def _create_plot_component():
# Create some RGBA image data
image = zeros((200,400,4), dtype=uint8)
image[:,0:40,0] += 255 # Vertical red stripe
image[0:25,:,1] += 255 # Horizontal green stripe; also yellow square
image[-80:,-160:,2] += 255 # Blue square
image[:,:,3] = 255
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("imagedata", image)
# Create the plot
plot = Plot(pd, default_origin="top left")
plot.x_axis.orientation = "top"
img_plot = plot.img_plot("imagedata")[0]
# Tweak some of the plot properties
plot.bgcolor = "white"
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
plot.overlays.append(ZoomTool(component=plot,
tool_mode="box", always_on=False))
imgtool = ImageInspectorTool(img_plot)
img_plot.tools.append(imgtool)
plot.overlays.append(ImageInspectorOverlay(component=img_plot,
image_inspector=imgtool))
return plot
def _create_plot_component(self):
pd = self.pd
# Create the plot
plot = Plot(pd, default_origin="top left",orientation="h")
shape = pd.get_data('imagedata').shape
plot.aspect_ratio = float(shape[1]) / shape[0]
plot.x_axis.orientation = "top"
#plot.y_axis.orientation = "top"
#img_plot = plot.img_plot("imagedata",colormap = jet)[0]
img_plot = plot.img_plot("imagedata",name = 'image', colormap = jet)[0]
# Tweak some of the plot properties
#plot.bgcolor = "white"
plot.bgcolor = bg_color
# Attach some tools to the plot
plot.tools.append(PanTool(plot,constrain_key="shift", drag_button = 'right'))
printer = DataPrinter(component=plot, process = self.process_selection)
plot.tools.append(printer)
plot.overlays.append(ZoomTool(component=plot,
tool_mode="box", always_on=False))
#plot.title = 'Default image'
imgtool = ImageInspectorTool(img_plot)
img_plot.tools.append(imgtool)
plot.overlays.append(ImageInspectorOverlay(component=img_plot,
image_inspector=imgtool))
return plot
def _image_plot_default(self):
plot = Plot(self.image_data, default_origin="top left")
#plot.x_axis.orientation = "top"
img_plot = plot.img_plot("image_data")[0]
plot.bgcolor = "black"
return plot
def _vr_image_plot_default(self):
plot = Plot(self.vr_image_data, default_origin="top left",
size=(512,512))
plot.aspect_ratio = 1.0
#plot.x_axis.orientation = "top"
img_plot = plot.img_plot("vr_image_data")[0]
plot.bgcolor = "black"
return plot
def _phi_plot_default(self):
data = ArrayPlotData(h=self.h_range, phi=self.phi_sample)
p = Plot(data)
p.plot(('h', 'phi'), type='line', name='phi', color='slateblue', line_width=2.7)
p.x_axis.title = 'h'
p.y_axis.title = 'Phi[h]'
p.x_grid.line_color = p.y_grid.line_color = 'slategray'
p.bgcolor = 'khaki'
p.title = 'Nonlinearity'
return p
def _units_plot_default(self):
N = min([self.N_CA, DISP_UNITS])
data = ArrayPlotData(i=numpy.arange(N), r=self.r[:N], i_aff=self.i_aff[:N])
p = Plot(data)
p.plot(('i', 'r', 'i_aff'), type='cmap_scatter', color_mapper=hot,
marker='circle', marker_size=3, line_width=0)
p.title = 'Place Cell Output'
p.x_axis.title = 'Output Units'
p.y_axis.title = 'Rate / Iaff'
p.value_range.set_bounds(0.0, 1.0)
p.x_grid.visible = p.y_grid.visible = False
p.bgcolor = 'slategray'
return p
def _create_plot_component(self):
# Create the plot
pd = self.pd
plot = Plot(pd, default_origin="top left", orientation="h")
plot.x_axis.orientation = "top"
plot.padding = 20
