Cvxpy

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Join the conversation! It lets you express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers. In addition to convex programming, CVXPY also supports a generalization of geometric programming, mixed-integer convex programs, and quasiconvex programs. For applications to machine learning, control, finance, and more, browse the library of examples. For background on convex optimization, see the book Convex Optimization by Boyd and Vandenberghe. Additional solvers are supported, but must be installed separately.

Cvxpy

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Here are some cvxpy ways to start contributing immediately:. We appreciate all contributions. We welcome you to join us!

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It automatically transforms the problem into standard form, calls a solver, and unpacks the results. The optimal value basically 1 here is the minimum value of the objective over all choices of variables that satisfy the constraints. The last thing printed gives values of x and y basically 1 and 0 respectively that achieve the optimal objective. Problems are immutable, meaning they cannot be changed after they are created. To change the objective or constraints, create a new problem. The value fields of the problem variables are not updated.

Cvxpy

Join the conversation! It lets you express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers. In addition to convex programming, CVXPY also supports a generalization of geometric programming, mixed-integer convex programs, and quasiconvex programs. For applications to machine learning, control, finance, and more, browse the library of examples. For background on convex optimization, see the book Convex Optimization by Boyd and Vandenberghe.

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Report repository. Custom properties. Dismiss alert. It is now developed by many people, across many institutions and countries. The CVXPY community consists of researchers, data scientists, software engineers, and students from all over the world. Version selector. Latest commit. For issues and long-form discussions, use Github Issues and Github Discussions. To get involved, see our contributing guide and join us on Discord. Please be respectful in your communications with the CVXPY community, and make sure to abide by our code of conduct. Getting started.

Join the conversation!

Report repository. Last commit date. Skip to content. Read more about the new backends here: Canonicalization backends. It lets you express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers. For more information about the team and our processes, see our governance document. Latest commit History 3, Commits. Latest commit. We welcome you to join us! For background on convex optimization, see the book Convex Optimization by Boyd and Vandenberghe. Custom properties. Jan 19, CVXPY is not a solver.