{"id":37691398,"url":"https://github.com/kousuke-nakano/turbogenius","last_synced_at":"2026-01-16T12:42:47.575Z","repository":{"id":160158551,"uuid":"531898430","full_name":"kousuke-nakano/turbogenius","owner":"kousuke-nakano","description":"Python wrappers for TurboRVB","archived":false,"fork":false,"pushed_at":"2025-12-02T07:39:43.000Z","size":7396,"stargazers_count":6,"open_issues_count":2,"forks_count":3,"subscribers_count":1,"default_branch":"devel","last_synced_at":"2025-12-05T02:20:23.912Z","etag":null,"topics":["ab-initio-simulations","electronic-structure","python","quantum-monte-carlo","turborvb"],"latest_commit_sha":null,"homepage":"https://turborvb.sissa.it","language":"Python","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/kousuke-nakano.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":".github/CODEOWNERS","security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2022-09-02T11:29:22.000Z","updated_at":"2025-12-02T07:39:48.000Z","dependencies_parsed_at":"2023-11-07T05:39:49.114Z","dependency_job_id":"4e20d5f9-c7cb-4914-8b28-19667526c320","html_url":"https://github.com/kousuke-nakano/turbogenius","commit_stats":null,"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"purl":"pkg:github/kousuke-nakano/turbogenius","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kousuke-nakano%2Fturbogenius","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kousuke-nakano%2Fturbogenius/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kousuke-nakano%2Fturbogenius/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kousuke-nakano%2Fturbogenius/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/kousuke-nakano","download_url":"https://codeload.github.com/kousuke-nakano/turbogenius/tar.gz/refs/heads/devel","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kousuke-nakano%2Fturbogenius/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28478726,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-16T11:59:17.896Z","status":"ssl_error","status_checked_at":"2026-01-16T11:55:55.838Z","response_time":107,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["ab-initio-simulations","electronic-structure","python","quantum-monte-carlo","turborvb"],"created_at":"2026-01-16T12:42:46.988Z","updated_at":"2026-01-16T12:42:47.555Z","avatar_url":"https://github.com/kousuke-nakano.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# TurboGenius\n\n\u003cimg src=\"logo/turbogenius_logo.png\" width=\"70%\"\u003e\n\n`TurboGenius` is an advanced python wrappers for the SISSA ab-initio quantum Monte Carlo code, `TurboRVB` and also provides useful command-line tools.\n\n![license](https://img.shields.io/github/license/kousuke-nakano/turbogenius) ![release](https://img.shields.io/github/release/kousuke-nakano/turbogenius/all.svg) ![fork](https://img.shields.io/github/forks/kousuke-nakano/turbogenius?style=social) ![stars](https://img.shields.io/github/stars/kousuke-nakano/turbogenius?style=social)\n\n`TurboRVB` software family is now composed of the 4 layered packages:\n\n- `TurboWorkflows` (Workflows for realizing QMC high-throughput calculations)\n- `TurboGenius` (Advanced python wrappers and command-line tools)\n- `pyturbo` (Python-Fortran90 wrappers)\n- `TurboRVB` (Quantum Monte Carlo kernel)\n\n`TurboGenius` is the third layer package, which also contains the second layer package `pyturbo` inside as a submodule.\n\n# Beta version\nThis is a **beta** version!!!! Contact the developers whenever you find bugs. Any suggestion is also welcome!\n\n# Features of `turbogenius`\nOne can manage any job of `TurboRVB` on python scripts, or on your terminal using the provided command line tool `turbogenius`.\n\nFor python users, several one-to-one corresponding python modules (classes) are provided, i.e., `makefort10.x` -\u003e `Makefort10_genius` class in `makefort10_genius.py`, `turborvb.x` -\u003e `vmc_genius` class in `vmc_genius.py`. `TurboGenius` is designed as a higher layer package that provide several complicated procedures and functions such as fully automatic workflows. `Turbo-Genius` is implemented based on the lower layer packages `pyturbo` and `TurboRVB`. You can see several examples of `TurboGenius` scripts in the `tests` directory. You can also see several simple workflows using `TurboGenius` in the `tests` directory.\n\n# Quick use of `turbogenius`\n\nInstalling from source\n\n    git clone https://github.com/kousuke-nakano/turbogenius.git\n    cd turbogenius\n    pip install -e . or pip install .\n\nLauching the command line tool. You can easily see what commands are implemented in ``TurboGenius``.\n\n    % turbogenius --help\n    Usage: turbogenius [OPTIONS] COMMAND [ARGS]...\n\n    Options:\n    --help  Show this message and exit.\n\n    Commands:\n    convertfort10        convertfort10_genius\n    convertfort10mol     convertfort10mol_genius\n    convertpfaff         readforward_genius\n    convertwf            convert wavefunction\n    correlated-sampling  correlated_sampling_genius\n    lrdmc                lrdmc_genius\n    lrdmcopt             lrdmc_genius\n    makefort10           makefort10_genius\n    prep                 prep_genius\n    vmc                  vmc_genius\n    vmcopt               vmcopt_genius\n\nYou can also see what options are implemented for each command, e.g., vmcopt\n\n    % turbogenius vmcopt --help\n    Usage: turbogenius vmcopt [OPTIONS]\n\n    Options:\n    -post                 Postprocess\n    -r                    Run a program\n    -g                    Generate an input file\n    -vmcoptsteps INTEGER  Specify vmcoptsteps\n    -optwarmup INTEGER    Specify optwarmupsteps\n    -steps INTEGER        Specify steps per one iteration\n    -bin INTEGER          Specify bin_block\n    -warmup INTEGER       Specify warmupblocks\n    -nw INTEGER           Specify num_walkers\n    -maxtime INTEGER      Specify maxtime\n    -optimizer TEXT       Specify optimizer, sr or lr\n    -learn FLOAT          Specify learning_rate\n    -reg FLOAT            Specify regularization\n    -opt_onebody          flag for opt_onebody\n    -opt_twobody          flag for opt_twobody\n    -opt_det_mat          flag for opt_det_mat\n    -opt_jas_mat          flag for opt_jas_mat\n    -opt_det_basis_exp    flag for opt_det_basis_exp\n    -opt_jas_basis_exp    flag for opt_jas_basis_exp\n    -opt_det_basis_coeff  flag for opt_det_basis_coeff\n    -opt_jas_basis_coeff  flag for opt_jas_basis_coeff\n    -twist                flag for twist_average\n    -kpts INTEGER...      kpts, Specify Monkhorst-Pack grids and shifts, [nkx,nky,nkz,kx,ky,kz]\n    -plot                 flag for plotting graph\n    -log TEXT             logger level, DEBUG, INFO, ERROR\n    --help                Show this message and exit.\n\n# Features of `pyturbo`\nOne can manage any job of `TurboRVB` on python scripts. There are one-to-one corresponding python modules (classes), i.e., `makefort10.x` -\u003e `Makefort10` class in `makefort10.py`, `convertfort10.x` -\u003e `Convertfort10mol` class in `convertfort10mol.py`. `pyturbo` is designed as a lower layer package such that the modules can be used as **components** of higher-level packages. Indeed, the classes are implemented as simple but flexible as possible. Other complicated methods and modules such as fully automatic workflows should be provided at the higher-level packages such as `TurboGenius`. You can see several examples of `pyturbo` scripts in the `tests` directory.\n\n# Installation\n- `git clone this repository`\n- `cd turbogenius`\n- `pip install -e .` or `pip install .`\n\n# Examples\nExamples are in the `example` directory.\n\n# Documentation for users\nYou can readily understand how to use `pyturbo` and `turbogenius` by looking at the sample python scripts in the `example` directory.\nYou can also see our tutorials [https://github.com/kousuke-nakano/turbotutorials].\n\n# Documentation for deveopers\nThere is a Read the Docs in the `docs` directory, but still in progress.\nYou can generate a html file using `sphinx`. Go to the `docs` directory,\nand type `make html`. The document is generated in `docs/_build/html`.\n`index.html` is the main page.\n\n# Reference\nK. Nakano et al., [TurboGenius: Python suite for high-throughput calculations of ab initio quantum Monte Carlo methods](https://doi.org/10.1063/5.0179003), *J. Chem. Phys.* 159, 224801 (2023).\n\n# How to contribute\n\nPlease do not directly push your changes to `main` and `devel` branch.\nPlease create a pull request on GitHub from your forked repository or a new branch (e.g. `devel-#1`). \n\n# How to check the version info.\n\n    # Confirm the version number via `setuptools-scm`\n    python -m setuptools_scm\n    e.g., 1.1.4.dev28+gceef293.d20221123 -\u003e \u003cnext-version\u003e = v1.1.4 or v1.1.4-alpha(for pre-release)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkousuke-nakano%2Fturbogenius","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkousuke-nakano%2Fturbogenius","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkousuke-nakano%2Fturbogenius/lists"}