def _create_plot_component():
# Create the index
numpoints = 100
low = -5
high = 15.0
x = arange(low, high, (high - low) / numpoints)
plotdata = ArrayPlotData(x=x, y1=jn(0, x), y2=jn(1, x))
# Create the left plot
left_plot = Plot(plotdata)
left_plot.x_axis.title = 'X'
left_plot.y_axis.title = 'j0(x)'
renderer = left_plot.plot(('x', 'y1'), type='line', color='blue',
width=2.0)[0]
renderer.overlays.append(LineInspector(renderer, axis='value',
write_metadata=True, is_listener=True))
renderer.overlays.append(LineInspector(renderer, axis='index',
write_metadata=True, is_listener=True))
left_plot.overlays.append(ZoomTool(left_plot, tool_mode='range'))
left_plot.tools.append(PanTool(left_plot))
# Create the right plot
right_plot = Plot(plotdata)
right_plot.index_range = left_plot.index_range
right_plot.orientation = 'v'
right_plot.x_axis.title = 'j1(x)'
right_plot.y_axis.title = 'X'
renderer2 = right_plot.plot(('x', 'y2'), type='line', color='red',
width=2.0)[0]
renderer2.index = renderer.index
renderer2.overlays.append(LineInspector(renderer2,
write_metadata=True, is_listener=True))
renderer2.overlays.append(LineInspector(renderer2, axis='value',
is_listener=True))
right_plot.overlays.append(ZoomTool(right_plot, tool_mode='range'))
right_plot.tools.append(PanTool(right_plot))
container = HPlotContainer(background='lightgray')
container.add(left_plot)
container.add(right_plot)
right_plot = Plot(plotdata)
right_plot.index_range = left_plot.index_range
right_plot.orientation = 'v'
right_plot.x_axis.title = 'j1(x)'
right_plot.y_axis.title = 'X'
renderer2 = right_plot.plot(('x', 'y2'), type='line', color='red',
width=2.0)[0]
renderer2.index = renderer.index
renderer2.overlays.append(LineInspector(renderer2,
write_metadata=True, is_listener=True))
renderer2.overlays.append(LineInspector(renderer2, axis='value',
is_listener=True))
right_plot.overlays.append(ZoomTool(right_plot, tool_mode='range'))
right_plot.tools.append(PanTool(right_plot))
container.add(right_plot)
return container
def _create_plot_component():
# Create the index
numpoints = 100
low = -5
high = 15.0
x = arange(low, high, (high-low)/numpoints)
plotdata = ArrayPlotData(x=x, y1=jn(0, x), y2=jn(1, x))
# Create the left plot
left_plot = Plot(plotdata)
left_plot.x_axis.title = "X"
left_plot.y_axis.title = "j0(x)"
renderer = left_plot.plot(("x", "y1"), type="line", color="blue",
width=2.0)[0]
renderer.overlays.append(LineInspector(renderer, axis='value',
write_metadata=True,
is_listener=True))
renderer.overlays.append(LineInspector(renderer, axis="index",
write_metadata=True,
is_listener=True))
left_plot.overlays.append(ZoomTool(left_plot, tool_mode="range"))
left_plot.tools.append(PanTool(left_plot))
# Create the right plot
right_plot = Plot(plotdata)
right_plot.index_range = left_plot.index_range
right_plot.orientation = "v"
right_plot.x_axis.title = "j1(x)"
right_plot.y_axis.title = "X"
renderer2 = right_plot.plot(("x", "y2"), type="line", color="red", width=2.0)[0]
renderer2.index = renderer.index
renderer2.overlays.append(LineInspector(renderer2, write_metadata=True, is_listener=True))
renderer2.overlays.append(LineInspector(renderer2, axis="value", is_listener=True))
