Python Line.xValues方法代碼示例

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
    def constructImage(self):
        plot = Plot()

        # Uneven error bars
        line = Line()
        line.xValues = [6,10,4,0,8,2,12]
        line.yValues = [50,90,30,10,70,20,110]
        line.yMins   = [y - 30 for y in line.yValues]
        line.yMaxes  = [y + 50 for y in line.yValues]
        line.label = "Asymmetric Errors"
        line.color = "red"

        # Even error bars
        line2 = Line()
        line2.xValues = [1,5,3,9,7,11]
        line2.yValues = [100, 120, 110, 140, 130, 150]
        line2.color = "blue"
        line2.label = "Symmetric Errors"
        line2.yErrors = [5,25,15,45,35,55]

        plot.add(line)
        plot.add(line2)
        plot.xLabel = "X Label"
        plot.yLabel = "Y Label"
        plot.hasLegend()
        plot.xLimits = (-1, 13)
        plot.save(self.imageName)

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
def histogram_plot(experiment_log_dir, plot_spec_string, output_filename,
                   has_legend, x_limit, verbose):
    queries = [
        plot_utils.plot_spec_string_to_query(plot_spec_string, 0, "HIST")]

    plot_data = metaprogram_utils.process_queries(
        queries, experiment_log_dir, verbose)

    if "plot_points" not in plot_data:
        warnings.warn("No data to plot!")
        return

    histogram_data = plot_data["plot_points"][0]

    cumulative_histogram = {}

    layout = PlotLayout()
    layout.dpi = 250

    for stat_name in histogram_data:
        plot = Plot()
        plot.setTitle(stat_name)
        if has_legend:
            plot.hasLegend(labelSize=8)

        if x_limit is not None:
            plot.setXLimits(0, x_limit)

        style_plot(plot, stat_name)

        for key, points in sorted(histogram_data[stat_name].items()):
            for size, count in itertools.izip(points["bin"], points["count"]):
                if size not in cumulative_histogram:
                    cumulative_histogram[size] = 0
                cumulative_histogram[size] += count

            line = Line()
            line.stepFunction("pre")
            line.label = str(key)
            line.xValues = points["bin"]
            line.yValues = points["count"]
            plot.add(line)

        layout.addPlot(plot)

        cumulative_plot = Plot()

        if x_limit is not None:
            cumulative_plot.setXLimits(0, x_limit)

        cumulative_plot.setTitle("Cumulative Histogram for " + stat_name)
        style_plot(cumulative_plot, stat_name)
        line = Line()
        line.stepFunction("pre")
        line.xValues = sorted(cumulative_histogram.keys())
        line.yValues = [cumulative_histogram[key] for key in line.xValues]

        cumulative_plot.add(line)
        layout.addPlot(cumulative_plot)
    layout.save(output_filename)

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
    def constructImage(self):
        layout = PlotLayout()

        plotBase10 = Plot()
        plotBase10.loglog = True

        lineBase10 = Line()
        lineBase10.marker = 'x'
        lineBase10.xValues = [1, 10, 100, 1000, 10000]
        lineBase10.yValues = [1, 25, 140, 1024, 10342]

        plotBase10.add(lineBase10)

        plotBase2 = Plot()
        plotBase2.logx = True
        plotBase2.logbase = 2

        lineBase2 = Line()
        lineBase2.marker = 'x'
        lineBase2.xValues = [1, 2, 4, 8, 16, 32, 64]
        lineBase2.yValues = [1, 2, 3, 4, 5, 6, 7]

        plotBase2.add(lineBase2)


        layout.addPlot(plotBase10)
        layout.addPlot(plotBase2)

        layout.width = 2
        layout.save(self.imageName)

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
def main():

    output_graph = sys.argv[1]

    plot = Plot()
    plot.hasLegend(location='lower right')
    plot.xLabel = 'Per-client throughput (Mbps)'  # Change this
    plot.yLabel = 'CDF'
    plot.xLimits = (0, 50)
    plot.yLimits = (0, 1)
    plot.legendLabelSize = FONT_SIZE
    plot.xTickLabelSize = FONT_SIZE - 2
    plot.yTickLabelSize = FONT_SIZE - 2
    plot.axesLabelSize = FONT_SIZE
    
    for csv_file in sys.argv[2:]:
        
        cdf_table = _make_cdf(csv_file)
        
        line = Line()
        line.xValues = [x for (x, _) in cdf_table]
        line.yValues = [y for (_, y) in cdf_table]
        line.color = colors.pop(0)
        line.lineStyle = line_styles.pop(0)
        
