def display_graph_example():
"""Display a simple (probabilistic) graphical model in the browser. """
d = DisplayNode()
graph = {
'nodes': [{
'name': 'A',
'type': 0
}, {
'name': 'B',
'type': 1
}, {
'name': 'C',
'type': 0
}, {
'name': 'D',
'type': 2
}],
'links': [{
'source': 'A',
'target': 'B',
'type': 't1'
}, {
'source': 'A',
'target': 'C',
'type': 't1'
}, {
'source': 'C',
'target': 'D',
'type': 't2'
}]
}
d.display_in_browser('graph', graph)
def display(self,
axis=None,
shrink=None,
rotate=None,
subsample_slices=None,
scales=None,
open_browser=None):
if axis is None:
axis = self._axis
if shrink is None:
shrink = self._shrink
if rotate is None:
rotate = self._rotate
if subsample_slices is None:
subsample_slices = self._subsample_slices
if subsample_slices is None:
subsample_slices = 1
if scales is None:
scales = self._scales
if open_browser is None:
open_browser = self._open_browser
if open_browser is None:
open_browser = False
D = DisplayNode()
images = []
n = 0
N_slices = 0
for j in range(len(self.volumes)):
N_slices += self.get_shape(j)[axis]
self._progress_bar = ProgressBar(height='6px',
width='100%%',
background_color=C.LIGHT_GRAY,
foreground_color=C.GRAY)
for j in range(len(self.volumes)):
if scales is None:
scale = 255 / (self.get_data(j).max() + 1e-9)
else:
scale = scales[j] * 255 / (self.get_data(j).max() + 1e-9)
images_inner = []
for i in range(0, self.get_shape(j)[axis], subsample_slices):
im = self.export_image(j,
i,
axis,
normalise=True,
scale=scale,
shrink=shrink,
rotate=rotate)
images_inner.append(im)
n += 1
self._progress_bar.set_percentage(n * 100.0 / N_slices *
subsample_slices)
images.append(images_inner)
return D.display('tipix', images, open_browser)
def display_image_example():
"""Display an image in the browser using Openseadragon.js """
N = 512
N_tiles = 6
max_iter = 6
d = DisplayNode()
print("Wait, generating awesome images .. ")
image = Image.new("RGB",(N*N_tiles,N))
for i in range(N_tiles):
print("%d / %d "%(i+1,N_tiles))
tile = polygon_fractal(n=i+3,imgx=N,imgy=N,maxIt=max_iter)
image.paste(tile,(i*N,0))
d.display_in_browser('image',image)
def display_image_example():
"""Display an image in the browser using Openseadragon.js """
N = 512
N_tiles = 6
max_iter = 6
d = DisplayNode()
print "Wait, generating awesome images .. "
image = Image.new("RGB",(N*N_tiles,N))
for i in range(N_tiles):
print "%d / %d "%(i+1,N_tiles)
tile = polygon_fractal(n=i+3,imgx=N,imgy=N,maxIt=max_iter)
image.paste(tile,(i*N,0))
d.display_in_browser('image',image)
def display(self, axis=None, max_size=256, open_browser=None):
if axis is None:
axis = self._axis
if open_browser is None:
open_browser = self._open_browser
if open_browser is None:
open_browser = False
D = DisplayNode()
self._progress_bar = ProgressBar(height='6px',
width='100%%',
background_color=C.LIGHT_GRAY,
foreground_color=C.GRAY)
volume = self.volumes[0] #FIXME: optionally use other grid
# make grid of regularly-spaced points
box_min = volume.get_world_grid_min()
box_max = volume.get_world_grid_max()
span = box_max - box_min
max_span = span.max()
n_points = numpy.uint32(span / max_span * max_size)
grid = volume.get_world_grid(n_points)
n = 0
images = []
for index in range(len(self.volumes)):
volume = self.volumes[index]
resampled = volume.compute_resample_on_grid(grid).data
self._resampled = resampled
sequence = []
for slice_index in range(n_points[axis]):
if axis == 0:
a = numpy.float32(resampled[slice_index, :, :].reshape(
(resampled.shape[1], resampled.shape[2])))
elif axis == 1:
a = numpy.float32(resampled[:, slice_index, :].reshape(
(resampled.shape[0], resampled.shape[2])))
else:
a = numpy.float32(resampled[:, :, slice_index].reshape(
(resampled.shape[0], resampled.shape[1])))
lookup_table = volume.get_lookup_table()
im = self.__array_to_im(a, lookup_table)
sequence.append(im.rotate(90)) #FIXME: make optional
n += 1
self._progress_bar.set_percentage(
n * 100.0 / (len(self.volumes) * max_size))
images.append(sequence)
if len(images) == 1:
return D.display('tipix', images[0], open_browser)
else:
return D.display('tipix', images, open_browser)
def display(self,scale=None,open_browser=False):
data = self.data
d = DisplayNode()
images = []
progress_bar = ProgressBar(height='6px', width='100%%', background_color=C.LIGHT_GRAY, foreground_color=C.GRAY)
if scale is not None:
scale = scale*255.0/(data.max()+1e-12)
else:
scale = 255.0/(data.max()+1e-12)
N_projections = self.data.shape[2]
N_x = self.data.shape[0]
N_y = self.data.shape[1]
print "SPECT Projection [N_projections: %d N_x: %d N_y: %d]"%(N_projections,N_x,N_y)
for i in range( N_projections ):
images.append( self.to_image(data,i,scale=scale,absolute_scale=True) )
progress_bar.set_percentage(i*100.0/N_projections)
progress_bar.set_percentage(100.0)
