diff --git a/control_notebooks/software_testing/Correlation_Testing.ipynb b/control_notebooks/software_testing/Correlation_Testing.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..f9d194b073f671a4fb0945c0bf2008a00f325aa4
--- /dev/null
+++ b/control_notebooks/software_testing/Correlation_Testing.ipynb
@@ -0,0 +1,5497 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "c7a798c5-e077-4067-a541-3d1ebd818b35",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import yaml\n",
+    "from AWAControl import MAGNET_CONFIG\n",
+    "import time\n",
+    "from xopt import Evaluator\n",
+    "from epics import caput\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "9b8fc36c-e609-41b6-bfa0-d56864105b1d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from AWAControl.badger.environments.awa import Environment\n",
+    "awa_env = Environment()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "6e456f65-4474-4850-b772-2fd0a428bd2d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from xopt import VOCS\n",
+    "from xopt.generators import get_generator\n",
+    "from xopt.generators.bayesian.models.standard import StandardModelConstructor\n",
+    "from xopt import Xopt\n",
+    "import time\n",
+    "from epics import caget_many\n",
+    "from xopt.utils import get_local_region\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "002d15fd-ff5e-4d48-a696-caa8427bca2d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "change BNC to V6 y\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "displaying image\n",
+      "fitting image\n",
+      "{'Cx': 192.79179879120724,\n",
+      " 'Cy': 139.28809239797994,\n",
+      " 'Sx': 15.247245514535376,\n",
+      " 'Sy': 13.848135818142765,\n",
+      " 'bb_penalty': -92.75713506935274,\n",
+      " 'correlation': 7.86323193835787,\n",
+      " 'log10_total_intensity': 6.840520422051217,\n",
+      " 'total_intensity': 6926605.0}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "CA.Client.Exception...............................................\n",
+      "    Warning: \"Identical process variable names on multiple servers\"\n",
+      "    Context: \"Channel: \"AWANIFG:ImgData\", Connecting to: 192.168.2.57:57744, Ignored: 192.168.0.2:57744\"\n",
+      "    Source File: ../cac.cpp line 1320\n",
+      "    Current Time: Thu Jul 11 2024 13:47:22.711624839\n",
+      "..................................................................\n",
+      "CA.Client.Exception...............................................\n",
+      "    Warning: \"Identical process variable names on multiple servers\"\n",
+      "    Context: \"Channel: \"AWANIFG:ImgData\", Connecting to: 192.168.2.57:57744, Ignored: awa3.hep.anl.gov:57744\"\n",
+      "    Source File: ../cac.cpp line 1320\n",
+      "    Current Time: Thu Jul 11 2024 13:47:22.713127833\n",
+      "..................................................................\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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yUqkEAIic4UpEZKFFuhbMmwcUFgJDhgD33QcA6B1hWhjhaiPLCwDgpZeAsDDg7Fng889tMFAickZ2LS2YM2cOFi9ejGXLluHUqVN45JFHUFJSgpkzZwIApk2bhueff968/eTJk/H5559j+fLlSEpKwsaNGzF37lxMnjzZHNASERFgNIrILWnmrgUpKcDSpdLl99+XygFQsTDCycZmZAHA1xd45RXp8ttvs7csEVnlYs87nzp1KrKysjBv3jykp6ejf//+WL9+vXkCWEpKikUG9sUXX4QgCHjxxRdx9epVBAcHY/LkyXhdnuVKREQAgLxSLYymL6r8PZspI/vWW9KSs9ddJ03QMukaJrXdOptR3LTjT58OvPqq1L1gyRLg0UebdjwicjqC2Ma+ky8sLISvry8KCgo48YuInNa5jCJc/8EO+LqrcGT+ONvfwdWrQMeOgFYLbN0KjB5tvulsRhHGfbADXmoXHHtpHAShCcvjfv65FMC2bw+cPw+oW6gnLhHZTUNiNYfqWkBERPUjt94KbK5s7DvvSEHsiBHAqFEWN0UHesJFIaC4XI/UgiaWBMycCUREAFeuAMuWNe1YROR0GMgSETmhXFMgG9AcgWxWVsXKW3PnSi2zKnF1USAmyBOAlJ1tEjc3qbcsALz5JmAwNO14RORUGMgSETmhnOYMZJcsAcrKgEGDpNW4rOgaKtXJnmtqIAsADzwABAQASUnAunVNPx4ROQ0GskRETijX1Hor0NattwyGinZYs2dXy8bKuoR6AbDBhC8AcHc3t/bCwoVNPx4ROQ0GskRETkhuvWXzjOy6dcClS1KGdOrUGjczZ2QzbRDIAsAjj0hB84YNwLlztjkmETk8BrJERE6oorTAxrP8P/tMOr/3XilTWoOupozs+Ywi2yxYExMD3HCDdJkLJBCRCQNZIiInlNscXQvOnwfWr5cyo488UuumHQI9oVIKKNEacDW/zDb3P2uWdP7NN0BpqW2OSUQOjYEsEZETapauBYsWSecTJ0o9ZGuhUirQMUjKyp6zRZ0sAIwfL91vfj7w00+2OSYROTQGskRETsjmXQv0euC776TLDz9cr10qJnzZoHMBACgUwEMPSZflpXGJqE1jIEtE5GREUUReiY27Fvz9N5CZCYSEABMm1GsXecKXTToXyP79bymg3bULuHDBdsclIofEQJaIyMkUlumhN0oTrGyWkf32W+n8rrsAlapeu8gTvs5l2igjC0irfMXHS5e//952xyUih8RAlojIyeSYWm95qV2gdlE2/YD5+cCaNdLladPqvVsX86IIxTAabdC5QCaP4dtvAVt0RCAih8VAlojIydh8oteqVUB5OdC7N9C/f7136xDgAbWLAmU6A06kFtpmLAAwZQrg5QVcvAjs3m274xKRw2EgS0TkZLKLbRzILlsmnU+bVuNKXta4KBUY1ysMAPBtQrJtxgIAnp7A7bdbjo2I2iQGskRETkbOyAbZYqJXUpI0sUqhAO6+u8G7zxgWDQD47UgqcorLmz4emVxe8PPPUraYiNokBrJERE7GpsvT/vyzdD5mjDTRqoEGRvmhX3tfaPVG/LQvpenjkV17LdCuHVBQIHVUIKI2iYEsEZGTsenytCtXSufyV/kNJAgCZgyPBgB8t+cSdAZj08cESBni//s/6bI8RiJqcxjIEhE5GZstT3vxIpCYKAWNt9zS6MNM6hOBYG81MgrL8dfx9KaNqTI5uP7tN5YXELVRDGSJiJyMzboW/PKLdD56tLQQQiO5uihw59AoAMAfR1KbNqbK4uKk8oLCQmDjRtsdl4gcBgNZIiInkyN3LWjqZK8mlhVUdk1MAADgnK2WqwWkTPFtt0mXWV5A1CYxkCUicjI2KS1ITgb275eCxVtvbfKY5MURLuWWQqMzNPl4ZiwvIGrTGMgSETkRURRtU1qwapV0PmpUk8oKZEFervDzUEEUgQtZxU0+ntmwYUB4uNS9YNMm2x2XiBwCA1kiIidSXK6H1tQZILApXQvk+li5M0ATCYKAriEVS9baTOXyAnnMRNRmMJAlInIicjbWXaWEu6uycQdJTwf27pUuT5lim4EB6BzqBQA4l2nDOlmgoqPC2rWAwYZlC0TU6jGQJSJyIjm2KCtYuxYQRWDIkEYtglCTriFSIHvWlhlZABg5EvDzA7KyKgJwImoTGMgSETmRXFPHgsCmdCz4/Xfp/KabbDCiCvKEr/OZNg5kVSrghhuky/LYiahNYCBLROREmjzRq7S0oierzQNZKSN7KaekWucCo1GEvimrfslj/e23xh+DiBwOA1kiIifS5NKCTZsAjQaIjgb69LHdwAAEe6nh666CUQQuZpVY3Pbib8fR+6UNuJRTUsPedZgwQcrMnj4NnD1rg9ESkSNgIEtE5ERyS6Reqo3uIStnNG+6CRAEG41KIggCulqZ8HUhqxg/7UuBRmfEnos5jTu4r6+0AhkA/PFHE0dKRI6CgSwRkRPJK9UBAPw8GhHIGgwVQaCNywpkna204Fq84yJEUbp8Na+s8QeXx8w6WaI2g4EsEZETyTcFsv6NCWT37ZNm/vv6Atdea+ORSeSM7FnTUrWZhRqsPnjVfPuV/CYEspMnS+e7dgE5jczsEpFDYSBLRORECsqkGlk/D1XDd163TjofP16qN20GXUIsOxcs+ScZWoMRKqVUxmAtI2s0injh12P4cseF2g/eoYNU12s0An//bduBE1GrxECWiMiJyBlZP/cmBLJyK6tmIGdkk3NKsGRXEn7YcwkAcO+IGADAVSsZ2dPpRfhxbwre2XAGBqNY+x1MnCid//WX7QZNRK0WA1kiIieSXyYFsr4NzcimpwMHD0qXJ0yw8agqBHur4ePmAqMIvLL2JIrK9egc4oVpcdHSMAo01YLVpGypk4HOICKtoI7SAzkIX79eyswSkVNzsfcAiIjINkRRREFja2Q3bJDOBw4EQkNtPLIKgiBg1pjOWHM4FZH+7ugY7IXbB7dHmI8bXBQC9EYRmUUahPu6m/dJrtSSKyW3FO39PWq+g2HDAB8fqdY3MVFanYyInBYDWSIiJ1GqNUBrWlSgwTWy8lfx8lfzzeihUZ3w0KhO1a4P83XDlbwyXM0rswhk5YwsAFzOLQWq71pBpQLi44HVq6XHxECWyKmxtICIyEnIZQWuSgXcVcr676jXV0yOaoFAtibt/KTgtWqdbHKlQPZSTmndB2KdLFGbwUCWiMhJ5JdKHQt8PVQQGrKYwb59QF4e4OcHxMY2z+DqoZ2/FMheqdK5oGppQZ3kGt+9e4HsbJuNj4haHwayREROoqCxHQvkzOW4cYCL/SrO2lvJyBZpdMgu1pp/vlyfQLZ9e6kNlyiyDReRk2MgS0TkJOTSggbXx65fL53bsawAqMjIVu4lm5xtGbjWKyMLVDwW+bERkVNiIEtE5CTkHrK+7g3oWJCTI83uB6SFEOyonZ/UjSC1Ukb2Yra0cELPcB8A0hK8hRpd3QeTyws2bYJ5/VsicjoMZImInER+Y1b12rpVCvR69QLCw5tpZPVjzsjml0E0BZ9yRrZXhA+CvKQAPaU+E77i4gB3dyAtDTh5snkGTER2x0CWiMhJNKpGdtMm6Tw+vhlG1DDhvm4ApDZicnZZnugVHeSJyAApY1uvOlk3N2DkSOmy/BiJyOkwkCUichLm5WkbkpFtRYGsm0qJIC81gIoJX3IP2Y5BnogyBbL1rpOVHxMDWSKnxUCWiMhJyKUFvvVd1SspCbhwAVAqgVGjmnFk9Ve1BVfljKwcyF5qaCC7bRugq0ddLRE5HAayREROIr+hpQWbN0vn11wDeHs306gapnILrrwSrfkxRQdWBLL1Ki0AgH79gMBAoLhY6pVLRE6HgSwRkZMoaGj7rY0bpfNWUFYgq9yCK8mUjQ3zcYO7q7LhpQUKBTB2rHSZ5QVETomBLBGRk6jIyNajtMBorMjItqZA1pSRTc0vMy9NGx0kBbBRgdL51bwy6A3G+h2QdbJETs1+S7gQEZFNNaj91pEjUg9ZLy+7LktblRzI/nMhG1fypcxrTJAnACDU2w2uLgpo9UakFWjMXQxqJQeye/YARUWtpoSCiGyDGVkiIieg0Rmg0UlZSt/6BLJyhnL0aEDVwJXAmlHfSF/4uqtQpNHj+NVCAFJ9LAAoFAIiTaUH9S4viIkBOnYE9Hpg+/ZmGTMR2Q8DWSIiJyDXxyoVArzV9fiyrRW13aosxNsN/zx3HT6/eyBuG9geIzoH4ZYB7cy3N7hOFmB5AZETYyBLROQEKpanVUEQhNo31miAnTuly60skAUAL7ULJvYJx3v/6ofv749FiI+b+bYuoVJpwM5zWfU/IANZIqfFQJaIyAnkl5rqY+vTeishASgrA8LCgJ49m3lktiVnZ/8+kYGMQg0AIL1Ag9fWnqx56drrrgMEAThxQlqyloicBgNZIiInkG8qLWhQfWx8vBTgOZAe4T4Y3MEfeqOI5fsuw2gU8fhPh/DVriR8suWc9Z0CA4GBA6XLcqcGInIKdg9kFy5ciOjoaLi5uSE2Nhb76mhanZ+fj1mzZiE8PBxqtRpdu3bFunXrWmi0REStU0FDFkNopfWx9fXvazoAAH7al4Ll+y9jX3IuAODY1YKad2J5AZFTsmsgu2LFCsyZMwfz58/HwYMH0a9fP4wfPx6ZmZlWt9dqtbj++uuRnJyMVatW4cyZM1i8eDHatWtndXsioraiovVWHT1k8/KAAweky/JiAQ5mYp8wBHi6Ir1Qg7m/HTdffy6zGBqdwfpOlQNZUWyBURJRS7BrIPv+++/jgQcewMyZM9GzZ08sWrQIHh4eWLJkidXtlyxZgtzcXKxZswbDhw9HdHQ0Ro0ahX79+rXwyImIWhfzYgh1lRZs3SothtC9O9C+fQuMzPbULkr8a3AkAMBgFNEj3AcBnq4wGEWcSS+yvtPw4YBaDVy9Cpw504KjJaLmZLdAVqvVIjExEfGVvtpSKBSIj49HQkKC1X1+//13xMXFYdasWQgNDUXv3r3xxhtvwGCo4RM4gPLychQWFlqciIicTV59V/Vy8LIC2d2xUVAIUonvglv7oFeEDwDgRGoN7/Hu7sCIEdJleWleInJ4dgtks7OzYTAYEBoaanF9aGgo0tPTre5z8eJFrFq1CgaDAevWrcPcuXPx3nvv4bXXXqvxfhYsWABfX1/zKTIy0qaPg4ioNSio76peThLIRgZ4YNm9Q7Fs5lD0j/RD73a+AIDjqayTJWpL7D7ZqyGMRiNCQkLw5ZdfYtCgQZg6dSr+97//YdGiRTXu8/zzz6OgoMB8unz5cguOmIioZdSrtODKFeDcOUChAEaNaqGRNZ+RXYJxbddgAEDvCCmQPVHbhC+5Jnj7dqCWb/KIyHHUY/mX5hEUFASlUomMjAyL6zMyMhAWFmZ1n/DwcKhUKiiVSvN1PXr0QHp6OrRaLVxdq3+lplaroVarbTt4IqJWpvKCCDWSl2gdMADw82v+QbUgubTgVHoRdAYjVEoreZoBAwBvb6CgADhypKIlFxE5LLtlZF1dXTFo0CBsrtTTz2g0YvPmzYiLi7O6z/Dhw3H+/HkYjUbzdWfPnkV4eLjVIJaIqK2Ql6ittWuBHMiOHt38A2phUQEe8Fa7QKs34nxmsfWNXFyAkSOly9u2tdjYiKj52LW0YM6cOVi8eDGWLVuGU6dO4ZFHHkFJSQlmzpwJAJg2bRqef/558/aPPPIIcnNz8cQTT+Ds2bP4888/8cYbb2DWrFn2eghERK1CvVb2koM3JwxkFQoBPU1Z2eO1lBcY5cfOQJbIKdittAAApk6diqysLMybNw/p6eno378/1q9fb54AlpKSAoWiItaOjIzEhg0b8NRTT6Fv375o164dnnjiCTz77LP2eghERHan1RtRopVqPmuskb16taI+Vp6972R6t/PF3qRcnEgtxO1Wbl+VeAUrz7phBQDs2CHVyVYqVSMix2PXQBYAZs+ejdmzZ1u9bZuVT8xxcXHYs2dPM4+KiMhxyGUFggB4u9UQyMplBf37O119rKxXpYzssSsF2HQqA8HeavRt74uVB67guz2XoPTvgCK1B7wLCoDDh4FBg+w7aCJqErsHskRE1DRy6y0fNxWUCsH6Rk5cViCTW3AduJSHyZ/uqna7IABKVxX2te+FsRf2S78TBrJEDs2h2m8REVF19Wq91QYC2Y5BnvBxk/Izri4KTOwdhpFdguDnoUK4rxu+nj4YE3uHISGqj7QD62SJHB4zskREDs4cyNY00Ss1VaqPFYSKWftOyEWpwDczh+JCVjHG9Qw1d3AQRREAIAgCCsp0+Dqqr7QD62SJHB4zskREDi7fVCPrW1PrLSfuH1vVoA7++NfgSIs2ZIIgQBCkkotruwTjVGgMCtWeQGEhcOiQvYZKRDbAQJaIyMHV2XqrDZQV1Feglxq9owKxN7KXdAXLC4gcWqMC2YMHD+LYsWPmn3/77TdMmTIFL7zwArRarc0GR0REdatYDKGOQNYJlqW1hdFdg7EnknWyRM6gUYHsQw89hLNnzwIALl68iDvuuAMeHh5YuXIl/vvf/9p0gEREVLtaa2RTU4GzZ52+PrYhxnQPwR7ThC9x505Ar7fziIiosRoVyJ49exb9+/cHAKxcuRLXXnstfvzxRyxduhS//PKLLcdHRER1qLVGtnL/WH//lhtUK9a3nS8yYrqhQO0JgXWyRA6tUYGsKIowGo0AgE2bNuGGG24AIK28lZ2dbbvRERFRnWqtkZUDWdbHmikUAq7pEoJ9kb2lK1heQOSwGhXIDh48GK+99hq+++47bN++HZMmTQIAJCUlmZeXJSKillFrjSwnelk1JDrAXF5QWyCr1Rtx5HI+DEaxZQZGRA3SqED2gw8+wMGDBzF79mz873//Q+fOnQEAq1atwrBhw2w6QCIiql2NCyKkpQFnzrA+1orKgWxtdbKfbj2Pmxf+g58PXG7J4RFRPTVqQYR+/fpZdC2QvfPOO3Bx4RoLREQtSS4t8HWvUiPL+tgadQvzxuXILsh384JfURFw8CAwdGi17Y5czgcAHE7Jx51Do1p4lERUl0ZlZDt27IicnJxq12s0GnTt2rXJgyIiovoxGEUUaqRsYrWMLNtu1UipEDAwJrDOOtlLOSUAgKTskhYaGRE1RKMC2eTkZBgMhmrXl5eX48qVK00eFBER1U+hqT4WAHyrTvZifWythkQHVPST3bq12u06gxFX8soAABcZyBK1Sg2qA/j999/Nlzds2ABfX1/zzwaDAZs3b0ZMTIztRkdERLXKM5UVeKtdoFJWyk2kp7M+tg5DogPwklwnu2sXBL0eqFQel5pfBr1pkld2cTmKNDp4u1l+WPjjSCoyCjW4f2THlhs4EZk1KJCdMmUKAGnd6unTp1vcplKpEB0djffee89mgyMiotpV9JCtko2V62P79QMCAlp4VI6hb3tfXAjvKNXJFhdL/WSHDDHfnpxTarF9cnYp+rSvSOCUavX4z89HoDUYMbFPONr5ubfY2IlI0qDSAqPRCKPRiKioKGRmZpp/NhqNKC8vx5kzZ3DjjTc211iJiKiKgpo6FrCsoE5uKiX6RPpjf/te0hVV6mSTq5QTXMwutvh5f3IetAapp3pWUXmzjZOIataoGtmkpCQEBQXZeixERNRA+WXyYghVOhYwkK2XwZX7ycpZbJPkHMtAtuqEr4QLFZOe80q0zTNAIqpVo3tlbd68GZs3bzZnZitbsmRJkwdGRER1k3vIWpQWpKcDp0+zPrYehsb44z25c8HOnYDBACiVAIBLptKCyAB3XM4tsxLIVqxkKdcqE1HLalRG9uWXX8a4ceOwefNmZGdnIy8vz+JEREQtw7wYQuWOBXJmsW9f1sfWYVBUAE6HxqBQ7QkUFgKHD5tvkzOyY7qFSD9XCmQLNTocu1pg/jmXGVkiu2hURnbRokVYunQp7rnnHluPh4iIGsDq8rRyIMuygjr5eqjQJdwP+9r3RPyF/VJJxqBBMBhFXM6VMrJjuoXg24RLuJhdAlEUIQgC9iflovKqtczIEtlHozKyWq2WS9ESEbUC8qpeFjWyrI9tkMHR/tXqZFPzy6AziHBVKhDbMQCCABRp9MgxZV53m+pjBUHaLbdEV+24RNT8GhXI3n///fjxxx9tPRYiImqgau23MjKAU6ekCOvaa+04MscxJDoAe+WFEXbsAAwGi/pYD1cXRPhKrbXkOll5oteQDlLpBid7EdlHo0oLNBoNvvzyS2zatAl9+/aFSmXZ9uX999+3yeCIiKh21WpkWR/bYEOiAzAntCOK1B7wLigAjh5Fcrn0u4sO9AQAdAz2xNX8MiRllaBzsBdOpRcCACb2CcO+5FyWFhDZSaMC2aNHj6J///4AgOPHj1vcJsjfsxARUbOrqJE1lRbIZQWjRtlnQA4ows8dYQFe2N+uJ667eADYtg2Xuo4HAEQHSYFsTJAndp7LRlJOCRIu5kAUgS4hXuga6g2ANbJE9tKoQHarlTWpiYio5ZlrZOXSAtbHNsoQU53sdRcPANu3IzlQalsWHegBQApkAWD3+WysSrwCABjZJRj+pg8QrJElso9G1cgSEZH9GY1iRUbWXQVkZkr1sQDrYxtoSEwA9sr9ZHfsQEpWEQCgQ2BFRhYAjlwpQFZRObqHeePxsZ0R4CkFsnmlWoiiWP3ARNSsGpWRHTNmTK0lBFu2bGn0gIiIqH6KyvXmFlA+7ipgg6k+tk8fIDDQfgNzQEOiAzAvrDNKXN3hmZcH9emTQGC0uUZWDmQBqaTgh/tj4efhCo3OAAAwGEUUavTwdVdZPT4RNY9GBbJyfaxMp9Ph8OHDOH78OKZPn26LcRERUR0KTBO93FVKuKmU7B/bBJ2DveDt5Yb97XpidFIiBiUdwcngGET4uQEA2vt7YHAHf5Trjfh6xmAEeqkBAG4qJTxdlSjRGpBfqmUgS9TCGhXIfvDBB1avf+mll1BcXNykARERUf3kl7E+1lYUCgHDOwVhb1RvjE5KxLArJ+DxzBy4KKUKPKVCwMqH4wBUn9Ts7+mKEm0Zcku05lIEImoZNq2R/fe//40lS5bY8pBERFQDufWWr7sKyMoCTpyQbmB9bKPMv6knBk+/BQAQn3Uaz1zf1eJ2QRCsltXJE77YuYCo5dk0kE1ISICbm5stD0lERDXIr7w87Y4d0pW9ewNBQXYcleMK8XbD2H/fAHh6QsjNrfhgUAd/T3YuILKXRpUW3HrrrRY/i6KItLQ0HDhwAHPnzrXJwIiIqHYFlZenZVmBbahUwPDhwN9/S7/TPn3q3CXAVNrB1b2IWl6jMrK+vr4Wp4CAAIwePRrr1q3D/PnzbT1GIiKywryql4eKCyHYkvw7lCfP1cHfk6UFRPbSqIzsN998Y+txEBFRA8mlBWG6YkBeZZH1sU0nZ7W3bwdEEahjxcoA1sgS2U2jAllZYmIiTpmab/fq1QsDBgywyaCIiKhucka2+9nD0hW9egEhIfYbkLMYPBhwdweys4GTJ6Xfay38zDWyDGSJWlqjAtnMzEzccccd2LZtG/z8/AAA+fn5GDNmDJYvX47g4GBbjpGIiKwoMLXfijlxQLqCZQW24eoq1clu2iSVbNQRyJozspzsRdTiGlUj+9hjj6GoqAgnTpxAbm4ucnNzcfz4cRQWFuLxxx+39RiJiMiKPFNGNvzwXukKTvSynQbUyfp7SpO9cllaQNTiGpWRXb9+PTZt2oQePXqYr+vZsycWLlyIcePG2WxwRERUs/xSLfzKCuFz9qR0BetjbacBdbIBptKCfAayRC2uURlZo9EIlar6MnwqlQpGo7HJgyIioroVlOkw9LKp12mPHkBoqH0H5EyGDAHc3IDMTOD06Vo3rZjspYPRKLbE6IjIpFGB7HXXXYcnnngCqamp5uuuXr2Kp556CmPHjrXZ4IiIyDpRFJFfqsM1KcekK1hWYFtqNTBsmHRZbm1WAz9TIGswiijS6Jt5YERUWaMC2U8//RSFhYWIjo5Gp06d0KlTJ8TExKCwsBCffPKJrcdIRERVlGgN0BtFXHPZFMhyopft1bNO1tVFAS+1VKnHOlmiltWoGtnIyEgcPHgQmzZtwmnTVy49evRAfHy8TQdHRETW5Zdq4VtWhO6ZydIVDGRtT85yb9tWZ52sv6cKxeV65JZoERPk2SLDI6IGZmS3bNmCnj17orCwEIIg4Prrr8djjz2Gxx57DEOGDEGvXr2wc+fO5horERGZ5JfqMPTKCSggAt27A2Fh9h6S8xk6VCoxyMgAzp6tdVO5TpYTvohaVoMC2Q8//BAPPPAAfHx8qt3m6+uLhx56CO+//77NBkdERNYVlFWqj2U2tnm4uQFxcdLlOupk/bkoApFdNCiQPXLkCCZMmFDj7ePGjUNiYmKTB0VERLXLL9Uh9rJpWVpO9Go+9ayT5TK1RPbRoEA2IyPDatstmYuLC7Kyspo8KCIiql1pRhZ6ZlyUfmBGtvlUrZOtgdy5IJerexG1qAYFsu3atcPx48drvP3o0aMIDw9v8qCIiKh2HvsSoICIzPAOAN93m09srLRkbVoacP58jZsFmFb3ymNpAVGLalAge8MNN2Du3LnQaDTVbisrK8P8+fNx44032mxwRERkXVBiAgDgSr+hdh6Jk3N3B665RrpcS51se38PAMCu89ko1xtaYGBEBDQwkH3xxReRm5uLrl274u2338Zvv/2G3377DW+99Ra6deuG3Nxc/O9//2uusRIRkUm7w/sAANmD4uw8kjagHnWyE3qHIdRHjav5Zfj5wJUWGhgRNSiQDQ0Nxe7du9G7d288//zzuOWWW3DLLbfghRdeQO/evbFr1y6EcolEIqLmlZ+PiOQzAICi2OF2HkwbUI86WTeVErPGdAYALNxyHhods7JELaHBCyJ06NAB69atQ15eHs6fPw9RFNGlSxf4+/s3x/iIiKiqXbugEI246B8BdYf29h6N87vmGkClAq5eBS5eBDp1srrZ1CGR+HzbBaQVaPDTvhTMHB7TwgMlansatUQtAPj7+2PIkCEYOnQog1giopZkqtXcG9kbfu6u9h1LW+DhIU36Amqtk1W7KDH7OlNWdusFlJTrW2BwRG1bowNZIiKyE1Ot5p6oPvDzqLklItlQPfvJ3j4oEpEB7sguLscrf5xsgYERtW0MZImIHElBAXDwIABgb2Qf+LozkG0R9ewn6+qiwNu39YMgACsOXMbao6ktMjyitqpVBLILFy5EdHQ03NzcEBsbi3379tVrv+XLl0MQBEyZMqV5B0hE1Frs3AkYjUj2C0e6TxAzsi0lLk6qk718WaqTrW3TToGYNVoqMXh+9TFczi1tiREStUl2D2RXrFiBOXPmYP78+Th48CD69euH8ePHIzMzs9b9kpOT8fTTT2PkyJEtNFIiolZg82YAwO4O/aBUCPBSN3jOLjWGp2dFP1nTc1CbJ+K7YECUH4o0eryx7lQzD46o7bJ7IPv+++/jgQcewMyZM9GzZ08sWrQIHh4eWLJkSY37GAwG3H333Xj55ZfRsWPHFhwtEZGdmQPZvvBzV0EQBDsPqA257jrpfMuWOjdVKRWYd2NPAMDuCzkQaylHIKLGs2sgq9VqkZiYiPj4ePN1CoUC8fHxSEhIqHG/V155BSEhIbjvvvvqvI/y8nIUFhZanIiIHFJmJnDsGAApI+vLsoKWNXasdL5lC2A01rl573a+ULsoUFCmQ1J2STMPjqhtsmsgm52dDYPBUG0RhdDQUKSnp1vdZ9euXfj666+xePHiet3HggUL4Ovraz5FRkY2edxERHaxdSsAoLBrT+R6+MLfg623WlRsrNSKKysLOH68zs1VSgX6tPMFABy+nN/MgyNqm+xeWtAQRUVFuOeee7B48WIEBQXVa5/nn38eBQUF5tPly5ebeZRERM3EVFaQalqW1o8dC1qWqytw7bXS5XrUyQJA/0g/AMChlPzmGRNRG2fXWQJBQUFQKpXIyMiwuD4jIwNhYWHVtr9w4QKSk5MxefJk83VG09c7Li4uOHPmDDpVWXFFrVZDrVY3w+iJiFqYKXi62PcaIB8sLbCHsWOB9eul5+Kpp+rcvH+UHwDg0OW8Zh4YUdtk14ysq6srBg0ahM2VPtkajUZs3rwZcXFx1bbv3r07jh07hsOHD5tPN910E8aMGYPDhw+zbICInFdystT2SanE6S4DAICretmDPOFr+3ZAp6tz8wFR0sqXp9OKUKY1NOfIiNoku/dtmTNnDqZPn47Bgwdj6NCh+PDDD1FSUoKZM2cCAKZNm4Z27dphwYIFcHNzQ+/evS329/PzA4Bq1xMRORX5A//QocgSpEwse8jaQf/+QEAAkJsLHDgg9ZetRYSvG4K91cgqKsfx1AIMiQ5omXEStRF2r5GdOnUq3n33XcybNw/9+/fH4cOHsX79