SER calculation: Fix offset problem

2 files changed, 308 insertions, 181 deletions

diff --git a/lab-windows/dsss_experiments-ber.ipynb b/lab-windows/dsss_experiments-ber.ipynb
index eda21d7..a5a2ad1 100644
--- a/lab-windows/dsss_experiments-ber.ipynb
+++ b/lab-windows/dsss_experiments-ber.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 92,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -14,6 +14,7 @@
     "import ipywidgets\n",
     "import itertools\n",
     "from multiprocessing import Pool\n",
+    "from collections import defaultdict\n",
     "\n",
     "import colorednoise\n",
     "\n",
@@ -154,11 +155,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 100,
    "metadata": {},
    "outputs": [],
    "source": [
-    "def run_ser_test(sample_duration=128, nbits=6, signal_amplitude=2.0e-3, decimation=10, threshold_factor=4.0, power_avg_width=2.5, max_lookahead=6.5, seed=0, ax=None, print=print):\n",
+    "def run_ser_test(sample_duration=128, nbits=6, signal_amplitude=2.0e-3, decimation=10, threshold_factor=4.0, power_avg_width=2.5, max_lookahead=6.5, seed=0, ax=None, print=print, ser_maxshift=3):\n",
     "\n",
     "    test_data, signal = generate_test_signal(sample_duration, nbits, signal_amplitude, decimation, seed)\n",
     "    cor_an = correlate(signal, nbits=nbits, decimation=decimation)\n",
@@ -271,14 +272,20 @@
     "\n",
     "    decoded = list(viz(chain))\n",
     "    print('decoding [ref|dec]:')\n",
-    "    failures = 0\n",
-    "    for i, (ref, found) in enumerate(itertools.zip_longest(test_data, decoded)):\n",
-    "        print(f'{ref or -1:>3d}|{found or -1:>3d} {\"✔\" if ref==found else \"✘\" if found else \" \"}', end='    ')\n",
-    "        if ref != found:\n",
-    "            failures += 1\n",
-    "        if i%8 == 7:\n",
+    "    failures = defaultdict(lambda: 0)\n",
+    "    for shift in range(-ser_maxshift, ser_maxshift):\n",
+    "        print(f'=== shift = {shift} ===')\n",
+    "        a = test_data if shift > 0 else test_data[-shift:]\n",
+    "        b = decoded if shift < 0 else decoded[shift:]\n",
+    "        for i, (ref, found) in enumerate(itertools.zip_longest(a, b)):\n",
+    "            print(f'{ref or -1:>3d}|{found or -1:>3d} {\"✔\" if ref==found else \"✘\" if found else \" \"}', end='    ')\n",
+    "            if ref != found:\n",
+    "                failures[shift] += 1\n",
+    "            if i%8 == 7:\n",
+    "                print()\n",
+    "        if i%8 != 7:\n",
     "            print()\n",
-    "    ser = failures/len(test_data)\n",
+    "    ser = min(failures.values())/len(test_data)\n",
     "    print(f'Symbol error rate e={ser}')\n",
     "    br = sampling_rate / decimation / (2**nbits) * nbits * (1 - ser) * 3600\n",
     "    print(f'maximum bitrate r={br} b/h')\n",
@@ -343,21 +350,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 111,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "<ipython-input-84-f36c7b0ffb61>:13: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
+      "<ipython-input-111-2589572e37aa>:13: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
       "  fig, ax = plt.subplots(figsize=(12, 9))\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b5eb2cd4f4224f75bc3dc73b6143d849",
+       "model_id": "794478ea08254c9da3608685434de9d6",
        "version_major": 2,
        "version_minor": 0
       },
@@ -373,73 +380,73 @@
      "output_type": "stream",
      "text": [
       "nbits=5\n",
-      "signal_amplitude=0.00029: ser=1.01000 ±0.012207515615390381, br=-5.62500\n",
-      "signal_amplitude=0.00020: ser=1.01469 ±0.013678792892649557, br=-8.26172\n",
-      "signal_amplitude=0.00052: ser=1.00406 ±0.018895270572288715, br=-2.28516\n",
-      "signal_amplitude=0.00043: ser=1.01000 ±0.018817586521655747, br=-5.62500\n",
-      "signal_amplitude=0.00024: ser=1.01156 ±0.014510233457804875, br=-6.50391\n",
-      "signal_amplitude=0.00036: ser=1.00687 ±0.014875787794264881, br=-3.86719\n",
-      "signal_amplitude=0.00032: ser=1.01156 ±0.01837117307087384, br=-6.50391\n",
-      "signal_amplitude=0.00022: ser=1.01000 ±0.013535254892317322, br=-5.62500\n",
-      "signal_amplitude=0.00057: ser=1.00281 ±0.012476540486048206, br=-1.58203\n",
-      "signal_amplitude=0.00039: ser=1.00812 ±0.014402148277253642, br=-4.57031\n",
-      "signal_amplitude=0.00047: ser=1.00438 ±0.012899854650343935, br=-2.46094\n",
-      "signal_amplitude=0.00027: ser=1.00937 ±0.014657549249448218, br=-5.27344\n",
-      "signal_amplitude=0.00063: ser=0.99938 ±0.019253652250936705, br=0.35156\n",
-      "signal_amplitude=0.00077: ser=0.99156 ±0.03231920868461974, br=4.74609\n",
-      "signal_amplitude=0.00093: ser=0.95156 ±0.06625442202223185, br=27.24609\n",
-      "signal_amplitude=0.00112: ser=0.76000 ±0.2099632594348354, br=135.00000\n",
