Generating simulated activation maps

The module nipy.labs.utils.simul_multisubject_fmri_dataset contains a various functions to create simulated activation maps in two, three and four dimensions. A 2D example is surrogate_2d_dataset(). The functions can position various activations and add noise, both as background noise and jitter in the activation positions and amplitude.

These functions can be useful to test methods.

Example

# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
import numpy as np

import pylab as pl

from nipy.labs.utils.simul_multisubject_fmri_dataset import \
     surrogate_2d_dataset

pos = np.array([[10, 10],
                [14, 20],
                [23, 18]])
ampli = np.array([4, 5, 2])

# First generate some noiseless data
noiseless_data = surrogate_2d_dataset(n_subj=1, noise_level=0, spatial_jitter=0,
                                      signal_jitter=0, pos=pos, ampli=ampli)

pl.figure(figsize=(10, 3))
pl.subplot(1, 4, 1)
pl.imshow(noiseless_data[0])
pl.title('Noise-less data')

# Second, generate some group data, with default noise parameters
group_data = surrogate_2d_dataset(n_subj=3, pos=pos, ampli=ampli)

pl.subplot(1, 4, 2)
pl.imshow(group_data[0])
pl.title('Subject 1')
pl.subplot(1, 4, 3)
pl.title('Subject 2')
pl.imshow(group_data[1])
pl.subplot(1, 4, 4)
pl.title('Subject 3')
pl.imshow(group_data[2])

[source code]

Exception occurred rendering plot.

Function documentation