io_volume.py

import nibabel as nb
import numpy as np

# function to read volumetric tissue classification and turn into 3D array
def load_volume(mri_vol):
    # if input is a filename, try to load it
    if isinstance(mri_vol, basestring):
    # importing nifti files
        if (mri_vol.endswith('nii') or mri_vol.endswith('nii.gz')):
            img=nb.load(mri_vol)
            # importing mnc files using pyminc, suggest to download if missing
        elif mri_vol.endswith('mnc'):
            try:
                import minc as pyezminc
                img=pyezminc.mnc2nii(mri_vol)
            except ValueError:
                print "failed import pyezminc. try installing"
# option to add in more file types here, eg analyze
# if volume is already an np array
    elif isinstance(mri_vol, nb.spatialimages.SpatialImage):
        img=mri_vol
# img_data=np.array(mri_vol)
    else:
                raise ValueError('volume must be a either filename or a nibabel image')
    return img;


# function to save volume data
def save_volume(fname, img, dtype='float32', CLOBBER=True):
    """
    Function to write volume data to file. Filetype is based on filename suffix
    Input:
        - fname:    you can figure that out
        - data:             numpy array
        - affine:              affine matrix
        - header:        header data to write to file (use img.header to get the header of root file)
        - data_type:        numpy data type ('uint32', 'float32' etc)
        - CLOBBER:          overwrite existing file
    """
    import os
    if (fname.endswith('nii') or fname.endswith('nii.gz')):
        if dtype is not None:  # if there is a particular data_type chosen, set it
        # data=data.astype(data_type)
            img.set_data_dtype(dtype)
        if not (os.path.isfile(fname)) or CLOBBER:
            img.to_filename(fname)
        else:
            print("This file exists and CLOBBER was set to false, file not saved.")
 #    elif full_fileName.endswith('mnc')
#               save minc using Thomas code


#loading in minc and converting to nii
def mnc2nii(input_fn):
	'''For a MINC input file, returns a nibabel nifti image.
		This image can then be saved as a nifti file.'''
	img_mnc=pyezminc.Image(fname=input_fn)

	#Create empty instance of a Nibabel image
	img_nii = nib.Nifti1Image(img_mnc.data, np.eye(4))

	for space, row in zip(['xspace', 'yspace', 'zspace'],['srow_x', 'srow_y', 'srow_z'] ):
		img_nii.header[row]=img_mnc.header[space]['direction_cosines'] + img_mnc.header[space]['start']
	affine= [img_nii.header['srow_x'], img_nii.header['srow_y'], img_nii.header['srow_z'], [0,0,0,1]]


	#Return data structure, data, header, affine
	return(img_nii) #, img_mnc.data, img_nii.header, affine )