{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "93c40dea",
   "metadata": {},
   "source": [
    "# FMCW Intro - Target speed\n",
    "\n",
    "You can open this workbook in Google Colab to experiment with mmWrt \n",
    "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/matt-chv/mmWrt/blob/main/docs/Speed.ipynb)\n",
    "\n",
    "Below is an intro to mmWrt for simple targets position and speed estimation based on 2D FFT Range Doppler\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df9597cc",
   "metadata": {},
   "source": [
    "## The problem\n",
    "\n",
    "As distance changes over time, how can FMCW radar measure speed ?\n",
    "\n",
    "## The solution\n",
    "\n",
    "A 2D FFT will allow to measure the speed of the targets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a484170f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running from git folder, using local path (latest) mmWrt code c:\\git\\mmWrt\n",
      "2026-06-29 21:13:22.168194\n"
     ]
    }
   ],
   "source": [
    "# Install a pip package in the current Jupyter kernel\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "import sys\n",
    "from os.path import abspath, basename, join, pardir\n",
    "import datetime\n",
    "\n",
    "# hack to handle if running from git cloned folder or stand alone (like Google Colab)\n",
    "cw = basename(abspath(join(\".\")))\n",
    "dp = abspath(join(\".\",pardir))\n",
    "if cw==\"docs\" and basename(dp) == \"mmWrt\":\n",
    "    # running from cloned folder\n",
    "    print(\"running from git folder, using local path (latest) mmWrt code\", dp)\n",
    "    sys.path.insert(0, dp)\n",
    "else:\n",
    "    print(\"running standalone, need to ensure mmWrt is installed\")\n",
    "    !{sys.executable} -m pip install mmWrt\n",
    "print(datetime.datetime.now())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "242be93b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0.11-pre.3\n"
     ]
    }
   ],
   "source": [
    "from os.path import abspath, join, pardir\n",
    "import sys\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.cm as cm\n",
    "from matplotlib import colors\n",
    "from numpy import where, expand_dims\n",
    "from numpy import complex128 as complex\n",
    "\n",
    "# uncomment below if the notebook is launched from project's root folder\n",
    "# dp = abspath(join(\".\",pardir))\n",
    "# sys.path.insert(0, dp)\n",
    "\n",
    "\n",
    "from mmWrt.Raytracing import rt_points  # noqa: E402\n",
    "from mmWrt.Scene import Radar, Transmitter, Receiver, Scatterer  # noqa: E402\n",
    "from mmWrt import RadarSignalProcessing as rsp  # noqa: E402\n",
    "from mmWrt import __version__ as mmWrt_ver\n",
    "print(mmWrt_ver)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c8d1d8c",
   "metadata": {},
   "source": [
    "## Step by step\n",
    "\n",
    "Looking at multiple 1D FFT before doing a 2D FFT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d8d8e108",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(32, 64)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.fft import fft, fft2\n",
    "c = 3e8\n",
    "\n",
    "debug_ON = False\n",
    "test = 0\n",
    "NC=32\n",
    "NA=64\n",
    "fs0 = 1e5\n",
    "slope0 = 28e10\n",
    "tic0 = 1.2e-3\n",
    "bw=0.2e9\n",
    "chirp_end_time0 = bw/slope0\n",
    "radar = Radar(transmitter=Transmitter(chirp_end_time=chirp_end_time0, chirp_slope=slope0,\n",
    "                                      chirp_period=tic0,\n",