evMEsJSUFKSlpdl5lEREdia3fBo7FvmlUiaQgawdKBTAmDHS5XrUyQqCgAGmOtnDrJMlsjm7Z2QBYPbs2Zg9e7bV27Zt21brvkuXLrX9gIiIWhNRtAxkz0qBLJentZOxY4FffpEC2RdfrHPz/lF++PtkButkiZqB3TOyRERUh5MngfR0wN0diItDfpmckWWNrF3I/WR37wZK615+dkCkVCfLjCyR7TGQJSJq7eSvsEeMANRqFJRqAbD9lt106QK0awdotVIwW4e+7X2hEIDUAg0yCjUtMECitoOBLBFRaycHsqYZ8xUZWQaydiEIFVnZetTJeqpd0C3MBwDw66GrzTkyojaHgSwRUWum1wPyXIGxY1GuN6DU1MaJ7bfsqAGBLADcOzwaAPDx5nNIzS9rpkERtT0MZImIWrODB4HCQsDPDxg4EAWmbKwgAN5urWK+btskB7KJiUB+fp2b3zawPYZE+6NUa8DLf5xo3rERtSEMZImIWjM54zd6NKBUoqC0omOBQiHYb1xtXbt2QLdugNFYkTGvhUIh4LUpfaBUCNhwIgNbTmfUuQ8R1Y2BLBFRayYHsqYMYJ7cQ5YTvexPXuVLbo1Wh25h3rhvRAwA4OU/TkJnMDbXyIjaDAayREStlUYD/POPdNkUyOYUlwMAAr3U9hoVyRpYJwsAT4ztgiAvV1zKKcXKA1eaaWBEbQcDWSKi1mr3bimYDQ8HuncHAOSUSK23Aj050cvuxoyRipVPngRSU+u1i6faBY+M7gwA+GTLOWh0huYcIZHTYyBLRNRa/f23dB4fLwVMAHKKTYGsFwNZuwsIAAYNki7Lz1U93B0bhXBfN6QVaPDD3pRmGhxR28BAloiotVq/XjqfMMF8VU6JqbTAk6UFrYL83GzYUO9d3FRKPD62CwDgs63nUVKub46REbUJDGSJiFqj1FTgyBEpE3v99earzaUFzMi2DnIg+/ffgKH+ZQL/N6g9OgR6IKdEi/XH05tpcETOj4EsEVFrJH9VPXgwEBxsvlqe7BXAGtnWITYW8PUFcnOBAwfqvZtKqcA1MYEAgKtcIIGo0RjIEhG1RnJZwfjxFlfLNbJB7FrQOri4SDXMQIPKCwAgxEd6DjOLNLYeFVGbwUCWiKi1MRiAjRuly5XqYwGWFrRK8nMkf/iopxBvUyBbWG7rERG1GQxkiYhamwMHpK+qfX2lr65NDEYReaVy+y1mZFsNOWu+d6/0vNVTsLcbACCziIEsUWMxkCUiam3kzN7110tfXZvklWohitJlfw+u7NVqREYCPXtKy9Vu2lTv3eTSgiwGskSNxkCWiKi1qaM+1t9DBRcl375blUa04ZJLC7KKyiHKn1CIqEH4TkhE1Jrk5gL79kmXqwayJVyettWqXCdbz6A02BTIag1G5JfqmmtkRE6NgSwRUWuyaZP0FXWvXtJX1pXIGVm23mqFRo4E3N2l/r/Hj9drF7WLEn6mEhHWyRI1DgNZIqLWxMpqXjK5h2wQOxa0Pm5uwOjR0uVGlBewBRdR4zCQJSJqLUSxIgiyFsiWsGNBq9aINlwhcucCtuAiahQGskRErcXx49JX0+7uwIgR1W5mD9lWTg5kd+4EiovrtUtFRpaBLFFjMJAlImot5EzemDHSV9VVyKUFgayRbZ26dAGiowGtFti2rV67BLO0gKhJGMgSEbUWtdTHAhWTvdi1oJUShAa34QpmRpaoSRjIEhG1BsXF0lfSQI2BbK65RpYZ2VargXWyIT5S5j2LNbJEjcJAloioNdi6FdDpgJgYoHNnq5tky6UFrJFtva67TlqN7fx56VQHdi0gahoGskRErcGff0rnEydKX1FXodUbUajRA2DXglbN21vqKQtUPKe14GQvoqZhIEtEZG+iCKxdK12ePNnqJnmlUlmBUiHA113VUiOjxrjxRun8jz/q3FQuLSjVGlBcrm/OURE5JQayRET2dugQcPUq4OlZ0VS/CrmsIMDTFQpF9YwttSLyh5Ht24GCglo39VK7wMNVCQDILGR5AVFDMZAlIrI3OXN3/fVW224BlToWcKJX69elC9CtG6DXA3//XefmLC8gajwGskRE9iYHsjWUFQBATgknejkU+bmsT3mBaXWvLAayRA3GQJaIyJ5SU4HERGmC16RJNW5WkZHlRC+HIAey69YBBkOtmwb7MCNL1FgMZImI7Eme2T50KBAaWuNm8vK0ASwtcAzDhgH+/kBODpCQUOumbMFF1HgMZImI7KkeZQVAxfK0QSwtcAwuLsANN0iX6ygvMJcWcFEEogZjIEtEZC8lJcCmTdLlOgJZ86peXJ7WccjP6e+/17oZJ3sRNR4DWSIie9mwASgrk1bz6tOn1k3lQNbfgxlZhzFxIuDqCpw+DZw6VeNmIT4sLSBqLAayRET28uuv0vktt1hdzasyeVUvLobgQHx8gLFjpcvyc22FXFqQVqCBKIotMTIip8FAlojIHnS6itW8brmlzs0Ly3QAAG83l+YcFdma/NzWEshGB3nAValAkUaPSzmlLTQwIufAQJaIyB62bQPy84GQECAurs7Ni0wZWR83ZmQdyk03Sdn2AweAy5etbqJ2UaJXOx8AwKHLeS05OiKHx0CWiMgeVq+Wzm++GVAqa91UZzCiTCf1IvVxZ0bWoYSGAsOHS5fXrKlxswGR/gCAQyn5zT8mIifCQJaIqKUZjcBvv0mXb721zs3lbCwAeKkZyDocubxA/vBixYAoPwAMZIkaioEsEVFL27sXSEuTJgNdd12dm8v1sZ6uSrgo+bbtcORAdscOIDvb6iYDO0gZ2VNphSjT1r4SGBFV4DsiEVFL++UX6XzSJKk9Ux3kjKw362MdU0wM0L+/ZSa+ighfN4R4q6E3ijieWtCy4yNyYAxkiYhakigCP/8sXb799nrtUqSRMrKsj3Vg8nMtP/dVCIJQqbyAE76I6ouBLBFRS9q7V5q97uUFTJhQr10KNXLrLWZkHZYcyG7eXGN5wYAoTvgiaigGskRELUnOyN10E+DuXq9dCs2lBczIOqwuXYABAwCDocaesgMi/QAwkCVqCAayREQtxWgEVq6ULv/rX/XeTZ7sxR6yDk5+zmsoL+jT3hdKhYD0Qg3SCspacGBEjouBLBFRS9mzB7hyBfD2BsaPr/duRczIOge5vGDLFiArq9rNHq4u6B7mDYBZWaL6YiBLRNRSVqyQzm++GXBzq/duhebJXszIOrROnYBBg6TMfA09ZfubygsOX85vuXEROTAGskRELcFoBFatki5PndqgXZmRdSJyeYH8oaaKfu39AADHrrAFF1F9MJAlImoJ27cDqamAry9w/fUN2pU1sk5EDmS3bQOuXq12c+92vgCA41cLYDSKLTgwIsfEQJaIqCV8/710/q9/AWp1g3ZlRtaJREcDI0ZI/YR/+qnazV1CvaB2UaCoXI/knJKWHx+Rg2EgS0TU3MrKKsoK/v3vBu/OGlknI78G5A83laiUCvSM8AEAHLvK8gKiujCQJSJqbmvXAoWFQFSUlI1rIDkj68OMrHO4/XZApQKOHAGOHat2c19TeQHrZInq1ioC2YULFyI6Ohpubm6IjY3Fvn37atx28eLFGDlyJPz9/eHv74/4+Phatycisjs583b33YCi4W+7RVzZy7kEBACTJkmXf/ih2s1ynexRZmSJ6mT3QHbFihWYM2cO5s+fj4MHD6Jfv34YP348MjMzrW6/bds23Hnnndi6dSsSEhIQGRmJcePG4aqVonkiIrvLzgbWrZMuN6KsQBRF88penOzlROTXwo8/Sh0tKulr6lxw4moBDJzwRVQruwey77//Ph544AHMnDkTPXv2xKJFi+Dh4YElS5ZY3f6HH37Ao48+iv79+6N79+746quvYDQasXnzZqvbl5eXo7Cw0OJERNRiVq4E9HppedKePRu8e5nOYA5mONnLiUyaJHWwuHwZ2LHD4qZOwZ5wVylRojUgKbvYTgMkcgx2DWS1Wi0SExMRHx9vvk6hUCA+Ph4JCQn1OkZpaSl0Oh0CAgKs3r5gwQL4+vqaT5GRkTYZOxFRvXzzjXTeiGwsABSWSdlYpUKAh6vSVqMie3Nzq1jpS36NmLhUmvB11FQnm11cDlFkdpaoKrsGstnZ2TAYDAgNDbW4PjQ0FOnp6fU6xrPPPouIiAiLYLiy559/HgUFBebT5cuXmzxuIqJ6OXYM2L8fcHFpdCBbUR/rAkEQbDk6srd775XOV64ECizrYfuY6mT3J+fiqRWHMfi1Tfjmn+QWHiBR62f30oKmePPNN7F8+XL8+uuvcKthuUe1Wg0fHx+LExFRi/j6a+n8ppuAkJBGHcLceov1sc7nmmuAHj2k9mxVVvrq214KZH/adxm/HpLmgPx9sn4JHqK2xK6BbFBQEJRKJTIyMiyuz8jIQFhYWK37vvvuu3jzzTfx999/o2/fvs05TCKihisvB777Trp8332NPkwhF0NwXoJQ8dqQP/SYyIEsAHippef+8OV86AyWE8OI2jq7BrKurq4YNGiQxUQteeJWXFxcjfu9/fbbePXVV7F+/XoMHjy4JYZKRNQwv/8O5OYC7doB48c3+jBcntbJ3XOPVHqybx9w/Lj56o5BXhjTLRhxHQPx1xMj4euugkZnxMlUTlgmqszupQVz5szB4sWLsWzZMpw6dQqPPPIISkpKMHPmTADAtGnT8Pzzz5u3f+uttzB37lwsWbIE0dHRSE9PR3p6OoqLObOTiFoROcM2YwagbPwkLS5P6+RCQoDJk6XLlbKyCoWAb2YOxU8PXoPIAA8M6uAPADhwKc8eoyRqteweyE6dOhXvvvsu5s2bh/79++Pw4cNYv369eQJYSkoK0tLSzNt//vnn0Gq1+L//+z+Eh4ebT++++669HgIRkaVLl4C//5Yumz6UN1ZFIMuMrNOSywu++w7QaKxuIgeyiZdyW2pURA6hVXzEnz17NmbPnm31tm3btln8nJyc3PwDIiJqikWLAFEExo4FOnVq0qHMk73cW8XbNTWH8eOByEipp+zPPwPTplXbZLCckU3OgyiK7GBBZGL3jCwRkVMpLwe++kq6PGtWkw/H5WnbABcX4OGHpcuffWZ1k36RflApBWQWleNKXlkLDo6odWMgS0RkSytXSsvStm9fUfvYBPKCCD6skXVu990HqFTA3r1AYmK1m91USvSKqOgtS0QSBrJERLa0cKF0/tBDUqatiYrYR7ZtCA2tWOmrhqzsYE74IqqGgSwRka0cPAjs2SNl1h54wCaHlPvIska2DZBLUX78UWrdVsXgaNOEr2QGskQyBrJERLby6afS+f/9n5RhswHWyLYhcXFA//5S54IqCyQAwKAOAQCAs5lF5kmARG0dA1kiIltITwd++EG6/NhjNjtsRY0sA1mnJwgVr52PPwZ0lsFqsLcagZ6uEEXgSi4nfBEBDGSJiGzj008BrRYYNkzKrNlIRUaWpQVtwt13S9n8K1ekVlxVhPi4AQAyi6z3myVqaxjIEhE1VUlJxQSdp5+22WH1BiNKtAYADGTbDLUaePxx6fK770r9iCsJ9VEDADILy1t6ZEStEgNZIqKm+uYbIC8P6NwZuOkmmx22uFxvvswa2Tbk4YcBDw/g8GFgyxaLm0K9pYxsRiEzskQAA1kioqYxGID335cuP/UUoFTa7NDy8rRuKgVcXfh23WYEBAD33itdrrL8upyRzWBpAREABrJERE3z889AUpIUfMyYYdNDF5Sxh2yb9dRTgEIBrF8PHDpkvlqukc1gaQERAAayRESNZzQCr74qXX7qKenrYBuSM7Ksj22DOnYE7rhDuiy/xgCEeMs1sszIEgEMZImIGu+XX4BTpwA/P5u23JKZM7LuzMi2Sf/7n9SS69dfgaNHAQCh5q4FzMgSAQxkiYgax2gEXnlFuvzkk4Cvr83vIqdEClYCPV1tfmxyAD17Vixb+9prACwDWaNRrGlPojaDgSwRUWOsWQMcPw74+FS0S7Kx7CItAKkRPrVRL74ona9aBZw4gSAvVwgCYDCKyCnR2ndsRK0AA1kiooYyGID586XLTzwB+Ps3y91kF0sZ2SAvBrJtVp8+wG23Sf1k58+Hi1Jhfj2wBRcRA1kioob77jspG+vnJ03yaiYMZAkA8NJLUq3sL78Ae/ZULIrAFlxEDGSJiBqkrAyYO1e6/MILzZaNBYCsIgayBKB3b2D6dOnys88ixJyR5YQvIgayREQN8emnwJUrQGRks3QqqKwiI8vJXm3eK68Abm7Ajh0YdW4vAC5TSwQwkCUiqr/cXOCNN6TLcmDRjLKLpck8QZzsRZGR5kmFk378BEqjgat7EYGBLFGrdzm3FG+sO8WJHa3BvHlAfr70Ve899zTrXWl0BhSXSwsisGsBAQCeew7w90fQpXO46/BfXBSBCAxkiVq9b/5Jxpc7LuLzbRfsPZS27fBh4PPPpcsffwwolc16d3J9rKuLAt5qruxFkOqxTf1kn97xHcquptt5QET2x0CWqJXLMtVJ/nM+284jacOMRmDWLOl86lRgzJhmv0u5PjbYSw1BEJr9/shBPPQQynr3hW95Cf61+jN7j4bI7hjIErVy+aVSneS5zGJ+lWgv330H7N4NeHoC777bIndZ0bGAE72oEqUSZR98BAC4OXE9DAl77DwgIvtiIEvUyhWU6cyXd1/IseNI2qisLODpp6XL8+YB7du3yN2aJ3qx9RZV4XvdKKzqEw8AMD74IKDlCl/UdjGQJWrl8ksrAlmWF9jB7NlAdra0wtKTT7bY3XIxBKqJUiFg8eSHkOPuA9XxYxWdNIjaIAayRK1cXmlFtmX3hRyIomjH0bQxv/wC/PyzNLFr6VLAteW+5jfXyLJjAVmhDg/D/Osfln54/XXgyBH7DojIThjIErVieoMRRRq9+eer+WW4lFNqxxG1IdnZwKOPSpefew4YOLBl756LIVAtQrzdsLb7SKSMngDo9cCMGYBOV+d+RM6GgSxRK1ZYKYgdGOUHAPjnAssLmp0oAjNnApmZQK9eFUvStqDsIi6GQDUL8VEDgoB1j8wFAgKk9nD/+5+9h0XU4hjIErVicscCb7ULru0aDADYfZ4TvprdRx8Ba9dKpQTffQeoWz6YZI0s1SbUW1pV7p8iJbSffyFd+c47wPr1dhwVUctjIEvUiuWbOhb4eaowvHMQAGD3hWwYjayTbTaJicB//ytdfu89YMAAuwyjov0WA1mqLrZjAABg57ls3HAlGFnT7pdumDYNSE2148iIWhYDWaJWTM7I+rm7ol97PygEIK9UZ87WkY3l5AD/+pdUa3jLLdIiCHag0RlQJC9Py0CWrLimYyC+vGcQgr3VOJ9ZjFGhk1DSo5fULu6OO9iSi9oMBrJkV4UaHQzMLtZIbr3l56GCq4sCAZ5SUJPFQNb2dDrg9tuBixeB6Gjg668BO62oJX9QcVUq4OPO5WnJunG9wrDxqWsR3yMUpQoV7rl+Doze3sDOncBjj0m13kROjoEs2c3BlDz0f/lvvLPhjL2H0mrJgayvuwoAEGKa+JNZ5DiBrFZvxOwfD+LrXUn2HkrtnngC2LoV8PIC/vhDWtfeTioWQ3Dl8rRUKz8PV3xy5wD0DPfBQfdQvPbveRAFAfjyS2DhQnsPj6jZMZAlu9l0MgNGEfj7ZHqTjpNZqMGbf512yq/b5RpZfw+pBZPcUzTLgQLZA8m5WHs0De9sOI1yvcHew7Huww+Bzz+XMrA//AD07m3X4WTL9bHsWED14O6qxBf3DIKvuwpLfHpg68w50g1PPilNWiRyYgxkyW5OpBYCAJKzS1CmbXyA897fZ7Fo+wV8808rz/g1QoFcI+shZWSbEsiW6w1Iyi6x3eDq6Up+GQBAozPicEp+i99/nZYtA556Srq8YAFw0032HQ/YsYAaLjLAA6/c3AsAsKDnjcD06YDBIJXL7Nhh59ERNR8GsmQXoijiRGoBAMAoAmcyihp9rD1JUjuqlNwym4ytNcmrUlrQlED22VVHMebdbXj0h0RkFGpsN8g6XM2reF4SLray1mFr1gD33Sddfuqpim4FdlbRsYCLIVD9DeoglcMk55ZCv+gL4MYbAY0GmDwZOHTIzqMjah4MZAkpOaU4fDnf5scVRRGP/3QIo97Zilk/HsRXOy+iwBSYZRaVm+sAAeBUWmGj7iO9QGNe6Sq9wHED2YxCDYrL9dWuN7ffMpUWyDWyjZnstT85DwCw7lg6xr63Hb8dvtrY4TbI1fyK52X3hVYUyP76q9ShwGCQVkV69127Te6qihlZaowIX3e4qRTQGURcKdZLyytfey1QWAjExwMHDth7iEQ2x0C2jTMYRdzxZQL+7/PduJJn26VP0wo0+P1IKi7llOLPo2l47c9TWPDXKQAwZ2NljQ1k9yXnmi+n5jdvlrFMa4BG1/Qaz5ScUpSUWy47O+qdrZj6RUK1Dg7m0oKqGdnChgWyZVqDOaDs3c4HxeV6/HfV0RbJzFbOyB5KyWtSGYnN/PCD9JWr3Klg8WJA0XreDuUPecGskaUGUCgERAd6AgAuZhcD7u7SxMXYWCA3F7juOmDXrma571KtHmkOnEwgx9V63rnJLhIv5SG1QAO9UcSxKwV179AAcg1sVIAH7h8RAwD4+2QGDEYRJ65Kt3m4KgE0IZBNqsjwZRRqmq2VV6lWjzHvbsPtixIgNqGlzfGrBRj97lY8vfKI+bp/zmdDozPiRGoh1h1Ls9jePNnL0xTIejUuI3sxuxgAEODpit9mjcDgDv4o1xvx6ZbzjX4s9VU5I6sziDhwSfrwUVCqa/mgVhSBTz4B7rlHysROnw78+CPg0rpaXGUxI0uN1CnECwBwMctUD+/jA2zcCIwaBRQVAePHS8GtjWh0Bny18yKGv7kFI9/a2izf7skyizS45+u9LfZtEjkGBrJt3N8nKjoGnM0otumxj1+VAuMh0QF4dmJ3eLu5ILdEi8OX88xB7g19wgEAp9OKGhUg7kuqyMjqjWKzdS44m1GM9EINjl0tMJcyNMb2s1kwisCW05nQ6o0AgCOV3vg/2XLOYtWuivZbTetacMH0T61TsCeUCgFPj+8GAFi+PwWXc6XHk1moQYEpcLYVo1E0Z2muMa1ElHAhB2fSizDi7S24eeGuJn0waBCdTlrg4PHHpYD20UeBJUtaXRC7/WyW+W8nhBlZaqBOQVJG9kJWpfdzb29g3TpgwgSgtBS4+WaplKaJf3t5JVqM/3AHXvvzFPJKddAbRSzfl9KkY9Zm6T/J2HkuG1/uuNhs90GOh4FsGyaKIv4+mWH++Wxm4ydcWSMHq70ifKBSKjCqazAAYNOpTJxIk/5R39QvAq5KBYrK9biS17CvpXJLtObg29tNCkbSCprnq/JLORWz/Q+m5DX6OHK2olxvxHFTeUXlDMbZjGJzOzKDUUShpmJBBKAikC0u16NUW72mtiYXMqXfU6dgKVtzTcdAjOwSBJ1BxJt/ncZLv59A3JtbcNOntg0ss4rLoTOIUCoE3DKgHQApiH/4+0QUafQ4m1Fsfp00q4wMYOLEihZbb78NfPppqyonEEURX2y/gJnf7EOp1oAh0f7myTtE9dXR9Dcuf3g18/AAfv8dePBBKYB95hlg5kygpPGdTNYdT8OlnFIEerpi5vBo6bpjac3SZs9oFLHmkJSJvZRT2nIfgKnVaz3v4tQinl11FA98ewAanQFnMoqQkluRXTzXhM4B1sh1sL3b+QIAru8ZCgD4/XAqLps6DPRr74fOpq/C6hPQnM8sxnt/n0FGoQb7TfWxXUK80MV0jLT85qnRqpyFbWwgK4qiRdCamCzVi55Ol37vtw1sDwD4ePN5iKKIwjKdOWEidy3wUrvAXSWVYzQkK3s+yzKQBYCnx0lZ2T+PpWHp7mQYjCIu5ZQiuQkZ56rkDydhPm4Y0UX6IHM6vciiDdiW05k2uz+rNm0C+vcHNm8GPD2lSV7PPNNqJnbJtpzOxIK/TsMoAlMHR+L7+2PhouRbNDVMx2BTjWzVQBYAVCpg0SLgo4+kD3HLlgFDhgDHjzfqvs6ZEgm3DmyHFyf1RKiPGoUaPbadyWr0+GuyJykHqaZERXG53mKyMLVtfJdsQ7KLy7HiwGVsPJmBdzacwcYTUja2e5g3ACApuwQ6g9Em95VTXG7OjvYIl44/umsIlArBXDPZ3t8dvh4q9Aj3AVB3nWyZ1oCZS/fhky3n8a8vEvDHkVQAwNCYAIT7uQOA+Y3O1pIrZ2Qv5TfqGGkFGovg88ClXJxILYDBKCLYW40XJ/WAp6sSJ9MKse1slrk+1kvtApUpoBEEoVHlBeaMbIin+bp+kX6YZCrt6BrqhRjTV5KJlxqfca5Kfq7b+bmjnZ87OgR6AJCWXr0rNgpAMwayJSXAf/4DjBsHpKcDvXoBe/ZIX6vakM5gxCt/nMTvptdjY8llMrcMaIc3b+sDtYvSFsOjNkbOyGYXl1svFRIEqbxm0yYgPBw4dUoKZt9/H9DX/1seoKJ8oXOIF5QKATf1iwCAZqlhXX3Q8piVvyWjto2BbBtyNr0i4/r1riQsS7gEAJgxLBqerkroDCKSa2mYv+bQVdzz9V7k1KMOVc6uxgR5wttNyib6eqgwuNJXpb0jpEytHOjWFch+suWcOZN7KacUa49KE6OGxgQgwtcNQMtkZE+nF1p0HagvORvrppL+7A4k55mv6x/pB39PV9zUX/r6PeFCDvKrLIYga2ggazCK5gxo5YwsALw/tR9WPRyHdY+PxDhTxtymgawpIxvhJz0/N/WLgEIAXpvSG49f1wUAcORKfr1eUw3y999Anz7SP2dRBB56CNi3r1lW7PrreDqW/JOE/60+Bn2lD4LZxeVYdywNC/46hadWHK6zK8hZ0zcigzr4c1laajQvtQtCfaT3iItZtcx7GDMGOHxYqpvVaKQPfXFx0nX1JGdkO4dI7+E3m96/Np3KRJHGdvX2ZVoD/jJNhPU3vR/a8psjcmwMZNsQedEBhel/ZHZxOQQBiO8Zis6h0htRTRO+SrV6zPvtOHaeyzZnQmsjB7I9I3wsro/vEWq+3Mt0W085I5tecyB7Jr3IXOD/8k29zJk9QApkw3yljGxaM7WTkj/9KwRpAYcjV/IbfAx5UteNfSPg6qJATokWa0yZi/6RfgCAfu2l4P5EakGlHrJVAtkGdi5IzS9Dud4IV6UC7f09LG5TuygxODoALkoFBpo+ZBy0YSCbKmdk/aXnZ871XXFo3jj8a0gkwnzd0DPcB6IoTXCyiVOnpJW5xo8HkpKAyEjgzz+lr1M9POrevxHkv4eicr35dZFXojUtPnEQX2y/iF8PXa2zQ8Q5U9ZcLpMhaqyOQVU6F9QkJET6+1i8GPD1lfrMDhoEPPAAkJZW665FGh3STe+3cnlYrwgfdAr2hFZvxIYTGbXt3iB/n0xHidaAyAB3TOgtfYtUW9KFGu6bf5Iw9YsE2ycVWgAD2TZEDlKnD4tGtCkQHNzBH0FeanQ1vRGdraFOdvXBqyjUSFnI4/WoZZUnMslZV1l8z0qBbDspgJVLCy7nlln9FG80injh12PQG0WM6xmK6cOiseLBOAyM8sPN/SMQ7uverBnZyvVYwzsHAQAOpeRDZzDivqX7cc/Xe80dCGpzyBTIDo0JMAesx01tyORAVq4nPn61sCIj6265ulOIT8MysnJ9bEyQ1LGgJgOjpED2bGaReZJZU1WUFkivN0EQzPW+ADCmu1Q3W7W8YPvZLHR+YR1+PnC5fnd07py0QlefPlJrIaUSeOIJ4MQJ4IYbbPBIrCvU6LC9Uj3gznPZAIANJ9JRpNEj0NPV/OFt06lMi44UlZVUmuzY1fShkqix5BIiue1erRQK4P77pQ+BU6cCRiPw1VdAly7Ac89JEyWtOG/64BXirTb/TQuCYM7K2rK8QC4ruHVAe3Q0lUAls7TAZkRRxMKtF7A3KRc/H7hi7+E0GAPZNkQOUgdE+ePTuwYirmMgnhjbFUDFP89zVjoXGI0ivvknyfyz3BqoNicrdSyoLCbIEyO7BCHEW41BHaR2TP6ergg3BaInrQTJB1PykHgpDx6uSrx0k7SWeJivG1Y/Ohwf3TEAAMw1sk3pWrDhRDpu/nQXhi3YjO5z/8Lzq48BqMjGBni6mjsvHErJw7Ldydh8OhM7z2WbM6s10RuM5j69/SP9zI8dkErW+pgC2y6hXnBRCCgo05mDXN8aMrKZtSyKUFCqw3nTcynXx3auI9MX7K1GVIAHRBE4nJJf67b1JZcWyBnZqq7rHgIA2HE2y+Jr+Z/2pkBvFPFLYi1vqqII7N4N3HEH0L271ErLYJBqYE+cAD78UGo71Iw2nsiAttK45UD2r+NS54l7R8Tgs7sHwlvtguzicvOHmarkWsMgL1f4e3JZWmoaOSN7IbMBwV54OLB8OfDPP1KJQUkJ8NZbQHS01Lbu5EmLzc/X8L4ysXcYAKnmuz4f8OtSrjeYl7ae3C/c/G0cA1nbSS3QmFtXrj3atFp/e2Ag20aIomiuke0a6oXe7Xzx04PXYEQXKcPYJVTOyFb/BL/zfDYuZJVA7SK9XM5lFltd4epsRhHOZxajSKMz12RWDWQBYOnModjz/FiLzNyAKD8AMHciqGyvaRLMqK7BiPCzHhDJGdmMQo1FQNQQb68/jSNXCpBaoIFGZ8TPBy6juFxvro/tEOhh/vp9X1IuPtx0zrzvZ1vP17oYw7nMYpTpDPBSu6BTsJdFrXCnYC/4mOqI1S5K84eKf85LQZGfew01sjV8BVSk0WHKZ/9g3Ac7sPtCtkUP2brI7Z5sUScriqLFZC9r+kf6w99DhUKN3nyfeoMR/1yQHvuRK/nVJyBmZkqtswYMAIYPB1askLJIkyZJ/4TXrAG6dWvy+OvjD9Ob/r8GSx0nDl/Ox5W8Uuw2jX9C7zC4uigw2hSwbzxpPbsl/911CWE2lprO3LmgPhnZqoYNk/6Ofv9dWhFMowE++0yaLDl6NPDtt0BRkfmbnqqBbKdgL/h5qFCuN1ZbwbExjl8tgFZvRJCXKzoFeyHalJG9lN22W3CdzShCeiMTN0UancWqjpUTFydSC2uvrW6FGMi2EemFGhSV6+GiEMyf1iuTg6fk7JJqn6LlbOydQ6MQ5OUKg1GsNjErJacUN36yC9d/sB2zfzwEAAj3dUOglZWJlAoBiipfccfGBAKoCFork2dzD40JqHabLNBLDReFAKPY8FWvACC9QIMLWSUQBODnh+LQ3t8dBqOI/cm55k/+0YGe6BXhA1elAoUaPYrL9ejb3hf+Hiok55TW+klWntTVt70vlArBoj9ov/Z+FtvKwb/clsvfwzJDV9tkL1EU8dwvx5CUXQKjCMz/7QROm2qPO9Wj9nKg6QNFU3rlygrLpN8RUHMgq1QI5iz3etPiHEeu5KPIVMai0RmlLP2VK1Kd64QJQEQE8NhjwJEjgJub1Avz0CFg7Vrpn3ALySvRYpcpA/vQqE7oGOQJg1HEq2tPQmcQ0S3U2zy5Tm49t/FkutVjya3v5A+URE0hv+6Sc0obt9qhIACTJwMJCVLbuilTpBKE7dul1fBCQnD9vNmYcmIreqkty5AUCgGDomz3gfhAsnQMeRJkVIAHBEGqSc8taZstuPZezMGED3dg6pcJNZYr1UQURdzz9T6MfmebeTGcqnM+5InUjoKBbBtxxhQUxQR5wtWl+tMe7usGb7UL9JVmuAPS10fbzmRBEKTuBhU1nJaftJfuToZWb7SYuNOrSn1sbeQgNfFSnkUGzmAUzW+GQ6JrDmSVCgGhPlJWNjW/4Z9SEy5KAUmfdr4YGhOAYZ2kwHrPhRxcyq7IyKpdlOhtqu0VBOD1KX1w73Bp+d2FW8/X+KYiT/TqZ6qF9fd0NWdI+5uCR5n8O5Y1pGvB93su4c9jaXBRSLWo5zKLccj0abtqxwJr5Izz4ZT8Ov8B6g1GrEq8UuP66lfypd9boKcr3F1rbiV1U3+5ZU8qtHojdpzJQruCTNx8Yite27AQUaNipUlbjzwCbNgglQ8MHgx88AFw9apUUtC/f52PzdbWn0iH3iiiZ7gPOgV7mb/dkCe5TDB9xQoAo7sFQ6UUcCGrxHLFJRPzRC/Wx5INRPi5Q+2igFZvNJf3NIogANddJ/VeTk4GXnoJ6NoV0Ggw+MAWfLj2Pfxr0mBg6FBgzhxg9WogMxODom0XyO5Ptnz/d1MpEW56r3eU8oIijQ7LdiejoLTpcw9KtXo8s+oojKLUTedYPUr9KruQVYLDl/NRpjPgr+NSwCpnZOXVF+szobs1YSDbRsj1sTVNJBEEoVJ5QUWd7LLdyQCAsd1DEB3kaZ68JddvAtIfqTwp58n4LuZifPmPoj66hXrDz0OFUq3BIkg+lVaI4nI9vNUu5klhNZFbPNUUWNXmn/NSDVacKYCVzxMu5uBSrvRmKddmyY3977mmA/q098W0YdHwVrtYrMpVmdEommu8KmdfX7ihB27uH2Fe8UpWtRzDt0ppQYi39Dizi8stAuctpzPw6tpTAIDnJnbHCzd0t9hP7hNbm26h3vB0VaKoXI+X/ziBYQs246ZPd1ldqee7PZfw9MojuGXhbqRYaYUjf6CoqT4WAFBejmvL0nB30m5MX78EuRMn456p1+KfRffio7Xv4d+H/4J/0lnpH2pcHPDGG8CZM8D+/cCTTwIB1l9juSVaq+UvtiRPZrmxnzSLeoRpIqBsYp+KQNbHTYVrOkqvKWvlBfLfHDsWkC0oFYL57/3o1XzbHDQyEpg/Hzh9GuUJe7Aw7l84FRwNwWiU/h4/+AC47TYgNBQz752Aj35/B32WfQpx9Wrpb7aBPWoBKXuYeEn6Rq7yt1gdAk0TvrIdowXXi2uOY/7vJ/DCr8eafKy3/jptsZDRplPS+4koivhg41ks2n6h1v0rv/9sPJkhzd8w/c99Znx3uCoVOJdZbE5+OYLWtcg4NZsz6VLGp7YZ0V1DvXEwJd/8NWdBqQ6rTJNt5KyjnC2s/ClwVeIVFJfr0SnYE49f1wWPjO6EE6mF6Nuu/hlZhULAkOgAbDyZgb1JuRgQVVGLCgCDov1rnXEPwNSCK6/BdUOiKCLhghRoDuskBSNxHaXz41cL4GMKJOU3z0dHd0JsTIA5MPF1V2H6sGh8uvU8vthx0dweRrb1TCYu5ZTC283FnLUDgLE9QjG2UjsyWY9wHwhCxTLoflVKCwK9pJ/1RhF5pVr4ebjio01n8bGpvdO4nqG4b0QMRBH4cW8KjlwpQISvGzzVdf+5uygV6Bfph90XcvCtqc9waoEGfx1Lx5RKAbcoivhxr7SmenqhBnd9tQc/PxRXUcMsisi8nI6ovDQMd8sG/iyQsqcpKdLp8mXpPDkZLkYjXq8yDp1CiaKeffCLezTOdemHtz54FEJISJ3jB6Sv6W/69B/0jPDBqofjmqUn68WsYuy5mAuFUNE7M65TIJQKAQajiI5BnuhW5W9tXM9Q7DyXjY0nM/DwqE7m60u17FhAtjemewhOpxdh5YEruLFvRI3b5ZZo8efRVNw2qD08XOsREggCLkT1wDvXTsOX4+/D4ZndIezaBcin48fhnnQBN+MCcGo7sGmptJ+rKxATA0RFSUGxfB4eLn0gDQyUzn19pa4jkLKHeaU6uKkUFt/wRQd5SkkGB8jInkgtwG+HpQznn8fSMCu1sFpbyvraeS7L3P/9toHt8cvBK9h4MgP/GdcNCRdy8NFmad7GiM5B1b7Zk1Uub0q8lIc9F3NRpjPAW+2CAZF+uLZrMDadysAfR1LRLaxl5ho0FQPZ5paSAuRZ+XqlpiL1ZrpePHAYfTKKMSRbAezPt7p9XE4qTqVexJW/r0LnlYctx1LR7VIyogI8EJcdCORcwMAiDfqnnoFLGqDdpYBSocC+nw5iQIEGD3buCMXePVADGAgAVy2PX9c4byq+itwrl5CzIRVQSl955Kw/g8FXcnBTuyhgl7bW48RevoSMy6lw2ZUDiFfqfb8ZBWWIPHoY0QoBsZfcgKsKhAG4Jf+sRVDc+ZgLcF4FNwDDASCl4lj3a7U4lnIUumQjzvplSQGJ6T4S1p7E8PQi3NgnDF47t9U5Jk8At+ecNHdg6LC/DLhcEeCoAExKPYpijQ4lv5fjh0NXceRSHkYBGNsjBHcGiBDWr4cA4CPfEry95wxGuAUB62qoHTYaAZ3OfHrycho6HL6EDj4qBKiAC6l5KDn5GzAwAtBqAZ0OWVkFeDAxCd4GDQIM5RBKSlD6UTkM7iKUxcVAbi7u1utxt/V7tOTrC03X7vi13BfngjrgVEgMCvsNxKo58XjrpQ3QG0U85uKFyPocC8DHW86jTGdA4qU8bDqVaa5PrcpgFPH86qMwGIG3buvToOVgf9onPfmju4WY63+93VQYEOmHA5fyMKF3WLUAOr5nKOb+dgIHU/JwstI/M3n2d6CnKwLYsYBs5I4hkfh82wXsOJeFK3ml1XpIA9IH0sd/OoRd57Nx/Goh3vq/vvU6ttzdpkuIF4SoKOCuu6QTIP2/S0jAsi//gNf5M7jOmA3/5PNAWZmUmT1zpvaDCwLg7w8EBMBf7YUfio1w8/GC65lvpF7QHh64I0eLsCsl6JgUCBzpALi4VJxUqtp/NgXJEATrJwDf7E7GxZxSPDO+O3w8XKvdXuO+Vj40L19zHD0z8qBUAAYjsOrrfMyb3MvqQ9foDNh+NhP92vuZe6MD0rd6aw5fxdLdSehpkL7tmR6pxen1F2HMBDJ2umLD1gvokSklftb/UIze47tDFEX8tC8FhRodHhjZCQVlOmgOHEQPSN/sZRZpsPqbLPTILEL/SD8ojh3F3W55uJp5EYf+uIKywGK4qyqFiS4u0qS/VkYQ29i0v8LCQvj6+qKgoAA+Po37VNQg//438MMPzX8/RK1QicoNxsBAeEeESpO0KmdioqKAjh2l6wUBty/aba6Hmzk8GvMn98LNn+7CkSsF+OiO/ubMZ20uZBUj/v3t5s8K/dr7Ys2s4Vazsl/tvIjX/pRKMV64oTsevLZTtW2s0egMiFuwGXmlOnw9fbBFVv1gSh6W70vB8xN7WG2jNeuHg/jzWBqGdw7E9/fFQhAErEq8gqdXHsE1HQOw/MG4eo2BqD7uWrwHuy/k4PHrOmPOuOrZtS2nM3Dv0gMApBhs3eMj6yzhAoD3/z6Dj7ecxx1DIvHmbdaD39fWnsRXu5JwV2wU3ri5F3DpkrRIifxtjHyemQnk5gI5OUCxY82Wb3OCgoAsGy1eU4eGxGqtIiO7cOFCvPPOO0hPT0e/fv3wySefYOjQoTVuv3LlSsydOxfJycno0qUL3nrrLdzQjE3Pm8TXFwgLs35bTV95Wru+IdtWuV5vFJFRKK3iFe7nDqt7mLYv0xnNK3uIggCFaZ/KuarMYqn+0NtNhRKtHkajCG83Vc39L+s5dhFASm4pDKI0y10QgCt5ZRAEoEOQl/WC7krHKNbqkVFQDrWq+gpWtY0lrUCDonIDAr1cEVjpMRRq9OaVwtxUSnQI8Kj18WgM0kQ5AVL7G1elAlfzy1Co0cPHXVV95n4tv5fs4nJkmPrEdg3zhkph+Wk/OacExeUGyJ9Cw3zdzP1l6zq21etUqoqTq6vFz3uvFuNifjmiw/wQ1yMcWkGJJftTke/ihjuv64EO0WFI1giYv+USilzc8NhN/VDs4Yunt15BuUqNHx+INZds1Ob2wZHmQPZaUx3yoA4BOHKlAAeS8+oVyH629QJEUZo8ePRKPo5cKcDOc9m41tQZwfz7yy7Bu39XZIbe+/ss4nuEmtepr82GE+nIK9UhwtcNo7tZljsMjPI3LyxhzbMTumPjyQz8cz4HW89k4rruoZWyWywrINu6c2gUdl/Iwc8HruDxsV0svnXQGYx43fRBzlvtgqJyPV7/8xS+u29oneU4NbXeqmxwtD++2pUkrRSoUEhlBTExtR53XeIlvLJsJ7xKi/BY/wDsPXAOxbmFeDQ2HN19XIDSUqC0FLnZBfhjz3l4G3W4pW8YBL1eqsHV66Vvlir/XPU2o1H69ksUUVimQ3pBGQRRRJCnK3zclLiSWwqDwQgBIgQRCPVRw91FYd6n1lMlRhHIK9VCbxThrlLCx80FBRodNDojVEoFvNRKKBUKGIxGaA0iSsv1qHwEtYsCvu4q5JfqzL2qvd1c4K5Smv+Hl2gN5s4w8j5GUYTOIN1nud6AynN2XRQC9EYRnmoXqF0UFl0ffN1VcDNNBNfojSgo00GAVMqmlF8PNcxJsDe7B7IrVqzAnDlzsGjRIsTGxuLDDz/E+PHjcebMGYRYqYnbvXs37rzzTixYsAA33ngjfvzxR0yZMgUHDx5E72ZYR73JFi6UTna09WQGHvj2AHqG+2DdEyNr3dYdwF87LuL1ddIb3OwxnfH0eMtP8t+sP43Pt1UUlHcP88aKB+OAKrPrG0oA8NI3+7D1TBZenNQDnmoXPL/6GGJjArDiobozVRev5OOmT/9BqI8ae1+IR36pFj/sTcG3CckoLNPj9sHtMXN4jMWkJ6NRxI2vb0JOiRY/PxSHwEotvjRFGox/fTMA4Ma+4fj0roG13r8bgNe/2otd57MxdXAk+rT3xfzfT8BgFPHn4yPQrgFdHM6cz8bdX+0FAJx9bSJQpdPExysOY/UhqXajdzsfrHl0ONCAr8YbQpGci+cXJcBNpcDe5+Px57E0vKk+hk7Bnnh2zihAEBANYGDHc/hg01k8eswAjT4LokqNGcOiEWeqJa7LpD7heHfDGYgAYk0TBQd18MeSf5Kszn4u1xtwObcMV/JK4e2mgqtSYV6Y4oUbeuCPI6n4elcSPtlyDiO7BJn/ORuNIp5bfRQanRHDTHWtO89l47lfjmH5g9dUaw1X1Q+m2uCpQ6LqrNuuKirQAzOHR+OLHRfx+p+nMLJLsHm9+q5svUU2Nq5XKPw9VEgv1GD72SyLbw+W70vBhawSBHi64rv7huKWhbux63w2tp3JwhhT32NRFGEwijCIIkRR6pTy474UbDOtZldbICt3QDmTUYSCMl21SatV/XroCv6z6jiMHv6Ahz+euAIgbACEcOC1/4wD3Cr2d9caMH/eegDA6LnXN6ok55fEK3hm1RGLQK9ziBfOZxajY7AnhnUKxPd7UtDOzx2/PDIMeaValJTrEebrhlAfN6hqeb/dcTYLz6w6gozCcnipXbD16dGAtxq52SWIf397jR1hhncOxH0jYvDgt4nQG0XzeDxclfj+/thqH5Izs0sw5t1t5p9/vD8WBWU6PPLDQfN1PcN9EOStxo5Ky4D/9cRIdA/zxq1vbTX3+t73wli4mbpBqEURs79IwP7kPNw6oB3en9q/nr9V+7B7IPv+++/jgQcewMyZMwEAixYtwp9//oklS5bgueeeq7b9Rx99hAkTJuCZZ54BALz66qvYuHEjPv30UyxatKja9uXl5Sgvr6gNLCyse3lVW3pm5RFz03SgenlktZdztdurv+DrOkbVahH5b6ZbWP0yPvePjEFGoQZ7k3IxY3h0tdv7VCoi7x7mjR8fuKba6lONNTQmEFvPZGHBX6fN18XW0j+2snBTTVFGYTm6z/0LWr3R4k3q24RL+DbhEtxUFW9AogiU641wVynNy8TKQrzdzG8kcseCutw3Iga7zmdjxYHLWGHq5DCyS1CDWpEBUr9ZPw8VQr3drLZLk1twKRUC3ry1b4PqOxtqcAd/9Aj3wam0Qgx5fRMMptfXHUOiLDI3s8Z0wtYzmeaeudPiOmD+5J71nmzlqXYxf9CSJ50MNrXxOZlWiO5z/7LYvtzU7q2qkV2C0D/SD+G+bvgu4RL2J+eh+9z15mR05ef8zVv7QhCA8R/uwL7kXHSftx51xaYanRFKhYCpQ+pbtWvp0TGdsTLxCi5klaDX/A3mdnOdmZElG1O7KHHbwPb4alcSHvwuESplxYu73NQv/Knru6JXhK/5A9a9y/ZDKQjm4LUmnYI9LToJVBXi7YaoAA+k5JZiyOub6vV3BUiLi7T398D7G88CkDqp+LhZ/n9xd1Ui3NcNaQUaXLNgc53Hru3+7hgSiQg/d7y/8ay5Xv2t2/qiV4QPtp3JwpW8MlyzYLPFvgpBmhgLUfofLf+eREj/f+X/Ox2DPPHB1P7m9+uYIE98NX0wlu9LwfGrhbiaX4YQbzUGR/vj2i7BuH1wJJQKAU+P74Y3/zqN85nFcHVR4Kvpg61+0xMT5ImOwZ64mFWC7mHeiOsUCKMItPd3x5W8MqiUAt69vR/8PVUY98EOFGn0aOfnju5h3hAEAfE9QrAs4RIifN0QYgpiAamL0YuTeuLmhf9g9aGrWGdq0xXg4Yrdz49t+C+7mdm1/ZZWq0ViYiLi4+PN1ykUCsTHxyMhIcHqPgkJCRbbA8D48eNr3H7BggXw9fU1nyIjG/fPp7F0BiM0uopTud7ypK16MliedAax2klvtDwZqpyMIixOgPSHN7ZH/WZ9C4KAF2/siT8eG4EgKwsaxMYEwMfNBb0ifPDD/bE2naAyrlcoXF0U5sfiohAwrlcNpRlVBHq6orspWNfopCC2Z7gP3v9XP3x/XyzGdAs231b5+QCAG/qEWw0Ypw6OlFopdq/f725U12AMjPKDQpCyif+5visW3l17JtcabzcVtj8zBr/Ost7g/5pOgVAIwJNju9Q4O9VWBEHAo6Ol+lGtwQiDUUSApytuHWj5Vb+LUoGP7uiPgVF+eHR0J7x8U68GdwwI8lJbvOZCfdzMq6BVft40OimI9XBVoluot3mJY5VSwJzru5r3nWn6IFaur/6cvzCpB6ICPRAZ4IG5N/aUHp/eWO1+qp4A4Ob+EQjzrXjjbwhfdxWem9jdfH+iKD1ueZliIlu6J64DPFyVMBjFan8/vdv54E7TB7JHx3RGhK8bRFEqR6spiL2mYwC+uGcQ/n5qFLzdak9gTOordXCp79/VjGHRePPWvnh8bBe8cEN3KBUCbuwbbvXY8kIq9Tl2bff3xi19zPfnqlTg0dGdMCQ6AB6uLnjrtr7m4N/fQyoPUymlhXfk/9eV/yfL/38VAjA9rgP+fHykuXe4bEy3EHxxz2D889x1OP3qBOx9YSw+u3sQ7hha8Q3PgyM7YlzPUHi6KvHZXQNrLc26O7YDBEH6QCIIApQKAU+M7QIA+O/47ugZ4YNwX3e8fksfKBUC7oqtSEDcPjgSahcFJver3tWiX6Qf7oqNAlDpvdcGSw43B7tO9kpNTUW7du2we/duxMVVfHX83//+F9u3b8fevXur7ePq6oply5bhzjvvNF/32Wef4eWXX0ZGRvX+jNYyspGRkS022SunuBxlVfpZVv3nbu1ffdX//0KVrarfbu0gFRfdVMpqn2qbQqMzwFWpqPNr2MYo0uiQb2oc7eOuqvMrqcp0BqO504CLUkCYj5vF7zu3RPp6qDKFQkCEr5vVoEv+aq0hGU+96c2ttkUAbEGjM8BN1bz3UVlOcTlKtdJrOchL3eyPT2YwikjNr94b2N1ViUBPV/PzptEZoDeK8KrUZkwUpfrwqsvcuqmU5iyJLKuovF69Z2t7vTREdnE5yky/z2BvdYs+l9S2FJfrkWdlFawwX8uvyDU6A3JKtFAKAhQKQGkKjBQKAUpBgItSgNql/q/Tmv7+rHF3VVZLnJRq9TW2BBNFEWkFmsatXFbD/Vl7Ty0o08FVqTC/3xmNIrJLyqHVGyEI0n9mQZD+R0vn0rHrCvLrIooiyvXGOt8XatqupFxfreVimdZQ7X1bqzdCpRRq/P9X+XesUAg1rtJoaw432as5qdVqqNXVs4otxdoSrc6gOf/perupGv0moFIqEBlQcxlAQANbHAmmN++GcFEq0ID3+kZr6cAn0EuN+lW72pZSIdT6nMqs/T4EQah35rRqYNvcrH3bQdQcvNQuFh/wauKmUto0UGnI3581tfW1FQShom+1jVh7D6maSFEoBPOiNM1JEIR6vcfXtJ21vuHWkg/WvomsfGxb/46bg11LC4KCgqBUKqtlUjMyMhBWw0z/sLCwBm1PRERERM7JroGsq6srBg0ahM2bKwqpjUYjNm/ebFFqUFlcXJzF9gCwcePGGrcnIiIiIudk99KCOXPmYPr06Rg8eDCGDh2KDz/8ECUlJeYuBtOmTUO7du2wYMECAMATTzyBUaNG4b333sOkSZOwfPlyHDhwAF9++aU9HwYRERERtTC7B7JTp05FVlYW5s2bh/T0dPTv3x/r169HaKjU7y4lJQUKRUXieNiwYfjxxx/x4osv4oUXXkCXLl2wZs2a1tlDloiIiIiaDZeoJSIiIqJWoyGxml1rZImIiIiIGouBLBERERE5JAayREREROSQGMgSERERkUNiIEtEREREDomBLBERERE5JAayREREROSQGMgSERERkUOy+8peLU1e/6GwsNDOIyEiIiKiquQYrT5rdrW5QLaoqAgAEBkZaeeREBEREVFNioqK4OvrW+s2bW6JWqPRiNTUVHh7e0MQhGa/v8LCQkRGRuLy5ctcErcN4vPfdvG5b7v43LddfO5tQxRFFBUVISIiAgpF7VWwbS4jq1Ao0L59+xa/Xx8fH76o2zA+/20Xn/u2i89928XnvunqysTKONmLiIiIiBwSA1kiIiIickgMZJuZWq3G/PnzoVar7T0UsgM+/20Xn/u2i89928XnvuW1ucleREREROQcmJElIiIiIofEQJaIiIiIHBIDWSIiIiJySAxkiYiIiMghMZBtZgsXLkR0dDTc3NwQGxuLffv22XtIZGMvvfQSBEGwOHXv3t18u0ajwaxZsxAYGAgvLy/cdtttyMjIsOOIqbF27NiByZMnIyIiAoIgYM2aNRa3i6KIefPmITw8HO7u7oiPj8e5c+cstsnNzcXdd98NHx8f+Pn54b777kNxcXELPgpqrLqe/xkzZlR7L5gwYYLFNnz+Hc+CBQswZMgQeHt7IyQkBFOmTMGZM2cstqnP+3xKSgomTZoEDw8PhISE4JlnnoFer2/Jh+KUGMg2oxUrVmDOnDmYP38+Dh48iH79+mH8+PHIzMy099DIxnr16oW0tDTzadeuXebbnnrqKfzxxx9YuXIltm/fjtTUVNx66612HC01VklJCfr164eFCxdavf3tt9/Gxx9/jEWLFmHv3r3w9PTE+PHjodFozNvcfffdOHHiBDZu3Ii1a9dix44dePDBB1vqIVAT1PX8A8CECRMs3gt++ukni9v5/Due7du3Y9asWdizZw82btwInU6HcePGoaSkxLxNXe/zBoMBkyZNglarxe7du7Fs2TIsXboU8+bNs8dDci4iNZuhQ4eKs2bNMv9sMBjEiIgIccGCBXYcFdna/PnzxX79+lm9LT8/X1SpVOLKlSvN1506dUoEICYkJLTQCKk5ABB//fVX889Go1EMCwsT33nnHfN1+fn5olqtFn/66SdRFEXx5MmTIgBx//795m3++usvURAE8erVqy02dmq6qs+/KIri9OnTxZtvvrnGffj8O4fMzEwRgLh9+3ZRFOv3Pr9u3TpRoVCI6enp5m0+//xz0cfHRywvL2/ZB+BkmJFtJlqtFomJiYiPjzdfp1AoEB8fj4SEBDuOjJrDuXPnEBERgY4dO+Luu+9GSkoKACAxMRE6nc7iddC9e3dERUXxdeBkkpKSkJ6ebvFc+/r6IjY21vxcJyQkwM/PD4MHDzZvEx8fD4VCgb1797b4mMn2tm3bhpCQEHTr1g2PPPIIcnJyzLfx+XcOBQUFAICAgAAA9XufT0hIQJ8+fRAaGmreZvz48SgsLMSJEydacPTOh4FsM8nOzobBYLB40QJAaGgo0tPT7TQqag6xsbFYunQp1q9fj88//xxJSUkYOXIkioqKkJ6eDldXV/j5+Vnsw9eB85Gfz9r+5tPT0xESEmJxu4uLCwICAvh6cAITJkzAt99+i82bN+Ott97C9u3bMXHiRBgMBgB8/p2B0WjEk08+ieHDh6N3794AUK/3+fT0dKvvDfJt1Hgu9h4AkaObOHGi+XLfvn0RGxuLDh064Oeff4a7u7sdR0ZELemOO+4wX+7Tpw/69u2LTp06Ydu2bRg7dqwdR0a2MmvWLBw/ftxiHgTZFzOyzSQoKAhKpbLarMWMjAyEhYXZaVTUEvz8/NC1a1ecP38eYWFh0Gq1yM/Pt9iGrwPnIz+ftf3Nh4WFVZvsqdfrkZuby9eDE+rYsSOCgoJw/vx5AHz+Hd3s2bOxdu1abN26Fe3btzdfX5/3+bCwMKvvDfJt1HgMZJuJq6srBg0ahM2bN5uvMxqN2Lx5M+Li4uw4MmpuxcXFuHDhAsLDwzFo0CCoVCqL18GZM2eQkpLC14GTiYmJQVhYmMVzXVhYiL1795qf67i4OOTn5yMxMdG8zZYtW2A0GhEbG9viY6bmdeXKFeTk5CA8PBwAn39HJYoiZs+ejV9//RVbtmxBTEyMxe31eZ+Pi4vDsWPHLD7IbNy4ET4+PujZs2fLPBBnZe/ZZs5s+fLlolqtFpcuXSqePHlSfPDBB0U/Pz+LWYvk+P7zn/+I27ZtE5OSksR//vlHjI+PF4OCgsTMzExRFEXx4YcfFqOiosQtW7aIBw4cEOPi4sS4uDg7j5oao6ioSDx06JB46NAhEYD4/vvvi4cOHRIvXbokiqIovvnmm6Kfn5/422+/iUePHhVvvvlmMSYmRiwrKzMfY8KECeKAAQPEvXv3irt27RK7dOki3nnnnfZ6SNQAtT3/RUVF4tNPPy0mJCSISUlJ4qZNm8SBAweKXbp0ETUajfkYfP4dzyOPPCL6+vqK27ZtE9PS0syn0tJS8zZ1vc/r9Xqxd+/e4rhx48TDhw+L69evF4ODg8Xnn3/eHg/JqTCQbWaffPKJGBUVJbq6uopDhw4V9+zZY+8hkY1NnTpVDA8PF11dXcV27dqJU6dOFc+fP2++vaysTHz00UdFf39/0cPDQ7zlllvEtLQ0O46YGmvr1q0igGqn6dOni6IoteCaO3euGBoaKqrVanHs2LHimTNnLI6Rk5Mj3nnnnaKXl5fo4+Mjzpw5UywqKrLDo6GGqu35Ly0tFceNGycGBweLKpVK7NChg/jAAw9US1zw+Xc81p5zAOI333xj3qY+7/PJycnixIkTRXd3dzEoKEj8z3/+I+p0uhZ+NM5HEEVRbOksMBERERFRU7FGloiIiIgcEgNZIiIiInJIDGSJiIiIyCExkCUiIiIih8RAloiIiIgcEgNZIiIiInJIDGSJiIiIyCExkCUiIiIih8RAlojIAcyYMQNTpkyx2fGWLl0KPz8/mx2PiMgeGMgSEbUSM2bMgCAIEAQBrq6u6Ny5M1555RXo9Xp89NFHWLp0qb2HSETUqrjYewBERFRhwoQJ+Oabb1BeXo5169Zh1qxZUKlUeP755+09NCKiVocZWSKiVkStViMsLAwdOnTAI488gvj4ePz+++8WpQVZWVkICwvDG2+8Yd5v9+7dcHV1xebNmwEA5eXlePrpp9GuXTt4enoiNjYW27Zts8MjIiJqPgxkiYhaMXd3d2i1WovrgoODsWTJErz00ks4cOAAioqKcM8992D27NkYO3YsAGD27NlISEjA8uXLcfToUdx+++2YMGECzp07Z4+HQUTULBjIEhG1QqIoYtOmTdiwYQOuu+66arffcMMNeOCBB3D33Xfj4YcfhqenJxYsWAAASElJwTfffIOVK1di5MiR6NSpE55++mmMGDEC33zzTUs/FCKiZsMaWSKiVmTt2rXw8vKCTqeD0WjEXXfdhZdeegmzZs2qtu27776L3r17Y+XKlUhMTIRarQYAHDt2DAaDAV27drXYvry8HIGBgS3yOIiIWgIDWSKiVmTMmDH4/PPP4erqioiICLi41Pw2feHCBaSmpsJoNCI5ORl9+vQBABQXF0OpVCIxMRFKpdJiHy8vr2YdPxFRS2IgS0TUinh6eqJz5851bqfVavHvf/8bU6dORbdu3XD//ffj2LFjCAkJwYABA2AwGJCZmYmRI0e2wKiJiOyDNbJERA7of//7HwoKCvDxxx/j2WefRdeuXXHvvfcCALp27Yq7774b06ZNw+rVq5GUlIR9+/ZhwYIF+PPPP+08ciIi22EgS0TkYLZt24YPP/wQ3333HXx8fKBQKPDdd99h586d+PzzzwEA33zzDaZNm4b//Oc/6NatG6ZMmYL9+/cjKirKzqMnIrIdQRRF0d6DICIiIiJqKGZkiYiIiMghMZAlIiIiIofEQJaIiIiIHBIDWSIiIiJySAxkiYiIiMghMZAlIiIiIofEQJaIiIiIHBIDWSIiIiJySAxkiYiIiMghMZAlIiIiIofEQJaIiIiIHBIDWSIiIiJySC72HgC1XkajEVqt1t7DICIichoqlQpKpdLew3AaDGTJKq1Wi6SkJBiNRnsPhYiIyKn4+fkhLCwMgiDYeygOj4EsVSOKItLS0qBUKhEZGQmFghUoRERETSWKIkpLS5GZmQkACA8Pt/OIHB8DWapGr9ejtLQUERER8PDwsPdwiIiInIa7uzsAIDMzEyEhISwzaCKm2qgag8EAAHB1dbXzSIiIiJyPnCTS6XR2HonjYyBLNWLtDhERke3x/6vtMJAlIiIiIofEQJac3ujRo/Hkk0/aexhERERkYwxkiSrZtm0bBEFAfn6+vYdCREREdWAgS0REREQOiYEsOZWSkhJMmzYNXl5eCA8Px3vvvWdx+3fffYfBgwfD29sbYWFhuOuuu8z9/JKTkzFmzBgAgL+/PwRBwIwZMwAA69evx4gRI+Dn54fAwEDceOONuHDhQos+NiIiIrLEQJbqJIoiSrV6u5xEUWzQWJ955hls374dv/32G/7++29s27YNBw8eNN+u0+nw6quv4siRI1izZg2Sk5PNwWpkZCR++eUXAMCZM2eQlpaGjz76CIAUIM+ZMwcHDhzA5s2boVAocMstt3DlMyIiIjvigghUpzKdAT3nbbDLfZ98ZTw8XOv3Mi0uLsbXX3+N77//HmPHjgUALFu2DO3btzdvc++995ovd+zYER9//DGGDBmC4uJieHl5ISAgAAAQEhICPz8/87a33XabxX0tWbIEwcHBOHnyJHr37t3Yh0dERERNwIwsOY0LFy5Aq9UiNjbWfF1AQAC6detm/jkxMRGTJ09GVFQUvL29MWrUKABASkpKrcc+d+4c7rzzTnTs2BE+Pj6Ijo6u135ERETUfJiRpTq5q5Q4+cp4u923rZSUlGD8+PEYP348fvjhBwQHByMlJQXjx4+HVqutdd/JkyejQ4cOWLx4MSIiImA0GtG7d+869yMiIqLmw0CW6iQIQr2/3renTp06QaVSYe/evYiKigIA5OXl4ezZsxg1ahROnz6NnJwcvPnmm4iMjAQAHDhwwOIY8rK88jK9AJCTk4MzZ85g8eLFGDlyJABg165dLfGQiIiIqBYsLSCn4eXlhfvuuw/PPPMMtmzZguPHj2PGjBlQKKSXeVRUFFxdXfHJJ5/g4sWL+P333/Hqq69aHKNDhw4QBAFr165FVlYWiouL4e/vj8DAQHz55Zc4f/48tmzZgjlz5tjjIRIREVElDGTJqbzzzjsYOXIkJk+ejPj4eIwYMQKDBg0CAAQHB2Pp0qVYuXIlevbsiTfffBPvvvuuxf7t2rXDyy+/jOeeew6hoaGYPXs2FAoFli9fjsTERPTu3RtPPfUU3nnnHXs8PCIiIqpEEBva34icnkajQVJSEmJiYuDm5mbv4RARETkV/p+1HWZkiYiIiMghMZAlIiIiIofEQJaIiIiIHBIDWSIiIiJySAxkiYiIiMghMZAlIiIiIofEQJaIiIiIHBIDWSIiIiJySAxkiYiIiMghMZAlpyGKIh588EEEBARAEAQcPnwYo0ePxpNPPmnvoZEDq89rKDo6Gh9++GGLjMfZJCcnm/9eqfWx9r5q7Toie2EgS05j/fr1WLp0KdauXYu0tDT07t0bq1evxquvvmrepq0EHAsXLkR0dDTc3NwQGxuLffv21bnPhx9+iG7dusHd3R2RkZF46qmnoNFozLfv2LEDkydPRkREBARBwJo1a5rxETTetm3bIAgC8vPzbXK8qq8hW9NoNJgxYwb69OkDFxcXTJkyxeoYrr/+egQHB8PHxwdxcXHYsGGDxTbR0dEQBKHaadasWTXe99KlS6ttX3W5zNWrV2PcuHEIDAxslqAlMjLS/PfqaE6cOIHbbrvN/Lu39t7y0ksvVfsdd+/evdbj1ud5ycjIwIwZMxAREQEPDw9MmDAB586ds+XDA2D9fdXadU1hqw8zGo0Gs2bNQmBgILy8vHDbbbchIyOj1n1EUcS8efMQHh4Od3d3xMfHV/s9vv766xg2bBg8PDzg5+dn9TgpKSmYNGkSPDw8EBISgmeeeQZ6vb5Jj4fqh4EsOY0LFy4gPDwcw4YNQ1hYGFxcXBAQEABvb297D61FrVixAnPmzMH8+fNx8OBB9OvXD+PHj0dmZmaN+/z444947rnnMH/+fJw6dQpff/01VqxYgRdeeMG8TUlJCfr164eFCxe2xMNodlqttl7bNfdryGAwwN3dHY8//jji4+OtbrNjxw5cf/31WLduHRITEzFmzBhMnjwZhw4dMm+zf/9+pKWlmU8bN24EANx+++213r+Pj4/FfpcuXbK4vaSkBCNGjMBbb73VxEdqnVKpNP+9OprS0lJ07NgRb775JsLCwmrcrlevXha/4127dtV57NqeF1EUMWXKFFy8eBG//fYbDh06hA4dOiA+Ph4lJSU2eWwya++r1q5rDZ566in88ccfWLlyJbZv347U1FTceuutte7z9ttv4+OPP8aiRYuwd+9eeHp6Yvz48RYf4rVaLW6//XY88sgjVo9hMBgwadIkaLVa7N69G8uWLcPSpUsxb948mz4+qoFIVEVZWZl48uRJsayszN5Dqbfp06eLAMynDh06iKIoiqNGjRKfeOIJ8+XK2zTk5Z+dnS3ecccdYkREhOju7i727t1b/PHHHy22GTVqlDh79mzxiSeeEP38/MSQkBDxyy+/FIuLi8UZM2aIXl5eYqdOncR169aZ99m6dasIQFy7dq3Yp08fUa1Wi7GxseKxY8ca/bsYOnSoOGvWLPPPBoNBjIiIEBcsWFDjPrNmzRKvu+46i+vmzJkjDh8+3Or2AMRff/21UeO7fPmyeMcdd4j+/v6ih4eHOGjQIHHPnj3m29esWSMOGDBAVKvVYkxMjPjSSy+JOp3O4r4XL14sTpkyRXR3dxc7d+4s/vbbb6IoimJSUlK153j69OmiKErPz6xZs8QnnnhCDAwMFEePHi2Koihu27ZNHDJkiOjq6iqGhYWJzz77rMX9VX4NiaIoZmRkiDfeeKPo5uYmRkdHi99//73YoUMH8YMPPmjU76Oy6dOnizfffHO9tu3Zs6f48ssv13j7E088IXbq1Ek0Go01bvPNN9+Ivr6+9bo/+Xd76NChem1fWW5urnjXXXeJQUFBopubm9i5c2dxyZIlNR73t99+Ezt37iyq1Wpx9OjR4tKlS0UAYl5ensW4//jjD7Fr166iu7u7eNttt4klJSXi0qVLxQ4dOoh+fn7iY489Jur1evNxv/32W3HQoEGil5eXGBoaKt55551iRkZGgx+PNTW9BubPny/269evQceq63k5c+aMCEA8fvy4+TqDwSAGBweLixcvbtB91fb6t/a+WtN77cqVK8XevXuLbm5uYkBAgDh27FixuLjYfD+LFy8Wu3fvLqrVarFbt27iwoULzbdV/ZsdNWpUgx6DKIpifn6+qFKpxJUrV5qvO3XqlAhATEhIsLqP0WgUw8LCxHfeecfiOGq1Wvzpp5+qbV/T87Ju3TpRoVCI6enp5us+//xz0cfHRywvL7d63474f7a1YkaW6iaKQEmJfU6iWK8hfvTRR3jllVfQvn17pKWlYf/+/dW2Wb16Ndq3b49XXnnFnOWQCYKApUuX1nh8jUaDQYMG4c8//8Tx48fx4IMP4p577qn2lf2yZcsQFBSEffv24bHHHsMjjzyC22+/HcOGDcPBgwcxbtw43HPPPSgtLbXY75lnnsF7772H/fv3Izg4GJMnT4ZOpwMgfWXl5eVV6+mNN94AIGUOEhMTLTJ7CoUC8fHxSEhIqPHxDRs2DImJiebHc/HiRaxbtw433HBDjfs0RnFxMUaNGoWrV6/i999/x5EjR/Df//4XRqMRALBz505MmzYNTzzxBE6ePIkvvvgCS5cuxeuvv25xnJdffhn/+te/cPToUdxwww24++67kZubi8jISPzyyy8AgDNnziAtLQ0fffSReb9ly5bB1dUV//zzDxYtWoSrV6/ihhtuwJAhQ3DkyBF8/vnn+Prrr/Haa6/V+BhmzJiBy5cvY+vWrVi1ahU+++yzatnuiRMn1vp89erVq0m/R6PRiKKiIgQEBFi9XavV4vvvv8e9994LQRBqPVZxcTE6dOiAyMhI3HzzzThx4kSTxmbN3LlzcfLkSfz11184deoUPv/8cwQFBVndNikpCf/3f/+HKVOm4MiRI3jooYfwv//9r9p2paWl+Pjjj7F8+XKsX78e27Ztwy233IJ169Zh3bp1+O677/DFF19g1apV5n10Oh1effVVHDlyBGvWrEFycjJmzJhhcdy6/tYefvjhBj/+c+fOISIiAh07dsTdd9+NlJSUOvep7XkpLy8HAItyA4VCAbVaXa9sr6yu17+191Vr16WlpeHOO+/Evffei1OnTmHbtm249dZbIZrev3/44QfMmzcPr7/+Ok6dOoU33ngDc+fOxbJlywDA/L6zadMmpKWlYfXq1eb96no+du7cCQBITEyETqezeO/r3r07oqKianzvS0pKQnp6usU+vr6+iI2NrfX9sqqEhAT06dMHoaGh5uvGjx+PwsLCZvl7oirsHUlT61Ptk2JxsShKIWXLnyp9oq/LBx98YM4OyKpm02rKmnTr1k1cvXp1g35PkyZNEv/zn/9Y3NeIESPMP+v1etHT01O85557zNelpaVZZAjkjOzy5cvN2+Tk5Iju7u7iihUrRFEURZ1OJ547d67WU05OjiiKonj16lURgLh7926LsT7zzDPi0KFDa308H330kahSqUQXFxcRgPjwww/XuC0amZH94osvRG9vb/N4qxo7dqz4xhtvWFz33XffieHh4Rb3/eKLL5p/Li4uFgGIf/31lyiKFb9TOXsnGzVqlDhgwACL61544QWxW7duFlnLhQsXil5eXqLBYDDvJ7+G5EzYvn37zNvLWZ/Kr6srV67U+nwlJydbffz1zci+9dZbov//t3f3MU1dbxzAvxXaWsBW3hG1QFABHUzGm9W4xbCAqAyNOmemNg4dG+okuM1M3hQUzFgIhETddDFbgnO4l2xzjI2RkSW4kcGEaFAURFBQNIIiMGmE5/eH6Q19b7H+Ju75JE3K7bmnh3vuy+lzzznX1dVkNPHLL78kBwcH6urqMpvPmTNn6LPPPqOzZ89STU0NrVixguRyOV27ds0g7eNEZBMTE2nz5s1GP9PPd/fu3fTcc8/ppMnIyDCIyAKg1tZWIU1KSgo5OTnR/fv3hWXx8fGUkpJislx//fUXAdBZx9KxZmqbmzq3VFRUUHl5OTU1NVFlZSWpVCpSKpXU399vslyW6kWj0ZBSqaS1a9dSb28vDQ8P08GDBwkAxcXFmcxXnzX7v7Hzqv6yhoYGAmByvw4MDDS4g5WXl0cqlYqITO9b/f39FutjaGiIiIjKyspIIpEYfHdUVBS9//77RstVW1tLAKi7u1tn+dq1a+nVV181SG8qIrt161aD7T44OEgAdO7AjcURWft5Ojq2MPYvu3jxotnPR0ZGkJ+fj/LycnR1dUGj0WB4eBhOTk466cLCwoT3Dg4OcHd3R2hoqLBM+4tdP4KnUqmE925ubggKCsKFCxcAAI6Ojpg1a9b4/jEr1dTUID8/H4cOHUJMTAxaW1uxc+dO5OXlISsry27f09jYiPDwcJORxKamJtTW1upEYEdGRvDgwQMMDQ0J23vsdnZ2doZcLjfbB1grIiJC5+8LFy5ApVLpRC0XLVqEgYEBXL9+HUql0iC9o6OjTj7BwcEGA0CmT59usSzjdeLECezbtw/fffcdvLy8jKb59NNPkZCQAF9fX7N5qVQqnX1v4cKFCAkJwccff2zXAW5vv/02Vq9eLdyVWLlyJRYuXGg0bUtLC6KionSWRUdHG6RzcnJCYGCg8Le3tzf8/f3h4uKis2zsftHQ0IC9e/eiqakJfX19wp2Azs5OzJ07FwDsfqwlJCQI78PCwhATEwM/Pz+Ul5cjOTnZ6DqW6kUsFuObb75BcnIy3Nzc4ODggJdffhkJCQlCFNQatu7/pjz//POIjY1FaGgo4uPjERcXhzVr1sDV1RWDg4Noa2tDcnIytm7dKqzz8OFDKBQKs/lOmTLlPzfGgdmOG7LMMicnYGDg3/vup0BhYSFKSkpQXFyM0NBQODs7Iy0tzWDAkFgs1vlbJBLpLNNeMLQXUGuMvciasmfPHuzZswceHh5wcHAwGKnb09NjdjBKVlYWNm7ciC1btgAAQkNDMTg4iDfffBMZGRmYNMk+vZBkMpnZzwcGBrBv3z6jAzTG3kY1tp2t2abOzs5WlvTxJCQkCLc8jfHz8xvXLceTJ09iy5YtOHXqlMmBYR0dHfj111+F27O2EIvFCA8PR2trq83rmpOQkICOjg5UVFSgqqoKsbGx2LZtGz766KNx52npWNMu0+4Xg4ODiI+PR3x8PMrKyuDp6YnOzk7Ex8frHMdjG8LGbNiwAUeOHBl3uadOnYo5c+bYtI2N1UtERAQaGxtx7949aDQaeHp6IiYmBpGRkeMu23g5ODigqqoKZ86cwS+//ILS0lJkZGSgrq5O+PF59OhRxMTEGKxnTllZGVJSUsym+emnn7B48WL4+PhAo9Hg7t27Oj8szZ37tMt7enowbdo0nXXmz59v9nv189HvZqY9B5s77zL74IYss0wkAv5PDYAnTSKRYGRkxOb1amtrkZSUhA0bNgB41BC9dOmSxQamtf78808h+tHX14dLly4hJCQEAODr62txWhpthFMikSAiIgLV1dXCNE6jo6Oorq7G9u3bTa4/NDRk0FjVXmRsifBYEhYWhmPHjqG3t9doVPaFF15AS0vLY0XFJBIJAFhVzyEhIfj6669BRMKPjNraWkyZMgUzZswwSB8cHIyHDx+ioaFBiBq2tLQYTPV17Ngx/PPPPya/V7/BZY0vvvgCb7zxBk6ePInly5ebTHf8+HF4eXmZTWPKyMgIzp07Z/e+0QDg6ekJtVoNtVqNxYsX47333jPakA0KCkJFRYXOMmN93m118eJF3LlzBwcPHsTMmTMBAPX19QbpLB1rcrn8scoxMDCAtrY2bNy40ep1zNWLNqp5+fJl1NfX2xRJt3X/N0ckEmHRokVYtGgRsrOz4efnh2+//Rbp6enw9fXFlStX8Prrrxtd19Qx+8orrxg0fvVp735ERERALBajuroaq1evBvDo2Ozs7NSJbo8VEBAAHx8fVFdXCw3X/v5+1NXVmZyhwBiVSoUDBw7g1q1bwl2SqqoqyOVyu10jmGnckGX/Kf7+/vj999/x2muvQSqVCgNOgoODUVBQgFWrVhldb/bs2fjqq69w5swZuLq6oqioCD09PXY7SeXm5sLd3R3e3t7IyMiAh4eH0BC1tWtBeno61Go1IiMjER0djeLiYgwODmLz5s1Cmk2bNmH69OkoKCgAACQmJqKoqAjh4eFC14KsrCwkJiYKDdqBgQGdiFB7ezsaGxvh5uZm9S3I9evXIz8/HytXrkRBQQGmTZuGs2fPwtfXFyqVCtnZ2VixYgWUSiXWrFmDSZMmoampCefPnzc7AGssPz8/iEQinD59GsuWLYNMJjMZZUtNTUVxcTF27NiB7du3o6WlBTk5OUhPTzcahQ4KCsLSpUuRkpKCw4cPw9HREWlpaQaRZlu7FjQ3N0Oj0aC3txf3798XGlPai+uJEyegVqtRUlKCmJgY3Lx5E8CjCPfY27Ojo6M4fvw41Gq10SmR9Os9NzcXCxYswKxZs3D37l0UFhaio6NDiMwDQG9vLzo7O9Hd3Q3gUeMAeBRpsjbalJ2djYiICMybNw/Dw8M4ffq08ENNX0pKCoqKirB7924kJyejsbFRGIhpaeCaOUqlEhKJBKWlpXjrrbdw/vx5o40+W441jUaD5uZm4X1XVxcaGxvh4uIi5PPuu+8iMTERfn5+6O7uRk5ODhwcHLB+/Xohn/HUy6lTp+Dp6QmlUolz585h586dWLlyJeLi4qwuv637vyl1dXWorq5GXFwcvLy8UFdXh9u3bwt1vG/fPrzzzjtQKBRYunQphoeHUV9fj76+PqSnp8PLywsymQyVlZWYMWMGJk+eDIVCYVPXAoVCgeTkZKSnp8PNzQ1yuRw7duyASqXCggULhHRjz/UikQhpaWnYv38/Zs+ejYCAAGRlZcHX11dnPufOzk7hOBgZGRGOz1mzZsHFxQVxcXGYO3cuNm7ciA8//BA3b95EZmYmtm3bBqlUavV2ZOP073bRZU+jidoJ3ZrBXn/88QeFhYWRVCrVmX4LAB0/ftxk3nfu3KGkpCRycXEhLy8vyszMpE2bNukMzNH/LiLjA0AwZqCUdmDSDz/8QPPmzSOJRELR0dHU1NRkw39uqLS0lJRKpZDf2OmttGXVTktF9GhA2d69eykwMJAmT55MM2fOpNTUVJ0BU9qy6r/G5pOTk2NQB/quXr1Kq1evJrlcTk5OThQZGUl1dXXC55WVlbRw4UKSyWQkl8spOjqaPvnkE+FzGBloplAodOovNzeXfHx8SCQS6Uy/pV8/RLZPv3Xjxg1avnw5SaVSUiqV9Pnnnz/29Ft+fn5Gt+3YMlja9kREP//8MwGglpYWo9+jX+9paWnCfuLt7U3Lli2jv//+W2cd7cAq/VdOTo6QRq1Wm50yKS8vj0JCQkgmk5GbmxslJSXRlStXiMi66bcOHz5MAIRzkrFBN8amudIfPHfixAny9/cnqVRKKpWKvv/++3EPYBtbdv3X2G2xbt06mjZtGkkkEpo+fTqtW7dOZ5Aa0fjqpaSkhGbMmEFisZiUSiVlZmYaTPVkqV6ILO//1gz2am5upvj4ePL09CSpVEpz5syh0tJSnXXKyspo/vz5JJFIyNXVlV588UWdAbZHjx6lmTNn0qRJk8Y1/RbRo2tXamqqMLXfqlWr6MaNGzpp9M/1o6OjlJWVRd7e3iSVSik2Ntbg+NGfckz7+u2334Q0V69epYSEBJLJZOTh4UG7du3S2Y7GyjoRr7NPIxGRHe8bsmfCgwcP0N7ejoCAAIOnyTD7qqmpwZIlS9DX12fyiTETiVqttjiVGXv2vPTSS1iyZAn27t37RPI/cOAAjhw5gmvXrj2R/J9VT7pe2PjxddZ+uGsBY8wuiAg1NTU2zWPJJr579+6hra0NP/74o93yPHToEKKiouDu7o7a2loUFhaa7ePNDD2JemHsacQNWcaYXYhEIoPHm7Jnn0KhwPXr1+2a5+XLl7F//3709vZCqVRi165d+OCDD+z6Hc+6J1EvjD2NuGsBM8C3PBhjjLEnh6+z9sOPqGWMMcYYYxMSN2SZSRysZ4wxxuyPr6/2ww1ZZkA7b6j+U6sYY4wx9viGhoYAjO/hKEwXD/ZiBhwdHeHk5ITbt29DLBbb7fGkjDHG2H8ZEWFoaAi3bt3C1KlTLT6ml1nGg72YURqNBu3t7VY9v54xxhhj1ps6dSp8fHwe62l17BFuyDKTRkdHuXsBY4wxZkdisZgjsXbEDVnGGGOMMTYhcedHxhhjjDE2IXFDljHGGGOMTUjckGWMMcYYYxMSN2QZY4wxxtiExA1ZxhhjjDE2IXFDljHGGGOMTUjckGWMMcYYYxPS/wAFolxGN916gwAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import scipy as sp \n",
+    "awa_env.screen_name = 'DYG6'\n",
+    "awa_env.image_diagnostic.test_measurement()\n",
+    "X,Y,Z=awa_env.image_diagnostic.get_processed_image()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "d53d165d-9a42-4da5-a811-aa00312c87f9",
+   "metadata": {
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true,
+     "source_hidden": true
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "362 362\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_2664430/217084843.py:6: DeprecationWarning: Please import `rotate` from the `scipy.ndimage` namespace; the `scipy.ndimage.interpolation` namespace is deprecated and will be removed in SciPy 2.0.0.\n",
+      "  img45=sp.ndimage.interpolation.rotate(X,45,reshape=False,order=1)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fcee018d940>]"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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"
+    }
+   ],
+   "source": [
+    "import scipy as sp\n",
+    "import numpy as np\n",
+    "dim1,dim2=np.shape(X)\n",
+    "print(dim1,dim2)\n",
+    "plt.imshow(X)\n",
+    "img45=sp.ndimage.interpolation.rotate(X,45,reshape=False,order=1)\n",
+    "\n",
+    "if dim1==dim2:\n",
+    "    img45_cropped=img45[int(dim1*(2-np.sqrt(2))/4):int(dim1*(2+np.sqrt(2))/4),int(dim2*(2-np.sqrt(2))/4):int(dim2*(2+np.sqrt(2))/4)]\n",
+    "if dim1<dim2:\n",
+    "    img45_cropped=img45[int(dim1*(2-np.sqrt(2))/4):int(dim1*(2+np.sqrt(2))/4),int(dim1*(2-np.sqrt(2))/4):int(dim1*(2+np.sqrt(2))/4)]\n",
+    "if dim2<dim1:\n",
+    "    img45_cropped=img45[int(dim2*(2-np.sqrt(2))/4):int(dim2*(2+np.sqrt(2))/4),int(dim2*(2-np.sqrt(2))/4):int(dim2*(2+np.sqrt(2))/4)]\n",
+    "\n",
+    "plt.imshow(img45_cropped) \n",
+    "plt.figure()\n",
+    "plt.plot(np.mean(img45_cropped,0))\n",
+    "plt.plot(np.mean(img45_cropped,1))\n",
+    "\n",
+    "#plt.imshow(img45)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "d920111d-8b18-4487-a5da-d3459310fbc8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# awa_env.screen_name = 'DYG4'\n",
+    "# awa_env.image_diagnostic.resolution = 50/460 #Yag4\n",
+    "\n",
+    "# awa_env.screen_name = 'DYG5'\n",
+    "# awa_env.image_diagnostic.resolution = 25/206.9578032921999 #Yag5\n",
+    "\n",
+    "awa_env.screen_name = 'DYG7'\n",
+    "awa_env.image_diagnostic.resolution = 25/500 #Yag7\n",
+    "\n",
+    "awa_env.image_diagnostic.save_image_location = \"./Data/\"\n",
+    "awa_env.image_diagnostic.target_charge = 1.4e-9\n",
+    "awa_env.image_diagnostic.charge_atol = 0.1\n",
+    "awa_env.image_diagnostic.target_charge_pv = \"AWAVXI11ICT:Ch1\"\n",
+    "awa_env.image_diagnostic.extra_pvs = [\"AWA:Drive:DS3:RB\",\"AWA:Drive:DS6:RB\",\"AWA:Bira3RB:Ch02\",\"AWA:Bira3RB:Ch03\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "342c1465-fc73-428a-8f27-3e25dbcd2fce",
+   "metadata": {
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "measured charge:  1.760018749548718e-09\n",
+      "charge error 0.35 outside atol 0.1\n",
+      "measured charge:  1.5472123643943435e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.5334999442926038e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.548264256334372e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.7552113872406286e-09\n",
+      "charge error 0.35 outside atol 0.1\n",
+      "measured charge:  1.628892494011259e-09\n",
+      "charge error 0.25 outside atol 0.1\n",
+      "measured charge:  1.6550529024649652e-09\n",
+      "charge error 0.27 outside atol 0.1\n",
+      "measured charge:  1.5128241436426726e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.7261294569946313e-09\n",
+      "charge error 0.33 outside atol 0.1\n",
+      "measured charge:  1.371416725102376e-09\n",
+      "fitting image\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'Cx': 453.6304323200373,\n",
+       " 'Cy': 396.7466490032778,\n",
+       " 'Sx': 1.2136119333369817,\n",
+       " 'Sy': 1.2828793740462705,\n",
+       " 'correlation': 6.285688767723659,\n",
+       " 'bb_penalty': -324.985745743595,\n",
+       " 'total_intensity': 214055521.0,\n",
+       " 'log10_total_intensity': 8.33052643380038,\n",
+       " 'AWA:Drive:DS3:RB': 180.25292968750003,\n",
+       " 'AWA:Drive:DS6:RB': 0.9594726562500001,\n",
+       " 'AWA:Bira3RB:Ch02': -0.000549,\n",
+       " 'AWA:Bira3RB:Ch03': 0.003296,\n",
+       " 'AWAVXI11ICT:Ch1': 1.371416725102376e-09,\n",
+       " 'save_filename': './Data/DYG7_1720709807.h5'}"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "awa_env.image_diagnostic.measure_beamsize(n_shots=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "ec96c1c4-1388-46de-be79-98f3cdfe4cea",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import epics\n",
+    "import os\n",
+    "import time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "130309f4-c162-4f75-8275-d53bf27eb61f",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m\n",
+      "Step 1/49\n",
+      "quad4 | skewquad3\n",
+      " -0.672 | -0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "setting camera DYG7\n",
+      "cannot connect to SI-138:cam1:GC_SetCameraName\n",
+      "None\n",
+      "cannot connect to SI-138:cam1:GC_SetCameraName\n",
+      "starting acquisition\n",
+      "measured charge:  4.431319945462096e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6260966653724137e-09\n",
+      "fitting image\n",
+      "measured charge:  4.194941454453029e-09\n",
+      "fitting image\n",
+      "measured charge:  4.7373826751282135e-09\n",
+      "fitting image\n",
+      "measured charge:  4.346089680547607e-09\n",
+      "fitting image\n",
+      "measured charge:  4.269726648545281e-09\n",
+      "fitting image\n",
+      "measured charge:  4.9922575331442416e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  4.385737360999367e-09\n",
+      "fitting image\n",
+      "measured charge:  4.2980592859024615e-09\n",
+      "fitting image\n",
+      "measured charge:  4.361814024103065e-09\n",
+      "fitting image\n",
+      "measured charge:  5.0942406181515394e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.603774386896633e-09\n",
+      "fitting image\n",
+      "measured charge:  4.165596551222042e-09\n",
+      "fitting image\n",
+      "measured charge:  6.306182239695858e-09\n",
+      "charge error 0.58 outside atol 0.2\n",
+      "measured charge:  4.29990009679753e-09\n",
+      "fitting image\n",
+      "measured charge:  4.690530255361074e-09\n",
+      "fitting image\n",
+      "measured charge:  4.5004620274856176e-09\n",
+      "fitting image\n",
+      "measured charge:  4.066565608149204e-09\n",
+      "fitting image\n",
+      "measured charge:  4.720858605508619e-09\n",
+      "fitting image\n",
+      "measured charge:  3.4271702105087795e-09\n",
+      "fitting image\n",
+      "measured charge:  2.4289265606091844e-09\n",
+      "charge error 0.39 outside atol 0.2\n",
+      "measured charge:  4.044546123616994e-09\n",
+      "fitting image\n",
+      "measured charge:  3.715163453972206e-09\n",
+      "fitting image\n",
+      "measured charge:  5.060644918724557e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.775683069328045e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 2/49\n",
+      "quad4 | skewquad3\n",
+      " -0.336 | -0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.859540831402939e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.906834541453101e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.594815293558069e-09\n",
+      "fitting image\n",
+      "measured charge:  5.2699011685814214e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  4.631638716198336e-09\n",
+      "fitting image\n",
+      "measured charge:  5.079629406820276e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.53688378590902e-09\n",
+      "fitting image\n",
+      "measured charge:  4.7914182199925375e-09\n",
+      "fitting image\n",
+      "measured charge:  4.855484563168529e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  6.099101821112294e-09\n",
+      "charge error 0.52 outside atol 0.2\n",
+      "measured charge:  4.785847155316938e-09\n",
+      "fitting image\n",
+      "measured charge:  5.404195708232672e-09\n",
+      "charge error 0.35 outside atol 0.2\n",
+      "measured charge:  4.579580872276028e-09\n",
+      "fitting image\n",
+      "measured charge:  5.459890144324339e-09\n",
+      "charge error 0.36 outside atol 0.2\n",
+      "measured charge:  4.421636775822375e-09\n",
+      "fitting image\n",
+      "measured charge:  4.258615139336396e-09\n",
+      "fitting image\n",
+      "measured charge:  3.828812813115754e-09\n",
+      "fitting image\n",
+      "measured charge:  3.960463213438338e-09\n",
+      "fitting image\n",
+      "measured charge:  4.620665898221189e-09\n",
+      "fitting image\n",
+      "measured charge:  5.239318851372997e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  5.103601375706836e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  5.099217291833619e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.04357528499427e-09\n",
+      "fitting image\n",
+      "measured charge:  4.265178656852526e-09\n",
+      "fitting image\n",
+      "measured charge:  3.477632204672795e-09\n",
+      "fitting image\n",
+      "measured charge:  4.3277031858150085e-09\n",
+      "fitting image\n",
+      "measured charge:  4.115655099473627e-09\n",
+      "fitting image\n",
+      "measured charge:  3.788030386221865e-09\n",
+      "fitting image\n",
+      "measured charge:  5.268831264793026e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  4.389588294163422e-09\n",
+      "fitting image\n",
+      "measured charge:  4.13911733305376e-09\n",
+      "fitting image\n",
+      "measured charge:  5.086643220543667e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.4273717483173764e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 3/49\n",
+      "quad4 | skewquad3\n",
+      " -0.168 | -0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  3.8619131867148025e-09\n",
+      "fitting image\n",
+      "measured charge:  3.847174091260692e-09\n",
+      "fitting image\n",
+      "measured charge:  4.727083500277037e-09\n",
+      "fitting image\n",
+      "measured charge:  3.4663477817202637e-09\n",
+      "fitting image\n",
+      "measured charge:  4.606865220062834e-09\n",
