{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "45d42661",
   "metadata": {},
   "source": [
    "# Gate Leakage Test\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f25318c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connected to: QDevil QDAC-II (serial:3, firmware:11-1.14) in 0.22s\n"
     ]
    }
   ],
   "source": [
    "from time import sleep\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import Image, display\n",
    "from qcodes_contrib_drivers.drivers.QDevil import QDAC2\n",
    "qdac_addr = '192.168.8.17'\n",
    "qdac = QDAC2.QDac2('QDAC', visalib='@py', address=f'TCPIP::{qdac_addr}::5025::SOCKET')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "30e8b591",
   "metadata": {},
   "outputs": [],
   "source": [
    "# For testing, connect resistors: 5M6 over ch 5, 33M between ch 3 & 4, and 5G over ch 1 \n",
    "arrangement = qdac.arrange(\n",
    "    contacts={'G1': 1, 'G2': 2, 'G3': 3, 'G4': 4, 'O5': 5})\n",
    "arrangement.set_virtual_voltages({\n",
    "    'G1': 0.01, 'G2': 0.015, 'G3': 0.013, 'G4': 0.021, 'O5': 0.005})\n",
    "sleep(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "be17c0ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Measure leakage by raising the voltage by 5 mV on each channel in turn. \n",
    "modulation_mV=5\n",
    "powerline_cycles=10\n",
    "leakage_matrix_Ohm = arrangement.leakage(\n",
    "    modulation_V=modulation_mV/1000, nplc=powerline_cycles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "de82ee13",
   "metadata": {},
   "outputs": [],
   "source": [
    "leakage_megaohm = leakage_matrix_Ohm / 1e6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3faf6e53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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33XWXwbNerrd06VK8+eabWLVqFQ4cOAAXFxeEh4ejpKREf01UVBR+/fVXfPPNN9i6dSt2796NSZMm1ddHqIFzCoiIiCwkSRI2bdqEESNGAKjqJfD19cXzzz+v3xskPz8fXl5eeO+99zBmzBicOHECoaGhOHToELp37w4ASE1NxeDBg5GdnW3wALT60mDnFOh0Opw/fx5NmzblQ06IiGRICIGrV6/C19cXDg511zFdUlKCsrIyi+sRQtT4e6NSqaBSqUyuKzMzE1qt1mDrdI1Gg549e2Lfvn0YM2YM9u3bB3d3d31CAFTtgOrg4IADBw7gwQcfNP/DmKnBJQWJiYlITExEWVlZrQ+YISIiecnKytLvcmptJSUlCGjtCu2FyttffBuurq41xvPnz5+P2NhYk+vSarUAAC8vL4NyLy8v/TmtVgtPT0+D846OjmjWrJn+mvrW4JKCmJgYxMTEID8/H+7u7vhtTzA8aj4plQCUlSuQ+HFVJhkzZhOUTpb/UtgjtpNx2E7Gub6dflp7EboKjsDWxsFRQofRbli+fLlRT9w0V1lZGbQXKpF5pDXcmprfG1FwVYeAbmeRlZUFNzc3fbk5vQRy1uCSgmrVXTgedwDNm9k4mAaqrBz6B8Q0bwYonWwcUAPFdjIO28k417eTQucEScekoDYOOkn/B7U+hoDdmjpYlBTo63FzM0gKzFX9PJCcnBz4+Pjoy3NyctClSxf9NRcuXDC4r6KiArm5uXXyPBFjcPUBERHJXqXQWXxYU0BAALy9vbFjxw59WUFBAQ4cOKB/mmevXr2Ql5eHI0eO6K/57rvvoNPp0LNnT6vGY6wG21NARERkLB0EdDC/18acewsLC5GRkaF/nZmZibS0NDRr1gytWrXCc889h0WLFqFt27YICAjAK6+8Al9fX/0Khfbt2yMiIgITJ07EqlWrUF5ejqlTp2LMmDE2WXkAMCkgIiI7oIMOlnzXN+fuw4cP47777tO/njlzJgAgOjoa7733HubMmYOioiJMmjQJeXl56NOnD1JTU/XDTwDw0UcfYerUqXjggQfg4OCAkSNH4s0337Tgk1iGSQEREZEZ+vXrh1tt9SNJEhYuXIiFCxfe9JpmzZph3bp1dRGeWZgUEBGR7FUKgUoL9uKz5F57wqSAiIhkzxZzCuwRVx8QERERAPYUEBGRHdBBoJI9BRZjUkBERLLH4QPr4PABERERAWBPARER2QGuPrAOJgVERCR7umuHJfcThw+IiIjoGvYUEBGR7FVauPrAknvtCZMCIiKSvUpRdVhyPzEpICIiO8A5BdbBOQVEREQEgD0FRERkB3SQUAnJovuJSQEREdkBnag6LLmfOHxARERE17CngIiIZK/SwuEDS+61J0wKiIhI9pgUWAeHD4iIiAgAewqIiMgO6IQEnbBg9YEF99oTJgVERCR7HD6wDg4fEBEREQD2FBARkR2ohAMqLfieW2nFWOSMSQEREcmesHBOgeCcAgBMCoiIyA5wToF1cE4BERERATAzKcjKysL48ePh6+sLpVKJ1q1bY/r06bh8+bL+mnHjxkGSJIMjIiLCaoETERFVqxQOFh9kxvDB6dOn0atXL7Rr1w7r169HQEAAfv31V8yePRvbtm3D/v370axZMwBAREQEUlJS9PeqVCrrRU5ERHSNDhJ0FnR+68AnIgFmJAUxMTFQKpXYvn071Go1AKBVq1bo2rUrgoKC8NJLLyE5ORlAVRLg7e1t3YiJiIioTpiUVuXm5uLrr7/GlClT9AlBNW9vb0RFRWHDhg0Qoirj2rlzJzw9PRESEoJnnnnGYHjhRqWlpSgoKDA4iIiIjFE90dCSg0xMCk6dOgUhBNq3b1/r+fbt2+PKlSu4ePEiIiIi8MEHH2DHjh1YsmQJdu3ahUGDBqGysvbVoPHx8dBoNPrD39/f9E9DRESNEucUWIdZSxKrewJuZcyYMfqfO3XqhM6dOyMoKAg7d+7EAw88UOP6uXPnYubMmfrXBQUFTAyIiIjqkUmpUXBwMCRJwokTJ2o9f+LECdxxxx1o0aJFjXOBgYFo3rw5MjIyar1XpVLBzc3N4CAiIjJG1URDyw4yMSnw8PDAgAEDkJSUhL///tvgnFarxUcffYRHHnkEklSzcbOzs3H58mX4+PhYFjEREdENdNe2OTb3sGTlgj0xuRVWrlyJ0tJShIeHY/fu3cjKykJqaioGDBgAPz8/LF68GIWFhZg9ezb279+PM2fOYMeOHYiMjERwcDDCw8Pr4nMQERGRhUxOCtq2bYvDhw8jMDAQo0ePRlBQECZNmoT77rsP+/btQ7NmzaBQKHDs2DEMHz4c7dq1w4QJE9CtWzf88MMP3KuAiIisjhMNrcOsiYatW7fGe++9d9PzarUaX3/9tbkxERERmURn4RAANy+qwgciERGR7FUKCZUWPOnQknvtCftLiIiICAB7CoiIyA5UryIw/34OHwBMCoiIyA7ohAN0FkwW1BmxKV9jwOEDIiIiAsCeAiIisgMcPrAOJgVERCR7Oli2gkBnvVBkjcMHREREBIA9BUREZAcs37yI35EBJgVERGQHLN2qmNscV2ErEBEREQD2FBARkR3QQYIOlkw05DbHAJMCIiKyAxw+sA4mBUREJHuW71PApADgnAIiIiK6hj0FREQkezohQWfJ5kV8dDIAJgVERGQHdBYOH3CfgipsBSIiIgLAngIiIrIDlj86md+RASYFRERkByohodKCvQYsudeeMDUiIiIiAOwpICIiO8DhA+tgUkBERLJXCcuGACqtF4qsMTUiIiIiAOwpICIiO8DhA+tgUkBERLLHByJZB1uBiIhkT1x7dLK5hzBxPkJlZSVeeeUVBAQEQK1WIygoCK+++iqEEP/EJATmzZsHHx8fqNVq9O/fH6dOnbL2R7cqJgVEREQmWrJkCZKTk7Fy5UqcOHECS5YswdKlS7FixQr9NUuXLsWbb76JVatW4cCBA3BxcUF4eDhKSkpsGPmtNfjhg7JyBcrKbR1Fw1RWrqj1ZzLEdjIO28k417eNgyM3vLmZ+m6b+h4+2Lt3LyIjIzFkyBAAQJs2bbB+/XocPHgQQFUvQUJCAl5++WVERkYCAD744AN4eXlh8+bNGDNmjNmx1qUGnxQkfvwgnJ2dbR1Gg7d87WhbhyALbCfjsJ2M02OCl61DaNDq8xuxtZ6SWFBQYFCuUqmgUqlqXN+7d2+sWbMGv//+O9q1a4eff/4Ze/bswbJlywAAmZmZ0Gq16N+/v/4ejUaDnj17Yt++fUwKjJWYmIjExERUVnLVKBER1S9/f3+D1/Pnz0dsbGyN61588UUUFBTgzjvvhEKhQGVlJRYvXoyoqCgAgFarBQB4eRkmjl5eXvpzDVGDSwpiYmIQExODgoICaDQaxIzZhObNbB1Vw1RWrtB/o5vx+CdQOjGRqs317bT1siv3OL8JBQSGehQCALadd0Elny9fK4UkMMi3CAB/726lrFyB+LeG19v7VVr46OTqe7OysuDm5qYvr62XAAA++eQTfPTRR1i3bh06dOiAtLQ0PPfcc/D19UV0dLTZcdhag0sKbqR0qoTSydZRNHxV7cR/nG7H0oemNBaVQmJSYAT+3jUc1ho+cHNzM0gKbmb27Nl48cUX9cMAnTp1wtmzZxEfH4/o6Gh4e3sDAHJycuDj46O/LycnB126dDE7zrrG1QdEREQmKi4uhoOD4Z9QhUIBnU4HAAgICIC3tzd27NihP19QUIADBw6gV69e9RqrKRp8TwEREdHt6OAAnQXfc029d9iwYVi8eDFatWqFDh064OjRo1i2bBnGjx8PAJAkCc899xwWLVqEtm3bIiAgAK+88gp8fX0xYsQIs+Osa0wKiIhI9iwd8jL13hUrVuCVV17BlClTcOHCBfj6+uLpp5/GvHnz9NfMmTMHRUVFmDRpEvLy8tCnTx+kpqY26BV1TAqIiIhM1LRpUyQkJCAhIeGm10iShIULF2LhwoX1F5iFmBQQEZHsWWuiYWPHpICIiGRPWPiURMEHIgFgUkBERHbA0uXGXKpchakRERERAWBPARER2QGdsGxegE7c/prGgEkBERHJns7COQWW3GtP2ApEREQEgD0FRERkB3SQoLNgsqAl99oTJgVERCR79b2job3i8AEREREBYE8BERHZAU40tA4mBUREJHs6WLjNMecUAODwAREREV3DngIiIpI9YeHqA8GeAgBMCoiIyA7wKYnWwaSAiIhkjxMNrYOtQERERADYU0BERHaAwwfWwaSAiIhkj9scWweHD4iIiAgAewqIiMgOcPjAOpgUEBGR7DEpsA4OHxAREREA9hQQEZEdYE+BdTApICIi2WNSYB0cPiAiIiIAZiYFWq0W06dPR3BwMJydneHl5YWwsDAkJyejuLjY4FohBAYNGgRJkrB582ZrxExERGRA4J+9Csw5hK0/QANh8vDB6dOnERYWBnd3d8TFxaFTp05QqVQ4fvw41qxZAz8/PwwfPlx/fUJCAiSJ3TJERFR3OHxgHSYnBVOmTIGjoyMOHz4MFxcXfXlgYCAiIyMhxD/5VlpaGv773//i8OHD8PHxsU7EREREN2BSYB0mJQWXL1/G9u3bERcXZ5AQXK+6V6C4uBiPPfYYEhMT4e3tfdu6S0tLUVpaqn9dUFBgSmhERERkIZPmFGRkZEAIgZCQEIPy5s2bw9XVFa6urnjhhRcAADNmzEDv3r0RGRlpVN3x8fHQaDT6w9/f35TQiIioEavuKbDkICutPjh48CDS0tLQoUMHlJaWYsuWLfjuu++QkJBgdB1z585Ffn6+/sjKyrJGaERE1AgwKbAOk4YPgoODIUkSTp48aVAeGBgIAFCr1QCA7777Dn/88Qfc3d0Nrhs5ciTuvfde7Ny5s0bdKpUKKpXKlHCIiIjIikzqKfDw8MCAAQOwcuVKFBUV3fS6F198EceOHUNaWpr+AIDly5cjJSXFooCJiIhuJIRk8UFmrD5ISkpCWFgYunfvjtjYWHTu3BkODg44dOgQ0tPT0a1bN3h7e9c6ubBVq1YICAiwSuBERETVqvcbsOR+MiMpCAoKwtGjRxEXF4e5c+ciOzsbKpUKoaGhmDVrFqZMmVIXcRIREVEdM+vZBz4+PlixYgVWrFhh9D3X719ARERkTdynwDr4QCQiIpI9S+cFcE5BFT4QiYiIiACwp4CIiOwAhw+sg0kBERHJHocPrINJARERyZ6wsKeASUEVzikgIiIiAOwpICIiOyAAWLLynYvmqzApICIi2dNBgsQdDS3G4QMiIiICwJ4CIiKyA1x9YB1MCoiISPZ0QoLEfQosxuEDIiIiAsCeAiIisgNCWLj6QKbLD86dO4ezZ8+iuLgYLVq0QIcOHaBSqcyuj0kBERHJXmOaU3DmzBkkJyfj448/RnZ2tsFTiJVKJe69915MmjQJI0eOhIODaQMCHD4gIiKSiWnTpuGuu+5CZmYmFi1ahN9++w35+fkoKyuDVqvFV199hT59+mDevHno3LkzDh06ZFL97CkgIiLZayw9BS4uLjh9+jQ8PDxqnPP09MT999+P+++/H/Pnz0dqaiqysrLQo0cPo+tnUkBERLLXWFYfxMfHG31tRESEyfVz+ICIiGSveqKhJYfc6HQ67N+/Hxs2bMC2bdtw5coVAEBBQQHGjx9vVp1MCoiIiGRmz549aNeuHXr37o1HH30UQ4YMgbe3N2bMmIG8vDy8//77ZtXLpICIiGSv6tu+ZMFh609gvOPHjyM8PBy9e/dGWloaioqKkJ2djZUrV2Lz5s0YNWqU2XUzKSAiItmzLCGwbJJifVuwYAFGjhyJDz74AJ07d4ZarYavry8mTpyIw4cPo7y83Oy6OdGQiIhIRnbu3Ikvvvii1nMeHh749NNPsXbtWrPqZlJARESyJ64dltwvF0VFRWjevPlNz7dp0wZPPvmkWXVz+ICIiGSvMQ0fBAUFYf/+/Tc9/9JLLyEwMNCsupkUEBERycgTTzyBOXPm4Pfffzco1+l0WLhwIf773/8abH1sCg4fEBGR/DWi8YPnn38ee/bsQefOnTFkyBC0bdsWubm5SE1NRWFhId577z08/vjjZtXNngIiIpI/S4cOzBg++PPPPzF27Fh4eHhArVajU6dOOHz48D8hCYF58+bBx8cHarUa/fv3x6lTpyz+qAqFAp9//jmSk5NRVFSETZs24ejRoxg1ahR++eUXPPDAA+wpICKixqu+H5185coVhIWF4b777sO2bdvQokULnDp1CnfccYf+mqVLl+LNN9/E+++/j4CAALzyyisIDw/Hb7/9BmdnZ/ODBSBJEp588smbTijU6XRm1dvgk4KycgXKzF9yadfKyhW1/kyGrm8bhZz6COvZ9W2jkNhON3N92/D37ubsvW2WLFkCf39/pKSk6MsCAgL0PwshkJCQgJdffhmRkZEAgA8++ABeXl7YvHkzxowZY/Z7nzt3zqjrWrVqZXLdDT4pSPz4QYszqsZg+drRtg5BFoZ6FNo6BFkY5Ftk6xBkgb93t1NSb+9krackFhQUGJSrVCqoVKoa12/ZsgXh4eEYNWoUdu3aBT8/P0yZMgUTJ04EAGRmZkKr1aJ///