right_plot.overlays.append(ZoomTool(right_plot, tool_mode="range"))
right_plot.tools.append(PanTool(right_plot))
container = HPlotContainer(background="lightgray")
container.add(left_plot)
container.add(right_plot)
right_plot = Plot(plotdata)
right_plot.index_range = left_plot.index_range
right_plot.orientation = "v"
right_plot.x_axis.title = "j1(x)"
right_plot.y_axis.title = "X"
renderer2 = right_plot.plot(("x", "y2"), type="line", color="red", width=2.0)[0]
renderer2.index = renderer.index
renderer2.overlays.append(LineInspector(renderer2, write_metadata=True, is_listener=True))
renderer2.overlays.append(LineInspector(renderer2, axis="value", is_listener=True))
right_plot.overlays.append(ZoomTool(right_plot, tool_mode="range"))
right_plot.tools.append(PanTool(right_plot))
container.add(right_plot)
return container
def __init__(self, **traits):
super(LassoDemoPlot, self).__init__(**traits)
x = np.random.random(N)
y = np.random.random(N)
x2 = np.array([])
y2 = np.array([])
data = ArrayPlotData(x=x, y=y, x2=x2, y2=y2)
plot1 = Plot(data, padding=10)
scatter_plot1 = plot1.plot(("x", "y"), type="scatter", marker="circle", color="blue")[0]
self.lasso = LassoSelection(scatter_plot1, incremental_select=True,
selection_datasource=scatter_plot1.index)
self.lasso.on_trait_change(self._selection_changed, 'selection_changed')
scatter_plot1.tools.append(self.lasso)
scatter_plot1.overlays.append(LassoOverlay(scatter_plot1, lasso_selection=self.lasso))
plot2 = Plot(data, padding=10)
plot2.index_range = plot1.index_range
plot2.value_range = plot1.value_range
plot2.plot(("x2", "y2"), type="scatter", marker="circle", color="red")
self.plot = HPlotContainer(plot1, plot2)
self.plot2 = plot2
self.data = data
def __init__(self, **traits):
super(LassoDemoPlot, self).__init__(**traits)
x = np.random.random(N)
y = np.random.random(N)
x2 = np.array([])
y2 = np.array([])
data = ArrayPlotData(x=x, y=y, x2=x2, y2=y2)
plot1 = Plot(data, padding=10)
scatter_plot1 = plot1.plot(("x", "y"),
type="scatter",
marker="circle",
color="blue")[0]
self.lasso = LassoSelection(scatter_plot1,
incremental_select=True,
selection_datasource=scatter_plot1.index)
self.lasso.on_trait_change(self._selection_changed,
'selection_changed')
scatter_plot1.tools.append(self.lasso)
scatter_plot1.overlays.append(
LassoOverlay(scatter_plot1, lasso_selection=self.lasso))
plot2 = Plot(data, padding=10)
plot2.index_range = plot1.index_range
plot2.value_range = plot1.value_range
plot2.plot(("x2", "y2"), type="scatter", marker="circle", color="red")
self.plot = HPlotContainer(plot1, plot2)
self.plot2 = plot2
self.data = data
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
self.container = HPlotContainer(scatter, line)
# Add pan/zoom so we can see they are connected
scatter.tools.append(PanTool(scatter))
scatter.tools.append(ZoomTool(scatter))
line.tools.append(PanTool(line))
line.tools.append(ZoomTool(line))
# Set the two plots' ranges to be the same
scatter.index_range = line.index_range
def _create_window(self):
# Create the model
#try:
# self.model = model = BrainModel()
# cmap = bone
#except SystemExit:
# sys.exit()
#except:
# print "Unable to load BrainModel, using generated data cube."
self.model = model = Model()
cmap = jet
self._update_model(cmap)
datacube = self.colorcube
# Create the plot
self.plotdata = ArrayPlotData()
self._update_images()
# Center Plot
centerplot = Plot(self.plotdata, padding=0)
imgplot = centerplot.img_plot("xy",
xbounds=(model.xs[0], model.xs[-1]),
ybounds=(model.ys[0], model.ys[-1]),
colormap=cmap)[0]
self._add_plot_tools(imgplot, "xy")
self.center = imgplot
# Right Plot
rightplot = Plot(self.plotdata, width=150, resizable="v", padding=0)
rightplot.value_range = centerplot.value_range
imgplot = rightplot.img_plot("yz",
xbounds=(model.zs[0], model.zs[-1]),
ybounds=(model.ys[0], model.ys[-1]),
colormap=cmap)[0]
self._add_plot_tools(imgplot, "yz")
self.right = imgplot
# Bottom Plot
bottomplot = Plot(self.plotdata, height=150, resizable="h", padding=0)
bottomplot.index_range = centerplot.index_range
imgplot = bottomplot.img_plot("xz",
xbounds=(model.xs[0], model.xs[-1]),
ybounds=(model.zs[0], model.zs[-1]),
colormap=cmap)[0]
self._add_plot_tools(imgplot, "xz")
self.bottom = imgplot
# Create Container and add all Plots
container = GridPlotContainer(padding=20, fill_padding=True,
bgcolor="white", use_backbuffer=True,
shape=(2,2), spacing=(12,12))
container.add(centerplot)
container.add(rightplot)
container.add(bottomplot)
self.container = container
return Window(self, -1, component=container)
def __init__(self):
super(CyclesPlot, self).__init__()
# Normally you'd pass in the data, but I'll hardwire things for this
# one-off plot.
srecs = read_time_series_from_csv("./biz_cycles.csv", date_col=0, date_format="%Y-%m-%d")
dt = srecs["Date"]
# Industrial production compared with trend (plotted on value axis)
iprod_vs_trend = srecs["Metric 1"]
# Industrial production change in last 6 Months (plotted on index axis)
iprod_delta = srecs["Metric 2"]
self._dates = dt
self._series1 = self._selected_s1 = iprod_delta
self._series2 = self._selected_s2 = iprod_vs_trend
end_x = np.array([self._selected_s1[-1]])
end_y = np.array([self._selected_s2[-1]])
plotdata = ArrayPlotData(
x=self._series1,
y=self._series2,
dates=self._dates,
selected_x=self._selected_s1,
selected_y=self._selected_s2,
endpoint_x=end_x,
endpoint_y=end_y,
)
cycles = Plot(plotdata, padding=20)
cycles.plot(("x", "y"), type="line", color=(0.2, 0.4, 0.5, 0.4))
cycles.plot(
("selected_x", "selected_y"), type="line", marker="circle", line_width=3, color=(0.2, 0.4, 0.5, 0.9)
)
cycles.plot(
("endpoint_x", "endpoint_y"),
type="scatter",
marker_size=4,
marker="circle",
color=(0.2, 0.4, 0.5, 0.2),
outline_color=(0.2, 0.4, 0.5, 0.6),
)
cycles.index_range = DataRange1D(low_setting=80.0, high_setting=120.0)
cycles.value_range = DataRange1D(low_setting=80.0, high_setting=120.0)
# dig down to use actual Plot object
cyc_plot = cycles.components[0]
# Add the labels in the quadrants
cyc_plot.overlays.append(
PlotLabel(
"\nSlowdown" + 40 * " " + "Expansion",
component=cyc_plot,
font="swiss 24",
color=(0.2, 0.4, 0.5, 0.6),
overlay_position="inside top",
)
)
cyc_plot.overlays.append(
PlotLabel(
"Downturn" + 40 * " " + "Recovery\n ",
component=cyc_plot,
font="swiss 24",
color=(0.2, 0.4, 0.5, 0.6),
overlay_position="inside bottom",
)
)
timeline = Plot(plotdata, resizable="h", height=50, padding=20)
timeline.plot(("dates", "x"), type="line", color=(0.2, 0.4, 0.5, 0.8), name="x")
timeline.plot(("dates", "y"), type="line", color=(0.5, 0.4, 0.2, 0.8), name="y")
# Snap on the tools
zoomer = ZoomTool(
timeline, drag_button="right", always_on=True, tool_mode="range", axis="index", max_zoom_out_factor=1.1
)
panner = PanTool(timeline, constrain=True, constrain_direction="x")
# dig down to get Plot component I want
x_plt = timeline.plots["x"][0]
range_selection = RangeSelection(x_plt, left_button_selects=True)
range_selection.on_trait_change(self.update_interval, "selection")
x_plt.tools.append(range_selection)
x_plt.overlays.append(RangeSelectionOverlay(x_plt))