+      "fitting image\n",
+      "measured charge:  4.491101269930319e-09\n",
+      "fitting image\n",
+      "measured charge:  5.042456554323264e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  4.118021856338677e-09\n",
+      "fitting image\n",
+      "measured charge:  3.779082099992338e-09\n",
+      "fitting image\n",
+      "measured charge:  4.1260893631869526e-09\n",
+      "fitting image\n",
+      "measured charge:  3.972160107716762e-09\n",
+      "fitting image\n",
+      "measured charge:  5.312011068694141e-09\n",
+      "charge error 0.33 outside atol 0.2\n",
+      "measured charge:  4.374530388994484e-09\n",
+      "fitting image\n",
+      "measured charge:  3.93778269407399e-09\n",
+      "fitting image\n",
+      "measured charge:  4.836838697820656e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.30970934937529e-09\n",
+      "fitting image\n",
+      "measured charge:  4.447878237593328e-09\n",
+      "fitting image\n",
+      "measured charge:  6.092084405019088e-09\n",
+      "charge error 0.52 outside atol 0.2\n",
+      "measured charge:  5.455972567321674e-09\n",
+      "charge error 0.36 outside atol 0.2\n",
+      "measured charge:  4.5394630825838674e-09\n",
+      "fitting image\n",
+      "measured charge:  3.814347497755542e-09\n",
+      "fitting image\n",
+      "measured charge:  4.86863141123393e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.321570151472996e-09\n",
+      "fitting image\n",
+      "measured charge:  2.8409800115266384e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  4.248415029650808e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6784408976824495e-09\n",
+      "fitting image\n",
+      "measured charge:  4.773319914832582e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 4/49\n",
+      "quad4 | skewquad3\n",
+      " 0 | -0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.595368257300508e-09\n",
+      "fitting image\n",
+      "measured charge:  4.576666555223056e-09\n",
+      "fitting image\n",
+      "measured charge:  4.103889760171788e-09\n",
+      "fitting image\n",
+      "measured charge:  3.904916474502681e-09\n",
+      "fitting image\n",
+      "measured charge:  4.3095238273378194e-09\n",
+      "fitting image\n",
+      "measured charge:  5.171531260340654e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  5.288435360469879e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  4.118614446147399e-09\n",
+      "fitting image\n",
+      "measured charge:  4.263118101408345e-09\n",
+      "fitting image\n",
+      "measured charge:  4.5171716191425584e-09\n",
+      "fitting image\n",
+      "measured charge:  4.137260311495143e-09\n",
+      "fitting image\n",
+      "measured charge:  4.720907237499012e-09\n",
+      "fitting image\n",
+      "measured charge:  5.446692863083617e-09\n",
+      "charge error 0.36 outside atol 0.2\n",
+      "measured charge:  4.92216262434621e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.830995654235955e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.649585721832579e-09\n",
+      "fitting image\n",
+      "measured charge:  3.941948834583024e-09\n",
+      "fitting image\n",
+      "measured charge:  4.826418843585949e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.1917911821873984e-09\n",
+      "fitting image\n",
+      "measured charge:  5.871695031735403e-09\n",
+      "charge error 0.47 outside atol 0.2\n",
+      "measured charge:  4.53770332500617e-09\n",
+      "fitting image\n",
+      "measured charge:  4.299599298931177e-09\n",
+      "fitting image\n",
+      "measured charge:  4.479170221624284e-09\n",
+      "fitting image\n",
+      "measured charge:  4.008585468509757e-09\n",
+      "fitting image\n",
+      "measured charge:  4.537240420505208e-09\n",
+      "fitting image\n",
+      "measured charge:  4.576118995035008e-09\n",
+      "fitting image\n",
+      "measured charge:  4.597659364402838e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 5/49\n",
+      "quad4 | skewquad3\n",
+      " 0.168 | -0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.276317183833872e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9447118521104205e-09\n",
+      "fitting image\n",
+      "measured charge:  5.23970070255672e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  4.2482763384189336e-09\n",
+      "fitting image\n",
+      "measured charge:  6.05678298355941e-09\n",
+      "charge error 0.51 outside atol 0.2\n",
+      "measured charge:  4.976342263996923e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  4.4685486346888184e-09\n",
+      "fitting image\n",
+      "measured charge:  3.88323921508791e-09\n",
+      "fitting image\n",
+      "measured charge:  4.129210816495206e-09\n",
+      "fitting image\n",
+      "measured charge:  5.18605781598502e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.516708714641596e-09\n",
+      "fitting image\n",
+      "measured charge:  4.278021104681991e-09\n",
+      "fitting image\n",
+      "measured charge:  4.665308264203244e-09\n",
+      "fitting image\n",
+      "measured charge:  3.830035817614562e-09\n",
+      "fitting image\n",
+      "measured charge:  3.934749498822291e-09\n",
+      "fitting image\n",
+      "measured charge:  4.592446735508224e-09\n",
+      "fitting image\n",
+      "measured charge:  4.427341128175202e-09\n",
+      "fitting image\n",
+      "measured charge:  5.9726730556083184e-09\n",
+      "charge error 0.49 outside atol 0.2\n",
+      "measured charge:  3.1293731180221137e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.342119869184824e-09\n",
+      "fitting image\n",
+      "measured charge:  3.5716270349642593e-09\n",
+      "fitting image\n",
+      "measured charge:  4.3848835993904475e-09\n",
+      "fitting image\n",
+      "measured charge:  4.2646689215459655e-09\n",
+      "fitting image\n",
+      "measured charge:  4.408963639366838e-09\n",
+      "fitting image\n",
+      "measured charge:  4.020638997384117e-09\n",
+      "fitting image\n",
+      "measured charge:  4.616742917664007e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 6/49\n",
+      "quad4 | skewquad3\n",
+      " 0.336 | -0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  3.941572386953821e-09\n",
+      "fitting image\n",
+      "measured charge:  3.891575098475696e-09\n",
+      "fitting image\n",
+      "measured charge:  5.186801705319319e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.8391280037380555e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.588194138127432e-09\n",
+      "fitting image\n",
+      "measured charge:  5.359384030876695e-09\n",
+      "charge error 0.34 outside atol 0.2\n",
+      "measured charge:  4.076111887741845e-09\n",
+      "fitting image\n",
+      "measured charge:  4.404498502176245e-09\n",
+      "fitting image\n",
+      "measured charge:  5.262393830214893e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  3.987933083262618e-09\n",
+      "fitting image\n",
+      "measured charge:  3.1561441281327723e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  3.759341114268495e-09\n",
+      "fitting image\n",
+      "measured charge:  3.2527722906439996e-09\n",
+      "fitting image\n",
+      "measured charge:  3.956662713449601e-09\n",
+      "fitting image\n",
+      "measured charge:  4.675663275784129e-09\n",
+      "fitting image\n",
+      "measured charge:  3.964508674563972e-09\n",
+      "fitting image\n",
+      "measured charge:  4.405707097196429e-09\n",
+      "fitting image\n",
+      "measured charge:  4.80110319081705e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.08463149198218e-09\n",
+      "fitting image\n",
+      "measured charge:  4.455841275721504e-09\n",
+      "fitting image\n",
+      "measured charge:  4.6941308238339695e-09\n",
+      "fitting image\n",
+      "measured charge:  5.77128618226856e-09\n",
+      "charge error 0.44 outside atol 0.2\n",
+      "measured charge:  5.22297850260608e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  4.595899606825007e-09\n",
+      "fitting image\n",
+      "measured charge:  4.728039929421136e-09\n",
+      "fitting image\n",
+      "measured charge:  4.613032476916748e-09\n",
+      "fitting image\n",
+      "measured charge:  4.188712957315023e-09\n",
+      "fitting image\n",
+      "measured charge:  5.203878738681356e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.928265038546309e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.834025247118069e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.890852628467037e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.318920608589812e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 7/49\n",
+      "quad4 | skewquad3\n",
+      " 0.672 | -0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.0602020221490376e-09\n",
+      "fitting image\n",
+      "measured charge:  3.951958018676755e-09\n",
+      "fitting image\n",
+      "measured charge:  4.206996784512312e-09\n",
+      "fitting image\n",
+      "measured charge:  4.755488185027348e-09\n",
+      "fitting image\n",
+      "measured charge:  4.273629816069325e-09\n",
+      "fitting image\n",
+      "measured charge:  2.883408721354125e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  3.785252959215843e-09\n",
+      "fitting image\n",
+      "measured charge:  3.785022407557698e-09\n",
+      "fitting image\n",
+      "measured charge:  4.777722010554283e-09\n",
+      "fitting image\n",
+      "measured charge:  4.059022246086106e-09\n",
+      "fitting image\n",
+      "measured charge:  4.895667195514505e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.785692253421773e-09\n",
+      "fitting image\n",
+      "measured charge:  5.014271614122064e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  3.983696696545252e-09\n",
+      "fitting image\n",
+      "measured charge:  4.045374668638255e-09\n",
+      "fitting image\n",
+      "measured charge:  4.56717070880548e-09\n",
+      "fitting image\n",
+      "measured charge:  4.607216451104508e-09\n",
+      "fitting image\n",
+      "measured charge:  4.229246820702545e-09\n",
+      "fitting image\n",
+      "measured charge:  6.098350727038568e-09\n",
+      "charge error 0.52 outside atol 0.2\n",
+      "measured charge:  4.677451852319079e-09\n",
+      "fitting image\n",
+      "measured charge:  4.2672896454718975e-09\n",
+      "fitting image\n",
+      "measured charge:  4.31179332022221e-09\n",
+      "fitting image\n",
+      "measured charge:  4.473905358369688e-09\n",
+      "fitting image\n",
+      "measured charge:  4.9787720623309936e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  3.830963427801409e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 8/49\n",
+      "quad4 | skewquad3\n",
+      " -0.672 | -0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  5.012115595881885e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  4.016045976070686e-09\n",
+      "fitting image\n",
+      "measured charge:  5.01224167881993e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  3.7904908046979885e-09\n",
+      "fitting image\n",
+      "measured charge:  4.70922115032975e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9697699354488496e-09\n",
+      "fitting image\n",
+      "measured charge:  4.319795984416541e-09\n",
+      "fitting image\n",
+      "measured charge:  3.799885784765053e-09\n",
+      "fitting image\n",
+      "measured charge:  4.756136611565783e-09\n",
+      "fitting image\n",
+      "measured charge:  4.238854340579411e-09\n",
+      "fitting image\n",
+      "measured charge:  3.5981945111892264e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9924828761401675e-09\n",
+      "fitting image\n",
+      "measured charge:  4.331507288173466e-09\n",
+      "fitting image\n",
+      "measured charge:  4.323477606206673e-09\n",
+      "fitting image\n",
+      "measured charge:  5.191313673315511e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.638312105989088e-09\n",
+      "fitting image\n",
+      "measured charge:  4.847103650160065e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  3.4719080392868274e-09\n",
+      "fitting image\n",
+      "measured charge:  4.959506589401937e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  3.5004261986813526e-09\n",
+      "fitting image\n",
+      "measured charge:  4.776304478094022e-09\n",
+      "fitting image\n",
+      "measured charge:  5.12976358534535e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  4.79981174129483e-09\n",
+      "fitting image\n",
+      "measured charge:  4.845361904430583e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.491710070402468e-09\n",
+      "fitting image\n",
+      "measured charge:  5.458573478214559e-09\n",
+      "charge error 0.36 outside atol 0.2\n",
+      "measured charge:  4.301613023569761e-09\n",
+      "fitting image\n",
+      "measured charge:  3.801530266513741e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 9/49\n",
+      "quad4 | skewquad3\n",
+      " -0.336 | -0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  3.888612149432325e-09\n",
+      "fitting image\n",
+      "measured charge:  5.04959464979977e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  4.9970973167792376e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  4.011732138405667e-09\n",
+      "fitting image\n",
+      "measured charge:  4.059852592292166e-09\n",
+      "fitting image\n",
+      "measured charge:  5.063732149521175e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.38291850674226e-09\n",
+      "fitting image\n",
+      "measured charge:  3.84666975950865e-09\n",
+      "fitting image\n",
+      "measured charge:  5.3671273244557605e-09\n",
+      "charge error 0.34 outside atol 0.2\n",
+      "measured charge:  4.672190591434205e-09\n",
+      "fitting image\n",
+      "measured charge:  4.818596297874443e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  3.876688305865603e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6164170981022964e-09\n",
+      "fitting image\n",
+      "measured charge:  4.493977762101929e-09\n",
+      "fitting image\n",
+      "measured charge:  4.48998093296682e-09\n",
+      "fitting image\n",
+      "measured charge:  5.296737021345812e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  4.205890857027436e-09\n",
+      "fitting image\n",
+      "measured charge:  4.519100688094174e-09\n",
+      "fitting image\n",
+      "measured charge:  5.055108076560862e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  4.122735557035627e-09\n",
+      "fitting image\n",
+      "measured charge:  3.1158210033701224e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  3.9824160541319326e-09\n",
+      "fitting image\n",
+      "measured charge:  4.551269849136787e-09\n",
+      "fitting image\n",
+      "measured charge:  3.985949978766087e-09\n",
+      "fitting image\n",
+      "measured charge:  3.669179205292741e-09\n",
+      "fitting image\n",
+      "measured charge:  4.6667816333932155e-09\n",
+      "fitting image\n",
+      "measured charge:  4.115723544497035e-09\n",
+      "fitting image\n",
+      "measured charge:  4.173921627500796e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 10/49\n",
+      "quad4 | skewquad3\n",
+      " -0.168 | -0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  3.221615395475194e-09\n",
