#!/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 matlab 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 matplotlib.numerix as nx
# set some global properties that affect the defaults of all figures
rc('lines', linewidth=2) # thicker plot lines
rc('grid', color=0.75, linestyle='-') # solid gray grid lines
rc('axes', hold=True, # hold state is on
grid=True, facecolor='y') # yellow background, grid on
rc('tick', color='r', labelsize=20) # big red ticks
def setapi(o, **kwargs):
"""
for all key, value pairs in kwargs, and all objects in (possibly)
iterable o, look for a method o.set_key and try to call
o.set_key(value) if it exists. This is basically a refinition of
the matlab interface set command
"""
if not iterable(o): o = [o]
for thiso in o: # iterate over the objects
for k,v in kwargs.items():
func = getattr(thiso, 'set_'+k)
if func is None: continue
func(v)
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 = nx.rand(100)
y = nx.rand(100)
area = nx.pi*(10 * nx.rand(100))**2 # 0 to 10 point radiuses
c = ax.scatter(x,y,area)
c.set_alpha(0.5)
# 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.
#setapi(labels, rotation=45, fontsize=12)
for l in labels:
l.set_rotation(45)
l.set_fontsize(12)
canvas = FigureCanvasAgg(fig)
canvas.print_figure('webapp.png', dpi=150)
make_fig()
