def _figure_image_default(self):
plot = Plot(self.plot_data_image, width=180, height=180, padding=3, padding_left=48, padding_bottom=32)
plot.img_plot('image', colormap=jet, name='image')
plot.aspect_ratio=1
#plot.value_mapper.domain_limits = (scanner.getYRange()[0],scanner.getYRange()[1])
#plot.index_mapper.domain_limits = (scanner.getXRange()[0],scanner.getXRange()[1])
plot.value_mapper.domain_limits = (0,self.size_xy)
plot.index_mapper.domain_limits = (0,self.size_xy)
container = HPlotContainer()
image = plot.plots['image'][0]
colormap = image.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=plot,
orientation='v',
resizable='v',
width=20,
height=200,
padding=8,
padding_left=20)
container = HPlotContainer()
container.add(plot)
container.add(colorbar)
return container
def __init__(self, signal_instance):
super(TemplatePicker, self).__init__()
try:
import cv
except:
try:
import cv2.cv as cv
except:
print "OpenCV unavailable. Can't do cross correlation without it. Aborting."
return None
self.OK_custom=OK_custom_handler()
self.sig=signal_instance
if not hasattr(self.sig.mapped_parameters,"original_files"):
self.titles=[os.path.splitext(self.sig.mapped_parameters.title)[0]]
else:
self.numfiles=len(self.sig.mapped_parameters.original_files.keys())
self.titles=self.sig.mapped_parameters.original_files.keys()
tmp_plot_data=ArrayPlotData(imagedata=self.sig.data[self.img_idx,self.top:self.top+self.tmp_size,self.left:self.left+self.tmp_size])
tmp_plot=Plot(tmp_plot_data,default_origin="top left")
tmp_plot.img_plot("imagedata", colormap=jet)
tmp_plot.aspect_ratio=1.0
self.tmp_plot=tmp_plot
self.tmp_plotdata=tmp_plot_data
self.img_plotdata=ArrayPlotData(imagedata=self.sig.data[self.img_idx,:,:])
self.img_container=self._image_plot_container()
self.crop_sig=None
def _create_plot_component():
# Create a GridContainer to hold all of our plots
container = GridContainer(padding=20, fill_padding=True,
bgcolor="lightgray", use_backbuffer=True,
shape=(3,3), spacing=(12,12))
# Create the initial series of data
x = linspace(-5, 15.0, 100)
pd = ArrayPlotData(index = x)
# Plot some bessel functions and add the plots to our container
for i in range(9):
pd.set_data("y" + str(i), jn(i,x))
plot = Plot(pd)
plot.plot(("index", "y" + str(i)),
color=tuple(COLOR_PALETTE[i]), line_width=2.0,
bgcolor = "white", border_visible=True)
# Tweak some of the plot properties
plot.border_width = 1
plot.padding = 10
# Set each plot's aspect ratio based on its position in the
# 3x3 grid of plots.
n,m = divmod(i, 3)
plot.aspect_ratio = float(n+1) / (m+1)
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
# Add to the grid container
container.add(plot)
return container
def plotImage(self, image, plot=None):
'''Plots a tiff image.
| image -- Image object
| plot -- plot instance to be updated
| if None, a plot instance will be created
Returns the plot instance.
'''
if plot == None:
pd = ArrayPlotData()
pd.set_data('imagedata', image.data)
plot = Plot(pd, default_origin = "bottom left", padding=0)
plot.bgcolor = 'white'
plot.fixed_preferred_size = (100, 100)
plot.x_axis.visible = False
plot.y_axis.visible = False
self.imageplot = plot
imgPlot = plot.img_plot("imagedata", colormap=self.cmap,
name='image')[0]
self.imgPlot = imgPlot
self.appendImageTools(imgPlot)
else:
plot.data.set_data('imagedata', image.data)
plot.aspect_ratio = float(image.data.shape[1]) / image.data.shape[0]
plot.invalidate_and_redraw()
return plot
def plotRRMap(self, ydata, title, plot=None):
'''Plots an RR map.
| ydata -- y-data to be plotted
| title -- RR type, to be displayed on y-axis
| plot -- plot instance to be updated
| if None, a plot instance will be created
Returns the plot instance.
