paveltrutman / polyopt Goto Github PK

Hi,

first of all, thanks for this package, it is really what I was looking for!
I'm trying to use it to optimize a simple 1d polynomial, with no constraints, but I'm getting this error:

Traceback (most recent call last):
  File "/home/student/repos/polyopt/demoPOPSolver.py", line 27, in <module>
    POP = polyopt.POPSolver(f, g, d)
  File "/home/student/repos/polyopt/polyopt/POPSolver.py", line 37, in __init__
    if max(gDegsHalf) > d:
ValueError: max() arg is an empty sequence

I guess the solver is not done for the unconstrained case. I was able to get around this by adding a dummy constraint (x+100>=0). Here is the code I'm running now:

f = {(0,): 5, (1,): -2, (2,): 1}
g = [{(0,): 1e2, (1,): 1,}] # constraint function x + 1e2 >=0
d = 2
POP = polyopt.POPSolver(f, g, d)
y0 = POP.getFeasiblePoint([array([[1]]), array([[2]]), array([[-1]]), array([[-2]])])
POP.setPrintOutput(False)
x = POP.solve(y0)

However, I still get an error:

    x = POP.solve(y0) #solve the problem
  File "/home/student/repos/polyopt/polyopt/POPSolver.py", line 80, in solve
    y = self.SDP.solve(startPoint, self.SDP.dampedNewton)
  File "/home/student/repos/polyopt/polyopt/SDPSolver.py", line 188, in solve
    x0 = method(start)
  File "/home/student/repos/polyopt/polyopt/SDPSolver.py", line 314, in dampedNewton
    FdLN = Utils.LocalNormA(Fd, Fdd)
  File "/home/student/repos/polyopt/polyopt/utils.py", line 29, in LocalNormA
    return sqrt(dot((solve(hessian, u)).T, u))[0,0]
  File "<__array_function__ internals>", line 6, in solve
  File "/home/student/.local/lib/python3.5/site-packages/numpy/linalg/linalg.py", line 399, in solve
    r = gufunc(a, b, signature=signature, extobj=extobj)
  File "/home/student/.local/lib/python3.5/site-packages/numpy/linalg/linalg.py", line 97, in _raise_linalgerror_singular
    raise LinAlgError("Singular matrix")
numpy.linalg.LinAlgError: Singular matrix

This time I'm not sure what the problem is. Any suggestion?
Moreover, would it be simple to modify the code to handle unconstrained minimization?

Hi,

All over your code, you cite 'Nesterov', with pages numbers. Could you provide the full reference to this book ? I have troubles matching the pages numbers, since there might have been a re-edition, so if you provide the full reference you used it would be great 👍

Nice code btw.

Hi, I've successfully installed the package polyopt according to the instruction on your webpage. But when I enter Python and import polyopt, I got the following error message:

import polyopt
Traceback (most recent call last):
File "", line 1, in
File "C:\Users\tong.chen\polyopt\polyopt_init_.py", line 3, in
from .SDPSolver import SDPSolver
File "C:\Users\tong.chen\polyopt\polyopt\SDPSolver.py", line 6, in
import gnuplot as gp
File "C:\Users\tong.chen\AppData\Local\Continuum\anaconda3\lib\site-packages\gnuplot_init_.py", line 164, in
from gnuplot.gp import GnuplotOpts, GnuplotProcess, test_persist
File "C:\Users\tong.chen\AppData\Local\Continuum\anaconda3\lib\site-packages\gnuplot\gp.py", line 31, in
from gnuplot.gp_win32 import GnuplotOpts, GnuplotProcess, test_persist
File "C:\Users\tong.chen\AppData\Local\Continuum\anaconda3\lib\site-packages\gnuplot\gp_win32.py", line 12, in
import Errors
ModuleNotFoundError: No module named 'Errors'

Could someone help me fix this issue please?

Thanks in advance!

Hi,

I do want to solve the SDP problem from example (4.1) in this paper. This problem seem quite easy to solve, but i do not manage to make it work using polyopt.

Could you explain to me how i should translate it's expression to the polyopt SDPsolver ? It keep running until values goes +/- np.inf and LocalNormA returns an error.