def trait_view(self, view):
""" Build the view. The local namespace is
"""
return View(VGroup(
Item('data_file', style='simple', label="HDF file to load"),
HSplit(
Item('ts_plot',
editor=ComponentEditor(size=(400, 600)),
show_label=False),
VGroup(
Item('tool_chooser', show_label=True, label="Choose tool"),
Item('ts1_chooser', label="TS 1"),
Item('ts2_chooser',
label="TS 2",
visible_when="tool_chooser in ['%s']" % CORRELATION),
Item('ma_window_size',
label="MA window size",
visible_when="tool_chooser in ['%s']" % MA),
Item('ts_analysis_plot',
editor=ComponentEditor(size=(400, 600)),
show_label=False),
Item('ts_analysis_details',
show_label=False,
style='readonly',
visible_when=("tool_chooser in ['%s']" %
CORRELATION))),
),
),
title='Time-series plotter and analyzer',
width=1300,
height=800,
resizable=True)
class Demo(HasTraits):
lodpi = Instance(Component)
hidpi = Instance(Component)
traits_view = View(
HGroup(
HGroup(
UItem(
"lodpi",
editor=ComponentEditor(high_resolution=False),
width=250,
height=250,
),
),
HGroup(
UItem(
"hidpi",
editor=ComponentEditor(high_resolution=True),
width=250,
height=250,
),
),
),
resizable=True,
title="HiDPI Example",
)
def _lodpi_default(self):
return MyComponent(quote="Pixelated")
def _hidpi_default(self):
return MyComponent(quote="Smooth")
class Demo(HasTraits):
filled = Instance(Component)
horizon = Instance(Component)
traits_view = View(
Group(
Item('filled', editor=ComponentEditor(size=filled_size),
show_label=False),
Item('horizon', editor=ComponentEditor(size=horizon_size),
show_label=False),
orientation = "vertical"),
resizable=False, title=title,
width=filled_size[0], height=filled_size[1]+horizon_size[1],
)
class Demo(HasTraits):
vu = Instance(VUMeter)
traits_view = View(
VGroup(
Group(
UItem("vu",
editor=ComponentEditor(size=(60, 60)),
style="custom")),
Item(
"object.vu.percent",
editor=RangeEditor(low=0.0, high=200.0, mode="slider"),
),
),
"_",
VGroup(
Item(
"object.vu.angle",
label="angle",
editor=RangeEditor(low=0.0, high=89.0, mode="slider"),
),
Item(
"object.vu._beta",
editor=RangeEditor(low=0.0, high=1.0, mode="slider"),
),
),
width=450,
height=380,
title="VU Meter",
resizable=True,
)
class Demo(HasTraits):
plot_data = Instance(DataFramePlotData)
plot = Instance(Component)
traits_view = View(Group(
Item('plot', editor=ComponentEditor(size=(900, 500)),
show_label=False),
orientation="vertical",
),
resizable=True,
title="pandas data example")
def _plot_data_default(self):
# Create a DataFrame with plottable data
index = linspace(-2.0, 10.0, 100)
df = DataFrame(index=index)
for i in range(5):
name = "y" + str(i)
df[name] = jn(i, index)
plot_data = DataFramePlotData(data_frame=df)
return plot_data
def _plot_default(self):
plot = Plot(self.plot_data, padding=50)
plot.plot(("index", "y0", "y1", "y2"), name="j_n, n<3", color="red")
plot.plot(("index", "y3"), name="j_3", color="blue")
plot.x_axis.title = "index"
plot.y_axis.title = "j_n"
return plot
class DataChooser(HasTraits):
plot = Instance(Plot)
data_name = Enum("jn0", "jn1", "jn2")
# default view for a traits class
traits_view = View(
Item('data_name', label="Y data"),
Item('plot', editor=ComponentEditor(), show_label=False),
width=800, height=600, resizable=True,
title="Data Chooser")
def _plot_default(self):
x = linspace(-5, 10, 100)
self.data = {"jn0": jn(0, x),
"jn1": jn(1, x),
"jn2": jn(2, x)}
self.plotdata = ArrayPlotData(x = x, y = self.data["jn0"])
plot = Plot(self.plotdata)
plot.plot(("x", "y"), type="line", color="blue")
return plot
# by default Enum trait displayed as a drop down menu
def _data_name_changed(self):
self.plotdata.set_data("y", self.data[self.data_name])
class Demo(HasStrictTraits):
