def test_mroi1(verbose=0):
nim = load(RefImage)
mroi = MultipleROI(affine=nim.get_affine(), shape=nim.get_shape())
pos = 1.0*np.array([[10,10,10],[0,0,0],[20,0,20],[0,0,35]])
rad = np.array([5.,6.,7.,8.0])
mroi.as_multiple_balls(pos,rad)
mroi.append_balls(np.array([[-10.,0.,10.]]),np.array([7.0]))
roiPath = os.path.join(WriteDir,"mroi.nii")
mroi.make_image(roiPath)
assert(os.path.isfile(roiPath))
roi = DiscreteROI( affine=affine, shape=shape)
roi.from_labelled_image(blobPath, 1)
roiPath2 = os.path.join(swd, "roi_blob_1.nii")
roi.make_image(roiPath2)
# --- 2.c take the blob closest to 'position as an ROI'
roiPath3 = os.path.join(swd, "blob_closest_to_%d_%d_%d.nii")%\
(position[0][0], position[0][1], position[0][2])
roi.from_position_and_image(blobPath, np.array(position))
roi.make_image(roiPath3)
# --- 2.d make a set of ROIs from all the blobs
mroi = MultipleROI( affine=affine, shape=shape)
mroi.from_labelled_image(blobPath)
roiPath4 = os.path.join(swd, "roi_all_blobs.nii")
mroi.make_image(roiPath4)
mroi.set_discrete_feature_from_image('activ', input_image)
mroi.discrete_to_roi_features('activ')
mroi.plot_roi_feature('activ')
# ---- 2.e the same, a bit more complex
mroi = MultipleROI( affine=affine, shape=shape)
mroi.as_multiple_balls(np.array([[-10.,0.,10.]]),np.array([7.0]))
mroi.from_labelled_image(blobPath,np.arange(1,20))
mroi.from_labelled_image(blobPath,np.arange(31,50))
roiPath5 = os.path.join(swd,"roi_some_blobs.nii")
mroi.set_discrete_feature_from_image('activ',input_image)
mroi.discrete_to_roi_features('activ')
valid = mroi.get_roi_feature('activ')>4.0
mroi.clean(valid)
mroi.make_image(roiPath5)
# contrast_path = op.join(swd, 'zmap.nii')
# save(contrast_image, contrast_path)
########################################
# Create ROIs
########################################
positions = np.array([[60, -30, 5],[50, 27, 5]])
# in mm (here in the MNI space)
radii = np.array([8,6])
mroi = MultipleROI( affine=mask.get_affine(), shape=mask.get_shape())
mroi.as_multiple_balls(positions, radii)
# to save an image of the ROIs
mroi.make_image((op.join(swd, "roi.nii")))
# exact the time courses with ROIs
mroi.set_discrete_feature_from_image('signal', image=fmri_data)
# ROI average time courses
mroi.discrete_to_roi_features('signal')
# roi-level contrast average
mroi.set_discrete_feature_from_image('contrast', image=contrast_image)
mroi.discrete_to_roi_features('contrast')
########################################
# GLM analysis on the ROI average time courses
########################################