# 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(timeline, orientation="bottom", tick_generator=tick_gen)
# Hack to remove default axis - FIXME: how do I *replace* an axis?
del (timeline.underlays[-2])
timeline.overlays.append(bottom_axis)
container = GridContainer(
padding=20, fill_padding=True, bgcolor="lightgray", use_backbuffer=True, shape=(2, 1), spacing=(30, 30)
)
# add a central "x" and "y" axis
x_line = LineInspector(cyc_plot, is_listener=True, color="gray", width=2)
y_line = LineInspector(cyc_plot, is_listener=True, color="gray", width=2, axis="value")
cyc_plot.overlays.append(x_line)
cyc_plot.overlays.append(y_line)
cyc_plot.index.metadata["selections"] = 100.0
cyc_plot.value.metadata["selections"] = 100.0
container.add(cycles)
container.add(timeline)
container.title = "Business Cycles"
self.plot = container
def __init__(self):
super(CyclesPlot, self).__init__()
# Normally you'd pass in the data, but I'll hardwire things for this
# one-off plot.
srecs = read_time_series_from_csv("./biz_cycles2.csv",
date_col=0,
date_format="%Y-%m-%d")
dt = srecs["Date"]
# Industrial production compared with trend (plotted on value axis)
iprod_vs_trend = srecs["Metric 1"]
# Industrial production change in last 6 Months (plotted on index axis)
iprod_delta = srecs["Metric 2"]
self._dates = dt
self._series1 = self._selected_s1 = iprod_delta
self._series2 = self._selected_s2 = iprod_vs_trend
end_x = np.array([self._selected_s1[-1]])
end_y = np.array([self._selected_s2[-1]])
plotdata = ArrayPlotData(x=self._series1,
y=self._series2,
dates=self._dates,
selected_x=self._selected_s1,
selected_y=self._selected_s2,
endpoint_x=end_x,
endpoint_y=end_y)
cycles = Plot(plotdata, padding=20)
cycles.plot(("x", "y"), type="line", color=(.2, .4, .5, .4))
cycles.plot(("selected_x", "selected_y"),
type="line",
marker="circle",
line_width=3,
color=(.2, .4, .5, .9))
cycles.plot(("endpoint_x", "endpoint_y"),
type="scatter",
marker_size=4,
marker="circle",
color=(.2, .4, .5, .2),
outline_color=(.2, .4, .5, .6))
cycles.index_range = DataRange1D(low_setting=80., high_setting=120.)
cycles.value_range = DataRange1D(low_setting=80., high_setting=120.)
# dig down to use actual Plot object
cyc_plot = cycles.components[0]
# Add the labels in the quadrants
cyc_plot.overlays.append(
PlotLabel("\nSlowdown" + 40 * " " + "Expansion",
component=cyc_plot,
font="swiss 24",
color=(.2, .4, .5, .6),
overlay_position="inside top"))
cyc_plot.overlays.append(
PlotLabel("Downturn" + 40 * " " + "Recovery\n ",
component=cyc_plot,
font="swiss 24",
color=(.2, .4, .5, .6),
overlay_position="inside bottom"))
timeline = Plot(plotdata, resizable='h', height=50, padding=20)
timeline.plot(("dates", "x"),
type="line",
color=(.2, .4, .5, .8),
name='x')
timeline.plot(("dates", "y"),
type="line",
color=(.5, .4, .2, .8),
name='y')
# Snap on the tools
zoomer = ZoomTool(timeline,
drag_button="right",
always_on=True,
tool_mode="range",
axis="index",
max_zoom_out_factor=1.1)
panner = PanTool(timeline, constrain=True, constrain_direction="x")
# dig down to get Plot component I want
x_plt = timeline.plots['x'][0]
range_selection = RangeSelection(x_plt, left_button_selects=True)
range_selection.on_trait_change(self.update_interval, 'selection')
x_plt.tools.append(range_selection)
x_plt.overlays.append(RangeSelectionOverlay(x_plt))
# 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(timeline,
orientation="bottom",
tick_generator=tick_gen)
