diff --git a/README.rst b/README.rst index 97d3920d..de4ae0b0 100644 --- a/README.rst +++ b/README.rst @@ -7,14 +7,17 @@ Overview ======== -``dynsight`` is structured to support a wide range of tasks commonly -encountered in the analysis of many-body dynamical systems. These tasks -include handling trajectory data, computing single-particle descriptors, -performing time-series clustering and conducting various auxiliary analyses. -To achieve this, dynsight is organized into specialized modules, each -addressing a specific aspect of this workflow. - -Previously in `cpctools`_. +``dynsight`` is an open platform for supporting a wide range of tasks commonly +encountered in the trajectory and data analysis of complex dynamical systems, essentially related +to the extraction of relevant information from data obtained from trajectories. +To achieve this, ``dynsight`` is organized into specialized modules, each addressing a +specific aspect of this workflow. For example, ``dynsight`` includes modules for, e.g., +resolving trajectory data from movies (experimental: e.g., object recognition and tracking), +handling trajectory data (from simulations and experiments), computing single-particle descriptors, +performing time-series clustering, maximum information extraction from data, and conducting +various auxiliary analyses. + +A bounce of all this was previously in `cpctools`_. .. _`cpctools`: https://github.com/GMPavanLab/cpctools @@ -28,7 +31,7 @@ To get ``dynsight``, you can install it with pip:: Optional Dependancies --------------------- -Old versions ``dynsight`` used ``cpctools`` for SOAP calculations, if +Old versions of ``dynsight`` used ``cpctools`` for SOAP calculations: if you are using Python 3.10 and below, you can use ``cpctools`` to access ``SOAPify`` and ``hd5er`` using :: @@ -93,25 +96,24 @@ and TBD * Most modules also use MDAnalysis, https://www.mdanalysis.org/pages/citations/ -* If you use SOAP, please cite https://doi.org/10.1103/PhysRevB.87.184115 and DScribe https://singroup.github.io/dscribe/latest/citing.html -* If you use timeSOAP, please cite https://doi.org/10.1063/5.0147025 -* If you use LENS, please cite: https://doi.org/10.1073/pnas.2300565120 -* If you use onion-clustering, please cite: https://doi.org/10.1073/pnas.2403771121 -* If you use tICA, please cite ``deeptime`` https://deeptime-ml.github.io/latest/index.html -* If you use ``dynsight.vision``, please cite Ultralytics YOLO https://docs.ultralytics.com/it/models/yolo11/#usage-examples -* If you use ``dynsight.track``, please cite Trackpy https://soft-matter.github.io/trackpy/dev/introduction.html +* If you use SOAP, please cite also original references: https://doi.org/10.1103/PhysRevB.87.184115 and DScribe https://singroup.github.io/dscribe/latest/citing.html +* If you use TimeSOAP, please cite also original reference: https://doi.org/10.1063/5.0147025 +* If you use LENS, please cite also original reference: https://doi.org/10.1073/pnas.2300565120 +* If you use onion-clustering, please cite also original reference: https://doi.org/10.1073/pnas.2403771121 +* If you use tools to calculate Information Gain and Maximum Information Extraction, please cite also original reference: https://doi.org/10.48550/arXiv.2504.12990 +* If you use tICA, please cite also original ``deeptime`` reference: https://deeptime-ml.github.io/latest/index.html +* If you use ``dynsight.vision``, please cite also original ``Ultralytics YOLO`` reference: https://docs.ultralytics.com/it/models/yolo11/#usage-examples +* If you use ``dynsight.track``, please cite also original ``Trackpy`` reference: https://soft-matter.github.io/trackpy/dev/introduction.html Acknowledgements ================ -We developed this code when working in the Pavan group, -https://www.gmpavanlab.polito.it/, whose members often provide very valuable -feedback, which we gratefully acknowledge. +This code is developed by the G.M. Pavan group, https://www.gmpavanlab.polito.it/, +whose members often provide very valuable feedback, which we gratefully acknowledge. Much of the original code in ``cpctools`` was written by Daniele Rapetti (Iximiel). -The work was funded by the European Union and ERC under projects DYNAPOL and the -NextGenerationEU project, CAGEX. +This work was primarily supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant Agreement no. 818776- DYNAPOL), and also partially by the European Union under the NextGenerationEU program (grant CAGEX, SOE_0000033). .. figure:: docs/source/_static/EU_image.png