1 files changed, 93 insertions, 0 deletions
diff --git a/util/plot_gen.py b/util/plot_gen.py
new file mode 100755
index 0000000..12f7089
--- /dev/null
+++ b/util/plot_gen.py
@@ -0,0 +1,93 @@
+#!/usr/bin/env python
+# -*- coding: UTF-8 -*-
+#
+# Script for plotting ECTester key generation results.
+#
+# Example usage:
+#
+#     > java -jar ECTesterReader.jar -g 10000 -b 192 -fp -o gen.csv
+#     ...
+#     > ./plot_gen.py gen.csv
+#     ...
+#
+
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.ticker as ticker
+from operator import itemgetter
+import argparse
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Plot results of ECTester key generation timing.")
+    parser.add_argument("-o", "--output", dest="output", type=argparse.FileType("wb"), help="Write image to [file], do not display.", metavar="file")
+    parser.add_argument("--pub", dest="pub", action="store_true", help="Show public key scatter plot.")
+    parser.add_argument("--priv", dest="priv", action="store_true", help="Show private key scatter plot.")
+    parser.add_argument("--hist", dest="hist", action="store_true", help="Show histogram.")
+    parser.add_argument("--skip-first", dest="skip_first", action="store_true", help="Skip first entry, as it's usually a large outlier.")
+    parser.add_argument("file", type=str, help="The file to plot(csv).")
+
+    opts = parser.parse_args()
+
+    with open(opts.file, "r") as f:
+        header = f.readline()
+    header_names = header.split(";")
+
+    plots = [opts.priv, opts.pub, opts.hist]
+    n_plots = sum(plots)
+    if n_plots == 0:
+        n_plots = 3
+        plots = [True, True, True]
+
+    hx = lambda x: int(x, 16)
+    data = np.genfromtxt(opts.file, delimiter=";", skip_header=1, converters={2: hx, 3: hx}, dtype=np.dtype([("index","u4"), ("time","u4"), ("pub", "O"), ("priv", "O")]))
+    if opts.skip_first:
+        data = data[1:]
+
+    if "nano" in header_names[1]:
+        unit = r"$\mu s$"
+        time_data = map(lambda x: x[1]/1000, data)
+    else:
+        unit = r"ms"
+        time_data = map(itemgetter(1), data)
+    priv_data = map(itemgetter(2), data)
+    pub_data = map(itemgetter(3), data)
+
+    plt.style.use("ggplot")
+    fig = plt.figure(tight_layout=True)
+    fig.suptitle(opts.file)
+
+    plot_i = 1
+    if plots[0]:
+        axe_private = fig.add_subplot(n_plots, 1, plot_i)
+        axe_private.scatter(time_data, priv_data, marker="x", s=10)
+        axe_private.set_ylabel("private key value\n(big endian)")
+        axe_private.set_xlabel("time ({})".format(unit))
+        plot_i += 1
+
+    if plots[1]:
+        axe_public = fig.add_subplot(n_plots, 1, plot_i)
+        axe_public.scatter(time_data, pub_data, marker="x", s=10)
+        axe_public.set_ylabel("public key value\n(big endian)")
+        axe_public.set_xlabel("time ({})".format(unit))
+        plot_i += 1
+
+    if plots[2]:
+        axe_hist = fig.add_subplot(n_plots, 1, plot_i)
+        time_max = max(time_data)
+        time_avg = np.average(time_data)
+        time_median = np.median(time_data)
+        axe_hist.hist(time_data, bins=time_max/3, log=True)
+        axe_hist.axvline(x=time_avg, alpha=0.7, linestyle="dotted", color="red", label="avg = {}".format(time_avg))
+        axe_hist.axvline(x=time_median, alpha=0.7, linestyle="dotted", color="green", label="median = {}".format(time_median))
+        axe_hist.set_ylabel("count\n(log)")
+        axe_hist.set_xlabel("time ({})".format(unit))
+        axe_hist.xaxis.set_major_locator(ticker.MaxNLocator())
+        axe_hist.legend(loc="best")
+
+    fig.text(0.01, 0.02, "Data size: {}".format(len(time_data)), size="small")
+
+    if opts.output is None:
+        plt.show()
+    else:
+        fig.set_size_inches(12, 10)
+        plt.savefig(opts.output, dpi=400)