def test_empty(self):
ds = GridDataSource()
self.assert_(ds.sort_order == ('none', 'none'))
self.assert_(ds.index_dimension == 'image')
self.assert_(ds.value_dimension == 'scalar')
self.assert_(ds.metadata == {"selections":[], "annotations":[]})
xdata, ydata = ds.get_data()
assert_ary_(xdata.get_data(), array([]))
assert_ary_(ydata.get_data(), array([]))
self.assert_(ds.get_bounds() == ((0,0),(0,0)))
def test_init(self):
test_xd = array([1,2,3])
test_yd = array([1.5, 0.5, -0.5, -1.5])
test_sort_order = ('ascending', 'descending')
ds = GridDataSource(xdata=test_xd, ydata=test_yd,
sort_order=test_sort_order)
self.assert_(ds.sort_order == test_sort_order)
xd, yd = ds.get_data()
assert_ary_(xd.get_data(), test_xd)
assert_ary_(yd.get_data(), test_yd)
self.assert_(ds.get_bounds() == ((min(test_xd),min(test_yd)),
(max(test_xd),max(test_yd))))
class PlotUI(HasTraits):
#Traits view definitions:
traits_view = View(
Group(Item('container',
editor=ComponentEditor(size=(800,600)),
show_label=False)),
buttons=NoButtons,
resizable=True)
plot_edit_view = View(
Group(Item('num_levels'),
Item('colormap')),
buttons=["OK","Cancel"])
num_levels = Int(15)
colormap = Enum(color_map_name_dict.keys())
#---------------------------------------------------------------------------
# Private Traits
#---------------------------------------------------------------------------
_image_index = Instance(GridDataSource)
_image_value = Instance(ImageData)
_cmap = Trait(jet, Callable)
#---------------------------------------------------------------------------
# Public View interface
#---------------------------------------------------------------------------
def __init__(self, *args, **kwargs):
super(PlotUI, self).__init__(*args, **kwargs)
self.create_plot()
def create_plot(self):
# Create the mapper, etc
self._image_index = GridDataSource(array([]),
array([]),
sort_order=("ascending","ascending"))
image_index_range = DataRange2D(self._image_index)
self._image_index.on_trait_change(self._metadata_changed,
"metadata_changed")
self._image_value = ImageData(data=array([]), value_depth=1)
image_value_range = DataRange1D(self._image_value)
# Create the contour plots
self.polyplot = ContourPolyPlot(index=self._image_index,
value=self._image_value,
index_mapper=GridMapper(range=
image_index_range),
color_mapper=\
self._cmap(image_value_range),
levels=self.num_levels)
self.lineplot = ContourLinePlot(index=self._image_index,
value=self._image_value,
index_mapper=GridMapper(range=
self.polyplot.index_mapper.range),
levels=self.num_levels)
# Add a left axis to the plot
left = PlotAxis(orientation='left',
title= "y",
mapper=self.polyplot.index_mapper._ymapper,
component=self.polyplot)
self.polyplot.overlays.append(left)
# Add a bottom axis to the plot
bottom = PlotAxis(orientation='bottom',
title= "x",
mapper=self.polyplot.index_mapper._xmapper,
component=self.polyplot)
self.polyplot.overlays.append(bottom)
# Add some tools to the plot
self.polyplot.tools.append(PanTool(self.polyplot,
constrain_key="shift"))
self.polyplot.overlays.append(ZoomTool(component=self.polyplot,
tool_mode="box", always_on=False))
self.polyplot.overlays.append(LineInspector(component=self.polyplot,
axis='index_x',
inspect_mode="indexed",
write_metadata=True,
is_listener=False,
color="white"))
self.polyplot.overlays.append(LineInspector(component=self.polyplot,
axis='index_y',
inspect_mode="indexed",
write_metadata=True,
color="white",
is_listener=False))
# Add these two plots to one container
contour_container = OverlayPlotContainer(padding=20,
use_backbuffer=True,
unified_draw=True)
contour_container.add(self.polyplot)
contour_container.add(self.lineplot)
# Create a colorbar
cbar_index_mapper = LinearMapper(range=image_value_range)
self.colorbar = ColorBar(index_mapper=cbar_index_mapper,
plot=self.polyplot,
padding_top=self.polyplot.padding_top,
padding_bottom=self.polyplot.padding_bottom,
padding_right=40,
resizable='v',
width=30)
self.pd = ArrayPlotData(line_index = array([]),