#plot.y_axis.orientation = "top"
# Tweak some of the plot properties
#plot.bgcolor = "white"
plot.bgcolor = bg_color
# Attach some tools to the plot
# plot.tools.append(PanTool(plot,constrain_key="shift", drag_button = 'right'))
printer = DataPrinter(component=plot, process=self.process_selection)
plot.tools.append(printer)
plot.overlays.append(
ZoomTool(component=plot, tool_mode="box", always_on=False))
return plot
def _field_plots_default(self):
zero = numpy.array([0], 'd')
data = ArrayPlotData(t=zero, h_rec=zero, h_aff=zero, h_sum=zero)
p = Plot(data)
p.plot(('t', 'h_aff'), name='Afferent', type='line', line_width=1, color='royalblue')
p.plot(('t', 'h_rec'), name='Recurrent', type='line', line_width=1, color='tomato')
p.plot(('t', 'h_sum'), name='Total', type='line', line_width=1, color='sienna')
p.legend.visible = True
p.legend.border_visible = False
p.legend.align = 'ur'
p.legend.bgcolor = (0.8, 0.8, 1.0, 0.4)
p.legend.border_padding = 6
p.legend.labels = ['Afferent', 'Recurrent', 'Total']
p.y_grid.visible = p.x_grid.visible = False
p.title = 'Synaptic Fields'
p.x_axis.title = 'Time (s)'
p.y_axis.title = 'Field Strength'
p.bgcolor = 'mintcream'
return p
def _plot_default(self):
self._pd = ArrayPlotData()
self._pd.set_data("imagedata", self._image)
plot = Plot(self._pd, default_origin="top left")
plot.x_axis.orientation = "top"
img_plot = plot.img_plot("imagedata")[0]
plot.bgcolor = "white"
# Tweak some of the plot properties
plot.title = "Click to add points, press Enter to clear selection"
plot.padding = 50
plot.line_width = 1
# Attach some tools to the plot
pan = PanTool(plot, drag_button="right", constrain_key="shift")
plot.tools.append(pan)
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _plot_default(self):
self._pd = ArrayPlotData()
self._pd.set_data("imagedata", self._image)
plot = Plot(self._pd, default_origin="top left")
plot.x_axis.orientation = "top"
img_plot = plot.img_plot("imagedata")[0]
plot.bgcolor = "white"
# Tweak some of the plot properties
plot.title = "Click to add points, press Enter to clear selection"
plot.padding = 50
plot.line_width = 1
# Attach some tools to the plot
pan = PanTool(plot, drag_button="right", constrain_key="shift")
plot.tools.append(pan)
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def add_plot(self, signal, sweep_point=None):
## waveform = signal.get_waveform()
## x = waveform.get_x()[-1][0].tolist()
## y = np.real(waveform.get_y()[0].tolist())
if sweep_point is None:
sweep_point = signal.get_circuit()._sweep_set._points[0]
trace = Trace(signal, self, self._next_color(), sweep_point)
x_name = trace.index_label
y_name = trace.label
x = trace.get_indices()
y = trace.get_values()
if type(y[0]) == complex:
y = [value.real for value in y]
#print x_name, len(x)
#print y_name, len(y)
#print x
#print y
if self.firstplot:
self.plotdata = ArrayPlotData()
self.plotdata.set_data(x_name, x)
self.plotdata.set_data(y_name, y)
plot = Plot(self.plotdata)
plot.padding = 1
plot.bgcolor = "white"
plot.border_visible = True
add_default_grids(plot)
add_default_axes(plot)
plot.tools.append(PanTool(plot))
# The ZoomTool tool is stateful and allows drawing a zoom
# box to select a zoom region.
zoom = CustomZoomTool(plot)
plot.overlays.append(zoom)
