{"id":27024302,"url":"https://github.com/ap-atul/wavelets","last_synced_at":"2025-04-04T21:19:10.964Z","repository":{"id":56696200,"uuid":"306623332","full_name":"AP-Atul/wavelets","owner":"AP-Atul","description":"A simple and easy implementation of Wavelet Transform","archived":false,"fork":false,"pushed_at":"2021-01-14T17:00:51.000Z","size":218,"stargazers_count":22,"open_issues_count":0,"forks_count":4,"subscribers_count":3,"default_branch":"main","last_synced_at":"2024-05-21T07:19:44.252Z","etag":null,"topics":["compression","denoising","discrete-wavelet-transform","wavelet-transform","wavelets"],"latest_commit_sha":null,"homepage":"https://ap-atul.github.io/wavelet","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/AP-Atul.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-10-23T12:01:53.000Z","updated_at":"2024-04-22T20:36:54.000Z","dependencies_parsed_at":"2022-08-15T23:31:04.814Z","dependency_job_id":null,"html_url":"https://github.com/AP-Atul/wavelets","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AP-Atul%2Fwavelets","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AP-Atul%2Fwavelets/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AP-Atul%2Fwavelets/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AP-Atul%2Fwavelets/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AP-Atul","download_url":"https://codeload.github.com/AP-Atul/wavelets/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247249521,"owners_count":20908213,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["compression","denoising","discrete-wavelet-transform","wavelet-transform","wavelets"],"created_at":"2025-04-04T21:19:10.377Z","updated_at":"2025-04-04T21:19:10.959Z","avatar_url":"https://github.com/AP-Atul.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Wavelets\nPython implementation of the Fast Wavelet Transform (FWT) on 1D, 2D, and 3D(soon) input signals/data.\nThe common wavelets like Haar, and Daubechies is available, along with 60+ wavelets. \n\nThe code is according to the software development process, so hopefully its user-friendly or\ndev-friendly.\n\n\n## Introduction\nThe simple Wavelet Transform is given by the formula\n\n![formula](https://github.com/AP-Atul/Wavelets/blob/master/img/wt.png)\n\nThe fundamental idea of wavelet transforms is that the transformation should allow only changes in time extension, but not shape.\nThis is affected by choosing suitable basis functions that allow for this.\nChanges in the time extension are expected to conform to the corresponding analysis frequency of the basis function.\n\n\n## API\nDimension implemented (1D, 2D)\nJust call  ```waveDec``` for wavelet decomposition for any dim, length array\nAnd ```waveRec``` for wavelet reconstruction for any dim, length array\n\nUpdate: Use it with any length of data. (1D \u0026 2D)\n\nCheck the ```examples/``` for some examples on the usage. Refer the html ```docs/```\n\n\n## Installation\n1. Install using pip\n```console\npip install git+https://github.com/AP-Atul/wavelets\n```\n\n2. Clone the repo and run setup\n```console\ngit clone https://github.com/AP-Atul/wavelets.git\npython setup.py install\n```\n\n\n## Examples\n1. Wavelet decomposition and reconstruction\n\n```python\nfrom wavelet import FastWaveletTransform\n\nWAVELET_NAME = \"db4\"\nt = FastWaveletTransform(WAVELET_NAME)\n\n# original data\ndata = [1, 1, 1, 1, 1, 1, 1, 1]\n\n# decomposition --\u003e reconstruction\ncoefficients = t.waveDec(data)\ndata = t.waveRec(coefficients)\n\n```\n\n2. Simple discrete transforms\n\n```python\nfrom wavelet import WaveletTransform, getExponent\n\ntransform = WaveletTransform(waveletName=\"db2\")\ndata = [1, 2, 3, 4, 5, 6, 7, 9]\n\n# dwt with max level\ncoefficients = transform.dwt(data, level=getExponent(len(data)))\n\n# inverse dwt with max level\ndata = transform.idwt(coefficients, level=len(coefficients))\n```\n\n## Applications\n(I'll try to provide some examples for this)\n1. Audio de-noising by cleaning the noise signal from the coefficients\n2. Data cleaning in the sense of Data Mining\n3. Data compression\n4. Digital Communications\n5. Image Processing\n6. etc.\n\n\n## Limitations\nThe performance can be improved. Help to make it even better by contributing\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fap-atul%2Fwavelets","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fap-atul%2Fwavelets","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fap-atul%2Fwavelets/lists"}