# Hack to remove default axis - FIXME: how do I *replace* an axis?
del (timeline.underlays[-2])
timeline.overlays.append(bottom_axis)
container = GridContainer(padding=20,
fill_padding=True,
bgcolor="lightgray",
use_backbuffer=True,
shape=(2, 1),
spacing=(30, 30))
# add a central "x" and "y" axis
x_line = LineInspector(cyc_plot,
is_listener=True,
color="gray",
width=2)
y_line = LineInspector(cyc_plot,
is_listener=True,
color="gray",
width=2,
axis="value")
cyc_plot.overlays.append(x_line)
cyc_plot.overlays.append(y_line)
cyc_plot.index.metadata["selections"] = 100.0
cyc_plot.value.metadata["selections"] = 100.0
container.add(cycles)
container.add(timeline)
container.title = "Business Cycles"
self.plot = container
def add_plot(self, label, beam):
# container = GridPlotContainer(padding=20, fill_padding=True,
# bgcolor="white", use_backbuffer=True,
# shape=(2,2), spacing=(12,12))
# self.container = container
self.plotdata = ArrayPlotData()
self.model = beam.Data
self.model.z_axis = self.model.z_axis[::-1]
cmap = jet
self._update_model(cmap)
self.plotdata.set_data("xy", self.model.dose)
self._update_images()
# Center Plot
centerplot = Plot(self.plotdata,
resizable='hv',
height=150,
width=150,
padding=0)
centerplot.default_origin = 'top left'
imgplot = centerplot.img_plot("xy",
xbounds=(self.model.x_axis[0],
self.model.x_axis[-1]),
ybounds=(self.model.y_axis[0],
self.model.y_axis[-1]),
colormap=cmap)[0]
imgplot.origin = 'top left'
self._add_plot_tools(imgplot, "xy")
left_axis = PlotAxis(centerplot, orientation='left', title='y')
bottom_axis = PlotAxis(centerplot,
orientation='bottom',
title='x',
title_spacing=30)
centerplot.underlays.append(left_axis)
centerplot.underlays.append(bottom_axis)
self.center = imgplot
# Right Plot
rightplot = Plot(self.plotdata,
height=150,
width=150,
resizable="hv",
padding=0)
rightplot.default_origin = 'top left'
rightplot.value_range = centerplot.value_range
imgplot = rightplot.img_plot("yz",
xbounds=(self.model.z_axis[0],
self.model.z_axis[-1]),
ybounds=(self.model.y_axis[0],
self.model.y_axis[-1]),
colormap=cmap)[0]
imgplot.origin = 'top left'
self._add_plot_tools(imgplot, "yz")
left_axis = PlotAxis(rightplot, orientation='left', title='y')
bottom_axis = PlotAxis(rightplot,
orientation='bottom',
title='z',
title_spacing=30)
rightplot.underlays.append(left_axis)
rightplot.underlays.append(bottom_axis)
self.right = imgplot
# Bottom Plot
bottomplot = Plot(self.plotdata,
height=150,
width=150,
resizable="hv",
padding=0)
bottomplot.index_range = centerplot.index_range
imgplot = bottomplot.img_plot("xz",
xbounds=(self.model.x_axis[0],
self.model.x_axis[-1]),
ybounds=(self.model.z_axis[0],
self.model.z_axis[-1]),
colormap=cmap)[0]
self._add_plot_tools(imgplot, "xz")
left_axis = PlotAxis(bottomplot, orientation='left', title='z')
bottom_axis = PlotAxis(bottomplot,
orientation='bottom',
title='x',
title_spacing=30)
bottomplot.underlays.append(left_axis)
bottomplot.underlays.append(bottom_axis)