-      "signal_amplitude=0.00136: ser=0.51375 ±0.30673813139223494, br=273.51562\n",
-      "signal_amplitude=0.00165: ser=0.39844 ±0.38814210912370745, br=338.37891\n",
-      "signal_amplitude=0.00070: ser=0.99281 ±0.023688242072809035, br=4.04297\n",
-      "signal_amplitude=0.00084: ser=0.96375 ±0.050769469787461836, br=20.39062\n",
-      "signal_amplitude=0.00102: ser=0.91063 ±0.10310321739645179, br=50.27344\n",
-      "signal_amplitude=0.00124: ser=0.72500 ±0.23567348639059932, br=154.68750\n",
-      "signal_amplitude=0.00150: ser=0.40969 ±0.3064419041596629, br=332.05078\n",
-      "signal_amplitude=0.00182: ser=0.32531 ±0.38085840544748384, br=379.51172\n",
-      "signal_amplitude=0.00200: ser=0.29000 ±0.3885339029608613, br=399.37500\n",
+      "signal_amplitude=0.00029: ser=0.99141 ±0.01434, br=4.83398\n",
+      "signal_amplitude=0.00020: ser=0.99344 ±0.01365, br=3.69141\n",
+      "signal_amplitude=0.00052: ser=0.98953 ±0.01621, br=5.88867\n",
+      "signal_amplitude=0.00024: ser=0.98984 ±0.01426, br=5.71289\n",
+      "signal_amplitude=0.00043: ser=0.98906 ±0.01531, br=6.15234\n",
+      "signal_amplitude=0.00036: ser=0.98859 ±0.01451, br=6.41602\n",
+      "signal_amplitude=0.00032: ser=0.98531 ±0.01621, br=8.26172\n",
+      "signal_amplitude=0.00022: ser=0.99125 ±0.01377, br=4.92188\n",
+      "signal_amplitude=0.00027: ser=0.99172 ±0.01339, br=4.65820\n",
+      "signal_amplitude=0.00047: ser=0.98938 ±0.01821, br=5.97656\n",
+      "signal_amplitude=0.00057: ser=0.98453 ±0.02223, br=8.70117\n",
+      "signal_amplitude=0.00039: ser=0.99328 ±0.01499, br=3.77930\n",
+      "signal_amplitude=0.00063: ser=0.97531 ±0.02277, br=13.88672\n",
+      "signal_amplitude=0.00077: ser=0.95766 ±0.03962, br=23.81836\n",
+      "signal_amplitude=0.00093: ser=0.89844 ±0.07690, br=57.12891\n",
+      "signal_amplitude=0.00112: ser=0.69250 ±0.15978, br=172.96875\n",
+      "signal_amplitude=0.00136: ser=0.34797 ±0.13550, br=366.76758\n",
+      "signal_amplitude=0.00165: ser=0.15875 ±0.07678, br=473.20312\n",
+      "signal_amplitude=0.00070: ser=0.97562 ±0.02444, br=13.71094\n",
+      "signal_amplitude=0.00084: ser=0.93437 ±0.05440, br=36.91406\n",
+      "signal_amplitude=0.00102: ser=0.83734 ±0.10122, br=91.49414\n",
+      "signal_amplitude=0.00124: ser=0.56047 ±0.18288, br=247.23633\n",
+      "signal_amplitude=0.00150: ser=0.24266 ±0.09904, br=426.00586\n",
+      "signal_amplitude=0.00182: ser=0.10359 ±0.03178, br=504.22852\n",
+      "signal_amplitude=0.00200: ser=0.06453 ±0.03562, br=526.20117\n",
       "nbits=6\n",
-      "signal_amplitude=0.00052: ser=1.00375 ±0.027432445434193427, br=-1.26562\n",
-      "signal_amplitude=0.00029: ser=1.01531 ±0.013528038013695853, br=-5.16797\n",
-      "signal_amplitude=0.00020: ser=1.02000 ±0.01698459780212649, br=-6.75000\n",
-      "signal_amplitude=0.00024: ser=1.01844 ±0.0197494066366562, br=-6.22266\n",
-      "signal_amplitude=0.00043: ser=1.01000 ±0.013535254892317322, br=-3.37500\n",
-      "signal_amplitude=0.00036: ser=1.01500 ±0.01860884366369926, br=-5.06250\n",
-      "signal_amplitude=0.00032: ser=1.00906 ±0.01443601182806387, br=-3.05859\n",
-      "signal_amplitude=0.00022: ser=1.01656 ±0.015200483133769137, br=-5.58984\n",
-      "signal_amplitude=0.00057: ser=0.98281 ±0.04926213365760764, br=5.80078\n",
-      "signal_amplitude=0.00027: ser=1.02000 ±0.015946688527716343, br=-6.75000\n",
-      "signal_amplitude=0.00047: ser=1.00687 ±0.02815276407388802, br=-2.32031\n",
-      "signal_amplitude=0.00039: ser=1.00906 ±0.016189792308735775, br=-3.05859\n",
-      "signal_amplitude=0.00077: ser=0.76906 ±0.23454244018940368, br=77.94141\n",
-      "signal_amplitude=0.00063: ser=0.94031 ±0.08557822627572974, br=20.14453\n",
-      "signal_amplitude=0.00112: ser=0.29750 ±0.347296478171029, br=237.09375\n",
-      "signal_amplitude=0.00093: ser=0.50125 ±0.3293776683952632, br=168.32812\n",
-      "signal_amplitude=0.00136: ser=0.37250 ±0.42536588111001566, br=211.78125\n",
-      "signal_amplitude=0.00165: ser=0.51000 ±0.46215950303980546, br=165.37500\n",
-      "signal_amplitude=0.00070: ser=0.90063 ±0.1848975645458858, br=33.53906\n",
-      "signal_amplitude=0.00084: ser=0.64687 ±0.26652421325275494, br=119.17969\n",
-      "signal_amplitude=0.00124: ser=0.38500 ±0.39889079606767064, br=207.56250\n",
-      "signal_amplitude=0.00102: ser=0.40875 ±0.3467111099315971, br=199.54688\n",
-      "signal_amplitude=0.00150: ser=0.40375 ±0.4435118198819508, br=201.23438\n",
-      "signal_amplitude=0.00182: ser=0.58531 ±0.46179168734397985, br=139.95703\n",
-      "signal_amplitude=0.00200: ser=0.61594 ±0.4584529436730666, br=129.62109\n"
+      "signal_amplitude=0.00024: ser=1.00156 ±0.01855, br=-0.52734\n",
+      "signal_amplitude=0.00020: ser=1.00172 ±0.01365, br=-0.58008\n",
