diff options
Diffstat (limited to 'util/plot_gen.py')
| -rwxr-xr-x | util/plot_gen.py | 37 |
1 files changed, 34 insertions, 3 deletions
diff --git a/util/plot_gen.py b/util/plot_gen.py index 12f7089..848d812 100755 --- a/util/plot_gen.py +++ b/util/plot_gen.py @@ -14,7 +14,9 @@ import numpy as np import matplotlib.pyplot as plt import matplotlib.ticker as ticker +import matplotlib.colors as colors from operator import itemgetter +from copy import deepcopy import argparse if __name__ == "__main__": @@ -23,6 +25,7 @@ if __name__ == "__main__": 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("--hw-hist", dest="hw_hist", action="store_true", help="Show Hamming weight 2D histogram (private key Hamming weight and generation time).") 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).") @@ -32,11 +35,11 @@ if __name__ == "__main__": header = f.readline() header_names = header.split(";") - plots = [opts.priv, opts.pub, opts.hist] + plots = [opts.priv, opts.pub, opts.hist, opts.hw_hist] n_plots = sum(plots) if n_plots == 0: - n_plots = 3 - plots = [True, True, True] + n_plots = 4 + plots = [True, 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")])) @@ -83,7 +86,35 @@ if __name__ == "__main__": axe_hist.set_xlabel("time ({})".format(unit)) axe_hist.xaxis.set_major_locator(ticker.MaxNLocator()) axe_hist.legend(loc="best") + plot_i += 1 + if plots[3]: + priv_bit_bins = {} + for i in range(len(data)): + skey = priv_data[i] + time = time_data[i] + skey_hw = 0 + while skey: + skey_hw += 1 + skey &= skey - 1 + if skey_hw in priv_bit_bins: + priv_bit_bins[skey_hw].append(time) + else: + priv_bit_bins[skey_hw] = [time] + priv_bit_x = [] + priv_bit_y = [] + for k,v in priv_bit_bins.items(): + priv_bit_x.extend([k] * len(v)) + priv_bit_y.extend(v) + axe_priv_hist = fig.add_subplot(n_plots, 1, plot_i) + h, xe, ye = np.histogram2d(priv_bit_x, priv_bit_y, bins=[max(priv_bit_bins) - min(priv_bit_bins), (max(time_data) - min(time_data))/5]) + cmap = deepcopy(plt.cm.plasma) + cmap.set_bad("black") + 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.set_xlabel("private key Hamming weight") + axe_priv_hist.set_ylabel("time ({})".format(unit)) + 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: |