Metadata-Version: 2.5
Name: bioimageflow-spot-tools
Version: 0.2.0
Summary: Spot detection and puncta quantification tools for BioImageFlow
Project-URL: Homepage, https://github.com/Inria-SAIRPICO/bioimageflow
Project-URL: Documentation, https://bioimageflow.readthedocs.io/latest/
Project-URL: Repository, https://github.com/Inria-SAIRPICO/bioimageflow
Project-URL: Issues, https://github.com/Inria-SAIRPICO/bioimageflow/issues
Author: BioImageFlow Contributors
License-Expression: BSD-4-Clause
License-File: LICENSE
Keywords: bioimage-analysis,bioimageflow,microscopy,workflow
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Image Processing
Requires-Python: >=3.10
Requires-Dist: bioimageflow-core<0.4,>=0.3.0
Requires-Dist: bioimageflow<1,>=0.1.6
Requires-Dist: imageio>=2.31.0
Requires-Dist: numpy>=1.23.5
Requires-Dist: pandas>=2.0.0
Requires-Dist: scikit-image>=0.21.0
Requires-Dist: scipy>=1.10.0
Description-Content-Type: text/markdown

# bioimageflow-spot-tools

Tools for puncta and spot quantification.

## Tools

- `AtlasSpotDetection`: wraps the external Atlas CLI for adaptive 2D TIFF spot detection.
- `DetectSpots`: detects local maxima after DoG/LoG-compatible filtering and returns one dataframe row per spot plus a label image.
- `AssignSpotsToLabels`: samples a label image at each detected spot coordinate.
- `SpotSummary`: aggregates spot counts and intensities per source and label.
- `FilterSpots`: filters spot dataframe rows by intensity, score, radius, and mask.
- `RenderSpots`: renders coordinate rows to binary mask or label images.
- `SpotsToLabels`: combines spot-coordinate rows into one label image.
- `MaskToLabels`: converts each mask row into a connected-component label image.
- `SpotColocalization`: computes a maximum-cardinality, minimum-total-distance one-to-one match between two spot tables.
- `SpotQualityMetrics`: computes annular-background SNR and indexed nearest-neighbor distances.

ATLAS is the primary external spot detection method used by the FISH and parameter-space exploration workflows.
The local spot table utilities support assignment, rendering, filtering, and summary after detection.
All coordinate consumers use finite `(y, x)` values and the same nearest-pixel rule: exact half values round upward.

## Example

See the FISH spot-counting and parameter-space exploration workflows in the main workflow catalog.
