diff options
Diffstat (limited to 'util/stats/barchart.py')
| -rw-r--r-- | util/stats/barchart.py | 246 |
1 files changed, 246 insertions, 0 deletions
diff --git a/util/stats/barchart.py b/util/stats/barchart.py new file mode 100644 index 000000000..a2cbea816 --- /dev/null +++ b/util/stats/barchart.py @@ -0,0 +1,246 @@ +# Copyright (c) 2005 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.numerix import array, arange, reshape, shape, transpose, zeros +from matplotlib.numerix import Float + +matplotlib.interactive(False) + +class BarChart(object): + def __init__(self, **kwargs): + self.init(**kwargs) + + def init(self, **kwargs): + self.colormap = 'jet' + self.inputdata = None + self.chartdata = None + self.xlabel = None + self.ylabel = None + self.legend = None + self.xticks = None + self.yticks = None + self.title = None + + for key,value in kwargs.iteritems(): + self.__setattr__(key, value) + + 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!" + + self.figure = pylab.figure() + self.axes = self.figure.add_subplot(111) + + 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) + + bars_in_group = len(self.chartdata) + if bars_in_group < 5: + width = 1.0 / ( bars_in_group + 1) + center = width / 2 + else: + width = .8 / bars_in_group + center = .1 + + bars = [] + for i,stackdata in enumerate(self.chartdata): + bottom = array([0] * len(stackdata[0])) + 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]) + stack.append(bar) + bottom += bardata + bars.append(stack) + + if self.xlabel is not None: + self.axes.set_xlabel(self.xlabel) + + if self.ylabel is not None: + self.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 + self.axes.set_yticks(ticks) + self.axes.set_yticklabels(self.yticks) + + if self.xticks is not None: + self.axes.set_xticks(arange(cshape[2]) + .5) + self.axes.set_xticklabels(self.xticks) + + 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.axes.legend(lbars, self.legend, loc='best') + + if self.title is not None: + self.axes.set_title(self.title) + + def savefig(self, name): + self.figure.savefig(name) + +if __name__ == '__main__': + 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' + chart1.graph() + #chart1.savefig('/tmp/test1.png') + + if False: + chart2 = BarChart() + chart2.data = data + chart2.colormap = 'gray' + chart2.graph() + #chart2.savefig('/tmp/test2.png') + + pylab.show() |