# The DragZoom tool just zooms in and out as the user drags
# the mouse vertically.
dragzoom = DragZoom(plot, drag_button="right")
plot.tools.append(dragzoom)
#~ # Add a legend in the upper right corner, and make it relocatable
#~ self.legend = Legend(component=plot, padding=10, align="ur")
#~ self.legend.tools.append(LegendTool(self.legend, drag_button="right"))
#~ plot.overlays.append(self.legend)
#~ self.legend.plots = {}
self.firstplot = False
self.container.add(plot)
self.plot = plot
else:
self.plotdata.set_data(x_name, x)
self.plotdata.set_data(y_name, y)
#self.plot.plot(self.plotdata.list_data())
pl = self.plot.plot( (x_name, y_name), name=trace.label, type="line",
color=trace.color, line_style=trace.line_style,
line_width=trace.line_width, marker=trace.marker,
marker_size=trace.marker_size, marker_color=trace.marker_color)
self.legend.plots[trace.label] = pl
self.Refresh()
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
def __init__(self, **kw):
super(MLabChacoPlot, self).__init__(**kw)
self.prices = get_data()
x = self.prices['Date']
pd = ArrayPlotData(index = x)
pd.set_data("y", self.prices["Crude Supply"])
# Create some line plots of some of the data
plot = Plot(pd, bgcolor="none", padding=30, border_visible=True,
overlay_border=True, use_backbuffer=False)
#plot.legend.visible = True
plot.plot(("index", "y"), name="Crude Price", color=(.3, .3, .8, .8))
#plot.tools.append(PanTool(plot))
plot.tools.append(PanTool(plot, constrain=True, drag_button="right",
constrain_direction="x"))
range_plt = plot.plots['Crude Price'][0]
range_selection = RangeSelection(range_plt, left_button_selects=True)
range_selection.on_trait_change(self.update_interval, 'selection')
range_plt.tools.append(range_selection)
range_plt.overlays.append(RangeSelectionOverlay(range_plt))
zoom = ZoomTool(component=plot, tool_mode="range", always_on=False,
axis="index", max_zoom_out_factor=1.0,)
plot.overlays.append(zoom)
# Set the plot's bottom axis to use the Scales ticking system
scale_sys = CalendarScaleSystem(fill_ratio=0.4,
default_numlabels=5,
default_numticks=10,)
tick_gen = ScalesTickGenerator(scale=scale_sys)
bottom_axis = ScalesPlotAxis(plot, orientation="bottom",
tick_generator=tick_gen,
label_color="white",
line_color="white")
# Hack to remove default axis - FIXME: how do I *replace* an axis?
del(plot.underlays[-2])
plot.overlays.append(bottom_axis)
# Create the mlab test mesh and get references to various parts of the
# VTK pipeline
f = mlab.figure(size=(700,500))
self.m = mlab.points3d(self.prices['Gasoline Supply'], self.prices['Jet Fuel Supply'], self.prices['Distillate Supply'], self.prices['Crude Supply'])
# Add another glyph module to render the full set of points
g2 = Glyph()
g2.glyph.glyph_source.glyph_source.glyph_type = "circle"
g2.glyph.glyph_source.glyph_source.filled = True
g2.actor.property.opacity = 0.75
self.m.module_manager.source.add_module(g2)
# Set a bunch of properties on the scene to make things look right
self.m.module_manager.scalar_lut_manager.lut_mode = 'PuBuGn'
self.m.glyph.mask_points.random_mode = False
self.m.glyph.mask_points.on_ratio = 1
self.m.scene.isometric_view()
self.m.scene.background = (.9, 0.95, 1.0)
scene = mlab.gcf().scene
render_window = scene.render_window
renderer = scene.renderer
rwi = scene.interactor
plot.resizable = ""
plot.bounds = [600,120]
plot.padding = 25
plot.bgcolor = "white"
plot.outer_position = [30,30]
plot.tools.append(MoveTool(component=plot,drag_button="right"))
container = OverlayPlotContainer(bgcolor = "transparent",
fit_window = True)
container.add(plot)
# Create the Enable Window
window = EnableVTKWindow(rwi, renderer,
component=container,
istyle_class = tvtk.InteractorStyleTrackballCamera,
bgcolor = "transparent",
event_passthrough = True,
)
mlab.show()
