How to use the duecredit.entries.BibTeX function in duecredit

def inject(injector):
    injector.add('mdp', None, Doi('10.3389/neuro.11.008.2008'),
                 description="Modular toolkit for Data Processing (MDP): a Python data processing framework",
                 tags=['implementation'])

    injector.add('mdp.nodes', 'PCANode.train', Doi('10.1007/b98835'),
                 description="Principal Component Analysis (and filtering)",
                 tags=['implementation'])

    injector.add('mdp.nodes', 'NIPALSNode.train', BibTeX("""
        @incollection{Word1966,
            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'])

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)

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'])


    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'),

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'),
                    description='Independent Slow Feature Analysis',
                    tags=['implementation'])

 
    injector.add('mdp.nodes', 'XSFANode.train', BibTeX("""
        @article{SprekelerZitoWiskott2009,
            author={Sprekeler, H., Zito, T., and Wiskott, L.},
            title={An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation.},
            journal={Journal of Machine Learning Research.},
            year={2009},
            volume={15},
            pages={921--947},
            }
        """), description="Non-linear Blind Source Separation using Slow Feature Analysis",
        tags=['edu'])

    injector.add('mdp.nodes', 'FDANode.train', BibTeX("""
        @book{Bishop2011,
            author={Bishop, Christopher M.},
            title={Neural Networks for Pattern Recognition},
            publisher={Oxford University Press, Inc}

def inject(injector):
    injector.add('numpy', None, BibTeX("""
    @article{van2011numpy,
        title={The NumPy array: a structure for efficient numerical computation},
        author={Van Der Walt, Stefan and Colbert, S Chris and Varoquaux, Gael},
        journal={Computing in Science \& Engineering},
        volume={13},
        number={2},
        pages={22--30},
        year={2011},
        publisher={AIP Publishing}
        }
    """),
    tags=['implementation'],
    cite_module=True,
    description="Scientific tools library")

injector.add('scipy.cluster.hierarchy', None, BibTeX("""
    @article{sneath1962numerical,
        title={Numerical taxonomy},
        author={Sneath, Peter HA and Sokal, Robert R},
        journal={Nature},
        volume={193},
        number={4818},
        pages={855--860},
        year={1962},
        publisher={Nature Publishing Group}
    }"""),
                 description="Hierarchical clustering",
                 min_version='0.4.3',
                 tags=['edu'])

    injector.add('scipy.cluster.hierarchy', None, BibTeX("""
    @article{batagelj1995comparing,
        title={Comparing resemblance measures},
        author={Batagelj, Vladimir and Bren, Matevz},
        journal={Journal of classification},
        volume={12},
        number={1},
        pages={73--90},
        year={1995},
        publisher={Springer}
    }"""),
                 description="Hierarchical clustering",
                 min_version='0.4.3',
                 tags=['edu'])

    injector.add('scipy.cluster.hierarchy', None, BibTeX("""
    @book{sokal1958statistical,

def inject(injector):
    injector.add('scipy', None, BibTeX("""
    @Misc{JOP+01,
      author =    {Eric Jones and Travis Oliphant and Pearu Peterson and others},
      title =     {{SciPy}: Open source scientific tools for {Python}},
      year =      {2001--},
      url = "http://www.scipy.org/",
      note = {[Online; accessed 2015-07-13]}
    }"""),
                 description="Scientific tools library",
                 tags=['implementation'])

    # scipy.cluster.hierarchy general references
    # TODO: we should allow to pass a list of entries
    injector.add('scipy.cluster.hierarchy', None, BibTeX("""
    @article{johnson1967hierarchical,
        title={Hierarchical clustering schemes},
        author={Johnson, Stephen C},

tags=['implementation'])

 
    injector.add('mdp.nodes', 'XSFANode.train', BibTeX("""
        @article{SprekelerZitoWiskott2009,
            author={Sprekeler, H., Zito, T., and Wiskott, L.},
            title={An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation.},
            journal={Journal of Machine Learning Research.},
            year={2009},
            volume={15},
            pages={921--947},
            }
        """), description="Non-linear Blind Source Separation using Slow Feature Analysis",
        tags=['edu'])

    injector.add('mdp.nodes', 'FDANode.train', BibTeX("""
        @book{Bishop2011,
            author={Bishop, Christopher M.},
            title={Neural Networks for Pattern Recognition},
            publisher={Oxford University Press, Inc}
            year={2011},
            pages={105--112},
            }
        """), description="(generalized) Fisher Discriminant Analysis",
        tags=['edu'])

def get_text_rendering(citation, style='harvard1'):
    from .collector import Citation
    entry = citation.entry
    if isinstance(entry, Doi):
        bibtex_rendering = get_bibtex_rendering(entry)
        bibtex_citation = copy.copy(citation)
        bibtex_citation.set_entry(bibtex_rendering)
        return get_text_rendering(bibtex_citation)
    elif isinstance(entry, BibTeX):
        return format_bibtex(entry, style=style)
    elif isinstance(entry, Text):
        return entry.format()
    elif isinstance(entry, Url):
        return "URL: {}".format(entry.format())
    else:
        return str(entry)