{
    "info": {
        "author": "Felipe Souza Lima",
        "author_email": "felipe.lima@eq.ufcg.edu.br",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: Apache Software License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering"
        ],
        "description": "# Description\n\nThis project is an adaptation from the work of Hans Bruun Nielsen, S\u00c3\u00b8ren Nymand and Lophaven Jacob S\u00c3\u00b8ndergaard.\n\n## Notes\n**This is a implementation that relies heavily on linear algebra solvers** (least-squares solvers, Cholesky and QR \ndecompositions, etc.). Therefore, it is strongly advised that your numpy library be integrated to a \n[BLAS library](http://markus-beuckelmann.de/blog/boosting-numpy-blas.html) (e.g.: Intel-MKL, OpenBLAS, ATLAS, etc.) \nin order to attain satisfactory performances of calculation.\n\nFor the sake of convenience, Anaconda handles the gritty details of how to combine numpy and those libraries natively.\n\n## Installation\n\nTo install through PyPi Repository:\n\n    pip install pydace\n\nTo install via conda\n\n    conda install -c felipes21 pydace\n\n## Usage\n\n### Example with dace model\n\n```python    \n    import numpy as np\n    import scipy.io as sio\n    from pydace import Dace\n    import matplotlib.pyplot as plt\n\n    # Load the training and validation data. (Here we are using a file from the\n    # github repo located in the folder pydace\\tests with the name \n    # 'doe_final_infill_mat'\n\n    mat_contents = sio.loadmat('doe_final_infill.mat')\n\n    design_data = mat_contents['MV']  # design sites\n    observed_data = mat_contents['CV']  # experiment results\n\n    # define the hyperparameters bounds and initial estimate\n    theta0 = 1 * np.ones((design_data.shape[1],))\n    lob = 1e-5 * np.ones(theta0.shape)\n    upb = 1e5 * np.ones(theta0.shape)\n\n    # select the training and validation data\n    design_val = design_data[:99, :]\n    observed_val = observed_data[:99, :]\n\n    design_train = design_data[100:, :]\n    observed_train = observed_data[100:, :]\n\n    # build the univariate kriging models with a first order polynomial \n    # regression and a gaussian regression model\n    observed_prediction = np.empty(observed_val.shape)\n    for j in np.arange(design_data.shape[1]):\n        # initialize the dace object\n        dace_obj = Dace('poly1', 'corrgauss', optimizer='boxmin')\n\n        # fit the training data using the default hyperparameter optimizer\n        dace_obj.fit(design_train, observed_train[:, j], theta0, lob, upb)\n\n        # predict the validation data\n        observed_prediction[:, [j]], *_ = dace_obj.predict(design_val)\n\n    # labels for the observed data\n    var_labels = ['L/F', 'V/F', 'xD', 'xB', 'J', 'QR'] \n\n    # plot the validation data\n    for var in np.arange(design_data.shape[1]):\n        plt.figure(var + 1)\n        plt.plot(observed_val[:, var], observed_prediction[:,var], 'b+')\n        plt.xlabel(var_labels[var] + ' - Observed')\n        plt.ylabel(var_labels[var] + ' - Kriging Prediction')\n\n    plt.show()\n```\n\n### Example of design of experiment data generation\nIt is also possible to generate design of experiment data with a variation reduction technique called Latin Hypercube\nSampling (LHS) that is already implemented in this toolbox.\n\nLets say we have a 4-th dimensional problem (i.e. 4 design/input variables). They are defined by the following bounds.\n\n![Variables to sample](lhsvariables.png)\n\nIf we want to build a latin hypercube within these bounds we would do the following:\n\n```python    \n    import numpy as np\n    from pydace.aux_functions import lhsdesign\n\n    lb = np.array([8.5, 0., 102., 0.])\n    ub = np.array([20., 100., 400., 400.])\n\n    lhs = lhsdesign(53, lb, ub, include_vertices=False)\n```\n\n## Contact/Talk to me\n\nMy e-email is felipe.lima@eq.ufcg.edu.br. Feel free to contact me anytime, or just nag me if I'm being lazy.\n\n\n",
        "description_content_type": "text/markdown",
        "docs_url": null,
        "download_url": "",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "https://github.com/feslima/pydace",
        "keywords": "surrogate,metamodel",
        "license": "Apache License 2.0",
        "maintainer": "",
        "maintainer_email": "",
        "name": "pydace",
        "package_url": "https://pypi.org/project/pydace/",
        "platform": "",
        "project_url": "https://pypi.org/project/pydace/",
        "project_urls": {
            "Homepage": "https://github.com/feslima/pydace"
        },
        "release_url": "https://pypi.org/project/pydace/0.1.1/",
        "requires_dist": [
            "scipy (>=1.2.0)",
            "pyDOE2"
        ],
        "requires_python": ">=3.5",
        "summary": "Design and Analysis of Computational Experiments as python toolbox.",
