c0a4836077
options, making existing options more visible and dealing with
holes in data better.
util/stats/barchart.py:
- move the options for BarChart to a base class ChartOptions so
they can be more easily set and copied.
- add an option to set the chart size (so you can adjust the aspect ratio)
- don't do the add_subplot thing, use add_axes directly so we can
affect the size of the figure itself to make room for the legend
- make the initial array bottom floating point so we don't lose precision
- add an option to set the limits on the y axis
- use a figure legend instead of an axes legend so we can put the legend
outside of the actual chart. Also add an option to set the fontsize of
the legend.
- initial hack at outputting csv files
util/stats/db.py:
don't print out an error when the run is missing from the database
just return None, the error will be print elsewhere.
util/stats/output.py:
- make StatOutput derive from ChartOptions so that it's easier to
set default chart options.
- make the various output functions (graph, display, etc.) take the
name of the data as a parameter instead of making it a parameter to
__init__. This allows me to create the StatOutput object with
generic parameters while still being able to specialize the name
after the fact
- add support for graph_group and graph_bars to be applied to multiple
configuration groups. This results in a cross product of the groups
to be generated and used.
- flush the html file output as we go so that we can load the file
while graphs are still being generated.
- make the proxy a parameter to the graph function so the proper system's
data can be graphed
- for any groups or bars that are completely missing, remove them from
the graph. This way, if we decide not to do a set of runs, there won't
be holes in the data.
- output eps and ps by default in addition to the png.
util/stats/profile.py:
- clean up the data structures that are used to store the function
profile information and try our best to avoid keeping extra data
around that isn't used.
- make get() return None if a job is missing so we know it was
missing rather than the all zeroes thing.
- make the function profile categorization stuff total up to 100%
- Fixup the x-axis and y-axis labels.
- fix the dot file output stuff.
util/stats/stats.py:
support the new options stuff for StatOutput
--HG--
extra : convert_revision : fae35df8c57a36257ea93bc3e0a0e617edc46bb7
269 lines
9.6 KiB
Python
269 lines
9.6 KiB
Python
# Copyright (c) 2005 The Regents of The University of Michigan
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# All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are
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# met: redistributions of source code must retain the above copyright
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# notice, this list of conditions and the following disclaimer;
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# redistributions in binary form must reproduce the above copyright
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# notice, this list of conditions and the following disclaimer in the
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# documentation and/or other materials provided with the distribution;
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# neither the name of the copyright holders nor the names of its
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# contributors may be used to endorse or promote products derived from
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# this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
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# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#
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# Authors: Nathan Binkert
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# Lisa Hsu
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import matplotlib, pylab
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from matplotlib.font_manager import FontProperties
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from matplotlib.numerix import array, arange, reshape, shape, transpose, zeros
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from matplotlib.numerix import Float
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matplotlib.interactive(False)
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from chart import ChartOptions
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class BarChart(ChartOptions):
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def __init__(self, default=None, **kwargs):
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super(BarChart, self).__init__(default, **kwargs)
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self.inputdata = None
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self.chartdata = None
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def gen_colors(self, count):
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cmap = matplotlib.cm.get_cmap(self.colormap)
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if count == 1:
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return cmap([ 0.5 ])
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else:
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return cmap(arange(count) / float(count - 1))
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# The input data format does not match the data format that the
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# graph function takes because it is intuitive. The conversion
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# from input data format to chart data format depends on the
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# dimensionality of the input data. Check here for the
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# dimensionality and correctness of the input data
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def set_data(self, data):
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if data is None:
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self.inputdata = None
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self.chartdata = None
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return
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data = array(data)
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dim = len(shape(data))
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if dim not in (1, 2, 3):
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raise AttributeError, "Input data must be a 1, 2, or 3d matrix"
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self.inputdata = data
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# If the input data is a 1d matrix, then it describes a
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# standard bar chart.
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if dim == 1:
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self.chartdata = array([[data]])
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# If the input data is a 2d matrix, then it describes a bar
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# chart with groups. The matrix being an array of groups of
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# bars.
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if dim == 2:
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self.chartdata = transpose([data], axes=(2,0,1))
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# If the input data is a 3d matrix, then it describes an array
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# of groups of bars with each bar being an array of stacked
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# values.
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if dim == 3:
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self.chartdata = transpose(data, axes=(1,2,0))
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def get_data(self):
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return self.inputdata
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data = property(get_data, set_data)
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# Graph the chart data.
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# Input is a 3d matrix that describes a plot that has multiple
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# groups, multiple bars in each group, and multiple values stacked
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# in each bar. The underlying bar() function expects a sequence of
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# bars in the same stack location and same group location, so the
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# organization of the matrix is that the inner most sequence
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# represents one of these bar groups, then those are grouped
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# together to make one full stack of bars in each group, and then
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# the outer most layer describes the groups. Here is an example
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# data set and how it gets plotted as a result.
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#
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# e.g. data = [[[10,11,12], [13,14,15], [16,17,18], [19,20,21]],
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# [[22,23,24], [25,26,27], [28,29,30], [31,32,33]]]
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#
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# will plot like this:
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#
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# 19 31 20 32 21 33
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# 16 28 17 29 18 30
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# 13 25 14 26 15 27
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# 10 22 11 23 12 24
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#
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# Because this arrangement is rather conterintuitive, the rearrange
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# function takes various matricies and arranges them to fit this
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# profile.
