Following up on yesterday's Domain Specific Languages (DSL) for Convex Optimization here is CVXPY, an effort to implement it in Python. From the page:
CVXPY is a Python-embedded modeling language for convex optimization problems. It allows you to express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers.
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CVXPY is a Python-embedded modeling language for convex optimization problems. It allows you to express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers.
CVXPY was designed and implemented by Steven Diamond, with input from Stephen Boyd and Eric Chu.
CVXPY was inspired by the MATLAB package CVX. See the book Convex Optimization by Boyd and Vandenberghe for general background on convex optimization.
CVXPY relies on the open source solvers ECOS, CVXOPT, and SCS.
The CVXPY documentation is at cvxpy.org. The attendant Github is here. From Yesterday's entry:
Steven Diamond also wrote http://dcp.stanford.edu/ to teach disciplined convex programming
Credit: Copyright ESA/Rosetta/NAVCAM
Description Four-image mosaic comprising images taken by Rosetta's navigation camera from a distance of 9.8 km from the centre of comet 67P/C-G – about 7.8 km from the surface. The corresponding image scale is about 66 cm/pixel, and the mosaic covers roughly 1200 x 1350 metres.The individual image frames and more information is available via the blog: CometWatch – 26 October
Description Four-image mosaic comprising images taken by Rosetta's navigation camera from a distance of 9.8 km from the centre of comet 67P/C-G – about 7.8 km from the surface. The corresponding image scale is about 66 cm/pixel, and the mosaic covers roughly 1200 x 1350 metres.The individual image frames and more information is available via the blog: CometWatch – 26 October
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