Howdy, I'm trying to track down a bug in this PR:
https://github.com/pydy/pydy/pull/122 I have quite large SymPy expressions which I evaluate with floating point numbers. I also cse those expressions and evaluate those with the same floating point numbers. I'm getting discrepancies in the results. I'd like to eliminate the possibility that the cse'd expressions are different from the original expression. I wrote this naive function to make the comparison: def compare_cse(expr): args = list(expr.free_symbols) args.remove(TIME) args += me.find_dynamicsymbols(expr) args = list(sm.ordered(args)) vals = list(np.random.random(len(args))) eval_expr = sm.lambdify(args, expr) res = eval_expr(*vals) replacements, reduced_expr = sm.cse(expr) for repl in replacements: var = repl[0] sub_expr = repl[1] eval_sub_expr = sm.lambdify(args, sub_expr) vals.append(eval_sub_expr(*vals)) args.append(var) eval_reduced_expr = sm.lambdify(args, reduced_expr[0]) cse_res = eval_reduced_expr(*vals) np.testing.assert_allclose(res, cse_res) This seems to work for small expressions, but for the large expressions run this actually kills my Python interpreter after some minutes. Is there a better way to write this? I need some way to verify that numerical evaluation of a cse'd expression gives the same result as numerical evaluation of the expression that can actually complete in a reasonable amount of time. Jason moorepants.info +01 530-601-9791 -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/CAP7f1Aivs53AcwyaoyO5%2Bzkn%2BPrX3TfoJJ5X85qQNZ6JRbo5JQ%40mail.gmail.com.
