How to use the nimare.due.Doi function in NiMARE

@due.dcite(Doi('10.3389/fninf.2011.00017'),
           description='Introduces the Cognitive Atlas.')
def extract_cogat():
    """
    Extract CogAt terms and perform hierarchical expansion.
    """
    pass

@due.dcite(Doi('10.1016/j.neuroimage.2010.02.048'),
           description='Validates the Lancaster MNI-to-Talairach and '
                       'Talairach-to-MNI transforms.')
def tal2mni(coords):
    """
    Python version of BrainMap's tal2icbm_other.m.
    This function converts coordinates from Talairach space to MNI
    space (normalized using templates other than those contained
    in SPM and FSL) using the tal2icbm transform developed and
    validated by Jack Lancaster at the Research Imaging Center in
    San Antonio, Texas.
    http://www3.interscience.wiley.com/cgi-bin/abstract/114104479/ABSTRACT
    FORMAT outpoints = tal2icbm_other(inpoints)
    Where inpoints is N by 3 or 3 by N matrix of coordinates
    (N being the number of points)
    ric.uthscsa.edu 3/14/07
    """

@due.dcite(Doi('10.1002/hbm.20345'),
           description='Introduces the Lancaster MNI-to-Talairach transform, '
                       'as well as its inverse, the Talairach-to-MNI '
                       'transform.')
@due.dcite(Doi('10.1016/j.neuroimage.2010.02.048'),
           description='Validates the Lancaster MNI-to-Talairach and '
                       'Talairach-to-MNI transforms.')
def mni2tal(coords):
    """
    Python version of BrainMap's icbm_other2tal.m.
    This function converts coordinates from MNI space (normalized using
    templates other than those contained in SPM and FSL) to Talairach space
    using the icbm2tal transform developed and validated by Jack Lancaster at
    the Research Imaging Center in San Antonio, Texas.
    http://www3.interscience.wiley.com/cgi-bin/abstract/114104479/ABSTRACT
    FORMAT outpoints = icbm_other2tal(inpoints)
    Where inpoints is N by 3 or 3 by N matrix of coordinates

@due.dcite(Doi('10.1002/hbm.20345'),
           description='Introduces the Lancaster MNI-to-Talairach transform, '
                       'as well as its inverse, the Talairach-to-MNI '
                       'transform.')
@due.dcite(Doi('10.1016/j.neuroimage.2010.02.048'),
           description='Validates the Lancaster MNI-to-Talairach and '
                       'Talairach-to-MNI transforms.')
def mni2tal(coords):
    """
    Python version of BrainMap's icbm_other2tal.m.
    This function converts coordinates from MNI space (normalized using
    templates other than those contained in SPM and FSL) to Talairach space
    using the icbm2tal transform developed and validated by Jack Lancaster at
    the Research Imaging Center in San Antonio, Texas.
    http://www3.interscience.wiley.com/cgi-bin/abstract/114104479/ABSTRACT
    FORMAT outpoints = icbm_other2tal(inpoints)
    Where inpoints is N by 3 or 3 by N matrix of coordinates

@due.dcite(Doi('10.1016/j.neuroimage.2010.02.048'),
           description='Validates the Lancaster MNI-to-Talairach and '
                       'Talairach-to-MNI transforms.')
def tal2mni(coords):
    """
    Python version of BrainMap's tal2icbm_other.m.
    This function converts coordinates from Talairach space to MNI
    space (normalized using templates other than those contained
    in SPM and FSL) using the tal2icbm transform developed and
    validated by Jack Lancaster at the Research Imaging Center in
    San Antonio, Texas.
    http://www3.interscience.wiley.com/cgi-bin/abstract/114104479/ABSTRACT
    FORMAT outpoints = tal2icbm_other(inpoints)
    Where inpoints is N by 3 or 3 by N matrix of coordinates
    (N being the number of points)
    ric.uthscsa.edu 3/14/07
    """

"""
Topic modeling with a Global Vectors for Word Representation (GloVe) model.
"""
from .base import TopicModel
from ...due import due, Doi


@due.dcite(Doi('10.1101/299024'),
           description='Introduces GloVe model-based annotation.')
class GloveModel(TopicModel):
    """
    Generate a GloVe topic model.
    """
    def __init__(self, text_df, coordinates_df):
        pass

@due.dcite(Doi('10.5281/zenodo.32508'),
           description='Python implementation of T-to-Z transform.')
def t_to_z(t_values, dof):
    """
    From Vanessa Sochat's TtoZ package.
    """
    # Select just the nonzero voxels
    nonzero = t_values[t_values != 0]

    # We will store our results here
    z_values = np.zeros(len(nonzero))

    # Select values less than or == 0, and greater than zero
    c = np.zeros(len(nonzero))
    k1 = (nonzero <= c)
    k2 = (nonzero > c)