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.setXLabel("X Label")
plot.setYLabel("Y Label")
plot.hasLegend()
plot.setXLimits(-1, 13)
plot.save(self.imageName)
def getBinBars(rows,
binKey,
quantityKey,
xLabelFormattingFunction,
xLabel,
yLabel,
xLabelRotation=0):
bins = []
countsPerBin = []
for row in rows:
bins.append(int(row[binKey]))
countsPerBin.append(int(row[quantityKey]))
bar = Bar()
bar.xValues = bins
bar.yValues = countsPerBin
if xLabelFormattingFunction is not None:
bar.xTickLabelPoints = range(len(bins))
bar.xTickLabels = map(xLabelFormattingFunction, bar.xTickLabelPoints)
if xLabelRotation > 0:
bar.setXTickLabelProperties(rotation=str(xLabelRotation))
barPlot = Plot()
barPlot.add(bar)
barPlot.setXLabel(xLabel)
barPlot.setYLabel(yLabel)
# barPlot.setXLimits(0, None)
return barPlot
def create_plot_objects_for_group(phase_name, group_name, min_timestamp,
max_timestamp, make_legend):
"""
Create and format two Boomslang plot objects: one for the time series plot,
and the other for a CDF of the y-axis values in the time series. min and
max timestamps are assumed to be adjusted with timestamp_adjuster (see
below) before being passed as arguments
"""
time_series_plot = Plot()
time_series_plot.setXLimits(
0, (max_timestamp - min_timestamp) / 1000000.0)
time_series_plot.setXLabel("Time (s)")
time_series_plot.setYLabel(group_name)
cdf_plot = Plot()
cdf_plot.setXLabel(group_name)
cdf_plot.setYLabel("CDF")
for plot in [time_series_plot, cdf_plot]:
if make_legend:
plot.hasLegend(labelSize = 8, columns=2)
plot.setTitle("Phase: %(phase_name)s, %(group_name)s" %
{"phase_name" : phase_name, "group_name" : group_name})
for color in ["red", "green", "blue", "teal", "orange", "purple",
"brown", "black"]:
plot.addLineColor(color)
for style in ["solid", "dashed", "dotted"]:
plot.addLineStyle(style)
return (time_series_plot, cdf_plot)
def constructImage(self):
plot = Plot()
bar = Bar()
bar.xValues = range(5)
bar.yValues = [2, 8, 4, 6, 5]
plot.add(bar)
plot.setXLabel("Widget ID")
plot.setYLabel("# Widgets Sold")
plot.save(self.imageName)
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)
def constructImage(self):
plot = Plot()
line = Line()
line.yValues = [25, 40, 30, 23, 10, 50]
line.xValues = range(len(line.yValues))
line.xTickLabels = ["X 1", "X 2", "X 3", "X 4", "X 5"]
line.yTickLabels = ["Y Ten", "Y Twenty", "Y Thirty", "Y Forty",
"Y Fifty", "Y Sixty"]
line.yTickLabelPoints = [10, 20, 30, 40, 50, 60]