'''
if plot == None:
pd = ArrayPlotData()
plot = Plot(pd, padding=(79, 5, 0, 0))
self.setData(ydata, None, plot)
plot.plot(('x', 'y'), name='rrplot', type="scatter", color='green',
marker="circle", marker_size=6)
plot.value_axis.title = title
plot.bgcolor = 'white'
plot.aspect_ratio = 2.5
plot.fixed_preferred_size = (100, 50)
plot.y_axis.tick_label_formatter = lambda val:('%.2E'%val)
plot.x_axis.visible = False
hgrid, vgrid = add_default_grids(plot)
self.appendRRTools(plot)
else:
self.setData(ydata, None, plot)
plot.invalidate_and_redraw()
return plot
def plotImage(self, image, title, plot):
'''plot one image
image: 2d ndarray or ssp matrix
title: string, plot title
plot: plot instance to be update, if None, a plot instance will be created
return: plot instance'''
if plot == None:
pd = ArrayPlotData()
pd.set_data('imagedata', image)
plot = Plot(pd, default_origin = "bottom left")
plot.title = title
plot.bgcolor = 'white'
if not title == 'Total Intensity':
plot.x_axis.visible = False
plot.y_axis.visible = False
imgPlot = plot.img_plot("imagedata", colormap=jet, name='image')[0]
# TODO: mess with color maps on else block
else:
imgPlot = plot.img_plot("imagedata", colormap=jet, name='image')[0]
self._appendTools(imgPlot, title)
else:
plot.data.set_data('imagedata', image)
plot.title = title
plot.aspect_ratio = float(image.shape[1]) / image.shape[0]
plot.invalidate_draw()
return plot
def plotImage(self, image, plot=None):
'''plot one image
image: Image object
plot: plot instance to be update, if None, a plot instance will be created
return: plot instance'''
if plot == None:
pd = ArrayPlotData()
pd.set_data('imagedata', image.data)
plot = Plot(pd, default_origin = "bottom left", padding=0)
#plot.title = image.name
plot.bgcolor = 'white'
plot.fixed_preferred_size = (100, 100)
plot.x_axis.visible = False
plot.y_axis.visible = False
self.imageplot = plot
# TODO: mess with color maps on else block
imgPlot = plot.img_plot("imagedata", colormap=jet, name='image')[0]
self.imgPlot = imgPlot
self._appendImageTools(imgPlot)
#plot.overlays.append(MyLineDrawer(plot))
else:
plot.data.set_data('imagedata', image.data)
imgPlot = plot.plots['image'][0]
#plot.title = image.name
plot.aspect_ratio = float(image.data.shape[1]) / image.data.shape[0]
plot.invalidate_draw()
return plot
def _plot_default(self):
julia = self.model.julia
apd = ArrayPlotData(julia=julia[:-1,:-1])
grid = np.linspace(-2, 2, self.model.resolution-1)
X, Y = np.meshgrid(grid, grid)
plot = Plot(apd)
plot.aspect_ratio = 1.0
plot.img_plot("julia", xbounds=X, ybounds=Y,
colormap=hot, interpolation='nearest')
return plot
def _mandelbrot_plot_default(self):
plot = Plot(self.plot_data)
renderer = plot.img_plot('mandelbrot',
xbounds=self.model.x_coords,
ybounds=self.model.y_coords)[0]
plot.aspect_ratio = 1.0
return plot
def _mandelbrot_plot_default(self):
plot = Plot(self.plot_data)
renderer = plot.img_plot(
'mandelbrot',
xbounds=self.model.x_coords,
ybounds=self.model.y_coords)[0]
plot.aspect_ratio = 1.0
return plot
def _create_mandelbrot_plot(self):
plot = Plot(self.mandelbrot_plot_data)
self.mandelbrot_renderer = plot.img_plot(
'mandelbrot',
xbounds=self.model.x_coords,
ybounds=self.model.y_coords,
name='mandelbrot_plot')[0]
plot.aspect_ratio = 1.0
plot.tools.append(MandelzoomTool(component=plot, params=self.model))
self.set_colormap()
return plot
def render_image(self):
plot = Plot(self.img_plotdata,default_origin="top left")
img=plot.img_plot("imagedata", colormap=gray)[0]
plot.title="%s of %s: "%(self.img_idx+1,self.numfiles)+self.titles[self.img_idx]
plot.aspect_ratio=float(self.sig.data.shape[2])/float(self.sig.data.shape[1])
csr = CursorTool(img, drag_button='left', color='white',
line_width=2.0)
self.csr=csr
csr.current_position=self.left, self.top
img.overlays.append(csr)
# attach the rectangle tool
plot.tools.append(PanTool(plot,drag_button="right"))
zoom = ZoomTool(plot, tool_mode="box", always_on=False, aspect_ratio=plot.aspect_ratio)
plot.overlays.append(zoom)
self.img_plot=plot
return plot
def __init__(self, controller, *args, **kw):
super(CellCropper, self).__init__(controller, *args, **kw)
try:
import cv
except:
try:
import cv2.cv as cv
except:
print "OpenCV unavailable. Can't do cross correlation without it. Aborting."
