Add RPA eval plots.

1 files changed, 380 insertions, 31 deletions

diff --git a/re/rpa.ipynb b/re/rpa.ipynb
index f328b2d..d435b15 100644
--- a/re/rpa.ipynb
+++ b/re/rpa.ipynb
@@ -55,7 +55,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%matplotlib inline\n",
+    "%matplotlib ipympl\n",
     "hv.extension(\"bokeh\")"
    ]
   },
@@ -115,26 +115,36 @@
     "    RTLMultiplier(add, dbl, None, True, AccumulationOrder.PeqPR, False),\n",
     "    SimpleLadderMultiplier(add, dbl, None, True, True),\n",
     "    BinaryNAFMultiplier(add, dbl, neg, None, ProcessingDirection.LTR, AccumulationOrder.PeqPR, True),\n",
+    "    BinaryNAFMultiplier(add, dbl, neg, None, ProcessingDirection.RTL, AccumulationOrder.PeqPR, True),\n",
     "    WindowNAFMultiplier(add, dbl, neg, 3, None, AccumulationOrder.PeqPR, True, True),\n",
     "    WindowNAFMultiplier(add, dbl, neg, 4, None, AccumulationOrder.PeqPR, True, True),\n",
     "    WindowNAFMultiplier(add, dbl, neg, 5, None, AccumulationOrder.PeqPR, True, True),\n",
-    "    #WindowNAFMultiplier(add, dbl, neg, 4, None, AccumulationOrder.PeqPR, False, True),  # Same set of multiples as Window NAF with precompute_negation\n",
+    "    WindowBoothMultiplier(add, dbl, neg, 3, None, AccumulationOrder.PeqPR, True, True),\n",
+    "    WindowBoothMultiplier(add, dbl, neg, 4, None, AccumulationOrder.PeqPR, True, True),\n",
+    "    WindowBoothMultiplier(add, dbl, neg, 5, None, AccumulationOrder.PeqPR, True, True),\n",
     "    SlidingWindowMultiplier(add, dbl, 3, None, ProcessingDirection.LTR, AccumulationOrder.PeqPR, True),\n",
     "    SlidingWindowMultiplier(add, dbl, 4, None, ProcessingDirection.LTR, AccumulationOrder.PeqPR, True),\n",
     "    SlidingWindowMultiplier(add, dbl, 5, None, ProcessingDirection.LTR, AccumulationOrder.PeqPR, True),\n",
+    "    SlidingWindowMultiplier(add, dbl, 3, None, ProcessingDirection.RTL, AccumulationOrder.PeqPR, True),\n",
+    "    SlidingWindowMultiplier(add, dbl, 4, None, ProcessingDirection.RTL, AccumulationOrder.PeqPR, True),\n",
+    "    SlidingWindowMultiplier(add, dbl, 5, None, ProcessingDirection.RTL, AccumulationOrder.PeqPR, True),\n",
+    "    FixedWindowLTRMultiplier(add, dbl, 3, None, AccumulationOrder.PeqPR, True),\n",
     "    FixedWindowLTRMultiplier(add, dbl, 4, None, AccumulationOrder.PeqPR, True),\n",
     "    FixedWindowLTRMultiplier(add, dbl, 5, None, AccumulationOrder.PeqPR, True),\n",
     "    FixedWindowLTRMultiplier(add, dbl, 8, None, AccumulationOrder.PeqPR, True),\n",
+    "    FixedWindowLTRMultiplier(add, dbl, 16, None, AccumulationOrder.PeqPR, True),\n",
     "    FullPrecompMultiplier(add, dbl, None, True, ProcessingDirection.LTR, AccumulationOrder.PeqPR, True, True),\n",
     "    FullPrecompMultiplier(add, dbl, None, False, ProcessingDirection.LTR, AccumulationOrder.PeqPR, True, True),\n",
-    "    #FullPrecompMultiplier(add, dbl, None, False, ProcessingDirection.RTL, AccumulationOrder.PeqPR, True, True),  # Same set of multiples as RTL multiplier\n",
     "    BGMWMultiplier(add, dbl, 2, None, ProcessingDirection.LTR, AccumulationOrder.PeqPR, True),\n",
     "    BGMWMultiplier(add, dbl, 3, None, ProcessingDirection.LTR, AccumulationOrder.PeqPR, True),\n",
+    "    BGMWMultiplier(add, dbl, 4, None, ProcessingDirection.LTR, AccumulationOrder.PeqPR, True),\n",
     "    BGMWMultiplier(add, dbl, 5, None, ProcessingDirection.LTR, AccumulationOrder.PeqPR, True),\n",
     "    CombMultiplier(add, dbl, 2, None, AccumulationOrder.PeqPR, True),\n",
     "    CombMultiplier(add, dbl, 3, None, AccumulationOrder.PeqPR, True),\n",
+    "    CombMultiplier(add, dbl, 4, None, AccumulationOrder.PeqPR, True),\n",
