{"id":18613924,"url":"https://github.com/enthought/blusky","last_synced_at":"2025-08-30T22:15:48.637Z","repository":{"id":50221871,"uuid":"193145510","full_name":"enthought/blusky","owner":"enthought","description":"BluSky","archived":false,"fork":false,"pushed_at":"2021-06-08T16:18:24.000Z","size":24333,"stargazers_count":5,"open_issues_count":42,"forks_count":4,"subscribers_count":21,"default_branch":"master","last_synced_at":"2025-04-11T10:58:04.723Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/enthought.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-06-21T18:46:23.000Z","updated_at":"2024-01-29T03:12:37.000Z","dependencies_parsed_at":"2022-08-27T19:40:59.837Z","dependency_job_id":null,"html_url":"https://github.com/enthought/blusky","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/enthought/blusky","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2Fblusky","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2Fblusky/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2Fblusky/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2Fblusky/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/enthought","download_url":"https://codeload.github.com/enthought/blusky/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/enthought%2Fblusky/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":272914558,"owners_count":25014443,"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","status":"online","status_checked_at":"2025-08-30T02:00:09.474Z","response_time":77,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":[],"created_at":"2024-11-07T03:24:21.172Z","updated_at":"2025-08-30T22:15:48.619Z","avatar_url":"https://github.com/enthought.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"BluSky - A Python implementation of the wavelet scattering transform\n====================================================================\n\nBluSky is a Python library for that implements the Mallat wavelet scattering transform using Keras/Tensorflow.  Features include:\n- 1D, 2D transforms.  3D on the way.\n- arbitrary order\n- Morlets \u0026 Gabor, modular library allows for arbitrary wavelets(?)\n- built in visualization of transform coefficients\n\nInstallation\n------------\nInstall the dependencies in a Conda environment:\n```\nconda create -n blusky python=3.8.5 traits matplotlib scikit-learn\nconda activate blusky\npython -m pip install tensorflow==2.4\n```\n\nInstall BluSky from source:\n```\ngit clone git@github.com:enthought/blusky.git\ncd blusky\npython -m pip install -e .\n```\n\nGetting Started\n---------------\n- wavelet scattering transform, implemented as a series of convolutions using Keras and Tensorflow.\n- following the approach of Bruna, and Mallat (refs)\n- the transform is implemented as a convolutional neural network. intermediate activations are easily interrogated to enable easy interrogation of the signal as it propagates through the cascade\n\n\nSupport\n-------\nThis effort was supported by [Sandia National Labs](https://www.sandia.gov/) with development and maintenance support \nby [Enthought](https://www.enthought.com).\n\n![Enthought logo](/blusky/images/enthought-logo.png)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fenthought%2Fblusky","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fenthought%2Fblusky","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fenthought%2Fblusky/lists"}