def test_predict_dti():
with nbtmp.InTemporaryDirectory() as tmpdir:
fbval = op.join(tmpdir, 'dti.bval')
fbvec = op.join(tmpdir, 'dti.bvec')
fdata = op.join(tmpdir, 'dti.nii.gz')
make_dti_data(fbval, fbvec, fdata)
file_dict = dti.fit_dti(fdata, fbval, fbvec, out_dir=tmpdir)
params_file = file_dict['params']
gtab = dpg.gradient_table(fbval, fbvec)
predict_fname = dti.predict(params_file,
gtab,
S0_file=fdata,
out_dir=tmpdir)
prediction = nib.load(predict_fname).get_fdata()
npt.assert_almost_equal(prediction, nib.load(fdata).get_fdata())
# If you have a mask into the volume, you will predict only that
# part of the volume:
mask = np.zeros(prediction.shape[:3], dtype=bool)
mask[2:4, 2:4, 2:4] = 1
file_dict = dti.fit_dti(fdata, fbval, fbvec, mask=mask, out_dir=tmpdir)
params_file = file_dict['params']
predict_fname = dti.predict(params_file,
gtab,
S0_file=fdata,
out_dir=tmpdir)
prediction = nib.load(predict_fname).get_fdata()
npt.assert_almost_equal(prediction[mask],
nib.load(fdata).get_fdata()[mask])
def test_predict_dti():
with nbtmp.InTemporaryDirectory() as tmpdir:
fbval = op.join(tmpdir, 'dti.bval')
fbvec = op.join(tmpdir, 'dti.bvec')
fdata = op.join(tmpdir, 'dti.nii.gz')
make_dti_data(fbval, fbvec, fdata)
file_dict = dti.fit_dti(fdata, fbval, fbvec, out_dir=tmpdir)
params_file = file_dict['params']
gtab = dpg.gradient_table(fbval, fbvec)
predict_fname = dti.predict(params_file, gtab, S0_file=fdata,
out_dir=tmpdir)
prediction = nib.load(predict_fname).get_data()
npt.assert_almost_equal(prediction, nib.load(fdata).get_data())
# If you have a mask into the volume, you will predict only that
# part of the volume:
mask = np.zeros(prediction.shape[:3], dtype=bool)
mask[2:4, 2:4, 2:4] = 1
file_dict = dti.fit_dti(fdata, fbval, fbvec, mask=mask,
out_dir=tmpdir)
params_file = file_dict['params']
predict_fname = dti.predict(params_file, gtab, S0_file=fdata,
out_dir=tmpdir)
prediction = nib.load(predict_fname).get_data()
npt.assert_almost_equal(prediction[mask],
nib.load(fdata).get_data()[mask])
def test_cli():
with nbtmp.InTemporaryDirectory() as tmpdir:
fbval = op.join(tmpdir, 'dti.bval')
fbvec = op.join(tmpdir, 'dti.bvec')
fdata = op.join(tmpdir, 'dti.nii.gz')
make_dti_data(fbval, fbvec, fdata)
cmd = " ".join([
"pyAFQ_dti", "-d",
op.join(tmpdir, "dti.nii.gz"), "-l",
op.join(tmpdir, "dti.bval"), "-c",
op.join(tmpdir, "dti.bvec")
])
out = os.system(cmd)
assert out == 0
assert op.exists(op.join(tmpdir, 'dti', 'dti_params.nii.gz'))
def test_fit_dti():
with nbtmp.InTemporaryDirectory() as tmpdir:
fbval = op.join(tmpdir, 'dti.bval')
fbvec = op.join(tmpdir, 'dti.bvec')
fdata = op.join(tmpdir, 'dti.nii.gz')
make_dti_data(fbval, fbvec, fdata)
cmd = ["pyAFQ_dti", "-d", fdata, "-l", fbval, "-c", fbvec,
"-o", tmpdir, '-b', '0']
out = runner.run_command(cmd)
npt.assert_equal(out[0], 0)
# Get expected values
names = ['FA', 'MD', 'AD', 'RD']
