{"name":"napari-nanopyx","display_name":"napari NanoPyx","visibility":"public","icon":"","categories":[],"schema_version":"0.2.0","on_activate":null,"on_deactivate":null,"contributions":{"commands":[{"id":"napari-nanopyx.benchmark","title":"Benchmark Liquid Engine methods","python_name":"napari_nanopyx.benchmarking:benchmark_nanopyx","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-nanopyx.estimate_drift_alignment","title":"Estimate Drift Alignment","python_name":"napari_nanopyx.drift_alignment:estimate_drift_alignment","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-nanopyx.apply_drift_alignment","title":"Apply Drift Alignment","python_name":"napari_nanopyx.drift_alignment:apply_drift_alignment","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-nanopyx.estimate_channel_registration","title":"Estimate Channel Registration","python_name":"napari_nanopyx.channel_registration:estimate_channel_registration","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-nanopyx.apply_channel_registration","title":"Apply Channel Registration","python_name":"napari_nanopyx.channel_registration:apply_channel_registration","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-nanopyx.generate_srrf_image","title":"Generate SRRF Image","python_name":"napari_nanopyx.srrf:generate_srrf_image","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-nanopyx.calculate_frc","title":"Calculate FRC","python_name":"napari_nanopyx.squirrel:calculate_frc","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-nanopyx.calculate_decorr_analysis","title":"Calculate Decorrelation Analysis","python_name":"napari_nanopyx.squirrel:calculate_decorr_analysis","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-nanopyx.calculate_error_map","title":"Calculate Error Map","python_name":"napari_nanopyx.squirrel:calculate_error_map","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-nanopyx.generate_esrrf_image","title":"Generate eSRRF Image","python_name":"napari_nanopyx.esrrf:generate_esrrf_image","short_title":null,"category":null,"icon":null,"enablement":null}],"readers":null,"writers":null,"widgets":[{"command":"napari-nanopyx.benchmark","display_name":"Benchmark Liquid Engine methods","autogenerate":false},{"command":"napari-nanopyx.estimate_drift_alignment","display_name":"Estimate Drift Correction","autogenerate":false},{"command":"napari-nanopyx.apply_drift_alignment","display_name":"Apply Drift Correction","autogenerate":false},{"command":"napari-nanopyx.estimate_channel_registration","display_name":"Estimate Channel Alignment","autogenerate":false},{"command":"napari-nanopyx.apply_channel_registration","display_name":"Apply Channel Alignment","autogenerate":false},{"command":"napari-nanopyx.generate_srrf_image","display_name":"Generate SRRF Image","autogenerate":false},{"command":"napari-nanopyx.calculate_frc","display_name":"Calculate FRC","autogenerate":false},{"command":"napari-nanopyx.calculate_decorr_analysis","display_name":"Calculate Decorrelation Analysis","autogenerate":false},{"command":"napari-nanopyx.calculate_error_map","display_name":"Calculate Error Map","autogenerate":false},{"command":"napari-nanopyx.generate_esrrf_image","display_name":"Generate eSRRF Image","autogenerate":false}],"sample_data":null,"themes":null,"menus":{},"submenus":null,"keybindings":null,"configuration":[]},"package_metadata":{"metadata_version":"2.1","name":"napari-nanopyx","version":"0.1.4","dynamic":null,"platform":null,"supported_platform":null,"summary":"napari plugin of Nanoscopy Python library (NanoPyx, the successor to NanoJ) - focused on light microscopy and super-resolution imaging","description":"# napari-nanopyx\n\n<img src=\"https://github.com/HenriquesLab/NanoPyx/blob/main/.github/logo.png\" align=\"right\" width=\"230\"/>\n\n[![License](https://img.shields.io/github/license/HenriquesLab/NanoPyx?color=Green)](https://github.com/HenriquesLab/NanoPyx/blob/main/LICENSE.txt)\n[![PyPI](https://img.shields.io/pypi/v/napari-nanopyx.svg?color=green)](https://pypi.org/project/napari-nanopyx)\n[![Python Version](https://img.shields.io/pypi/pyversions/napari-nanopyx.svg?color=green)](https://python.org)\n[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-nanopyx)](https://napari-hub.org/plugins/napari-nanopyx)\n[![Docs](https://img.shields.io/badge/documentation-link-blueviolet)](https://github.com/HenriquesLab/napari-NanoPyx/wiki/3.