Bases: nipy.modalities.fmri.filters.Filter
A class for FIR filters: i.e. the filter is a collection of square waves. Parameters (start and duration) are specified as a kx2 matrix for k square waves.
>>> GUI = True
>>> from nipy.modalities.fmri import filters
>>> from pylab import *
>>> from numpy import *
>>> parameters = array([[1., 2.], [2., 5.], [4., 8.]])
>>> IRF = filters.FIR(parameters)
>>> _ = plot(arange(0, 15, 0.1), sum(IRF(arange(0, 15, 0.1)), axis=0))
>>> ylab = ylabel('Filters')
>>> xlab = xlabel('Time (s)')
>>> show()
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Bases: object
Takes a list of impulse response functions (IRFs): main purpose is to convolve a functions with each IRF for Design. The class assumes the range of the filter is effectively 50 seconds, can be changed by setting tmax – this is just for the __mul__ method for convolution.
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A class for a Gamma density which knows how to differentiate itself.
By default, normalized to integrate to 1.
Parameters: |
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Bases: nipy.modalities.fmri.filters.Filter
A class that represents the Gamma basis in SPM: i.e. the filter is a collection of a certain number of Gamma densities. Parameters are specified as a kx2 matrix for k Gamma functions.
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Returns: | TODO |