for n in names:
fname = op.join(tmpdir, "dti_%s.nii.gz" % n)
img = nib.load(fdata)
affine = img.get_affine()
shape = img.shape[:-1]
assert_image_shape_affine(fname, shape, affine)
def test_fit_dti():
with nbtmp.InTemporaryDirectory() as tmpdir:
fbval = op.join(tmpdir, 'dti.bval')
fbvec = op.join(tmpdir, 'dti.bvec')
fdata = op.join(tmpdir, 'dti.nii.gz')
make_dti_data(fbval, fbvec, fdata)
cmd = ["pyAFQ_dti", "-d", fdata, "-l", fbval, "-c", fbvec,
"-o", tmpdir, '-b', '0']
out = runner.run_command(cmd)
npt.assert_equal(out[0], 0)
# Get expected values
names = ['FA', 'MD', 'AD', 'RD']
for n in names:
fname = op.join(tmpdir, "dti_%s.nii.gz" % n)
img = nib.load(fdata)
affine = img.affine
shape = img.shape[:-1]
assert_image_shape_affine(fname, shape, affine)
def test_predict_dti():
with nbtmp.InTemporaryDirectory() as tmpdir:
fbval = op.join(tmpdir, 'dti.bval')
fbvec = op.join(tmpdir, 'dti.bvec')
fdata = op.join(tmpdir, 'dti.nii.gz')
make_dti_data(fbval, fbvec, fdata)
cmd1 = ["pyAFQ_dti", "-d", fdata, "-l", fbval, "-c", fbvec,
"-o", tmpdir]
out = runner.run_command(cmd1)
npt.assert_equal(out[0], 0)
# Get expected values
fparams = op.join(tmpdir, "dti_params.nii.gz")
cmd2 = ["pyAFQ_dti_predict", "-p", fparams, "-l", fbval, "-c", fbvec,
"-o", tmpdir, '-b', '0']
out = runner.run_command(cmd2)
npt.assert_equal(out[0], 0)
pred = nib.load(op.join(tmpdir, "dti_prediction.nii.gz")).get_data()
data = nib.load(op.join(tmpdir, "dti.nii.gz")).get_data()
npt.assert_array_almost_equal(pred, data)
def test_predict_dti():
with nbtmp.InTemporaryDirectory() as tmpdir:
fbval = op.join(tmpdir, 'dti.bval')
fbvec = op.join(tmpdir, 'dti.bvec')
fdata = op.join(tmpdir, 'dti.nii.gz')
make_dti_data(fbval, fbvec, fdata)
cmd1 = ["pyAFQ_dti", "-d", fdata, "-l", fbval, "-c", fbvec,
"-o", tmpdir]
out = runner.run_command(cmd1)
npt.assert_equal(out[0], 0)
# Get expected values
fparams = op.join(tmpdir, "dti_params.nii.gz")
cmd2 = ["pyAFQ_dti_predict", "-p", fparams, "-l", fbval, "-c", fbvec,
"-o", tmpdir, '-b', '0']
out = runner.run_command(cmd2)
npt.assert_equal(out[0], 0)
pred = nib.load(op.join(tmpdir, "dti_prediction.nii.gz")).get_fdata()
data = nib.load(op.join(tmpdir, "dti.nii.gz")).get_fdata()
npt.assert_array_almost_equal(pred, data)
def test_noise_from_b0():
out_shape = (5, 6, 7)
with nbtmp.InTemporaryDirectory() as tmpdir:
# make artificial dti data
fbval = op.join(tmpdir, 'dti.bval')
fbvec = op.join(tmpdir, 'dti.bvec')
fdata = op.join(tmpdir, 'dti.nii.gz')
make_dti_data(fbval, fbvec, fdata, out_shape=out_shape)
# make artifical mask
mask = np.ones(out_shape)
mask[0, 0, :] = 0
# load data and mask
bvals, bvecs = read_bvals_bvecs(fbval, fbvec)
img, data, gtab, mask = ut.prepare_data(fdata,
fbval,
fbvec,
mask=mask,
b0_threshold=50)
# test noise_from_b0
noise = dti.noise_from_b0(data, gtab, bvals, mask=mask)
npt.assert_almost_equal(noise, 0)