     "    CombMultiplier(add, dbl, 5, None, AccumulationOrder.PeqPR, True)\n",
-    "]"
+    "]\n",
+    "print(len(multipliers))"
    ]
   },
   {
@@ -333,7 +343,9 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "b6c70d89-1c7d-4d7c-bc65-0cf766b86c0a",
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [],
    "source": [
     "p256 = get_params(\"secg\", \"secp256r1\", \"projective\")\n",
@@ -342,27 +354,54 @@
   },
   {
    "cell_type": "markdown",
+   "id": "6361c477-5ddf-46ff-8918-864a453b676b",
+   "metadata": {},
+   "source": [
+    "Let's see if the result is correct."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1556e604-d0ab-403c-bd44-d53be8e18283",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(multipliers[0] in res)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "id": "068e1ba5-9884-4d2b-97f6-d54313daddad",
    "metadata": {},
    "source": [
+    "#### What about (symmetric) noise?\n",
     "Now we can examine how the method performs in the presence of noise and with various majority vote parameters. Note that the code below spawns several processes (`num_cores`) and saturates their CPU fully, so set this to something appropriate."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4e9ca09b-9fe4-4c91-ac37-530892b1df48",
+   "id": "76b0f82c-64ac-4646-91b9-99f7962200d3",
    "metadata": {},
    "outputs": [],
    "source": [
     "errs = (0, 0.1, 0.2, 0.3, 0.4, 0.5)\n",
     "majs = (1, 3, 5, 7, 9, 11)\n",
+    "num_tries = 100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4e9ca09b-9fe4-4c91-ac37-530892b1df48",
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "correct_tries = np.zeros((len(errs), len(majs)))\n",
     "precise_tries = np.zeros((len(errs), len(majs)))\n",
     "query_tries = np.zeros((len(errs), len(majs)))\n",
-    "total_tries = 0\n",
-    "\n",
-    "num_tries = 50"
+    "total_tries = 0"
    ]
   },
   {
@@ -388,8 +427,8 @@
     "        res = rpa_distinguish(params, multipliers, oracle, majority=majority)\n",
     "        if mult in res:\n",
     "            correct += 1\n",
-    "            if len(res) == 1:\n",
-    "                precise += 1\n",
+    "        if len(res) == 1:\n",
+    "            precise += 1\n",
     "    return correct, precise, calls\n",
     "\n",
     "with TemporaryConfig() as cfg:\n",
@@ -404,7 +443,7 @@
     "                    futures.append(pool.submit(measure_mult, *a))\n",
     "                    args.append(a)\n",
     "        results = [None for _ in futures]\n",
-    "        for future in tqdm(as_completed(futures), total=len(futures)):\n",
+    "        for future in tqdm(as_completed(futures), total=len(futures), smoothing=0):\n",
     "            j = futures.index(future)\n",
     "            a = args[j]\n",
     "            results[j] = future.result()"
@@ -440,12 +479,33 @@
   },
   {
    "cell_type": "markdown",
+   "id": "8c747434-84bb-4acd-a994-45a4b4859a6e",
+   "metadata": {},
+   "source": [
+    "And save the results for later."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "857f39ad-f6ba-4006-8da9-92f4318819e2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "np.save(\"rpa_re_correct_rate\", correct_rate)\n",
+    "np.save(\"rpa_re_precise_rate\", precise_rate)\n",
+    "np.save(\"rpa_re_query_rate\", query_rate)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "id": "9bda1baa-359a-4f9b-889d-f64e055deff6",
    "metadata": {},
    "source": [
-    "We can plot two heatmaps:\n",
+    "We can plot several heatmaps:\n",
     " - One for the average number of queries to the oracle.\n",
-    " - One for the success rate of the distinguisher."