76ezQaDXr27Il9+/ZZlBTcmHwAVT0H15dJkoTKykqT625wSUFiYiISExPN+jBERNRImTkvwOB+AP7+/gbF8+fPR2xsbI3LT58+jeTkZMycORP/+c9/cOjQIUybNg1KpRLR0dHQarUAAC8vL4P7vLy89OfMJUkSWrZsiXHjxmHYsGFwdLTen/IGlxTExMQgJiYGBQUF0Gg0iBmzCc2b2TqqhqmsXKH/pjLj8U+gdGIiVZvr2+mrHBdUQj7rkeuTAgKDvap6CLZedGU73YQCAkNbVPU48ffu5srKFYh/a7itwzBZVlYW3Nzc9K9r6yUAqsbsu3fvjri4OABA165d8csvv2DVqlWIjo6u0xizs7Px/vvvIyUlBatWrcLYsWMxYcIEtG/f3uK6G1xScCOlUyWUTraOouGraif+43Q7lZBQKaNNSurVdc1SCYlJgRH4e9dwWGuioZubm0FScDM+Pj4IDQ01KGvfvj02btwIAPD29gYA5OTkwMfHR39NTk4OunTpYn6g1+p+4YUX8MILL2DPnj1ISUlBz549ERoaigkTJmDChAlwcDBvcSGXJBIRkfwJKxwmCAsLw8mTJw3Kfv/9d7Ru3RpA1bi/t7c3duzYoT9fUFCAAwcOoFevXiZ/vJvp06cP3nnnHZw6dQpNmjTB5MmTkZeXZ3Z9TAqIiIhMNGPGDOzfvx9xcXHIyMjAunXrsGbNGsTExACoGvd/7rnnsGjRImzZsgXHjx/HE088AV9fX4wYMcJqcezduxdPPfUU2rVrh8LCQiQmJsLd3d3s+hr88AEREdHtWGv1gbF69OiBTZs2Ye7cuVi4cCECAgKQkJCAqKgo/TVz5sxBUVERJk2ahLy8PPTp0wepqakWr6j766+/8MEHHyAlJQVXrlxBVFQUfvzxR3Ts2NGiegEmBUREZC/qeXuNoUOHYujQoTc9L0kSFi5ciIULF1r1fVu1agU/Pz9ER0dj+PDhcHJygk6nw7Fjxwyu69y5s8l1MykgIiKSkcrKSpw7dw6vvvoqFi1aBAA1tjW2m30KiIiITFXfwwe2lJmZWWd1MykgIiL5a0RPSaxe4VAXuPqAiIjsgGSFo+Ez9rkH1f7880+TrmdSQEREJBM9evTA008/jUOHDt30mvz8fLz11lvo2LGjfjMlY3H4gIiI5K+RDB/89ttvWLx4MQYMGABnZ2d069YNvr6+cHZ2xpUrV/Dbb7/h119/xb/+9S8sXboUgwcPNql+9hQQEZH81fOOhrbi4eGBZcuW4a+//sLKlSvRtm1bXLp0CadOnQIAREVF4ciRI9i3b5/JCQHAngIiIiLZUavVePjhh/Hwww9btV4mBUREJH9WenRyY8ekgIiIZM9aT0ls7DingIiIiACwp4CIiOxBI1l9UNeYFBARkfxxToFVcPiAiIhIptauXYuwsDD4+vri7NmzAICEhAR8/vnnZtXHpICIiGRPEpYfcpOcnIyZM2di8ODByMvL0z8V0d3dHQkJCWbVyaSAiIjkr5FsXnS9FStW4K233sJLL70EhUKhL+/evTuOHz9uVp2cU0BERPLXCOcUZGZmomvXrjXKVSoVioqKzKqTPQVEREQyFBAQgLS0tBrlqampaN++vVl1sqeAiIjkrxEuSZw5cyZiYmJQUlICIQQOHjyI9evXIz4+Hm+//bZZdTIpICIi+WuEScFTTz0FtVqNl19+GcXFxXjsscfg6+uL//u//8OYMWPMqpNJARERkUxFRUUhKioKxcXFKCwshKenp0X1MSkgIiL5a4Q9BZmZmaioqEDbtm3RpEkTNGnSBABw6tQpODk5oU2bNibXyYmGREQkf9WrDyw5ZGbcuHHYu3dvjfIDBw5g3LhxZtXJpICIiEiGjh49irCwsBrl99xzT62rEozB4QMiIpI9S3cllOOOhpIk4erVqzXK8/Pz9bsbmoo9BUREJH+NcEfDvn37Ij4+3iABqKysRHx8PPr06WNWnWYlBVqtFtOnT0dwcDCcnZ3h5eWFsLAwJCcno7i4GADw9NNPIygoCGq1Gi1atEBkZCTS09PNCpKIiIgMLVmyBN999x1CQkLw5JNP4sknn0RISAh2796N119/3aw6TU4KTp8+ja5du2L79u2Ii4vD0aNHsW/fPsyZMwdbt27Ft99+CwDo1q0bUlJScOLECXz99dcQQmDgwIFmd2kQERHRP0JDQ3Hs2DGMHj0aFy5cwNWrV/HEE08gPT0dHTt2NKtOk+cUTJkyBY6Ojjh8+DBcXFz05YGBgYiMjIQQVX0wkyZN0p9r06YNFi1ahLvuugtnzpxBUFBQjXpLS0tRWlqqf11QUGBqaERE1EhJsHBOgdUiqV++vr6Ii4uzWn0mJQWXL1/W9xBcnxBcT5JqNm1RURFSUlIQEBAAf3//Wu+Lj4/HggULTAmHiIioSiN8IBIA5OXl4eDBg7hw4QJ0Op3BuSeeeMLk+kxKCjIyMiCEQEhIiEF58+bNUVJSAgCIiYnBkiVLAABJSUmYM2cOioqKEBISgm+++QZKpbLWuufOnYuZM2fqXxcUFNw0gSAiImrsvvjiC0RFRaGwsBBubm4GX8olSTIrKbDK6oODBw8iLS0NHTp0MBgCiIqKwtGjR7Fr1y60a9cOo0eP1icPN1KpVHBzczM4iIiIjNIIVx88//zzGD9+PAoLC5GXl4crV67oj9zcXLPqNKmnIDg4GJIk4eTJkwblgYGBAAC1Wm1QrtFooNFo0LZtW9xzzz244447sGnTJjz66KNmBUtERFSrRrjN8Z9//olp06bptze2BpN6Cjw8PDBgwACsXLkSRUVFJr2REAJCCIOeBCIiIjJPeHg4Dh8+bNU6TV59kJSUhLCwMHTv3h2xsbHo3LkzHBwccOjQIaSnp6Nbt244ffo0NmzYgIEDB6JFixbIzs7Ga6+9BrVajcGDB1v1AxARETXGHQ2HDBmC2bNn47fffkOnTp3g5ORkcH748OEm12lyUhAUFISjR48iLi4Oc+fORXZ2NlQqFUJDQzFr1ixMmTIFeXl5+OGHH5CQkIArV67Ay8sLffv2xd69ey1+rCMREVENjXD4YOLEiQCAhQsX1jgnSZJZ+wKZ9ewDHx8frFixAitWrKj1fJMmTfDVV1+ZUzUREREZ4cYliNbAByIREZH8NcKegrrApICIiGSvMc4pAKo2B9y1axfOnTuHsrIyg3PTpk0zuT4mBURERDJ09OhRDB48GMXFxSgqKkKzZs1w6dIlNGnSBJ6enmYlBXx0MhERyV/1NseWHDIzY8YMDBs2DFeuXIFarcb+/ftx9uxZdOvWDW+88YZZdTIpICIi+WuEOxqmpaXh+eefh4ODAxQKBUpLS+Hv74+lS5fiP//5j1l1MikgIiLZq55TYMkhN05OTnBwqPoz7unpiXPnzgGo2k04KyvLrDo5p4CIiEiGunbtikOHDqFt27b497//jXnz5uHSpUtYu3YtOnbsaFad7CkgIiL5a4TDB3FxcfDx8QEALF68GHfccQeeeeYZXLx4EatXrzarTvYUEBGR/Fk6BCDDpKB79+76nz09PZGammpxnewpICIikqH7778feXl5NcoLCgpw//33m1UnewqIiEj+GuGOhjt37qyxYREAlJSU4IcffjCrTiYFREQkf40oKTh27Jj+599++w1arVb/urKyEqmpqfDz8zOrbiYFREREMtKlSxdIkgRJkmodJlCr1Td9YOHtMCkgIiLZa0zPPsjMzIQQAoGBgTh48CBatGihP6dUKuHp6QmFQmFW3UwKiIiIZKR169YA6ubRyVx9QEREJEPvv/8+vvzyS/3rOXPmwN3dHb1798bZs2fNqpNJARERyV8j3bxIrVYDAPbt24eVK1di6dKlaN68OWbMmGFWnRw+ICIi2WtMcwqqZWVlITg4GACwefNmPPzww5g0aRLCwsLQr18/s+pkTwEREdmHRtRLAACurq64fPkyAGD79u0YMGAAAMDZ2Rl///23WXWyp4CIiEiGBgwYgKeeegpdu3bF77//jsGDBwMAfv31V7Rp08asOtlTQERE8tcI5xQkJiaiV69euHjxIjZu3AgPDw8AwJEjR/Doo4+aVSd7CoiISPYa45wCd3d3rFy5skb5ggULzK6TSQEREZFMHDt2DB07doSDg4PBdse16dy5s8n1MykgIiL5ayTPPujSpQu0Wi08PT312x0L8U/w1a8lSUJlZaXJ9TMpICIi2WsswweZmZn6bY0zMzOtXj+TAiIiIpmo3uL4xp+thasPiIhI/my8+uC1116DJEl47rnn9GUlJSWIiYmBh4cHXF1dMXLkSOTk5Fj2Rtepi22OG3xPQVm5AmXlto6iYSorV9T6Mxm6vm0UEIBkw2AaMMV1/yoq5DLAagPXtw1/726u3tvGhnMKDh06hNWrV9eY2Ddjxgx8+eWX+N///geNRoOpU6fioYcewo8//mhBoP+Ii4tDcnIygH+2OU5ISMDWrVsxY8YMfPbZZybX2eCTgsSPH4Szs7Otw2jwlq8dbesQZGGwV5GtQ5CFoS0KbR2CLPD37nZKbB2AyQoKCgxeq1QqqFSqm15fWFiIqKgovPXWW1i0aJG+PD8/H++88w7WrVuH+++/HwCQkpKC9u3bY//+/bjnnnssjrVRbHOcmJiI0NBQ9OjRw9ahEBGRTFRPNLTkAAB/f39oNBr9ER8ff8v3jYmJwZAhQ9C/f3+D8iNHjqC8vNyg/M4770SrVq2wb98+q3zmRrHNcUxMDGJiYlBQUACNRoOYMZvQvJmto2qYysoV+m8qMx7/BEon05efNAZsJ+OwnYzDdjJOWbkC8W8Nr783tNLwQVZWFtzc3PTFt+ol+Pjjj/HTTz/h0KFDNc5ptVoolUq4u7sblHt5eUGr1VoQ6D/qYpvjBpcU3EjpVAmlk62jaPiq2on/ON0O28k4bCfjsJ0aECslBW5ubgZJwc1kZWVh+vTp+Oabb2w2xJ2YmIiXX34ZWVlZ3OaYiIjIVo4cOYILFy7gX//6l76ssrISu3fvxsqVK/H111+jrKwMeXl5Br0FOTk58Pb2tkoMdbHNcYObU0BERGQqa80pMNYDDzyA48ePIy0tTX90794dUVFR+p+dnJywY8cO/T0nT57EuXPn0KtXL6t97h9++AFjx45F79698eeffwIA1q5diz179phVH3sKiIhI/up5SWLTpk3RsWNHgzIXFxd4eHjoyydMmICZM2eiWbNmcHNzw7PPPotevXpZZeUBAGzcuBGPP/44oqKi8NNPP6G0tBRA1cqHuLg4fPXVVybXyZ4CIiKiOrB8+XIMHToUI0eORN++feHt7W3W3gE3s2jRIqxatQpvvfUWnJz+mXwXFhaGn376yaw62VNARESy1xCefbBz506D187OzkhMTERiYqLlldfi5MmT6Nu3b41yjUaDvLw8s+pkTwEREcmfjbc5tgVvb29kZGTUKN+zZw8CAwPNqpNJARERkQxNnDgR06dPx4EDByBJEs6fP4+PPvoIs2bNwjPPPGNWnRw+ICIi+bPhsw9s5cUXX4ROp8MDDzyA4uJi9O3bFyqVCrNmzcKzzz5rVp1MCoiISPYkWPasMzk