line_value = array([]),
scatter_index = array([]),
scatter_value = array([]),
scatter_color = array([]))
self.cross_plot = Plot(self.pd, resizable="h")
self.cross_plot.height = 100
self.cross_plot.padding = 20
self.cross_plot.plot(("line_index", "line_value"),
line_style="dot")
self.cross_plot.plot(("scatter_index","scatter_value","scatter_color"),
type="cmap_scatter",
name="dot",
color_mapper=self._cmap(image_value_range),
marker="circle",
marker_size=8)
self.cross_plot.index_range = self.polyplot.index_range.x_range
self.pd.set_data("line_index2", array([]))
self.pd.set_data("line_value2", array([]))
self.pd.set_data("scatter_index2", array([]))
self.pd.set_data("scatter_value2", array([]))
self.pd.set_data("scatter_color2", array([]))
self.cross_plot2 = Plot(self.pd, width = 140, orientation="v", resizable="v", padding=20, padding_bottom=160)
self.cross_plot2.plot(("line_index2", "line_value2"),
line_style="dot")
self.cross_plot2.plot(("scatter_index2","scatter_value2","scatter_color2"),
type="cmap_scatter",
name="dot",
color_mapper=self._cmap(image_value_range),
marker="circle",
marker_size=8)
self.cross_plot2.index_range = self.polyplot.index_range.y_range
# Create a container and add components
self.container = HPlotContainer(padding=40, fill_padding=True,
bgcolor = "white", use_backbuffer=False)
inner_cont = VPlotContainer(padding=0, use_backbuffer=True)
inner_cont.add(self.cross_plot)
inner_cont.add(contour_container)
self.container.add(self.colorbar)
self.container.add(inner_cont)
self.container.add(self.cross_plot2)
def update(self, model):
self.minz = model.minz
self.maxz = model.maxz
self.colorbar.index_mapper.range.low = self.minz
self.colorbar.index_mapper.range.high = self.maxz
self._image_index.set_data(model.xs, model.ys)
self._image_value.data = model.zs
self.pd.set_data("line_index", model.xs)
self.pd.set_data("line_index2", model.ys)
self.container.invalidate_draw()
self.container.request_redraw()
#---------------------------------------------------------------------------
# Event handlers
#---------------------------------------------------------------------------
def _metadata_changed(self, old, new):
""" This function takes out a cross section from the image data, based
on the line inspector selections, and updates the line and scatter
plots."""
self.cross_plot.value_range.low = self.minz
self.cross_plot.value_range.high = self.maxz
self.cross_plot2.value_range.low = self.minz
self.cross_plot2.value_range.high = self.maxz
if self._image_index.metadata.has_key("selections"):
x_ndx, y_ndx = self._image_index.metadata["selections"]
if y_ndx and x_ndx:
self.pd.set_data("line_value",
self._image_value.data[y_ndx,:])
self.pd.set_data("line_value2",
self._image_value.data[:,x_ndx])
xdata, ydata = self._image_index.get_data()
xdata, ydata = xdata.get_data(), ydata.get_data()
self.pd.set_data("scatter_index", array([xdata[x_ndx]]))
self.pd.set_data("scatter_index2", array([ydata[y_ndx]]))
self.pd.set_data("scatter_value",
array([self._image_value.data[y_ndx, x_ndx]]))
self.pd.set_data("scatter_value2",
array([self._image_value.data[y_ndx, x_ndx]]))
self.pd.set_data("scatter_color",
array([self._image_value.data[y_ndx, x_ndx]]))
self.pd.set_data("scatter_color2",
array([self._image_value.data[y_ndx, x_ndx]]))
else:
self.pd.set_data("scatter_value", array([]))
self.pd.set_data("scatter_value2", array([]))
self.pd.set_data("line_value", array([]))
self.pd.set_data("line_value2", array([]))
def _colormap_changed(self):
self._cmap = color_map_name_dict[self.colormap]
if hasattr(self, "polyplot"):
value_range = self.polyplot.color_mapper.range
self.polyplot.color_mapper = self._cmap(value_range)
value_range = self.cross_plot.color_mapper.range
self.cross_plot.color_mapper = self._cmap(value_range)
# FIXME: change when we decide how best to update plots using
# the shared colormap in plot object
self.cross_plot.plots["dot"][0].color_mapper = self._cmap(value_range)
self.cross_plot2.plots["dot"][0].color_mapper = self._cmap(value_range)
