Table Of Contents

Previous topic

modalities.fmri.protocol

Next topic

neurospin.clustering.GGMixture

This Page

modalities.fmri.utils

Module: modalities.fmri.utils

Inheritance diagram for nipy.modalities.fmri.utils:

Classes

CutPoly

class nipy.modalities.fmri.utils.CutPoly(power, trange=(None, None))

Bases: object

A polynomial function of the form f(t) = t^n with an optionally fixed time range on which the function exists.

__init__(power, trange=(None, None))
Paramters:
power : float

f(t) = t^power

trange : (float or None, float or None)

A tuple with the upper and lower bound of the function. None signifies no boundary. Default = (None, None)

LinearInterpolant

class nipy.modalities.fmri.utils.LinearInterpolant(x, y, fill_value=0.0)

Bases: object

A little wrapper around scipy.interpolate call to force the interpolant to take a keywords argument ‘time=’.

__init__(x, y, fill_value=0.0)
Parameters:
x : numpy.ndarray

A 1D array of monotonically increasing real values. x cannot include duplicate values (otherwise f is overspecified)

y : numpy.ndarray

An N-D array of real values. y’s length along the interpolation axis must be equal to the length of x.

fill_value : float

If provided, then this value will be used to fill in for requested points outside of the data range.

Prerequisite:

len(x) == len(y)

WaveFunction

class nipy.modalities.fmri.utils.WaveFunction(start, duration, height)

Bases: object

A square wave function of a specified start, duration and height. f(t) = height if (start <= t < start + duration), 0 otherwise

__init__(start, duration, height)
Parameters:
start : float

The time of the rising edge of the square wave.

duration : float

The width of the square wave

height : float

The height of the square wave

Function

nipy.modalities.fmri.utils.ConvolveFunctions(fn1, fn2, interval, dt, padding_f=0.10000000000000001, normalize=(0, 0))

Convolve fn1 with fn2 – where fn1 may return a multidimensional output.

Parameters:
fn1 : TODO

TODO

fn2 : TODO

TODO

interval : TODO

TODO

dt : TODO

TODO

padding_f : float

TODO

normalize : TODO

TODO

Returns:

TODO