{"id":18730712,"url":"https://github.com/simonrp84/pycoxmunk","last_synced_at":"2025-04-12T17:33:46.461Z","repository":{"id":37382666,"uuid":"300246933","full_name":"simonrp84/PyCoxMunk","owner":"simonrp84","description":"Python package for estimating sea surface reflectance.","archived":false,"fork":false,"pushed_at":"2025-03-21T09:34:07.000Z","size":5056,"stargazers_count":9,"open_issues_count":1,"forks_count":2,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-11T11:48:08.976Z","etag":null,"topics":["earth-observation","oceanography","reflectance","remote-sensing","satellite"],"latest_commit_sha":null,"homepage":"https://pycoxmunk.readthedocs.io/en/latest/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/simonrp84.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2020-10-01T10:59:19.000Z","updated_at":"2025-03-21T09:34:08.000Z","dependencies_parsed_at":"2024-01-22T20:15:54.678Z","dependency_job_id":"087a92d0-242a-49e7-bdce-5737bf7cdd8a","html_url":"https://github.com/simonrp84/PyCoxMunk","commit_stats":{"total_commits":145,"total_committers":3,"mean_commits":"48.333333333333336","dds":"0.17931034482758623","last_synced_commit":"903ed09c1f4fd5f697ecd753401d3c8cf5be92d6"},"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simonrp84%2FPyCoxMunk","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simonrp84%2FPyCoxMunk/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simonrp84%2FPyCoxMunk/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/simonrp84%2FPyCoxMunk/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/simonrp84","download_url":"https://codeload.github.com/simonrp84/PyCoxMunk/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248605555,"owners_count":21132191,"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":["earth-observation","oceanography","reflectance","remote-sensing","satellite"],"created_at":"2024-11-07T14:44:54.435Z","updated_at":"2025-04-12T17:33:46.435Z","avatar_url":"https://github.com/simonrp84.png","language":"Python","readme":"\n[![PyCoxMunk Tests](https://github.com/simonrp84/PyCoxMunk/workflows/Tests/badge.svg)](https://github.com/simonrp84/PyCoxMunk/actions)\n[![codecov](https://codecov.io/gh/simonrp84/PyCoxMunk/branch/main/graph/badge.svg?token=4GMLURHA5V)](https://codecov.io/gh/simonrp84/PyCoxMunk)\n\nPyCoxMunk\n=========\n\n### A python library for simulating satellite-viewed sea surface reflectances.\n\nThe pycoxmunk library computes the sea surface reflectance, using the \n[Cox-Munk method](https://doi.org/10.1364/JOSA.44.000838), as expected to be seen from space based on the satellite and \nweather conditions at the sea surface. A description of the algorithm and this library are given in \n[this paper](https://joss.theoj.org/papers/10.21105/joss.05074.pdf), published in the \n[Journal of Open Source Software](https://joss.theoj.org/).\n\nThe main purpose of this library is to enable an easy method for computing sea surface reflectance that is applicable\nto a wide variety of low-earth and geostationary orbit satellites and sensors. The library is closely linked to the \n[satpy library](https://github.com/pytroll/satpy) that loads, calibrates and produces projection information for many \nsatellites. Under the hood, pycoxmunk uses [dask](https://github.com/dask/dask) and \n[xarray](https://github.com/pydata/xarray) to store and process data. Results are made available via the same `satpy` \nscene used to provide the input satellite images.\n\nAs well as computing the sea surface reflectance, pycoxmunk can also compute the four BRDF terms, which can be useful in\nradiative transfer, cloud and aerosol properties retrieval codes, and other uses such as cloud or sea ice detection.\n\nInstallation\n------------\n\npycoxmunk can be installed from PyPI with pip:\n\n```bash\n    pip install pycoxmunk\n```\n\nIt is also available from `conda-forge` for conda installations:\n\n```bash\n    conda install -c conda-forge pycoxmunk\n```\n\nTests\n-----\n\npycoxmunk comes with a set of scripts for testing the functionality of the library. These are located in the `./Tests/`\nsubdirectory and can be run using `pytest`:\n\n```\n\ncd Tests\npytest .\n\n```\n\nThis will run all tests. You can also run just a single test script with, for example, `pytest test_CMCalcs.py`.\nYou may first need to install pytest via: `conda install pytest`.\n\nOnce testing is complete, a summary will be displayed. This should indicate that all tests have passed, as well as\npotentially listing some warnings depending on your environment and the current status of `pycoxmunk`'s dependencies.\n\nCredits\n-------\n\nThis code was written by Simon Proud and is based on a fortran implementation of the Cox-Munk algorithm written by \nGreg McGarragh as part of the [ORAC algorithm](https://github.com/ORAC-CC/orac).\n\nFeedback and Contribution\n-------------------------\n\nFeedback, suggestions, bug reports or any other type of contribution is welcome.\n\nIf you encounter any problems with this code or the documentation then please file an \n[issue](https://github.com/simonrp84/PyCoxMunk/issues).\nIt may help in debugging any problems to enable satpy's debug mode:\n\n\n```python\n    from satpy import debug_on\n    debug_on()\n```\n\nThis will print additional log and diagnostic information.\n\nSuggestions for new features are welcome, but may not always be possible for me to code due to limited time. You can\nalso submit your own [pull requests](https://github.com/simonrp84/PyCoxMunk/pulls) that add features of fix bugs. \nThis is the recommended way to change the library code, rather than emailing me your updates. \nBy submitting a pull request please ensure that your code changes and additions are documented and, where appropriate, \ncovered by tests.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsimonrp84%2Fpycoxmunk","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsimonrp84%2Fpycoxmunk","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsimonrp84%2Fpycoxmunk/lists"}