def __init__(self, x, y, color="blue", bgcolor="white"):
self.y_values = y[:]
if type(x) == ArrayDataSource:
self.x_values = x.get_data()[:]
plot = create_line_plot((x, self.y_values),
color=color,
bgcolor=bgcolor,
add_grid=True,
add_axis=True)
else:
self.x_values = x[:]
plot = create_line_plot((self.x_values, self.y_values),
color=color,
bgcolor=bgcolor,
add_grid=True,
add_axis=True)
plot.resizable = ""
plot.bounds = [PLOT_SIZE, PLOT_SIZE]
plot.unified_draw = True
plot.tools.append(PanTool(plot, drag_button="right"))
plot.tools.append(MoveTool(plot))
plot.overlays.append(ZoomTool(plot, tool_mode="box", always_on=False))
self.plot = plot
self.numpoints = len(self.x_values)
self.current_index = self.numpoints / 2
self.increment = 2
def create_plot():
# Create some data
numpts = 200
x = sort(random(numpts))
y = random(numpts)
color = exp(-(x**2 + y**2))
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
pd.set_data("color", color)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value", "color"),
type="cmap_scatter",
name="my_plot",
color_mapper=jet,
marker="square",
fill_alpha=0.5,
marker_size=6,
outline_color="black",
border_visible=True,
bgcolor="white")
# Tweak some of the plot properties
plot.title = "Colormapped Scatter Plot"
plot.padding = 50
plot.x_grid.visible = False
plot.y_grid.visible = False
plot.x_axis.font = "modern 16"
plot.y_axis.font = "modern 16"
# Set colors
#plot.title_color = "white"
#for axis in plot.x_axis, plot.y_axis:
# axis.trait_set(title_color="white", tick_label_color="white")
# Right now, some of the tools are a little invasive, and we need the
# actual ColomappedScatterPlot object to give to them
cmap_renderer = plot.plots["my_plot"][0]
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
selection = ColormappedSelectionOverlay(cmap_renderer,
fade_alpha=0.35,
selection_type="mask")
cmap_renderer.overlays.append(selection)
plot.tools.append(MoveTool(plot, drag_button="right"))
return plot
def main():
# Create some x-y data series to plot
x = linspace(-2.0, 10.0, 100)
pd = ArrayPlotData(index=x)
for i in range(5):
pd.set_data("y" + str(i), jn(i, x))
# 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", "y0", "y1", "y2"), name="j_n, n<3", color="auto")
plot.plot(("index", "y3"), name="j_3", color="auto")
plot.tools.append(PanTool(plot))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
# Create the mlab test mesh and get references to various parts of the
# VTK pipeline
f = mlab.figure(size=(600, 500))
m = mlab.test_mesh()
scene = mlab.gcf().scene
render_window = scene.render_window
renderer = scene.renderer
rwi = scene.interactor
plot.resizable = ""
plot.bounds = [200, 200]
plot.padding = 25
plot.bgcolor = "lightgray"
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.InteractorStyleSwitch,
#istyle_class = tvtk.InteractorStyle,
istyle_class=tvtk.InteractorStyleTrackballCamera,
bgcolor="transparent",
event_passthrough=True, )
mlab.show()
return window, render_window
def create_colorbar(colormap):
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
orientation='v',
resizable='',
height=400,
width=30,
padding=20)
colorbar.tools.append(RangeSelection(component=colorbar))
colorbar.overlays.append(
RangeSelectionOverlay(component=colorbar,
border_color="white",
alpha=0.8,
fill_color="lightgray"))
colorbar.tools.append(MoveTool(colorbar, drag_button="left"))
return colorbar
def _plot_default(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 a Plot and associate it with the PlotData
plot = Plot(plotdata)
# Create a scatter plot in the Plot
plot.plot(("x", "y"), type="scatter", color="blue")
plot.tools.append(PanTool(plot))
# Add our custom overlay to the plot
overlay = CustomOverlay(plot)