    "                                      chirp_count=NC),\n",
    "              receiver=Receiver(adc_sample_rate=fs0, adc_sample_count=NA,\n",
    "                                adc_sample_count_max=256,\n",
    "                                debug=debug_ON), debug=debug_ON)\n",
    "\n",
    "x1, v1 = 5, 0\n",
    "target1 = Scatterer(xt=lambda t: v1*t+x1)\n",
    "x2, v2 = 3, 0.6\n",
    "target2 = Scatterer(xt=lambda t: v2*t+x2)\n",
    "\n",
    "scatterers = [target1, target2]\n",
    "\n",
    "bb = rt_points([radar], scatterers, \n",
    "               radar, datatype=complex, debug=debug_ON)\n",
    "cube = bb[\"adc_cube\"][0,:,0,:]\n",
    "print(cube.shape)\n",
    "Z_fft2 = abs(fft2(cube))\n",
    "Data_fft2 = Z_fft2\n",
    "\n",
    "plt.xlabel(\"Range\")\n",
    "plt.ylabel(\"Velocity\")\n",
    "plt.title('Velocity-Range 2D FFT')\n",
    "plt.imshow(Data_fft2[0:NC//2,:NA//2])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61c36205-f026-4967-852b-8f22e234caf9",
   "metadata": {},
   "source": [
    "## Plotting the Range Doppler with units\n",
    "\n",
    "> leveraging the plot_range_doppler utility function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ed4a514b-7374-4656-a207-8ad7de4356ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mmWrt.Plots import plot_range_doppler\n",
    "fig, _, _ = plot_range_doppler(bb[\"adc_cube\"][0,:,0,:], radar, no_speed_shift=False)\n",
    "\n",
    "# adding comments in picture\n",
    "fig.text(0.3, 0.5, f\"target1: @d={x1}, v={v1}\", color=\"white\", fontsize=12)\n",
    "target1 = plt.Circle((0.22, 0.48), 0.05, fill=False, color=\"white\")\n",
    "fig.text(0.30, 0.25, f\"target2: @d={x2}, v={v2}\", color=\"white\", fontsize=12)\n",
    "target2 = plt.Circle((0.2, 0.25), 0.05, fill=False, color=\"white\")\n",
    "fig.add_artist(target1)\n",
    "fig.add_artist(target2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88123e00-3d39-49de-a7cb-0885d88105fa",
   "metadata": {},
   "source": [
    "## Illustration of 1D FFT and 2D FFT"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e630151e-2526-42b5-ae42-8f92907b606a",
   "metadata": {},
   "source": [
    "### Plot all the range FFT\n",
    "\n",
    "> Scroll output of next cell to see all the range FFTs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b92cc7a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\matth\\AppData\\Local\\Temp\\ipykernel_20228\\360286218.py:2: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed in 3.11. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap()`` or ``pyplot.get_cmap()`` instead.\n",
      "  cmap = cm.get_cmap(name='CMRmap_r')\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAi8AAAGzCAYAAADnmPfhAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvZiW1igAAAAlwSFlzAAAPYQAAD2EBqD+naQAAHaNJREFUeJzt3QuQVnX9+PHPLpdFEhYJAVEQUQMJxRGEMP1pSYL2NywrL5hgBKOJmrdRnAIv02CF5I1k1Ix/k4hZaeUUE17Q0UgEclJTJv1p4AWR/HMREnD3+c85DRury7Ls+vjsl+f1mjmuz3nO2ee7h7Psm3N5tqJQKBQCACARlaUeAADArhAvAEBSxAsAkBTxAgAkRbwAAEkRLwBAUsQLAJAU8QIAJEW8AABJES8AQFLEC9Ai7777bkybNi1Gjx4dXbt2jYqKipgzZ06Dyx533HH589lUWVkZnTt3jv79+8c3vvGNWLBgQZNfc/z48XWf54PT/Pnz82VeffXVHS7zmc98Jq6++uodPr/9lI0ZaF3alnoAQNrWrFkT1157bfTp0ycGDx4cCxcubHT5/fbbL6ZPn57//8aNG+Oll16K3/zmN/GLX/wivv71r+cf27Vrt9PXraqqijvvvPND87MxbO+MM86Ik046qd68vffeO/bZZ5846KCD6kXYeeedF1/+8pfjK1/5St38Hj167HQswMdLvAAtkkXAm2++GT179owlS5bEkUce2ejy1dXVcdZZZ9Wbd/3118eFF14YP/nJT6Jv377xgx/8YKev27Zt2w99noYcccQRO1zusMMOqxdhWbxk85ryeYHScdoIaJHsCEgWLi3Rpk2buPnmm2PgwIFx6623xrp16z6y8QG7H/ECtApZwGSneDZt2hRPPPFEk9bJjpZsPzUUPdnn++ByW7duLcJXAHxcxAvQagwaNCj/+PLLL+902ex6mezale2nMWPGfGi57GLiDy735JNPFmX8wMfDNS9Aq7HnnnvmHzds2LDTZTt06BC///3v683ba6+9PrTcpEmT4mtf+1qjF/UCaREvQKuR3fGT6dSpU5NOM40cOXKnyx188MFNWg5Ih9NGQKvx3HPP5R+3v4UZ4IPEC9Aq1NTUxNy5c6Njx45x9NFHl3o4QCsmXoBWES7Z+7y88MIL+cfsnXcBdsQ1L0CLZe/Nsnbt2njjjTfyx9mFtK+99lr+/xdccEH+xnTbZLczZ++iu+025m3vsJvdYXT66afHddddV6KvAkiFeAFabMaMGfHPf/6z7nEWI9mUyd6tdvt4yaIm+11G2+4uyt6hd8SIEXHbbbfFF77whRKMHkhNRaFQKJR6EAAATeWaFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIym73Pi+1tbX5G2Vlv9itoqKi1MMBAJoge+eW7DfK9+rVKyorK8srXrJw6d27d6mHAQA0w8qVK2O//fYrr3jJjrhk/v716ujUvnlHXtpsbv5mafN692iJa/7fBc1e955V/7dFr73o4qebve6AqTUteu3//d+bm71udfWYFr1227ZdolRqa98rybr/0fw/s0Lh/Ra9ckvG3tLXbrmW7estUcqvvfTbvTTK9esuhQ0bNkb//v+n7ud4WcXLtlNFWbh0bm681Db/UqA2bdtES1S12aPZ61ZUtOyPs1OH0p1m69Sp+V93S3+JX9u2pfslgLW17Uuy7n+8X8J4aVey12658gyI0m/30ijXr7uUmnLJhwt2AYCkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACApRYuXd955J8aOHRudO3eOLl26xIQJE+Ldd99t0rqFQiFOPPHEqKioiAceeKBYQwQAElS0eMnC5fnnn48FCxbEgw8+GI8//nhMmjSpSeveeOONebgAAHxQ2yiCF154IebPnx9PP/10DB06NJ93yy23xEknnRQzZsyIXr167XDdZ555Jm644YZYsmRJ7LPPPsUYHgCQsKIceVm0aFF+qmhbuGRGjhwZlZWV8dRTT+1wvU2bNsWZZ54Zs2bNip49ezbptTZv3hzr16+vNwEAu6+ixMuqVauie/fu9ea1bds2unbtmj+3IxdffHEcddRRMWbMmCa/1vTp06O6urpu6t27d4vGDgDsRvFy5ZVX5teiNDa9+OKLzRrI7373u3jkkUfy6112xZQpU2LdunV108qVK5v1+gDAbnjNy6WXXhrjx49vdJl+/frlp3xWr15db/7777+f34G0o9NBWbi8/PLL+emm7Z166qlxzDHHxMKFCxtcr6qqKp8AgPKwS/Gy995759POjBgxItauXRtLly6NIUOG1MVJbW1tDB8+fIdHdb71rW/Vm3fooYfGj3/84zj55JN3ZZgAwG6sKHcbHXLIITF69OiYOHFizJ49O7Zu3RqTJ0+O008/ve5Oo9dffz2OP/74+PnPfx7Dhg3Lj8g0dFSmT58+ccABBxRjmABAgor2Pi933313DBgwIA+U7Bbpo48+Om6//fa657OgWb58eX6HEQBASY+8ZLI7i+bOnbvD5/v27Zu/k25jdvY8AFB+/G4jACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSUrR4eeedd2Ls2LHRuXPn6NKlS0yYMCHefffdRpe/4IILon///rHHHntEnz594sILL4x169YVa4gAQIKKFi9ZuDz//POxYMGCePDBB+Pxxx+PSZMm7XD5N954I59mzJgRzz33XMyZMyfmz5+fRw8AwDZtowheeOGFPDyefvrpGDp0aD7vlltuiZNOOimPk169en1onUGDBsWvf/3ruscHHnhgfP/734+zzjor3n///WjbtihDBQASU5QjL4sWLcpPFW0Ll8zIkSOjsrIynnrqqSZ/nuyUUXbaqbFw2bx5c6xfv77eBADsvooSL6tWrYru3bvXm5cFSNeuXfPnmmLNmjVx3XXXNXqqKTN9+vSorq6um3r37t2isQMAu1G8XHnllVFRUdHo9OKLL7Z4UNnRky9+8YsxcODAuPrqqxtddsqUKfkRmm3TypUrW/z6AEDrtUsXklx66aUxfvz4Rpfp169f9OzZM1avXl1vfnbdSnZHUfZcYzZs2BCjR4+OTp06xf333x/t2rVrdPmqqqp8AgDKwy7Fy957751POzNixIhYu3ZtLF26NIYMGZLPe+SRR6K2tjaGDx/e6BGXUaNG5THyu9/9Ljp06LArwwMAykBRrnk55JBD8qMnEydOjMWLF8eTTz4ZkydPjtNPP73uTqPXX389BgwYkD+/LVxOOOGE2LhxY/z0pz/NH2fXx2RTTU1NMYYJACSoaPcf33333XmwHH/88fldRqeeemrcfPPNdc9v3bo1li9fHps2bcofL1u2rO5OpIMOOqje53rllVeib9++xRoqAJCQosVLdmfR3Llzd/h8FiOFQqHu8XHHHVfvMQBAQ/xuIwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkvKxxMusWbOib9++0aFDhxg+fHgsXry40eXvu+++GDBgQL78oYceGn/4wx8+jmECAAkoerzce++9cckll8S0adNi2bJlMXjw4Bg1alSsXr26weX//Oc/xxlnnBETJkyIv/71r3HKKafk03PPPVfsoQIACSh6vMycOTMmTpwY55xzTgwcODBmz54dHTt2jLvuuqvB5W+66aYYPXp0XH755XHIIYfEddddF0cccUTceuutDS6/efPmWL9+fb0JANh9FTVetmzZEkuXLo2RI0f+9wUrK/PHixYtanCdbP72y2eyIzU7Wn769OlRXV1dN/Xu3fsj/ioAgLKJlzVr1kRNTU306NGj3vzs8apVqxpcJ5u/K8tPmTIl1q1bVzetXLnyI/wKAIDWpm0krqqqKp8AgPJQ1CMv3bp1izZt2sRbb71Vb372uGfPng2uk83fleUBgPJS1Hhp3759DBkyJB5++OG6ebW1tfnjESNGNLhONn/75TMLFizY4fIAQHkp+mmj7DbpcePGxdChQ2PYsGFx4403xsaNG/O7jzJnn3127LvvvvmFt5mLLroojj322Ljhhhvii1/8YsybNy+WLFkSt99+e7GHCgAkoOjxctppp8Xbb78dU6dOzS+6Pfzww2P+/Pl1F+WuWLEivwNpm6OOOirmzp0b3/3ud+Oqq66Kgw8+OB544IEYNGhQsYcKACTgY7lgd/LkyfnUkIULF35o3te+9rV8AgD4IL/bCABIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApHws8TJr1qzo27dvdOjQIYYPHx6LFy/e4bJ33HFHHHPMMbHXXnvl08iRIxtdHgAoL0WPl3vvvTcuueSSmDZtWixbtiwGDx4co0aNitWrVze4/MKFC+OMM86IRx99NBYtWhS9e/eOE044IV5//fViDxUASEDR42XmzJkxceLEOOecc2LgwIExe/bs6NixY9x1110NLn/33XfHt7/97Tj88MNjwIABceedd0ZtbW08/PDDDS6/efPmWL9+fb0JANh9FTVetmzZEkuXLs1P/dS9YGVl/jg7qtIUmzZtiq1bt0bXrl0bfH769OlRXV1dN2VHagCA3VdR42XNmjVRU1MTPXr0qDc/e7xq1aomfY4rrrgievXqVS+AtjdlypRYt25d3bRy5cqPZOwAQOvUNlqx66+/PubNm5dfB5Nd7NuQqqqqfAIAykNR46Vbt27Rpk2beOutt+rNzx737Nmz0XVnzJiRx8tDDz0Uhx12WDGHCQAkpKinjdq3bx9Dhgypd7HttotvR4wYscP1fvjDH8Z1110X8+fPj6FDhxZziABAYop+2ii7TXrcuHF5hAwbNixuvPHG2LhxY373Uebss8+OfffdN7/wNvODH/wgpk6dGnPnzs3fG2bbtTF77rlnPgEA5a3o8XLaaafF22+/nQdJFiLZLdDZEZVtF/GuWLEivwNpm9tuuy2/S+mrX/1qvc+TvU/M1VdfXezhAgCt3Mdywe7kyZPzqSHZxbjbe/XVVz+OIQEAifK7jQCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACApH0u8zJo1K/r27RsdOnSI4cOHx+LFi5u03rx586KioiJOOeWUoo8RAEhD0ePl3nvvjUsuuSSmTZsWy5Yti8GDB8eoUaNi9erVja736quvxmWXXRbHHHNMsYcIACSk6PEyc+bMmDhxYpxzzjkxcODAmD17dnTs2DHuuuuuHa5TU1MTY8eOjWuuuSb69etX7CECAAkparxs2bIlli5dGiNHjvzvC1ZW5o8XLVq0w/Wuvfba6N69e0yYMGGnr7F58+ZYv359vQkA2H0VNV7WrFmTH0Xp0aNHvfnZ41WrVjW4zhNPPBE//elP44477mjSa0yfPj2qq6vrpt69e38kYwcAWqdWdbfRhg0b4hvf+EYeLt26dWvSOlOmTIl169bVTStXriz6OAGA0mlbzE+eBUibNm3irbfeqjc/e9yzZ88PLf/yyy/nF+qefPLJdfNqa2v/M9C2bWP58uVx4IEH1lunqqoqnwCA8lDUIy/t27ePIUOGxMMPP1wvRrLHI0aM+NDyAwYMiGeffTaeeeaZuulLX/pSfO5zn8v/3ykhAKCoR14y2W3S48aNi6FDh8awYcPixhtvjI0bN+Z3H2XOPvvs2HffffNrV7L3gRk0aFC99bt06ZJ//OB8AKA8FT1eTjvttHj77bdj6tSp+UW6hx9+eMyfP7/uIt4VK1bkdyABALSKeMlMnjw5nxqycOHCRtedM2dOkUYFAKTIIQ8AICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAEiKeAEAkiJeAICkiBcAICniBQBIingBAJIiXgCApIgXACApbWM3UygU8o8btvznY3O02Vrb/HXfr4mW2Fzz72avWyi836LX3vBe87dZS23Y0Pyvu7JyfYteu23b0jV8be17JVn3P2pKtq+1ZOwtfe2Wa9n3eEuU8msv/XYvjXL9ukthw4aN9X6ON6ai0JSlEvLaa69F7969Sz0MAKAZVq5cGfvtt195xUttbW288cYb0alTp6ioqPjQ8+vXr8/jJts4nTt3LskYU2ObNY/ttutss+ax3Xadbdb6tluWIxs2bIhevXpFZWVleZ02yr7gnRVbJtvodthdY5s1j+2262yz5rHddp1t1rq2W3V1dZOWc8EuAJAU8QIAJKXs4qWqqiqmTZuWf6RpbLPmsd12nW3WPLbbrrPN0t5uu90FuwDA7q3sjrwAAGkTLwBAUsQLAJAU8QIAJEW8AABJKat4mTVrVvTt2zc6dOgQw4cPj8WLF5d6SK3a1Vdfnf+Khe2nAQMGlHpYrc7jjz8eJ598cv6W1tk2euCBB+o9n93QN3Xq1Nhnn31ijz32iJEjR8Y//vGPKGc722bjx4//0L43evToKGfTp0+PI488Mv/VJ927d49TTjklli9fXm+Z9957L84///z45Cc/GXvuuWeceuqp8dZbb0U5a8p2O+644z60v5177rlRrm677bY47LDD6t5Fd8SIEfHHP/6xVe1nZRMv9957b1xyySX5/enLli2LwYMHx6hRo2L16tWlHlqr9ulPfzrefPPNuumJJ54o9ZBanY0bN+b7UxbHDfnhD38YN998c8yePTueeuqp+MQnPpHve9lfAOVqZ9ssk8XK9vvePffcE+Xssccey39g/OUvf4kFCxbE1q1b44QTTsi35TYXX3xx/P73v4/77rsvXz77PW9f+cpXopw1ZbtlJk6cWG9/y75vy9V+++0X119/fSxdujSWLFkSn//852PMmDHx/PPPt579rFAmhg0bVjj//PPrHtfU1BR69epVmD59eknH1ZpNmzatMHjw4FIPIynZt9T9999f97i2trbQs2fPwo9+9KO6eWvXri1UVVUV7rnnnhKNsnVvs8y4ceMKY8aMKdmYUrB69ep82z322GN1+1W7du0K9913X90yL7zwQr7MokWLSjjS1r3dMscee2zhoosuKum4Wru99tqrcOedd7aa/awsjrxs2bIlL8jscP32v8Axe7xo0aKSjq21y05vZIf2+/XrF2PHjo0VK1aUekhJeeWVV2LVqlX19r3sF49lpy3te41buHBhfpi/f//+cd5558W//vWvUg+pVVm3bl3+sWvXrvnH7O+47KjC9vtadpq3T58+9rVGtts2d999d3Tr1i0GDRoUU6ZMiU2bNpVohK1LTU1NzJs3Lz9SlZ0+ai372W73W6UbsmbNmvwPoEePHvXmZ49ffPHFko2rtct+wM6ZMyf/4ZEdRr3mmmvimGOOieeeey4/f8zOZeGSaWjf2/YcDZ8yyg5DH3DAAfHyyy/HVVddFSeeeGL+l2ObNm2i3NXW1sZ3vvOd+OxnP5v/sM1k+1P79u2jS5cu9Za1rzW+3TJnnnlm7L///vk/1P72t7/FFVdckV8X85vf/CbK1bPPPpvHSnZ6O7uu5f7774+BAwfGM8880yr2s7KIF5on+2GxTXbxVhYz2Tf4L3/5y5gwYUJJx8bu7fTTT6/7/0MPPTTf/w488MD8aMzxxx8f5S67hiP7R4Rr0D6a7TZp0qR6+1t2cX22n2XhnO135ah///55qGRHqn71q1/FuHHj8utbWouyOG2UHQrM/rX2wauhs8c9e/Ys2bhSk5X2pz71qXjppZdKPZRkbNu/7Hstk522zL6P7XsRkydPjgcffDAeffTR/MLKbbL9KTtFvnbt2