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 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):
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 generatePlot(stepType):
line = Line()
line.xValues = xVals
line.yValues = yVals
line.marker = 'o'
line.stepFunction(stepType)
plot = Plot()
plot.add(line)
plot.setTitle(r'"%s" Steps' % (stepType))
plot.setXLimits(0, 6)
plot.setYLimits(0, 6)
return plot
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):
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.setYLimits(0, 7)
plot.setXLimits(0, 9)
plot.add(stack)
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 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)
#!/usr/bin/env python
from boomslang import Plot, Line, PlotLayout
import numpy
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("split.png")