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):
scatter = Scatter()
scatter.label="Hooray dots with vlines!"
scatter.xValues = [
7, 6, 3, 5, 7, 6, 1, 1, 6, 5, 8, 6, 7, 8, 0, 2, 9, 3, 9,
5, 4, 5, 0, 0, 2, 3, 1, 4, 1, 3, 3, 8, 1, 5, 2, 6, 0, 3,
5, 1, 4, 9, 5, 1, 9, 9, 9, 7, 6, 5, 8, 6, 0, 2, 6, 9, 2,
5, 6, 9, 7, 8, 7, 6, 5, 9, 9, 2, 4, 9, 0, 1, 1, 1, 6, 4,
5, 8, 9, 1, 2, 1, 4, 5, 9, 7, 4, 9, 2, 9, 2, 5, 2, 2, 0,
2, 1, 9, 3, 6]
scatter.yValues = [
2, 5, 9, 5, 9, 3, 6, 1, 6, 0, 0, 6, 2, 5, 3, 9, 2, 7, 6,
2, 3, 1, 9, 9, 5, 2, 9, 0, 2, 3, 0, 2, 5, 5, 8, 4, 1, 9,
8, 6, 1, 6, 9, 2, 4, 9, 2, 8, 1, 1, 2, 1, 0, 6, 3, 4, 2,
5, 6, 8, 6, 9, 0, 6, 8, 6, 8, 1, 6, 2, 2, 3, 6, 2, 2, 2,
0, 2, 4, 6, 8, 5, 1, 4, 2, 3, 5, 3, 1, 0, 6, 0, 1, 6, 8,
9, 3, 9, 3, 7]
vline1 = VLine()
vline1.xValues = [2,8]
vline1.color = 'CornflowerBlue'
vline2 = VLine()
vline2.xValues = [1,9]
vline2.color = 'GoldenRod'
plot = Plot()
plot.hasLegend()
plot.add(scatter)
plot.add(vline1)
plot.add(vline2)
plot.save(self.imageName)
def constructImage(self):
scatter = Scatter()
scatter.label = "Hooray dots with vlines!"
scatter.xValues = [
7, 6, 3, 5, 7, 6, 1, 1, 6, 5, 8, 6, 7, 8, 0, 2, 9, 3, 9, 5, 4, 5,
0, 0, 2, 3, 1, 4, 1, 3, 3, 8, 1, 5, 2, 6, 0, 3, 5, 1, 4, 9, 5, 1,
9, 9, 9, 7, 6, 5, 8, 6, 0, 2, 6, 9, 2, 5, 6, 9, 7, 8, 7, 6, 5, 9,
9, 2, 4, 9, 0, 1, 1, 1, 6, 4, 5, 8, 9, 1, 2, 1, 4, 5, 9, 7, 4, 9,
2, 9, 2, 5, 2, 2, 0, 2, 1, 9, 3, 6
]
scatter.yValues = [
2, 5, 9, 5, 9, 3, 6, 1, 6, 0, 0, 6, 2, 5, 3, 9, 2, 7, 6, 2, 3, 1,
9, 9, 5, 2, 9, 0, 2, 3, 0, 2, 5, 5, 8, 4, 1, 9, 8, 6, 1, 6, 9, 2,
4, 9, 2, 8, 1, 1, 2, 1, 0, 6, 3, 4, 2, 5, 6, 8, 6, 9, 0, 6, 8, 6,
8, 1, 6, 2, 2, 3, 6, 2, 2, 2, 0, 2, 4, 6, 8, 5, 1, 4, 2, 3, 5, 3,
1, 0, 6, 0, 1, 6, 8, 9, 3, 9, 3, 7
]
vline1 = VLine()
vline1.xValues = [2, 8]
vline1.color = 'CornflowerBlue'
vline2 = VLine()
vline2.xValues = [1, 9]
vline2.color = 'GoldenRod'
plot = Plot()
plot.hasLegend()
plot.add(scatter)
plot.add(vline1)
plot.add(vline2)
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 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 constructImage(self):
bar1 = Bar()
bar1.xValues = range(5)
bar1.yValues = [1, 2, 1, 2, 3]
bar1.color = "red"
bar1.label = "Red Cluster"
bar2 = Bar()
bar2.xValues = range(5)
bar2.yValues = [2, 2, 3, 3, 4]
bar2.color = "blue"
bar2.label = "Blue Cluster"
bar3 = Bar()
bar3.xValues = range(5)
bar3.yValues = [3, 5, 4, 5, 3]
bar3.color = "green"
bar3.label = "Green Cluster"
stackedBars = StackedBars()
stackedBars.add(bar1)
stackedBars.add(bar2)
stackedBars.add(bar3)
stackedBars.xTickLabels = ["A", "B", "C", "D", "E"]
plot = Plot()
plot.add(stackedBars)
plot.setYLimits(0, 15)
plot.hasLegend()
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):