self.bottom = imgplot
# Create Container and add all Plots
# container = GridPlotContainer(padding=20, fill_padding=True,
# bgcolor="white", use_backbuffer=True,
# shape=(2,2), spacing=(12,12))
self.container.add(centerplot)
self.container.add(rightplot)
self.container.add(bottomplot)
#return Window(self, -1, component=container)
# return container
return label
def add_plot(self, label, beam):
# container = GridPlotContainer(padding=20, fill_padding=True,
# bgcolor="white", use_backbuffer=True,
# shape=(2,2), spacing=(12,12))
# self.container = container
self.plotdata = ArrayPlotData()
self.model = beam.Data
self.model.z_axis = self.model.z_axis[::-1]
cmap = jet
self._update_model(cmap)
self.plotdata.set_data("xy",self.model.dose)
self._update_images()
# Center Plot
centerplot = Plot(self.plotdata, resizable='hv', height=150, width=150, padding=0)
centerplot.default_origin = 'top left'
imgplot = centerplot.img_plot("xy",
xbounds=(self.model.x_axis[0], self.model.x_axis[-1]),
ybounds=(self.model.y_axis[0], self.model.y_axis[-1]),
colormap=cmap)[0]
imgplot.origin = 'top left'
self._add_plot_tools(imgplot, "xy")
left_axis = PlotAxis(centerplot, orientation='left', title='y')
bottom_axis = PlotAxis(centerplot, orientation='bottom', title='x',
title_spacing=30)
centerplot.underlays.append(left_axis)
centerplot.underlays.append(bottom_axis)
self.center = imgplot
# Right Plot
rightplot = Plot(self.plotdata, height=150, width=150, resizable="hv", padding=0)
rightplot.default_origin = 'top left'
rightplot.value_range = centerplot.value_range
imgplot = rightplot.img_plot("yz",
xbounds=(self.model.z_axis[0], self.model.z_axis[-1]),
ybounds=(self.model.y_axis[0], self.model.y_axis[-1]),
colormap=cmap)[0]
imgplot.origin = 'top left'
self._add_plot_tools(imgplot, "yz")
left_axis = PlotAxis(rightplot, orientation='left', title='y')
bottom_axis = PlotAxis(rightplot, orientation='bottom', title='z',
title_spacing=30)
rightplot.underlays.append(left_axis)
rightplot.underlays.append(bottom_axis)
self.right = imgplot
# Bottom Plot
bottomplot = Plot(self.plotdata, height=150, width=150, resizable="hv", padding=0)
bottomplot.index_range = centerplot.index_range
imgplot = bottomplot.img_plot("xz",
xbounds=(self.model.x_axis[0], self.model.x_axis[-1]),
ybounds=(self.model.z_axis[0], self.model.z_axis[-1]),
colormap=cmap)[0]
self._add_plot_tools(imgplot, "xz")
left_axis = PlotAxis(bottomplot, orientation='left', title='z')
bottom_axis = PlotAxis(bottomplot, orientation='bottom', title='x',
title_spacing=30)
bottomplot.underlays.append(left_axis)
bottomplot.underlays.append(bottom_axis)
self.bottom = imgplot
# Create Container and add all Plots
# container = GridPlotContainer(padding=20, fill_padding=True,
# bgcolor="white", use_backbuffer=True,
# shape=(2,2), spacing=(12,12))
self.container.add(centerplot)
self.container.add(rightplot)
self.container.add(bottomplot)
#return Window(self, -1, component=container)
# return container
return label