{"name":"napari-flowreg-formats","display_name":"FlowReg Formats","visibility":"public","icon":null,"categories":[],"schema_version":"0.1.0","on_activate":null,"on_deactivate":null,"contributions":{"commands":[{"id":"napari-flowreg-formats.get_reader","title":"Read a microscopy recording","python_name":"napari_flowreg_formats.reader:napari_get_reader","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-flowreg-formats.write_hdf5","title":"Save as FlowReg HDF5","python_name":"napari_flowreg_formats.writer:write_hdf5","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-flowreg-formats.write_mat","title":"Save as MATLAB MAT","python_name":"napari_flowreg_formats.writer:write_mat","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-flowreg-formats.write_tiff","title":"Save as TIFF","python_name":"napari_flowreg_formats.writer:write_tiff","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-flowreg-formats.import_widget","title":"Open the FlowReg import dialog","python_name":"napari_flowreg_formats.import_widget:FlowRegImportWidget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-flowreg-formats.export_widget","title":"Open the FlowReg export dialog","python_name":"napari_flowreg_formats.export_widget:FlowRegExportWidget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-flowreg-formats.open_import","title":"FlowReg Import...","python_name":"napari_flowreg_formats.import_widget:show_import_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-flowreg-formats.open_export","title":"FlowReg Export...","python_name":"napari_flowreg_formats.export_widget:show_export_widget","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-flowreg-formats.sample_2d","title":"Generate a synthetic 2D time series","python_name":"napari_flowreg_formats._sample_data:make_sample_2d","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-flowreg-formats.sample_3d","title":"Generate a synthetic 3D volume time series","python_name":"napari_flowreg_formats._sample_data:make_sample_3d","short_title":null,"category":null,"icon":null,"enablement":null}],"readers":[{"command":"napari-flowreg-formats.get_reader","filename_patterns":["*.tif","*.tiff","*.btf","*.tf8","*.tf2","*.h5","*.hdf5","*.hdf","*.mat","*.mdf"],"accepts_directories":false}],"writers":[{"command":"napari-flowreg-formats.write_hdf5","layer_types":["image+"],"filename_extensions":[".h5",".hdf5",".hdf"],"display_name":"FlowReg HDF5"},{"command":"napari-flowreg-formats.write_mat","layer_types":["image+"],"filename_extensions":[".mat"],"display_name":"MATLAB MAT"},{"command":"napari-flowreg-formats.write_tiff","layer_types":["image+"],"filename_extensions":[".tif",".tiff"],"display_name":"TIFF"}],"widgets":[{"command":"napari-flowreg-formats.import_widget","display_name":"FlowReg Import","autogenerate":false},{"command":"napari-flowreg-formats.export_widget","display_name":"FlowReg Export","autogenerate":false}],"sample_data":[{"command":"napari-flowreg-formats.sample_2d","key":"synthetic-2d","display_name":"Synthetic 2P recording (2D + time)"},{"command":"napari-flowreg-formats.sample_3d","key":"synthetic-3d","display_name":"Synthetic 2P recording (3D volumes + time)"}],"themes":null,"menus":{"napari/file/io_utilities":[{"command":"napari-flowreg-formats.open_import","when":null,"group":null,"alt":null},{"command":"napari-flowreg-formats.open_export","when":null,"group":null,"alt":null}]},"submenus":null,"keybindings":null,"configuration":[]},"package_metadata":{"metadata_version":"2.4","name":"napari-flowreg-formats","version":"0.1.0a1","dynamic":["license-file"],"platform":null,"supported_platform":null,"summary":"napari reader and writer plugin for 2-photon microscopy formats (TIFF/ScanImage, HDF5, MAT, MDF)","description":"[](https://pypi.org/project/napari-flowreg-formats/)\n[](https://pypi.org/project/napari-flowreg-formats/)\n[](LICENSE.txt)\n[](https://pypistats.org/packages/napari-flowreg-formats)\n[](https://pepy.tech/projects/napari-flowreg-formats)[](https://github.com/FlowRegSuite/napari-flowreg-formats/actions/workflows/test.yml)\n[](https://napari-flowreg-formats.readthedocs.io/en/latest/?badge=latest)\n\n# ![\"FlowReg](\"https://raw.githubusercontent.com/FlowRegSuite/napari-flowreg-formats/HEAD/img/flowreglogo.png\")
