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added doc string
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oliverfunk committed Dec 14, 2023
1 parent 8fc8594 commit 306f309
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Showing 3 changed files with 15 additions and 3 deletions.
4 changes: 4 additions & 0 deletions bluemira/equilibria/optimisation/problem/_minimal_current.py
Original file line number Diff line number Diff line change
Expand Up @@ -51,6 +51,10 @@ class MinimalCurrentCOP(CoilsetOptimisationProblem):
Optimiser conditions
opt_algorithm:
optimiser algorithm
opt_parameters:
Optimiser specific parameters,
see https://nlopt.readthedocs.io/en/latest/NLopt_Reference/#algorithm-specific-parameters
Otherwise, the parameters can be founded by digging through the source code.

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constraints:
List of optimisation constraints to apply to the optimisation problem
"""
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7 changes: 6 additions & 1 deletion bluemira/equilibria/optimisation/problem/_nested_position.py
Original file line number Diff line number Diff line change
Expand Up @@ -83,7 +83,12 @@ class NestedCoilsetPositionCOP(CoilsetOptimisationProblem):
for defaults see
:class:`~bluemira.optimisation._algorithm.AlgorithDefaultTolerances`
along with `max_eval=100`
opt_parameters:
Optimiser specific parameters,
see https://nlopt.readthedocs.io/en/latest/NLopt_Reference/#algorithm-specific-parameters
Otherwise, the parameters can be founded by digging through the source code.
constraints:
List of optimisation constraints to apply to the optimisation problem
Notes
-----
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7 changes: 5 additions & 2 deletions bluemira/equilibria/optimisation/problem/_position.py
Original file line number Diff line number Diff line change
Expand Up @@ -70,9 +70,12 @@ class CoilsetPositionCOP(CoilsetOptimisationProblem):
for defaults see
:class:`~bluemira.optimisation._algorithm.AlgorithDefaultTolerances`
along with `max_eval=100`
opt_parameters:
Optimiser specific parameters,
see https://nlopt.readthedocs.io/en/latest/NLopt_Reference/#algorithm-specific-parameters
Otherwise, the parameters can be founded by digging through the source code.
constraints:
contraints on the problem
List of optimisation constraints to apply to the optimisation problem
Notes
-----
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