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Python Graph.gca方法代码示例

本文整理汇总了Python中graphs.Graph.gca方法的典型用法代码示例。如果您正苦于以下问题:Python Graph.gca方法的具体用法?Python Graph.gca怎么用?Python Graph.gca使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在graphs.Graph的用法示例。


在下文中一共展示了Graph.gca方法的1个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: makeResults

# 需要导入模块: from graphs import Graph [as 别名]
# 或者: from graphs.Graph import gca [as 别名]
    def makeResults(cls, methods, checkName="bw", saveResults=True):
        """Make result to graphics
        :param methods : results to process
        :param checkName: name of the current check being processed
        :param saveResults : save results to json file ?"""
        if saveResults:
            try:
                fn = cls.saveResults(methods, checkName)
                info("Saved bandwidth results to file %s\n" % fn)
            except Exception as e:
                error("Could not save bandwidth results : %s\n" % e)

        import numpy as np
        from matplotlib.backends.backend_pdf import PdfPages

        try:
            for name, method in methods.iteritems():
                info("Result of measures for method %s:" % name)
                for pair in method["pairs"]:
                    info(pair.printAll())
                info("\n")
        except Exception as e:
            error("Could not print results %s\n" % e)

        nmethods = len(methods)
        gr = 1
        ncols = 3
        nlines = nmethods
        nbins = 15
        # dict(step : dict(method, data))
        # mboxes = {}
        try:
            fn = "checks/%s.pdf" % checkName
            pdf = PdfPages(fn)
            for name, method in methods.iteritems():
                avgs = {}
                ts = {}
                adiffs = {}
                rdiffs = {}
                steps = {"total": None}
                for target, tsteps in method["real_steps"].iteritems():
                    st = zip(*tsteps)
                    step_time = np.array((0,) + st[1])
                    step_values = np.array((0,) + st[0])
                    steps[target] = (step_time, step_values)
                    steps["total"] = (
                        (step_time, np.minimum(steps["total"][1], step_values))
                        if steps["total"] is not None
                        else (step_time, step_values)
                    )

                for pair in method["pairs"]:
                    avg = map(lambda measure: measure.bw / (1000 ** 2), pair.measures)
                    adiff = map(lambda measure: measure.bw / (1000 ** 2) - measure.step, pair.measures)
                    rdiff = map(
                        lambda measure: abs(measure.bw / (1000.0 ** 2) - measure.step) / float(measure.step),
                        pair.measures,
                    )
                    t = map(lambda measure: measure.timestamp, pair.measures)
                    avgs[pair.getPair()] = np.array(avg)
                    ts[pair.getPair()] = np.array(t)
                    adiffs[pair.getPair()] = np.array(adiff)
                    rdiffs[pair.getPair()] = np.array(rdiff)

                # plot the data
                Graph.subplot(nlines, ncols, gr)
                for pair in method["pairs"]:
                    Graph.scatter(
                        ts[pair.getPair()],
                        avgs[pair.getPair()],
                        color=Graph.getColor(pair.getPair()),
                        label="%s,%s" % pair.getPair(),
                    )
                    Graph.hold = True
                for target, tsteps in steps.iteritems():
                    Graph.step(tsteps[0], tsteps[1], "r", where="post", label=target, color=Graph.getColor(target))
                    Graph.hold = True

                Graph.decorate(
                    g_xlabel="Time (s)",
                    g_ylabel="BW estimation with %s (Mbps)" % name,
                    g_title="Measure for Bandwidth for tool %s" % name,
                )
                ax = Graph.gca()
                ax.set_yscale("log")
                Graph.legend(loc=2)

                Graph.draw()
                Graph.subplot(nlines, ncols, gr + 1)
                Graph.hist(
                    rdiffs.values(),
                    nbins,
                    label=["%s,%s" % x for x in rdiffs.keys()],
                    g_xlabel="Relative error",
                    g_title="Relative error for tool %s" % name,
                )
                Graph.legend(loc=2)
                # ax = Graph.gca()
                # ax.set_yscale('log')

#.........这里部分代码省略.........
开发者ID:wicaksana,项目名称:mininet-NetProbes,代码行数:103,代码来源:check.py


注:本文中的graphs.Graph.gca方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。