return d.display('tipix', images, open_browser)
def display(self,scale=None,open_browser=False):
data = self.data
d = DisplayNode()
images = []
progress_bar = ProgressBar(height='6px', width='100%%', background_color=LIGHT_GRAY, foreground_color=GRAY)
if scale is not None:
scale = scale * 255.0 / (data.max() + 1e-12)
else:
scale = 255.0 / (data.max() + 1e-12)
N_projections = self.data.shape[2]
N_x = self.data.shape[0]
N_y = self.data.shape[1]
print("SPECT Projection [N_projections: %d N_x: %d N_y: %d]" % (N_projections, N_x, N_y))
for i in range(N_projections):
images.append(self.to_image(data, i, scale=scale, absolute_scale=True))
progress_bar.set_percentage(i * 100.0 / N_projections)
progress_bar.set_percentage(100.0)
return d.display('tipix', images, open_browser)
def display(self,axis=None, max_size=256, open_browser=None):
if axis is None:
axis = self._axis
if open_browser is None:
open_browser = self._open_browser
if open_browser is None:
open_browser = False
D = DisplayNode()
self._progress_bar = ProgressBar(height='6px', width='100%%', background_color=C.LIGHT_GRAY, foreground_color=C.GRAY)
volume = self.volumes[0] #FIXME: optionally use other grid
# make grid of regularly-spaced points
box_min = volume.get_world_grid_min()
box_max = volume.get_world_grid_max()
span = box_max-box_min
max_span = span.max()
n_points = numpy.uint32(span / max_span * max_size)
grid = volume.get_world_grid(n_points)
n=0
images = []
for index in range(len(self.volumes)):
volume = self.volumes[index]
resampled = volume.compute_resample_on_grid(grid).data
self._resampled = resampled
sequence = []
for slice_index in range(n_points[axis]):
if axis == 0:
a = numpy.float32(resampled[slice_index,:,:].reshape((resampled.shape[1],resampled.shape[2])))
elif axis == 1:
a = numpy.float32(resampled[:,slice_index,:].reshape((resampled.shape[0],resampled.shape[2])))
else:
a = numpy.float32(resampled[:,:,slice_index].reshape((resampled.shape[0],resampled.shape[1])))
lookup_table = volume.get_lookup_table()
im = self.__array_to_im( a, lookup_table )
sequence.append(im.rotate(90)) #FIXME: make optional
n+=1
self._progress_bar.set_percentage(n*100.0/(len(self.volumes)*max_size))
images.append(sequence)
if len(images)==1:
return D.display('tipix', images[0], open_browser)
else:
return D.display('tipix', images, open_browser)
def display(self,axis=None,shrink=None,rotate=None,subsample_slices=None,scales=None,open_browser=None):
if axis is None:
axis = self._axis
if shrink is None:
shrink = self._shrink
if rotate is None:
rotate = self._rotate
if subsample_slices is None:
subsample_slices = self._subsample_slices
if subsample_slices is None:
subsample_slices=1
if scales is None:
scales = self._scales
if open_browser is None:
open_browser = self._open_browser
if open_browser is None:
open_browser = False
D = DisplayNode()
images = []
n=0
N_slices = 0
for j in range(len(self.volumes)):
N_slices += self.get_shape(j)[axis]
self._progress_bar = ProgressBar(height='6px', width='100%%', background_color=C.LIGHT_GRAY, foreground_color=C.GRAY)
for j in range(len(self.volumes)):
if scales is None:
scale = 255/(self.get_data(j).max()+1e-9)
else:
scale = scales[j]*255/(self.get_data(j).max()+1e-9)
images_inner = []
for i in range(0,self.get_shape(j)[axis],subsample_slices):
im = self.export_image(j,i,axis,normalise=True,scale=scale,shrink=shrink,rotate=rotate)
images_inner.append(im)
n+=1
self._progress_bar.set_percentage(n*100.0/N_slices*subsample_slices)
images.append(images_inner)
return D.display('tipix', images, open_browser)
def _repr_html_(self):
d = DisplayNode()
d.display('graph', self.make_graph_of_self() )
return d._repr_html_()
def display_geometry_example():
"Under development: webGL display based on three.js "
d = DisplayNode()
d.display_in_browser("three_cubes",{})
def _repr_html_(self):
display_node = DisplayNode()
return display_node.display('graph',self.export_dictionary())._repr_html_()
def display_in_browser(self):
"""Displays the graph in a web browser. """
display_node = DisplayNode()
display_node.display_in_browser('graph',self.export_dictionary())
def _repr_html_(self):
d = DisplayNode()
d.display('graph', self.make_graph_of_self() )
return d._repr_html_()
def display_geometry_example():
"Under development: webGL display based on three.js "
d = DisplayNode()
d.display_in_browser("three_cubes",{})
def display_graph_example():
"""Display a simple (probabilistic) graphical model in the browser. """
d = DisplayNode()
graph = {'nodes':[{'name': 'A', 'type': 0}, {'name': 'B', 'type': 1}, {'name': 'C', 'type': 0}, {'name': 'D', 'type': 2}], 'links': [{'source': 'A', 'target': 'B', 'type': 't1'},
{'source': 'A', 'target': 'C', 'type': 't1'},{'source': 'C', 'target': 'D', 'type': 't2'} ] }
d.display_in_browser('graph',graph)
