def __init__(self):
# Create the data and the PlotData object
x = linspace(-14, 14, 100)
y = sin(x) * x**3
plotdata = ArrayPlotData(x = x, y = y)
# Create the scatter plot
scatter = Plot(plotdata)
scatter.plot(("x", "y"), type="scatter", color="blue")
# Create the line plot
line = Plot(plotdata)
line.plot(("x", "y"), type="line", color="blue")
# Create a horizontal container and put the two plots inside it
container = HPlotContainer(scatter, line)
container.spacing = 0
scatter.padding_right = 0
line.padding_left = 0
line.y_axis.orientation = "right"
self.plot = container
def _create_plot_component(file_name):
# Create a scalar field to colormap
z = load(file_name)
pd = ArrayPlotData()
pd.set_data("imagedata", z)
# Create the plot
plot = Plot(pd)
plot.bgcolor = 'gray'
img_plot = plot.img_plot("imagedata",
name='my_plot',
colormap=jet,
hide_grids=True)[0]
#cont_plot=plot.contour_plot('imagedata', type='line', name='countour')
# Tweak some of the plot properties
#plot.title = file_name
plot.padding = 40
plot.padding_right=20
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
#plot.tools.append(TraitsTool(plot))
zoom = ZoomTool(component=img_plot, tool_mode="box", always_on=False)
img_plot.overlays.append(zoom)
#plot.y_axis.tick_label_formatter = lambda x: "%.3e" % x
#plot.x_axis.tick_label_formatter = lambda x: "%.3e" % x
#plot.tools.append(SaveTool(plot))
# Right now, some of the tools are a little invasive, and we need the
# actual CMapImage object to give to them
my_plot = img_plot#plot.plots["my_plot"][0]
colormap = my_plot.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=my_plot,
orientation='v',
resizable='v',
width=25,
padding=0)
colorbar.origin = 'bottom left'
#colorbar._axis.tick_label_formatter = lambda x: '%.0e'%(x*10e6) + u' [\u00b5' + 'Watt]'
colorbar._axis.tick_label_formatter = lambda x: ('%.0e'%(x*1e6))
colorbar._axis.orientation = 'right'
colorbar._axis.title = u'Intensity [\u00b5W]'
colorbar.padding_top = plot.padding_top
colorbar.padding_bottom = plot.padding_bottom
colorbar.padding_right = 100
# create a range selection for the colorbar
range_selection = RangeSelection(component=colorbar)
colorbar.tools.append(range_selection)
colorbar.overlays.append(RangeSelectionOverlay(component=colorbar,
border_color="white",
alpha=0.5,
fill_color="lightgray"))
range_selection.listeners.append(my_plot)
imgtool = ImageInspectorTool(img_plot)
img_plot.tools.append(imgtool)
plot.overlays.append(ImageInspectorOverlay(component=img_plot, image_inspector=imgtool))
# we also want to the range selection to inform the cmap plot of
# the selection, so set that up as well
# Create a container to position the plot and the colorbar side-by-side
container = HPlotContainer(use_backbuffer = True)
container.add(plot)
container.add(colorbar)
container.bgcolor = "white"
container.tools.append(SaveTool(container))
container.tools.append(TraitsTool(container))
#my_plot.set_value_selection((-1.3, 6.9))
return container