return None
self.OK_custom=OK_custom_handler()
self.template = self.data[self.top:self.top+self.tmp_size,self.left:self.left+self.tmp_size]
tmp_plot_data=ArrayPlotData(imagedata=self.template)
tmp_plot=Plot(tmp_plot_data,default_origin="top left")
tmp_plot.img_plot("imagedata", colormap=jet)
tmp_plot.aspect_ratio=1.0
self.tmp_plot=tmp_plot
self.tmp_plotdata=tmp_plot_data
self.crop_sig=None
def plotRRMap(self, rr, rrchoice, plot=None):
if plot == None:
pd = ArrayPlotData(y=np.array([0]), x=np.array([0]))
plot = Plot(pd, padding=(70, 5, 0, 0))
self._setData(rr, plot)
plot.plot(('x', 'y'), name='rrplot', type="scatter", color='green',
marker="circle", marker_size=6)
#plot.title = 'rrplot'
plot.value_axis.title = rrchoice
#plot.y_axis.visible = False
plot.bgcolor = 'white'
plot.aspect_ratio = 2.5
plot.fixed_preferred_size = (100, 50)
#left, bottom = add_default_axes(plot)
hgrid, vgrid = add_default_grids(plot)
self._appendCMapTools(plot)
else:
self._setData(rr, plot)
plot.request_redraw()
return plot
def _render_image(array_plot_data, title=None, tools=["zoom","pan"]):
plot = Plot(array_plot_data, default_origin="top left")
# the cursor tool, if any
csr = None
img_renderer = plot.img_plot("imagedata", colormap=gray, name="base_plot")[0]
# todo: generalize title and aspect ratio
plot.title = title
data_array = array_plot_data.arrays['imagedata']
plot.aspect_ratio=float(data_array.shape[1]) / float(data_array.shape[0])
# attach the rectangle tool
if "pan" in tools:
plot.tools.append(PanTool(plot,drag_button="right"))
if "zoom" in tools:
zoom = ZoomTool(plot, tool_mode="box", always_on=False, aspect_ratio=plot.aspect_ratio)
plot.overlays.append(zoom)
if "csr" in tools:
csr = CursorTool(img_renderer, drag_button='left', color='red',
line_width=2.0)
csr.current_position = 64, 64
img_renderer.overlays.append(csr)
return plot, csr
def _plot_default(self):
distr_len = len(self.data)
# PolygonPlot holding the circles of the Hinton diagram
polyplot = Plot(self.plot_data)
for idx in range(distr_len):
p = polyplot.plot(('x%d' % idx, 'y%d' % idx),
type="polygon",
face_color=get_class_color(idx),
edge_color='black')
self._set_title(polyplot)
self._remove_grid_and_axes(polyplot)
# create x axis for labels
axis = self._create_increment_one_axis(polyplot, 1., distr_len,
'bottom')
self._add_index_axis(polyplot, axis)
# create y axis for probability density
#prob_axis = self._create_probability_axis(polyplot)
#polyplot.value_axis = prob_axis
#polyplot.underlays.append(prob_axis)
# tweak some of the plot properties
range2d = DataRange2D(low=(0.5, 0.), high=(distr_len + 0.5, 1.))