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#
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# This code deals with one of the dimensions in the matrix being
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# one wide.
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#
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def graph(self):
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if self.chartdata is None:
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raise AttributeError, "Data not set for bar chart!"
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self.figure = pylab.figure(figsize=self.chart_size)
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self.axes = self.figure.add_axes(self.figure_size)
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dim = len(shape(self.inputdata))
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cshape = shape(self.chartdata)
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if dim == 1:
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colors = self.gen_colors(cshape[2])
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colors = [ [ colors ] * cshape[1] ] * cshape[0]
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if dim == 2:
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colors = self.gen_colors(cshape[0])
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colors = [ [ [ c ] * cshape[2] ] * cshape[1] for c in colors ]
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if dim == 3:
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colors = self.gen_colors(cshape[1])
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colors = [ [ [ c ] * cshape[2] for c in colors ] ] * cshape[0]
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colors = array(colors)
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bars_in_group = len(self.chartdata)
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if bars_in_group < 5:
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width = 1.0 / ( bars_in_group + 1)
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center = width / 2
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else:
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width = .8 / bars_in_group
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center = .1
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bars = []
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for i,stackdata in enumerate(self.chartdata):
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bottom = array([0.0] * len(stackdata[0]), Float)
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stack = []
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for j,bardata in enumerate(stackdata):
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bardata = array(bardata)
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ind = arange(len(bardata)) + i * width + center
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bar = self.axes.bar(ind, bardata, width, bottom=bottom,
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color=colors[i][j])
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stack.append(bar)
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bottom += bardata
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bars.append(stack)
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if self.xlabel is not None:
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self.axes.set_xlabel(self.xlabel)
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if self.ylabel is not None:
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self.axes.set_ylabel(self.ylabel)
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if self.yticks is not None:
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ymin, ymax = self.axes.get_ylim()
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nticks = float(len(self.yticks))
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ticks = arange(nticks) / (nticks - 1) * (ymax - ymin) + ymin
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self.axes.set_yticks(ticks)
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self.axes.set_yticklabels(self.yticks)
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elif self.ylim is not None:
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self.axes.set_ylim(self.ylim)
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if self.xticks is not None:
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self.axes.set_xticks(arange(cshape[2]) + .5)
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self.axes.set_xticklabels(self.xticks)
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if self.legend is not None:
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if dim == 1:
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lbars = bars[0][0]
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if dim == 2:
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lbars = [ bars[i][0][0] for i in xrange(len(bars))]
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if dim == 3:
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number = len(bars[0])
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lbars = [ bars[0][number - j - 1][0] for j in xrange(number)]
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self.figure.legend(lbars, self.legend, self.legend_loc,
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prop=FontProperties(size=self.legend_size))
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if self.title is not None:
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self.axes.set_title(self.title)
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def savefig(self, name):
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self.figure.savefig(name)
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def savecsv(self, name):
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f = file(name, 'w')
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data = array(self.inputdata)
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dim = len(data.shape)
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if dim == 1:
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#if self.xlabel:
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# f.write(', '.join(list(self.xlabel)) + '\n')
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f.write(', '.join([ '%f' % val for val in data]) + '\n')
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if dim == 2:
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#if self.xlabel:
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# f.write(', '.join([''] + list(self.xlabel)) + '\n')
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for i,row in enumerate(data):
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ylabel = []
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#if self.ylabel:
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# ylabel = [ self.ylabel[i] ]
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f.write(', '.join(ylabel + [ '%f' % val for val in row]) + '\n')
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if dim == 3:
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f.write("don't do 3D csv files\n")
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pass
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f.close()
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if __name__ == '__main__':
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from random import randrange
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import random, sys
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dim = 3
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number = 5
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args = sys.argv[1:]
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if len(args) > 3:
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sys.exit("invalid number of arguments")
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elif len(args) > 0:
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myshape = [ int(x) for x in args ]
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else:
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myshape = [ 3, 4, 8 ]
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# generate a data matrix of the given shape
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size = reduce(lambda x,y: x*y, myshape)
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#data = [ random.randrange(size - i) + 10 for i in xrange(size) ]
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data = [ float(i)/100.0 for i in xrange(size) ]
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data = reshape(data, myshape)
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# setup some test bar charts
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if True:
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chart1 = BarChart()
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chart1.data = data
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chart1.xlabel = 'Benchmark'
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chart1.ylabel = 'Bandwidth (GBps)'
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chart1.legend = [ 'x%d' % x for x in xrange(myshape[-1]) ]
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chart1.xticks = [ 'xtick%d' % x for x in xrange(myshape[0]) ]
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chart1.title = 'this is the title'
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chart1.graph()
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chart1.savefig('/tmp/test1.png')
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chart1.savefig('/tmp/test1.ps')
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chart1.savefig('/tmp/test1.eps')
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chart1.savecsv('/tmp/test1.csv')
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if False:
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chart2 = BarChart()
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chart2.data = data
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chart2.colormap = 'gray'
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chart2.graph()
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chart2.savefig('/tmp/test2.png')
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chart2.savefig('/tmp/test2.ps')
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#pylab.show()
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