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taming main runs on ci/cd server #65

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taming main runs on ci/cd server #65

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1d746ca
taming main runs on ci/cd server
Jan 10, 2024
22254ae
use get_solver to avoid the selection of mosek in ci/cd
Jan 10, 2024
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3 changes: 2 additions & 1 deletion experiments.py
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Expand Up @@ -28,4 +28,5 @@
# Hence we do not perform them on a GitHub CI server
scaling_large_main(fitting=True)
scaling_large_main(fitting=False)
taming_main()

taming_main()
3 changes: 2 additions & 1 deletion experiments/markowitz.py
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Expand Up @@ -15,6 +15,7 @@

import cvxpy as cp
import numpy as np
from utils import get_solver


@dataclass
Expand Down Expand Up @@ -110,7 +111,7 @@ def markowitz(data: Data, param: Parameters) -> tuple[np.ndarray, float, cp.Prob
]

problem = cp.Problem(cp.Maximize(objective), constraints)
problem.solve()
problem.solve(solver=get_solver())
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The idea was to keep this function 1:1 in sync with the paper. I'd rather not install mosek on CI...

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problem.solve(solver=get_solver())
problem.solve()

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Yes, I don't want to install Mosek on CI/CD but I would prefer to have this function also able to run this during a test or for people without a license

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One of the points we make in the paper is that the solve method works without arguments. I think specifying one here defeats that point a bit (the only reason why we do specify one at all is to ensure replicability). How about this:
I'll update the README and requirements to make the distinction between exact replication (requires mosek license) and qualitative replication (no license required)?

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The problem is that the hard dependency on mosek would install it for everybody. Maybe let's add a link to a page where people could download a 30 day license. Not testing code is a sin I could live with

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Please assume that the average user has no Mosek license at hand. He will download and run this package and end up with an error message that no license is found. He/she will then argue that this is our fault and whether we can provide the missing license file :-)

assert problem.status in {cp.OPTIMAL, cp.OPTIMAL_INACCURATE}, problem.status
return w.value, c.value, problem

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