.. AUTO-GENERATED FILE -- DO NOT EDIT!

nipype.interfaces.fsl.model
===========================


:class:`Cluster`
----------------


:class:`ContrastMgr`
--------------------


:class:`FEAT`
-------------


:class:`FEATModel`
------------------


:class:`FEATRegister`
---------------------


Register feat directories to a specific standard

Inputs:: 

	[Mandatory]
	feat_dirs : (a directory name)
		Lower level feat dirs
	reg_image : (a file name)
		image to register to (will be treated as standard)

	[Optional]
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	reg_dof : (an integer)
		registration degrees of freedom


Outputs:: 

	fsf_file : (an existing file name)
		FSL feat specification file

:class:`FILMGLS`
----------------


:class:`FLAMEO`
---------------


:class:`L2Model`
----------------


Generate subject specific second level model

Examples
~~~~~~~~

>>> from nipype.interfaces.fsl import L2Model
>>> model = L2Model(num_copes=3) # 3 sessions

Inputs:: 

	[Mandatory]
	num_copes : (an integer)
		number of copes to be combined

	[Optional]
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run


Outputs:: 

	design_con : (an existing file name)
		design contrast file
	design_grp : (an existing file name)
		design group file
	design_mat : (an existing file name)
		design matrix file

:class:`Level1Design`
---------------------


Generate FEAT specific files

Examples
~~~~~~~~

>>> level1design = Level1Design()
>>> level1design.inputs.interscan_interval = 2.5
>>> level1design.inputs.bases = {'dgamma':{'derivs': False}}
>>> level1design.inputs.session_info = 'session_info.npz'
>>> level1design.run() # doctest: +SKIP

Inputs:: 

	[Mandatory]
	bases : (a dictionary with keys which are 'dgamma' and with values which are a dictionary with keys which are 'derivs' and with values which are a boolean or a dictionary with keys which are 'gamma' and with values which are a dictionary with keys which are 'derivs' and with values which are a boolean or a dictionary with keys which are 'none' and with values which are None)
		name of basis function and options e.g., {'dgamma': {'derivs': True}}
	interscan_interval : (a float)
		Interscan  interval (in secs)
	model_serial_correlations : (a boolean)
		Option to model serial correlations using an autoregressive estimator (order 1). Setting this option is only useful in the context of the fsf file. If you set this to False, you need to repeat this option for FILMGLS by setting autocorr_noestimate to True
	session_info	Session specific information generated by ``modelgen.SpecifyModel``

	[Optional]
	contrasts : (a list of items which are a tuple of the form: (a string, 'T', a list of items which are a string, a list of items which are a float) or a tuple of the form: (a string, 'T', a list of items which are a string, a list of items which are a float, a list of items which are a float) or a tuple of the form: (a string, 'F', a list of items which are a tuple of the form: (a string, 'T', a list of items which are a string, a list of items which are a float) or a tuple of the form: (a string, 'T', a list of items which are a string, a list of items which are a float, a list of items which are a float)))
		List of contrasts with each contrast being a list of the form - [('name', 'stat', [condition list], [weight list], [session list])]. if session list is None or not provided, all sessions are used. For F contrasts, the condition list should contain previously defined T-contrasts.
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run


Outputs:: 

	ev_files : (a list of items which are a list of items which are an existing file name)
		condition information files
	fsf_files : (an existing file name)
		FSL feat specification files

:class:`MELODIC`
----------------


:class:`MultipleRegressDesign`
------------------------------


Generate multiple regression design

.. note::
  FSL does not demean columns for higher level analysis.

Please see `FSL documentation <http://www.fmrib.ox.ac.uk/fsl/feat5/detail.html#higher>`_
for more details on model specification for higher level analysis.

Examples
~~~~~~~~

>>> from nipype.interfaces.fsl import L2Model
>>> model = MultipleRegressDesign()
>>> model.inputs.contrasts = [['group mean','T',['reg1'],[1]]]
>>> model.inputs.regressors = dict(reg1=[1,1,1],reg2=[2.,-4,3])
>>> model.run() # doctest: +SKIP

Inputs:: 

	[Mandatory]
	contrasts : (a list of items which are a tuple of the form: (a string, 'T', a list of items which are a string, a list of items which are a float) or a tuple of the form: (a string, 'F', a list of items which are a tuple of the form: (a string, 'T', a list of items which are a string, a list of items which are a float)))
		List of contrasts with each contrast being a list of the form - [('name', 'stat', [condition list], [weight list])]. if session list is None or not provided, all sessions are used. For F contrasts, the condition list should contain previously defined T-contrasts without any weight list.
	regressors : (a dictionary with keys which are a string and with values which are a list of items which are a float)
		dictionary containing named lists of regressors

	[Optional]
	groups : (a list of items which are an integer)
		list of group identifiers (defaults to single group)
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run


Outputs:: 

	design_con : (an existing file name)
		design t-contrast file
	design_fts : (an existing file name)
		design f-contrast file
	design_grp : (an existing file name)
		design group file
	design_mat : (an existing file name)
		design matrix file

:class:`Randomise`
------------------


:class:`SMM`
------------


:class:`SmoothEstimate`
-----------------------