+      "signal_amplitude=0.00052: ser=0.95688 ±0.04998, br=14.55469\n",
+      "signal_amplitude=0.00029: ser=1.00078 ±0.01391, br=-0.26367\n",
+      "signal_amplitude=0.00043: ser=0.98406 ±0.02215, br=5.37891\n",
+      "signal_amplitude=0.00036: ser=0.99844 ±0.01733, br=0.52734\n",
+      "signal_amplitude=0.00027: ser=0.99469 ±0.01339, br=1.79297\n",
+      "signal_amplitude=0.00032: ser=0.99766 ±0.01541, br=0.79102\n",
+      "signal_amplitude=0.00047: ser=0.97813 ±0.03233, br=7.38281\n",
+      "signal_amplitude=0.00022: ser=1.00016 ±0.01612, br=-0.05273\n",
+      "signal_amplitude=0.00057: ser=0.93609 ±0.07689, br=21.56836\n",
+      "signal_amplitude=0.00039: ser=0.99625 ±0.01883, br=1.26562\n",
+      "signal_amplitude=0.00063: ser=0.86875 ±0.08992, br=44.29688\n",
+      "signal_amplitude=0.00077: ser=0.58109 ±0.17566, br=141.38086\n",
+      "signal_amplitude=0.00093: ser=0.28594 ±0.13348, br=240.99609\n",
+      "signal_amplitude=0.00112: ser=0.12547 ±0.06352, br=295.15430\n",
+      "signal_amplitude=0.00165: ser=0.06500 ±0.01642, br=315.56250\n",
+      "signal_amplitude=0.00136: ser=0.08516 ±0.06513, br=308.75977\n",
+      "signal_amplitude=0.00070: ser=0.75609 ±0.15173, br=82.31836\n",
+      "signal_amplitude=0.00084: ser=0.46125 ±0.18383, br=181.82812\n",
+      "signal_amplitude=0.00102: ser=0.19703 ±0.10488, br=271.00195\n",
+      "signal_amplitude=0.00124: ser=0.10562 ±0.06833, br=301.85156\n",
+      "signal_amplitude=0.00182: ser=0.06563 ±0.02007, br=315.35156\n",
+      "signal_amplitude=0.00150: ser=0.06984 ±0.01818, br=313.92773\n",
+      "signal_amplitude=0.00200: ser=0.06500 ±0.02196, br=315.56250\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x7fe2bdd64430>"
+       "<matplotlib.legend.Legend at 0x7fe3073ed0a0>"
       ]
      },
-     "execution_count": 84,
+     "execution_count": 111,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "sample_duration=128\n",
-    "sample_reps = 25\n",
+    "sample_reps = 50\n",
     "sweep_points = 25\n",
     "\n",
     "default_params = dict(\n",
@@ -461,24 +468,185 @@
     "        params['nbits'] = nbits\n",
     "        sers, brs = [], []\n",
     "        for i in range(sample_reps):\n",
-    "            ser, br = run_ser_test(**params, sample_duration=sample_duration, print=noprint, seed=np.random.randint(0xffffffff))\n",
+    "            seed = np.random.randint(0xffffffff)\n",
+    "            ser, br = run_ser_test(**params, sample_duration=sample_duration, print=noprint, seed=seed)\n",
     "            sers.append(ser)\n",
     "            brs.append(br)\n",
+    "            #print(f'nbits={nbits} ampl={v:>.5f} seed={seed:08x} > ser={ser:.5f}')\n",
     "        sers, brs = np.array(sers), np.array(brs)\n",
-    "        ser = np.mean(sers)\n",
-    "        print(f'signal_amplitude={v:<.5f}: ser={ser:<.5f} ±{np.std(sers):<.5f}, br={np.mean(brs):<.5f}')\n",
-    "        return ser\n",
+    "        ser, std = np.mean(sers), np.std(sers)\n",
+    "        print(f'signal_amplitude={v:<.5f}: ser={ser:<.5f} ±{std:<.5f}, br={np.mean(brs):<.5f}')\n",
+    "        return ser, std\n",
     "    \n",
     "    vs = 0.2e-3 * 10 ** np.linspace(0, 1.0, sweep_points)\n",
     "    with Pool(6) as p:\n",
-    "        data = p.map(calculate_ser, vs)\n",
+    "        data = np.array(p.map(calculate_ser, vs))\n",
+    "        sers, stds = data[:,0], data[:,1]\n",
     "    \n",
-    "    ax.plot(vs, data, label=f'{nbits} bit')\n",
+    "    l, = ax.plot(vs, np.clip(sers, 0, 1), label=f'{nbits} bit')\n",
+    "    ax.fill_between(vs, np.clip(sers + stds, 0, 1), np.clip(sers - stds, 0, 1), facecolor=l.get_color(), alpha=0.3)\n",
     "ax.grid()\n",
     "ax.set_xlabel('Amplitude in mHz')\n",
     "ax.set_ylabel('Symbol error rate')\n",
     "ax.legend()"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "<ipython-input-101-d477d71c27f9>:1: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
+      "  fig, ax = plt.subplots(figsize=(12, 9))\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "cfaf2edf2f214ca6a3e97994a14a80f5",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "avg_peak 1.6752232386509318\n",
+      "skipped 2 symbols at 15749.0\n",
+      "skipped 3 symbols at 42209.0\n",
+      "skipped 2 symbols at 57959.5\n",
+      "skipped 2 symbols at 61108.5\n",
+      "skipped 2 symbols at 77489.5\n",
+      "decoding [ref|dec]:\n",
+      "=== shift = -3 ===\n",
+      "102| 69 ✘      2|124 ✘      3|102 ✘     78|  2 ✘     29|  3 ✘    122| 78 ✘     73| 29 ✘     98|123 ✘    \n",
+      " 34| 73 ✘     -1| 98 ✘     97| 34 ✘      7| -1       97| 97 ✔     86|  7 ✘    120| 97 ✘     95| 86 ✘    \n",
+      " 90|120 ✘     49| 95 ✘     89| 90 ✘     83| 49 ✘     19| 89 ✘     84| 83 ✘    117| -1       92| 84 ✘    \n",
