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int | iteration (self) |
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Annotated[ArrayLike, dict(dtype='float64', shape=(None), order='C')] | x (self) |
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scipy.sparse.csc_matrix[float] | g (self) |
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scipy.sparse.csc_matrix[float] | H (self) |
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scipy.sparse.csc_matrix[float] | A_e (self) |
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scipy.sparse.csc_matrix[float] | A_i (self) |
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Solver iteration information exposed to a user callback.
◆ A_e()
scipy.sparse.csc_matrix[float] jormungandr.optimization.SolverIterationInfo.A_e |
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self | ) |
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The equality constraint Jacobian.
◆ A_i()
scipy.sparse.csc_matrix[float] jormungandr.optimization.SolverIterationInfo.A_i |
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self | ) |
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The inequality constraint Jacobian.
◆ g()
scipy.sparse.csc_matrix[float] jormungandr.optimization.SolverIterationInfo.g |
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self | ) |
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The gradient of the cost function.
◆ H()
scipy.sparse.csc_matrix[float] jormungandr.optimization.SolverIterationInfo.H |
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self | ) |
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The Hessian of the Lagrangian.
◆ iteration()
int jormungandr.optimization.SolverIterationInfo.iteration |
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◆ x()
Annotated[ArrayLike, dict(dtype='float64', shape=(None), order='C')] jormungandr.optimization.SolverIterationInfo.x |
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self | ) |
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The documentation for this class was generated from the following file: