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# Copyright (c) 2005-2006 The Regents of The University of Michigan
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met: redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer;
# redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution;
# neither the name of the copyright holders nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
# Authors: Nathan Binkert
# Lisa Hsu
import matplotlib, pylab
from matplotlib.font_manager import FontProperties
from matplotlib.numerix import array, arange, reshape, shape, transpose, zeros
from matplotlib.numerix import Float
from matplotlib.ticker import NullLocator
matplotlib.interactive(False)
from chart import ChartOptions
class BarChart(ChartOptions):
def __init__(self, default=None, **kwargs):
super(BarChart, self).__init__(default, **kwargs)
self.inputdata = None
self.chartdata = None
def gen_colors(self, count):
cmap = matplotlib.cm.get_cmap(self.colormap)
if count == 1:
return cmap([ 0.5 ])
else:
return cmap(arange(count) / float(count - 1))
# The input data format does not match the data format that the
# graph function takes because it is intuitive. The conversion
# from input data format to chart data format depends on the
# dimensionality of the input data. Check here for the
# dimensionality and correctness of the input data
def set_data(self, data):
if data is None:
self.inputdata = None
self.chartdata = None
return
data = array(data)
dim = len(shape(data))
if dim not in (1, 2, 3):
raise AttributeError, "Input data must be a 1, 2, or 3d matrix"
self.inputdata = data
# If the input data is a 1d matrix, then it describes a
# standard bar chart.
if dim == 1:
self.chartdata = array([[data]])
# If the input data is a 2d matrix, then it describes a bar
# chart with groups. The matrix being an array of groups of
# bars.
if dim == 2:
self.chartdata = transpose([data], axes=(2,0,1))
# If the input data is a 3d matrix, then it describes an array
# of groups of bars with each bar being an array of stacked
# values.
if dim == 3:
self.chartdata = transpose(data, axes=(1,2,0))
def get_data(self):
return self.inputdata
data = property(get_data, set_data)
# Graph the chart data.
# Input is a 3d matrix that describes a plot that has multiple
# groups, multiple bars in each group, and multiple values stacked
# in each bar. The underlying bar() function expects a sequence of
# bars in the same stack location and same group location, so the
# organization of the matrix is that the inner most sequence
# represents one of these bar groups, then those are grouped
# together to make one full stack of bars in each group, and then
# the outer most layer describes the groups. Here is an example
# data set and how it gets plotted as a result.
#
# e.g. data = [[[10,11,12], [13,14,15], [16,17,18], [19,20,21]],
# [[22,23,24], [25,26,27], [28,29,30], [31,32,33]]]
#
# will plot like this:
#
# 19 31 20 32 21 33
# 16 28 17 29 18 30
# 13 25 14 26 15 27
# 10 22 11 23 12 24
#
# Because this arrangement is rather conterintuitive, the rearrange
# function takes various matricies and arranges them to fit this
# profile.
#
# This code deals with one of the dimensions in the matrix being
# one wide.
#
def graph(self):
if self.chartdata is None:
raise AttributeError, "Data not set for bar chart!"
dim = len(shape(self.inputdata))
cshape = shape(self.chartdata)
if dim == 1:
colors = self.gen_colors(cshape[2])
colors = [ [ colors ] * cshape[1] ] * cshape[0]
if dim == 2:
colors = self.gen_colors(cshape[0])
colors = [ [ [ c ] * cshape[2] ] * cshape[1] for c in colors ]
if dim == 3:
colors = self.gen_colors(cshape[1])
colors = [ [ [ c ] * cshape[2] for c in colors ] ] * cshape[0]
colors = array(colors)
self.figure = pylab.figure(figsize=self.chart_size)
outer_axes = None
inner_axes = None
if self.xsubticks is not None:
color = self.figure.get_facecolor()
self.metaaxes = self.figure.add_axes(self.figure_size, axisbg=color, frameon=False)