+      "119|117 ✘     16| 92 ✘     45|119 ✘     23| 16 ✘     16| 45 ✘    111| 23 ✘      9| 16 ✘     89|111 ✘    \n",
+      " 18|  9 ✘     36| 89 ✘      2| 18 ✘    115| 36 ✘     40|  2 ✘    100|115 ✘    105| 40 ✘     93|100 ✘    \n",
+      " 85|105 ✘    107| 93 ✘     90| 85 ✘     62|107 ✘    116| 90 ✘     42| 62 ✘    123|116 ✘     40| 42 ✘    \n",
+      " -1|123 ✘     77| 40 ✘     40| -1       57| 77 ✘    110| 40 ✘     29| 57 ✘     94|110 ✘      1| 29 ✘    \n",
+      " 29| 94 ✘     71|  1 ✘    119| 29 ✘     15| 71 ✘    115|119 ✘    120| 15 ✘     70|115 ✘     50| -1      \n",
+      " 71| -1       50| 50 ✔     61| 71 ✘     38| 50 ✘      4| 61 ✘      3| 38 ✘    124|  4 ✘     95|  3 ✘    \n",
+      " 27|124 ✘     48| 95 ✘    116| 27 ✘      3| 64 ✘     63|116 ✘     19|  3 ✘     79| 63 ✘      2| 19 ✘    \n",
+      " 43| 79 ✘     92|  2 ✘      8| 43 ✘     65| 92 ✘     35|  8 ✘     30| 65 ✘     73| 35 ✘     73| 30 ✘    \n",
+      " 38| 73 ✘     58| -1       49| 38 ✘     45| 58 ✘     58| 49 ✘     46| 45 ✘    116| -1      101| 46 ✘    \n",
+      "  5|116 ✘     78|101 ✘    126|  5 ✘    105| 78 ✘    108|126 ✘     59| 76 ✘     46|108 ✘     27| 59 ✘    \n",
+      " 14| 46 ✘     57| 27 ✘     81| 14 ✘      3| 57 ✘      9| 81 ✘    126|  3 ✘     18|  9 ✘     76|126 ✘    \n",
+      "101| 55 ✘    124| 76 ✘      4|101 ✘      3|124 ✘    102|  4 ✘     79|  3 ✘    121|102 ✘    103| 79 ✘    \n",
+      " 92| -1       30|103 ✘      4| 92 ✘    103| 30 ✘     59|  4 ✘     -1|103 ✘     -1| 48 ✘    \n",
+      "=== shift = -2 ===\n",
+      "124| 69 ✘    102|124 ✘      2|102 ✘      3|  2 ✘     78|  3 ✘     29| 78 ✘    122| 29 ✘     73|123 ✘    \n",
+      " 98| 73 ✘     34| 98 ✘     -1| 34 ✘     97| -1        7| 97 ✘     97|  7 ✘     86| 97 ✘    120| 86 ✘    \n",
+      " 95|120 ✘     90| 95 ✘     49| 90 ✘     89| 49 ✘     83| 89 ✘     19| 83 ✘     84| -1      117| 84 ✘    \n",
+      " 92|117 ✘    119| 92 ✘     16|119 ✘     45| 16 ✘     23| 45 ✘     16| 23 ✘    111| 16 ✘      9|111 ✘    \n",
+      " 89|  9 ✘     18| 89 ✘     36| 18 ✘      2| 36 ✘    115|  2 ✘     40|115 ✘    100| 40 ✘    105|100 ✘    \n",
+      " 93|105 ✘     85| 93 ✘    107| 85 ✘     90|107 ✘     62| 90 ✘    116| 62 ✘     42|116 ✘    123| 42 ✘    \n",
+      " 40|123 ✘     -1| 40 ✘     77| -1       40| 77 ✘     57| 40 ✘    110| 57 ✘     29|110 ✘     94| 29 ✘    \n",
+      "  1| 94 ✘     29|  1 ✘     71| 29 ✘    119| 71 ✘     15|119 ✘    115| 15 ✘    120|115 ✘     70| -1      \n",
+      " 50| -1       71| 50 ✘     50| 71 ✘     61| 50 ✘     38| 61 ✘      4| 38 ✘      3|  4 ✘    124|  3 ✘    \n",
+      " 95|124 ✘     27| 95 ✘     48| 27 ✘    116| 64 ✘      3|116 ✘     63|  3 ✘     19| 63 ✘     79| 19 ✘    \n",
+      "  2| 79 ✘     43|  2 ✘     92| 43 ✘      8| 92 ✘     65|  8 ✘     35| 65 ✘     30| 35 ✘     73| 30 ✘    \n",
+      " 73| 73 ✔     38| -1       58| 38 ✘     49| 58 ✘     45| 49 ✘     58| 45 ✘     46| -1      116| 46 ✘    \n",
+      "101|116 ✘      5|101 ✘     78|  5 ✘    126| 78 ✘    105|126 ✘    108| 76 ✘     59|108 ✘     46| 59 ✘    \n",
+      " 27| 46 ✘     14| 27 ✘     57| 14 ✘     81| 57 ✘      3| 81 ✘      9|  3 ✘    126|  9 ✘     18|126 ✘    \n",
+      " 76| 55 ✘    101| 76 ✘    124|101 ✘      4|124 ✘      3|  4 ✘    102|  3 ✘     79|102 ✘    121| 79 ✘    \n",
+      "103| -1       92|103 ✘     30| 92 ✘      4| 30 ✘    103|  4 ✘     59|103 ✘     -1| 48 ✘    \n",
+      "=== shift = -1 ===\n",
+      " 69| 69 ✔    124|124 ✔    102|102 ✔      2|  2 ✔      3|  3 ✔     78| 78 ✔     29| 29 ✔    122|123 ✘    \n",
+      " 73| 73 ✔     98| 98 ✔     34| 34 ✔     -1| -1 ✔     97| 97 ✔      7|  7 ✔     97| 97 ✔     86| 86 ✔    \n",
+      "120|120 ✔     95| 95 ✔     90| 90 ✔     49| 49 ✔     89| 89 ✔     83| 83 ✔     19| -1       84| 84 ✔    \n",
+      "117|117 ✔     92| 92 ✔    119|119 ✔     16| 16 ✔     45| 45 ✔     23| 23 ✔     16| 16 ✔    111|111 ✔    \n",
+      "  9|  9 ✔     89| 89 ✔     18| 18 ✔     36| 36 ✔      2|  2 ✔    115|115 ✔     40| 40 ✔    100|100 ✔    \n",
+      "105|105 ✔     93| 93 ✔     85| 85 ✔    107|107 ✔     90| 90 ✔     62| 62 ✔    116|116 ✔     42| 42 ✔    \n",
+      "123|123 ✔     40| 40 ✔     -1| -1 ✔     77| 77 ✔     40| 40 ✔     57| 57 ✔    110|110 ✔     29| 29 ✔    \n",
+      " 94| 94 ✔      1|  1 ✔     29| 29 ✔     71| 71 ✔    119|119 ✔     15| 15 ✔    115|115 ✔    120| -1      \n",
+      " 70| -1       50| 50 ✔     71| 71 ✔     50| 50 ✔     61| 61 ✔     38| 38 ✔      4|  4 ✔      3|  3 ✔    \n",
+      "124|124 ✔     95| 95 ✔     27| 27 ✔     48| 64 ✘    116|116 ✔      3|  3 ✔     63| 63 ✔     19| 19 ✔    \n",
+      " 79| 79 ✔      2|  2 ✔     43| 43 ✔     92| 92 ✔      8|  8 ✔     65| 65 ✔     35| 35 ✔     30| 30 ✔    \n",
+      " 73| 73 ✔     73| -1       38| 38 ✔     58| 58 ✔     49| 49 ✔     45| 45 ✔     58| -1       46| 46 ✔    \n",