polyplot.range2d = range2d
polyplot.aspect_ratio = ((range2d.x_range.high - range2d.x_range.low) /
(range2d.y_range.high - range2d.y_range.low))
polyplot.border_visible = False
polyplot.padding = [0, 0, 25, 25]
# create a container to position the plot and the colorbar side-by-side
container = HPlotContainer(use_backbuffer=True, valign='center')
container.add(polyplot)
container.bgcolor = 0xFFFFFF # light gray: 0xEEEEEE
self.decorate_plot(container, self.data)
return container
def _create_plot_component():
# Create a GridContainer to hold all of our plots
container = GridContainer(padding=20,
fill_padding=True,
bgcolor="lightgray",
use_backbuffer=True,
shape=(3, 3),
spacing=(12, 12))
# Create the initial series of data
x = linspace(-5, 15.0, 100)
pd = ArrayPlotData(index=x)
# Plot some bessel functions and add the plots to our container
for i in range(9):
pd.set_data("y" + str(i), jn(i, x))
plot = Plot(pd)
plot.plot(("index", "y" + str(i)),
color=tuple(COLOR_PALETTE[i]),
line_width=2.0,
bgcolor="white",
border_visible=True)
# Tweak some of the plot properties
plot.border_width = 1
plot.padding = 10
# Set each plot's aspect ratio based on its position in the
# 3x3 grid of plots.
n, m = divmod(i, 3)
plot.aspect_ratio = float(n + 1) / (m + 1)
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
# Add to the grid container
container.add(plot)
return container
def _reconstruction_default(self):
self.plot_data = ArrayPlotData(original=self.image,
reconstruction=self.result)
rows, cols = self.image.shape[:2]
aspect = cols / float(rows)
old = Plot(self.plot_data)
old.img_plot('original', colormap=gray, origin='top left')
old.title = 'Old'
old.aspect_ratio = aspect
self.new = Plot(self.plot_data)
self.new.img_plot('reconstruction', colormap=gray, origin='top left')
self.new.title = 'New'
self.new.aspect_ratio = aspect
container = HPlotContainer(bgcolor='none')
container.add(old)
container.add(self.new)
return container
def _reconstruction_default(self):
self.plot_data = ArrayPlotData(original=self.image,
reconstruction=self.result)
rows, cols = self.image.shape[:2]
aspect = cols/float(rows)
old = Plot(self.plot_data)
old.img_plot('original', colormap=gray, origin='top left')
old.title = 'Old'
old.aspect_ratio = aspect
self.new = Plot(self.plot_data)
self.new.img_plot('reconstruction', colormap=gray, origin='top left')
self.new.title = 'New'
self.new.aspect_ratio = aspect
container = HPlotContainer(bgcolor='none')
container.add(old)
container.add(self.new)
return container
def _plot_default(self):
distr_len = len(self.data)
# PolygonPlot holding the circles of the Hinton diagram
polyplot = Plot(self.plot_data)
for idx in range(distr_len):
p = polyplot.plot(('x%d' % idx, 'y%d' % idx),
type="polygon",
face_color=get_class_color(idx),
edge_color='black')
self._set_title(polyplot)
self._remove_grid_and_axes(polyplot)
# create x axis for labels
axis = self._create_increment_one_axis(polyplot, 1., distr_len, 'bottom')
self._add_index_axis(polyplot, axis)
# create y axis for probability density
#prob_axis = self._create_probability_axis(polyplot)
#polyplot.value_axis = prob_axis
#polyplot.underlays.append(prob_axis)
# tweak some of the plot properties
range2d = DataRange2D(low=(0.5, 0.), high=(distr_len+0.5, 1.))
