Added a new plotter script.

Author: StuntsPT

benchmarks/system_speedup_plotter.py

@@ -0,0 +1,59 @@
+#!/usr/bin/python3
+
+# Copyright 2015-2017 Francisco Pina Martins <[email protected]>
+# 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
+
+def data_harverster(datafile_name):
+    """
+    Gather speedup data from a csv file and return a np array with it.
+    """
+    timearray = numpy.genfromtxt(datafile_name, delimiter=";", autostrip=True,
+                                 dtype=float, skip_header=False, names=True,
+                                 filling_values=False)
+
+    return timearray
+
+
+def draw_plot(timearray):
+    """
+    Draw a line plot based on speedup data.
+    """
+    system_cores = max(map(int, timearray["CPUs"]))
+    names = [x for x in timearray.dtype.names if x != "CPUs"]
+    linetypes = ("k-", "k:", "k--")
+    lines = {k: v for k, v in zip(names, linetypes)}
+    plt.axis([1, system_cores + 1, 1, system_cores + 1])
+    for name in names:
+        plt.plot(list(map(int, timearray["CPUs"])), timearray[name],
+                 lines[name],
+                 fillstyle="full", ms=7, label=name)
+    plt.plot(range(1, system_cores + 2), range(1, system_cores + 2), 'k-.',
+             label="Linear scaling")
+
+    plt.grid(True)
+    plt.xlabel("Number of threads")
+    plt.ylabel("Speed increase")
+    plt.xticks(list(map(int, timearray["CPUs"])))
+    plt.legend(loc=2, fontsize="small")
+    plt.savefig(argv[1] + "_plot.svg", format="svg")
+    #plt.show()
+
+if __name__ == "__main__":
+    from sys import argv
+    TIMEARRAY = data_harverster(argv[1])
+    draw_plot(TIMEARRAY)