+      "116|116 ✔    101|101 ✔      5|  5 ✔     78| 78 ✔    126|126 ✔    105| 76 ✘    108|108 ✔     59| 59 ✔    \n",
+      " 46| 46 ✔     27| 27 ✔     14| 14 ✔     57| 57 ✔     81| 81 ✔      3|  3 ✔      9|  9 ✔    126|126 ✔    \n",
+      " 18| 55 ✘     76| 76 ✔    101|101 ✔    124|124 ✔      4|  4 ✔      3|  3 ✔    102|102 ✔     79| 79 ✔    \n",
+      "121| -1      103|103 ✔     92| 92 ✔     30| 30 ✔      4|  4 ✔    103|103 ✔     59| 48 ✘    \n",
+      "=== shift = 0 ===\n",
+      " 10| 69 ✘     69|124 ✘    124|102 ✘    102|  2 ✘      2|  3 ✘      3| 78 ✘     78| 29 ✘     29|123 ✘    \n",
+      "122| 73 ✘     73| 98 ✘     98| 34 ✘     34| -1       -1| 97 ✘     97|  7 ✘      7| 97 ✘     97| 86 ✘    \n",
+      " 86|120 ✘    120| 95 ✘     95| 90 ✘     90| 49 ✘     49| 89 ✘     89| 83 ✘     83| -1       19| 84 ✘    \n",
+      " 84|117 ✘    117| 92 ✘     92|119 ✘    119| 16 ✘     16| 45 ✘     45| 23 ✘     23| 16 ✘     16|111 ✘    \n",
+      "111|  9 ✘      9| 89 ✘     89| 18 ✘     18| 36 ✘     36|  2 ✘      2|115 ✘    115| 40 ✘     40|100 ✘    \n",
+      "100|105 ✘    105| 93 ✘     93| 85 ✘     85|107 ✘    107| 90 ✘     90| 62 ✘     62|116 ✘    116| 42 ✘    \n",
+      " 42|123 ✘    123| 40 ✘     40| -1       -1| 77 ✘     77| 40 ✘     40| 57 ✘     57|110 ✘    110| 29 ✘    \n",
+      " 29| 94 ✘     94|  1 ✘      1| 29 ✘     29| 71 ✘     71|119 ✘    119| 15 ✘     15|115 ✘    115| -1      \n",
+      "120| -1       70| 50 ✘     50| 71 ✘     71| 50 ✘     50| 61 ✘     61| 38 ✘     38|  4 ✘      4|  3 ✘    \n",
+      "  3|124 ✘    124| 95 ✘     95| 27 ✘     27| 64 ✘     48|116 ✘    116|  3 ✘      3| 63 ✘     63| 19 ✘    \n",
+      " 19| 79 ✘     79|  2 ✘      2| 43 ✘     43| 92 ✘     92|  8 ✘      8| 65 ✘     65| 35 ✘     35| 30 ✘    \n",
+      " 30| 73 ✘     73| -1       73| 38 ✘     38| 58 ✘     58| 49 ✘     49| 45 ✘     45| -1       58| 46 ✘    \n",
+      " 46|116 ✘    116|101 ✘    101|  5 ✘      5| 78 ✘     78|126 ✘    126| 76 ✘    105|108 ✘    108| 59 ✘    \n",
+      " 59| 46 ✘     46| 27 ✘     27| 14 ✘     14| 57 ✘     57| 81 ✘     81|  3 ✘      3|  9 ✘      9|126 ✘    \n",
+      "126| 55 ✘     18| 76 ✘     76|101 ✘    101|124 ✘    124|  4 ✘      4|  3 ✘      3|102 ✘    102| 79 ✘    \n",
+      " 79| -1      121|103 ✘    103| 92 ✘     92| 30 ✘     30|  4 ✘      4|103 ✘    103| 48 ✘     59| -1      \n",
+      "=== shift = 1 ===\n",
+      " 10|124 ✘     69|102 ✘    124|  2 ✘    102|  3 ✘      2| 78 ✘      3| 29 ✘     78|123 ✘     29| 73 ✘    \n",
+      "122| 98 ✘     73| 34 ✘     98| -1       34| 97 ✘     -1|  7 ✘     97| 97 ✔      7| 86 ✘     97|120 ✘    \n",
+      " 86| 95 ✘    120| 90 ✘     95| 49 ✘     90| 89 ✘     49| 83 ✘     89| -1       83| 84 ✘     19|117 ✘    \n",
+      " 84| 92 ✘    117|119 ✘     92| 16 ✘    119| 45 ✘     16| 23 ✘     45| 16 ✘     23|111 ✘     16|  9 ✘    \n",
+      "111| 89 ✘      9| 18 ✘     89| 36 ✘     18|  2 ✘     36|115 ✘      2| 40 ✘    115|100 ✘     40|105 ✘    \n",
+      "100| 93 ✘    105| 85 ✘     93|107 ✘     85| 90 ✘    107| 62 ✘     90|116 ✘     62| 42 ✘    116|123 ✘    \n",
+      " 42| 40 ✘    123| -1       40| 77 ✘     -1| 40 ✘     77| 57 ✘     40|110 ✘     57| 29 ✘    110| 94 ✘    \n",
+      " 29|  1 ✘     94| 29 ✘      1| 71 ✘     29|119 ✘     71| 15 ✘    119|115 ✘     15| -1      115| -1      \n",
+      "120| 50 ✘     70| 71 ✘     50| 50 ✔     71| 61 ✘     50| 38 ✘     61|  4 ✘     38|  3 ✘      4|124 ✘    \n",
+      "  3| 95 ✘    124| 27 ✘     95| 64 ✘     27|116 ✘     48|  3 ✘    116| 63 ✘      3| 19 ✘     63| 79 ✘    \n",
+      " 19|  2 ✘     79| 43 ✘      2| 92 ✘     43|  8 ✘     92| 65 ✘      8| 35 ✘     65| 30 ✘     35| 73 ✘    \n",
+      " 30| -1       73| 38 ✘     73| 58 ✘     38| 49 ✘     58| 45 ✘     49| -1       45| 46 ✘     58|116 ✘    \n",
+      " 46|101 ✘    116|  5 ✘    101| 78 ✘      5|126 ✘     78| 76 ✘    126|108 ✘    105| 59 ✘    108| 46 ✘    \n",
+      " 59| 27 ✘     46| 14 ✘     27| 57 ✘     14| 81 ✘     57|  3 ✘     81|  9 ✘      3|126 ✘      9| 55 ✘    \n",
+      "126| 76 ✘     18|101 ✘     76|124 ✘    101|  4 ✘    124|  3 ✘      4|102 ✘      3| 79 ✘    102| -1      \n",
+      " 79|103 ✘    121| 92 ✘    103| 30 ✘     92|  4 ✘     30|103 ✘      4| 48 ✘    103| -1       59| -1      \n",
+      "=== shift = 2 ===\n",
+      " 10|102 ✘     69|  2 ✘    124|  3 ✘    102| 78 ✘      2| 29 ✘      3|123 ✘     78| 73 ✘     29| 98 ✘    \n",
+      "122| 34 ✘     73| -1       98| 97 ✘     34|  7 ✘     -1| 97 ✘     97| 86 ✘      7|120 ✘     97| 95 ✘    \n",
+      " 86| 90 ✘    120| 49 ✘     95| 89 ✘     90| 83 ✘     49| -1       89| 84 ✘     83|117 ✘     19| 92 ✘    \n",
+      " 84|119 ✘    117| 16 ✘     92| 45 ✘    119| 23 ✘     16| 16 ✔     45|111 ✘     23|  9 ✘     16| 89 ✘    \n",
+      "111| 18 ✘      9| 36 ✘     89|  2 ✘     18|115 ✘     36| 40 ✘      2|100 ✘    115|105 ✘     40| 93 ✘    \n",