        "version": "0.1.1"
    },
    "last_serial": 5907872,
    "releases": {
        "0.0.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "ab4525c39f6f62f3b77b93a5b1020a58",
                    "sha256": "e8622cef06e03b55406d6f793c1249f9b89309a84c198796f0f033726315f5de"
                },
                "downloads": -1,
                "filename": "pydace-0.0.1-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "ab4525c39f6f62f3b77b93a5b1020a58",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": null,
                "size": 12030,
                "upload_time": "2019-04-02T00:38:44",
                "url": "https://files.pythonhosted.org/packages/e8/d6/ba88da28144fb57e01e8032f72e9f2a754db9edc7651bf1d026aa103050d/pydace-0.0.1-py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "6a219ec914f9cc5343291049e7764158",
                    "sha256": "82308838c7a9d4cddf0d7c05d019707e1629d1777f5bfe8a5a114a72a08bd67e"
                },
                "downloads": -1,
                "filename": "pydace-0.0.1.tar.gz",
                "has_sig": false,
                "md5_digest": "6a219ec914f9cc5343291049e7764158",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 10599,
                "upload_time": "2019-04-02T00:38:47",
                "url": "https://files.pythonhosted.org/packages/ab/9e/52586f9254464a2b6d92ab66b29a288bc93cc19be31f890efe4f0399b368/pydace-0.0.1.tar.gz"
            }
        ],
        "0.0.2": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "b421804e65d5ef9de508701ee6c0a565",
                    "sha256": "d3710d8cbc18de9fc3c8b060228c0449b793a266b60dc427023d5a0d335b30cb"
                },
                "downloads": -1,
                "filename": "pydace-0.0.2-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "b421804e65d5ef9de508701ee6c0a565",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": null,
                "size": 12046,
                "upload_time": "2019-04-02T01:00:03",
                "url": "https://files.pythonhosted.org/packages/10/ed/a47e2fbf7531a4954c2584cb7ff994583570ef7b1f7c70361a7e1e793a6e/pydace-0.0.2-py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "99518e1fd54c8a11cdf69ac12c584a79",
                    "sha256": "a936c41d6b00f84b5206b6c6525598d718de17ac6369bbde46ae51ac331fdbc0"
                },
                "downloads": -1,
                "filename": "pydace-0.0.2.tar.gz",
                "has_sig": false,
                "md5_digest": "99518e1fd54c8a11cdf69ac12c584a79",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 10651,
                "upload_time": "2019-04-02T01:00:04",
                "url": "https://files.pythonhosted.org/packages/be/43/b1763e899a728a7f02ea0eda91cea3d934f907c75e833214137b35b625d7/pydace-0.0.2.tar.gz"
            }
        ],
        "0.0.3": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "01e263ca01b4ddc9617aad70ff66eaa1",
                    "sha256": "f64def81440352299f89c65fed4fe895d947c79277d217be00201f6fe1191075"
                },
                "downloads": -1,
                "filename": "pydace-0.0.3-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "01e263ca01b4ddc9617aad70ff66eaa1",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": ">=3.5",
                "size": 18115,
                "upload_time": "2019-04-19T00:47:15",
                "url": "https://files.pythonhosted.org/packages/ec/3a/85936c4f91cd3cd2d951b101bdca117c688ca5dee70d1f41c1b2ec897542/pydace-0.0.3-py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "c4fd6bf8744810b923958c2913f6d3ed",
                    "sha256": "983e2a6885a6036fbbaf2bbbb491032fd225f5edc66d348893fdff79d1de72b9"
                },
                "downloads": -1,
                "filename": "pydace-0.0.3.tar.gz",
                "has_sig": false,
                "md5_digest": "c4fd6bf8744810b923958c2913f6d3ed",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": ">=3.5",
                "size": 11808,
                "upload_time": "2019-04-19T00:47:16",
                "url": "https://files.pythonhosted.org/packages/1d/a6/4a50f436d98be1eeffd77f83950426c6093d11aec965ac840bacc433e19f/pydace-0.0.3.tar.gz"
            }
        ],
        "0.0.4": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "275c359b8c7bd9ed19802bfea2a79564",
                    "sha256": "6e626131e95d5e01516ccfc6c5c246429903bb21fd1b1ee51cdd605c80cff1f7"
                },
                "downloads": -1,
                "filename": "pydace-0.0.4-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "275c359b8c7bd9ed19802bfea2a79564",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": ">=3.5",
                "size": 20195,
                "upload_time": "2019-04-19T01:52:39",
                "url": "https://files.pythonhosted.org/packages/29/10/028ce9af9b48c7f069e0b1d3e29201b692936f6747e5203bd40c1ecd7af1/pydace-0.0.4-py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "3f036423ad06ff2f8403e1bc713ace12",
