{"id":37065722,"url":"https://github.com/vsquicciarini/madys","last_synced_at":"2026-02-27T20:20:02.097Z","repository":{"id":37433317,"uuid":"333572220","full_name":"vsquicciarini/madys","owner":"vsquicciarini","description":"MADYS: isochronal parameter determination for young stellar and substellar objects","archived":false,"fork":false,"pushed_at":"2025-11-17T16:06:11.000Z","size":34059,"stargazers_count":7,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-11-17T16:24:48.018Z","etag":null,"topics":["astronomy","direct-imaging","gaia","model-comparison","parameter-estimation","python","sql","stellar-astrophysics"],"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/vsquicciarini.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2021-01-27T22:02:02.000Z","updated_at":"2025-11-17T16:06:17.000Z","dependencies_parsed_at":"2025-04-11T16:37:57.982Z","dependency_job_id":null,"html_url":"https://github.com/vsquicciarini/madys","commit_stats":null,"previous_names":[],"tags_count":12,"template":false,"template_full_name":null,"purl":"pkg:github/vsquicciarini/madys","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vsquicciarini%2Fmadys","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vsquicciarini%2Fmadys/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vsquicciarini%2Fmadys/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vsquicciarini%2Fmadys/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/vsquicciarini","download_url":"https://codeload.github.com/vsquicciarini/madys/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vsquicciarini%2Fmadys/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28413474,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-14T05:26:33.345Z","status":"ssl_error","status_checked_at":"2026-01-14T05:21:57.251Z","response_time":107,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: 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":["astronomy","direct-imaging","gaia","model-comparison","parameter-estimation","python","sql","stellar-astrophysics"],"created_at":"2026-01-14T07:41:50.708Z","updated_at":"2026-02-27T20:20:02.076Z","avatar_url":"https://github.com/vsquicciarini.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\nManifold Age Determination for Young Stars (MADYS) \n==========\n\nDescription\n-----------\nThis repository hosts the code of `MADYS`: the Manifold Age Determination for Young Stars, a flexible Python tool for parameter determination of young stellar and substellar objects.\n\n`MADYS` automatically retrieves and cross-matches photometry from several catalogs, estimates interstellar extinction, and derives parameter (age, mass, radius, Teff, logg, logL) estimates for individual objects through isochronal fitting.\n\nHarmonising the heterogeneity of publicly-available isochrone grids, the tool allows to choose amongst several models, many of which with customisable astrophysical parameters. Particular attention has been dedicated to the categorization of these models, labeled through a four-level taxonomical classification.\n\nAt the moment of writing, MADYS includes 21 models, 153 isochrone grids, and more then 250 photometric filters (a thorough description of each of them is provided). However, despite our efforts, the model list is far from being complete. If you wish a new model to be included in a new version of `MADYS`, or a new set of photometric filters to be added to the current list, feel free to get in contact with us.\n\nSix classes are defined to handle a large variety of possible applications, spanning from the characterization of directly-imaged planets to the study of stellar associations. Notably, large direct imaging survey will benefit from `MADYS`' capability to compute planetary masses corresponding to detection limits of direct imaging observations.\n\nFinally, several dedicated plotting functions are included to allow a visual perception of the numerical output.\n\nLatest news:\n------------\n\nFeb 27, 2026 - Version v2.1.1 published! Fixed minor bugs introduced in v2.1.0.\n\nFeb 10, 2026 - Version v2.1.0 published! Several updates in the DetectionMap class: it is now possible to compute physical maps and detection probability maps as a function of Teff instead of mass; added new functions for advanced plotting of these maps; now possible to account for the fact the outermost part of a non-circular field of view are not fully covered by an observation; fixed minor bugs.\n\nNov 17, 2025 - Version v2.0.0 published! A new class, DetectionMap, now handles the conversion of contrast curves to mass curves and detection probability maps, including the possibility to extrapolate outside a model's dynamical range; added new patchwork models connecting BEX and ATMO/Ames-Dusty/Ames-Cond; expanded roster of available filters for several substellar models; improved ADQL queries; added several new plotting functions.