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simple numerical solve (2-variables!!)

asked 2012-09-17 00:01:13 -0500

mattias gravatar image

updated 2012-09-20 01:54:48 -0500


Thanks for the help, I'm trying to move from Mathematica to Sage, but I'm still having some trouble with the basics. Specifically, I'm moving from 1-var to 2-var numerical optimization/solver. I want to optimize function g or, equivalently, solve the system of first-order conditions, f. So far, I have not been able to get any of the scipy routines to work. Is there a simple way to do this? (Note: the objective function is concave wrt to both arguments.)

Thanks! jv


y_a = 50 y_b = 50 x = 40 alpha_a = .2 alpha_b = .2


v(n)= n^.5 v1(n) = derivative(v(n),n) u(n)= n^.5 u1(n) = derivative(u(n),n)


var('g_a') var('x_a')

Optimization (over [0, x])

g = (v(g_a+alpha_b(x-g_a))-u(y_a)+u(y_a-x_a))(v(x-g_a+alpha_a*(g_a))-u(y_b)+u(y_b-(x-x_a)))

f1 = ((1-alpha_b)v1(g_a+alpha_b(x - g_a)))/((1-alpha_a)v1(x-g_a+alpha_a(g_a)))==(v(g_a+alpha_b(x-g_a))-u(y_a)+u(y_a-x_a))/(v(x-g_a+alpha_a(g_a))-u(y_b)+u(y_b-(x-x_a)))

f2 = (u1(x_a)/u1(x-x_a)) == (v(g_a+alpha_b(x-g_a))-u(y_a)+u(y_a-x_a))/(v(x-g_a+alpha_a(g_a))-u(y_b)+u(y_b-(x-x_a)))

f(g_a, x_a) = (f1, f2)

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Did you completely change your question? If you have another question to ask, please revert this one to its first version and ask your second question as a separate topic.

niles gravatar imageniles ( 2012-09-20 02:43:00 -0500 )edit

Hi mattias. If you restore the first question and ask the second as a separate one I can show how to obtain (20,20) as the answer

achrzesz gravatar imageachrzesz ( 2012-09-20 07:56:07 -0500 )edit

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answered 2012-09-17 00:52:12 -0500

achrzesz gravatar image

updated 2012-09-17 05:46:54 -0500

eq=g_a == -31375155/31496372*sqrt(-4/5*g_a + 1) + 31375155/31496372*sqrt(4/5*g_a + 8) - 35/8
[g_a == (-35/8)]
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answered 2012-09-17 03:01:35 -0500

niles gravatar image

updated 2012-09-17 03:05:48 -0500

What function are you using to do this? simplify? Showing us a minimal example might be helpful.

If you're not using it already, I recommend find_root for numerical solutions to 1-variable equations.

As far as I can tell, Maxima is used primarily for symbolic manipulations in Sage, and other things are used for numerical optimization. So if you're using a function that uses Maxima, you might only get symbolic output.

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Thanks, this is exactly what I was looking for. I was using solve with a rather messy function. After a bit of troubleshooting I was able to get find_root to work for me.

mattias gravatar imagemattias ( 2012-09-17 05:57:16 -0500 )edit

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Asked: 2012-09-17 00:01:13 -0500

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Last updated: Sep 20 '12