self.container.request_redraw()
def _num_levels_changed(self):
if self.num_levels > 3:
self.polyplot.levels = self.num_levels
self.lineplot.levels = self.num_levels
def create_plot(self):
# Create the mapper, etc
self._image_index = GridDataSource(array([]),
array([]),
sort_order=("ascending","ascending"))
image_index_range = DataRange2D(self._image_index)
self._image_index.on_trait_change(self._metadata_changed,
"metadata_changed")
self._image_value = ImageData(data=array([]), value_depth=1)
image_value_range = DataRange1D(self._image_value)
# Create the contour plots
self.polyplot = ContourPolyPlot(index=self._image_index,
value=self._image_value,
index_mapper=GridMapper(range=
image_index_range),
color_mapper=\
self._cmap(image_value_range),
levels=self.num_levels)
self.lineplot = ContourLinePlot(index=self._image_index,
value=self._image_value,
index_mapper=GridMapper(range=
self.polyplot.index_mapper.range),
levels=self.num_levels)
# Add a left axis to the plot
left = PlotAxis(orientation='left',
title= "y",
mapper=self.polyplot.index_mapper._ymapper,
component=self.polyplot)
self.polyplot.overlays.append(left)
# Add a bottom axis to the plot
bottom = PlotAxis(orientation='bottom',
title= "x",
mapper=self.polyplot.index_mapper._xmapper,
component=self.polyplot)
self.polyplot.overlays.append(bottom)
# Add some tools to the plot
self.polyplot.tools.append(PanTool(self.polyplot,
constrain_key="shift"))
self.polyplot.overlays.append(ZoomTool(component=self.polyplot,
tool_mode="box", always_on=False))
self.polyplot.overlays.append(LineInspector(component=self.polyplot,
axis='index_x',
inspect_mode="indexed",
write_metadata=True,
is_listener=False,
color="white"))
self.polyplot.overlays.append(LineInspector(component=self.polyplot,
axis='index_y',
inspect_mode="indexed",
write_metadata=True,
color="white",
is_listener=False))
# Add these two plots to one container
contour_container = OverlayPlotContainer(padding=20,
use_backbuffer=True,
unified_draw=True)
contour_container.add(self.polyplot)
contour_container.add(self.lineplot)
# Create a colorbar
cbar_index_mapper = LinearMapper(range=image_value_range)
self.colorbar = ColorBar(index_mapper=cbar_index_mapper,
plot=self.polyplot,
padding_top=self.polyplot.padding_top,
padding_bottom=self.polyplot.padding_bottom,
padding_right=40,
resizable='v',
width=30)
self.pd = ArrayPlotData(line_index = array([]),
line_value = array([]),
scatter_index = array([]),
scatter_value = array([]),
scatter_color = array([]))
self.cross_plot = Plot(self.pd, resizable="h")
self.cross_plot.height = 100
self.cross_plot.padding = 20
self.cross_plot.plot(("line_index", "line_value"),
line_style="dot")
self.cross_plot.plot(("scatter_index","scatter_value","scatter_color"),
type="cmap_scatter",
name="dot",
color_mapper=self._cmap(image_value_range),
marker="circle",
marker_size=8)
self.cross_plot.index_range = self.polyplot.index_range.x_range
self.pd.set_data("line_index2", array([]))
self.pd.set_data("line_value2", array([]))
self.pd.set_data("scatter_index2", array([]))
self.pd.set_data("scatter_value2", array([]))
self.pd.set_data("scatter_color2", array([]))
self.cross_plot2 = Plot(self.pd, width = 140, orientation="v", resizable="v", padding=20, padding_bottom=160)
self.cross_plot2.plot(("line_index2", "line_value2"),
line_style="dot")
self.cross_plot2.plot(("scatter_index2","scatter_value2","scatter_color2"),
type="cmap_scatter",
name="dot",
color_mapper=self._cmap(image_value_range),
marker="circle",
marker_size=8)
self.cross_plot2.index_range = self.polyplot.index_range.y_range
# Create a container and add components
self.container = HPlotContainer(padding=40, fill_padding=True,
bgcolor = "white", use_backbuffer=False)
inner_cont = VPlotContainer(padding=0, use_backbuffer=True)
inner_cont.add(self.cross_plot)
inner_cont.add(contour_container)
self.container.add(self.colorbar)
self.container.add(inner_cont)
self.container.add(self.cross_plot2)
