def update_image(self, image, mode='world'):
if type(image) != ni_api.Image:
try:
image = load_spatial_image(image)
except RuntimeError:
self.image = None
self._image_loaded = False
raise
self.blender.main = image
# this reference may no longer be necessary
self.image = self.blender.main
self._image_loaded = True
# need to update:
# slider ranges
# plugin params
limits = self.blender.bbox
print 'new limits:', limits
self.update_ranges(limits)
self._update_plugin_params()
planes = self.blender.cut_image((0,0,0))
self.ortho_figs_widget.initialize_plots(planes, (0,0,0), limits)
if hasattr(self, 'mayavi_widget') and self.mayavi_widget is not None:
self.mayavi_widget.mr_vis.blender = self.blender
def update_image(self, image, mode='world'):
if type(image) != ni_api.Image:
try:
image = load_spatial_image(image)
except RuntimeError:
self.image = None
self._image_loaded = False
raise
self._image_loaded = True
self.viewer.blender.main = image
self.image = self.viewer.blender.main
self._update_plugin_args()
def load_resampled_slicer(image, bbox=None, fliplr=False, mask=False):
from xipy.slicing.image_slicers import ResampledVolumeSlicer
from xipy.io import load_spatial_image
if type(image) in (str, unicode):
return ResampledVolumeSlicer(load_spatial_image(image),
bbox=bbox,
mask=mask,
fliplr=fliplr)
elif type(image) is ni_api.Image:
return ResampledVolumeSlicer(image,
bbox=bbox,
mask=mask,
fliplr=fliplr)
elif type(image) is ResampledVolumeSlicer:
return image
else:
raise ValueError('unknown type for image argument '+str(type(image)))
def plot_tfbeam(beam, stats=None, with3d=False):
from xipy.vis.ortho_viewer import ortho_viewer
struct = load_spatial_image(beam.coreg.mrpath)
sman = TimeFreqSnPMaps(stats_results=stats)
bbox = vu.world_limits(struct)
bman = TFBeamManager(bbox, bstats_manager=sman)
bman.update_beam(beam)
win = ortho_viewer(image=struct, mayavi_viewer=with3d)
win.make_tool_from_functional_manager(NmTimeFreqWindow, bman)
win.show()
## app.exec_()
## # XYZ: this is truly ugly
bman.signal_image_props()
bman.signal_new_image()
return win
def load_sampled_slicer(overlay, bbox=None, grid_spacing=None,
mask=False, fliplr=False):
from xipy.slicing.image_slicers import SampledVolumeSlicer
from xipy.io import load_spatial_image
if type(overlay) in (str, unicode):
return SampledVolumeSlicer(load_spatial_image(overlay), bbox=bbox,
mask=mask,
grid_spacing=grid_spacing,
fliplr=fliplr)
elif type(overlay) is ni_api.Image:
return SampledVolumeSlicer(overlay, bbox=bbox,
mask=mask,
grid_spacing=grid_spacing,
fliplr=fliplr)
elif type(overlay) is SampledVolumeSlicer:
return overlay
else:
raise ValueError('unknown type for image argument '+str(type(overlay)))
from xipy import TEMPLATE_MRI_PATH
from xipy.vis.three_dee_viewer import MayaviViewer
from xipy.overlay.image_overlay import ImageOverlayManager, ImageOverlayWindow
import xipy.io as xio
from PyQt4 import QtCore, QtGui
import sys, os
if QtGui.QApplication.startingUp():
app = QtGui.QApplication(sys.argv)
else:
app = QtGui.QApplication.instance()
anat = xio.load_spatial_image(TEMPLATE_MRI_PATH)
func = xio.load_image(os.path.join(os.path.dirname(__file__),
'../data/dtk_dti_out/dti_fa.nii'))
func_man = ImageOverlayManager(None, overlay=func)
# ^^^^ API will change soon
win = MayaviViewer(image=anat)
win.make_tool_from_functional_manager(ImageOverlayWindow, func_man)
win.show()
app.exec_()
op = optparse.OptionParser(usage=usage)
op.add_option('-m', '--main-spline-order', dest='main_spline_order',
type='int', default=0)
op.add_option('-o', '--over-spline-order', dest='over_spline_order',
type='int', default=0)
return op
if __name__=='__main__':
import sys
import xipy.volume_utils as vu
import xipy.io as xio
op = make_option_parser()
op.add_option('-i', '--index-slicer', dest='use_index_slicer',
action='store_true', default=False)
(opts, args) = op.parse_args()
files = args
cls = ResampledIndexVolumeSlicer if opts.use_index_slicer \
else ResampledVolumeSlicer
orders = (opts.main_spline_order, opts.over_spline_order)
images = [cls(xio.load_spatial_image(i), order=o)
for i, o in zip(files, orders)]
if QtGui.QApplication.startingUp():
app = QtGui.QApplication(sys.argv)
else:
app = QtGui.QApplication.instance()
win = SimpleOrtho(*images)
win.show()
sys.exit(app.exec_())
planes = self.image.cut_image(xyz_loc, axes=axes)
self.ortho_figs_widget.update_plot_data(
planes, fig_labels=axes
)
if __name__=='__main__':
import sys
import xipy.io as xio
from test_two_images import make_option_parser
op = make_option_parser()
op.add_option('-t', '--vtk-order', dest='vtk_order',
action='store_true', default=False)
(opts, args) = op.parse_args()
images = []
for arg in args:
images.append(xio.load_spatial_image(arg))
images = images + [None] * (2-len(images))
if QtGui.QApplication.startingUp():
app = QtGui.QApplication(sys.argv)
else:
app = QtGui.QApplication.instance()
kws = dict(vtk_order=opts.vtk_order,
main_spline_order=opts.main_spline_order,
over_spline_order=opts.over_spline_order)
win = BlendedOrtho(*images, **kws)
win.show()
sys.exit(app.exec_())
import numpy as np
import xipy.colors.rgba_blending as rb
import xipy
import xipy.io as xio
import xipy.colors.mayavi_tools as mt
from enthought.mayavi import mlab
from enthought.tvtk.api import tvtk
over_img = xio.load_spatial_image('tfbeam_img.nii')
over_img._data = np.ma.masked_where(over_img._data > 1e10, over_img._data)
main_img = xio.load_spatial_image(xipy.TEMPLATE_MRI_PATH)
bi = rb.BlendedImages(vtk_order = True)
m_src = mt.MasterSource(blender=bi)
bi.main = main_img
bi.over = over_img
m_src = mlab.pipeline.add_dataset(m_src)
aa1 = mlab.pipeline.set_active_attribute(
m_src, point_scalars=m_src.main_channel
)
ipw1 = mt.image_plane_widget_rgba(aa1)
ipw1.ipw.plane_orientation = 'x_axes'
aa2 = mlab.pipeline.set_active_attribute(
m_src, point_scalars=m_src.main_channel
)
