manipulations like differentiation and matrix operations. I
would like to do some Monte Carlo work on this to get the distribution
of the function result as a function of the distributions of the
inputs. However, the subs method (like /. in Mathematica) is much to
slow. Is there an elegant solution for that?
What came to my mind is writing the result to a file and then
importing that like for a more trivial case:
X, F, B = sympy.symbols('XFB')
Y = X/F - B
f = open('sympy_function.py' ,'w')
f.write('def fsympy(X,F,B):\n')
f.write(' return %s\n' % Y)
f.close()
from sympy_function import *
With numerical values for x, f and b:
y = fsympy(x, f, b) is 300 times faster than y = Y.subs({X:x, F:f,
B:b}) and only 10% slower than straightaway y = x/f -b
So that works but I do not consider it elegant. Something better?
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