range_tool = Any
select = Button("Select")
view = View(
VGroup(
UItem('plot', editor=ComponentEditor()),
UItem('select')
)
)
plot = Instance(Component)
def _plot_default(self):
plot_data = ArrayPlotData(
x=np.linspace(0, 1, 10), y=np.linspace(0, 1, 10)
)
plot = Plot(plot_data)
r, = plot.plot(("x", "y"))
range_tool = RangeSelection(r)
r.overlays.append(RangeSelectionOverlay(axis='index', component=r))
r.tools.append(range_tool)
self.range_tool = range_tool
return plot
def _select_changed(self):
self.range_tool.selection = (0.2, 0.4)
class Plots(HasTraits):
composite_plot = Instance(Component)
traits_view = View(Group(Item('composite_plot',
editor=ComponentEditor(),
show_label=False),
orientation="vertical"),
resizable=True,
title="Two Chaco Plots")
def _composite_plot_default(self):
x_line = np.linspace(-14, 14, 100)
y_line = np.sin(x_line) * x_line**3
x = np.linspace(0, 10, 51)
y = np.linspace(0, 5, 51)
X, Y = np.meshgrid(x, y)
z = np.exp(-(X**2 + Y**2) / 100)
plotdata = ArrayPlotData(x=x_line, y=y_line, zdata=z[:-1, :-1])
line_plot = Plot(plotdata)
line_plot.plot(('x', 'y'), type='line', color='blue')
img_plot = Plot(plotdata)
img_plot.img_plot("zdata", xbounds=x, ybounds=y, colormap=jet)
cp = VPlotContainer()
cp.add(img_plot)
cp.add(line_plot)
return cp
class LegendWindow(HasTraits):
plot = Instance(OverlayPlotContainer)
traits_view = View(
UItem('plot', editor=ComponentEditor(bgcolor='white',
width=500, height=500), show_label=False, resizable=True),
title='Legend', scrollable=True,
)
def __init__(self,legend):
super(LegendWindow,self).__init__()
self.legend = self.add_legend(legend)
def _plot_default(self):
self.container = OverlayPlotContainer(bgcolor="white", padding=10)
self.container.add(self.legend)
return self.container
def get_legend(self):
if self.legend:
return self.legend
def add_legend(self, legend):
legend.set(component=None,
padding=10,
error_icon='blank',
visible=True,
resizable='hv',
clip_to_component=True)
return legend
def default_traits_view(self):
view = KromView(
HGroup(
VGroup(
Group(
Item("select_all_collections", label="All"),
UItem('displayed_log_collection_names',
editor=CheckListEditor(
values=self._all_log_collection_names),
style='custom'),
HGroup(
UItem("color_editor"),
),
label='Experiments/Simulations',
show_border=True,
),
Group(
UItem('displayed_log_family_names',
editor=CheckListEditor(
values=self._all_log_family_names,
format_func=lambda a: a),
style='custom'),
label='Plot Grouping', show_border=True,
),
visible_when='_show_control'
),
VGroup(
UItem('_container', editor=ComponentEditor(),
show_label=False),
show_border=True,
),
),
title="Chromatogram Plot",
)
return view
class Demo(HasTraits):
plot = Instance(Component)
scatter_renderer = Instance(Component)
alpha = DelegatesTo('scatter_renderer')
traits_view = View(Group(Item('plot',
editor=ComponentEditor(size=size,
bgcolor=bg_color),
show_label=False),
Group(
Item('alpha',
editor=RangeEditor(low=0.0,
high=1.0)), ),
orientation="vertical"),
resizable=True,
title=title)
def _plot_default(self):
return _create_plot_component()
def _scatter_renderer_default(self):
renderer = _create_scatter_renderer(self.plot)
return renderer
class ContainerExample(HasTraits):
plot = Instance(HPlotContainer)
traits_view = View(Item('plot', editor=ComponentEditor(),
show_label=False),
width=1000,
height=600,
resizable=True,
title="Chaco Plot")
def _plot_default(self):
x = linspace(-14, 14, 100)
y = sin(x) * x**3
plotdata = ArrayPlotData(x=x, y=y)
scatter = Plot(plotdata)
scatter.plot(("x", "y"), type="scatter", color="blue")
line = Plot(plotdata)
line.plot(("x", "y"), type="line", color="blue")
container = HPlotContainer(scatter, line)