napari-FlowReg-Formats\n\nThis repository contains the file format support for the Flow-Registration toolbox in napari. It reads and writes the microscopy formats used across the FlowRegSuite through the `pyflowreg` and `flowreg3d` I/O layers, so a recording that opens here opens identically in the motion correction pipeline.\n\n**Everything works out of the box.** Drag a recording into napari and it opens: **TIFF** (including **ScanImage**, **OME-TIFF**, **ImageJ hyperstacks** and **BigTIFF**), **HDF5**, **MATLAB MAT** in both the classic and the **v7.3** container, and **Sutter MDF**. **MAT and HDF5 videos work in both 2D and 3D**, including multi-channel recordings, volumetric time series, and the MATLAB axis order that older Flow-Registration data is written in. The structure is detected from the file itself, so no configuration is needed for the common cases.\n\nRecordings load lazily, so a volumetric stack larger than memory can be inspected frame by frame. An import dialog covers what automatic detection cannot settle on its own: 2D against 3D interpretation, axis order, which datasets are channels, and folding a flat ScanImage page sequence into `(T, Z, Y, X)` volumes.\n\nThe publication for the underlying toolbox can be found [here](https://doi.org/10.1002/jbio.202100330) and the project website with video results [here](https://www.snnu.uni-saarland.de/flow-registration/).\n\n**[Read the Documentation](https://napari-flowreg-formats.readthedocs.io/)**\n\n**Related projects**\n- PyFlowReg: https://github.com/FlowRegSuite/pyflowreg\n- flowreg3D: https://github.com/FlowRegSuite/flowreg3d\n- napari motion correction plugin: https://github.com/FlowRegSuite/napari-flowreg\n- Original Flow-Registration repo: https://github.com/FlowRegSuite/flow_registration\n- ImageJ/Fiji plugin: https://github.com/FlowRegSuite/flow_registration_IJ\n\n\n\n## Installation via pip and conda\n\nTo install the plugin via conda, you can create a new environment and install `napari` along with the plugin:\n\n conda create -n flowreg -c conda-forge python=3.11\n conda activate flowreg\n\nYou can then install `napari-flowreg-formats` via [pip]:\n\n pip install napari[all] napari-flowreg-formats\n\nor directly from the GitHub repository:\n\n pip install git+https://github.com/FlowRegSuite/napari-flowreg-formats.git\n\n`napari` is not a runtime dependency of this package, following napari plugin practice, so install it alongside as shown above.\n\nThe plugin depends on `pyflowreg` and `flowreg3d`, which are currently published as pre-releases. The dependency specifiers name those pre-releases explicitly, so a plain `pip install` resolves them and no `--pre` flag is needed.\n\n## Supported formats\n\n| Family | Extensions | 2D | 3D | Lazy | Auto-detected |\n|---|---|---|---|---|---|\n| **TIFF** | `.tif` `.tiff` | **yes** | **yes** | **yes** | series axes, ImageJ hyperstack structure |\n| **BigTIFF** | `.btf` `.tf8` `.tf2` | **yes** | **yes** | **yes** | as above, without the 4 GB limit |\n| **OME-TIFF** | `.ome.tif` `.ome.tiff` | **yes** | **yes** | **yes** | OME axes, physical pixel size |\n| **ScanImage TIFF** | `.tif` | **yes** | **yes** | **yes** | slices per volume, frames per slice, channels, z step, frame rate |\n| **HDF5** | `.h5` `.hdf5` `.hdf` | **yes** | **yes** | **yes** | dataset discovery, writer provenance, stored axis order |\n| **MATLAB MAT** | `.mat` (v5/v7 and v7.3) | **yes** | **yes** | v7.3 only | variable discovery, MATLAB axis order and dimension reversal |\n| **Sutter MDF** | `.mdf` | **yes** | — | no | acquisition metadata; **Windows only** |\n\nExtension matching is case-insensitive, so `.TIF`, `.H5` and `.MAT` work as written. See the [supported formats reference](https://napari-flowreg-formats.readthedocs.io/en/latest/supported_formats.html) for the full matrix, including the formats this plugin deliberately leaves to others.\n\n## Usage\n\nDrag a recording into napari. For extensions that napari's built-in reader also claims, such as `.tif` and `.h5`, napari shows a reader chooser; select **FlowReg Formats** and tick the box to remember that choice for the extension.\n\nFor explicit control over dimensions, channels and TIFF reshaping, open **File > FlowReg Import** or **Plugins > FlowReg Formats > FlowReg Import**. The dialog reports the detected structure, lets you override every field, and loads off the Qt event loop so the viewer stays responsive.