                    "sha256": "e50b2b788a638896316cfc051c0c4626ba83af4aae0ea62a34c170e1b8f889fd"
                },
                "downloads": -1,
                "filename": "pydace-0.0.4.tar.gz",
                "has_sig": false,
                "md5_digest": "3f036423ad06ff2f8403e1bc713ace12",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": ">=3.5",
                "size": 11541,
                "upload_time": "2019-04-19T01:52:40",
                "url": "https://files.pythonhosted.org/packages/7c/9f/1e47478fdca70cd37db24007fbbe783383aaa03d3c1d78c1164a79f10797/pydace-0.0.4.tar.gz"
            }
        ],
        "0.1.0": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "ebe9979fa05ce31524e60456348570b6",
                    "sha256": "289f148261a5ef30f5c1fd63912881d14397e541cc0b822bacd464f8acc77bdd"
                },
                "downloads": -1,
                "filename": "pydace-0.1.0-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "ebe9979fa05ce31524e60456348570b6",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": ">=3.5",
                "size": 19465,
                "upload_time": "2019-07-25T17:32:48",
                "url": "https://files.pythonhosted.org/packages/d7/34/31fc099634925406280187486a30c66c18c972b3ebb9f019f0385db1299c/pydace-0.1.0-py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "ceea041e152c5cc732f439f1e24e4135",
                    "sha256": "1b94670020d233e0ca700e07f3ea1a83dafc0a3055ae69def9775839a60cfb80"
                },
                "downloads": -1,
                "filename": "pydace-0.1.0.tar.gz",
                "has_sig": false,
                "md5_digest": "ceea041e152c5cc732f439f1e24e4135",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": ">=3.5",
                "size": 14748,
                "upload_time": "2019-07-25T17:32:50",
                "url": "https://files.pythonhosted.org/packages/20/36/a130560b33cf5b90fe31668850637ce558a59e78562168e22e0f371e20ac/pydace-0.1.0.tar.gz"
            }
        ],
        "0.1.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "e21e982f4c408829c58c71969214125d",
                    "sha256": "e64c9d3db05cc7d2e7c198fb3454b9ad3b4b5dde97474793548ab52c3435b320"
                },
                "downloads": -1,
                "filename": "pydace-0.1.1-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "e21e982f4c408829c58c71969214125d",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": ">=3.5",
                "size": 14697,
                "upload_time": "2019-09-30T16:51:37",
                "url": "https://files.pythonhosted.org/packages/4c/1f/1cb37e0b8686d59d39324faeabf53aba4633641bc18e8073992f9a3ec02b/pydace-0.1.1-py3-none-any.whl"
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "b0db996c935c49017c16f9bd08f82576",
                    "sha256": "e41a7368e999da38f867ed851d76d80c16cfb64d535e725583f15ea2a0a9e4fa"
                },
                "downloads": -1,
                "filename": "pydace-0.1.1.tar.gz",
                "has_sig": false,
                "md5_digest": "b0db996c935c49017c16f9bd08f82576",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": ">=3.5",
                "size": 14118,
                "upload_time": "2019-09-30T16:51:39",
                "url": "https://files.pythonhosted.org/packages/76/e4/0e8685dfc9f8dd6dffe1cebe0c46019592e11ac224915ab3ed9144abef07/pydace-0.1.1.tar.gz"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "e21e982f4c408829c58c71969214125d",
                "sha256": "e64c9d3db05cc7d2e7c198fb3454b9ad3b4b5dde97474793548ab52c3435b320"
            },
            "downloads": -1,
            "filename": "pydace-0.1.1-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "e21e982f4c408829c58c71969214125d",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.5",
            "size": 14697,
            "upload_time": "2019-09-30T16:51:37",
            "url": "https://files.pythonhosted.org/packages/4c/1f/1cb37e0b8686d59d39324faeabf53aba4633641bc18e8073992f9a3ec02b/pydace-0.1.1-py3-none-any.whl"
        },
        {
            "comment_text": "",
            "digests": {
                "md5": "b0db996c935c49017c16f9bd08f82576",
                "sha256": "e41a7368e999da38f867ed851d76d80c16cfb64d535e725583f15ea2a0a9e4fa"
            },
            "downloads": -1,
            "filename": "pydace-0.1.1.tar.gz",
            "has_sig": false,
            "md5_digest": "b0db996c935c49017c16f9bd08f82576",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.5",
            "size": 14118,
            "upload_time": "2019-09-30T16:51:39",
            "url": "https://files.pythonhosted.org/packages/76/e4/0e8685dfc9f8dd6dffe1cebe0c46019592e11ac224915ab3ed9144abef07/pydace-0.1.1.tar.gz"
        }
    ]
}