polyplot.range2d = range2d
polyplot.aspect_ratio = ((range2d.x_range.high - range2d.x_range.low)
/ (range2d.y_range.high - range2d.y_range.low))
polyplot.border_visible = False
polyplot.padding = [0, 0, 25, 25]
# create a container to position the plot and the colorbar side-by-side
container = HPlotContainer(use_backbuffer=True, valign='center')
container.add(polyplot)
container.bgcolor = 0xFFFFFF # light gray: 0xEEEEEE
self.decorate_plot(container, self.data)
return container
def _brain_default(self):
plot = Plot(self.brain_data, padding=0)
plot.width = self.brain_voxels.shape[1]
plot.height = self.brain_voxels.shape[0]
plot.aspect_ratio = 1.
plot.index_axis.visible = False
plot.value_axis.visible = False
renderer = plot.img_plot("axial", colormap=gray)[0]
plot.color_mapper.range = DataRange1D(low=0., high=1.0)
plot.bgcolor = 'pink'
# Brain tools
plot.tools.append(PanTool(plot, drag_button="right"))
plot.tools.append(ZoomTool(plot))
imgtool = ImageInspectorTool(renderer)
renderer.tools.append(imgtool)
overlay = ImageInspectorOverlay(component=renderer, image_inspector=imgtool,
bgcolor="white", border_visible=True)
renderer.overlays.append(overlay)
# Brain track cursor
self.cursor = CursorTool2D(renderer, drag_button='left', color='red', line_width=2.0)
#self.cursor.on_trait_change(self.update_stackedhist, 'current_index')
self.cursor.current_positionyou = (0., 0.)
renderer.overlays.append(self.cursor)
# Brain colorbar
colormap = plot.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=plot,
orientation='v',
resizable='v',
width=20,
padding=(30, 0, 0, 0))
colorbar.padding_top = plot.padding_top
colorbar.padding_bottom = plot.padding_bottom
# Noisy brain
plot2 = Plot(self.brain_data, padding=0)
plot2.width = self.brain_voxels.shape[1]
plot2.height = self.brain_voxels.shape[0]
plot2.aspect_ratio = 1.
plot2.index_axis.visible = False
plot2.value_axis.visible = False
renderer2 = plot2.img_plot("noisy_axial", colormap=gray)[0]
plot2.color_mapper.range = DataRange1D(low=0., high=1.0)
plot2.bgcolor = 'pink'
plot2.range2d = plot.range2d
# Brain_map tools
plot2.tools.append(PanTool(plot2, drag_button="right"))
plot2.tools.append(ZoomTool(plot2))
imgtool2 = ImageInspectorTool(renderer2)
renderer2.tools.append(imgtool2)
overlay2 = ImageInspectorOverlay(component=renderer2, image_inspector=imgtool2,
bgcolor="white", border_visible=True)
renderer2.overlays.append(overlay2)
# Brain_map track cursor
self.cursor2 = CursorTool2D(renderer2, drag_button='left', color='red', line_width=2.0)
#self.cursor2.on_trait_change(self.cursor2_changed, 'current_index')
self.cursor2.current_position = (0., 0.)
renderer2.overlays.append(self.cursor2)
# Brain_map colorbar
colormap2 = plot2.color_mapper
colorbar2 = ColorBar(index_mapper=LinearMapper(range=colormap2.range),
color_mapper=colormap2,
plot=plot2,
orientation='v',
resizable='v',
width=20,
padding=(30, 0, 0, 0))
colorbar2.padding_top = plot2.padding_top
colorbar2.padding_bottom = plot2.padding_bottom
# Create a container to position the plot and the colorbar side-by-side
container = HPlotContainer(use_backbuffer=True, padding=(0, 0, 10, 10))
container.add(plot)
container.add(colorbar)
container.bgcolor = "lightgray"
container2 = HPlotContainer(use_backbuffer=True, padding=(0, 0, 10, 10))
container2.add(plot2)
container2.add(colorbar2)
container2.bgcolor = "lightgray"
Hcontainer = HPlotContainer(use_backbuffer=True)
Hcontainer.add(container)
Hcontainer.add(container2)
Hcontainer.bgcolor = "lightgray"
return Hcontainer