+      "fitting image\n",
+      "measured charge:  3.0269469415469868e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  3.4787327286031513e-09\n",
+      "fitting image\n",
+      "measured charge:  4.547775550568921e-09\n",
+      "fitting image\n",
+      "measured charge:  4.041440880972032e-09\n",
+      "fitting image\n",
+      "measured charge:  4.028041867030538e-09\n",
+      "fitting image\n",
+      "measured charge:  4.654301223714464e-09\n",
+      "fitting image\n",
+      "measured charge:  4.261999565629642e-09\n",
+      "fitting image\n",
+      "measured charge:  4.267817392626805e-09\n",
+      "fitting image\n",
+      "measured charge:  4.865167732808244e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.469476244875661e-09\n",
+      "fitting image\n",
+      "measured charge:  3.527038704527114e-09\n",
+      "fitting image\n",
+      "measured charge:  5.0028827224494296e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  3.843663582029277e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9526478724661445e-09\n",
+      "fitting image\n",
+      "measured charge:  4.191126544985668e-09\n",
+      "fitting image\n",
+      "measured charge:  4.20176974613908e-09\n",
+      "fitting image\n",
+      "measured charge:  4.280332024817329e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6902530677897614e-09\n",
+      "fitting image\n",
+      "measured charge:  4.4707406766254236e-09\n",
+      "fitting image\n",
+      "measured charge:  3.593286282530691e-09\n",
+      "fitting image\n",
+      "measured charge:  3.855908036495627e-09\n",
+      "fitting image\n",
+      "measured charge:  4.536644228326763e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 11/49\n",
+      "quad4 | skewquad3\n",
+      " 0 | -0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.132683500845137e-09\n",
+      "fitting image\n",
+      "measured charge:  5.620103733662349e-09\n",
+      "charge error 0.41 outside atol 0.2\n",
+      "measured charge:  4.909469674857659e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.067185215730256e-09\n",
+      "fitting image\n",
+      "measured charge:  3.7026218040092215e-09\n",
+      "fitting image\n",
+      "measured charge:  4.8218798578173025e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.092742227266335e-09\n",
+      "fitting image\n",
+      "measured charge:  4.3140952344334365e-09\n",
+      "fitting image\n",
+      "measured charge:  4.120928968652329e-09\n",
+      "fitting image\n",
+      "measured charge:  4.098603282699253e-09\n",
+      "fitting image\n",
+      "measured charge:  4.164076351226472e-09\n",
+      "fitting image\n",
+      "measured charge:  3.876497380273741e-09\n",
+      "fitting image\n",
+      "measured charge:  4.630961470702649e-09\n",
+      "fitting image\n",
+      "measured charge:  4.200031602779318e-09\n",
+      "fitting image\n",
+      "measured charge:  4.986677462544665e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  5.008756386176173e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  4.298628460308453e-09\n",
+      "fitting image\n",
+      "measured charge:  3.848283621115167e-09\n",
+      "fitting image\n",
+      "measured charge:  3.7136774764885255e-09\n",
+      "fitting image\n",
+      "measured charge:  5.12306317778227e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  3.983496765029276e-09\n",
+      "fitting image\n",
+      "measured charge:  3.462336543106528e-09\n",
+      "fitting image\n",
+      "measured charge:  4.332622221582582e-09\n",
+      "fitting image\n",
+      "measured charge:  4.702414472861644e-09\n",
+      "fitting image\n",
+      "measured charge:  3.8678462895409746e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6718107363275753e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 12/49\n",
+      "quad4 | skewquad3\n",
+      " 0.168 | -0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.777630150128008e-09\n",
+      "fitting image\n",
+      "measured charge:  5.5942657372930556e-09\n",
+      "charge error 0.4 outside atol 0.2\n",
+      "measured charge:  4.081041730618317e-09\n",
+      "fitting image\n",
+      "measured charge:  5.105634913378694e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  3.639526299455955e-09\n",
+      "fitting image\n",
+      "measured charge:  4.07711154532182e-09\n",
+      "fitting image\n",
+      "measured charge:  4.673474836217108e-09\n",
+      "fitting image\n",
+      "measured charge:  3.5805230868338e-09\n",
+      "fitting image\n",
+      "measured charge:  4.174881659014617e-09\n",
+      "fitting image\n",
+      "measured charge:  4.079011795316313e-09\n",
+      "fitting image\n",
+      "measured charge:  5.149283025335153e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  3.245956607251781e-09\n",
+      "fitting image\n",
+      "measured charge:  4.068154253168182e-09\n",
+      "fitting image\n",
+      "measured charge:  4.89562576826342e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  5.065093845251726e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.622764278546734e-09\n",
+      "fitting image\n",
+      "measured charge:  3.910195747235903e-09\n",
+      "fitting image\n",
+      "measured charge:  4.4806616026626044e-09\n",
+      "fitting image\n",
+      "measured charge:  4.474155723060844e-09\n",
+      "fitting image\n",
+      "measured charge:  4.666790639317452e-09\n",
+      "fitting image\n",
+      "measured charge:  4.007230977518517e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9152318600172806e-09\n",
+      "fitting image\n",
+      "measured charge:  4.0973766758308516e-09\n",
+      "fitting image\n",
+      "measured charge:  3.3345370759478702e-09\n",
+      "fitting image\n",
+      "measured charge:  3.2467887546426402e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 13/49\n",
+      "quad4 | skewquad3\n",
+      " 0.336 | -0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  3.729086612699006e-09\n",
+      "fitting image\n",
+      "measured charge:  3.888010553699497e-09\n",
+      "fitting image\n",
+      "measured charge:  3.988610328758176e-09\n",
+      "fitting image\n",
+      "measured charge:  3.5436780499755962e-09\n",
+      "fitting image\n",
+      "measured charge:  4.2569292303366226e-09\n",
+      "fitting image\n",
+      "measured charge:  4.049587639952757e-09\n",
+      "fitting image\n",
+      "measured charge:  5.046741573031024e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  4.590206061581216e-09\n",
+      "fitting image\n",
+      "measured charge:  4.611411410570797e-09\n",
+      "fitting image\n",
+      "measured charge:  5.7827561272585406e-09\n",
+      "charge error 0.45 outside atol 0.2\n",
+      "measured charge:  4.8114509976584914e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  5.4998836522633495e-09\n",
+      "charge error 0.37 outside atol 0.2\n",
+      "measured charge:  4.2998064351864624e-09\n",
+      "fitting image\n",
+      "measured charge:  4.164764403831189e-09\n",
+      "fitting image\n",
+      "measured charge:  4.3177876633324776e-09\n",
+      "fitting image\n",
+      "measured charge:  4.229915060274119e-09\n",
+      "fitting image\n",
+      "measured charge:  4.358400778852443e-09\n",
+      "fitting image\n",
+      "measured charge:  4.065236333745489e-09\n",
+      "fitting image\n",
+      "measured charge:  4.406867060226092e-09\n",
+      "fitting image\n",
+      "measured charge:  3.763373967100178e-09\n",
+      "fitting image\n",
+      "measured charge:  4.835943508960783e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  3.979608006983865e-09\n",
+      "fitting image\n",
+      "measured charge:  4.077705936315343e-09\n",
+      "fitting image\n",
+      "measured charge:  5.1661691331052784e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  4.791800071176255e-09\n",
+      "fitting image\n",
+      "measured charge:  4.439906193541046e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 14/49\n",
+      "quad4 | skewquad3\n",
+      " 0.672 | -0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  5.666983171201813e-09\n",
+      "charge error 0.42 outside atol 0.2\n",
+      "measured charge:  4.7573596160644626e-09\n",
+      "fitting image\n",
+      "measured charge:  3.2565493752299973e-09\n",
+      "fitting image\n",
+      "measured charge:  4.5127533127574324e-09\n",
+      "fitting image\n",
+      "measured charge:  3.894314700600352e-09\n",
+      "fitting image\n",
+      "measured charge:  3.373689430571699e-09\n",
+      "fitting image\n",
+      "measured charge:  3.924075677526708e-09\n",
+      "fitting image\n",
+      "measured charge:  4.224461072612461e-09\n",
+      "fitting image\n",
+      "measured charge:  4.04058351699352e-09\n",
+      "fitting image\n",
+      "measured charge:  3.7604200239809215e-09\n",
+      "fitting image\n",
+      "measured charge:  4.50509107249574e-09\n",
+      "fitting image\n",
+      "measured charge:  5.2143202071338685e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.577570750007035e-09\n",
+      "fitting image\n",
+      "measured charge:  4.692933035922819e-09\n",
+      "fitting image\n",
+      "measured charge:  3.3955468084694197e-09\n",
+      "fitting image\n",
+      "measured charge:  4.9317395240810255e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  3.4764902534913452e-09\n",
+      "fitting image\n",
+      "measured charge:  4.621078369546961e-09\n",
+      "fitting image\n",
+      "measured charge:  4.359742661549985e-09\n",
+      "fitting image\n",
+      "measured charge:  4.325419283452122e-09\n",
+      "fitting image\n",
+      "measured charge:  4.990242007320867e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  4.302117355321801e-09\n",
+      "fitting image\n",
+      "measured charge:  4.14649678729732e-09\n",
+      "fitting image\n",
+      "measured charge:  5.216885094330089e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  3.9365668943146214e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 15/49\n",
+      "quad4 | skewquad3\n",
+      " -0.672 | -0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  3.8104749503736754e-09\n",
+      "fitting image\n",
+      "measured charge:  4.9819511535538794e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  4.485252822791237e-09\n",
+      "fitting image\n",
+      "measured charge:  4.314705836090381e-09\n",
+      "fitting image\n",
+      "measured charge:  5.206715604786756e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  5.409640689970225e-09\n",
+      "charge error 0.35 outside atol 0.2\n",
+      "measured charge:  5.823273779982637e-09\n",
+      "charge error 0.46 outside atol 0.2\n",
+      "measured charge:  3.999833511426604e-09\n",
+      "fitting image\n",
+      "measured charge:  4.240594285124094e-09\n",
+      "fitting image\n",
+      "measured charge:  4.6496937929222765e-09\n",
+      "fitting image\n",
+      "measured charge:  3.821253240389239e-09\n",
+      "fitting image\n",
+      "measured charge:  4.023034573206418e-09\n",
+      "fitting image\n",
+      "measured charge:  4.349387649969095e-09\n",
+      "fitting image\n",
+      "measured charge:  3.947584741912437e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6566717778414044e-09\n",
+      "fitting image\n",
+      "measured charge:  3.2156318594739524e-09\n",
+      "fitting image\n",
+      "measured charge:  5.298779564941646e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  4.614230264827898e-09\n",
+      "fitting image\n",
+      "measured charge:  3.778453486487052e-09\n",
+      "fitting image\n",
+      "measured charge:  3.822528479248037e-09\n",
+      "fitting image\n",
+      "measured charge:  4.079469296262758e-09\n",
+      "fitting image\n",
+      "measured charge:  4.49925703483515e-09\n",
+      "fitting image\n",
+      "measured charge:  4.668541390971045e-09\n",
+      "fitting image\n",
+      "measured charge:  3.903625024980464e-09\n",
+      "fitting image\n",
+      "measured charge:  4.772628259858402e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 16/49\n",
+      "quad4 | skewquad3\n",
+      " -0.336 | -0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.22829219274337e-09\n",
+      "fitting image\n",
+      "measured charge:  4.42613973789446e-09\n",
+      "fitting image\n",
+      "measured charge:  4.300233315990855e-09\n",
+      "fitting image\n",
+      "measured charge:  4.646529111178144e-09\n",
+      "fitting image\n",
+      "measured charge:  4.52994562194848e-09\n",
+      "fitting image\n",
+      "measured charge:  3.68090311734349e-09\n",
+      "fitting image\n",
+      "measured charge:  3.896449104622465e-09\n",
+      "fitting image\n",
+      "measured charge:  4.897569246693667e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.543447303425277e-09\n",
+      "fitting image\n",
+      "measured charge:  5.1246788405737076e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  5.401059845445701e-09\n",
+      "charge error 0.35 outside atol 0.2\n",
+      "measured charge:  4.016211685074888e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9740981825924915e-09\n",
+      "fitting image\n",
+      "measured charge:  4.5377699688447825e-09\n",
+      "fitting image\n",
+      "measured charge:  4.4414047793185465e-09\n",
+      "fitting image\n",
+      "measured charge:  5.5135456391899295e-09\n",
+      "charge error 0.38 outside atol 0.2\n",
+      "measured charge:  4.098248449287989e-09\n",
+      "fitting image\n",
+      "measured charge:  4.623133521436623e-09\n",
+      "fitting image\n",
+      "measured charge:  3.755731539871618e-09\n",
+      "fitting image\n",
+      "measured charge:  3.538708581032962e-09\n",
+      "fitting image\n",
+      "measured charge:  3.629403640718018e-09\n",
+      "fitting image\n",
+      "measured charge:  4.063878240384656e-09\n",
+      "fitting image\n",
+      "measured charge:  5.0322006079079586e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  4.101065502360295e-09\n",
+      "fitting image\n",
+      "measured charge:  3.738757174044893e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 17/49\n",
+      "quad4 | skewquad3\n",
+      " -0.168 | -0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  3.70190493244738e-09\n",
+      "fitting image\n",
+      "measured charge:  5.5747246830852105e-09\n",
+      "charge error 0.39 outside atol 0.2\n",
+      "measured charge:  4.954760467378142e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  3.5525074580065175e-09\n",
+      "fitting image\n",
+      "measured charge:  3.738287064804499e-09\n",
+      "fitting image\n",
+      "measured charge:  4.845767171017037e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.232831178511884e-09\n",
+      "fitting image\n",
+      "measured charge:  2.90393502366334e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.049484972417578e-09\n",
+      "fitting image\n",
+      "measured charge:  3.0534405691939042e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  3.821067718351897e-09\n",
+      "fitting image\n",
+      "measured charge:  4.5863227070903176e-09\n",
+      "fitting image\n",
+      "measured charge:  4.708893334690812e-09\n",
+      "fitting image\n",