+      "100| 85 ✘    105|107 ✘     93| 90 ✘     85| 62 ✘    107|116 ✘     90| 42 ✘     62|123 ✘    116| 40 ✘    \n",
+      " 42| -1      123| 77 ✘     40| 40 ✔     -1| 57 ✘     77|110 ✘     40| 29 ✘     57| 94 ✘    110|  1 ✘    \n",
+      " 29| 29 ✔     94| 71 ✘      1|119 ✘     29| 15 ✘     71|115 ✘    119| -1       15| -1      115| 50 ✘    \n",
+      "120| 71 ✘     70| 50 ✘     50| 61 ✘     71| 38 ✘     50|  4 ✘     61|  3 ✘     38|124 ✘      4| 95 ✘    \n",
+      "  3| 27 ✘    124| 64 ✘     95|116 ✘     27|  3 ✘     48| 63 ✘    116| 19 ✘      3| 79 ✘     63|  2 ✘    \n",
+      " 19| 43 ✘     79| 92 ✘      2|  8 ✘     43| 65 ✘     92| 35 ✘      8| 30 ✘     65| 73 ✘     35| -1      \n",
+      " 30| 38 ✘     73| 58 ✘     73| 49 ✘     38| 45 ✘     58| -1       49| 46 ✘     45|116 ✘     58|101 ✘    \n",
+      " 46|  5 ✘    116| 78 ✘    101|126 ✘      5| 76 ✘     78|108 ✘    126| 59 ✘    105| 46 ✘    108| 27 ✘    \n",
+      " 59| 14 ✘     46| 57 ✘     27| 81 ✘     14|  3 ✘     57|  9 ✘     81|126 ✘      3| 55 ✘      9| 76 ✘    \n",
+      "126|101 ✘     18|124 ✘     76|  4 ✘    101|  3 ✘    124|102 ✘      4| 79 ✘      3| -1      102|103 ✘    \n",
+      " 79| 92 ✘    121| 30 ✘    103|  4 ✘     92|103 ✘     30| 48 ✘      4| -1      103| -1       59| -1      \n",
+      "Symbol error rate e=0.0859375\n",
+      "maximum bitrate r=308.49609375 b/h\n",
+      "nbits=6 ampl=0.00387 seed=cbb3b8cf > ser=0.08594\n"
+     ]
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(12, 9))\n",
+    "\n",
+    "params = dict(default_params)\n",
+    "params['signal_amplitude'] = 2.0e-3\n",
+    "params['nbits'] = 6\n",
+    "seed = 0xcbb3b8cf\n",
+    "ser, br = run_ser_test(**params, sample_duration=sample_duration, print=print, seed=seed, ax=ax)\n",
+    "print(f'nbits={nbits} ampl={v:>.5f} seed={seed:08x} > ser={ser:.5f}')"
+   ]
   }
  ],
  "metadata": {
diff --git a/lab-windows/dsss_experiments.ipynb b/lab-windows/dsss_experiments.ipynb
index f2bbc0b..ee35464 100644
--- a/lab-windows/dsss_experiments.ipynb
+++ b/lab-windows/dsss_experiments.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -21,7 +21,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -30,7 +30,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 105,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -48,7 +48,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -75,13 +75,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "01394154cc52483e9d4483f1178d94c3",
+       "model_id": "5081f9508a894fcf810e2d9c92c24a3e",
        "version_major": 2,
        "version_minor": 0
       },
@@ -102,10 +102,10 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x7fcfd7369250>"
+       "<matplotlib.image.AxesImage at 0x7ff8d9616610>"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -117,7 +117,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -133,7 +133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -157,7 +157,7 @@
        "       -1,  1,  1, -1,  1,  1,  1,  1, -1,  1,  1, -1, -1,  1, -1,  1,  1,  1,  1,  1, -1, -1, -1, -1,  1,  1,  1,  1, -1, -1,  1,  1])"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -178,7 +178,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -192,7 +192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -209,7 +209,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "182fd5ac86e74ad299a67e5f1d0b2b2b",
+       "model_id": "ec8de5680ba541938b7d1843b841c327",
        "version_major": 2,
        "version_minor": 0
       },
@@ -230,10 +230,10 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x7fcfd6c90070>"
+       "<matplotlib.image.AxesImage at 0x7ff8d955afa0>"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -260,13 +260,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "4cb2661eebb84478b06d285166ec13bc",
+       "model_id": "bb32b5050ee14ddc8eb64697a8eb774b",
        "version_major": 2,
        "version_minor": 0
       },
@@ -288,10 +288,10 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x7fcfd6c6cfa0>"
+       "<matplotlib.image.AxesImage at 0x7ff8d8eb9e20>"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -317,7 +317,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -330,7 +330,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a2e2f747193b478bbfa792a0995ad4ed",
+       "model_id": "48b3ae259e8046a5b90a82c4e80bab2e",
        "version_major": 2,
        "version_minor": 0
       },
@@ -352,10 +352,10 @@
     {
      "data": {
       "text/plain": [
-       "(2.0, 1.0234353995297893)"
+       "(2.0, 1.0121324810255907)"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -399,7 +399,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -419,7 +419,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 145,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -431,17 +431,9 @@
      ]
     },
