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#!/usr/bin/env python
# This example shows how to use the agg backend directly to create
# images, which may be of use to web application developers who want
# full control over their code without using the pylab interface to
# manage figures, figure closing etc.
# The rc command is used to create per-script default figure
# customizations of the rc parameters; see
# http://matplotlib.sf.net/matplotlibrc .  You may prefer to set the
# rc parameters in the rc file itself.  Note that you can keep
# directory level default configurations by placing different rc files
# in the directory that the script runs in.
# I am making no effort here to make a figure that looks good --
# rather I am just trying to show the various ways to use matplotlib
# to customize your figure using the matplotlib API

import matplotlib
matplotlib.use('Agg')  # force the antigrain backend
from matplotlib import rc
from matplotlib.backends.backend_agg import FigureCanvasAgg
from matplotlib.figure import Figure
from matplotlib.cbook import iterable
import numpy as np

def make_fig():
    make a figure

    No need to close figures or clean up since the objects will be
    destroyed when they go out of scope
    fig = Figure()
    #ax = fig.add_subplot(111)  # add a standard subplot

    # add an axes at left, bottom, width, height; by making the bottom
    # at 0.3, we save some extra room for tick labels
    ax = fig.add_axes([0.2, 0.3, 0.7, 0.6])

    line,  = ax.plot([1,2,3], 'ro--', markersize=12, markerfacecolor='g')

    # make a translucent scatter collection
    x = np.random.rand(100)
    y = np.random.rand(100)
    area = np.pi*(10 * np.random.rand(100))**2 # 0 to 10 point radiuses
    c = ax.scatter(x,y,area)

    # add some text decoration
    ax.set_title('My first image')
    ax.set_ylabel('Some numbers')
    ax.set_xticks( (.2,.4,.6,.8) )
    labels = ax.set_xticklabels(('Bill', 'Fred', 'Ted', 'Ed'))

    # To set object properties, you can either iterate over the
    # objects manually, or define you own set command, as in setapi
    # above.
    for l in labels:

    canvas = FigureCanvasAgg(fig)
    canvas.print_figure('webapp.png', dpi=150)


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