{"id":32415792,"url":"https://github.com/jiwoncpark/node-to-joy","last_synced_at":"2025-10-25T15:30:10.888Z","repository":{"id":48297354,"uuid":"238280454","full_name":"jiwoncpark/node-to-joy","owner":"jiwoncpark","description":"Modeling the external convergence from photometric catalogs","archived":false,"fork":false,"pushed_at":"2023-05-02T23:34:49.000Z","size":4921,"stargazers_count":4,"open_issues_count":5,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2023-07-31T13:56:56.711Z","etag":null,"topics":["graph-convolutional-network","uncertainty-quantification"],"latest_commit_sha":null,"homepage":"","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/jiwoncpark.png","metadata":{"files":{"readme":"README.rst","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":"2020-02-04T18:51:17.000Z","updated_at":"2023-03-02T08:16:00.000Z","dependencies_parsed_at":"2022-08-30T09:21:33.949Z","dependency_job_id":null,"html_url":"https://github.com/jiwoncpark/node-to-joy","commit_stats":null,"previous_names":[],"tags_count":0,"template":null,"template_full_name":null,"purl":"pkg:github/jiwoncpark/node-to-joy","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jiwoncpark%2Fnode-to-joy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jiwoncpark%2Fnode-to-joy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jiwoncpark%2Fnode-to-joy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jiwoncpark%2Fnode-to-joy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jiwoncpark","download_url":"https://codeload.github.com/jiwoncpark/node-to-joy/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jiwoncpark%2Fnode-to-joy/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":280978316,"owners_count":26423960,"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":"2025-10-25T02:00:06.499Z","response_time":81,"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":["graph-convolutional-network","uncertainty-quantification"],"created_at":"2025-10-25T15:30:06.197Z","updated_at":"2025-10-25T15:30:10.883Z","avatar_url":"https://github.com/jiwoncpark.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"=========================================================================\nNode to Joy - Modeling the external convergence from photometric catalogs\n=========================================================================\n\n.. image:: https://readthedocs.org/projects/node-to-joy/badge/?version=latest\n        :target: https://node-to-joy.readthedocs.io/en/latest/?badge=latest\n        :alt: Documentation Status\n        \nThis package contains functionality to\n\n* postprocess the coarse convergence values of an existing simulation to introduce finer fluctuations at galaxy-galaxy lensing scales\n* train a Bayesian graph neural network to infer convergence given photometric measurements of galaxies around a line of sight\n* hierarchically infer the mean and standard deviation of convergence in the population\n\n.. image:: plots/gallery_opaque.png\n\nInstallation\n============\n\n0. Virtual environments are strongly recommended, to prevent dependencies with conflicting versions. Create a conda virtual environment and activate it:\n\n::\n\n$conda create -n n2j python=3.8 -y\n$conda activate n2j\n\n1. Clone the repo and install.\n\n::\n\n$git clone https://github.com/jiwoncpark/node-to-joy.git\n$cd node-to-joy\n$pip install -e . -r requirements.txt\n\n2. (Optional) To run the notebooks, add the Jupyter kernel.\n\n::\n\n$python -m ipykernel install --user --name n2j --display-name \"Python (n2j)\"\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjiwoncpark%2Fnode-to-joy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjiwoncpark%2Fnode-to-joy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjiwoncpark%2Fnode-to-joy/lists"}