+    " - One for the success rate of the reverse-engineering.\n",
+    " - One for the precision of the reverse-engineering."
    ]
   },
   {
@@ -457,19 +517,19 @@
    "source": [
     "fig, ax = plt.subplots()\n",
     "im = ax.imshow(query_rate.T, cmap=\"plasma\")\n",
-    "cbar_ax = fig.add_axes((0.90, 0.15, 0.04, 0.69))\n",
+    "cbar_ax = fig.add_axes((0.85, 0.15, 0.04, 0.69))\n",
     "cbar = fig.colorbar(im, cax=cbar_ax)\n",
-    "cbar.ax.set_ylabel(\"Average oracle query rate\", rotation=-90, va=\"bottom\")\n",
+    "cbar.ax.set_ylabel(\"Oracle query rate\", rotation=-90, va=\"bottom\")\n",
     "\n",
     "ax.set_xticks(np.arange(len(errs)), labels=errs)\n",
     "ax.set_yticks(np.arange(len(majs)), labels=reversed(majs))\n",
-    "ax.set_xlabel(\"err\")\n",
-    "ax.set_ylabel(\"majority\")\n",
+    "ax.set_xlabel(\"error probability\")\n",
+    "ax.set_ylabel(\"majority vote\")\n",
     "for i in range(len(errs)):\n",
     "    for j in range(len(majs)):\n",
-    "        text = ax.text(i, j, f\"{query_rate[i, j]:.2f}\",\n",
-    "                       ha=\"center\", va=\"center\", color=\"w\")\n",
-    "fig.savefig(\"rpa_re_query_rate.png\", bbox_inches=\"tight\")\n",
+    "        text = ax.text(i, j, f\"{query_rate[i, j]:.1f}\",\n",
+    "                       ha=\"center\", va=\"center\", color=\"w\" if i - j <= 2 else \"black\")\n",
+    "fig.savefig(\"rpa_re_query_rate.pdf\", bbox_inches=\"tight\")\n",
     "plt.show()"
    ]
   },
@@ -482,20 +542,309 @@
    "source": [
     "fig, ax = plt.subplots()\n",
     "im = ax.imshow(correct_rate.T, vmin=0, cmap=\"viridis\")\n",
-    "cbar_ax = fig.add_axes((0.90, 0.15, 0.04, 0.69))\n",
+    "cbar_ax = fig.add_axes((0.85, 0.15, 0.04, 0.69))\n",
     "cbar = fig.colorbar(im, cax=cbar_ax)\n",
     "cbar.ax.set_ylabel(\"Success rate\", rotation=-90, va=\"bottom\")\n",
     "cbar.ax.axhline(100 / len(multipliers), color=\"red\", linestyle=\"--\")\n",
     "\n",
     "ax.set_xticks(np.arange(len(errs)), labels=errs)\n",
     "ax.set_yticks(np.arange(len(majs)), labels=reversed(majs))\n",
-    "ax.set_xlabel(\"err\")\n",
-    "ax.set_ylabel(\"majority\")\n",
+    "ax.set_xlabel(\"error probability\")\n",
+    "ax.set_ylabel(\"majority vote\")\n",
     "for i in range(len(errs)):\n",
     "    for j in range(len(majs)):\n",
-    "        text = ax.text(i, j, f\"{correct_rate[i, j]:.2f}%\",\n",
-    "                       ha=\"center\", va=\"center\", color=\"w\")\n",
-    "fig.savefig(\"rpa_re_success_rate.png\", bbox_inches=\"tight\")\n",
+    "        c_rate = correct_rate[i, j]\n",
+    "        text = ax.text(i, j, f\"{c_rate:.1f}%\",\n",
+    "                       ha=\"center\", va=\"center\", color=\"w\" if c_rate < 80 else \"black\")\n",
+    "fig.savefig(\"rpa_re_success_rate.pdf\", bbox_inches=\"tight\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "56114e99-e949-488f-85bb-f6bd2e221d39",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "im = ax.imshow(precise_rate.T, vmin=0, cmap=\"viridis\")\n",
+    "cbar_ax = fig.add_axes((0.85, 0.15, 0.04, 0.69))\n",
+    "cbar = fig.colorbar(im, cax=cbar_ax)\n",
+    "cbar.ax.set_ylabel(\"Precision\", rotation=-90, va=\"bottom\")\n",
+    "\n",
+    "ax.set_xticks(np.arange(len(errs)), labels=errs)\n",
+    "ax.set_yticks(np.arange(len(majs)), labels=reversed(majs))\n",
+    "ax.set_xlabel(\"error probability\")\n",
+    "ax.set_ylabel(\"majority vote\")\n",
+    "for i in range(len(errs)):\n",
+    "    for j in range(len(majs)):\n",
+    "        p_rate = precise_rate[i, j]\n",
