import matplotlib, pylabfrom matplotlib.numerix import array, arange, reshape, shape, transpose, zerosfrom matplotlib.numerix import Floatmatplotlib.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()