nrL29ca324Nyf6hlinn/a19+/Zx0EEHxZAhQ/I7trIL7G+66aZWs59VlssfQvYH8PDDD9c7fJg9zg6L0TTvvvtu/i+R7F8lNE122iP7ht5+31u/fn1+15F9r+lee+21/JqXct73smubsx/A2eH7Rx55JN+3tpf9HdeuXbt6+1p26iO7Tq2c97WdbbeGZEccMuW8v31Q9jNz8+bNrWc/K5SJefPm5Xd4zJkzp/D3v/+9MGnSpEKXLl0Kq1atKvXQWq1LL720sHDhwsIrr7xSePLJJwsjR44sdOvWLb9an//asGFD4a9//Ws+Zd9SM2fOzP//n//8Z/789ddfn+9rv/3tbwt/+9vf8rtoDjjggMK///3vQrlqbJtlz1122WX5nQvZvvfQQw8VjjjiiMLBBx9ceO+99wrl6rzzzitUV1fn35Nvvvlm3bRp06a6Zc4999xCnz59Co888khhyZIlhREjRuRTOdvZdnvppZcK1157bb69sv0t+z7t169f4X/+538K5erKK6/M78bKtkf2d1b2uKKiovCnP/2p1exnZRMvmVtuuSXf4O3bt89vnf7LX/5S6iG1aqeddlphn332ybfXvvvumz/OvtGp79FHH81/AH9wym733Xa79Pe+971Cjx498oA+/vjjC8uXLy+Us8a2WfZD5YQTTijsvffe+S2Z+++/f2HixIll/w+NhrZXNv3sZz+rWyYL4m9/+9v5ba0dO3YsfPnLX85/UJeznW23FStW5KHStWvX/PvzoIMOKlx++eWFdevWFcrVN7/5zfz7Lvu7P/s+zP7O2hYurWU/q8j+8/Ed5wEAaJmyuOYFANh9iBcAICniBQBIingBAJIiXgCApIgXACAp4gUASIp4AQCSIl4AgKSIFwAgKeIFAIiU/H+wH2UMHUYfuwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bb = rt_points([radar], scatterers, radar, debug=debug_ON)\n",
    "cmap = cm.get_cmap(name='CMRmap_r')\n",
    "ffts = []\n",
    "for chirp_i in range(15):\n",
    "    adc = bb[\"adc_cube\"][0,chirp_i,0,:]\n",
    "    range_profile = fft(adc)\n",
    "\n",
    "    mag_r = abs(range_profile[:len(range_profile)//2])\n",
    "    mag_r = expand_dims(mag_r, axis=0)\n",
    "    plt.imshow(mag_r, cmap,\n",
    "           aspect='auto',\n",
    "           norm=colors.LogNorm(vmin=min(mag_r[0][:]), vmax=max(mag_r[0][:])))\n",
    "    plt.title(\"1D FFT\")\n",
    "    # plt.savefig(fp_fft_1D)\n",
    "    plt.show()\n",
    "    ffts.append(range_profile[:21])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3c3b723-bfbb-4c85-8913-d8a52276b656",
   "metadata": {},
   "source": [
    "### Range FFT on cube\n",
    "\n",
    "> 1D FFT on 2D cube, shows 2 targets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "aacf8578",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from numpy import array\n",
    "ffts = array(ffts)\n",
    "plt.imshow(abs(ffts), cmap=cmap)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36d4e36f-e606-494c-968f-ab6583998be0",
   "metadata": {},
   "source": [
    "### Range Doppler FFT on cube\n",
    "\n",
    "> 2nd FFT on 2D cube shows one static target and one moving\n",
    "\n",
    "> similarly as to a 2D FFT would."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9ed9d214",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiIAAAGOCAYAAACqgmgiAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvZiW1igAAAAlwSFlzAAAPYQAAD2EBqD+naQAAHwRJREFUeJzt3QuQHVWdP/DfTIbMhDxJeCTZJBBZ5BWMokAh+yBLCszGALuriIUa8Y1BjOgupmoDUrg7ohaFSiqw7kqw5GkVgRXdULxCcCViEtgFH4G4MUQhRCgzQxIzITP9r+76z5ghM0km3vbce+fzqeqa3L59T5++5/btb06fvt2QZVkWAAAJNKZYKQBAThABAJIRRACAZAQRACAZQQQASEYQAQCSEUQAgGQEEQAgmaaoMl1dXfHCCy/EyJEjo6GhIXV1AID9kP8+6quvvhoTJ06MxsbG2g0ieQiZPHly6moAAAdg48aNMWnSpNoNInlPSO7ZZ5fFyJHDo9Zk2a5Sy+/q2lZa2U1N46JMXV07Si1/4sQZpZW9ZcsrUabOzq2llp9lHVGryt6ngMp49dWt8YY3nNpzHK/ZINJ9OiYPIaNGjYhaU34QKa/spqZy3++urqr7uO23UaNGlVp+Z2e5w7WyrNwQWCZBBGrLQIdVGKwKACQjiAAAyQgiAEAygggAUH9BZNGiRXHUUUdFS0tLnHbaafHEE0+UtSoAoEaVEkTuvPPOuPzyy+Oqq66KNWvWxPTp0+Occ86JzZs3l7E6AKBGlRJErrvuuvjoRz8aF198cZxwwglx4403xsEHHxzf+ta3ylgdAFCjKh5Edu7cGatXr46ZM2f+YSWNjcXjxx9/vNKrAwBqWMV/Yerll1+Ozs7OOOKII3rNzx//4he/2GP5jo6OYurW3t5e6SoBAFUq+VUzra2tMXr06J7JfWYAYPCoeBA59NBDY8iQIfHSSy/1mp8/Hj9+/B7LL1iwINra2nqm/GY5AMDgUPEgMnTo0HjrW98aDz30UM+8rq6u4vHpp5++x/LNzc3FfTx2nwCAwaGUu5Dll+7OnTs33va2t8Wpp54a119/fWzbtq24igYAoNQg8p73vCd++