1 files changed, 0 insertions, 186 deletions

diff --git a/util/plot_gen.py b/util/plot_gen.py
deleted file mode 100755
index 4ee1ddc..0000000
--- a/util/plot_gen.py
+++ /dev/null
@@ -1,186 +0,0 @@
-#!/usr/bin/env python3
-# -*- 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
-from scipy.stats import entropy
-import matplotlib.pyplot as plt
-from matplotlib import ticker, colors
-from copy import deepcopy
-import argparse
-
-from utils import hw, moving_average, plot_hist, miller_correction
-
-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("--priv", dest="priv", action="store_true", help="Show private key MSB heatmap plot.")
-    parser.add_argument("--entropy", dest="entropy", action="store_true", help="Show estimated entropy of private key MSB conditioned on time of generation.")
-    parser.add_argument("--hist", dest="hist", action="store_true", help="Show keygen time histogram.")
-    parser.add_argument("--export-hist", dest="export_hist", action="store_true", help="Show export time histogram.")
-    parser.add_argument("--avg", dest="avg", action="store_true", help="Show moving average of keygen time.")
-    parser.add_argument("--hw-hist", dest="hw_hist", action="store_true", help="Show Hamming weight heatmap (private key Hamming weight and keygen 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", type=str, nargs="?", default="", 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(";")
-    if len(header_names) not in (4, 5):
-        print("Bad data?")
-        exit(1)
-
-    plots = [opts.priv, opts.hist, opts.export_hist, opts.avg, opts.hw_hist]
-    n_plots = sum(plots)
-    if n_plots == 0:
-        plots = [True for _ in range(5)]
-        if len(header_names) == 4:
-            n_plots = 4
-            plots[2] = False
-        else:
-            n_plots = 5
-
-
-    if plots[2] and len(header_names) != 5:
-        n_plots = n_plots - 1
-        if n_plots == 0:
-            print("Nothing to plot.")
-            exit(1)
-        plots[2] = False
-
-    hx = lambda x: int(x, 16)
-    if len(header_names) == 4:
-        data = np.genfromtxt(opts.file, delimiter=";", skip_header=1, converters={2: hx, 3: hx}, dtype=np.dtype([("index", "u4"), ("gen_time", "u4"), ("pub", "O"), ("priv", "O")]))
-    else:
-        data = np.genfromtxt(opts.file, delimiter=";", skip_header=1, converters={3: hx, 4: hx}, dtype=np.dtype([("index", "u4"), ("gen_time", "u4"), ("export_time", "u4"), ("pub", "O"), ("priv", "O")]))
-
-    if opts.skip_first:
-        data = data[opts.skip_first:]
-
-
-    gen_time_data = data["gen_time"]
-    export_time_data = None
-    if "export_time" in data.dtype.names:
-        export_time_data = data["export_time"]
-    pub_data = data["pub"]
-    priv_data = data["priv"]
-
-    gen_unit = "ms"
-    if header_names[1].endswith("[nano]"):
-        gen_unit = r"$\mu s$"
-        np.floor_divide(gen_time_data, 1000, out=gen_time_data)
-    export_unit = "ms"
-    if len(header_names) == 5 and header_names[2].endswith("[nano]"):
-        export_unit = r"$\mu s$"
-        np.floor_divide(export_time_data, 1000, out=export_time_data)
-
-    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)
-
-    max_gen_time = max(gen_time_data)
-    min_gen_time = min(gen_time_data)
-    bit_size = len(bin(max(priv_data))) - 2
-
-    sorted_data = np.sort(data, order="gen_time")
-
-    cmap = deepcopy(plt.cm.plasma)
-    cmap.set_bad("black")
-
-    norm = colors.Normalize()
-    if opts.log:
-        norm = colors.LogNorm()
-
-    plot_i = 1
-    if plots[0]:
-        axe_private = fig.add_subplot(n_plots, 1, plot_i)
-        priv_msb = np.array(list(map(lambda x: x >> (bit_size - 8), priv_data)), dtype=np.dtype("u1"))
-        max_msb = max(priv_msb)
-        min_msb = min(priv_msb)
-        heatmap, xedges, yedges = np.histogram2d(priv_msb, gen_time_data, bins=[max_msb - min_msb, max_gen_time - min_gen_time])
-        extent = [min_msb, max_msb, 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("keygen time ({})".format(gen_unit))
-        plot_i += 1
-
-    if plots[1]:
-        axe_hist = fig.add_subplot(n_plots, 1, plot_i)
-        plot_hist(axe_hist, gen_time_data, "keygen time ({})".format(gen_unit), opts.log)
-        plot_i += 1
-
-    if plots[2]:
-        axe_hist = fig.add_subplot(n_plots, 1, plot_i)
-        plot_hist(axe_hist, export_time_data, "export time ({})".format(export_unit), opts.log)
-        plot_i += 1
-
-    if plots[3]:
-        axe_avg = fig.add_subplot(n_plots, 1, plot_i)
-        #if len(header_names) == 5:
-        #   axe_other = axe_avg.twinx()
-        #   axe_other.plot(moving_average(export_time_data, 100), color="green", alpha=0.6, label="export, window = 100")
-        #   axe_other.plot(moving_average(export_time_data, 1000), color="yellow", alpha=0.6, label="export, window = 1000")
-        #   axe_other.legend(loc="lower right")
-        axe_avg.plot(moving_average(gen_time_data, 100), label="window = 100")
-        axe_avg.plot(moving_average(gen_time_data, 1000), label="window = 1000")
-        axe_avg.set_ylabel("keygen time ({})".format(gen_unit))
-        axe_avg.set_xlabel("index")
-        axe_avg.legend(loc="best")
-        plot_i += 1
-
-    if plots[4]:
-        axe_priv_hist = fig.add_subplot(n_plots, 1, plot_i)
-        priv_hw = np.array(list(map(hw, priv_data)), dtype=np.dtype("u2"))
-        h, xe, ye = np.histogram2d(priv_hw, gen_time_data, bins=[max(priv_hw) - min(priv_hw), max_gen_time - min_gen_time])
-        im = axe_priv_hist.imshow(h.T, origin="low", cmap=cmap, aspect="auto", extent=[xe[0], xe[-1], ye[0], ye[-1]], norm=norm)
-        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("keygen time ({})".format(gen_unit))
-        axe_priv_hist.legend(loc="best")
-        fig.colorbar(im, ax=axe_priv_hist)
-
-    fig.text(0.01, 0.02, "Data size: {}".format(len(gen_time_data)), size="small")
-
-    if opts.entropy:
-        i = 0
-        entropies = {}
-        while i < len(data):
-            time_val = sorted_data["gen_time"][i]
-            j = i
-            msbs = [0 for _ in range(256)]
-            while j < len(data) and sorted_data["gen_time"][j] == time_val:
-                msbs[(sorted_data["priv"][j] >> (bit_size - 8)) & 0xff] += 1
-                j += 1
-            if j - 100 > i:
-                entropies[time_val] = miller_correction(entropy(msbs, base=2), j - i, 256)
-            i = j
-    
-        entropy = sum(entropies.values())/len(entropies)
-        fig.text(0.01, 0.04, "Entropy of privkey MSB(estimated): {:.2f} b".format(entropy), 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')