bar1 = Bar()
bar1.xValues = range(5)
bar1.yValues = [1, 2, 1, 2, 3]
bar1.color = "red"
bar1.label = "Red Cluster"
bar2 = Bar()
bar2.xValues = range(5)
bar2.yValues = [2, 2, 3, 3, 4]
bar2.color = "blue"
bar2.label = "Blue Cluster"
bar3 = Bar()
bar3.xValues = range(5)
bar3.yValues = [3, 5, 4, 5, 3]
bar3.color = "green"
bar3.label = "Green Cluster"
stackedBars = StackedBars()
stackedBars.add(bar1)
stackedBars.add(bar2)
stackedBars.add(bar3)
stackedBars.xTickLabels = ["A", "B", "C", "D", "E"]
plot = Plot()
plot.add(stackedBars)
plot.yLimits = (0, 15)
plot.hasLegend()
plot.save(self.imageName)
def constructImage(self):
bar1 = Bar()
bar1.xValues = range(5)
bar1.yValues = [2, 4, 6, 8, 10]
bar1.color = "red"
bar1.label = "Red Cluster"
bar2 = Bar()
bar2.xValues = range(5)
bar2.yValues = [3, 12, 4, 8, 14]
bar2.color = "blue"
bar2.label = "Blue Cluster"
bar3 = Bar()
bar3.xValues = range(5)
bar3.yValues = [1, 6, 9, 13, 20]
bar3.color = "green"
bar3.label = "Green Cluster"
clusteredBars = ClusteredBars()
clusteredBars.add(bar1)
clusteredBars.add(bar2)
clusteredBars.add(bar3)
clusteredBars.spacing = 0.5
clusteredBars.xTickLabels = ["A", "B", "C", "D", "E"]
plot = Plot()
plot.add(clusteredBars)
plot.hasLegend()
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 latency(output_graph_filename, csv_file_dir_list):
"""
Plots three graphs side-by-side. First, redis performance; second, pkt-in
latency; third, pkt-out latency.
"""
layout = PlotLayout()
redis_plot = Plot()
pkt_in_plot = Plot()
flow_mod_plot = Plot()
redis_plot.yLabel = 'CDF'
flow_mod_plot.hasLegend(location='lower right')
flow_mod_plot.legendLabelSize = 12
redis_plot.xLabel = '(a) Query completion time (ms)'
pkt_in_plot.xLabel = '(b) Switch processing time for ingress (ms)'
flow_mod_plot.xLabel = '(c) Switch processing time for egress (ms)'
for csv_dir in csv_file_dir_list:
color = colors.pop(0)
line_style = line_styles.pop(0)
line_label = csv_dir.split('/')[-2]
attr_dict = {'color': color, 'label': capitalize(line_label),
'yLimits': (0, 1), 'lineStyle': line_style}
redis_line = get_line_from_csv(os.path.join(csv_dir, 'async_redis_latency.csv'),
xLimits=(0,400), **attr_dict)
pkt_in_line = get_line_from_csv(os.path.join(csv_dir, 'pkt_in_durations.csv'),
xLimits=(0,140), **attr_dict)
flow_mod_line = get_line_from_csv(os.path.join(csv_dir, 'flow_mod_durations.csv'),
xLimits=(0,140), **attr_dict)
redis_plot.add(redis_line)
pkt_in_plot.add(pkt_in_line)
flow_mod_plot.add(flow_mod_line)
layout.addPlot(redis_plot)
layout.addPlot(pkt_in_plot)
layout.addPlot(flow_mod_plot)
layout.width = 3
layout.setPlotDimensions(4.5,4.5*0.618)
layout.save('data/graphs/' + output_graph_filename + '.pdf')
print 'Done.'