\n\nApr 28, 2024 - Version v1.3.0 published! Expanded the features of the CurveObject class; added Hipparcos catalog and Gaia DR3-Hipparcos proper motion to the automatic ADQL query done by SampleObject; increased completeness of catalog cross-matches; improved readability of code following Docstring Conventions (PEP 8).\n\nJan 22, 2024 - Version v1.2.0 published! A more accurate parameter derivation was introduced when providing [age_opt, age_min, age_max] triplets; SampleObject instances can now be merged; a higher degree of control of plotting options is now possible; fixed minor bugs.\n\nOct 18, 2023 - Version v1.1.0 published! Several new functionalities added: a class to handle the conversion of direct imaging contrast curves into mass curves; functions to easily export/import SampleObject and FitParams instances; a new attribute of SampleObject containing information on photometric quality. Better exploitation of log files; better handling of output files and objects; general improvement of computational performances. \n\nOct 10, 2023 - MADYS has now a full documentation on [readthedocs](https://madys.readthedocs.io/en/latest/). Have a look at it!\n\nSep 09, 2023 - Version v1.0.0 published! Newly added models: Dartmouth (magnetic and non-magnetic, Feiden 2016), solar-metallicity PARSEC v2.0 (Nguyen et al. 2022), latest version of ATMO (Chabrier et al. 2023); added JWST filters to PARSEC (v1.2 and v2.0) isochrones, and Gaia, 2MASS, Panstarrs and HST filters to ATMO 2020. Inserted possibility to estimate synthetic photometry for fitted objects in bands not employed when deriving their parameters.\n\nFeb 17, 2023 - Changed default queried catalog from Gaia DR2 to Gaia DR3 when providing a list of stars with non-Gaia identifiers (i.e., with 'id_type'='other').\n\nJan 19, 2023 - Added the possibility to take into account uncertainties on E(B-V) values, which can now be provided at inizialization through a dedicated keyword 'ebv_err'.\n\nAug 03, 2022 - Sloan Digital Sky Survey added to the list of automatically searchable surveys. Its filters are now available with the following models: PARSEC, MIST, AMES-Dusty, AMES-Cond, BT-Settl, NextGen.\n\nJun 20, 2022 - BEX models (Linder et al. 2019, Marleau et al. 2019) added to the list of available models.\n\nJun 17, 2022 - Gaia DR3 now available! The new catalog replaces, for all intents and purposes, Gaia EDR3.\n\n\nInstallation:\n------------\nCatalog queries are mediated by the [TAP Gaia Query](https://github.com/mfouesneau/tap) package (tap). If you import madys from the command line, the module is automatically installed if not found. However, **this does not work from Jupyter Notebook**. We suggest to manually install the package from pip, through:\n\n```sh\npip install git+https://github.com/mfouesneau/tap\n```\nPlease make sure you use the command above, as just using `pip install tap` will download **a different**, although homonymous, package.\nIf not installed on your machine, the `git` command can be installed following [this guide](https://github.com/git-guides/install-git).\n\n\nNote that TAP Gaia Query might require the installation of [lxml](https://lxml.de/) (v4.6.3).\n\nOnce TAP Gaia Query is installed, the current `MADYS` repository can be installed using pip:\n\n```sh\npip install madys\n```\nNote that, when using for the first time an extinction map, `MADYS` will download the relevant file (0.7 GB or 2.2 GB, depending on the map).\n\n\nRequirements\n------------\n\nThis package relies on usual packages for data science and astronomy: [numpy](https://numpy.org/), [scipy](https://www.scipy.org/), [pandas](https://pandas.pydata.org/), [matplotlib](https://matplotlib.org/), [astropy](https://www.astropy.org/) and [h5py](https://www.h5py.org/). In addition, it also requires [astroquery](https://github.com/astropy/astroquery/), [TAP Gaia Query](https://github.com/mbonav/tapGaia), and [scikit-image](https://scikit-image.org/docs/0.25.x/user_guide/install.html). TAP might require the installation of [lxml](https://lxml.de/).\n\nThe current version is guaranteed to work with the following versions of these packages:\n* numpy \u003c= v1.18.1;\n* scipy \u003c= v1.6.1;\n* pandas \u003c= v1.1.4;\n* matplotlib \u003c= v3.3.4;\n* astropy \u003c= v4.3.1;\n* astroquery \u003c= v0.4.7;\n* h5py \u003c= v3.2.1;\n* tap \u003c= v0.1;\n* lxml \u003c= v4.6.3;\n* scikit-image \u003c= v0.25.\n\nFor the moment being, the only known compatibility issue is related to astroquery, which we explicitly require to be \u003c= v0.4.7 during installation. Additional version requirements will be introduced in future releases if any compatibility issue arises.\n\n\nExamples\n--------\n\nThe package is fully documented on readthedocs.io:\n\n[https://madys.readthedocs.io/en/latest/](https://madys.readthedocs.io/en/latest/) \n\nand a detailed description of its features, together with several examples of the kind of scientific results that can be obtained with it, is provided in [Squicciarini \u0026 Bonavita (2022)](https://ui.adsabs.harvard.edu/abs/2022A%26A...666A..15S/abstract).