Source code for niworkflows.viz.notebook
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
#
# Copyright 2021 The NiPreps Developers <nipreps@gmail.com>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# We support and encourage derived works from this project, please read
# about our expectations at
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# https://www.nipreps.org/community/licensing/
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"""Visualization component for Jupyter Notebooks."""
from pathlib import Path
import nibabel as nb
import numpy as np
from .utils import compose_view, cuts_from_bbox, plot_registration
[docs]
def display(
fixed_image,
moving_image,
contour=None,
cuts=None,
fixed_label='F',
moving_label='M',
):
"""Plot the flickering panels to show a registration process."""
from IPython.display import SVG
from IPython.display import display as _disp
if isinstance(fixed_image, (str, Path)):
fixed_image = nb.load(str(fixed_image))
if isinstance(moving_image, (str, Path)):
moving_image = nb.load(str(moving_image))
if cuts is None:
n_cuts = 7
if contour is not None:
if isinstance(contour, (str, Path)):
contour = nb.load(str(contour))
cuts = cuts_from_bbox(contour, cuts=n_cuts)
else:
hdr = fixed_image.header.copy()
hdr.set_data_dtype('uint8')
mask_nii = nb.Nifti1Image(
np.ones(fixed_image.shape, dtype='uint8'), fixed_image.affine, hdr
)
cuts = cuts_from_bbox(mask_nii, cuts=n_cuts)
# Call composer
_disp(
SVG(
compose_view(
plot_registration(
fixed_image,
'fixed-image',
estimate_brightness=True,
cuts=cuts,
label=fixed_label,
contour=contour,
compress=False,
),
plot_registration(
moving_image,
'moving-image',
estimate_brightness=True,
cuts=cuts,
label=moving_label,
contour=contour,
compress=False,
),
)
)
)