     {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "<ipython-input-145-babcf8a4e867>:33: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
-      "  fig, ((ax1, ax3), (ax2, ax4)) = plt.subplots(2, 2, figsize=(16, 9))\n"
-     ]
-    },
-    {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "10aa67d294304f2ba26c8e6d5555d5e6",
+       "model_id": "73f4caf6a80f448183c41b711412a471",
        "version_major": 2,
        "version_minor": 0
       },
@@ -455,10 +447,10 @@
     {
      "data": {
       "text/plain": [
-       "(0.002, 0.014074279)"
+       "(0.0020000000000000005, 0.014544699)"
       ]
      },
-     "execution_count": 145,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -470,7 +462,7 @@
     "\n",
     "#test_data = np.random.randint(0, 2, 100)\n",
     "#test_data = np.array([0, 1, 0, 0, 1, 1, 1, 0])\n",
-    "test_data = np.random.RandomState(seed=0).randint(0, 2 * (2**nbits), 64)\n",
+    "test_data = np.random.RandomState(seed=0xcbb3b8cf).randint(0, 2 * (2**nbits), 128)\n",
     "#test_data = np.random.RandomState(seed=0).randint(0, 8, 64)\n",
     "#test_data = np.array(list(range(8)) * 8)\n",
     "#test_data = np.array([0, 1] * 32)\n",
@@ -542,13 +534,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c08b2a1dbdef429eb22b598bd3dc0146",
+       "model_id": "9fa8fa6a6837412da95630c634a12e21",
        "version_major": 2,
        "version_minor": 0
       },
@@ -569,10 +561,10 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7fcfd1635700>]"
+       "[<matplotlib.lines.Line2D at 0x7ff8ad6f3b50>]"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -592,13 +584,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "20117316e02548a99386c39e45e71ef1",
+       "model_id": "854dec05e45340ae91cf271b2facd7ed",
        "version_major": 2,
        "version_minor": 0
       },
@@ -623,7 +615,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-15-f158dfc14cca>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0msosh\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbutter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'highpass'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'sos'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdecimation\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0msosl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbutter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.8\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'lowpass'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'sos'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdecimation\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0mcor2_pe_flt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msosfilt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msosh\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcor2_pe\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     11\u001b[0m \u001b[0mcor2_pe_flt2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msosfilt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msosh\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msosfiltfilt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msosl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcor2_pe\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m<ipython-input-24-f158dfc14cca>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0msosh\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbutter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'highpass'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'sos'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdecimation\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0msosl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbutter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.8\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'lowpass'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'sos'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdecimation\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0mcor2_pe_flt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msosfilt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msosh\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcor2_pe\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     11\u001b[0m \u001b[0mcor2_pe_flt2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msosfilt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msosh\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msosfiltfilt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msosl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcor2_pe\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
       "\u001b[0;31mNameError\u001b[0m: name 'cor2_pe' is not defined"
      ]
     }
@@ -650,21 +642,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "<ipython-input-57-3e7dc7c98d30>:1: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