\n\nWe recommend you check out the [examples](https://github.com/vsquicciarini/madys/blob/main/examples/) provided and the [docs](https://madys.readthedocs.io/en/latest/), for a better understanding of its usage.\n\nIf you find a bug or want to suggest improvements, please create a [ticket](https://github.com/vsquicciarini/madys/issues).\n\n\nRecent papers using `MADYS`:\n-----------------------\n\n`MADYS` has already been employed, starting from its preliminary forms, in several publications, including: \n\n* `Disk Evolution Study Through Imaging of Nearby Young Stars (DESTINYS): V721 CrA and BN CrA have wide and structured disks in polarised IR`, [Columba et al. 2025, arXiv:2511.01717](https://ui.adsabs.harvard.edu/abs/2025arXiv251101717C/abstract)\n* `The SPHERE infrared survey for exoplanets (SHINE): IV. Complete observations, data reduction and analysis, detection performances, and final results`, [Chomez et al. 2025, A\u0026A 697, A99](https://ui.adsabs.harvard.edu/abs/2025A%26A...697A..99C/abstract)\n* `The COBREX archival survey: Improved constraints on the occurrence rate of wide-orbit substellar companions: I. A uniform re-analysis of 400 stars from the GPIES survey`, [Squicciarini et al. 2025, A\u0026A 693, A54](https://ui.adsabs.harvard.edu/abs/2025A%26A...693A..54S/abstract)\n* `Population of giant planets around B stars from the first part of the BEAST survey`, [Delorme et al. 2024, A\u0026A 692, A263](https://ui.adsabs.harvard.edu/abs/2024A%26A...692A.263D/abstract)\n* `Young stellar objects from the LAMOST and ZTF surveys: Physical properties, classification, and light curve analysis`, [Zhang et al. 2024, A\u0026A 686, A269](https://ui.adsabs.harvard.edu/abs/2024A%26A...686A.269Z/abstract)\n* `An imaged 15 MJup companion within a hierarchical quadruple system`, [Chomez et al. 2023, A\u0026A 676, L10](https://ui.adsabs.harvard.edu/abs/2023A%26A...676L..10C/abstract)\n* `BEAST detection of a brown dwarf and a low-mass stellar companion around the young bright B star HIP 81208`, [Viswanath et al. 2023, A\u0026A 675, A54](https://ui.adsabs.harvard.edu/abs/2023A%26A...676L..10C/abstract)\n* `Resolved near-UV hydrogen emission lines at 40-Myr super-Jovian protoplanet Delorme 1 (AB)b. Indications of magnetospheric accretion`, [Ringqvist et al. 2023, A\u0026A 669, L12](https://ui.adsabs.harvard.edu/abs/2023A%26A...669L..12R/abstract)\n* `Detecting planetary mass companions near the water frost-line using JWST interferometry`, [Ray et al. 2023, MNRAS 519, 2718](https://ui.adsabs.harvard.edu/abs/2023MNRAS.519.2718R/abstract)\n* `A scaled-up planetary system around a supernova progenitor`, [Squicciarini et al. 2022, A\u0026A 664, A9](https://ui.adsabs.harvard.edu/abs/2022A%26A...664A...9S/abstract)\n* `Results from The COPAINS Pilot Survey: four new brown dwarfs and a high companion detection rate for accelerating stars`, [Bonavita et al. 2022, MNRAS 513, 5588](https://ui.adsabs.harvard.edu/abs/2022MNRAS.513.5588B/abstract)\n* `A wide-orbit giant planet in the high-mass b Centauri binary system`, [Janson et al. 2021, Natur.600..231J](https://ui.adsabs.harvard.edu/abs/2021Natur.600..231J/abstract)\n* `Unveiling the star formation history of the Upper Scorpius association through its kinematics`, [Squicciarini et al. 2021, MNRAS 507, 1381](https://ui.adsabs.harvard.edu/abs/2021MNRAS.507.1381S/abstract)\n* `New binaries from the SHINE survey`, [Bonavita et al. 2021, arXiv210313706B](https://ui.adsabs.harvard.edu/abs/2021arXiv210313706B/abstract)\n* `BEAST begins: sample characteristics and survey performance of the B-star Exoplanet Abundance Study`, [Janson, Squicciarini et al. 2021, A\u0026A 646, A164](https://ui.adsabs.harvard.edu/abs/2021A%26A...646A.164J/abstract)\n\nAuthors\n-----------------------\n[Vito Squicciarini](https://orcid.org/0000-0002-3122-6809), University of Exeter, UK (v.squicciarini@exeter.ac.uk)\n\n[Mariangela Bonavita](https://orcid.org/0000-0002-7520-8389), The Open University, UK\n\nWe are grateful for your effort, and hope that these tools will contribute to your scientific work and discoveries. Please feel free to report any bug or possible improvement to the authors.\n\nAttribution\n-----------------------\nPlease cite [Squicciarini \u0026 Bonavita (2022)](https://ui.adsabs.harvard.edu/abs/2022A%26A...666A..15S/abstract) whenever you publish results obtained with `MADYS`.\n\nAcknowledgements\n-----------------------\nWe would like to thank Raffaele Gratton, Antoine Chomez, Sebastian Marino, Kellen Lawson, Aarynn Carter, Giovanni Strampelli for the insightful discussions and the useful tips that contributed to the improvement of this tool.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvsquicciarini%2Fmadys","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvsquicciarini%2Fmadys","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvsquicciarini%2Fmadys/lists"}