#!/usr/bin/env python
"""
Draws several overlapping line plots.
Left-drag pans the plot.
Mousewheel up and down zooms the plot in and out.
Pressing "z" brings up the Zoom Box, and you can click-drag a rectangular region to
zoom. If you use a sequence of zoom boxes, pressing alt-left-arrow and
alt-right-arrow moves you forwards and backwards through the "zoom history".
Right-click and dragging on the legend allows you to reposition the legend.
Double-clicking on line or scatter plots brings up a traits editor for the plot.
"""
# Major library imports
from numpy import linspace
from scipy.special import jn
from time import time
from enthought.chaco.example_support import COLOR_PALETTE
from enthought.enable.example_support import DemoFrame, demo_main
# Enthought library imports
from enthought.enable.api import Window, Component, ComponentEditor
from enthought.traits.api import HasTraits, Instance
from enthought.traits.ui.api import Item, Group, View
# Chaco imports
from enthought.chaco.api import create_line_plot, OverlayPlotContainer, PlotLabel, \
create_scatter_plot, Legend, PlotGrid
from enthought.chaco.tools.api import PanTool, ZoomTool, \
LegendTool, TraitsTool
from enthought.chaco.scales.api import CalendarScaleSystem
from enthought.chaco.scales_tick_generator import ScalesTickGenerator
from enthought.chaco.axis import PlotAxis
#===============================================================================
# # Create the Chaco plot.
#===============================================================================
def add_default_axes(plot, orientation="normal", vtitle="",htitle=""):
"""
Creates left and bottom axes for a plot. Assumes that the index is
horizontal and value is vertical by default; set orientation to
something other than "normal" if they are flipped.
"""
if orientation in ("normal", "h"):
v_mapper = plot.value_mapper
h_mapper = plot.index_mapper
else:
v_mapper = plot.index_mapper
h_mapper = plot.value_mapper
left = PlotAxis(orientation='left',
title= vtitle,
mapper=v_mapper,
component=plot)
bottom = PlotAxis(orientation='bottom',
title= htitle,
mapper=h_mapper,
component=plot)
plot.underlays.append(left)
plot.underlays.append(bottom)
return left, bottom
def add_default_grids(plot, orientation="normal", tick_gen=None):
"""
Creates horizontal and vertical gridlines for a plot. Assumes that the
index is horizontal and value is vertical by default; set orientation to
something other than "normal" if they are flipped.
"""
if orientation in ("normal", "h"):
v_mapper = plot.index_mapper
h_mapper = plot.value_mapper
else:
v_mapper = plot.value_mapper
h_mapper = plot.index_mapper
vgrid = PlotGrid(mapper=v_mapper, orientation='vertical',
component=plot,
line_color="lightgray", line_style="dot",
tick_generator = tick_gen)
hgrid = PlotGrid(mapper=h_mapper, orientation='horizontal',
component=plot,
line_color="lightgray", line_style="dot",
tick_generator = ScalesTickGenerator())
plot.underlays.append(vgrid)
plot.underlays.append(hgrid)
return hgrid, vgrid
def _create_plot_component():
container = OverlayPlotContainer(padding = 50, fill_padding = True,
bgcolor = "lightgray", use_backbuffer=True)
# Create the initial X-series of data
numpoints = 100
low = -5
high = 15.0
x = linspace(low, high, numpoints)
now = time()
timex = linspace(now, now+7*24*3600, numpoints)
# Plot some bessel functions
value_mapper = None
index_mapper = None
plots = {}
for i in range(10):
y = jn(i, x)
if i%2 == 1:
plot = create_line_plot((timex,y), color=tuple(COLOR_PALETTE[i]), width=2.0)
plot.index.sort_order = "ascending"
else:
plot = create_scatter_plot((timex,y), color=tuple(COLOR_PALETTE[i]))
plot.bgcolor = "white"
plot.border_visible = True
if i == 0:
value_mapper = plot.value_mapper
index_mapper = plot.index_mapper
left, bottom = add_default_axes(plot)
left.tick_generator = ScalesTickGenerator()
bottom.tick_generator = ScalesTickGenerator(scale=CalendarScaleSystem())
add_default_grids(plot, tick_gen=bottom.tick_generator)
else:
plot.value_mapper = value_mapper
value_mapper.range.add(plot.value)
plot.index_mapper = index_mapper
index_mapper.range.add(plot.index)
if i==0:
plot.tools.append(PanTool(plot))
zoom = ZoomTool(plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
# Add a legend in the upper right corner, and make it relocatable
legend = Legend(component=plot, padding=10, align="ur")
legend.tools.append(LegendTool(legend, drag_button="right"))
plot.overlays.append(legend)
container.add(plot)
plots["Bessel j_%d"%i] = plot
# Set the list of plots on the legend
legend.plots = plots
# Add the title at the top
container.overlays.append(PlotLabel("Bessel functions",
component=container,
font = "swiss 16",
overlay_position="top"))
# Add the traits inspector tool to the container
container.tools.append(TraitsTool(container))
return container
#===============================================================================
# Attributes to use for the plot view.
size=(800,700)
title="Simple line plot"
#===============================================================================
# # Demo class that is used by the demo.py application.
#===============================================================================
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,
width=size[0], height=size[1]
)
def _plot_default(self):
return _create_plot_component()
demo = Demo()
#===============================================================================
# Stand-alone frame to display the plot.
#===============================================================================
class PlotFrame(DemoFrame):
def _create_window(self):
# Return a window containing our plots
return Window(self, -1, component=_create_plot_component())
if __name__ == "__main__":
demo_main(PlotFrame, size=size, title=title)
#--EOF---