# You can set tick label properties with a dictionary ...
line.xTickLabelProperties = {
"color" : "blue",
"weight" : "bold",
"rotation" : 45
}
line.yTickLabelProperties = {
"style" : "italic",
"alpha" : 0.5,
"color" : "red"
}
# (clearing for demonstrative purposes)
line.xTickLabelProperties.clear()
line.yTickLabelProperties.clear()
# You can also set by direct elementwise access
line.xTickLabelProperties["color"] = "blue"
line.xTickLabelProperties["weight"] = "bold"
line.xTickLabelProperties["rotation"] = "45"
line.yTickLabelProperties["style"] = "italic"
line.yTickLabelProperties["alpha"] = 0.5
line.yTickLabelProperties["color"] = "red"
plot.add(line)
plot.setTitle("Craaazy Title")
plot.setTitleProperties(style="italic", weight="bold", rotation="5",
color="orange")
plot.setXLabel("X Label")
plot.setYLabel("Y Label")
plot.setYLimits(0, 60)
plot.setPlotParameters(bottom=.15, left=0.15)
plot.save(self.imageName)
def constructImage(self):
cluster = ClusteredBars()
colors = ['red','green','blue','CornflowerBlue','LightSalmon']
yVals = [[
[1, 3, 2, 5, 4],
[2, 2, 2, 2, 2],
[1, 3, 2, 4, 3],
[0, 4, 0, 4, 0],
[5, 5, 5, 5, 5]
],[
[2, 2, 2, 2, 2],
[2, 2, 2, 2, 2],
[2, 2, 2, 2, 2],
[2, 2, 2, 2, 2],
[2, 2, 2, 2, 2]
],
[
[1, 3, 1, 3, 1],
[1, 3, 1, 3, 1],
[1, 3, 1, 3, 1],
[1, 3, 1, 3, 1],
[1, 3, 1, 3, 1],
]]
for i in xrange(3):
stack = StackedBars()
for j in xrange(5):
bar = Bar()
bar.xValues = range(5)
bar.yValues = yVals[i][j]
bar.color = colors[j]
bar.label = "Subject %d" % (j+1,)
stack.add(bar)
cluster.add(stack)
cluster.spacing = 0.5
cluster.xTickLabels = ["1", "2", "3", "4", "5"]
plot = Plot()
plot.add(cluster)
plot.hasLegend()
plot.setXLabel('Nested Cars')
plot.setYLabel('Party (lampshades)')
plot.save(self.imageName)
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.grid.color = "#ff0000"
plot.grid.style = "dotted"
plot.grid.visible = True
plot.save(self.imageName)
def constructImage(self):
plot = Plot()
line = Line()
line.xValues = xrange(100)
line.xTickLabels = ["Whoa this label is really long why is this label so long"]
line.xTickLabelPoints = [42]
line.xTickLabelProperties["rotation"] = 45
line.yValues = [math.sin(x) for x in xrange(100)]
line.yTickLabels = ["Look at this value. Pretty sweet value right?"]
line.yTickLabelPoints = [0.3]
plot.add(line)
plot.setXLabel("Value")
plot.setYLabel("sin(Value)")
plot.save(self.imageName)
def constructImage(self):
plot = Plot()
line = Line()
line.xValues = xrange(100)
line.xTickLabels = [
"Whoa this label is really long why is this label so long"
]
line.xTickLabelPoints = [42]
line.xTickLabelProperties["rotation"] = 45
line.yValues = [math.sin(x) for x in xrange(100)]
line.yTickLabels = ["Look at this value. Pretty sweet value right?"]
line.yTickLabelPoints = [0.3]
plot.add(line)
plot.setXLabel("Value")
plot.setYLabel("sin(Value)")
plot.save(self.imageName)
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.setXTickLabelSize(24)
plot.setYTickLabelSize(36)
plot.setAxesLabelSize(18)
plot.setPlotParameters(bottom=0.14)
plot.save(self.imageName)
def constructImage(self):
line = Line()
line.xValues = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
line.yValues = [0, 1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
plot = Plot()
plot.useLatexLabels()
plot.setXLabel(r"$x$")
plot.setYLabel(r"$f(x) = x^2$")
plot.setTitle(r"LaTeX is Number $\sum_{n=1}^{\infty}\frac{-e^{i\pi}}{2^n}$")
plot.add(line)
layout = PlotLayout()
layout.useLatexLabels()
layout.addPlot(plot)
layout.setAxesLabelSize(18)
layout.setPlotParameters(top=0.84)
layout.save(self.imageName)
def constructImage(self):
line = Line()
line.xValues = numpy.arange(0, 150, 0.01)
line.yValues = numpy.cos(.02 * numpy.pi * line.xValues)
plot = Plot()
plot.add(line)
plot.setXLimits(0, 150)
plot.setYLimits(-1, 1)
plot.setXLabel("X")
plot.setYLabel("cos(X)")
splitPlots = plot.split(2)
layout = PlotLayout()
layout.width = 2
layout.addPlot(plot, grouping="unsplit")
for s in splitPlots:
layout.addPlot(s, grouping="splits")
layout.save(self.imageName)
def constructImage(self):
cluster = ClusteredBars()
colors = ['red', 'green', 'blue', 'CornflowerBlue', 'LightSalmon']
yVals = [[[1, 3, 2, 5, 4], [2, 2, 2, 2, 2], [1, 3, 2, 4, 3],
[0, 4, 0, 4, 0], [5, 5, 5, 5, 5]],
[[2, 2, 2, 2, 2], [2, 2, 2, 2, 2], [2, 2, 2, 2, 2],
[2, 2, 2, 2, 2], [2, 2, 2, 2, 2]],
[
[1, 3, 1, 3, 1],
[1, 3, 1, 3, 1],
[1, 3, 1, 3, 1],
[1, 3, 1, 3, 1],
[1, 3, 1, 3, 1],
]]
for i in xrange(3):
stack = StackedBars()
for j in xrange(5):
bar = Bar()
bar.xValues = range(5)
bar.yValues = yVals[i][j]
bar.color = colors[j]
bar.label = "Subject %d" % (j + 1, )
stack.add(bar)
cluster.add(stack)
cluster.spacing = 0.5
cluster.xTickLabels = ["1", "2", "3", "4", "5"]
plot = Plot()
plot.add(cluster)
plot.hasLegend()
plot.setXLabel('Nested Cars')
plot.setYLabel('Party (lampshades)')
plot.save(self.imageName)
def create_plot_objects_for_group(phase_name, group_name, min_timestamp,
max_timestamp, make_legend):
"""
Create and format two Boomslang plot objects: one for the time series plot,
and the other for a CDF of the y-axis values in the time series. min and
max timestamps are assumed to be adjusted with timestamp_adjuster (see
below) before being passed as arguments
"""
time_series_plot = Plot()
time_series_plot.setXLimits(0, (max_timestamp - min_timestamp) / 1000000.0)
time_series_plot.setXLabel("Time (s)")
time_series_plot.setYLabel(group_name)
cdf_plot = Plot()
cdf_plot.setXLabel(group_name)
cdf_plot.setYLabel("CDF")
for plot in [time_series_plot, cdf_plot]:
if make_legend:
plot.hasLegend(labelSize=8, columns=2)
plot.setTitle("Phase: %(phase_name)s, %(group_name)s" % {
"phase_name": phase_name,
"group_name": group_name
})
for color in [
"red", "green", "blue", "teal", "orange", "purple", "brown",
"black"
]:
plot.addLineColor(color)
for style in ["solid", "dashed", "dotted"]:
plot.addLineStyle(style)
return (time_series_plot, cdf_plot)
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.setXLabel("Shared X Axis")
plot.setYLabel("First Plot's Y Axis")
plot.setTwinX("Second Plot's Y Axis", 1)
plot.hasLegend()
plot.save(self.imageName)
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)
def plotExperiments(script_arguments_file):
script_arguments_fp = open(script_arguments_file, "r")
script_arguments = json.load(script_arguments_fp)
script_arguments_fp.close()
disk = script_arguments["disk"]
sort_strategies = script_arguments["sort_strategies"]
max_key_lengths = map(int, script_arguments["max_key_lengths"])
max_value_lengths = map(int, script_arguments["max_value_lengths"])
pareto_as = map(float, script_arguments["pareto_as"])
pareto_bs = map(int, script_arguments["pareto_bs"])
byte_counts = map(int, script_arguments["byte_counts"])
timeout = script_arguments["timeout"]
experiments = [(sort_strategy, max_key_length, max_value_length, pareto_a,
pareto_b, byte_count) for sort_strategy in sort_strategies
for max_key_length in max_key_lengths
for max_value_length in max_value_lengths
for pareto_a in pareto_as for pareto_b in pareto_bs
for byte_count in byte_counts]
# Open each file and store information about the experiment
file_id = 0
experiment_outcomes = {}
for experiment in experiments:
filename = os.path.join(disk, "stats_%d.json" % file_id)
sort_time = None
scratch_size = None
if os.path.exists(filename):
fp = open(filename, "r")
try:
stats_json = json.load(fp)
# time might not be present if the run timed out
if "time" in stats_json:
# sort time in seconds
sort_time = stats_json["time"] / 1000000.0
# scratch size in megabytes
scratch_size = stats_json["scratch_size"] / 1000000.0
except ValueError:
# If the JSON somehow doesn't parse, just skip this file
pass
experiment_outcomes[experiment] = (sort_time, scratch_size)
file_id += 1
# Specify colors manually so we can sync up a line to its scatter
colors = ["red", "green", "blue", "teal", "orange"]
if len(sort_strategies) > len(colors):
print >> sys.stderr, "Only %d colors but %d lines" % (
len(colors), len(sort_strategies))
sys.exit(1)
# Plot sort time vs scratch size
plot = Plot()
plot.setXLabel("Scratch Size (MB)")
plot.setYLabel("Sort Time (s)")
plot.hasLegend(labelSize=8, columns=3)
plot.setTitle("Sort Time vs Scratch Size")
lines = {}
for (sort_strategy, color) in zip(sort_strategies, colors):
line = LineAndScatter(sort_strategy, color)
lines[sort_strategy] = line
for experiment, (sort_time, scratch_size) in \
experiment_outcomes.iteritems():
# Mark this experiment on the line corresponding to its sort strategy
line = lines[experiment[0]]
if scratch_size is not None:
line.add_point(scratch_size, sort_time)
map(lambda l: l.add_to_plot(plot), lines.values())
layout = PlotLayout()
layout.addPlot(plot)
output_file = os.path.join(disk, "SortTimeVsScratchSize.pdf")
layout.save(output_file)
# Plot Sort time vs Scratch Size of a particular strategy:
# First sort the experiments by sort strategy
strategy_outcomes = {}
for experiment in experiments:
sort_strategy = experiment[0]
parameters = experiment[1:]
if parameters not in strategy_outcomes:
strategy_outcomes[parameters] = {}
strategy_outcomes[parameters][sort_strategy] = \
experiment_outcomes[experiment]
# Create one plot per strategy, with that strategy's scratch size
# on the x-axis
layout = PlotLayout()
for major_sort_strategy in sort_strategies:
# Set up plot boilerplate
plot = Plot()
plot.setXLabel("Scratch Size of %s (MB)" % (major_sort_strategy))
plot.setYLabel("Sort Time (s)")
plot.hasLegend(labelSize=8, columns=3)
plot.setTitle("Sort Time vs Scratch Size of %s" %
(major_sort_strategy))
lines = {}
for (sort_strategy, color) in zip(sort_strategies, colors):
line = LineAndScatter(sort_strategy, color)
lines[sort_strategy] = line
# For each configuration, plot the sort times on the y axis, and the
# scratch time for the major_sort_strategy on the x-axis
for outcome_by_strategy in strategy_outcomes.values():
scratch_size = outcome_by_strategy[major_sort_strategy][1]
if scratch_size is not None:
# Plot the sort time of each strategy using this scratch
# As the x-axis value.
for sort_strategy in sort_strategies:
sort_time = outcome_by_strategy[sort_strategy][0]
lines[sort_strategy].add_point(scratch_size, sort_time)
map(lambda l: l.add_to_plot(plot), lines.values())
layout.addPlot(plot)
output_file = os.path.join(disk, "SortTimeVsScratchSizeByStrategy.pdf")
layout.save(output_file)
# Plot individual parameter graphs using median parameters
median_max_key_length = median(max_key_lengths)
median_max_value_length = median(max_value_lengths)
median_pareto_a = median(pareto_as)
median_pareto_b = median(pareto_bs)
median_byte_count = median(byte_counts)
for (parameter_name, x_label, parameter_values, fixed_parameters) in [
("MaxKeyLength", "Max Key Length (bytes)", max_key_lengths,
(None, median_max_value_length, median_pareto_a, median_pareto_b,
median_byte_count)),
("MaxValueLength", "Max Value Length (bytes)", max_value_lengths,
(median_max_key_length, None, median_pareto_a, median_pareto_b,
median_byte_count)),
("ParetoA", "Pareto A", pareto_as,
(median_max_key_length, median_max_value_length, None,
median_pareto_b, median_byte_count)),
("ParetoB", "Pareto B (bytes)", pareto_bs,
(median_max_key_length, median_max_value_length, median_pareto_a,
None, median_byte_count)),
("FileSize", "File Size (bytes)", byte_counts,
(median_max_key_length, median_max_value_length, median_pareto_a,
median_pareto_b, None))
]:
time_plot = Plot()
size_plot = Plot()
for (plot, label, unit) in [(time_plot, "Sort Time", "s"),
(size_plot, "Scratch Size", "MB")]:
plot.setXLabel(x_label)
plot.setYLabel("%s (%s)" % (label, unit))
plot.hasLegend(labelSize=8, columns=3)
plot.setTitle("%s vs %s" % (label, parameter_name))
for (sort_strategy, color) in zip(sort_strategies, colors):
# Each sort strategy has its own line on each of the two plots
time_line = LineAndScatter(sort_strategy, color)
size_line = LineAndScatter(sort_strategy, color)
# Compute the set of parameters corresponding to this experiment.
for parameter in parameter_values:
# Apply this parameter to the None value in the tuple of
# fixed parameters.
parameters = [sort_strategy]
for fixed_parameter in fixed_parameters:
if fixed_parameter is None:
parameters.append(parameter)
else:
parameters.append(fixed_parameter)
# Plot sort time and scratch size for this experiment
(sort_time,
scratch_size) = experiment_outcomes[tuple(parameters)]
time_line.add_point(parameter, sort_time)
size_line.add_point(parameter, scratch_size)
# Add lines to plots
time_line.add_to_plot(time_plot)
size_line.add_to_plot(size_plot)
# Save the plot as a pdf
layout = PlotLayout()
layout.addPlot(time_plot)
layout.addPlot(size_plot)
output_file = os.path.join(disk, "%s.pdf" % (parameter_name))
layout.save(output_file)
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 plot_timeline_for_phase(log_directory, job, phase, phase_data):
min_timestamp = phase_data["min_timestamp"]
max_timestamp = phase_data["max_timestamp"]
description = Description(os.path.join(log_directory, job, "description"))
stage_ordering = description.getStageOrdering(phase)
duration_lists = {}
for stage in stage_ordering:
duration_lists[stage] = []
for key in phase_data:
if key in ["min_timestamp", "max_timestamp"]:
continue
hostname, stage, worker_id = key
worker_duration_info = Duration(
hostname.split('.')[0], stage, worker_id,
(phase_data[key][0] - min_timestamp) / 1000000.0,
(phase_data[key][1] - min_timestamp) / 1000000.0)
duration_lists[stage].append(worker_duration_info)
def sort_function(x):
return (x.hostname, x.worker_id, x.start_time, x.stop_time)
layout = PlotLayout()
for stage in stage_ordering:
duration_list = duration_lists[stage]
duration_list.sort(key=sort_function)
bars = {}
# Set up a "padding" bar that will appear to move bars up so that they
# start when the worker starts
start_bar = Bar()
start_bar.linewidth = 0
start_bar.color = "white"
for i, duration in enumerate(duration_list):
if duration.hostname not in bars:
bars[duration.hostname] = Bar()
bars[duration.hostname].yValues.append(
duration.stop_time - duration.start_time)
start_bar.yValues.append(duration.start_time)
# Make sure that all bars have the same number of y-axis values,
# give them x-axis values and set their colors
start_bar.xValues = range(len(start_bar.yValues))
start_bar.xTickLabelProperties = {
"rotation" : 90
}
bar_colors = ["red", "blue", "green", "orange", "gray", "pink",
"purple", "black"]
offset = 0
for i, (hostname, bar) in enumerate(bars.items()):
# Pad y axis with zeroes so that bars can be laid out next to
# each other with a StackedBars
num_y_values = len(bar.yValues)
bar.yValues = (([0] * offset) + bar.yValues +
([0] *
(len(duration_list) - (num_y_values + offset))))
# Put the label for this hostname roughly in the middle of its bar
# cluster
start_bar.xTickLabels.append(hostname)
# Subtracting 0.5 to account for half the width of the bar
start_bar.xTickLabelPoints.append(offset + (num_y_values / 2.0)
- 0.5)
offset += num_y_values
bar.xValues = range(len(bar.yValues))
bar.color = bar_colors[i % len(bar_colors)]
bar.label = hostname
stacked_bars = StackedBars()
stacked_bars.add(start_bar)
for hostname in sorted(bars.keys()):
stacked_bars.add(bars[hostname])
plot = Plot()
plot.setYLimits(0, ((max_timestamp - min_timestamp) / 1000000.0) * 1.05)
plot.setXLabel("Worker")
plot.setYLabel("Time (s)")
plot.setTitle(stage)
plot.add(stacked_bars)
layout.addPlot(plot)
return layout
#!/usr/bin/env python
from boomslang import Bar, Line, Scatter, Plot, PlotLayout
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)
#!/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 Bar, Plot
plot = Plot()
bar = Bar()
bar.xValues = range(5)
bar.yValues = [2, 8, 4, 6, 5]
plot.add(bar)
plot.setXLabel("Widget ID")
plot.setYLabel("# Widgets Sold")
plot.save("bar.png")
#!/usr/bin/env python
from boomslang import Label, Line, Plot
import numpy
line = Line()
line.xValues = numpy.arange(0.0, 5.0, 0.01)
line.yValues = numpy.cos(2 * numpy.pi * line.xValues)
maxLabel = Label(2, 1, "Maximum!")
maxLabel.setTextOffset(0.5, 0.5)
maxLabel.hasArrow()
minLabel = Label(1.5, -1, "Minimum!")
minLabel.setTextPosition(1, -2)
minLabel.hasArrow()
randomLabel = Label(2, -1.7, "A Point!")
randomLabel.setTextOffset(0, 0.2)
randomLabel.marker = 'o'
plot = Plot()
plot.add(line)
plot.add(minLabel)
plot.add(maxLabel)
plot.add(randomLabel)
plot.setYLimits(-3, 3)
plot.setXLabel("X")
plot.setYLabel("cos(x)")
plot.save("label.png")
def plot_timeline_for_phase(log_directory, job, phase, phase_data):
min_timestamp = phase_data["min_timestamp"]
max_timestamp = phase_data["max_timestamp"]
description = Description(os.path.join(log_directory, job, "description"))
stage_ordering = description.getStageOrdering(phase)
duration_lists = {}
for stage in stage_ordering:
duration_lists[stage] = []
for key in phase_data:
if key in ["min_timestamp", "max_timestamp"]:
continue
hostname, stage, worker_id = key
worker_duration_info = Duration(
hostname.split('.')[0], stage, worker_id,
(phase_data[key][0] - min_timestamp) / 1000000.0,
(phase_data[key][1] - min_timestamp) / 1000000.0)
duration_lists[stage].append(worker_duration_info)
def sort_function(x):
return (x.hostname, x.worker_id, x.start_time, x.stop_time)
layout = PlotLayout()
for stage in stage_ordering:
duration_list = duration_lists[stage]
duration_list.sort(key=sort_function)
bars = {}
# Set up a "padding" bar that will appear to move bars up so that they
# start when the worker starts
start_bar = Bar()
start_bar.linewidth = 0
start_bar.color = "white"
for i, duration in enumerate(duration_list):
if duration.hostname not in bars:
bars[duration.hostname] = Bar()
bars[duration.hostname].yValues.append(duration.stop_time -
duration.start_time)
start_bar.yValues.append(duration.start_time)
# Make sure that all bars have the same number of y-axis values,
# give them x-axis values and set their colors
start_bar.xValues = range(len(start_bar.yValues))
start_bar.xTickLabelProperties = {"rotation": 90}
bar_colors = [
"red", "blue", "green", "orange", "gray", "pink", "purple", "black"
]
offset = 0
for i, (hostname, bar) in enumerate(bars.items()):
# Pad y axis with zeroes so that bars can be laid out next to
# each other with a StackedBars
num_y_values = len(bar.yValues)
bar.yValues = (([0] * offset) + bar.yValues +
([0] * (len(duration_list) -
(num_y_values + offset))))
# Put the label for this hostname roughly in the middle of its bar
# cluster
start_bar.xTickLabels.append(hostname)
# Subtracting 0.5 to account for half the width of the bar
start_bar.xTickLabelPoints.append(offset + (num_y_values / 2.0) -
0.5)
offset += num_y_values
bar.xValues = range(len(bar.yValues))
bar.color = bar_colors[i % len(bar_colors)]
bar.label = hostname
stacked_bars = StackedBars()
stacked_bars.add(start_bar)
for hostname in sorted(bars.keys()):
stacked_bars.add(bars[hostname])
plot = Plot()
plot.setYLimits(0,
((max_timestamp - min_timestamp) / 1000000.0) * 1.05)
plot.setXLabel("Worker")
plot.setYLabel("Time (s)")
plot.setTitle(stage)
plot.add(stacked_bars)
layout.addPlot(plot)
return layout
bar4 = Bar()
bar4.xValues = threadsData["4"][0]
bar4.yValues = threadsData["4"][1]
bar4.color = "orange"
bar4.label = "4 Threads"
bar8 = Bar()
bar8.xValues = threadsData["8"][0]
bar8.yValues = threadsData["8"][1]
bar8.color = "yellow"
bar8.label = "8 Threads"
clusteredBars = ClusteredBars()
clusteredBars.add(bar1)
clusteredBars.add(bar2)
clusteredBars.add(bar3)
clusteredBars.add(bar4)
clusteredBars.add(bar8)
clusteredBars.spacing = 0.1
clusteredBars.xTickLabels = ["1", "21", "41", "61", "81", "101"]
plot = Plot()
plot.add(clusteredBars)
plot.setXLabel("K")
plot.setYLabel("WpS")
plot.hasLegend()
plot.save("omp_for.png")
#!/usr/bin/env python
from boomslang import Line, Plot, PlotLayout
line = Line()
line.xValues = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
line.yValues = [0, 1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
plot = Plot()
plot.useLatexLabels()
plot.setXLabel(r"$x$")
plot.setYLabel(r"$f(x) = x^2$")
plot.setTitle(r"LaTeX is Number $\sum_{n=1}^{\infty}\frac{-e^{i\pi}}{2^n}$")
plot.add(line)
layout = PlotLayout()
layout.addPlot(plot)
layout.setAxesLabelSize(18)
layout.setPlotParameters(top=0.84)
layout.save("latex.png")
y = (float(row1[' OptWpS']) + float(row2[' OptWpS']) + float(row3[' OptWpS'])) / 3.0
dataY.append(y)
y = (float(row1[' Opt2WpS']) + float(row2[' Opt2WpS']) + float(row3[' Opt2WpS'])) / 3.0
dataY.append(y)
except:
pass
bars = []
labels = ['Reference', 'OMP - For', 'OMP - Tasks', 'Comp-Opt', 'Manual-Opt']
colors = ['yellow', 'red', 'orange', 'blue', 'green']
index = 0
for y in dataY:
bar = Bar()
bar.xValues = [index]
bar.yValues = [y]
bar.color = colors[index]
bar.label = labels[index]
index += 1
bars.append(bar)
plot = Plot()
for bar in bars:
plot.add(bar)
plot.setXLabel("Versions")
plot.setYLabel("WpS")
plot.hasLegend()
plot.save("seq.png")