        # Extract the filename
        line.label = capitalize( csv_file.split('/')[-2].replace('.csv', '') )
        plot.add(line)
        
    plot.save(output_graph)

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
    def constructImage(self):
        lines = []

        for i in xrange(3):
            line = Line()
            line.xValues = xrange(5)
            line.yValues = [(i+1 / 2.0) *  pow(x, i+1) for x in line.xValues]
            line.label = "Line %d" % (i + 1)
            lines.append(line)

        plot = Plot()
        plot.add(lines[0])

        inset = Plot()
        inset.add(lines[1])
        inset.hideTickLabels()
        inset.setTitle("Inset in Yo Inset\nSo You Can Inset\nWhile You Inset")

        insideInset = Plot()
        insideInset.hideTickLabels()
        insideInset.add(lines[2])

        inset.addInset(insideInset, width=0.4, height=0.3,
                       location="upper left")

        plot.addInset(inset, width=0.4, height=0.4, location="lower right")

        plot.save(self.imageName)

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
    def constructImage(self):

        line = Line()
        line.xValues = range(5)
        line.yValues = [2,3,5,7,9]
        line.label = "A Line"

        linePlot1 = Plot()
        linePlot1.setTitle("Small Legend")
        linePlot1.add(line)
        linePlot1.hasLegend()
        linePlot1.setLegendLabelSize(10)

        linePlot2 = Plot()
        linePlot2.setTitle("Large Legend")
        linePlot2.add(line)
        linePlot2.hasLegend()
        linePlot2.setLegendLabelSize(30)

        linePlot3 = Plot()
        linePlot3.setTitle("Inherited from Layout")
        linePlot3.add(line)
        linePlot3.hasLegend()

        layout = PlotLayout()
        layout.setWidth(2)
        layout.addPlot(linePlot1)
        layout.addPlot(linePlot2)
        layout.addPlot(linePlot3)
        layout.setLegendLabelSize(15)
        layout.setPlotParameters(left=0.03, bottom=0.03, right=0.98, top=0.94)

        layout.save(self.imageName)

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
    def constructImage(self):
        line = Line()
        line.xValues = range(5)
        line.yValues = [2,3,5,7,9]
        line.label = "A Line"

        linePlot1 = Plot()
        linePlot1.title = "Small Legend"
        linePlot1.add(line)
        linePlot1.hasLegend()
        linePlot1.legendLabelSize = 10

        linePlot2 = Plot()
        linePlot2.title = "Large Legend"
        linePlot2.add(line)
        linePlot2.hasLegend()
        linePlot2.legendLabelSize = 30

        linePlot3 = Plot()
        linePlot3.title = "Inherited from Layout"
        linePlot3.add(line)
        linePlot3.hasLegend()

        layout = PlotLayout()
        layout.width = 2
        layout.addPlot(linePlot1)
        layout.addPlot(linePlot2)
        layout.addPlot(linePlot3)
        layout.legendLabelSize = 15

        layout.save(self.imageName)

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
def get_line_from_csv(filename, **attr_dict):

    xs = []
    ys = []
    
    with open(filename) as fobj:
        for line in fobj:
            line = line.strip()
            if line:
                if ',' in line:
                    (x, y) = line.split(',')
                elif '\t' in line:
                    (x, y) = line.split('\t')
                else:
                    (x, y) = line.split()
                xs += [float(x)]
                ys += [float(y)]
                
    line = Line()
    line.xValues = xs
    line.yValues = ys
    
    for (attr, value) in attr_dict.items():
        setattr(line, attr, value)
    
    return line             

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
    def constructImage(self):
        line = Line()
        line.xValues = [2, 1, 3, 4, 0]
        line.yValues = [2, 1, 3, 4, 0]

        plot = Plot()
        plot.add(line)

        plot.save(self.imageName)

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
    def constructImage(self):
        line = Line()
        line.yValues = [25, 40, 30, 23, 10, 50]
        line.xValues = range(len(line.yValues))

        plot = Plot()
        plot.add(line)
        plot.xLabel = "X Label"
        plot.yLabel = "Y Label"
        plot.yLimits = (0, 60)
        plot.save(self.imageName)

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
    def constructImage(self):
        plot = Plot()
        plot.projection = 'polar'

        r = arange(0,1,0.001)
        theta = 2*2*pi*r

        line = Line()
        line.xValues = theta
        line.yValues = r
        plot.add(line)
        plot.save(self.imageName)

