{ "info": { "author": "Vinicius Rezende Carvalho", "author_email": "vrcarva@ufmg.br", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Programming Language :: Python :: 3", "Topic :: Scientific/Engineering :: Mathematics" ], "description": "# Empirical Wavelet Transform Python package\n\nOriginal paper: \nGilles, J., 2013. Empirical Wavelet Transform. IEEE Transactions on Signal Processing, 61(16), pp.3999\u00e2\u20ac\u201c4010. \nAvailable at: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6522142. \nOriginal Matlab toolbox: https://www.mathworks.com/matlabcentral/fileexchange/42141-empirical-wavelet-transforms\n\newtpy performs the Empirical Wavelet Transform of a 1D signal over N scales. Main function is EWT1D:\n\newt, mfb ,boundaries = EWT1D(f, N = 5, log = 0,detect = \"locmax\", completion = 0, reg = 'average', lengthFilter = 10,sigmaFilter = 5) \nOther functions include: \nEWT_Boundaries_Detect \nEWT_Boundaries_Completion \nEWT_Meyer_FilterBank \nEWT_beta \nEWT_Meyer_Wavelet \nLocalMax \nLocalMaxMin \n\nSome functionalities from J.Gilles' MATLAB toolbox have not been implemented, such as EWT of 2D inputs, preprocessing, adaptive/ScaleSpace boundaries_detect.\n\nThe Example folder contains test signals and scripts\n\n## Installation \n\n1) Dowload the project from https://github.com/vrcarva/vmdpy, then run \"python setup.py install\" from the project folder\n\nOR\n\n2) pip install ewtpy\n\n\n## Citation and Contact\nIf you find this package useful, we kindly ask you to cite it in your work. \nVinicius Carvalho (2019-), Empirical Wavelet Transform in Python \n\nA paper will soon be submitted and linked here. \n\n@author: Vin\u00c3\u00adcius Rezende Carvalho\nPrograma de p\u00c3\u00b3s gradua\u00c3\u00a7\u00c3\u00a3o em engenharia el\u00c3\u00a9trica - PPGEE UFMG\nUniversidade Federal de Minas Gerais - Belo Horizonte, Brazil\nN\u00c3\u00bacleo de Neuroci\u00c3\u00aancias - NNC \n\nAny questions, comments, suggestions and/or corrections, please get in contact with vrcarva@ufmg.br\n\n## Example script\n```python\n#%% Example script\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport ewtpy\n\nT = 1000\nt = np.arange(1,T+1)/T\nf = np.cos(2*np.pi*0.8*t) + 2*np.cos(2*np.pi*10*t)+0.8*np.cos(2*np.pi*100*t)\newt, mfb ,boundaries = ewtpy.EWT1D(f, N = 3)\nplt.plot(f)\nplt.plot(ewt)\n```\n\n\n\n\n\n\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": "http://github.com/vrcarva/ewtpy", "keywords": "EWT,empirical,wavelet", "license": "", "maintainer": "", "maintainer_email": "", "name": "ewtpy", "package_url": "https://pypi.org/project/ewtpy/", "platform": "", "project_url": "https://pypi.org/project/ewtpy/", "project_urls": { "Homepage": "http://github.com/vrcarva/ewtpy" }, "release_url": "https://pypi.org/project/ewtpy/0.1/", "requires_dist": [ "numpy", "scipy" ], "requires_python": "", "summary": "Empirical Wavelet Transofrm (EWT) algorithm", "version": "0.1" }, "last_serial": 5120255, "releases": { "0.1": [ { "comment_text": "", "digests": { "md5": "0ef2bbbfaf2a006e5a7393abbed70eb1", "sha256": "be16da7f7391ef0e0ea1250465be7e4a50ffa77f2512e48815c2bdf94ccb761c" }, "downloads": -1, "filename": "ewtpy-0.1-py3-none-any.whl", "has_sig": false, "md5_digest": "0ef2bbbfaf2a006e5a7393abbed70eb1", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 7917, "upload_time": "2019-04-09T19:04:30", "url": "https://files.pythonhosted.org/packages/a2/b6/144670270625719a4e53145a859e8d963568cd860930aea85cac2b49e354/ewtpy-0.1-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "71382adb1beac254744c15bb329c426d", "sha256": "71a34ddc2b1f4cd23f2edb2558dd6a0454eb5bf246a679bed760f406f10803fe" }, "downloads": -1, "filename": "ewtpy-0.1.tar.gz", "has_sig": false, "md5_digest": "71382adb1beac254744c15bb329c426d", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 6378, "upload_time": "2019-04-09T19:04:32", "url": "https://files.pythonhosted.org/packages/8b/16/1815191dabf210e68ca3a1233387a10d756c90e11ba522f54e88fd12713c/ewtpy-0.1.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "0ef2bbbfaf2a006e5a7393abbed70eb1", "sha256": "be16da7f7391ef0e0ea1250465be7e4a50ffa77f2512e48815c2bdf94ccb761c" }, "downloads": -1, "filename": "ewtpy-0.1-py3-none-any.whl", "has_sig": false, "md5_digest": "0ef2bbbfaf2a006e5a7393abbed70eb1", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 7917, "upload_time": "2019-04-09T19:04:30", "url": "https://files.pythonhosted.org/packages/a2/b6/144670270625719a4e53145a859e8d963568cd860930aea85cac2b49e354/ewtpy-0.1-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "71382adb1beac254744c15bb329c426d", "sha256": "71a34ddc2b1f4cd23f2edb2558dd6a0454eb5bf246a679bed760f406f10803fe" }, "downloads": -1, "filename": "ewtpy-0.1.tar.gz", "has_sig": false, "md5_digest": "71382adb1beac254744c15bb329c426d", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 6378, "upload_time": "2019-04-09T19:04:32", "url": "https://files.pythonhosted.org/packages/8b/16/1815191dabf210e68ca3a1233387a10d756c90e11ba522f54e88fd12713c/ewtpy-0.1.tar.gz" } ] }