container.spacing = 0
scatter.padding_right = 0
line.padding_left = 0
line.y_axis_orientation = "right"
return container
class GridContainerExample(HasTraits):
plot = Instance(GridPlotContainer)
traits_view = View(Item('plot', editor=ComponentEditor(),
show_label=False),
width=1000,
height=600,
resizable=True)
def _plot_default(self):
# Create a GridContainer to hold all of our plots: 2 rows, 3 columns
container = GridPlotContainer(shape=(2, 3),
spacing=(10, 5),
valign='top',
bgcolor='lightgray')
pd = ArrayPlotData(data=np.arange(36).reshape(6, 6))
plots = []
renderers = []
for i in range(6):
plot = Plot(pd)
r, = plot.img_plot("data")
plots.append(plot)
renderers.append(r)
add_tools(r)
# Add to the grid container
container.add(plot)
share_attr(plots, "range2d")
share_attr([rend.index_mapper for rend in renderers], "range")
return container
def default_traits_view(self):
prod_comp_names = self.model.all_data.keys()
time_slice_max = self.model.active_anim_data.columnliqZ.shape[2] - 1
return View(
VGroup(
HGroup(
Item('model.product_component',
label='Component',
editor=EnumEditor(values=prod_comp_names)),
Spring(),
Item("time_description",
style="readonly",
show_label=False),
Spring(),
Item("model.simulation_name",
style="readonly",
label="Simulation"),
),
Item('model.time_slice',
label='Time slice',
editor=RangeEditor(low=0,
high=time_slice_max,
mode='slider')),
HGroup(
UItem('model.plot',
editor=ComponentEditor(),
show_label=False), ),
show_border=True,
),
resizable=True,
title="Animation Plot",
width=1000,
height=800,
)
class DoubleScatterView(HasTraits):
sv1=Instance(ScatterView)
sv2=Instance(ScatterView)
plot1=Instance(Plot)
plot2=Instance(Plot)
totalplot = Instance(Component)
traits_view = View(
Group(
Item('totalplot', editor=ComponentEditor(),
show_label=False),
# Item('plot1',editor=ComponentEditor()),
# orientation = "vertical"),
),resizable=True, title='Test'
)
# def _totalplot_default(self):
# return self.create_plots()
def create_plots(self):
container = HPlotContainer()
container.add(self.plot1)
container.add(self.plot2)
self.totalplot=container
def update(self, sv1, sv2):
self.sv1=sv1
self.sv2=sv2
self.plot1=self.sv1.sigplot
self.plot2=self.sv2.sigplot
self.create_plots()
class Demo(HasTraits):
plot = Instance(Component)
controller = Instance(TimerController, ())
timer = Instance(Timer)
traits_view = View(
Group(
Item('plot', editor=ComponentEditor(size=size),
show_label=False),
orientation = "vertical"),
resizable=True, title=title,
width=size[0], height=size[1],
handler=DemoHandler
)
def __init__(self, **traits):
super(Demo, self).__init__(**traits)
self.plot = _create_plot_component(self.controller)
def edit_traits(self, *args, **kws):
# Start up the timer! We should do this only when the demo actually
# starts and not when the demo object is created.
self.timer = Timer(20, self.controller.onTimer)
return super(Demo, self).edit_traits(*args, **kws)
def configure_traits(self, *args, **kws):
# Start up the timer! We should do this only when the demo actually
# starts and not when the demo object is created.
self.timer = Timer(20, self.controller.onTimer)
return super(Demo, self).configure_traits(*args, **kws)
class Demo(HasTraits):
plot = Instance(Component)
traits_view = View(Group(Item('plot',
editor=ComponentEditor(size=size),
show_label=False),
orientation="vertical"),
resizable=True,
title=title)
def _selection_changed(self):
mask = self.index_datasource.metadata['selections']
print("New selection: ")
print(compress(mask, arange(len(mask))))
# Ensure that the points are printed immediately:
sys.stdout.flush()
def _plot_default(self):
plot = _create_plot_component()
