#!/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 chaco.example_support import COLOR_PALETTE
# Enthought library imports
from enable.api import Component, ComponentEditor
from traits.api import HasTraits, Instance
from traitsui.api import Item, Group, View

# Chaco imports
from chaco.api import create_line_plot, OverlayPlotContainer, PlotLabel, \
                                 create_scatter_plot, Legend, PlotGrid
from chaco.tools.api import PanTool, ZoomTool, \
                                       LegendTool, TraitsTool

from chaco.scales.api import CalendarScaleSystem
from chaco.scales_tick_generator import ScalesTickGenerator
from 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()

if __name__ == "__main__":
    demo.configure_traits()

#--EOF---