# Add the MoveTool to the overlay so it can be dragged around usin gthe
# right mouse button.
overlay.tools.append(MoveTool(overlay, drag_button="right"))
plot.overlays.append(overlay)
return plot
def main():
from tvtk.api import tvtk
from mayavi import mlab
from enable.vtk_backend.vtk_window import EnableVTKWindow
f = mlab.figure(size=(900, 850))
m = mlab.test_mesh()
scene = mlab.gcf().scene
render_window = scene.render_window
renderer = scene.renderer
rwi = scene.interactor
# Create the plot
timer_controller = TimerController()
plots = create_plot_component(timer_controller)
specplot, timeplot, spectrogram = plots
for i, p in enumerate(plots):
p.resizable = ""
p.bgcolor = "transparent"
p.bounds = [200, 200]
p.outer_x = 0
p.outer_y = i * 250
p.tools.append(MoveTool(p, drag_button="right"))
p.tools.append(PanTool(p))
p.tools.append(ZoomTool(p))
spectrogram.tools[-1].tool_mode = "range"
spectrogram.tools[-1].axis = "value"
spectrogram.tools[-2].constrain = True
spectrogram.tools[-2].constrain_direction = "y"
container = OverlayPlotContainer(bgcolor="transparent", fit_window=True)
container.add(*plots)
container.timer_callback = timer_controller.on_timer
window = EnableVTKWindow(
rwi,
renderer,
component=container,
istyle_class=tvtk.InteractorStyleTrackballCamera,
bgcolor="transparent",
event_passthrough=True,
)
mlab.show()
def _create_plot_component():
# Create some x-y data series to plot
x = linspace(-2.0, 10.0, 100)
pd = ArrayPlotData(index=x)
for i in range(5):
pd.set_data("y" + str(i), jn(i, x))
# Create some line plots of some of the data
plot1 = Plot(pd)
plot1.plot(("index", "y0", "y1", "y2"), name="j_n, n<3", color="red")
plot1.plot(("index", "y3"), name="j_3", color="blue")
# Tweak some of the plot properties
plot1.title = "Inset Plot"
plot1.padding = 50
# Attach some tools to the plot
plot1.tools.append(PanTool(plot1))
zoom = ZoomTool(component=plot1, tool_mode="box", always_on=False)
plot1.overlays.append(zoom)
# Create a second scatter plot of one of the datasets, linking its
# range to the first plot
plot2 = Plot(pd, range2d=plot1.range2d, padding=50)
plot2.plot(('index', 'y3'), type="scatter", color="blue", marker="circle")
plot2.resizable = ""
plot2.bounds = [250, 250]
plot2.position = [550, 150]
plot2.bgcolor = "white"
plot2.border_visible = True
plot2.unified_draw = True
plot2.tools.append(PanTool(plot2))
plot2.tools.append(MoveTool(plot2, drag_button="right"))
zoom = ZoomTool(component=plot2, tool_mode="box", always_on=False)
plot2.overlays.append(zoom)
# Create a container and add our plots
container = OverlayPlotContainer()
container.add(plot1)
container.add(plot2)
return container
def image_histogram_plot_component(self):
xs = np.arange(0, len(self.im))
ys = np.arange(0, len(self.im[0]))
index = GridDataSource(xdata=xs,
ydata=ys,
sort_order=('ascending', 'ascending'))
index_mapper = GridMapper(range=DataRange2D(index))
color_source = ImageData(data=np.flipud(self.im), value_depth=1)
reversed_grays = reverse(Greys)
color_mapper = reversed_grays(DataRange1D(color_source))
plot = CMapImagePlot(
index=index,
index_mapper=index_mapper,
value=color_source,
value_mapper=color_mapper,
)
#: Add overlay for zoom
data_box_overlay = MyDataBox(
component=plot,
data_position=[0, 0],
data_bounds=self.data_bounds,
)
move_tool = MoveTool(component=data_box_overlay)
resize_tool = ResizeTool(component=data_box_overlay)
data_box_overlay.tools.append(move_tool)
data_box_overlay.tools.append(resize_tool)
data_box_overlay.on_trait_change(self.update_position, 'position')
data_box_overlay.on_trait_change(self.update_data_bounds, 'bounds')
#: Add to plot
plot.overlays.append(data_box_overlay)
return plot
def image_histogram_plot_component(self):
xs = np.arange(0, len(self.im))
ys = np.arange(0, len(self.im[0]))
index = GridDataSource(xdata=xs,
ydata=ys,
sort_order=('ascending', 'ascending'))
index_mapper = GridMapper(range=DataRange2D(index))
color_source = ImageData(data=self.im, value_depth=1)
reversed_grays = reverse(Greys)
color_mapper = reversed_grays(DataRange1D(color_source))
plot = CMapImagePlot(
index=index,
index_mapper=index_mapper,
value=color_source,
value_mapper=color_mapper,
orientation='h',
origin='top left',
)
self.data_box_overlay = DataBox(
component=plot,
data_position=[0, 0],
data_bounds=[self.my_data_bounds, self.my_data_bounds],
)
move_tool = MoveTool(component=self.data_box_overlay)
self.data_box_overlay.tools.append(move_tool)
self.data_box_overlay.on_trait_change(self.update_my_position,
'position')
#: Add to plot
plot.overlays.append(self.data_box_overlay)
return plot
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()
