Hi, how do I go about substituting the results from functions such as
minimize_constrained back into the function that was trying to
minimize? For example, if I have
x,y = var('x y')
f = x*y(admittedly a trivial example) and I want to minimize the function over the range x in [1,10] and y in [1,10], I would use a = sage.numerical.optimize.minimize_constrained(f,[(1,10),(1,10)], (5,5)) and get back a = (1.0,1.0) If I try the command f((1.0,1.0)) I get an error and any similar attempt also gives me an error. If I had a dictionary of values for the result of minimize_constrained, I would use .substitute(). Functions like optimize.linear_program by default return a dictionary of values and functions like find_fit offer the option of returning a dictionary of values (through the solution_dict argument) but minimize_constrained doesn't seem to offer anything similar. I am dealing with functions with a nonconstant number of variables, so I can't do anything like .substitute(x=a[0]) Suggestions would be greatly appreciated, Greg --~--~---------~--~----~------------~-------~--~----~ To post to this group, send email to sage-support@googlegroups.com To unsubscribe from this group, send email to sage-support-unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/sage-support URLs: http://www.sagemath.org -~----------~----~----~----~------~----~------~--~---