\n\n\n\nAbove, a flat ScanImage page sequence has been probed: the volume structure was read from the acquisition metadata, the recording was identified as a volumetric time series, and the 16 slices per volume were filled in automatically. **Load** applies it; **Copy as Python** emits the equivalent script.\n\nLayers are written back with **File > Save Selected Layers**, or through **File > FlowReg Export** for control over the dataset naming pattern, MATLAB axis order, the MAT container version and compression. Selected layers become the channels of one recording.\n\n\n\nThe same import is available from a script, with no GUI:\n\n```python\nimport napari\nfrom napari_flowreg_formats import ImportSpec, load\n\nviewer = napari.Viewer()\n\n# automatic: the structure is detected from the file\nviewer.open(\"recording.tif\", plugin=\"napari-flowreg-formats\")\n\n# explicit: fold a flat ScanImage page sequence into volumes\nfor data, meta, layer_type in load(\n \"scanimage_volumes.tif\",\n ImportSpec(is_3d=True, slices_per_volume=30, frames_per_slice=1, lazy=\"always\"),\n):\n viewer._add_layer_from_data(data, meta, layer_type)\n\nnapari.run()\n```\n\nThe **Copy as Python** button in the import dialog emits exactly this call for the settings currently on screen, so an interactive import is always reproducible.\n\nTwo synthetic sample recordings are available under **File > Open Sample > FlowReg Formats**, so the plugin can be tried without any data on disk.\n\n## Citation\n\nDetails on the original method and video results can be found [here](https://www.snnu.uni-saarland.de/flow-registration/).\n\nIf you use parts of this code or the plugin for your work, please cite\n\n> \"Pyflowreg,\" (in preparation), 2025.\n\nand\n\n> P. Flotho, S. Nomura, B. Kuhn and D. J. Strauss, \"Software for Non-Parametric Image Registration of 2-Photon Imaging Data,\" J Biophotonics, 2022. [doi:https://doi.org/10.1002/jbio.202100330](https://doi.org/10.1002/jbio.202100330)\n\nBibTeX entry\n```\n@article{flotea2022a,\n author = {Flotho, P. and Nomura, S. and Kuhn, B. and Strauss, D. J.},\n title = {Software for Non-Parametric Image Registration of 2-Photon Imaging Data},\n year = {2022},\n journal = {J Biophotonics},\n doi = {https://doi.org/10.1002/jbio.202100330}\n}\n```\n\n## License\n\nDistributed under the MIT License. See [LICENSE.txt](LICENSE.txt).\n","description_content_type":"text/markdown","keywords":null,"home_page":null,"download_url":null,"author":null,"author_email":"Philipp Flotho ","maintainer":null,"maintainer_email":null,"license":null,"classifier":["Development Status :: 3 - Alpha","Framework :: napari","Intended Audience :: Science/Research","Operating System :: OS Independent","Programming Language :: Python :: 3","Programming Language :: Python :: 3.10","Programming Language :: Python :: 3.11","Programming Language :: Python :: 3.12","Programming Language :: Python :: 3.13","Topic :: Scientific/Engineering :: Image Processing","Topic :: Scientific/Engineering :: Bio-Informatics"],"requires_dist":["pyflowreg>=0.1.0a9","flowreg3d>=0.1.0a1","numpy>=1.24","scipy>=1.10","h5py>=3.10","tifffile>=2024.9.0","dask[array]>=2023.5.0","qtpy","pytest>=7.0; extra == \"testing\"","pytest-cov>=4.0; extra == \"testing\"","pytest-qt; extra == \"testing\"","npe2>=0.7; extra == \"testing\"","cloudpickle; extra == \"testing\"","tomli>=2.0.0; python_version < \"3.11\" and extra == \"testing\"","napari[pyqt6]; extra == \"testing\"","napari[pyqt6]>=0.4.18; extra == \"dev\"","pre-commit; extra == \"dev\"","ruff; extra == \"dev\"","build; extra == \"dev\"","twine; extra == \"dev\"","sphinx~=7.3; extra == \"docs\"","myst-parser; extra == \"docs\"","linkify-it-py; extra == \"docs\"","sphinx-copybutton; extra == \"docs\"","sphinx-design; extra == \"docs\"","sphinxcontrib-bibtex; extra == \"docs\"","pydata-sphinx-theme; extra == \"docs\"","sphinx-autodoc-typehints; extra == \"docs\""],"requires_python":">=3.10","requires_external":null,"project_url":["Homepage, https://github.com/FlowRegSuite/napari-flowreg-formats","Source, https://github.com/FlowRegSuite/napari-flowreg-formats","Tracker, https://github.com/FlowRegSuite/napari-flowreg-formats/issues","Documentation, https://napari-flowreg-formats.readthedocs.io/"],"provides_extra":["testing","dev","docs"],"provides_dist":null,"obsoletes_dist":null},"npe1_shim":false}