Finish DSSS demodulation stage 1

1 files changed, 98 insertions, 5 deletions

diff --git a/lab-windows/scratch.ipynb b/lab-windows/scratch.ipynb
index 671bedf..ddd2455 100644
--- a/lab-windows/scratch.ipynb
+++ b/lab-windows/scratch.ipynb
@@ -2,11 +2,12 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
     "import json\n",
+    "import csv\n",
     "\n",
     "import numpy as np\n",
     "from matplotlib import pyplot as plt\n",
@@ -17,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -170,13 +171,105 @@
    "source": [
     "sig.butter(8, 20e-3, output='sos', fs=10.0)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "655ce5c77d2a4047905245df39a095b0",
+       "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 0x7f4609ce6a90>]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "ax.plot([0-0.00012937261, 0-0.00022784119 , 0-0.00039295876 , 0-0.00066361829 , 00-0.0010971602 , 00-0.0017754816 ,\n",
+    "    00-0.0028116399 , 00-0.0043560231 , 00-0.0066005666 , 00-0.0097788338 , 000-0.014159188 , 000-0.020027947 ,\n",
+    "    000-0.027659611 , 000-0.037272236 , 000-0.048968014 , 0000-0.06266222 , 0000-0.07800759 , 000-0.094325546 ,\n",
+    "    0000-0.11055938 , 0000-0.12526666 , 0000-0.13666715 , 0000-0.14275811 , 0000-0.14149973 , 00000-0.1310612 ,\n",
+    "    0000-0.11010384 , 000-0.078063987 , 000-0.035389599 , 00000.016317957 , 00000.074297836 , 000000.13478363 ,\n",
+    "    000000.19331697 , 000000.24519242 , 000000.28597909 , 000000.31204596 , 000000.32101141 , 000000.31204596 ,\n",
+    "    000000.28597909 , 000000.24519242 , 000000.19331697 , 000000.13478363 , 00000.074297836 , 00000.016317957 ,\n",
+    "    000-0.035389599 , 000-0.078063987 , 0000-0.11010384 , 00000-0.1310612 , 0000-0.14149973 , 0000-0.14275811 ,\n",
+    "    0000-0.13666715 , 0000-0.12526666 , 0000-0.11055938 , 000-0.094325546 , 0000-0.07800759 , 0000-0.06266222 ,\n",
+    "    000-0.048968014 , 000-0.037272236 , 000-0.027659611 , 000-0.020027947 , 000-0.014159188 , 00-0.0097788338 ,\n",
+    "    00-0.0066005666 , 00-0.0043560231 , 00-0.0028116399 , 00-0.0017754816 , 00-0.0010971602 , 0-0.00066361829 ,\n",
+    "    0-0.00039295876 , 0-0.00022784119 , 0-0.00012937261 ])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = np.genfromtxt('/tmp/foo.csv', delimiter=',')[1000:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7c771472882e4ceeb8aeddfa5c08ca17",
+       "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"
+    }
+   ],
+   "source": [
+    "fig, axs = plt.subplots(2, figsize=(15, 9), sharex=True)\n",
+    "axs = axs.flatten()\n",
+    "axs[0].set_title('corr')\n",
+    "axs[1].set_title('cwt')\n",
+    "#axs[2].set_title('iir')\n",
+    "\n",
+    "axs[0].plot(data[:,0], label='corr')\n",
+    "axs[1].plot(data[:,1], label='cwt')\n",
+    "axs[0].plot(data[:,2], label='avg')\n",
+    "axs[1].plot(data[:,2], label='avg')\n",
+    "\n",
+    "for ax in axs:\n",
+    "    ax.legend()\n",
+    "    ax.grid()"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "winlabenv",
+   "display_name": "labenv",
    "language": "python",
-   "name": "winlabenv"
+   "name": "labenv"
   },
   "language_info": {
    "codemirror_mode": {
@@ -188,7 +281,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.8.1"
   }
  },
  "nbformat": 4,