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def inject(injector):
#http://nipy.org/nipype/about.html
injector.add('nipype', None, Doi('10.3389/fninf.2011.00013'),
description='Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python',
tags=['implementation'])
#http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/
injector.add('nipype.interfaces', 'fsl', Doi('10.1016/j.neuroimage.2004.07.051'),
description='Advances in functional and structural MR image analysis and implementation as FSL',
tags=['implementation'])
injector.add('nipype.interfaces', 'fsl', Doi('10.1016/j.neuroimage.2008.10.055'),
description='Bayesian analysis of neuroimaging data in FSL',
tags=['implementation'])
injector.add('nipype.interfaces', 'fsl', Doi('10.1016/j.neuroimage.2011.09.015'),
description='FSL.',
tags=['implementation'])
author={Wold, H.},
title={Nonlinear estimation by iterative least squares procedures.},
booktitle={Research Papers in Statistics},
publisher={Wiley}
year={1966},
editor={David, F.},
pages={411--444},
}
"""), description="Principal Component Analysis using the NIPALS algorithm.",
tags=['edu'])
injector.add('mdp.nodes', 'FastICANode.train', Doi('10.1109/72.761722'),
description="Independent Component Analysis using the FastICA algorithm",
tags=['implementation'])
injector.add('mdp.nodes', 'CuBICANode.train', Doi('10.1109/TSP.2004.826173'),
description='Independent Component Analysis using the CuBICA algorithm.',
tags=['implementation'])
injector.add('mdp.nodes', 'NIPALSNode.train', BibTeX("""
@conference{ZieheMuller1998,
author={Ziehe, Andreas and Muller, Klaus-Robert},
title={TDSEP an efficient algorithm for blind separation using time structure.},
booktitle={Proc. 8th Int. Conf. Artificial Neural Networks},
year={1998},
editor={Niklasson, L, Boden, M, and Ziemke, T},
publisher={ICANN}
}
"""), description='Independent Component Analysis using the TDSEP algorithm',
tags=['edu'])
tags=['implementation'])
injector.add('mdp.nodes', 'NIPALSNode.train', BibTeX("""
@conference{ZieheMuller1998,
author={Ziehe, Andreas and Muller, Klaus-Robert},
title={TDSEP an efficient algorithm for blind separation using time structure.},
booktitle={Proc. 8th Int. Conf. Artificial Neural Networks},
year={1998},
editor={Niklasson, L, Boden, M, and Ziemke, T},
publisher={ICANN}
}
"""), description='Independent Component Analysis using the TDSEP algorithm',
tags=['edu'])
injector.add('mdp.nodes', 'JADENode.train', Doi('10.1049/ip-f-2.1993.0054'),
description='Independent Component Analysis using the JADE algorithm',
tags=['implementation'])
injector.add('mdp.nodes', 'JADENode.train', Doi('10.1162/089976699300016863'),
description='Independent Component Analysis using the JADE algorithm',
tags=['implementation'])
injector.add('mdp.nodes', 'SFANode.train', Doi('10.1162/089976602317318938'),
description='Slow Feature Analysis',
tags=['implementation'])
injector.add('mdp.nodes', 'SFA2Node.train', Doi('10.1162/089976602317318938'),
description='Slow Feature Analysis (via the space of inhomogeneous polynomials)',
tags=['implementation'])
injector.add('mdp.nodes', 'ISFANode.train', Doi('10.1007/978-3-540-30110-3_94'),
Olivier and Blondel, Mathieu and Prettenhofer, Peter and Weiss,
Ron and Dubourg, Vincent and others},
journal={The Journal of Machine Learning Research},
volume={12},
pages={2825--2830},
year={2011},
publisher={JMLR.org}
}
"""), description="Machine Learning library")
# sklearn.cluster.affinity_propagation_
injector.add('sklearn.cluster.affinity_propagation_', None, Doi('10.1126/science.1136800'),
description="Affinity propagation clustering algorithm", tags=['implementation'])
# sklearn.cluster.bicluster
injector.add('sklearn.cluster.bicluster', 'SpectralCoclustering._fit', Doi('10.1101/gr.648603'),
description="Spectral Coclustering algorithm", tags=['implementation'])
injector.add('sklearn.cluster.bicluster', 'SpectralBiclustering._fit', Doi('10.1101/gr.648603'),
description="Spectral Biclustering algorithm", tags=['implementation'])