-      "  fig, ax = plt.subplots()\n"
-     ]
-    },
-    {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "25fe274dea83415491fd7f86d38188d7",
+       "model_id": "b3f68635d3ad4863b990c0b6e742840b",
        "version_major": 2,
        "version_minor": 0
       },
@@ -678,10 +662,10 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7fcf84cb4a60>]"
+       "[<matplotlib.lines.Line2D at 0x7ff8a9b7a820>]"
       ]
      },
-     "execution_count": 57,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -695,21 +679,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 146,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "<ipython-input-146-badd40342f73>:11: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
-      "  fig, (ax1, ax3) = plt.subplots(2, figsize=(12, 5))\n"
-     ]
-    },
-    {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "509bf67d93b74741b48bca58529c4b9d",
+       "model_id": "e6e78aec5f92465fbda1d231f7123196",
        "version_major": 2,
        "version_minor": 0
       },
@@ -724,22 +700,30 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "cor_an (65, 40949)\n",
-      "cwt_res (65, 40949)\n",
-      "th (65, 40949)\n",
+      "cor_an (65, 81269)\n",
+      "cwt_res (65, 81269)\n",
+      "th (65, 81269)\n",
       "[((65,), (65,)), ((65,), (65,)), ((65,), (65,)), ((65,), (65,)), ((65,), (65,))]\n",
-      "peaks: 982\n",
-      "avg_peak 1.6673786030736735\n",
-      "skipped 2 symbols at 30238.5\n",
+      "peaks: 1852\n",
+      "avg_peak 1.6610203317347632\n",
+      "skipped 3 symbols at 42209.0\n",
       "decoding [ref|dec]:\n",
-      " 44| 44 ✔     47| 47 ✔    117|117 ✔     64| 64 ✔     67| 67 ✔    123|123 ✔     67| 67 ✔    103|103 ✔    \n",
-      "  9|  9 ✔     83| 83 ✔     21| 21 ✔    114|114 ✔     36| 36 ✔     87| 87 ✔     70| 70 ✔     88| 88 ✔    \n",
-      " 88| 88 ✔     12| 12 ✔     58| 58 ✔     65| 65 ✔    102|102 ✔     39| 39 ✔     87| 87 ✔     46| 46 ✔    \n",
-      " 88| 88 ✔     81| 81 ✔     37| 37 ✔     25| 25 ✔     77| 77 ✔     72| 72 ✔      9|  9 ✔     20| 20 ✔    \n",
-      "115|115 ✔     80| 80 ✔    115|115 ✔     69| 69 ✔    126|126 ✔     79| 79 ✔     47| 47 ✔     64| 64 ✔    \n",
-      " 82| 82 ✔     99| 99 ✔     88| 88 ✔     49| 49 ✔    115|115 ✔     29| 29 ✔     19| -1       19| 19 ✔    \n",
-      " 14| 14 ✔     39| 39 ✔     32| 32 ✔     65| 64 ✘      9|  9 ✔     57| 57 ✔    127|127 ✔     32| 32 ✔    \n",
-      " 31| 31 ✔     74| 74 ✔    116|116 ✔     23| 23 ✔     35| 35 ✔    126|126 ✔     75| 75 ✔    114| 26 ✘    \n",
+      " 10| 10 ✔     69| 69 ✔    124|124 ✔    102|102 ✔      2|  2 ✔      3|  3 ✔     78| 78 ✔     29| 29 ✔    \n",
+      "122|123 ✘     73| 73 ✔     98| 98 ✔     34| 34 ✔     -1| -1 ✔     97| 97 ✔      7|  7 ✔     97| 97 ✔    \n",
+      " 86| 86 ✔    120|120 ✔     95| 95 ✔     90| 90 ✔     49| 49 ✔     89| 89 ✔     83| 83 ✔     19| 19 ✔    \n",
+      " 84| 84 ✔    117|117 ✔     92| 92 ✔    119|119 ✔     16| 16 ✔     45| 45 ✔     23| 23 ✔     16| 16 ✔    \n",
+      "111|111 ✔      9|  9 ✔     89| 89 ✔     18| 18 ✔     36| 36 ✔      2|  2 ✔    115|115 ✔     40| 40 ✔    \n",
+      "100|100 ✔    105|105 ✔     93| 93 ✔     85| 85 ✔    107|107 ✔     90| 90 ✔     62| 62 ✔    116|116 ✔    \n",
+      " 42| 42 ✔    123|123 ✔     40| 40 ✔     -1| -1 ✔     77| 77 ✔     40| 40 ✔     57| 57 ✔    110|110 ✔    \n",
+      " 29| 29 ✔     94| 94 ✔      1|  1 ✔     29| 29 ✔     71| 71 ✔    119|119 ✔     15| 15 ✔    115|115 ✔    \n",
+      "120| -1       70| -1       50| 50 ✔     71| 71 ✔     50| 50 ✔     61| 61 ✔     38| 38 ✔      4|  4 ✔    \n",
+      "  3|  3 ✔    124|124 ✔     95| 95 ✔     27| 27 ✔     48| 48 ✔    116|116 ✔      3|  3 ✔     63| 63 ✔    \n",
+      " 19| 19 ✔     79| 79 ✔      2|  2 ✔     43| 43 ✔     92| 92 ✔      8|  8 ✔     65| 65 ✔     35| 35 ✔    \n",
+      " 30| 30 ✔     73| 73 ✔     73| 73 ✔     38| 38 ✔     58| 58 ✔     49| 49 ✔     45| 45 ✔     58| 58 ✔    \n",
+      " 46| 46 ✔    116|116 ✔    101|101 ✔      5|  5 ✔     78| 78 ✔    126|126 ✔    105| 76 ✘    108|108 ✔    \n",
+      " 59| 59 ✔     46| 46 ✔     27| 27 ✔     14| 14 ✔     57| 57 ✔     81| 81 ✔      3|  3 ✔      9|  9 ✔    \n",
+      "126|126 ✔     18| 55 ✘     76| 76 ✔    101|101 ✔    124|124 ✔      4|  4 ✔      3|  3 ✔    102|102 ✔    \n",
+      " 79| 79 ✔    121|121 ✔    103|103 ✔     92| 92 ✔     30| 30 ✔      4|  4 ✔    103|103 ✔     59| 58 ✘    \n",
       "Symbol error rate e=0.046875\n",
       "maximum bitrate r=321.6796875 b/h\n"
      ]
@@ -896,34 +880,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "987be038c1b34e6e9509f7f224bbb620",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7f8fcb61c850>]"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, axs = plt.subplots(2, 1, figsize=(9, 7))\n",
     "fig.tight_layout()\n",