def create_basis(X, basis, mask):
""" Create a (polynomial) basis set """
# check whether we are using a polynomial basis set
if type(basis) is int or (type(basis) is str and len(basis) == 1):
dimpoly = int(basis)
dimx = X.shape[1]
print('Generating polynomial basis set of degree', dimpoly, '...')
Phi = np.zeros((X.shape[0], X.shape[1] * dimpoly))
colid = np.arange(0, dimx)
for d in range(1, dimpoly + 1):
Phi[:, colid] = X**d
colid += dimx
else: # custom basis set
if type(basis) is str:
print('Loading custom basis set from', basis)
# Phi_vol = fileio.load_data(basis)
# we load the data this way instead so we can apply the same mask
Phi_vol = fileio.load_nifti(basis, vol=True)
Phi = fileio.vol2vec(Phi_vol, mask)
print('Basis set consists of', Phi.shape[1], 'basis functions.')
# maskid = np.where(mask.ravel())[0]
else:
raise ValueError("I don't know what to do with basis:", basis)
return Phi
def load_data(datafile, maskfile=None):
""" load 4d nifti data """
if datafile.endswith("nii.gz") or datafile.endswith("nii"):
# we load the data this way rather than fileio.load() because we need
# access to the volumetric representation (to know the # coordinates)
dat = fileio.load_nifti(datafile, vol=True)
dim = dat.shape
if len(dim) <= 3:
dim = dim + (1, )
else:
raise ValueError("No routine to handle non-nifti data")
mask = fileio.create_mask(dat, mask=maskfile)
dat = fileio.vol2vec(dat, mask)
maskid = np.where(mask.ravel())[0]
# generate voxel coordinates
i, j, k = np.meshgrid(np.linspace(0, dim[0] - 1, dim[0]),
np.linspace(0, dim[1] - 1, dim[1]),
np.linspace(0, dim[2] - 1, dim[2]),
indexing='ij')
# voxel-to-world mapping
img = nib.load(datafile)
world = np.vstack(
(i.ravel(), j.ravel(), k.ravel(), np.ones(np.prod(i.shape), float))).T
world = np.dot(world, img.affine.T)[maskid, 0:3]
return dat, world, mask
def load_response_vars(datafile, maskfile=None, vol=True):
""" load response variables (of any data type)"""
if fileio.file_type(datafile) == 'nifti':
dat = fileio.load_nifti(datafile, vol=vol)
volmask = fileio.create_mask(dat, mask=maskfile)
Y = fileio.vol2vec(dat, volmask).T
else:
Y = fileio.load(datafile)
volmask = None
if fileio.file_type(datafile) == 'cifti':
Y = Y.T
return Y, volmask