def screenshot_tracking(tracking, t1, directory="."):
"""
Compute 3 view screenshot with streamlines on T1.
Parameters
----------
tracking : string
tractogram filename.
t1 : string
t1 filename.
directory : string
Directory to save the mosaic.
Returns
-------
name : string
Path of the mosaic
"""
tractogram = nib.streamlines.load(tracking, True).tractogram
t1 = nib.load(t1)
t1_data = t1.get_data()
slice_name = ['sagittal', 'coronal', 'axial']
img_center = [(int(t1_data.shape[0] / 2) + 5, None, None),
(None, int(t1_data.shape[1] / 2), None),
(None, None, int(t1_data.shape[2] / 2))]
center = [(330, 90, 60), (70, 330, 60), (70, 90, 400)]
viewup = [(0, 0, -1), (0, 0, -1), (0, -1, 0)]
size = (1920, 1080)
image = np.array([])
for i, _axis in enumerate(slice_name):
streamlines = []
it = 0
slice_idx = img_center[i][i]
for streamline in tractogram:
if it > 10000:
break
stream = streamline.streamline
if slice_idx in np.array(stream, dtype=int)[:, i]:
it += 1
idx = np.where(np.array(stream, dtype=int)[:, i] == \
slice_idx)[0][0]
lower = idx - 2
if lower < 0:
lower = 0
upper = idx + 2
if upper > len(stream) - 1:
upper = len(stream) - 1
streamlines.append(stream[lower:upper])
ren = window.Renderer()
streamline_actor = actor.line(streamlines, linewidth=0.2)
ren.add(streamline_actor)
min_val = np.min(t1_data[t1_data > 0])
max_val = np.percentile(t1_data[t1_data > 0], 99)
t1_color = np.float32(t1_data - min_val) \
/ np.float32(max_val - min_val) * 255.0
slice_actor = actor.slicer(t1_color, opacity=0.8, value_range=(0, 255),
interpolation='nearest')
ren.add(slice_actor)
slice_actor.display(img_center[i][0], img_center[i][1],
img_center[i][2])
camera = ren.GetActiveCamera()
camera.SetViewUp(viewup[i])
center_cam = streamline_actor.GetCenter()
camera.SetPosition(center[i])
camera.SetFocalPoint((center_cam))
img2 = renderer_to_arr(ren, size)
if image.size == 0:
image = img2
else:
image = np.hstack((image, img2))
streamlines = []
it = 0
for streamline in tractogram:
if it > 10000:
break
it += 1
streamlines.append(streamline.streamline)
ren = window.Renderer()
streamline_actor = actor.streamtube(streamlines, linewidth=0.2)
ren.add(streamline_actor)
camera = ren.GetActiveCamera()
camera.SetViewUp(0, 0, -1)
center = streamline_actor.GetCenter()
camera.SetPosition(center[0], 350, center[2])
camera.SetFocalPoint(center)
img2 = renderer_to_arr(ren, (3 * 1920, 1920))
image = np.vstack((image, img2))
imgs_comb = Image.fromarray(image)
imgs_comb = imgs_comb.resize((3 * 1920, 1920 + 1080))
image_name = os.path.basename(str(tracking)).split(".")[0]
name = os.path.join(directory, image_name + '.png')
imgs_comb.save(name)
return name
def screenshot_fa_peaks(fa, peaks, directory='.'):
"""
Compute 3 view screenshot with peaks on FA.
Parameters
----------
fa : string
FA filename.
peaks : string
Peak filename.
directory : string
Directory to save the mosaic.
Returns
-------
name : string
Path of the mosaic
"""
slice_name = ['sagittal', 'coronal', 'axial']
data = nib.load(fa).get_data()
evecs_data = nib.load(peaks).get_data()
evecs = np.zeros(data.shape + (1, 3))
evecs[:, :, :, 0, :] = evecs_data[...]
middle = [data.shape[0] // 2 + 4, data.shape[1] // 2,
data.shape[2] // 2]
slice_display = [(middle[0], None, None), (None, middle[1], None),
(None, None, middle[2])]
concat = []
for j, slice_name in enumerate(slice_name):
image_name = os.path.basename(str(peaks)).split(".")[0]
name = os.path.join(directory, image_name + '.png')
slice_actor = actor.slicer(data, interpolation='nearest', opacity=0.3)
peak_actor = actor.peak_slicer(evecs, colors=None)
peak_actor.GetProperty().SetLineWidth(2.5)
slice_actor.display(slice_display[j][0], slice_display[j][1],
slice_display[j][2])
peak_actor.display(slice_display[j][0], slice_display[j][1],
slice_display[j][2])
renderer = window.ren()
renderer.add(slice_actor)
renderer.add(peak_actor)
center = slice_actor.GetCenter()
pos = None
viewup = None
if slice_name == "sagittal":
pos = (center[0] - 350, center[1], center[2])
viewup = (0, 0, -1)
elif slice_name == "coronal":
pos = (center[0], center[1] + 350, center[2])
viewup = (0, 0, -1)
elif slice_name == "axial":
pos = (center[0], center[1], center[2] + 350)
viewup = (0, -1, 1)
camera = renderer.GetActiveCamera()
camera.SetViewUp(viewup)
camera.SetPosition(pos)
camera.SetFocalPoint(center)
img = renderer_to_arr(renderer, (1080, 1080))
if len(concat) == 0:
concat = img
else:
concat = np.hstack((concat, img))
imgs_comb = Image.fromarray(concat)
imgs_comb.save(name)
return name