1 files changed, 0 insertions, 107 deletions

diff --git a/util/plot_dh.py b/util/plot_dh.py
deleted file mode 100755
index 60e20ae..0000000
--- a/util/plot_dh.py
+++ /dev/null
@@ -1,107 +0,0 @@
-#!/usr/bin/env python3
-# -*- 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
-from matplotlib import ticker, colors
-import argparse
-from copy import deepcopy
-from operator import itemgetter
-
-from utils import hw, moving_average, plot_hist
-
-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("--priv", dest="priv", action="store_true", help="Show private key MSB heatmap plot.")
-    parser.add_argument("--hist", dest="hist", action="store_true", help="Show time histogram.")
-    parser.add_argument("--hw-hist", dest="hw_hist", action="store_true", help="Show Hamming weight heatmap (private key Hamming weight and time).")
-    parser.add_argument("--avg", dest="avg", action="store_true", help="Show moving average of time.")
-    parser.add_argument("--log", dest="log", action="store_true", help="Use logarithmic scale.")
-    parser.add_argument("--skip-first", dest="skip_first", nargs="?", const=1, type=int, help="Skip first entry, as it's usually a large outlier.")
-    parser.add_argument("-t", "--title", dest="title", nargs="?", default="", type=str, help="What title to give the figure.")
-    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[opts.skip_first:]
-
-    time_data = data["time"]
-    if "nano" in header_names[1]:
-        unit = r"$\mu s$"
-        time_data = np.array(list(map(lambda x: x//1000, time_data)))
-    else:
-        unit = r"ms"
-    priv_data = data["priv"]
-    pub_data = data["pub"]
-    secret_data = data["secret"]
-
-    plt.style.use("ggplot")
-    fig = plt.figure()
-    layout_kwargs = {}
-    if opts.title is None:
-        fig.suptitle(opts.file)
-        layout_kwargs["rect"] = [0, 0.02, 1, 0.98]
-    elif opts.title:
-        fig.suptitle(opts.title)
-        layout_kwargs["rect"] = [0, 0.02, 1, 0.98]
-    fig.tight_layout(**layout_kwargs)
-
-    time_max = max(time_data)
-    time_min = min(time_data)
-    bit_size = len(bin(max(priv_data))) - 2
-
-    cmap = deepcopy(plt.cm.plasma)
-    cmap.set_bad("black")
-
-    norm = colors.Normalize()
-    if opts.log:
-        norm = colors.LogNorm()
-
-    axe_private = fig.add_subplot(3,1,1)
-    priv_msb = np.array(list(map(lambda x: x >> (bit_size - 8), priv_data)), dtype=np.dtype("u1"))
-    heatmap, xedges, yedges = np.histogram2d(priv_msb, time_data, bins=[128, time_max - time_min])
-    extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]]
-    axe_private.imshow(heatmap.T, extent=extent, aspect="auto", cmap=cmap, origin="low", interpolation="nearest", norm=norm)
-    axe_private.set_xlabel("private key MSB value")
-    axe_private.set_ylabel("ECDH time ({})".format(unit))
-
-    axe_hist = fig.add_subplot(3,1,2)
-    plot_hist(axe_hist, time_data, "ECDH time ({})".format(unit), opts.log)
-    axe_hist.legend(loc="best")
-
-    axe_priv_hist = fig.add_subplot(3,1,3)
-    priv_hw = np.array(list(map(hw, priv_data)), dtype=np.dtype("u2"))
-    h, xe, ye = np.histogram2d(priv_hw, time_data, bins=[max(priv_hw) - min(priv_hw), time_max - time_min])
-    im = axe_priv_hist.imshow(h.T, origin="low", cmap=cmap, aspect="auto", extent=[xe[0], xe[-1], ye[0], ye[-1]], norm=colors.LogNorm())
-    axe_priv_hist.axvline(x=bit_size//2, alpha=0.7, linestyle="dotted", color="white", label=str(bit_size//2) + " bits")    
-    axe_priv_hist.set_xlabel("private key Hamming weight")
-    axe_priv_hist.set_ylabel("time ({})".format(unit))
-    axe_priv_hist.legend(loc="best")
-    fig.colorbar(im, ax=axe_priv_hist)
-
-    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)
-        ext = opts.output.name.split(".")[-1]
-        plt.savefig(opts.output, format=ext, dpi=400, bbox_inches='tight')