SER calculation: Fix offset problem

1 files changed, 68 insertions, 109 deletions

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",