9vfxpVXXhmbNm2KN7/5zbFs2bI9BrACAINbQ5ZlWVSR/KqZfNDqiy8+FqNGlXtb+lq8ZXlX19bSym5qOjTK1NVV7q3oR4w4pbSyu7peizJ1dpbXrrksK/e9r+V9CqiM9vZX47DDTijGew5kmEXyq2YAgMFLEAEAkhFEAIBkBBEAIBlBBACor8t3K2HYsBNi2LBRNTcKv+wR/p2dW0ore/v2VVGmkSP/cCPEWryypUxNTWNSVwHgjzJ06IHdK06PCACQjCACACQjiAAAyQgiAEAygggAkIwgAgAkI4gAAMkIIgBAMoIIAJCMIAIAJCOIAADJCCIAQDKCCACQjCACACQjiAAAyQgiAEAygggAkIwgAgAkI4gAAMkIIgBAMoIIAJCMIAIAJNMUVSrLdhVTWWWXpcyyc11dW0sru6PjV1GmESN2lFp+lpX3cW5oKHdXKftzU3b9AQ6UHhEAIBlBBABIRhABAJIRRACAZAQRACAZQQQASEYQAQCSEUQAgPoJIq2trXHKKafEyJEj4/DDD4/zzz8/1q5dW+nVAAB1oOJB5NFHH4158+bFypUr44EHHojXXnstzj777Ni2bVulVwUA1LiK/+7zsmXLej1esmRJ0TOyevXq+Ku/+qtKrw4AqGGl34Cira2t+Dt27Ng+n+/o6Cimbu3t7WVXCQAYDINVu7q6Yv78+XHGGWfEtGnT+h1TMnr06J5p8uTJZVYJABgsQSQfK/LMM8/EHXfc0e8yCxYsKHpNuqeNGzeWWSUAYDCcmrn00kvjvvvuixUrVsSkSZP6Xa65ubmYAIDBp+JBJMuy+NSnPhVLly6N5cuXx9SpUyu9CgCgTjSVcTrmtttui3vvvbf4LZFNmzYV8/PxH8OGDav06gCAGlbxMSKLFy8uxnqceeaZMWHChJ7pzjvvrPSqAIAaV8qpGQCA/eFeMwBAMoIIAJCMIAIAJCOIAAD1e6+ZA9XVtSO6uoaWVPquUutdpp07f11a2Z2bH4wy7Rr9zlLLb2oq7+Pc2NhSWtnsXUND1X5NARWgRwQASEYQAQCSEUQAgGQEEQAgGUEEAEhGEAEAkhFEAIBkBBEAIBlBBABIRhABAJIRRACAZAQRACAZQQQASEYQAQCSEUQAgGQEEQAgGUEEAEhGEAEAkhFEAIBkBBEAIBlBBABIRhABAJIRRACAZJqiSu3Y8fMYOnR4KWXv2vVylOX3v38mypSt+lppZX/kc7dGmf79/htKLf/gMTNLK3vo0ElRpsbGEaWWP2RIeeU3NJT9NdJUs3Wv9fLLVMt1p7L0iAAAyQgiAEAygggAkIwgAgAkI4gAAMkIIgBAMoIIAFC/QeRLX/pSNDQ0xPz588teFQBQY0oNIj/5yU/ipptuije96U1lrgYAqFGlBZGtW7fGRRddFN/85jfjkEMOKWs1AEANKy2IzJs3L2bPnh0zZ+79Z7c7Ojqivb291wQADA6l/Nj/HXfcEWvWrClOzexLa2trXH311WVUAwAYbD0iGzdujE9/+tNx6623RktLyz6XX7BgQbS1tfVM+esBgMGh4j0iq1evjs2bN8fJJ5/cM6+zszNWrFgRN9xwQ3EqZsiQIT3PNTc3FxMAMPhUPIicddZZ8fTTT/ead/HFF8dxxx0XV1xxRa8QAgAMbhUPIiNHjoxp06b1mjd8+PAYN27cHvMBgMHNL6sCAPV11czrLV++/E+xGgCgxugRAQCSEUQAgGQEEQAgGUEEAKjvwaoHYujQKTF06MhSym5qGl9KuWWXnWs/eUdpZf/7+94RZRp+yA9KLb+5+c9LK3vIkBFRpoaGlpLLb6rJsv8U5dcy7w31QI8IAJCMIAIAJCOIAADJCCIAQDKCCACQjCACACQjiAAAyQgiAEAygggAkIwgAgAkI4gAAMkIIgBAMoIIAJCMIAIAJCOIAADJCCIAQDKCCACQjCACACQjiAAAyQgiAEAygggAkIwgAgAkI4gAAMk0RZVqahoXTU2jSik7y3ZFWZqaxkSZGhrOL63stvdtiTINGzat1PKHDCnvvW9oKHdXKbv8Wua9gfqmRwQASEYQAQCSEUQAgGQEEQAgGUEEAEhGEAEAkhFEAID6CiK/+c1v4n3ve1+MGzcuhg0bFieddFKsWrWqjFUBADWs4r8U9Lvf/S7OOOOMmDFjRvzXf/1XHHbYYfHcc8/FIYccUulVAQA1ruJB5Nprr43JkyfHzTff3DNv6tSplV4NAFAHKn5q5j//8z/jbW97W7z73e+Oww8/PN7ylrfEN7/5zUqvBgCoAxUPIv/3f/8XixcvjmOOOSbuv//+uOSSS+Kyyy6LW265pc/lOzo6or29vdcEAAwOFT8109XVVfSI/Ou//mvxOO8ReeaZZ+LGG2+MuXPn7rF8a2trXH311ZWuBgAwGHtEJkyYECeccEKveccff3w8//zzfS6/YMGCaGtr65k2btxY6SoBAIOlRyS/Ymbt2rW95j377LNx5JFH9rl8c3NzMQEAg0/Fe0Q+85nPxMqVK4tTM+vWrYvbbrst/u3f/i3mzZtX6VUBADWu4kHklFNOiaVLl8btt98e06ZNi2uuuSauv/76uOiiiyq9KgCgxlX81Ezune98ZzEBAOyNe80AAMkIIgBAMoIIAJCMIAIAJCOIAAD1ddVMtWtoKHOzW0osO6Kp6dDSyh468s1RpsbGETXbruV+ZspX6/UH6pceEQAgGUEEAEhGEAEAkhFEAIBkBBEAIBlBBABIRhABAJIRRACAZAQRACAZQQQASEYQAQCSEUQAgGQEEQAgGUEEAEhGEAEAkhFEAIBkBBEAIBlBBABIRhABAJIRRACAZAQRACAZQQQASKYp3arrU0NDuW9pY2NLaWU3NY2PWn5vAKg9ekQAgGQEEQAgGUEEAEhGEAEAkhFEAIBkBBEAIBlBBAConyDS2dkZCxcujKlTp8awYcPi6KOPjmuuuSayLKv0qgCAGlfxX5i69tprY/HixXHLLbfEiSeeGKtWrYqLL744Ro8eHZdddlmlVwcA1LCKB5Ef/ehHcd5558Xs2bOLx0cddVTcfvvt8cQTT1R6VQBAjav4qZm3v/3t8dBDD8Wzzz5bPP6f//mf+OEPfxizZs2q9KoAgBpX8R6Rz3/+89He3h7HHXdcDBkypBgz8i//8i9x0UUX9bl8R0dHMXXLXwsADA4V7xG566674tZbb43bbrst1qxZU4wV+epXv1r87Utra2sxfqR7mjx5cqWrBABUqYaswpez5EEi7xWZN29ez7wvfvGL8Z3vfCd+8Ytf7FePSF7G7373UowaNaqSVasLnZ1bSit727ZVUaaRI8+s2bv71vqdg2u9/kD1y4/feYdCW1vbgI7fFf922r59ezQ29u5oyU/RdHV19bl8c3NzMQEAg0/Fg8icOXOKMSFTpkwpLt998skn47rrrosPfehDlV4VAFDjKh5EvvGNbxQ/aPbJT34yNm/eHBMnToyPf/zjceWVV1Z6VQBAjav4GJFKnWMyRqRvxoj0zxiR+q0/UL9jRNxrBgBIRhABAJIRRACAZAQRACAZQQQASMZQ+hpT5tUPQ4aMKK1s0sqyXVGrXPED9U2PCACQjCACACQjiAAAyQgiAEAygggAkIwgAgAkI4gAAMkIIgBAMoIIAJCMIAIAJCOIAADJCCIAQDKCCACQjCACACQjiAAAyQgiAEAygggAkIwgAgAkI4gAAMkIIgBAMoIIAJCMIAIAJCOIAADJNEWV2rXrldi1a2cpZTc2tkStyrJdpZXd0NBUs3UvW9l1L/u9r2W1/Lkpm88N9bCv6hEBAJIRRACAZAQRACAZQQQASEYQAQCSEUQAgGQEEQCgdoLIihUrYs6cOTFx4sRoaGiIe+65p9fzWZbFlVdeGRMmTIhhw4bFzJkz47nnnqtknQGAwRpEtm3bFtOnT49Fixb1+fyXv/zl+PrXvx433nhj/PjHP47hw4fHOeecEzt27KhEfQGAOjLgn+WbNWtWMfUl7w25/vrr45//+Z/jvPPOK+Z9+9vfjiOOOKLoObnwwgv/+BoDAHWjomNE1q9fH5s2bSpOx3QbPXp0nHbaafH444/3+ZqOjo5ob2/vNQEAg0NFg0geQnJ5D8ju8sfdz71ea2trEVa6p8mTJ1eySgBAFUt+1cyCBQuira2tZ9q4cWPqKgEAtRhExo8fX/x96aWXes3PH3c/93rNzc0xatSoXhMAMDhUNIhMnTq1CBwPPfRQz7x8zEd+9czpp59eyVUBAIPxqpmtW7fGunXreg1Qfeqpp2Ls2LExZcqUmD9/fnzxi1+MY445pggmCxcuLH5z5Pzzz6903QGAwRZEVq1aFTNmzOh5fPnllxd/586dG0uWLIl/+qd/Kn5r5GMf+1hs2bIl/uIv/iKWLVsWLS0tla05AFDzGrL8xz+qSH4qJ7965re//VmMGjWylHU0NtZuKMqyXaWV3dHxh56uMrS0TCu1/IaGAefqqlHLdScdnxuq7fg9Zsy44sKTgYz3TH7VDAAweAkiAEAygggAkIwgAgAkU7UjnXbufD527hxeStmNjSOiLLU9eKzcund1bS21/Fp+72u57uXz3tQjn/n609W144Bep0cEAEhGEAEAkhFEAIBkBBEAIBlBBABIRhABAJIRRACAZAQRACAZQQQASEYQAQCSEUQAgGQEEQAgGUEEAEhGEAEAkhFEAIBkBBEAIBlBBABIRhABAJIRRACAZAQRACAZQQQASEYQAQCSEUQAgGSaokq1tBwfLS2jSim7oaFqN3ufsmxHiWX/OsrU1HRoqeXXcruShs8MVM6QIV0H9Do9IgBAMoIIAJCMIAIAJCOIAADJCCIAQDKCCACQjCACANROEFmxYkXMmTMnJk6cGA0NDXHPPff0PPfaa6/FFVdcESeddFIMHz68WOYDH/hAvPDCC5WuNwAwGIPItm3bYvr06bFo0aI9ntu+fXusWbMmFi5cWPy9++67Y+3atXHuuedWqr4AQB0Z8M8Kzpo1q5j6Mnr06HjggQd6zbvhhhvi1FNPjeeffz6mTJly4DUFAOpO6b9v3NbWVpzCGTNmTJ/Pd3R0FFO39vb2sqsEAAyGwao7duwoxoy8973vjVGj+r5vTGtra9GT0j1Nnjy5zCoBAIMhiOQDVy+44ILIsiwWL17c73ILFiwoek26p40bN5ZVJQBgMJya6Q4hGzZsiIcffrjf3pBcc3NzMQEAg09TWSHkueeei0ceeSTGjRtX6VUAAIM1iGzdujXWrVvX83j9+vXx1FNPxdixY2PChAnxrne9q7h097777ovOzs7YtGlTsVz+/NChQytbewCgpjVk+SCOAVi+fHnMmDFjj/lz586NL3zhCzF16tQ+X5f3jpx55pn7LD+/aiYftPrKKxv2ekrnj9HQUPrFQqXJsh2llb1z56+jTC0tx5Vafi23K2n4zEDldB+/8/GeAzl+D3gvzMPE3rLLAHMNADCIudcMAJCMIAIAJCOIAADJCCIAQDKCCACQTNVeu9bY2FJM9FbmRUlZtqu8wmucyzwByqFHBABIRhABAJIRRACAZAQRACAZQQQASEYQAQCSEUQAgGQEEQAgGUEEAEhGEAEAkhFEAIBkBBEAIBlBBABIRhABAJIRRACAZAQRACAZQQQASEYQAQCSEUQAgGQEEQAgGUEEAEhGEAEAkmmKKtXQ0FRMZciyXaWUW+u8LwD8qekRAQCSEUQAgGQEEQAgGUEEAEhGEAEAkhFEAIBkBBEAoHaCyIoVK2LOnDkxceLEaGhoiHvuuaffZT/xiU8Uy1x//fV/bD0BgDo04CCybdu2mD59eixatGivyy1dujRWrlxZBBYAgL4M+KdLZ82aVUx785vf/CY+9alPxf333x+zZ88e6CoAgEGi4r+h3tXVFe9///vjH//xH+PEE0/c5/IdHR3F1K29vb3SVQIABstg1WuvvTaamprisssu26/lW1tbY/To0T3T5MmTK10lAGAwBJHVq1fH1772tViyZEkxSHV/LFiwINra2nqmjRs3VrJKAMBgCSKPPfZYbN68OaZMmVL0iuTThg0b4rOf/WwcddRRfb6mubk5Ro0a1WsCAAaHio4RyceGzJw5s9e8c845p5h/8cUXV3JVAMBgDCJbt26NdevW9Txev359PPXUUzF27NiiJ2TcuHG9lj/ooINi/Pjxceyxx1amxgDA4A0iq1atihkzZvQ8vvzyy4u/c+fOLcaGAACUFkTOPPPMyLJsv5f/1a9+NdBVAACDhHvNAADJCCIAQDKCCACQjCACANTPvWb+WN0DYcu850yW7Ypa1dW1rbSyd+wor+zcrl3l3keooaGpJssGqAfdx+2BXNCSq7pv11dffbX4O2XK1NRVAQAO4Die3ztufzVkA40uJcvv3vvCCy/EyJEj9+t+NXkCy2+Ul9+jpt5/Ht621ifbWp9sa30aTNs60O3N40QeQiZOnBiNjY212yOSV37SpEkDft1guk+Nba1PtrU+2db6NJi2dSDbO5CekG4GqwIAyQgiAEAyNR9Empub46qrrir+1jvbWp9sa32yrfVpMG3rn2p7q26wKgAweNR8jwgAULsEEQAgGUEEAEhGEAEAkqmJILJo0aI46qijoqWlJU477bR44okn9rr8d7/73TjuuOOK5U866aT4wQ9+ENWutbU1TjnllOIXZQ8//PA4//zzY+3atXt9zZIlS4pfn919yre52n3hC1/Yo955e9Vbm+byz+3rtzWf5s2bVxdtumLFipgzZ07xS4p5Xe+5555ez+dj4a+88sqYMGFCDBs2LGbOnBnPPfdcxff51Nv62muvxRVXXFF8NocPH14s84EPfKD4lehK7wvV0K4f/OAH96j3O97xjrpr11xf+28+feUrX6mpdm3dj2PMjh07iu+mcePGxYgRI+If/uEf4qWXXtpruQe6j9dUELnzzjvj8ssvLy4fWrNmTUyfPj3OOeec2Lx5c5/L/+hHP4r3vve98eEPfziefPLJ4s3Op2eeeSaq2aOPPlp8AFauXBkPPPBA8cV29tlnx7Zte78RXf5Ldy+++GLPtGHDhqgFJ554Yq96//CHP+x32Vpt09xPfvKTXtuZt23u3e9+d120af75zPfJ/ADTly9/+cvx9a9/PW688cb48Y9/XByk8/03/8Kr1D5fDdu6ffv2oq4LFy4s/t59993Fl/y5555b0X2hWto1lweP3et9++2377XMWmzX3O7bmE/f+ta3imCRH6RrqV0f3Y9jzGc+85n43ve+V/zHL18+D9J///d/v9dyD2Qf30NW5U499dRs3rx5PY87OzuziRMnZq2trX0uf8EFF2SzZ8/uNe+0007LPv7xj2e1ZPPmzfll1dmjjz7a7zI333xzNnr06KzWXHXVVdn06dP3e/l6adPcpz/96ezoo4/Ourq66qpNc/nndenSpT2P820cP3589pWvfKVn3pYtW7Lm5ubs9ttvr9g+Xw3b2pcnnniiWG7Dhg0V2xeqZVvnzp2bnXfeeQMqp17aNd/uv/mbv9nrMrXQrptfd4zJ982DDjoo++53v9uzzM9//vNimccff7zPMg50H3+9qu4R2blzZ6xevbro6tn9XjT548cff7zP1+Tzd18+l6ez/pavVm1tbcXfsWPH7nW5rVu3xpFHHlnclOi8886Ln/70p1EL8q67vCv0DW94Q1x00UXx/PPP97tsvbRp/nn+zne+Ex/60If2ekPHWm3T11u/fn1s2rSpV9vl96HIu+T7a7sD2eereR/O23nMmDEV2xeqyfLly4su/mOPPTYuueSSeOWVV/pdtl7aNT9N8f3vf7/ond2Xam/XttcdY/L2yXtJdm+j/HTSlClT+m2jA9nH+1LVQeTll1+Ozs7OOOKII3rNzx/nG9+XfP5Alq9G+R2I58+fH2eccUZMmzat3+XyL4C8m/Dee+8tDnD5697+9rfHr3/966hm+Yc0HwuxbNmyWLx4cfFh/su//Mviro312qa5/Nzzli1bivPr9damfelun4G03YHs89Uo75bOx4zkpxT3dqOwge4L1SI/LfPtb387Hnroobj22muLbvxZs2YVbVfP7XrLLbcUYyz2dbqi2tu1q49jTN4OQ4cO3SM47+t4273M/r6mJu6+SxTn8fLxD/s6p3j66acXU7f8gHX88cfHTTfdFNdcc01Uq/wLq9ub3vSmYqfNewDuuuuu/fqfRq36j//4j2Lb8/8l1Vub8gf5/yovuOCCYhBffhCqx33hwgsv7Pl3PkA3r/vRRx9d9JKcddZZUa/y/yTkvRv7GkBe7e06bz+PMX8qVd0jcuihh8aQIUP2GLWbPx4/fnyfr8nnD2T5anPppZfGfffdF4888khMmjRpQK896KCD4i1veUusW7cuakmewN/4xjf2W+9ab9NcPuD0wQcfjI985CODok1z3e0zkLY7kH2+GkNI3t75gMCB3iZ+X/tCtcpPP+Rt11+9a71dc4899lgxAHmg+3C1teul/Rxj8nbIT6HlvbYDOd52L7O/r6m5IJJ3E731rW8tuv9271LKH+/+v8bd5fN3Xz6XfyH0t3y1yP/3lH9Ali5dGg8//HBMnTp1wGXkXZ9PP/10cRlVLcnHRPzyl7/st9612qa7u/nmm4vz6bNnzx4UbZrLP8P5l9Hubdfe3l6MrO+v7Q5kn6+2EJKPDchDZ34JZKX3hWqVnzrMx4j0V+9abtfdezTzbcivsKnFds32cYzJty3/j8/ubZQHr3xsS39tdCD7eH+Vq2p33HFHMQJ3yZIl2c9+9rPsYx/7WDZmzJhs06ZNxfPvf//7s89//vM9y//3f/931tTUlH31q18tRvzmo5fzkcBPP/10Vs0uueSS4mqJ5cuXZy+++GLPtH379p5lXr+tV199dXb//fdnv/zlL7PVq1dnF154YdbS0pL99Kc/zarZZz/72WI7169fX7TXzJkzs0MPPbQYxV1Pbbr71QFTpkzJrrjiij2eq/U2ffXVV7Mnn3yymPKvk+uuu674d/eVIl/60peK/fXee+/N/vd//7e44mDq1KnZ73//+54y8isQvvGNb+z3Pl+N27pz587s3HPPzSZNmpQ99dRTvfbhjo6Ofrd1X/tCNW5r/tznPve54kqKvN4PPvhgdvLJJ2fHHHNMtmPHjrpq125tbW3ZwQcfnC1evLjPMmqhXS/Zj2PMJz7xieK76uGHH85WrVqVnX766cW0u2OPPTa7++67ex7vzz6+L1UfRHJ5A+dvztChQ4tLwFauXNnz3F//9V8Xl5Lt7q677sre+MY3FsufeOKJ2fe///2s2uU7QF9Tfjlnf9s6f/78nvfliCOOyP72b/82W7NmTVbt3vOe92QTJkwo6v1nf/ZnxeN169bVXZt2y4NF3pZr167d47lab9NHHnmkz89t9zbll/ctXLiw2Jb8IHTWWWft8T4ceeSRRbjc332+Grc1P+D0tw/nr+tvW/e1L1TjtuYHrrPPPjs77LDDiv8Q5Nv00Y9+dI9AUQ/t2u2mm27Khg0bVlya2pdaaNfYj2NMHh4++clPZoccckgRvP7u7/6uCCuvL2f31+zPPr4vDf+/YACAP7mqHiMCANQ3QQQASEYQAQCSEUQAgGQEEQAgGUEEAEhGEAEAkhFEAIBkBBEAIBlBBABIRhABAJIRRACASOX/AbRS4AirnbaIAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fft2_from_fft = fft(ffts, axis=0)\n",
    "plt.imshow(abs(fft2_from_fft), cmap=cmap)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "01142773-effe-471b-ad35-8fe886ae3e97",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "last checked on version 0.0.11-pre.3\n"
     ]
    }
   ],
   "source": [
    "# non regression hook, check the index and max value haven't changed\n",
    "from numpy import argmax, unravel_index, abs as np_abs\n",
    "flat_index = argmax(np_abs(fft2_from_fft))\n",
    "\n",
    "# convert to 2D index\n",
    "i, j = unravel_index(flat_index, fft2_from_fft.shape)\n",
    "assert (i,j) == (0, 6)\n",
    "assert np_abs(fft2_from_fft)[i, j]==465.46585\n",
    "print(\"last checked on version\", mmWrt_ver)"
   ]
  }
 ],
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