# sklearn.cluster.birch
injector.add('sklearn.cluster.birch', 'Birch._fit', Doi('10.1145/233269.233324'),
description="BIRCH clustering algorithm", tags=['implementation'])
injector.add('sklearn.cluster.birch', 'Birch._fit', Url('https://code.google.com/p/jbirch/'),
description="Java implementation of BIRCH clustering algorithm", tags=['another-implementation'])
# sklearn.cluster.dbscan_
injector.add('sklearn.cluster.dbscan_', 'dbscan',
BibTeX("""@inproceedings{ester1996density,
title={A density-based algorithm for discovering clusters in large spatial databases with noise.},
author={Ester, Martin and Kriegel, Hans-Peter and Sander, J{\"o}rg and Xu, Xiaowei},
booktitle={Kdd},
def inject(injector):
#http://martinos.org/mne/stable/cite.html
injector.add('mne', None, Doi('10.1016/j.neuroimage.2013.10.027'),
description='MNE software for processing MEG and EEG data.',
tags=['implementation'])
injector.add('mne', None, Doi('10.3389/fnins.2013.00267'),
description='MEG and EEG data analysis with MNE-Python.',
tags=['implementation'])
description="Java implementation of BIRCH clustering algorithm", tags=['another-implementation'])
# sklearn.cluster.dbscan_
injector.add('sklearn.cluster.dbscan_', 'dbscan',
BibTeX("""@inproceedings{ester1996density,
title={A density-based algorithm for discovering clusters in large spatial databases with noise.},
author={Ester, Martin and Kriegel, Hans-Peter and Sander, J{\"o}rg and Xu, Xiaowei},
booktitle={Kdd},
volume={96},
number={34},
pages={226--231},
year={1996}
}"""), description="dbscan clustering algorithm", tags=['implementation'])
# sklearn.cluster.mean_shift_
injector.add('sklearn.cluster.mean_shift_', 'mean_shift', Doi('10.1109/34.1000236'),
description="Mean shift clustering algorithm", tags=['implementation'])
# sklearn.cluster.spectral
injector.add('sklearn.cluster.spectral', 'discretize', Doi('10.1109/ICCV.2003.1238361'),
description="Multiclass spectral clustering", tags=['reference'])
injector.add('sklearn.cluster.spectral', 'spectral_clustering', Doi('10.1109/34.868688'),
description="Spectral clustering", tags=['implementation'])
injector.add('sklearn.cluster.spectral', 'spectral_clustering', Doi('10.1007/s11222-007-9033-z'),
description="Spectral clustering", tags=['implementation'])
# sklearn.ensemble.forest and tree
Breiman_2001 = Doi("10.1023/A:1010933404324")
Breiman_1984 = BibTeX("""@BOOK{breiman-friedman-olshen-stone-1984,
author = {L. Breiman and J. Friedman and R. Olshen and C. Stone},
title = {{Classification and Regression Trees}},
publisher = {Wadsworth and Brooks},
def inject(injector):
injector.add('nibabel', None,
Doi('10.5281/zenodo.60847'),
cite_module=True,
description="I/O library to access to common neuroimaging file formats",
tags=['implementation'])
def get_bibtex_rendering(entry):
if isinstance(entry, Doi):
return BibTeX(import_doi(entry.doi))
elif isinstance(entry, BibTeX):
return entry
else:
raise ValueError("Have no clue how to get bibtex out of %s" % entry)
def inject(injector):
#http://nipy.org/nipype/about.html
injector.add('nipype', None, Doi('10.3389/fninf.2011.00013'),
description='Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python',
tags=['implementation'])
#http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/
injector.add('nipype.interfaces', 'fsl', Doi('10.1016/j.neuroimage.2004.07.051'),
description='Advances in functional and structural MR image analysis and implementation as FSL',
tags=['implementation'])
injector.add('nipype.interfaces', 'fsl', Doi('10.1016/j.neuroimage.2008.10.055'),
description='Bayesian analysis of neuroimaging data in FSL',
tags=['implementation'])
injector.add('nipype.interfaces', 'fsl', Doi('10.1016/j.neuroimage.2011.09.015'),
description='FSL.',
tags=['implementation'])
def inject(injector):
#http://scikit-image.org
injector.add('skimage', None, Doi('10.7717/peerj.453'),
description='scikit-image: Image processing in Python.',
tags=['implementation'])