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
def make_line_objects_for_stat_name(
    query_number, stat_name, stat_name_data, min_timestamps):

    lines = []

    for points_info in sorted(stat_name_data):
        lines_dict = {}
        lines_dict["query_number"] = query_number
        lines_dict["stat_name"] = stat_name

        hostname = points_info[0].split('.')[0][-3:]

        if len(points_info) == 4:
            (phase, stage, worker_id) = points_info[1:]
            lines_dict["stage"] = stage
            lines_dict["worker_id"] = worker_id
            label = "h:%s s:%s i:%d n:%s" % (
                hostname, stage, worker_id, stat_name)

        elif len(points_info) == 3:
            (phase, logger_name) = points_info[1:]
            lines_dict["logger_name"] = logger_name
            label = "h:%s l:%s n:%s" % (
                hostname, logger_name, stat_name)

        lines_dict["hostname"] = hostname
        lines_dict["phase"] = phase

        min_timestamp = min_timestamps[phase]

        def timestamp_adjuster(x):
            """
            Adjust an absolute timestamp in microseconds to time in seconds
            relative to the min timestamp
            """
            return float(x - min_timestamp) / 1000000.0

        time_series_line = Line()
        time_series_line.label = label
        time_series_line.stepFunction("pre")

        time_series_line.xValues = map(
            timestamp_adjuster, stat_name_data[points_info]["x_values"])
        time_series_line.yValues = stat_name_data[points_info]["y_values"]

        lines_dict["time_series_line"] = time_series_line
        lines_dict["cdf_line"] = Utils.getCDF(
            stat_name_data[points_info]["y_values"])
        lines_dict["cdf_line"].label = label

        lines.append(lines_dict)
    return lines

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
    def constructImage(self):
        line = Line()
        line.xValues = range(5)
        line.yValues = [2, 4, 6, 8, 10]

        linePlot = Plot()
        linePlot.add(line)
        linePlot.setXLabel("X Data")
        linePlot.setYLabel("Y Data")
        linePlot.setTitle("Data as Line")

        bar = Bar()
        bar.xValues = range(5)
        bar.yValues = [2, 4, 6, 8, 10]

        barPlot = Plot()

        barPlot.add(bar)
        barPlot.setXLabel("X Data")
        barPlot.setYLabel("Y Data")
        barPlot.setTitle("Data as Bars")

        scatter = Scatter()
        scatter.xValues = range(5)
        scatter.yValues = [2, 4, 6, 8, 10]

        scatterPlot = Plot()
        scatterPlot.add(scatter)
        scatterPlot.setXLabel("X Data")
        scatterPlot.setYLabel("Y Data")
        scatterPlot.setTitle("Data as Points")


        layout = PlotLayout()
        # Plots in the same grouping are placed together on the same line
        layout.addPlot(linePlot, grouping="topRow")
        layout.addPlot(barPlot, grouping="topRow")

        # Plots without a grouping are arranged as follows:

        # * While you can make a row of N plots, where N is the size of the plot
        # grouping with the largest size, do so.

        # * If you can't make a row of N plots, make the plots stretch across a
        # single row.

        layout.addPlot(scatterPlot)

        # Set values similar to those given in the "Configure subplots" sliders
        # in the interactive figure
        layout.setPlotParameters(hspace=0.48)
        layout.save(self.imageName)

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
    def constructImage(self):
        plot = Plot()

        line = Line()
        line.yValues = [25, 40, 30, 23, 10, 50]
        line.xValues = range(len(line.yValues))

        plot.add(line)
        plot.setXLabel("X Label")
        plot.setYLabel("Y Label")
        plot.setYLimits(0, 60)

        plot.save(self.imageName)

# 需要導入模塊: from boomslang import Line [as 別名]
# 或者: from boomslang.Line import xValues [as 別名]
    def constructImage(self):
        line1 = Line()
        line2 = Line()
        line3 = Line()

        line1.xValues = range(0,10)
        line1.yValues = [2,5,2,3,2,2,1,0,1,0]
        line2.xValues = range(0,10)
        line2.yValues = [3,1,2,3,2,1,5,3,1,7]
        line3.xValues = range(0,10)
        line3.yValues = [2,1,3,1,3,4,1,4,5,0]

        stack = StackedLines()
        stack.addLine(line1, "red")
        stack.addLine(line2, "green")
        stack.addLine(line3, "blue")

        plot = Plot()
        plot.xLimits = (0, 9)
        plot.yLimits = (0, 7)
        plot.add(stack)
        plot.save(self.imageName)