-Methods)\n[![Wiki](https://img.shields.io/badge/wiki-click_me-blue)](https://github.com/HenriquesLab/napari-NanoPyx/wiki)\n\nnapari plugin of [NanoPyx](https://github.com/HenriquesLab/NanoPyx) (the successor to NanoJ) - focused on light microscopy and super-resolution imaging.\n\n----------------------------------\n\nThis [napari] plugin was generated with [Cookiecutter] using [@napari]'s [cookiecutter-napari-plugin] template.\n\n## What is the NanoPyx 🔬 Library?\n\nNanoPyx is a library specialized in the analysis of light microscopy and super-resolution data.\nIt is a successor to [NanoJ](https://github.com/HenriquesLab/NanoJ-Core), which is a Java library for the analysis of super-resolution microscopy data.\n\nNanoPyx focuses on performance, by heavily exploiting cython aided multiprocessing and simplicity. It implements methods for the bioimage analysis field, with a special emphasis on those developed by the [Henriques Laboratory](https://henriqueslab.github.io/).\nIt will be distributed as a Python Library and also as [Codeless Jupyter Notebooks](https://github.com/HenriquesLab/NanoPyx#codeless-jupyter-notebooks-available), that can be run locally or on Google Colab, and as a [napari plugin](https://github.com/HenriquesLab/napari-NanoPyx).\n\nYou can read more about NanoPyx in our [preprint](https://www.biorxiv.org/content/10.1101/2023.08.13.553080v1).\n\nCurrently it implements the following approaches:\n- A reimplementation of the NanoJ image registration, SRRF and Super Resolution metrics\n- eSRRF\n- Non-local means denoising\n- More to come soon™\n\nif you found this work useful, please cite: [preprint](https://www.biorxiv.org/content/10.1101/2023.08.13.553080v1) and  [![DOI](https://zenodo.org/badge/505388398.svg)](https://zenodo.org/badge/latestdoi/505388398)\n\n## Installation\n\nYou can install `napari-nanopyx` via [pip]:\n\n    pip install napari-nanopyx\n\n## User Documentation\n\nYou can find installation and usage instructions in the [wiki](https://github.com/HenriquesLab/napari-NanoPyx/wiki).\n\n## Contributing\n\nContributions are very welcome.\nPlease read our [Contribution Guidelines](https://github.com/HenriquesLab/NanoPyx/blob/main/CONTRIBUTING.md) to know how to proceed.\n\n## License\n\nDistributed under the terms of the [CC-By v4.0] license,\n\"napari-nanopyx\" is free and open source software\n\n## Issues\n\nIf you encounter any problems, please [file an issue] along with a detailed description.\n\n[napari]: https://github.com/napari/napari\n[Cookiecutter]: https://github.com/audreyr/cookiecutter\n[@napari]: https://github.com/napari\n[MIT]: http://opensource.org/licenses/MIT\n[BSD-3]: http://opensource.org/licenses/BSD-3-Clause\n[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt\n[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt\n[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0\n[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt\n[CC-By v4.0]: https://creativecommons.org/licenses/by/4.0/\n[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin\n\n[napari]: https://github.com/napari/napari\n[tox]: https://tox.readthedocs.io/en/latest/\n[pip]: https://pypi.org/project/pip/\n[PyPI]: https://pypi.org/\n\n## Citing\n\nIf you found this work useful, please cite: [preprint](https://www.biorxiv.org/content/10.1101/2023.08.13.553080v1) and  [![DOI](https://zenodo.org/badge/505388398.svg)](https://zenodo.org/badge/latestdoi/505388398)\n","description_content_type":"text/markdown","keywords":null,"home_page":null,"download_url":null,"author":"Ricardo Henriques, Bruno Saraiva, Inês Cunha, António Brito","author_email":"bruno.msaraiva2@gmail.com","maintainer":null,"maintainer_email":null,"license":"LGPL-3.0-only","classifier":["Development Status :: 2 - Pre-Alpha","Framework :: napari","Intended Audience :: Developers","License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)","Operating System :: OS Independent","Programming Language :: Python","Programming Language :: Python :: 3","Topic :: Software Development :: Testing"],"requires_dist":["napari","nanopyx >=0.3.1","scikit-image","magicgui","pytest ; extra == 'testing'","pytest-cov ; extra == 'testing'"],"requires_python":">=3.9","requires_external":null,"project_url":["Bug Tracker, https://github.com/HenriquesLab/napari-NanoPyx/issues","Documentation, https://github.com/HenriquesLab/napari-NanoPyx/wiki","Source Code, https://github.com/HenriquesLab/napari-NanoPyx","User Support, https://github.com/HenriquesLab/napari-NanoPyx/issues"],"provides_extra":["testing"],"provides_dist":null,"obsoletes_dist":null},"npe1_shim":false}