2828of the FOOOF approach is that these peaks are characterized in terms of their specific center
2929frequency, amplitude and bandwidth without requiring predefining specific bands of interest.
3030In particular, it separates these peaks from a dynamic, and independently interesting 1/f
31- background. This conception of the 1/f as potentially functional (and therefore worth carefully
31+ background. This conception of the 1/f as potenhttps://github.com/voytekresearch/fooof/releasestially functional (and therefore worth carefully
3232modeling) is based on work from the Voytek lab and others that collectively shows that 1/f changes
3333across task demands and participant demographics, and that it may index underlying
3434excitation/inhibition (EI) balance.
5050 long_description = long_description ,
5151 author = 'The Voytek Lab' ,
5252 author_email = 'voyteklab@gmail.com' ,
53- url = 'https://github.com/voytekresearch /fooof' ,
53+ url = 'https://github.com/fooof-tools /fooof' ,
5454 packages = find_packages (),
5555 license = 'Apache License, 2.0' ,
5656 classifiers = [
6767 'Programming Language :: Python :: 3.6' ,
6868 'Programming Language :: Python :: 3.7'
6969 ],
70- download_url = 'https://github.com/voytekresearch/fooof/releases ' ,
70+ download_url = '' ,
7171 keywords = ['neuroscience' , 'neural oscillations' , 'power spectra' , '1/f' , 'electrophysiology' ],
7272 install_requires = ['numpy' , 'scipy>=0.19.0' ],
7373 tests_require = ['pytest' ],
7676 'tests' : ['pytest' ],
7777 'all' : ['matplotlib' , 'tqdm' , 'pytest' ]
7878 }
79- )
79+ )
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