+J02SJLz00kuYPXs2MjIyUFhYiNDQULi6uuLvv/+GWq02uU4OHxAREcmYUqlEaGgo7r77bjg5OWHZsmUICAgwqy4mBUREJH+NaKJhaWkp5s6di+7du6N3797YvHkzgKqnMAYEBGD58uWYMWOGWXVz+ICIiGSvISxJrC/z5s3D6tWr0b9/f+zduxejRo3Ck08+if3792PZsmUYNWoUFAqFWXUzKSAiIvlrRBMN//e//+GDDz7A8OHD8csvv6Bz586oqKjAzz//DEmybHYEhw+IiIhkJDs7G926dQMAdOzYESqVCjNmzLA4IQDYU0BERPZCRt/2LVFZWQmlUql/7ejoCFdXV6vUzaSAiIhkrzHNKRBCYNy4cVCpVACAkpISTJ48GS4uLgbXmfOcBSYFREREMhIdHW3weuzYsVarm0kBERHJXyOaaJiSklJndTMpICIi2WtMwwd1iasPiIiICAB7CoiIyB40ouGDusSkgIiIZI/DB9bB4QMiIiICwJ4CIiKyBxw+sAomBUREJH9MCqyCSQEREcke5xRYB+cUEBEREQD2FBARkT3g8IFVMCkgIiLZk4SAJMz/y27JvfaEwwdEREQEgD0FRERkDzh8YBVm9RRotVpMnz4dwcHBcHZ2hpeXF8LCwpCcnIzi4mLk5ubi2WefRUhICNRqNVq1aoVp06YhPz/f2vETERHpVx9YcpAZPQWnT59GWFgY3N3dERcXh06dOkGlUuH48eNYs2YN/Pz8EBgYiPPnz+ONN95AaGgozp49i8mTJ+P8+fP49NNP6+JzEBERkYVMTgqmTJkCR0dHHD58GC4uLvrywMBAREZGQggBSZKwceNG/bmgoCAsXrwYY8eORUVFBRwda75taWkpSktL9a8LCgpMDY2IiBorDh9YhUnDB5cvX8b27dsRExNjkBBcT5KkWsvz8/Ph5uZWa0IAAPHx8dBoNPrD39/flNCIiKgR4/CBdZiUFGRkZEAIgZCQEIPy5s2bw9XVFa6urnjhhRdq3Hfp0iW8+uqrmDRp0k3rnjt3LvLz8/VHVlaWKaERERGRhayy+uDgwYPQ6XSIiooyGAIAqoYBhgwZgtDQUMTGxt60DpVKBZVKZY1wiIioseHwgVWYlBQEBwdDkiScPHnSoDwwMBAAoFarDcqvXr2KiIgING3aFJs2bYKTk5OF4RIREdXEZx9Yh0nDBx4eHhgwYABWrlyJoqKiW15bUFCAgQMHQqlUYsuWLXB2drYoUCIiopsSVjjI9H0KkpKSUFFRge7du2PDhg04ceIETp48iQ8//BDp6elQKBT6hKCoqAjvvPMOCgoKoNVqodVqUVlZWRefg4iIiCxk8pyCoKAgHD16FHFxcZg7dy6ys7OhUqkQGhqKWbNmYcqUKTh48CAOHDgAoGrI4XqZmZlo06aNVYInIiKqxiEAy5k10dDHxwcrVqzAihUraj3fr18/CD5cgoiI6osQVYcl9xMfiERERERV+EAkIiKSPa4+sA4mBUREJH/cp8AqOHxAREREANhTQEREdkDSVR2W3E9MCoiIyB5w+MAqOHxAREREANhTQEREdoCrD6yDSQEREckfNy+yCiYFREQke+wpsA7OKSAiIiIA7CkgIiJ7wNUHVsGkgIiIZI/DB9bB4QMiIiICwJ4CIiKyB1x9YBVMCoiISPY4fGAdHD4gIiIiAOwpICIie8DVB1bBpICIiGSPwwfWweEDIiIiAsCeAiIisgc6UXVYcj8xKSAiIjvAOQVWwaSAiIhkT4KFcwqsFom8cU4BERERAWBPARER2QPuaGgVTAqIiEj2uCTROjh8QEREZKL4+Hj06NEDTZs2haenJ0aMGIGTJ08aXFNSUoKYmBh4eHjA1dUVI0eORE5Ojo0iNk6D7ykoK1egrNzWUTRMZeWKWn8mQ2wn47CdjMN2Mk69t009rz7YtWsXYmJi0KNHD1RUVOA///kPBg4ciN9++w0uLi4AgBkzZuDLL7/E//73P2g0GkydOhUPPfQQfvzxRwsCrVuSEA1zIKWgoAAajQYvvvginJ2dbR0OERGZqKSkBK+99hry8/Ph5uZWJ+9R/bfi3n7z4eho/t+KiooS/LBzAbKysgxiValUUKlUt73/4sWL8PT0xK5du9C3b1/k5+ejRYsWWLduHR5++GEAQHp6Otq3b499+/bhnnvuMTvWutTghg8SExMRGhqKHj162DoUIiJqZPz9/aHRaPRHfHy8Uffl5+cDAJo1awYAOHLkCMrLy9G/f3/9NXfeeSdatWqFffv2WT9wK2lwwwcxMTGIiYnRZ38xYzaheTNbR9UwlZUrsHztaADAjMc/gdKp0sYRNUxsJ+OwnYzDdjJOWbkC8W8Nr7831F07LLkfqLWn4La36nR47rnnEBYWho4dOwIAtFotlEol3N3dDa718vKCVqu1INC61eCSghspnSqhdLJ1FA1fVTvxH6fbYTsZh+1kHLZTwyEJAcmC0fDqe93c3Ewe6oiJicEvv/yCPXv2mP3+DUWDGz4gIiKSi6lTp2Lr1q34/vvv0bJlS325t7c3ysrKkJeXZ3B9Tk4OvL296zlK4zEpICIi+RNWOEx5OyEwdepUbNq0Cd999x0CAgIMznfr1g1OTk7YsWOHvuzkyZM4d+4cevXqZc4nrBcNfviAiIjotup5R8OYmBisW7cOn3/+OZo2baqfJ6DRaKBWq6HRaDBhwgTMnDkTzZo1g5ubG5599ln06tWrwa48AJgUEBGRHajvHQ2Tk5MBAP369TMoT0lJwbhx4wAAy5cvh4ODA0aOHInS0lKEh