+    "        text = ax.text(i, j, f\"{p_rate:.1f}%\",\n",
+    "                       ha=\"center\", va=\"center\", color=\"w\" if p_rate < 80 else \"black\")\n",
+    "fig.savefig(\"rpa_re_precision.pdf\", bbox_inches=\"tight\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b8eeb49e-7734-4fda-bf28-ac39f6c8a626",
+   "metadata": {},
+   "source": [
+    "Another way to look at these metrics is a scatter plot."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1e1b1769-6aa9-4b95-a7b7-dd5cfd501d27",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "ax.grid()\n",
+    "for i, err in enumerate(errs):\n",
+    "    qrs = query_rate[i, :]\n",
+    "    crs = correct_rate[i, :]\n",
+    "    ax.scatter(qrs, crs, label=f\"error = {err}\")\n",
+    "ax.set_xlabel(\"oracle queries\")\n",
+    "ax.set_ylabel(\"success rate\")\n",
+    "ax.legend()\n",
+    "fig.savefig(\"rpa_re_scatter.pdf\", bbox_inches=\"tight\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "921b1c7b-fd40-415e-b737-1a85e07a9ba5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "for i, err in enumerate(errs):\n",
+    "    crs = correct_rate[i, :]\n",
+    "    ax.plot(list(reversed(majs)), crs, label=f\"error = {err}\")\n",
+    "ax.set_xlabel(\"majority vote\")\n",
+    "ax.set_ylabel(\"success rate\")\n",
+    "ax.set_xticks(majs)\n",
+    "ax.legend()\n",
+    "fig.savefig(\"rpa_re_plot.pdf\", bbox_inches=\"tight\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e3981f44-ed3b-43f5-b4bd-e2d4b2ff95e8",
+   "metadata": {},
+   "source": [
+    "#### What about (asymmetric) noise?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "40652fa3-39f9-47ad-9424-ee2fdaac78d3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "correct_tries_b = np.zeros((len(errs), len(errs), len(majs)))\n",
+    "precise_tries_b = np.zeros((len(errs), len(errs), len(majs)))\n",
+    "query_tries_b =   np.zeros((len(errs), len(errs), len(majs)))\n",
+    "total_tries_b = 0\n",
+    "\n",
+    "num_tries_b = 100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d6dce31a-1369-4556-8e01-4e19ad14d21e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "num_cores = 30\n",
+    "\n",
+    "def measure_mult(params, multipliers, simulated_oracle, i, mult, err_0, err_1, majority):\n",
+    "    correct = 0\n",
+    "    precise = 0\n",
+    "    calls = 0\n",
+    "    p = lru_cache(maxsize=2)(partial(simulated_oracle, simulate_mult_id=i))\n",
+    "    biased = biased_oracle(p, flip_0=err_0, flip_1=err_1)\n",
+    "    def oracle(scalar, affine_point):\n",
+    "        nonlocal calls\n",
+    "        calls += 1\n",
+    "        return biased(scalar, affine_point)\n",
+    "    for j in range(num_tries_b):\n",
+    "        res = rpa_distinguish(params, multipliers, oracle, majority=majority)\n",
+    "        if mult in res:\n",
+    "            correct += 1\n",
+    "        if len(res) == 1:\n",
+    "            precise += 1\n",
+    "    return correct, precise, calls\n",
+    "\n",
+    "with TemporaryConfig() as cfg:\n",
+    "    cfg.log.enabled = False\n",
+    "    with ProcessPoolExecutor(max_workers=num_cores) as pool:\n",
+    "        futures = []\n",
+    "        args = []\n",
+    "        for i, mult in enumerate(multipliers):\n",
+    "            for err_0 in errs:\n",
+    "                for err_1 in errs:\n",
+    "                    for majority in majs:\n",
+    "                        a = (params, multipliers, simulated_oracle, i, mult, err_0, err_1, majority)\n",
+    "                        futures.append(pool.submit(measure_mult, *a))\n",
