def METHOD_NAME(self):
    imgnames = [ 'avg152T1_LR_nifti_resampled.nii.gz',
          'avg152T1_LR_nifti.nii.gz',
                 'avg152T1_LR_nifti_resampled_resliced.nii.gz']
    images = [0,0,0];
    names=[' reference','target','true'];
    print('\n\n');
    print('----------------------------------------------------------')
    for i in range(0,3):
        name=my_path+'/../test/testdata/'+imgnames[i];
        images[i]=bis.bisImage().load(name)
        print('__ loaded ',names[i], 'from ', name,'dims=',images[i].dimensions,images[i].spacing,images[i].dimensions,images[i].get_data().dtype);
    print('----------------------------------------------------------')
    reslice_matr = [ [  0.866,  -0.525  , 0.000,  68.758 ],
       [  0.500,   0.909 ,  0.000 ,  9.793 ],
       [ 0.000,   0.000 ,  1.000 ,  2.250 ],
       [ 0.000,   0.000,   0.000 ,  1.000  ]];
    matr=np.zeros([4,4],dtype=np.float32);
    for row in range(0,4):
        for col in range(0,4):
            matr[row][col]=reslice_matr[row][col];
    reference_image=images[0];
    target_image=images[1];
    true_image=images[2];
    paramobj = {
        "interpolation" : 1,
        "dimensions" : reference_image.dimensions,
        "spacing" : reference_image.spacing,
        "datatype" : "float",
        "backgroundValue" : 0.0,
        "numthreads" : 4
    };
    print(paramobj);
    print('----------------------------------------------------------');
    out_obj=libbis.resliceImageWASM(images[1],matr,paramobj,debug=2);
    cc=np.corrcoef(images[2].get_data().flatten(),out_obj.get_data().flatten())[0,1];
    if cc>0.999:
        testpass=True
    else:
        testpass=False;
    print('----------------------------------------------------------')
    print('__ post reslicing correlation out v true=',cc, 'pass=',testpass);
    print('----------------------------------------------------------')
    self.assertEqual(testpass,True);