{"library":"pylbfgs","title":"PyLBFGS","description":"PyLBFGS provides L-BFGS and OWL-QN optimization algorithms for large-scale unconstrained and bound-constrained optimization. Current version is 0.2.0.16, but development appears to be in maintenance mode with infrequent releases.","language":"python","status":"maintenance","last_verified":"Fri May 01","install":{"commands":["pip install pylbfgs"],"cli":null},"imports":["from pylbfgs import LBFGS","from pylbfgs import owl_qn"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"import numpy as np\nfrom pylbfgs import LBFGS\n\ndef evaluate(x, g):\n    # f(x) = (x-2)^2, gradient = 2*(x-2)\n    f = np.sum((x - 2.0) ** 2)\n    g[:] = 2.0 * (x - 2.0)\n    return f\n\nx0 = np.array([0.0, 0.0])\noptimizer = LBFGS()\nresult = optimizer.minimize(evaluate, x0)\nprint(\"Optimal x:\", result)\n","lang":"python","description":"Minimize a simple quadratic function using L-BFGS.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}