Added script to plot clustering times.

Author: StuntsPT

benchmarks/bar_plotter.py

@@ -0,0 +1,60 @@
+#!/usr/bin/python3
+
+# Copyright 2015 Francisco Pina Martins <f.pinamartins@gmail.com>
+# This file is part of speedup_plotter.
+# speedup_plotter is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+
+# speedup_plotter is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+
+# You should have received a copy of the GNU General Public License
+# along with speedup_plotter. If not, see <http://www.gnu.org/licenses/>.
+
+import matplotlib.pyplot as plt
+import numpy
+
+from speedup_plotter import data_harverster
+
+
+def draw_bar_plot(dataframes):
+    """
+    Draws a bar plot with the different times for single vs. multiple
+    threads implementations."""
+
+    N = len(dataframes[:, 0])
+    single_times = dataframes[:, 1]
+    threaded_times = dataframes[:, 2]
+
+    locs = numpy.arange(N)  # the x locations for the groups
+
+    width = 0.35       # the width of the bars
+
+    fig, ax = plt.subplots()
+    rects1 = ax.bar(locs, single_times, width, color='grey')
+
+    rects2 = ax.bar(locs+width, threaded_times, width, color='darkgrey')
+
+    # add some text for labels, title and axes ticks
+    ax.set_ylabel('Time (s)')
+    ax.set_title('Time to calculate clustering for each value of "K", single, '
+                 'vs. multiple threading')
+    ax.set_xticks(locs+width)
+
+    ax.set_xticklabels(list(map(int, dataframes[:, 0])))
+
+    ax.legend((rects1[0], rects2[0]), ('Single thread', '8 threads'), loc="upper left")
+
+    ax.grid(True, zorder=0)
+
+    plt.savefig(argv[1] + "_plot.svg", format="svg")
+
+if __name__ == "__main__":
+    from sys import argv
+    # Usage: python3 bar_plotter.py K_times.csv
+    dataframes = data_harverster(argv[1])
+    draw_bar_plot(dataframes)