gem5/util/stats/barchart.py
Nathan Binkert 02098f8e7b Totally re-work the way that jobfiles are done so there is more
information that can be used for other aspects of sending jobs.
New graphing output stuff with matplotlib.

util/pbs/job.py:
    Shuffle code around and create the JobDir class which encapsulates
    all of the functionality needed for making, organizing, and cleaning
    a job directory.
    Better status output
util/pbs/jobfile.py:
    Majory re-working of the jobfile code.
    A job file now consists of several objects that describe how
    jobs should be run, it includes information about checkpoints,
    and graphing.
util/pbs/send.py:
    use the new jobfile code.
    deal with the 15 character limit of pbs by truncating the name and
    using the raj hack.
util/stats/db.py:
    fix the __str__ function for nodes
    provide __getitem__ for the Database class
util/stats/stats.py:
    use the jobfile stuff to figure out what the proper naming
    and organziation of the graphs should be.
    move all output code to output.py, get rid of ploticus and use
    matplotlib

--HG--
rename : util/categories.py => util/stats/categories.py
extra : convert_revision : 0d793cbf6ad9492290e8ec875ce001c84095e1f7
2005-09-17 16:51:26 -04:00

246 lines
8.6 KiB
Python

# 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()