+    "                        args.append(a)\n",
+    "        results = [None for _ in futures]\n",
+    "        for future in tqdm(as_completed(futures), total=len(futures), smoothing=0):\n",
+    "            j = futures.index(future)\n",
+    "            a = args[j]\n",
+    "            results[j] = future.result()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f4ddde62-18bb-46b2-a2e2-565cc21d654f",
+   "metadata": {},
+   "source": [
+    "Now we accumulate the results across the error rate and majority vote parameters."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "20b9ac29-401f-4068-8b2a-4b2f14e14b28",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for a, result in zip(args, results):\n",
+    "    i = errs.index(a[5])\n",
+    "    j = errs.index(a[6])\n",
+    "    k = majs.index(a[7])\n",
+    "    correct_tries_b[i, j, k] += result[0]\n",
+    "    precise_tries_b[i, j, k] += result[1]\n",
+    "    query_tries_b[i, j, k] += result[2]\n",
+    "total_tries_b += num_tries_b\n",
+    "\n",
+    "correct_rate_b = (correct_tries_b * 100) / (total_tries_b * len(multipliers))\n",
+    "precise_rate_b = (precise_tries_b * 100) / (total_tries_b * len(multipliers))\n",
+    "query_rate_b = query_tries_b / (total_tries_b * len(multipliers))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "67a6bba8-84e8-48f1-9b3b-b0b8715c71a6",
+   "metadata": {},
+   "source": [
+    "And save the results for later."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "85933a5e-f526-4002-9203-0e4ae4f731d0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "np.save(\"rpa_re_correct_rate_b\", correct_rate_b)\n",
+    "np.save(\"rpa_re_precise_rate_b\", precise_rate_b)\n",
+    "np.save(\"rpa_re_query_rate_b\", query_rate_b)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5fd78523-0463-4932-ae64-42a444104d2c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig, axs = plt.subplots(nrows=2, ncols=3, sharex=\"col\", sharey=\"row\")\n",
+    "vmin = np.min(query_rate_b)\n",
+    "vmax = np.max(query_rate_b)\n",
+    "\n",
+    "for row in range(2):\n",
+    "    for col in range(3):\n",
+    "        ax = axs[row, col]\n",
+    "        level = row * 3 + col\n",
+    "        im = ax.imshow(query_rate_b[::-1,:,level], cmap=\"plasma\", vmin=vmin, vmax=vmax)\n",
+    "        ax.set_xticks(np.arange(len(errs)), labels=errs)\n",
+    "        ax.set_yticks(np.arange(len(errs)), labels=list(reversed(errs)))\n",
+    "        for i in range(len(errs)):\n",
+    "            for j in range(len(errs)):\n",
+    "                q_rate = f\"{query_rate_b[i, len(errs) - j - 1, level]:.0f}\"\n",
+    "                loc = f\"{errs[i]} {errs[j]}\"\n",
+    "                text = ax.text(i, j, q_rate, ha=\"center\", va=\"center\")\n",
+    "        ax.set_xlabel(\"$e_1$\")\n",
+    "        ax.set_ylabel(\"$e_O$\")\n",
+    "        ax.set_title(majs[level])\n",
+    "fig.set_size_inches((10,6))\n",
+    "fig.tight_layout(h_pad=1.5, rect=(0, 0, 0.9, 1))\n",
+    "cbar_ax = fig.add_axes((0.9, 0.10, 0.02, 0.84))\n",
+    "cbar = fig.colorbar(im, cax=cbar_ax)\n",
+    "cbar.ax.set_ylabel(\"Oracle query rate\", rotation=-90, va=\"bottom\")\n",
+    "fig.savefig(\"rpa_re_asymmetric_query_rate.pdf\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6b976938-f10d-439b-83b2-94d20d00ecbc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig, axs = plt.subplots(nrows=2, ncols=3, sharex=\"col\", sharey=\"row\")\n",
+    "for row in range(2):\n",
+    "    for col in range(3):\n",
