1 files changed, 69 insertions, 0 deletions
diff --git a/util/plot_dh.py b/util/plot_dh.py
new file mode 100755
index 0000000..2354688
--- /dev/null
+++ b/util/plot_dh.py
@@ -0,0 +1,69 @@
+#!/usr/bin/env python
+# -*- coding: UTF-8 -*-
+#
+# Script for plotting ECTester ECDH results.
+#
+# Example usage:
+#
+#     > java -jar ECTesterReader.jar -dh 10000 -b 192 -fp -o dh.csv
+#     ...
+#     > ./plot_dh.py dh.csv
+#     ...
+#
+
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.ticker as ticker
+import argparse
+from operator import itemgetter
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Plot ECTester ECDH 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("--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(";")
+
+    hx = lambda x: int(x, 16)
+    data = np.genfromtxt(opts.file, delimiter=";", skip_header=1, converters={2: hx, 3: hx, 4: hx}, dtype=np.dtype([("index","u4"), ("time","u4"), ("pub", "O"), ("priv", "O"), ("secret","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)
+    secret_data = map(itemgetter(4), data)
+
+    plt.style.use("ggplot")
+    fig = plt.figure(tight_layout=True)
+    fig.suptitle(opts.file)
+
+    axe_hist = fig.add_subplot(1,1,1)
+    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)