Bases: nipy.modalities.fmri.protocol.ExperimentalRegressor, nipy.fixes.scipy.stats.models.formula.Factor
Return a factor that is a function of experimental time based on an iterator. If the delta attribute is False, it is assumed that the iterator returns rows of the form:
type, start, stop
Here, type is a hashable object and start and stop are floats.
If delta is True, then the events are assumed to be delta functions and the rows are assumed to be of the form:
type, start
where the events are (square wave) approximations of a delta function, non zero on [start, start+dt).
Notes
self[key] returns the __UNCONVOLVED__ factor, even if the ExperimentalFactor has been convolved with an HRF.
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Determine an ExperimentalFactor from an iterator
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Returns: | None |
Return the ‘main effect’ for an ExperimentalFactor.
Returns: | ExperimentalQuantitative |
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Returns: | TODO |
Bases: nipy.fixes.scipy.stats.models.formula.Formula
A formula with no intercept.
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Returns: | TODO |
Bases: nipy.modalities.fmri.protocol.ExperimentalRegressor, nipy.fixes.scipy.stats.models.formula.Quantitative
Generate a regressor that is a function of time based on a function fn.
Bases: object
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Returns: | self |
Returns: | TODO |
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Bases: nipy.modalities.fmri.protocol.ExperimentalQuantitative
This returns a step function from an iterator returning tuples
(start, stop, height)
with height defaulting to 1 if not present.
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