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)
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 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 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):
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):
scatter = Scatter()
scatter.label="Hooray dots!"
scatter.xValues = [
7, 6, 3, 5, 7, 6, 1, 1, 6, 5, 8, 6, 7, 8, 0, 2, 9, 3, 9,
5, 4, 5, 0, 0, 2, 3, 1, 4, 1, 3, 3, 8, 1, 5, 2, 6, 0, 3,
5, 1, 4, 9, 5, 1, 9, 9, 9, 7, 6, 5, 8, 6, 0, 2, 6, 9, 2,
5, 6, 9, 7, 8, 7, 6, 5, 9, 9, 2, 4, 9, 0, 1, 1, 1, 6, 4,
5, 8, 9, 1, 2, 1, 4, 5, 9, 7, 4, 9, 2, 9, 2, 5, 2, 2, 0,
2, 1, 9, 3, 6]
scatter.yValues = [
2, 5, 9, 5, 9, 3, 6, 1, 6, 0, 0, 6, 2, 5, 3, 9, 2, 7, 6,
2, 3, 1, 9, 9, 5, 2, 9, 0, 2, 3, 0, 2, 5, 5, 8, 4, 1, 9,
8, 6, 1, 6, 9, 2, 4, 9, 2, 8, 1, 1, 2, 1, 0, 6, 3, 4, 2,
5, 6, 8, 6, 9, 0, 6, 8, 6, 8, 1, 6, 2, 2, 3, 6, 2, 2, 2,
0, 2, 4, 6, 8, 5, 1, 4, 2, 3, 5, 3, 1, 0, 6, 0, 1, 6, 8,
9, 3, 9, 3, 7]
plot = Plot()
plot.hasLegend()
plot.add(scatter)
plot.save(self.imageName)
#!/usr/bin/env python
import random
from boomslang import Scatter, Plot
scatter = Scatter()
scatter.label="Hooray dots!"
for i in range(100):
scatter.xValues.append(random.uniform(0, 10))
scatter.yValues.append(random.uniform(0, 10))
plot = Plot()
plot.hasLegend()
plot.add(scatter)
plot.save("scatter.png")
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)
def constructImage(self):
bnw = BoxAndWhisker()
bnw.label="Whiskers"
sequences = [
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[3, 8, 9, 5, 6, 8, 5, 9, 4, 2, 2, 5, 9, 8, 6, 2, 5, 2, 6, 9, 5, 5,
6, 4, 9, 5, 3, 6, 6, 8, 9, 2, 9, 1, 4, 9, 2, 5, 7, 7, 8, 2, 3, 7,
2, 1, 8, 3, 9, 9, 6, 7, 5, 2, 1, 9, 9, 5, 4, 5, 3, 9, 4, 3, 5, 2,
6, 8, 7, 1, 1, 9, 4, 9, 2, 8, 5, 9, 9, 9, 4, 9, 4, 8, 1, 2, 8, 6,
6, 9, 7, 9, 3, 5, 4, 7, 7, 9, 5, 4],
[14, 9, 5, 1, 7, 14, 6, 5, 3, 4, 19, 5, 4, 13, 14, 10, 1, 7, 15, 5,
2, 1, 14, 10, 15, 2, 1, 2, 17, 15, 15, 5, 15, 7, 3, 8, 11, 17, 4,
11, 14, 12, 4, 1, 19, 3, 2, 2, 11, 11, 4, 11, 10, 16, 3, 11, 5,
12, 6, 17, 13, 4, 12, 1, 2, 9, 11, 19, 4, 16, 10, 6, 8, 18, 9, 12,
14, 14, 16, 16, 13, 13, 12, 19, 2, 4, 12, 8, 10, 4, 13, 16, 4, 9,
12, 17, 11, 18, 5, 14],
[23, 7, 14, 5, 10, 15, 14, 17, 27, 16, 3, 7, 10, 21, 8, 17, 20, 24,
19, 9, 20, 14, 1, 8, 10, 26, 28, 3, 13, 2, 7, 1, 18, 24, 25, 27,
2, 14, 27, 10, 22, 28, 12, 1, 14, 4, 13, 10, 14, 26, 21, 13, 4, 5,
