[SciPy-user] questions about solving equations in scipy
fdu.xiaojf@gmai...
fdu.xiaojf@gmai...
Wed Jun 13 02:37:04 CDT 2007
Hi all,
I have posted this to python-list, and some people kindly pointed that here is
a better place for scipy related questions.
I have two questions about scipy.
1) When I was trying to solve a single variable equations using scipy, I
found two methods: scipy.optimize.fsolve,and scipy.optimize.newton.
I have tried both, and it seemed that both worked well, and fsolve ran
faster.
My questions is, which is the right choose ?
And I also found that there are models and functions in both scipy and numpy,
such as scipy.linalg.solve() and numpy.linalg.solve(), and both can solve a
linear equation. Are they the same in the ground?
2) I have to solve a linear equation, with the constraint that all
variables should be positive. Currently I can solve this problem by
manually adjusting the solution in each iteration after get the solution
bu using scipy.linalg.solve().
I found a web page about optimization solver in
openoffice(http://wiki.services.openoffice.org/wiki/Optimization_Solver#Non-Linear_Programming).
Openoffice has an option of "Allow only positive values", so I think that
may be a well-defined problem. Sorry for my ignorance if I was wrong.
Is there a smart way in python?
Thanks in advance.
Xiao Jianfeng
More information about the SciPy-user
mailing list