fcb9718dcd
2) make subticks vertical so they can be longer 3) make inner and outer axes farther apart to make room for subtick's vertical labels --HG-- extra : convert_revision : 91a1aab3f1078921edd53428e6712744210c9f1b
298 lines
11 KiB
Python
298 lines
11 KiB
Python
# 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()
|