1, 16, 15, 9, 19, 24, 29, 4, 27, 19, 17, 1, 21, 23, 28, 28, 3, 28,
21, 22, 1, 14, 28, 28, 2, 16, 24, 21, 2, 27, 5, 9, 14, 20, 7, 20,
16, 13, 11, 17, 27, 22, 19, 28, 6, 25],
[3, 36, 4, 3, 14, 13, 14, 36, 19, 24, 38, 32, 26, 14, 25, 25, 16,
14, 19, 10, 5, 15, 37, 10, 4, 20, 6, 29, 22, 20, 14, 10, 17, 37,
26, 4, 13, 32, 18, 27, 7, 35, 20, 2, 2, 11, 18, 17, 18, 8, 36, 22,
39, 12, 6, 2, 21, 1, 33, 3, 30, 25, 1, 6, 17, 38, 22, 20, 20, 21,
34, 19, 14, 13, 10, 30, 39, 8, 30, 25, 37, 6, 33, 10, 32, 17, 6,
32, 5, 34, 27, 21, 29, 15, 3, 30, 15, 28, 15, 37],
[43, 4, 5, 29, 17, 10, 7, 31, 12, 9, 33, 42, 6, 43, 25, 32, 9, 4,
42, 25, 37, 45, 23, 6, 46, 1, 49, 8, 39, 34, 31, 14, 42, 49, 37,
40, 6, 37, 27, 36, 4, 45, 30, 14, 19, 38, 28, 43, 14, 24, 36, 43,
18, 36, 36, 12, 31, 44, 43, 21, 42, 3, 2, 13, 37, 47, 9, 12, 35,
46, 45, 14, 24, 20, 42, 3, 9, 8, 46, 32, 11, 24, 36, 47, 11, 39,
31, 6, 34, 48, 45, 38, 27, 42, 5, 30, 19, 20, 18, 9],
[22, 57, 14, 54, 52, 54, 2, 47, 5, 9, 47, 55, 27, 41, 6, 23, 58,
23, 28, 17, 16, 12, 6, 47, 12, 36, 28, 15, 49, 42, 6, 23, 6, 34,
31, 36, 11, 38, 31, 42, 30, 18, 30, 40, 12, 16, 52, 23, 47, 10,
19, 15, 28, 20, 18, 35, 21, 29, 25, 41, 15, 34, 2, 11, 58, 15, 22,
17, 16, 49, 43, 30, 1, 30, 33, 46, 25, 21, 20, 42, 42, 44, 21, 3,
41, 44, 52, 52, 8, 50, 41, 3, 12, 19, 53, 47, 26, 2, 49, 14],
[53, 9, 51, 39, 36, 61, 61, 20, 35, 4, 43, 18, 46, 61, 8, 51, 26,
5, 8, 2, 49, 33, 35, 22, 5, 59, 65, 16, 44, 60, 43, 4, 54, 48, 1,
48, 43, 28, 60, 49, 39, 39, 37, 57, 32, 68, 8, 51, 38, 25, 1, 28,
16, 60, 2, 42, 58, 8, 49, 59, 59, 64, 63, 44, 26, 20, 18, 52, 64,
58, 35, 53, 30, 69, 6, 58, 5, 15, 20, 43, 61, 19, 57, 45, 51, 23,
67, 55, 21, 33, 30, 1, 41, 35, 61, 24, 42, 24, 18, 57],
[12, 29, 23, 7, 24, 26, 65, 38, 73, 11, 72, 23, 68, 28, 2, 52, 33,
50, 51, 29, 24, 18, 24, 23, 63, 65, 71, 30, 27, 19, 11, 24, 55,
64, 51, 64, 21, 15, 2, 39, 16, 59, 31, 44, 25, 46, 33, 20, 53, 24,
45, 64, 10, 67, 69, 29, 12, 59, 27, 41, 77, 61, 8, 24, 15, 66, 71,
75, 65, 56, 58, 63, 33, 63, 17, 1, 41, 17, 7, 38, 65, 44, 76, 21,
38, 46, 38, 15, 52, 69, 69, 50, 32, 46, 11, 59, 26, 14, 68, 57],
[17, 37, 8, 75, 88, 15, 4, 57, 12, 68, 37, 54, 75, 39, 39, 36, 66,
75, 46, 80, 14, 54, 83, 2, 28, 13, 66, 51, 84, 63, 66, 83, 66, 76,
48, 61, 46, 53, 36, 12, 16, 68, 3, 21, 38, 18, 75, 34, 2, 17, 25,
33, 16, 16, 59, 47, 16, 75, 60, 73, 44, 61, 9, 43, 18, 38, 67, 67,
89, 43, 78, 89, 37, 22, 33, 77, 79, 71, 45, 71, 49, 80, 83, 53,
62, 29, 88, 84, 71, 14, 69, 21, 75, 56, 55, 79, 31, 75, 30, 42]
]
xSequence = []
for i in range(10):
xSequence.append(sequences[i])
bnw.xSequence = xSequence
plot = Plot()
plot.hasLegend()
plot.add(bnw)
plot.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)
scatter3 = Scatter()
scatter3.xValues = x
scatter3.yValues = surf
scatter3.label = "Original Surface"
scatter3.markerSize = 1
scatter3.color = "blue"
scatterPlot = Plot()
scatterPlot.add(scatter1)
scatterPlot.add(scatter2)
scatterPlot.xLabel = "Distance Along Cross Section"
scatterPlot.yLabel = "Surface Height"
scatterPlot.setTwinX("1st Derivative", 1)
scatterPlot.title = "Surface (filtered)"
scatterPlot.hasLegend()
layout = PlotLayout()
layout.addPlot(scatterPlot)
layout.plot()
layout.save("profile1_filtered.png")
# plot the filtered surface with the original surface
scatter1 = Scatter()
scatter1.xValues = x
scatter1.yValues = surfFiltered
scatter1.markerSize = 1
scatter1.label = "Filtered Surface"
scatter1.color = "black"
scatter2 = Scatter()
#!/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")
def constructImage(self):
bnw = BoxAndWhisker()
bnw.label = "Whiskers"
sequences = [[
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
3, 8, 9, 5, 6, 8, 5, 9, 4, 2, 2, 5, 9, 8, 6, 2, 5, 2,
6, 9, 5, 5, 6, 4, 9, 5, 3, 6, 6, 8, 9, 2, 9, 1, 4, 9,
2, 5, 7, 7, 8, 2, 3, 7, 2, 1, 8, 3, 9, 9, 6, 7, 5, 2,
1, 9, 9, 5, 4, 5, 3, 9, 4, 3, 5, 2, 6, 8, 7, 1, 1, 9,
4, 9, 2, 8, 5, 9, 9, 9, 4, 9, 4, 8, 1, 2, 8, 6, 6, 9,
7, 9, 3, 5, 4, 7, 7, 9, 5, 4
],
[
14, 9, 5, 1, 7, 14, 6, 5, 3, 4, 19, 5, 4, 13, 14, 10,
1, 7, 15, 5, 2, 1, 14, 10, 15, 2, 1, 2, 17, 15, 15, 5,
15, 7, 3, 8, 11, 17, 4, 11, 14, 12, 4, 1, 19, 3, 2, 2,
11, 11, 4, 11, 10, 16, 3, 11, 5, 12, 6, 17, 13, 4, 12,
1, 2, 9, 11, 19, 4, 16, 10, 6, 8, 18, 9, 12, 14, 14,
16, 16, 13, 13, 12, 19, 2, 4, 12, 8, 10, 4, 13, 16, 4,
9, 12, 17, 11, 18, 5, 14
],
[
23, 7, 14, 5, 10, 15, 14, 17, 27, 16, 3, 7, 10, 21, 8,
17, 20, 24, 19, 9, 20, 14, 1, 8, 10, 26, 28, 3, 13, 2,
7, 1, 18, 24, 25, 27, 2, 14, 27, 10, 22, 28, 12, 1,
14, 4, 13, 10, 14, 26, 21, 13, 4, 5, 1, 16, 15, 9, 19,
24, 29, 4, 27, 19, 17, 1, 21, 23, 28, 28, 3, 28, 21,
22, 1, 14, 28, 28, 2, 16, 24, 21, 2, 27, 5, 9, 14, 20,
7, 20, 16, 13, 11, 17, 27, 22, 19, 28, 6, 25
],
[
3, 36, 4, 3, 14, 13, 14, 36, 19, 24, 38, 32, 26, 14,
25, 25, 16, 14, 19, 10, 5, 15, 37, 10, 4, 20, 6, 29,
22, 20, 14, 10, 17, 37, 26, 4, 13, 32, 18, 27, 7, 35,
20, 2, 2, 11, 18, 17, 18, 8, 36, 22, 39, 12, 6, 2, 21,
1, 33, 3, 30, 25, 1, 6, 17, 38, 22, 20, 20, 21, 34,
19, 14, 13, 10, 30, 39, 8, 30, 25, 37, 6, 33, 10, 32,
17, 6, 32, 5, 34, 27, 21, 29, 15, 3, 30, 15, 28, 15,
37
],
[
43, 4, 5, 29, 17, 10, 7, 31, 12, 9, 33, 42, 6, 43, 25,
32, 9, 4, 42, 25, 37, 45, 23, 6, 46, 1, 49, 8, 39, 34,
31, 14, 42, 49, 37, 40, 6, 37, 27, 36, 4, 45, 30, 14,
19, 38, 28, 43, 14, 24, 36, 43, 18, 36, 36, 12, 31,
44, 43, 21, 42, 3, 2, 13, 37, 47, 9, 12, 35, 46, 45,
14, 24, 20, 42, 3, 9, 8, 46, 32, 11, 24, 36, 47, 11,
39, 31, 6, 34, 48, 45, 38, 27, 42, 5, 30, 19, 20, 18,
9
],
[
22, 57, 14, 54, 52, 54, 2, 47, 5, 9, 47, 55, 27, 41,
6, 23, 58, 23, 28, 17, 16, 12, 6, 47, 12, 36, 28, 15,
49, 42, 6, 23, 6, 34, 31, 36, 11, 38, 31, 42, 30, 18,
30, 40, 12, 16, 52, 23, 47, 10, 19, 15, 28, 20, 18,
35, 21, 29, 25, 41, 15, 34, 2, 11, 58, 15, 22, 17, 16,
49, 43, 30, 1, 30, 33, 46, 25, 21, 20, 42, 42, 44, 21,
3, 41, 44, 52, 52, 8, 50, 41, 3, 12, 19, 53, 47, 26,
2, 49, 14
],
[
53, 9, 51, 39, 36, 61, 61, 20, 35, 4, 43, 18, 46, 61,
8, 51, 26, 5, 8, 2, 49, 33, 35, 22, 5, 59, 65, 16, 44,
60, 43, 4, 54, 48, 1, 48, 43, 28, 60, 49, 39, 39, 37,
57, 32, 68, 8, 51, 38, 25, 1, 28, 16, 60, 2, 42, 58,
8, 49, 59, 59, 64, 63, 44, 26, 20, 18, 52, 64, 58, 35,
53, 30, 69, 6, 58, 5, 15, 20, 43, 61, 19, 57, 45, 51,
23, 67, 55, 21, 33, 30, 1, 41, 35, 61, 24, 42, 24, 18,
57
],
[
12, 29, 23, 7, 24, 26, 65, 38, 73, 11, 72, 23, 68, 28,
2, 52, 33, 50, 51, 29, 24, 18, 24, 23, 63, 65, 71, 30,
27, 19, 11, 24, 55, 64, 51, 64, 21, 15, 2, 39, 16, 59,
31, 44, 25, 46, 33, 20, 53, 24, 45, 64, 10, 67, 69,
29, 12, 59, 27, 41, 77, 61, 8, 24, 15, 66, 71, 75, 65,
56, 58, 63, 33, 63, 17, 1, 41, 17, 7, 38, 65, 44, 76,
21, 38, 46, 38, 15, 52, 69, 69, 50, 32, 46, 11, 59,
26, 14, 68, 57
],
[
17, 37, 8, 75, 88, 15, 4, 57, 12, 68, 37, 54, 75, 39,
39, 36, 66, 75, 46, 80, 14, 54, 83, 2, 28, 13, 66, 51,
84, 63, 66, 83, 66, 76, 48, 61, 46, 53, 36, 12, 16,
68, 3, 21, 38, 18, 75, 34, 2, 17, 25, 33, 16, 16, 59,
47, 16, 75, 60, 73, 44, 61, 9, 43, 18, 38, 67, 67, 89,
43, 78, 89, 37, 22, 33, 77, 79, 71, 45, 71, 49, 80,
83, 53, 62, 29, 88, 84, 71, 14, 69, 21, 75, 56, 55,
79, 31, 75, 30, 42
]]
xSequence = []
for i in range(10):
xSequence.append(sequences[i])
bnw.xSequence = xSequence
plot = Plot()
plot.hasLegend()
plot.add(bnw)
plot.save(self.imageName)