+      "measured charge:  5.905519481635712e-09\n",
+      "charge error 0.48 outside atol 0.2\n",
+      "measured charge:  3.705033590495072e-09\n",
+      "fitting image\n",
+      "measured charge:  4.406306891744341e-09\n",
+      "fitting image\n",
+      "measured charge:  5.337022321226967e-09\n",
+      "charge error 0.33 outside atol 0.2\n",
+      "measured charge:  4.003734877765728e-09\n",
+      "fitting image\n",
+      "measured charge:  4.045963656077257e-09\n",
+      "fitting image\n",
+      "measured charge:  3.642968363663834e-09\n",
+      "fitting image\n",
+      "measured charge:  4.920660436198985e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  3.6430278027631386e-09\n",
+      "fitting image\n",
+      "measured charge:  4.6738909099126026e-09\n",
+      "fitting image\n",
+      "measured charge:  4.928519005607188e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  3.6559422979857304e-09\n",
+      "fitting image\n",
+      "measured charge:  3.5406916855294883e-09\n",
+      "fitting image\n",
+      "measured charge:  4.544913467875937e-09\n",
+      "fitting image\n",
+      "measured charge:  4.627187988486369e-09\n",
+      "fitting image\n",
+      "measured charge:  4.727641867573995e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 18/49\n",
+      "quad4 | skewquad3\n",
+      " 0 | -0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.410676566139063e-09\n",
+      "fitting image\n",
+      "measured charge:  4.6582530232289e-09\n",
+      "fitting image\n",
+      "measured charge:  5.108017880907165e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  6.256127313303113e-09\n",
+      "charge error 0.56 outside atol 0.2\n",
+      "measured charge:  4.398610428970876e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9223645519394034e-09\n",
+      "fitting image\n",
+      "measured charge:  2.7822830003253522e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.0258624333877565e-09\n",
+      "fitting image\n",
+      "measured charge:  3.244573297303279e-09\n",
+      "fitting image\n",
+      "measured charge:  4.821780792651717e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.076839566412719e-09\n",
+      "fitting image\n",
+      "measured charge:  4.768136104895357e-09\n",
+      "fitting image\n",
+      "measured charge:  4.255646786738512e-09\n",
+      "fitting image\n",
+      "measured charge:  4.057572292298872e-09\n",
+      "fitting image\n",
+      "measured charge:  3.391676062272226e-09\n",
+      "fitting image\n",
+      "measured charge:  4.205175786650389e-09\n",
+      "fitting image\n",
+      "measured charge:  4.704039141577184e-09\n",
+      "fitting image\n",
+      "measured charge:  4.259692247864019e-09\n",
+      "fitting image\n",
+      "measured charge:  4.262426446434162e-09\n",
+      "fitting image\n",
+      "measured charge:  4.246705705248296e-09\n",
+      "fitting image\n",
+      "measured charge:  3.166944032366269e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.066761937295577e-09\n",
+      "fitting image\n",
+      "measured charge:  4.693105949666332e-09\n",
+      "fitting image\n",
+      "measured charge:  4.272981389530893e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9472731369370495e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 19/49\n",
+      "quad4 | skewquad3\n",
+      " 0.168 | -0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  5.043286900529316e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  3.6294558750781325e-09\n",
+      "fitting image\n",
+      "measured charge:  4.800932078258331e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.2973424143406205e-09\n",
+      "fitting image\n",
+      "measured charge:  4.172948987693278e-09\n",
+      "fitting image\n",
+      "measured charge:  5.1287441147322284e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  4.499075115167531e-09\n",
+      "fitting image\n",
+      "measured charge:  5.327346356326735e-09\n",
+      "charge error 0.33 outside atol 0.2\n",
+      "measured charge:  4.578752327254768e-09\n",
+      "fitting image\n",
+      "measured charge:  4.103578155196401e-09\n",
+      "fitting image\n",
+      "measured charge:  3.396550068418994e-09\n",
+      "fitting image\n",
+      "measured charge:  4.018774771086311e-09\n",
+      "fitting image\n",
+      "measured charge:  5.282806657879776e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  4.864443656506958e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  5.113657390606172e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  4.613477369569363e-09\n",
+      "fitting image\n",
+      "measured charge:  4.149749727098137e-09\n",
+      "fitting image\n",
+      "measured charge:  4.194723511088717e-09\n",
+      "fitting image\n",
+      "measured charge:  4.274955488103313e-09\n",
+      "fitting image\n",
+      "measured charge:  5.054371391965877e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  5.3532167740229145e-09\n",
+      "charge error 0.34 outside atol 0.2\n",
+      "measured charge:  3.5292055298760753e-09\n",
+      "fitting image\n",
+      "measured charge:  5.028265019057079e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  3.400609939023128e-09\n",
+      "fitting image\n",
+      "measured charge:  4.19214781678359e-09\n",
+      "fitting image\n",
+      "measured charge:  3.498426883521396e-09\n",
+      "fitting image\n",
+      "measured charge:  4.149593024018041e-09\n",
+      "fitting image\n",
+      "measured charge:  4.769625684748753e-09\n",
+      "fitting image\n",
+      "measured charge:  4.991980150680621e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  5.169537348735149e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  3.6291208547000057e-09\n",
+      "fitting image\n",
+      "measured charge:  3.7909266914264934e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 20/49\n",
+      "quad4 | skewquad3\n",
+      " 0.336 | -0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.49982440805622e-09\n",
+      "fitting image\n",
+      "measured charge:  4.047665775740448e-09\n",
+      "fitting image\n",
+      "measured charge:  4.211072865779871e-09\n",
+      "fitting image\n",
+      "measured charge:  4.186286761350542e-09\n",
+      "fitting image\n",
+      "measured charge:  4.006438456193821e-09\n",
+      "fitting image\n",
+      "measured charge:  4.082037785828707e-09\n",
+      "fitting image\n",
+      "measured charge:  3.779649473213401e-09\n",
+      "fitting image\n",
+      "measured charge:  4.751676877929579e-09\n",
+      "fitting image\n",
+      "measured charge:  5.034652020459973e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  4.308619632553839e-09\n",
+      "fitting image\n",
+      "measured charge:  4.576787234606583e-09\n",
+      "fitting image\n",
+      "measured charge:  5.216496038407188e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.526586412242769e-09\n",
+      "fitting image\n",
+      "measured charge:  4.075357191298641e-09\n",
+      "fitting image\n",
+      "measured charge:  5.134091832488989e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  4.25220652371543e-09\n",
+      "fitting image\n",
+      "measured charge:  4.03170727815725e-09\n",
+      "fitting image\n",
+      "measured charge:  4.349742483380364e-09\n",
+      "fitting image\n",
+      "measured charge:  5.061723828436978e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  3.315069870318051e-09\n",
+      "fitting image\n",
+      "measured charge:  4.16167176948006e-09\n",
+      "fitting image\n",
+      "measured charge:  4.2676102563713955e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9188918675894734e-09\n",
+      "fitting image\n",
+      "measured charge:  3.1521941298031385e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  3.907659678996939e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 21/49\n",
+      "quad4 | skewquad3\n",
+      " 0.672 | -0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.797252257652994e-09\n",
+      "fitting image\n",
+      "measured charge:  3.834700886321124e-09\n",
+      "fitting image\n",
+      "measured charge:  4.560942211667467e-09\n",
+      "fitting image\n",
+      "measured charge:  4.8876086945903304e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.550891600322656e-09\n",
+      "fitting image\n",
+      "measured charge:  4.064865289670806e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6647699048317343e-09\n",
+      "fitting image\n",
+      "measured charge:  3.972599596814987e-09\n",
+      "fitting image\n",
+      "measured charge:  4.700883465757168e-09\n",
+      "fitting image\n",
+      "measured charge:  5.348555307685946e-09\n",
+      "charge error 0.34 outside atol 0.2\n",
+      "measured charge:  4.500892510659732e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6906637379307348e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6383483245779504e-09\n",
+      "fitting image\n",
+      "measured charge:  5.2182774102028244e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.776826821694277e-09\n",
+      "fitting image\n",
+      "measured charge:  4.68099838524706e-09\n",
+      "fitting image\n",
+      "measured charge:  3.121975651930208e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  5.120240721155466e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  4.582262836486185e-09\n",
+      "fitting image\n",
+      "measured charge:  3.878145464392028e-09\n",
+      "fitting image\n",
+      "measured charge:  4.081378552181364e-09\n",
+      "fitting image\n",
+      "measured charge:  4.942182793718462e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  5.736092831898491e-09\n",
+      "charge error 0.43 outside atol 0.2\n",
+      "measured charge:  4.00854043888908e-09\n",
+      "fitting image\n",
+      "measured charge:  4.027789701154579e-09\n",
+      "fitting image\n",
+      "measured charge:  4.601704825528345e-09\n",
+      "fitting image\n",
+      "measured charge:  3.0627995255644044e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.318895392002146e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 22/49\n",
+      "quad4 | skewquad3\n",
+      " -0.672 | 0\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.948737305310488e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  4.5965048049275644e-09\n",
+      "fitting image\n",
+      "measured charge:  4.318473914752269e-09\n",
+      "fitting image\n",
+      "measured charge:  4.325565179423309e-09\n",
+      "fitting image\n",
+      "measured charge:  3.739070580205081e-09\n",
+      "fitting image\n",
+      "measured charge:  4.059890417173653e-09\n",
+      "fitting image\n",
+      "measured charge:  4.30099161480378e-09\n",
+      "fitting image\n",
+      "measured charge:  4.500564695020928e-09\n",
+      "fitting image\n",
+      "measured charge:  4.465394760053588e-09\n",
+      "fitting image\n",
+      "measured charge:  4.7271969749212485e-09\n",
+      "fitting image\n",
+      "measured charge:  4.704040942762115e-09\n",
+      "fitting image\n",
+      "measured charge:  4.55470470860535e-09\n",
+      "fitting image\n",
+      "measured charge:  3.318241756801627e-09\n",
+      "fitting image\n",
+      "measured charge:  3.61733750354983e-09\n",
+      "fitting image\n",
+      "measured charge:  4.66186439881057e-09\n",
+      "fitting image\n",
+      "measured charge:  4.903990470608334e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.597700791653917e-09\n",
+      "fitting image\n",
+      "measured charge:  5.5341583983707166e-09\n",
+      "charge error 0.38 outside atol 0.2\n",
+      "measured charge:  4.226633301515927e-09\n",
+      "fitting image\n",
+      "measured charge:  5.155479101146385e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  4.890432952401958e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  3.9602002404533494e-09\n",
+      "fitting image\n",
+      "measured charge:  4.806899403596146e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.102079569418898e-09\n",
+      "fitting image\n",
+      "measured charge:  4.801524668066927e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.798956178501115e-09\n",
+      "fitting image\n",
+      "measured charge:  4.508711454001653e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 23/49\n",
+      "quad4 | skewquad3\n",
+      " -0.336 | 0\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  3.973006664586241e-09\n",
+      "fitting image\n",
+      "measured charge:  4.467700276634412e-09\n",
+      "fitting image\n",
+      "measured charge:  4.536139896574721e-09\n",
+      "fitting image\n",
+      "measured charge:  4.033524673649452e-09\n",
+      "fitting image\n",
+      "measured charge:  5.5802849406517416e-09\n",
+      "charge error 0.4 outside atol 0.2\n",
+      "measured charge:  4.80901219340031e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  5.5046297742871814e-09\n",
+      "charge error 0.38 outside atol 0.2\n",
+      "measured charge:  4.2152966442034064e-09\n",
+      "fitting image\n",
+      "measured charge:  4.920968438804782e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  3.841612032509335e-09\n",
+      "fitting image\n",
+      "measured charge:  4.6961733674298024e-09\n",
+      "fitting image\n",
+      "measured charge:  4.5955375686744255e-09\n",
+      "fitting image\n",
+      "measured charge:  5.553623802815804e-09\n",
+      "charge error 0.39 outside atol 0.2\n",
+      "measured charge:  4.772586832607324e-09\n",
+      "fitting image\n",
+      "measured charge:  4.237921326838173e-09\n",
+      "fitting image\n",
+      "measured charge:  4.901187827014782e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.747735885524174e-09\n",
+      "fitting image\n",
+      "measured charge:  3.7948929004195535e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6405205534815415e-09\n",
+      "fitting image\n",
+      "measured charge:  4.791724421413404e-09\n",
+      "fitting image\n",
+      "measured charge:  3.425977826152148e-09\n",
+      "fitting image\n",
+      "measured charge:  5.4292790081586674e-09\n",
+      "charge error 0.36 outside atol 0.2\n",
+      "measured charge:  3.754137491298121e-09\n",
+      "fitting image\n",
+      "measured charge:  5.073847603519802e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.264548242162439e-09\n",
+      "fitting image\n",
+      "measured charge:  4.900515985073612e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.98347675710384e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  6.215090919348436e-09\n",
+      "charge error 0.55 outside atol 0.2\n",
+      "measured charge:  4.43420544355781e-09\n",
+      "fitting image\n",
+      "measured charge:  4.889671051219305e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.50232085022903e-09\n",
+      "fitting image\n",
+      "measured charge:  4.211665455588594e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 24/49\n",
+      "quad4 | skewquad3\n",
+      " -0.168 | 0\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  3.900597233283152e-09\n",
+      "fitting image\n",
+      "measured charge:  6.153710142752195e-09\n",
+      "charge error 0.54 outside atol 0.2\n",
+      "measured charge:  3.977534843245852e-09\n",
+      "fitting image\n",
+      "measured charge:  4.2533412701575574e-09\n",
