:orphan: .. _api_ref: API Reference ************* This reference provides detailed documentation for all modules, classes, and methods in the current release of Neurolearn. :mod:`nltools.data`: Data Types =============================== .. autoclass:: nltools.data.Brain_Data :members: .. autoclass:: nltools.data.Adjacency :members: .. autoclass:: nltools.data.Groupby :members: .. autoclass:: nltools.data.Design_Matrix :members: :mod:`nltools.analysis`: Analysis Tools ======================================= .. autoclass:: nltools.analysis.Roc :members: :mod:`nltools.stats`: Stats Tools ================================= .. automodule:: nltools.stats :members: :mod:`nltools.datasets`: Dataset Tools ====================================== .. automodule:: nltools.datasets :members: :mod:`nltools.cross_validation`: Cross-Validation Tools ======================================================= .. automodule:: nltools.cross_validation :members: .. autoclass:: nltools.cross_validation.KFoldStratified :members: :mod:`nltools.mask`: Mask Tools =============================== .. automodule:: nltools.mask :members: :mod:`nltools.file_reader`: File Reading ======================================== .. automodule:: nltools.file_reader :members: :mod:`nltools.utils`: Utilities =============================== .. automodule:: nltools.utils :members: :mod:`nltools.prefs`: Preferences ================================= This module can be used to adjust the default MNI template settings that are used internally by all `Brain_Data` operations. By default all operations are performed in **MNI152 2mm space**. Thus any files loaded with be resampled to this space by default.You can control this on a per-file loading basis using the `mask` argument of `Brain_Data`, e.g. .. code-block:: from nltools.data import Brain_Data # my_brain will be resampled to 2mm brain = Brain_Data('my_brain.nii.gz') # my_brain will now be resampled to the same space as my_mask brain = Brain_Data('my_brain.nii.gz', mask='my_mask.nii.gz') # will be resampled Alternatively this module can be used to switch between 2mm or 3mm MNI spaces with and without ventricles: .. code-block:: from nltools.prefs import MNI_Template, resolve_mni_path from nltools.data import Brain_Data # Update the resolution globally MNI_Template['resolution'] = '3mm' # This works too: MNI_Template.resolution = 3 # my_brain will be resampled to 3mm and future operation will be in 3mm space brain = Brain_Data('my_brain.nii.gz') # get the template nifti files resolve_mni_path(MNI_Template) # will print like: { 'resolution': '3mm', 'mask_type': 'with_ventricles', 'mask': '/Users/Esh/Documents/pypackages/nltools/nltools/resources/MNI152_T1_3mm_brain_mask.nii.gz', 'plot': '/Users/Esh/Documents/pypackages/nltools/nltools/resources/MNI152_T1_3mm.nii.gz', 'brain': '/Users/Esh/Documents/pypackages/nltools/nltools/resources/MNI152_T1_3mm_brain.nii.gz' } .. automodule:: nltools.prefs :members: :show-inheritance: :mod:`nltools.plotting`: Plotting Tools ======================================= .. automodule:: nltools.plotting :members: :mod:`nltools.simulator`: Simulator Tools ========================================= .. automodule:: nltools.simulator :members: .. autoclass:: nltools.simulator.Simulator :members: Index ===== * :ref:`genindex` * :ref:`modindex`