{
    "info": {
        "author": "IMDA Digital Services Lab",
        "author_email": "",
        "bugtrack_url": null,
        "classifiers": [
            "Environment :: Console",
            "License :: OSI Approved :: Apache Software License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
        ],
        "description": "# intelligent-sensing-toolbox\n\nIntelligent Sensing Toolbox (Isensing) is a Python package that focuses on multivariate time series analysis. This toolbox includes multiple open-source machine learning algorithms and statistic calculations.\n\nIn data analytics, making sense of massive numbers of data requires machine learning to work on datasets from different multiple sources in order to generate insights. For situation where a node that generates data points of multiple features in time series, massive number of nodes will make analysis more challenging.\n\nIsensing provides a list of algorithms that does features extraction, decomposition and anomaly detections.\n\n### Installation\n\nIsensing is built upon Python 3. To install Isensing, make sure Python 3 and pip is installed.\n\n```python\npip install isensing\n```\n\n### Dependencies\n```\npandas\nnumpy\nscipy\nsklearn\nstatsmodels\nmatplotlib\nplotly\nshapely\n```\nThese dependencies will be installed automatically using pip.\n\n### Modules\n#### anomaly\n```python\n# class\nAlphaHull\nHDR\n\n# functions\noutlier_detection()\nisensing_anomalies()\n```\n\n#### decomposition\n```python\n# class\nRobustPCA\n```\n\n#### features_extraction\n```python\n# functions\nmultiple_regression()\nfast_DTW()\npearsonr_correlation()\n```\n\n### Tutorial\n[Link](https://gitlab.com/imda-dsl/intelligent-sensing-toolbox/blob/master/demo/Intelligent%20Sensing%20Toolkit%20Tutorial/Intelligent%20Sensing%20Toolbox%20Tutorial.md)\n\n### References\n* https://github.com/robjhyndman/anomalous-acm\n* http://blog.thehumangeo.com/2014/05/12/drawing-boundaries-in-python/\n* https://feb.kuleuven.be/public/u0017833/Programs/pca/robpca.txt\n\n### License\nApache License 2.0\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://gitlab.com/imda-dsl/intelligent-sensing-toolbox",
        "keywords": "",
        "license": "",
        "maintainer": "",
        "maintainer_email": "",
        "name": "isensing",
        "package_url": "https://pypi.org/project/isensing/",
        "platform": "",
        "project_url": "https://pypi.org/project/isensing/",
        "project_urls": {
            "Homepage": "https://gitlab.com/imda-dsl/intelligent-sensing-toolbox"
        },
        "release_url": "https://pypi.org/project/isensing/0.1.1/",
        "requires_dist": [
            "pandas",
            "numpy",
            "statsmodels",
            "scipy",
            "fastdtw",
            "sklearn",
            "matplotlib",
            "plotly",
            "descartes",
            "shapely"
        ],
        "requires_python": "",
        "summary": "Intelligent Sensing Toolbox for Multivariate Time Series",
        "version": "0.1.1"
    },
    "last_serial": 4515009,
    "releases": {
        "0.1.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "90c08161860788b18e988c2d11de587a",
                    "sha256": "ac9ac8c79bad127a1d3f6e798eb03cf740eddae687db203847f6ddddcf5cf051"
                },
                "downloads": -1,
                "filename": "isensing-0.1.1-py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "90c08161860788b18e988c2d11de587a",
                "packagetype": "bdist_wheel",
                "python_version": "py3",
                "requires_python": null,
                "size": 18396,
                "upload_time": "2018-11-22T02:24:39",
                "url": "https://files.pythonhosted.org/packages/b4/04/5df171243a2f6de1ae07075807494ada9e12c34d36f088ce488c7bf1ca95/isensing-0.1.1-py3-none-any.whl"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "90c08161860788b18e988c2d11de587a",
                "sha256": "ac9ac8c79bad127a1d3f6e798eb03cf740eddae687db203847f6ddddcf5cf051"
            },
            "downloads": -1,
            "filename": "isensing-0.1.1-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "90c08161860788b18e988c2d11de587a",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": null,
            "size": 18396,
            "upload_time": "2018-11-22T02:24:39",
            "url": "https://files.pythonhosted.org/packages/b4/04/5df171243a2f6de1ae07075807494ada9e12c34d36f088ce488c7bf1ca95/isensing-0.1.1-py3-none-any.whl"
        }
    ]
}