def setReslicedGM(self, rgm):
"""
Sets the resliced gray matter segmentation file (rc1_....nii if SPM was used)
:param rgm: string, path to the resliced GM segmentation file
"""
self.rgm = checkFileExists(
rgm, 'resliced WM segmentation map (rc1_filename.nii)')
def setMovementParameterFile(self, rp_file):
"""
Sets the movement parameters across the functional run (rp_....txt file if SPM was used)
:param rp_file: string, path to the estimated movement parameters
"""
self.movementParamFile = checkFileExists(
rp_file, 'Estimated movement (rp_filename.txt)')
def setReslicedCSF(self, rcsf):
"""
Sets the resliced cerebrospinal fluid segmentation file (rc3_....nii if SPM was used)
:param rcsf: string, path to the resliced CSF segmentation file
"""
self.rcsf = checkFileExists(
rcsf, 'resliced CSF segmentation map (rc3_filename.nii)')
def setReslicedWM(self, rwm):
"""
Sets the resliced white matter segmentation file (rc2_....nii if SPM was used)
:param rwm: string, path to the resliced WM segmentation file
"""
self.rwm = checkFileExists(
rwm, 'resliced WM segmentation map (rc2_filename.nii)')
def setFunctionalFileToDisplay(self, fn_file):
"""
Sets the functional nifti filename (.nii or.nii.gz) used to display on the figure
:param fn_file: str, path to the 4D functional file
"""
self.functional_fn = nib.load(
checkFileExists(fn_file,
'Functional run (functional_filename.nii)'))
# Sets the raw data directly in class attribute
self.f_img = self.functional_fn.get_data()
self.Nt = self.f_img.shape[-1]
def setFunctionalData(self, fn_file):
"""
Sets the path to nifti (.nii or .nii.gz) functional 4D file. Loads the file with nibabel and sets the data into
self.f_img
:param fn_file: string, path to the functional file
"""
self.functional_fn = checkFileExists(
fn_file, 'Functional run (functional_filename.nii)')
# Load file directly
f = nib.load(self.functional_fn)
self.f_hdr = f.get_header()
self.f_aff = f.get_affine()
# Sets the raw data directly in class attribute
self.f_img = f.get_data()
# (Ni,Nj,Nk) = number of voxels in the (X,Y,Z) dimension
# Nt = number of fMRI timepoints (=number of volumes)
self.fn_shape = [self.Ni, self.Nj, self.Nk, self.Nt] = self.f_img.shape
#Sets the default slice index for generating the plot
self.setDefaultSliceIndex()