From 2b6c217eec4d0cb72c44eb2ff1ad23c14030a8e1 Mon Sep 17 00:00:00 2001 From: MOHAMMAD TORABI <72619172+mtorabi59@users.noreply.github.com> Date: Tue, 28 Nov 2023 06:43:05 +0330 Subject: [PATCH] Update README.rst --- README.rst | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/README.rst b/README.rst index 29b1e45..178c933 100644 --- a/README.rst +++ b/README.rst @@ -1,18 +1,18 @@ .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.10161177.svg :target: https://doi.org/10.5281/zenodo.10161177 -dFC +pydfc ======= -An implementation of several well-known dynamic Functional Connectivity assessment methods. +An implementation of several well-known dynamic Functional Connectivity (dFC) assessment methods. Simply do these steps in the main repository directory to learn how to use the dFC functions: - * ``conda create --name multi_analysis_dfc_env python=3.8.5`` - * ``conda activate multi_analysis_dfc_env`` + * ``conda create --name pydfc_env python=3.11`` + * ``conda activate pydfc_env`` * ``pip install -e '.'`` * run the code cells in demo jupyter notebooks -The ``dFC_methods_demo.ipynb`` illustrates how to load data and apply each of the implemented dFC methods individually. -The ``multi_analysis_demo.ipynb`` illustrates how to use the ``multi_analysis_dfc`` toolbox to apply multiple dFC methods at the same time on a dataset and compare their results. +The ``dFC_methods_demo.ipynb`` illustrates how to load data and apply each of the dFC methods implemented in the ``pydfc`` toolbox individually. +The ``multi_analysis_demo.ipynb`` illustrates how to use the ``pydfc`` toolbox to apply multiple dFC methods at the same time on a dataset and compare their results. For more details about the implemented methods and the comparison analysis see `our paper `_.