Release 1.0.8

Release 1.0.8 of pydfc toolbox.

HIGHLIGHTS

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• Add fuzzy concept to state-based methods
• Add transform to KMeansCustom
• Make KMeansCustom faster
• Add more flexibility to data_loader nifti functions
• Make SW and SWC and DHMM faster in parallel
• Discard few samples with few frequencies at the beginning and end of TF dFC and average only over frequencies that exist (not those parts in cone on influence)
• nilearn version is pinned to 0.10.2 in dependencies, addressing the label decoding error when loading BOLD data using data_loader

Release 1.0.7

Release 1.0.7 of pydfc toolbox.

HIGHLIGHTS

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• Some bugs in sliding window technique's window definition are solved.
• GraphLasso (Graphical Lasso) has been added besides pear_corr as sw_method
• Now you can set the clstr_distance parameter in Sliding Window + Clustering technique to manhattan. Previously euclidean was the only option.

Release 1.0.5

Release 1.0.5 of pydfc toolbox.

HIGHLIGHTS

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• Some bugs in sliding window technique's window definition are solved.
• GraphLasso (Graphical Lasso) has been added besides pear_corr as sw_method
• Now you can set the clstr_distance parameter in Sliding Window + Clustering technique to manhattan. Previously euclidean was the only option.

Release 1.0.3

Release 1.0.3 of pydfc toolbox.

HIGHLIGHTS

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• You can easily install the toolbox by following the instructions in README.rst.
• The dFC_methods_demo.ipynb illustrates how to assess dFC using each of the methods implemented in the toolbox.
• The multi_analysis_demo.ipynb illustrates how to use the toolbox for applying multiple dFC methods together and assessing analytical flexibility.

Release 1.0.2

Release 1.0.2 of pydfc toolbox.

HIGHLIGHTS

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• You can easily install the toolbox by following the instructions in README.rst.
• The dFC_methods_demo.ipynb illustrates how to assess dFC using each of the methods implemented in the toolbox.
• The multi_analysis_demo.ipynb illustrates how to use the toolbox for applying multiple dFC methods together and assessing analytical flexibility.

Release 1.0.1

Release 1.0.1 of pydfc toolbox.

HIGHLIGHTS

---

• You can easily install the toolbox by following the instructions in README.rst.
• The dFC_methods_demo.ipynb illustrates how to assess dFC using each of the methods implemented in the toolbox.
• The multi_analysis_demo.ipynb illustrates how to use the toolbox for applying multiple dFC methods together and assessing analytical flexibility.

Release 1.0.0

The first release of pydfc toolbox.

HIGHLIGHTS

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• You can easily install the toolbox by following the instructions in README.rst.
• The dFC_methods_demo.ipynb illustrates how to assess dFC using each of the methods implemented in the toolbox.
• The multi_analysis_demo.ipynb illustrates how to use the toolbox for applying multiple dFC methods together and assessing analytical flexibility.