4cjKSnJ/CDrAZMCIiIiExmzxY+zszMSExORmJhYDxFZB5MCIiKSPz4QySqYFBARkexJuqrDkvuJqw+IiIjoGvYUEBGR/HH4wCqYFBARkfzV81MS7RWHD4iIiAgAewqIiMgOWOvZB40dkwIiIpI/zimwCg4fEBEREQD2FBARkT0QACzZa4AdBQCYFBARkR3gnALrYFJARETyJ2DhnAKrRSJrnFNAREREANhTQERE9oCrD6yCSQEREcmfDoBk4f3E4QMiIiKqwp4CIiKSPa4+sA4mBUREJH+cU2AVHD4gIiIiAOwpICIie8CeAqtgUkBERPLHpMAqOHxAREREANhTQERE9oD7FFgFkwIiIpI9Lkm0DiYFREQkf5xTYBVmzSnQarWYPn06goOD4ezsDC8vL4SFhSE5ORnFxcUAgDVr1qBfv35wc3ODJEnIy8uzZtxERERkZSb3FJw+fRphYWFwd3dHXFwcOnXqBJVKhePHj2PNmjXw8/PD8OHDUVxcjIiICERERGDu3Ll1ETsREVEVnQAkC77t69hTAJiRFEyZMgWOjo44fPgwXFxc9OWBgYGIjIyEuNYF89xzzwEAdu7caZVAiYiIborDB1ZhUlJw+fJlbN++HXFxcQYJwfUkybzpn6WlpSgtLdW/LigoMKseIiIiMo9JcwoyMjIghEBISIhBefPmzeHq6gpXV1e88MILZgUSHx8PjUajP/z9/c2qh4iIGiPxT2+BOQfYUwBYafOigwcPIi0tDR06dDD4tm+KuXPnIj8/X39kZWVZIzQiImoMLEkILB16sCMmDR8EBwdDkiScPHnSoDwwMBAAoFarzQ5EpVJBpVKZfT8RERFZxqSeAg8PDwwYMAArV65EUVFRXcVERERkGp2w/CDThw+SkpJQUVGB7t27Y8OGDThx4gROnjyJDz/8EOnp6VAoFACq9jJIS0tDRkYGAOD48eNIS0tDbm6udT8BERGR0Fl+kOlLEoOCgnD06FHExcVh7ty5yM7OhkqlQmhoKGbNmoUpU6YAAFatWoUFCxbo7+vbty8AICUlBePGjbNO9ERERGQ1Zm1z7OPjgxUrVmDFihU3vSY2NhaxsbHmxkVERGQ87lNgFXz2ARERyZ/OwmWFnFMAgEkBERHZA/YUWIVV9ikgIiIi+WNPARERyZ+AhT0FVotE1pgUEBGR/HH4wCo4fEBEREQA2FNARET2QKcDYMEGRDpuXgQwKSAiInvA4QOr4PABERERAWBPARER2QP2FFgFkwIiIpI/7mhoFRw+ICIiIgDsKSAiIjsghA7CgscfW3KvPWFSQERE8ieEZUMAnFMAgEkBERHZA2HhnAImBQA4p4CIiIiuYU8BERHJn04HSBbMC+CcAgBMCoiIyB5w+MAqOHxAREREANhTQEREdkDodBAWDB9wSWIVJgVERCR/HD6wCg4fEBEREQD2FBARkT3QCUBiT4GlmBQQEZH8CQHAkiWJTAoADh8QERHRNewpICIi2RM6AWHB8IFgTwEA9hQQEZE9EDrLDzMkJiaiTZs2cHZ2Rs+ePXHw4EErf7D6xaSAiIhkT+iExYepNmzYgJkzZ2L+/Pn46aefcNdddyE8PBwXLlyog09YPxr88EFZuQJl5baOomEqK1fU+jMZYjsZh+1kHLaTcRpD2yxbtgwTJ07Ek08+CQBYtWoVvvzyS7z77rt48cUXbRydeSTRQAdS8vPz4e7ujhkzZkClUtk6HCIiMlFpaSmWL1+OvLw8aDSaOnmPgoICaDQa9MFgOMLJ7HoqUI49+ApZWVlwc3PTl6tUqlr/BpWVlaFJkyb49NNPMWLECH15dHQ08vLy8Pnnn5sdiy01uJ6CxMREJCYmoqysDACwfPlyG0dERESWuHr1ap0lBUqlEt7e3tij/criulxdXeHv729QNn/+fMTGxta49tKlS6isrISXl5dBuZeXF9LT0y2OxVYaXFIQExODmJgY6HQ6tGvXDkeOHIEkSbYOC0BVRurv718jk7S1Hj164NChQ7YOQ4/tZBy2k3HYTsZpiO0khEC3bt3g6+tbZ+/h7OyMzMxM/RdJSwghavy9aWw91Q0uKajm4OAApVJZZ9mlJdzc3BrMLx0AKBSKBhVPNbaTcdhOxmE7GaehtZNSqYSDQ93OaXd2doazs3OdvseNmjdvDoVCgZycHIPynJwceHt712ss1tSgVx/ExMTYOgRZYDsZh+1kHLaTcdhOxrHXdlIqlejWrRt27NihL9PpdNixYwd69eplw8gs02AnGjZE1RNa8vPzG1Qm3tCwnYzDdjIO28k4bKf6t2HDBkRHR2P16tW4++67kZCQgE8++QTp6ek15hrIRYMdPmiIVCoV5s+f3+jGmEzFdjIO28k4bCfjsJ3q3yOPPIKLFy9i3rx50Gq16NKlC1JTU2WbEADsKSAiIqJrGvScAiIiIqo/TAqIiIgIAJMCIiIiuoZJAREREQFgUkBERETXMCmohVarxfTp0xEcHAxnZ2d4eXkhLCwMycnJKC4uBgCsWbMG/fr1g5ubGyRJQl5enm2DtoHbtVNubi6effZZhISEQK1Wo1WrVpg2bRry8/NtHXq9Mub/p6effhpBQUFQq9Vo0aIFIiMjZb1/ujmMaadqQggMGjQIkiRh8+bNtgnYRrKysjB+/Hj4+vpCqVSidevWmD59Oi5fvqy/Zty4cZAkyeCIiIiwYdQkF9yn4AanT59GWFgY3N3dERcXh06dOkGlUuH48eNYs2YN/Pz8MHz4cBQXFyMiIgIRERGYO3eurcOud8a0U2BgIM6fP4833ngDoaGhOHv2LCZPnozz58/j008/tfVHqBfG/v/UrVs3REVFoVWrVsjNzUVsbCwGDhyIzMxMKBT2/whaY9upWkJCQoN5Jkp9On36NHr16oV27dph/fr1CAgIwK+//orZs2dj27Zt2L9/P5o1awYAiIiIQEpKiv5e7l9ARhFkIDw8XLRs2VIUFhbWel6n0xm8/v777wUAceXKlXqIruEwtZ2qffLJJ0KpVIry8vK6DK/BMLedfv75ZwFAZGRk1GV4DYYp7XT06FHh5+cn/vrrLwFAbNq0qZ6itL2IiAjRsmVLUVxcbFD+119/iSZNmojJkycLIYSIjo4WkZGRNoiQ5I7DB9e5fPkytm/fjpiYGLi4uNR6TWP8dnIjS9qpegtWR0f776Qyt52KioqQkpKCgICAGo9xtUemtFNxcTEee+wxJCYmyvqhM+bIzc3F119/jSlTpkCtVhuc8/b2RlRUFDZs2ABxbT+6nTt3wtPTEyEhIXjmmWcMhheIboZJwXUyMjIghEBISIhBefPmzeHq6gpXV1e88MILNoqu4TC3nS5duoRXX30VkyZNqq9QbcrUdkpKStKXb9u2Dd988w2USmV9h13vTGmnGTNmoHfv3oiMjLRFqDZ16tQpCCHQvn37Ws+3b98eV65cwcWLFxEREYEPPvgAO3bswJIlS7Br1y4MGjQIlZWV9Rw1yY39f12zgoMHD0Kn0yEqKgqlpaW2DqfBulU7FRQUYMiQIQgNDUVsbKxtAmwgbtZOUVFRGDBgAP766y+88cYbGD16NH788cd6fyRsQ3FjO23ZsgXfffcdjh49auvQbEoYsTP9mDFj9D936tQJnTt3RlBQEHbu3IkHHnigLsMjmWNPwXWCg4MhSRJOnjxpUB4YGIjg4OAaXXaNlantdPXqVURERKBp06bYtGkTnJyc6jNcmzG1nTQaDdq2bYu+ffvi008/RXp6OjZt2lSfIduEse303Xff4Y8//oC7uzscHR31Q1AjR45Ev3796jvselfdTidOnKj1/IkTJ3DHHXegRYsWNc4FBgaiefPmyMjIqOswSeaYFFzHw8MDAwYMwMqVK1FUVGTrcBosU9qpoKAAAwcOhFKpxJYtWxrVt15L/n8SQkAI0Sh6poxtpxdffBHHjh1DWlqa/gCA5cuXG8yyt1fV7ZSUlIS///7b4JxWq8VHH32ERx55pNZ5KtnZ2bh8+TJ8fHzqK1ySKSYFN0hKSkJFRQW6d++ODRs24MSJEzh58iQ+/PBDpKen65eHabVapKWl6TPv48ePIy0tDbm5ubYMv94Y007VCUFRURHeeecdFBQUQKvVQqvVNpqxTWPa6fTp04iPj8eRI0dw7tw57N27F6NGjYJarcbgwYNt/RHqhTHt5O3tjY4dOxocANCqVSsEBATY+BPUj5UrV6K0tBTh4eHYvXs3srKykJqaigEDBsDPzw+LFy9GYWEhZs+ejf379+PMmTPYsWMHIiMjERwcjPDwcFt/BGrobLbuoQE7f/68mDp1qggICBBOTk7C1dVV3H333eL1118XRUVFQggh5s+fLwDUOFJSUmwbfD26XTtVL9es7cjMzLR1+PXmdu30559/ikGDBglPT0/h5OQkWrZsKR577DGRnp5u69DrlTG/dzdCI1uSKIQQZ86cEdHR0cLLy0s4OTkJf39/8eyzz4pLly4JIYQoLi4WAwcOFC1atBBOTk6idevWYuLEiUKr1do4cpIDSQgjZq0QERGR3ePwAREREQFgUkBERETXMCkgIiIiAEwKiIiI6BomBURERASASQERERFdw6SAiIiIADApICIiomuYFBAREREAJgVERER0DZMCIiIiAgD8P0A9Sdh/UPTrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show the leakage matrix but cap it off at 100 MΩ\n",
    "fig, ax = plt.subplots()\n",
    "plt.title(f'Gate Leakage ({modulation_mV}mV)')\n",
    "img = ax.imshow(leakage_megaohm, interpolation='none', vmin=0, vmax=100)\n",
    "ticks = np.arange(len(arrangement.contact_names))\n",
    "minorticks = np.arange(-0.5, len(ticks), 1)\n",
    "ax.set_xticks(ticks, labels=arrangement.contact_names)\n",
    "ax.set_yticks(ticks, labels=arrangement.contact_names)\n",
    "ax.set_xticks(minorticks, minor=True)\n",
    "ax.set_yticks(minorticks, minor=True)\n",
    "ax.grid(which='minor', color='grey', linewidth=1.5)\n",
    "plt.gca().invert_yaxis()\n",
    "colorbar = fig.colorbar(img)\n",
    "colorbar.set_label('Resistance (MΩ)')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  },
  "nbsphinx": {
   "execute": "never"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}