# Retrieve the plot hooked to the RectangularSelection tool.
my_plot = plot.plots["my_plot"][0]
rect_selection = my_plot.active_tool
# Set up the trait handler for the selection
self.index_datasource = my_plot.index
rect_selection.on_trait_change(self._selection_changed,
'selection_changed')
return plot
class Demo(HasTraits):
plot = Instance(Component)
traits_view = View(VGroup(HGroup(spring,
Label('Click point to select/unselect'),
spring),
Item('plot',
editor=ComponentEditor(size=size,
bgcolor=bg_color),
show_label=False),
orientation="vertical"),
resizable=True,
title=title)
def _metadata_handler(self):
sel_indices = self.index_datasource.metadata.get('selections', [])
print("Selection indices:", sel_indices)
hover_indices = self.index_datasource.metadata.get('hover', [])
print("Hover indices:", hover_indices)
def _plot_default(self):
plot = _create_plot_component()
# Retrieve the plot hooked to the tool.
my_plot = plot.plots["my_plot"][0]
# Set up the trait handler for the selection
self.index_datasource = my_plot.index
self.index_datasource.on_trait_change(self._metadata_handler,
"metadata_changed")
return plot
class MieComparePlot(HasTraits):
''' Developed 4_14_12, container object that stores two instances of plots and a creates
a third plot to combine both plots. Especially useful for comparing scattering cross section
plots for full nanoparticles and composite nanoparticles '''
# Mie1=Instance(ScatterView) #Try making Plot if doesn't work
# Mie2=Instance(ScatterView)
# plot1=DelegatesTo('Mie1', prefix='sigplot')
# plot2=DelegatesTo('Mie1', prefix='sigplot')
plot1 = Instance(ToolbarPlot)
def _plot1_default(self):
return ToolbarPlot()
def _plot1_changed(self):
print('changed in mie_compare')
print(self.plot1)
# container = GridContainer(padding=40, fill_padding=True,
# bgcolor="lightgray", use_backbuffer=True,
# shape=(2,3), spacing=(20,20))
# TotalPlot=Instance(Component)
traits_view = View(
Item('plot1', show_label=False, editor=ComponentEditor()), ),
class Demo(DemoFrame):
canvas = Instance(Component)
traits_view = View(
Item(
"canvas",
editor=ComponentEditor(),
show_label=False,
width=200,
height=200,
),
resizable=True,
)
def _canvas_default(self):
image = stars()
container = ConstraintsContainer(bounds=[500, 500])
container.add(image)
ratio = float(image.data.shape[1]) / image.data.shape[0]
container.layout_constraints = [
image.left == container.contents_left,
image.right == container.contents_right,
image.top == container.contents_top,
image.bottom == container.contents_bottom,
image.layout_width == ratio * image.layout_height,
]
return container
class MyPlot(HasTraits):
""" Displays a plot with a few buttons to control which overlay
to display
"""
plot = Instance(Plot)
traits_view = View(Item('plot', editor=ComponentEditor(),
show_label=False),
resizable=True)
def __init__(self, x_index, y_index, data, **kw):
super(MyPlot, self).__init__(**kw)
