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)
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)
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)
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)
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)
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)
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.title = ("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)
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)
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)
def __init__(self, label, color):
line = Line()
line.marker = "."
line.label = label
line.color = color
self.line = line
scatter = Scatter()
scatter.marker = "x"
scatter.color = color
scatter.markerSize = 200
self.scatter = scatter
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
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
def constructImage(self):
line1 = Line()
line1.xValues = range(7)
line1.yValues = [1, 2, 4, 8, 16, 32, 64]
line1.label = "First Plot"
line1.lineStyle = "-"
line1.color = "red"
line2 = Line()
line2.xValues = range(7)
line2.yValues = [100, 90, 80, 70, 60, 50, 40]
line2.label = "Second Plot"
line2.lineStyle = "--"
line2.color = "blue"
plot = Plot()
plot.add(line1)
plot.add(line2)
plot.xLabel = "Shared X Axis"
plot.yLabel = "First Plot's Y Axis"
plot.setTwinX("Second Plot's Y Axis", 1)
plot.hasLegend()
plot.save(self.imageName)
def constructImage(self):
plot = Plot()
for i in xrange(6):
line = Line()
line.xValues = xrange(5)
line.yValues = [(i + 1) * x for x in line.xValues]
line.label = "Line %d" % (i + 1)
plot.add(line)
plot.addLineColor("red")
plot.addLineColor("blue")
plot.addLineColor("green")
plot.addMarker("")
plot.addMarker("x")
plot.hasLegend(columns=2)
plot.save(self.imageName)
def constructImage(self):
plot = Plot()
for i in xrange(24):
line = Line()
line.xValues = xrange(5)
line.yValues = [(i+1) * x for x in line.xValues]
line.label = "Line %d" % (i + 1)
plot.add(line)
plot.addLineColor("red")
plot.addLineColor("blue")
plot.addLineStyle("-")
plot.addLineStyle("dashed")
plot.addLineStyle("dotted")
plot.addMarker('none')
plot.addMarker('x')
plot.addMarker('o')
plot.hasLegend(columns=2)
plot.setLegendLabelSize(8)
plot.save(self.imageName)
def constructImage(self):
plot = Plot()
for i in xrange(24):
line = Line()
line.xValues = xrange(5)
line.yValues = [(i + 1) * x for x in line.xValues]
line.label = "Line %d" % (i + 1)
plot.add(line)
plot.addLineColor("red")
plot.addLineColor("blue")
plot.addLineStyle("-")
plot.addLineStyle("dashed")
plot.addLineStyle("dotted")
plot.addMarker('none')
plot.addMarker('x')
plot.addMarker('o')
plot.hasLegend(columns=2)
plot.setLegendLabelSize(8)
plot.save(self.imageName)
#!/usr/bin/env python
from boomslang import Line, Plot
plot = Plot()
for i in xrange(6):
line = Line()
line.xValues = xrange(5)
line.yValues = [(i+1) * x for x in line.xValues]
line.label = "Line %d" % (i + 1)
plot.add(line)
plot.addLineColor("red")
plot.addLineColor("blue")
plot.addLineStyle("-")
plot.addLineStyle("--")
plot.addLineStyle(":")
plot.hasLegend(columns=2)
plot.save("linestyles.png")
#!/usr/bin/env python
from boomslang import Line, Plot
line1 = Line()
line1.xValues = range(7)
line1.yValues = [1, 2, 4, 8, 16, 32, 64]
line1.label = "First Plot"
line1.lineStyle = "-"
line1.color = "red"
line2 = Line()
line2.xValues = range(7)
line2.yValues = [100, 90, 80, 70, 60, 50, 40]
line2.label = "Second Plot"
line2.lineStyle = "--"
line2.color = "blue"
plot = Plot()
plot.add(line1)
plot.add(line2)
plot.setXLabel("Shared X Axis")
plot.setYLabel("First Plot's Y Axis")
plot.setTwinX("Second Plot's Y Axis", 1)
plot.hasLegend()
plot.save("twinx.png")
#!/usr/bin/env python
from boomslang import Line, Plot
plot = Plot()
# Uneven error bars
line = Line()
line.xValues = range(6)
line.yValues = [25, 21, 30, 23, 10, 30]
line.yMins = [10, 18, 10, 10, 5, 20]
line.yMaxes = [30, 50, 40, 30, 20, 45]
line.label = "Asymmetric Errors"
line.color = "red"
line.xValues = range(len(line.yValues))
# Even error bars
line2 = Line()
line2.xValues = range(6)
line2.yValues = [35, 40, 45, 40, 55, 50]
line2.color = "blue"
line2.label = "Symmetric Errors"
line2.yErrors = [3, 6, 5, 3, 5, 4]
plot.add(line)
plot.add(line2)
plot.setXLabel("X Label")
plot.setYLabel("Y Label")
plot.hasLegend()
plot.save("errorbars.png")
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)
