{ "info": { "author": "Shahrouz Ryan Alimo", "author_email": "salimoha@ucsd.edu", "bugtrack_url": null, "classifiers": [], "description": "=======\npyDOGS4\n=======\nFor Imperial Collage collaborator\n\n======\npyDOGS\n======\nA derivative-free global optimization algorithm based on Delaunay triangulation designed to solve efficiently the problems whose function evaluations process is inaccurate, but its accuracy can be improved by increasing its computational cost. This package is particularly well-suited when the objective function is the infinite time-averaged value of a statistics of a stationary and ergodic process. Moreover, a new UQ method is developed to quantify the expected squared averaging error which is multiscale, meaning that it is based on an autocorrelation model that is tuned to the data to fit the statistic of interest at a large range of different timescales. In addition a transient detector scheme is developed to delete the transient part of the signal.\n\n\n======\nOutput\n======\nOptimization code generetes a file called allpoints/pts_to_eval.dat which has the format of:\nflagin=1\nIDin=3\nAwin=0.75\nlambdain=0.5\nfangle=0.5\n\nMoreover, it reads surr_J_new.dat from the current directory.\nA_w is the same parameter as the current \u2018Aw\u2019 and the two other parameters would be replaced by b_1 and b_2.\n \nThe range for these parameters would be:\nA : [0.05 ; 0.15] (\u00e0 same as current Aw)\nB_1 : [0 ; 0.2] (\u00e0 in place of lambda)\nB_2 : [0 ; 0.13] (\u00e0 in place of fangle)\n \n", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/deltadogs/pyDOGS4", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "pydogs", "package_url": "https://pypi.org/project/pydogs/", "platform": "", "project_url": "https://pypi.org/project/pydogs/", "project_urls": { "Homepage": "https://github.com/deltadogs/pyDOGS4" }, "release_url": "https://pypi.org/project/pydogs/0.1.5/", "requires_dist": null, "requires_python": "", "summary": "A Delaunay based approach of hyperparmeter optimization.", "version": "0.1.5" }, "last_serial": 4013305, "releases": { "0.1": [ { "comment_text": "", "digests": { "md5": "324ec82c3a81cfd7911cf6cedf063277", "sha256": "6300e1f025ea74b2584faead8a435f752683de6c4014f75220a8680e9b227b7d" }, "downloads": -1, "filename": "pydogs-0.1.tar.gz", "has_sig": false, "md5_digest": "324ec82c3a81cfd7911cf6cedf063277", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 14622, "upload_time": "2018-06-28T22:21:39", "url": "https://files.pythonhosted.org/packages/b0/ec/b8261d2e8129a8aeb909ef0f8afac160a2a45d952e8e14fae32954cb1da3/pydogs-0.1.tar.gz" } ], "0.1.1": [ { "comment_text": "", "digests": { "md5": "9edb42aafd4670ae730d26f062e22dda", "sha256": "2815a18d4d235a9e20a5509d3c281f3bb9657bda0d50302e3a533dee4ef20e24" }, "downloads": -1, "filename": "pydogs-0.1.1.tar.gz", "has_sig": false, "md5_digest": "9edb42aafd4670ae730d26f062e22dda", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 14642, "upload_time": "2018-06-28T22:27:44", "url": "https://files.pythonhosted.org/packages/c6/ee/de03c29d73c9d1c0596a0e0a9ec75caba9739eb8e18f8aacf76ed798a19e/pydogs-0.1.1.tar.gz" } ], "0.1.2": [ { "comment_text": "", "digests": { "md5": "6a18a09b968980d502ef14ee8e9f3fde", "sha256": "c4017d5b291afeee29cb91cf1f27469cd5ecc7b87179d26616ebce44774b1fce" }, "downloads": -1, "filename": "pydogs-0.1.2.tar.gz", "has_sig": false, "md5_digest": "6a18a09b968980d502ef14ee8e9f3fde", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 16128, "upload_time": "2018-06-28T22:49:42", "url": "https://files.pythonhosted.org/packages/1d/04/77e47058ee2c2b6204d7dd27cdf5ef804e93e408f6f12cc332b33a7fb394/pydogs-0.1.2.tar.gz" } ], "0.1.3": [ { "comment_text": "", "digests": { "md5": "334af71dff9dba7289180e2746dd2bec", "sha256": "4299f4c5d840f842a7bad161646f2f40b2ca255c3ba0b7d469a291882a4e721e" }, "downloads": -1, "filename": "pydogs-0.1.3.tar.gz", "has_sig": false, "md5_digest": "334af71dff9dba7289180e2746dd2bec", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 16181, "upload_time": "2018-06-28T22:53:17", "url": "https://files.pythonhosted.org/packages/e5/30/13f54f9240e60c86d0d0b45751b11d3c58d19ab43253df4d32bd121abe8f/pydogs-0.1.3.tar.gz" } ], "0.1.4": [ { "comment_text": "", "digests": { "md5": "149729a8d892796c747ec34833fe14cd", "sha256": "115004fb6dcac3593ff029f79e652c6619e46cc4d43395b89a761c7f24fc8c56" }, "downloads": -1, "filename": "pydogs-0.1.4.tar.gz", "has_sig": false, "md5_digest": "149729a8d892796c747ec34833fe14cd", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 24673, "upload_time": "2018-06-28T23:15:59", "url": "https://files.pythonhosted.org/packages/45/66/212f117de5c7ff822ba3d8e654c5a859e5f321b30e7fab15a64e2b8eb185/pydogs-0.1.4.tar.gz" } ], "0.1.5": [ { "comment_text": "", "digests": { "md5": "cbc71b901bd0d41c4f9541d4cd27ccb2", "sha256": "33235465e4cc1220bd8ba229309b32040369fab0fa5f4e1f45f01508fe8fc0c9" }, "downloads": -1, "filename": "pydogs-0.1.5.tar.gz", "has_sig": false, "md5_digest": "cbc71b901bd0d41c4f9541d4cd27ccb2", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 24676, "upload_time": "2018-06-28T23:29:53", "url": "https://files.pythonhosted.org/packages/89/41/42c71165117e5e9972f11b6d04deec6541f1f2afacc098b2383f728ac739/pydogs-0.1.5.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "cbc71b901bd0d41c4f9541d4cd27ccb2", "sha256": "33235465e4cc1220bd8ba229309b32040369fab0fa5f4e1f45f01508fe8fc0c9" }, "downloads": -1, "filename": "pydogs-0.1.5.tar.gz", "has_sig": false, "md5_digest": "cbc71b901bd0d41c4f9541d4cd27ccb2", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 24676, "upload_time": "2018-06-28T23:29:53", "url": "https://files.pythonhosted.org/packages/89/41/42c71165117e5e9972f11b6d04deec6541f1f2afacc098b2383f728ac739/pydogs-0.1.5.tar.gz" } ] }