def test_normalize_tpms(tmpdir):
tempdir = str(tmpdir)
in_mask = example_data('tpms_msk.nii.gz')
mskdata = nb.load(in_mask, mmap=NUMPY_MMAP).get_data()
mskdata[mskdata > 0.0] = 1.0
mapdata = []
in_files = []
out_files = []
for i in range(3):
mapname = example_data('tpm_%02d.nii.gz' % i)
filename = os.path.join(tempdir, 'modtpm_%02d.nii.gz' % i)
out_files.append(os.path.join(tempdir, 'normtpm_%02d.nii.gz' % i))
im = nb.load(mapname, mmap=NUMPY_MMAP)
data = im.get_data()
mapdata.append(data.copy())
nb.Nifti1Image(2.0 * (data * mskdata), im.affine,
im.header).to_filename(filename)
in_files.append(filename)
normalize_tpms(in_files, in_mask, out_files=out_files)
sumdata = np.zeros_like(mskdata)
for i, tstfname in enumerate(out_files):
normdata = nb.load(tstfname, mmap=NUMPY_MMAP).get_data()
sumdata += normdata
assert np.all(normdata[mskdata == 0] == 0)
assert np.allclose(normdata, mapdata[i])
assert np.allclose(sumdata[sumdata > 0.0], 1.0)
def test_normalize_tpms(tmpdir):
in_mask = example_data("tpms_msk.nii.gz")
mskdata = np.asanyarray(nb.load(in_mask).dataobj)
mskdata[mskdata > 0.0] = 1.0
mapdata = []
in_files = []
out_files = []
for i in range(3):
mapname = example_data("tpm_%02d.nii.gz" % i)
filename = tmpdir.join("modtpm_%02d.nii.gz" % i).strpath
out_files.append(tmpdir.join("normtpm_%02d.nii.gz" % i).strpath)
im = nb.load(mapname)
data = im.get_fdata()
mapdata.append(data)
nb.Nifti1Image(2.0 * (data * mskdata), im.affine,
im.header).to_filename(filename)
in_files.append(filename)
normalize_tpms(in_files, in_mask, out_files=out_files)
sumdata = np.zeros_like(mskdata)
for i, tstfname in enumerate(out_files):
normdata = nb.load(tstfname).get_fdata()
sumdata += normdata
assert np.all(normdata[mskdata == 0] == 0)
assert np.allclose(normdata, mapdata[i])
assert np.allclose(sumdata[sumdata > 0.0], 1.0)
def test_normalize_tpms():
tempdir = mkdtemp()
in_mask = example_data('tpms_msk.nii.gz' )
mskdata = nb.load( in_mask ).get_data()
mskdata[mskdata>0.0] = 1.0
mapdata = []
in_files = []
out_files = []
for i in range(3):
mapname = example_data('tpm_%02d.nii.gz' % i)
filename = os.path.join(tempdir, 'modtpm_%02d.nii.gz' % i )
out_files.append(os.path.join(tempdir, 'normtpm_%02d.nii.gz' % i ))
im = nb.load(mapname)
data = im.get_data()
mapdata.append( data.copy() )
nb.Nifti1Image(2.0 * (data * mskdata), im.get_affine(),
im.get_header() ).to_filename(filename)
in_files.append( filename )
normalize_tpms( in_files, in_mask, out_files=out_files )
sumdata = np.zeros_like(mskdata)
for i,tstfname in enumerate( out_files ):
normdata = nb.load( tstfname ).get_data()
sumdata+=normdata
yield assert_equal, np.all( normdata[mskdata==0]==0 ), True
yield assert_equal, np.allclose( normdata, mapdata[i] ), True
yield assert_equal, np.allclose(sumdata[sumdata>0.0], 1.0 ), True
rmtree(tempdir)
def test_normalize_tpms():
tempdir = mkdtemp()
in_mask = example_data('tpms_msk.nii.gz' )
mskdata = nb.load( in_mask ).get_data()
mskdata[mskdata>0.0] = 1.0
mapdata = []
in_files = []
out_files = []
for i in range(3):
mapname = example_data('tpm_%02d.nii.gz' % i)
filename = os.path.join(tempdir, 'modtpm_%02d.nii.gz' % i )
out_files.append(os.path.join(tempdir, 'normtpm_%02d.nii.gz' % i ))
im = nb.load(mapname)
data = im.get_data()
mapdata.append( data.copy() )
nb.Nifti1Image(2.0 * (data * mskdata), im.get_affine(),
im.get_header() ).to_filename(filename)
in_files.append( filename )
normalize_tpms( in_files, in_mask, out_files=out_files )
sumdata = np.zeros_like(mskdata)
for i,tstfname in enumerate( out_files ):
normdata = nb.load( tstfname ).get_data()
sumdata+=normdata
yield assert_equal, np.all( normdata[mskdata==0]==0 ), True
yield assert_equal, np.allclose( normdata, mapdata[i] ), True
yield assert_equal, np.allclose(sumdata[sumdata>0.0], 1.0 ), True
rmtree(tempdir)