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"""
Implementation of a standard financial plot visualization using Chaco
renderers and scales. This differs from the financial_plot.py example
in that it uses a date-oriented axis.
"""
# Major library imports
from numpy import abs, arange, cumprod, linspace, random
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 ArrayDataSource, BarPlot, DataRange1D, \
LabelAxis, LinearMapper, VPlotContainer, PlotAxis, PlotGrid, \
FilledLinePlot, add_default_grids, PlotLabel
from enthought.chaco.tools.api import PanTool, ZoomTool
from enthought.chaco.scales.api import CalendarScaleSystem
from enthought.chaco.scales_tick_generator import ScalesTickGenerator
def create_dates(numpoints, units="days"):
""" Returns **numpoints** number of dates that evenly bracket the current
date and time. **units** should be one of "weeks", "days", "hours"
"minutes", or "seconds".
"""
units_map = { "weeks" : 7*24*3600,
"days" : 24*3600,
"hours" : 3600,
"minutes" : 60,
"seconds" : 1 }
now = time.time()
dt = units_map[units]
dates = linspace(now, now+numpoints*dt, numpoints)
return dates
#===============================================================================
# # Create the Chaco plot.
#===============================================================================
def _create_plot_component():
# Create the data and datasource objects
# In order for the date axis to work, the index data points need to
# be in units of seconds since the epoch. This is because we are using
# the CalendarScaleSystem, whose formatters interpret the numerical values
# as seconds since the epoch.
numpoints = 500
index = create_dates(numpoints)
returns = random.lognormal(0.01, 0.1, size=numpoints)
price = 100.0 * cumprod(returns)
volume = abs(random.normal(1000.0, 1500.0, size=numpoints) + 2000.0)
time_ds = ArrayDataSource(index)
vol_ds = ArrayDataSource(volume, sort_order="none")
price_ds = ArrayDataSource(price, sort_order="none")
xmapper = LinearMapper(range=DataRange1D(time_ds))
vol_mapper = LinearMapper(range=DataRange1D(vol_ds))
price_mapper = LinearMapper(range=DataRange1D(price_ds))
price_plot = FilledLinePlot(index = time_ds, value = price_ds,
index_mapper = xmapper,
value_mapper = price_mapper,
edge_color = "blue",
face_color = "paleturquoise",
bgcolor = "white",
border_visible = True)
price_plot.overlays.append(PlotAxis(price_plot, orientation='left')),
# Set the plot's bottom axis to use the Scales ticking system
bottom_axis = PlotAxis(price_plot, orientation="bottom",# mapper=xmapper,
tick_generator=ScalesTickGenerator(scale=CalendarScaleSystem()))
price_plot.overlays.append(bottom_axis)
hgrid, vgrid = add_default_grids(price_plot)
vgrid.tick_generator = bottom_axis.tick_generator
price_plot.tools.append(PanTool(price_plot, constrain=True,
constrain_direction="x"))
price_plot.overlays.append(ZoomTool(price_plot, drag_button="right",
always_on=True,
tool_mode="range",
axis="index",
max_zoom_out_factor=10.0,
))
vol_plot = BarPlot(index = time_ds, value = vol_ds,
index_mapper = xmapper,
value_mapper = vol_mapper,
line_color = "transparent",
fill_color = "black",
bar_width = 1.0,
bar_width_type = "screen",
antialias = False,
height = 100,
resizable = "h",
bgcolor = "white",
border_visible = True)
hgrid, vgrid = add_default_grids(vol_plot)
# Use the same tick generator as the x-axis on the price plot
vgrid.tick_generator = bottom_axis.tick_generator
vol_plot.underlays.append(PlotAxis(vol_plot, orientation='left'))
vol_plot.tools.append(PanTool(vol_plot, constrain=True,
constrain_direction="x"))
container = VPlotContainer(bgcolor = "lightblue",
spacing = 40,
padding = 50,
fill_padding=False)
container.add(vol_plot)
container.add(price_plot)
container.overlays.append(PlotLabel("Financial Plot with Date Axis",
component=container,
#font="Times New Roman 24"))
font="Arial 24"))
return container
#===============================================================================
# Attributes to use for the plot view.
size=(800,600)
title="Financial plot example"
#===============================================================================
# # 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---
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