for tick in self.metaaxes.xaxis.majorTicks:
tick.tick1On = False
tick.tick2On = False
self.metaaxes.set_yticklabels([])
self.metaaxes.set_yticks([])
size = [0] * 4
size[0] = self.figure_size[0]
size[1] = self.figure_size[1] + .12
size[2] = self.figure_size[2]
size[3] = self.figure_size[3] - .12
self.axes = self.figure.add_axes(size)
outer_axes = self.metaaxes
inner_axes = self.axes
else:
self.axes = self.figure.add_axes(self.figure_size)
outer_axes = self.axes
inner_axes = self.axes
bars_in_group = len(self.chartdata)
width = 1.0 / ( bars_in_group + 1)
center = width / 2
bars = []
for i,stackdata in enumerate(self.chartdata):
bottom = array([0.0] * len(stackdata[0]), Float)
stack = []
for j,bardata in enumerate(stackdata):
bardata = array(bardata)
ind = arange(len(bardata)) + i * width + center
bar = self.axes.bar(ind, bardata, width, bottom=bottom,
color=colors[i][j])
if self.xsubticks is not None:
self.metaaxes.bar(ind, [0] * len(bardata), width)
stack.append(bar)
bottom += bardata
bars.append(stack)
if self.xlabel is not None:
outer_axes.set_xlabel(self.xlabel)
if self.ylabel is not None:
inner_axes.set_ylabel(self.ylabel)
if self.yticks is not None:
ymin, ymax = self.axes.get_ylim()
nticks = float(len(self.yticks))
ticks = arange(nticks) / (nticks - 1) * (ymax - ymin) + ymin
inner_axes.set_yticks(ticks)
inner_axes.set_yticklabels(self.yticks)
elif self.ylim is not None:
self.inner_axes.set_ylim(self.ylim)
if self.xticks is not None:
outer_axes.set_xticks(arange(cshape[2]) + .5)
outer_axes.set_xticklabels(self.xticks)
if self.xsubticks is not None:
inner_axes.set_xticks(arange((cshape[0] + 1)*cshape[2])*width + 2*center)
self.xsubticks.append('')
inner_axes.set_xticklabels(self.xsubticks * cshape[2], fontsize=7, rotation=90)
if self.legend is not None:
if dim == 1:
lbars = bars[0][0]
if dim == 2:
lbars = [ bars[i][0][0] for i in xrange(len(bars))]
if dim == 3:
number = len(bars[0])
lbars = [ bars[0][number - j - 1][0] for j in xrange(number)]
self.figure.legend(lbars, self.legend, self.legend_loc,
prop=FontProperties(size=self.legend_size))
if self.title is not None:
self.axes.set_title(self.title)
def savefig(self, name):
self.figure.savefig(name)
def savecsv(self, name):
f = file(name, 'w')
data = array(self.inputdata)
dim = len(data.shape)
if dim == 1:
#if self.xlabel:
# f.write(', '.join(list(self.xlabel)) + '\n')
f.write(', '.join([ '%f' % val for val in data]) + '\n')
if dim == 2:
#if self.xlabel:
# f.write(', '.join([''] + list(self.xlabel)) + '\n')
for i,row in enumerate(data):
ylabel = []
#if self.ylabel:
# ylabel = [ self.ylabel[i] ]
f.write(', '.join(ylabel + [ '%f' % val for val in row]) + '\n')
if dim == 3:
f.write("don't do 3D csv files\n")
pass
f.close()
if __name__ == '__main__':
from random import randrange
import random, sys
dim = 3
number = 5
args = sys.argv[1:]
if len(args) > 3:
sys.exit("invalid number of arguments")
elif len(args) > 0:
myshape = [ int(x) for x in args ]
else:
myshape = [ 3, 4, 8 ]
# generate a data matrix of the given shape
size = reduce(lambda x,y: x*y, myshape)
#data = [ random.randrange(size - i) + 10 for i in xrange(size) ]
data = [ float(i)/100.0 for i in xrange(size) ]
data = reshape(data, myshape)
# setup some test bar charts
if True:
chart1 = BarChart()
chart1.data = data
chart1.xlabel = 'Benchmark'
chart1.ylabel = 'Bandwidth (GBps)'
chart1.legend = [ 'x%d' % x for x in xrange(myshape[-1]) ]
chart1.xticks = [ 'xtick%d' % x for x in xrange(myshape[0]) ]
chart1.title = 'this is the title'
if len(myshape) > 2:
chart1.xsubticks = [ '%d' % x for x in xrange(myshape[1]) ]
chart1.graph()
chart1.savefig('/tmp/test1.png')
chart1.savefig('/tmp/test1.ps')
chart1.savefig('/tmp/test1.eps')
chart1.savecsv('/tmp/test1.csv')
if False:
chart2 = BarChart()
chart2.data = data
chart2.colormap = 'gray'
chart2.graph()
chart2.savefig('/tmp/test2.png')
chart2.savefig('/tmp/test2.ps')
# pylab.show()
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