+    "        ax = axs[row, col]\n",
+    "        level = row * 3 + col\n",
+    "        im = ax.imshow(correct_rate_b[::-1,:,level], cmap=\"viridis\", vmin=0, vmax=100)\n",
+    "        ax.set_xticks(np.arange(len(errs)), labels=errs)\n",
+    "        ax.set_yticks(np.arange(len(errs)), labels=list(reversed(errs)))\n",
+    "        for i in range(len(errs)):\n",
+    "            for j in range(len(errs)):\n",
+    "                c = correct_rate_b[i, len(errs) - j - 1, level]\n",
+    "                c_rate = f\"{c:.0f}%\"\n",
+    "                loc = f\"{errs[i]} {errs[j]}\"\n",
+    "                text = ax.text(i, j, c_rate, ha=\"center\", va=\"center\", color=\"w\" if c < 50 else \"black\")\n",
+    "        ax.set_xlabel(\"$e_1$\")\n",
+    "        ax.set_ylabel(\"$e_O$\")\n",
+    "        ax.set_title(majs[level])\n",
+    "fig.set_size_inches((10,6))\n",
+    "fig.tight_layout(h_pad=1.5, rect=(0, 0, 0.9, 1))\n",
+    "cbar_ax = fig.add_axes((0.9, 0.10, 0.02, 0.84))\n",
+    "cbar = fig.colorbar(im, cax=cbar_ax)\n",
+    "cbar.ax.set_ylabel(\"Success rate\", rotation=-90, va=\"bottom\")\n",
+    "cbar.ax.axhline(100 / len(multipliers), color=\"red\", linestyle=\"--\")\n",
+    "fig.savefig(\"rpa_re_asymmetric_success_rate.pdf\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "868c4a7a-5c0f-4ee6-9a1a-2c251dfae34c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "ax.grid()\n",
+    "crs_accumulated = {}\n",
+    "for i, err_0 in enumerate(errs):\n",
+    "    for j, err_1 in enumerate(errs):\n",
+    "        crs = correct_rate_b[i, j, :]\n",
+    "        total_err = round(err_0 + err_1, 1)\n",
+    "        l = crs_accumulated.setdefault(total_err, [])\n",
+    "        l.append(crs)\n",
+    "        #ax.scatter(majs, crs, label=str(err_0 + err_1))\n",
+    "for total_err in crs_accumulated.keys():\n",
+    "    crs = np.mean(crs_accumulated[total_err], axis=0)\n",
+    "    ax.plot(majs, crs, label=f\"total_error = {total_err}\")\n",
+    "ax.set_xticks(majs)\n",
+    "ax.set_xlabel(\"majority\")\n",
+    "ax.set_ylabel(\"success rate\")\n",
+    "ax.legend(bbox_to_anchor=(1, 1.02))\n",
+    "fig.tight_layout()\n",
     "plt.show()"
    ]
   },
@@ -569,7 +918,7 @@
     "table = [[\"True multiplier\", \"Reversed\", \"Correct\", \"Remaining\"]]\n",
     "with TemporaryConfig() as cfg:\n",
     "    cfg.log.enabled = False\n",
-    "    for i, mult in tqdm(enumerate(multipliers)):\n",
+    "    for i, mult in tqdm(enumerate(multipliers), total=len(multipliers)):\n",
     "        res = rpa_distinguish(params, multipliers, partial(simulated_rpa_oracle, simulate_mult_id = i))\n",
     "        table.append([mult, res, mult in res, len(res)])\n",
     "display(HTML(tabulate.tabulate(table, tablefmt=\"html\", headers=\"firstrow\")))"
@@ -591,14 +940,14 @@
    "outputs": [],
    "source": [
     "diff_real = normalize(simulated_rpa_trace(multipliers[0], scalar, P0_target.to_affine(), NormalNoice(0, 1)))\n",
-    "diff_nothing = normalize(simulated_rpa_trace(multipliers[5], scalar, P0_target.to_affine(), NormalNoice(0, 1)))\n",
+    "diff_nothing = normalize(simulated_rpa_trace(multipliers[7], scalar, P0_target.to_affine(), NormalNoice(0, 1)))\n",
     "plot_traces(diff_real, diff_nothing).opts(responsive=True, height=600)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "efea0ab4-1745-4a13-87fa-501f35cbe903",
+   "id": "9dc922b4-3123-489f-98e2-4c20f1d65816",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -620,7 +969,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,