# Create the data source for the MultiLinePlot.
ds = MultiArrayDataSource(data=data)
xs = ArrayDataSource(x_index, sort_order='ascending')
xrange = DataRange1D()
xrange.add(xs)
ys = ArrayDataSource(y_index, sort_order='ascending')
yrange = DataRange1D()
yrange.add(ys)
mlp = MultiLinePlot(index=xs,
yindex=ys,
index_mapper=LinearMapper(range=xrange),
value_mapper=LinearMapper(range=yrange),
value=ds,
global_max=np.nanmax(data),
global_min=np.nanmin(data),
**kw)
self.plot = Plot()
self.plot.add(mlp)
class Demo(HasTraits):
plot = Instance(Component)
controller = Instance(TimerController, ())
timer = Instance(Timer)
traits_view = View(
Group(
Item('plot', editor=ComponentEditor(size=size),
show_label=False),
orientation = "vertical"),
resizable=True, title=title,
width=size[0], height=size[1],
handler=DemoHandler
)
def __init__(self, **traits):
super(Demo, self).__init__(**traits)
self.cqtkernel = CQTKernel(TOP_MIDINUMBER, BINS, SAMPLING_RATE)
self.plot = _create_plot_component(self.controller, self.cqtkernel)
def edit_traits(self, *args, **kws):
self.timer = Timer(20, self.controller.onTimer)
return super(Demo, self).edit_traits(*args, **kws)
def configure_traits(self, *args, **kws):
self.timer = Timer(20, self.controller.onTimer)
return super(Demo, self).configure_traits(*args, **kws)
class ScriptedComponentView(ModelView):
""" ModelView of a ScriptedComponent displaying the script and image
"""
#: the component we are editing
model = Instance(ScriptedComponent, ())
view = View(
HSplit(
VGroup(
UItem("model.draw_script"),
UItem(
"model.error",
visible_when="model.error != ''",
style="readonly",
height=100,
),
),
VGroup(
UItem("model", editor=ComponentEditor(), springy=True),
UItem("model.fps_display", style="readonly"),
),
),
resizable=True,
title="Kiva Explorer",
)
class ExamplePlotApp(HasTraits):
plot = Instance(Plot)
traits_view = View(
Item(
'plot',
editor=ComponentEditor(),
width=600,
height=600,
show_label=False),
resizable=True)
def __init__(self, index, series1, series2, **kw):
super(ExamplePlotApp, self).__init__(**kw)
plot_data = ArrayPlotData(index=index)
plot_data.set_data('series1', series1)
plot_data.set_data('series2', series2)
self.plot = ToolbarPlot(plot_data)
line_plot = self.plot.plot(('index', 'series1'), color='auto')[0]
# Add pan and zoom tools
line_plot.tools.append(PanTool(line_plot))
line_plot.tools.append(ZoomTool(line_plot))
# Set the domain_limits
line_plot.index_mapper.domain_limits = (3.3, 6.6)
def default_traits_view(self):
no_endlabel = DefaultOverride(low_label='',
high_label='',
mode='logslider')
no_endlabel_linear = DefaultOverride(low_label='',
high_label='',
mode='slider')
return View(Group(Item('reconstruction', editor=ComponentEditor()),
show_labels=False,
show_left=False),
HGroup(Item('pulses_used', style='readonly'),
Item('absolute_sum'), Item('amplitudes_one'),
Item('replace'), Item('subtract')),
Item('amplitude_threshold_min',
editor=no_endlabel,
label='Minimum absolute amplitude'),
Item('amplitude_threshold_max', editor=no_endlabel),
Item('area_threshold_min', editor=no_endlabel),
Item('area_threshold_max', editor=no_endlabel),
Item('volume_threshold_min', editor=no_endlabel),
Item('volume_threshold_max', editor=no_endlabel),
Item('circularity_min'),
Item('circularity_max'),
Item('lifetime_min', editor=no_endlabel_linear),
Item('lifetime_max', editor=no_endlabel_linear),
Item('output_threshold', editor=no_endlabel_linear),
HGroup(Item('save_file', show_label=False),
Item('save_button', show_label=False)),
width=800,
height=600,
resizable=True,
title='DPT 2D reconstruction')
def default_traits_view(self):
view = View(
VGroup(
self.axis_hgroup,
UItem("_component", editor=ComponentEditor()),
VGroup(UItem("reset_plot", enabled_when="reset_enabled")),
))
return view
def default_traits_view(self):
return View(
VGroup(
Item('plot', editor=ComponentEditor(),
show_label=False),
),
resizable=True
)
def default_traits_view(self):
"""Implemented to removes the reset_plot option from the
parent class View"""
view = View(
VGroup(
self.axis_hgroup,
UItem("_component", editor=ComponentEditor()),
))
return view
class Demo(HasTraits):
canvas = Instance(Component)
traits_view = View(Item('canvas', editor=ComponentEditor(bgcolor="lightgray"),
show_label=False, width=500, height=500),
resizable=True, title="Gradient Example")
def _canvas_default(self):
return MyCanvas()
def _get_traits_group(self):
return VGroup(
HGroup(
Item('flip_order'),
Item('offset'),
Item('value_range'),
),
UItem('component', editor=ComponentEditor()),
)