+      "fitting image\n",
+      "measured charge:  4.961059210724485e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  4.8216673180075035e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  3.5104245756661713e-09\n",
+      "fitting image\n",
+      "measured charge:  3.4543843120872594e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6656560877674967e-09\n",
+      "fitting image\n",
+      "measured charge:  3.8654957433393525e-09\n",
+      "fitting image\n",
+      "measured charge:  4.124536741864411e-09\n",
+      "fitting image\n",
+      "measured charge:  4.019089978431418e-09\n",
+      "fitting image\n",
+      "measured charge:  4.60551613262611e-09\n",
+      "fitting image\n",
+      "measured charge:  4.493188843146955e-09\n",
+      "fitting image\n",
+      "measured charge:  4.697702573349484e-09\n",
+      "fitting image\n",
+      "measured charge:  3.90802892188683e-09\n",
+      "fitting image\n",
+      "measured charge:  4.502189363736471e-09\n",
+      "fitting image\n",
+      "measured charge:  4.157509231340748e-09\n",
+      "fitting image\n",
+      "measured charge:  3.761588992934819e-09\n",
+      "fitting image\n",
+      "measured charge:  4.695751890179925e-09\n",
+      "fitting image\n",
+      "measured charge:  5.014793957722324e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  4.760805282642064e-09\n",
+      "fitting image\n",
+      "measured charge:  4.0552307520214835e-09\n",
+      "fitting image\n",
+      "measured charge:  4.557799144141147e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 25/49\n",
+      "quad4 | skewquad3\n",
+      " 0 | 0\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.287115286882575e-09\n",
+      "fitting image\n",
+      "measured charge:  3.898630339450169e-09\n",
+      "fitting image\n",
+      "measured charge:  4.23908669342235e-09\n",
+      "fitting image\n",
+      "measured charge:  5.38832907107575e-09\n",
+      "charge error 0.35 outside atol 0.2\n",
+      "measured charge:  4.118146138091794e-09\n",
+      "fitting image\n",
+      "measured charge:  4.002522680375946e-09\n",
+      "fitting image\n",
+      "measured charge:  5.008767193285209e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  5.1742654589107965e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  5.022191423814231e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  5.025696529491129e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  3.7207615364202524e-09\n",
+      "fitting image\n",
+      "measured charge:  3.95546132316873e-09\n",
+      "fitting image\n",
+      "measured charge:  3.826476676392757e-09\n",
+      "fitting image\n",
+      "measured charge:  4.7197796957961965e-09\n",
+      "fitting image\n",
+      "measured charge:  4.130763437817626e-09\n",
+      "fitting image\n",
+      "measured charge:  4.69012138640503e-09\n",
+      "fitting image\n",
+      "measured charge:  4.145207138959894e-09\n",
+      "fitting image\n",
+      "measured charge:  4.287151310579268e-09\n",
+      "fitting image\n",
+      "measured charge:  3.560045416515095e-09\n",
+      "fitting image\n",
+      "measured charge:  4.398255595559613e-09\n",
+      "fitting image\n",
+      "measured charge:  3.821055110058065e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6830231118869755e-09\n",
+      "fitting image\n",
+      "measured charge:  5.1778372084263734e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  4.648575257143699e-09\n",
+      "fitting image\n",
+      "measured charge:  3.1336995639809624e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  3.871164071995609e-09\n",
+      "fitting image\n",
+      "measured charge:  5.137368187692669e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  4.042377497083114e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 26/49\n",
+      "quad4 | skewquad3\n",
+      " 0.168 | 0\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.013756670153285e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6470336378224876e-09\n",
+      "fitting image\n",
+      "measured charge:  5.053025906898747e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  4.578058871095659e-09\n",
+      "fitting image\n",
+      "measured charge:  4.088592297420727e-09\n",
+      "fitting image\n",
+      "measured charge:  4.5535933775659585e-09\n",
+      "fitting image\n",
+      "measured charge:  4.3476765243817935e-09\n",
+      "fitting image\n",
+      "measured charge:  4.335914787449549e-09\n",
+      "fitting image\n",
+      "measured charge:  4.061902340627435e-09\n",
+      "fitting image\n",
+      "measured charge:  4.289892713888595e-09\n",
+      "fitting image\n",
+      "measured charge:  3.600701760470942e-09\n",
+      "fitting image\n",
+      "measured charge:  4.425410258038787e-09\n",
+      "fitting image\n",
+      "measured charge:  3.376927960893886e-09\n",
+      "fitting image\n",
+      "measured charge:  4.337319711616114e-09\n",
+      "fitting image\n",
+      "measured charge:  4.866390737306923e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  5.044164077540974e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  4.596890258480873e-09\n",
+      "fitting image\n",
+      "measured charge:  4.7095399600444495e-09\n",
+      "fitting image\n",
+      "measured charge:  4.754391263466578e-09\n",
+      "fitting image\n",
+      "measured charge:  4.602727898511053e-09\n",
+      "fitting image\n",
+      "measured charge:  3.98777097662801e-09\n",
+      "fitting image\n",
+      "measured charge:  3.794491236202817e-09\n",
+      "fitting image\n",
+      "measured charge:  4.61972748092544e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 27/49\n",
+      "quad4 | skewquad3\n",
+      " 0.336 | 0\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.847472893049955e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.719426663569726e-09\n",
+      "fitting image\n",
+      "measured charge:  4.377842767894726e-09\n",
+      "fitting image\n",
+      "measured charge:  4.142400892996621e-09\n",
+      "fitting image\n",
+      "measured charge:  5.089678216980159e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.79605086737225e-09\n",
+      "fitting image\n",
+      "measured charge:  4.9432923235730656e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  4.558460178973414e-09\n",
+      "fitting image\n",
+      "measured charge:  5.161280717479872e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  4.7305003478972505e-09\n",
+      "fitting image\n",
+      "measured charge:  3.856563667773244e-09\n",
+      "fitting image\n",
+      "measured charge:  4.937393443258655e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.806967848619685e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.32357126781774e-09\n",
+      "fitting image\n",
+      "measured charge:  4.704366957216128e-09\n",
+      "fitting image\n",
+      "measured charge:  5.25348156768193e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  4.610112756309261e-09\n",
+      "fitting image\n",
+      "measured charge:  3.977408760307813e-09\n",
+      "fitting image\n",
+      "measured charge:  4.171338728456355e-09\n",
+      "fitting image\n",
+      "measured charge:  4.0970236436043804e-09\n",
+      "fitting image\n",
+      "measured charge:  4.589123549499077e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9332473106750675e-09\n",
+      "fitting image\n",
+      "measured charge:  3.987324282790471e-09\n",
+      "fitting image\n",
+      "measured charge:  4.211535770280836e-09\n",
+      "fitting image\n",
+      "measured charge:  4.075811089875492e-09\n",
+      "fitting image\n",
+      "measured charge:  5.072449884092553e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.8315107930970374e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.0713693680876375e-09\n",
+      "fitting image\n",
+      "measured charge:  3.966052289962155e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 28/49\n",
+      "quad4 | skewquad3\n",
+      " 0.672 | 0\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  3.942247831264585e-09\n",
+      "fitting image\n",
+      "measured charge:  4.1544616266102955e-09\n",
+      "fitting image\n",
+      "measured charge:  4.828706348318556e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  3.349110462397777e-09\n",
+      "fitting image\n",
+      "measured charge:  4.983633460183929e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  3.964991392098075e-09\n",
+      "fitting image\n",
+      "measured charge:  4.182470050698389e-09\n",
+      "fitting image\n",
+      "measured charge:  3.764465485106428e-09\n",
+      "fitting image\n",
+      "measured charge:  5.423452175237576e-09\n",
+      "charge error 0.36 outside atol 0.2\n",
+      "measured charge:  4.955952851734775e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  4.137541296328479e-09\n",
+      "fitting image\n",
+      "measured charge:  5.106025770486522e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  5.973051304422426e-09\n",
+      "charge error 0.49 outside atol 0.2\n",
+      "measured charge:  6.330741394836744e-09\n",
+      "charge error 0.58 outside atol 0.2\n",
+      "measured charge:  4.202992750637889e-09\n",
+      "fitting image\n",
+      "measured charge:  4.860862901067338e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  5.9026033633979495e-09\n",
+      "charge error 0.48 outside atol 0.2\n",
+      "measured charge:  4.268968349732357e-09\n",
+      "fitting image\n",
+      "measured charge:  4.455243282358391e-09\n",
+      "fitting image\n",
+      "measured charge:  4.827427507090168e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.969737319229708e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  4.178357945734136e-09\n",
+      "fitting image\n",
+      "measured charge:  4.894626110683444e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  5.20645083061684e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.631863864301962e-09\n",
+      "fitting image\n",
+      "measured charge:  3.433589633238657e-09\n",
+      "fitting image\n",
+      "measured charge:  3.489707347765097e-09\n",
+      "fitting image\n",
+      "measured charge:  5.125105721378082e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  3.6180129478607092e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9737217349632895e-09\n",
+      "fitting image\n",
+      "measured charge:  3.805903543278063e-09\n",
+      "fitting image\n",
+      "measured charge:  4.618870116946928e-09\n",
+      "fitting image\n",
+      "measured charge:  4.966505993646703e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  5.5650090921187175e-09\n",
+      "charge error 0.39 outside atol 0.2\n",
+      "measured charge:  5.354936905534413e-09\n",
+      "charge error 0.34 outside atol 0.2\n",
+      "measured charge:  4.658139548584687e-09\n",
+      "fitting image\n",
+      "measured charge:  4.683484020310843e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 29/49\n",
+      "quad4 | skewquad3\n",
+      " -0.672 | 0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.1759191414759546e-09\n",
+      "fitting image\n",
+      "measured charge:  3.779255013735855e-09\n",
+      "fitting image\n",
+      "measured charge:  4.0223411170474355e-09\n",
+      "fitting image\n",
+      "measured charge:  4.639655789871423e-09\n",
+      "fitting image\n",
+      "measured charge:  3.721818831914739e-09\n",
+      "fitting image\n",
+      "measured charge:  4.7039706965537795e-09\n",
+      "fitting image\n",
+      "measured charge:  4.882473516643371e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  3.970771394213625e-09\n",
+      "fitting image\n",
+      "measured charge:  5.062249774407092e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.266079249266915e-09\n",
+      "fitting image\n",
+      "measured charge:  5.90958115342467e-09\n",
+      "charge error 0.48 outside atol 0.2\n",
+      "measured charge:  4.76681763760055e-09\n",
+      "fitting image\n",
+      "measured charge:  4.219316888741385e-09\n",
+      "fitting image\n",
+      "measured charge:  4.534209026438302e-09\n",
+      "fitting image\n",
+      "measured charge:  3.917528370673992e-09\n",
+      "fitting image\n",
+      "measured charge:  3.7900945440356406e-09\n",
+      "fitting image\n",
+      "measured charge:  3.851246570158657e-09\n",
+      "fitting image\n",
+      "measured charge:  4.905285522500272e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.728400166386919e-09\n",
+      "fitting image\n",
+      "measured charge:  4.12050929258725e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6092880085498904e-09\n",
+      "fitting image\n",
+      "measured charge:  4.9042948708444065e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  5.0095795276429176e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  3.950329747591487e-09\n",
+      "fitting image\n",
+      "measured charge:  5.640664258483111e-09\n",
+      "charge error 0.41 outside atol 0.2\n",
+      "measured charge:  3.935943684363847e-09\n",
+      "fitting image\n",
+      "measured charge:  4.365111993524683e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 30/49\n",
+      "quad4 | skewquad3\n",
+      " -0.336 | 0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  3.757122054559432e-09\n",
+      "fitting image\n",
+      "measured charge:  5.220093004510232e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  4.913525943092069e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.186018384811162e-09\n",
+      "fitting image\n",
+      "measured charge:  4.363552167462956e-09\n",
+      "fitting image\n",
+      "measured charge:  5.139234215175301e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  5.2118327708852924e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.8844151938888195e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.214466297997354e-09\n",
+      "fitting image\n",
+      "measured charge:  5.810537602057999e-09\n",
+      "charge error 0.45 outside atol 0.2\n",
+      "measured charge:  4.9011391950243854e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  5.4468135424671425e-09\n",
+      "charge error 0.36 outside atol 0.2\n",
+      "measured charge:  4.594563127682111e-09\n",
+      "fitting image\n",
+      "measured charge:  4.546642605311586e-09\n",
+      "fitting image\n",
+      "measured charge:  5.464852408527755e-09\n",
+      "charge error 0.37 outside atol 0.2\n",
+      "measured charge:  4.678258783122401e-09\n",
+      "fitting image\n",
+      "measured charge:  3.798271923158411e-09\n",
+      "fitting image\n",
+      "measured charge:  5.8387711742495905e-09\n",
+      "charge error 0.46 outside atol 0.2\n",
+      "measured charge:  4.225111300335686e-09\n",
+      "fitting image\n",
+      "measured charge:  4.254544461623227e-09\n",
+      "fitting image\n",
+      "measured charge:  5.145399670844256e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  4.65286928177557e-09\n",
+      "fitting image\n",
+      "measured charge:  3.8037277120048744e-09\n",
+      "fitting image\n",
+      "measured charge:  4.660178489810798e-09\n",
+      "fitting image\n",
+      "measured charge:  3.947656789305571e-09\n",
+      "fitting image\n",
+      "measured charge:  5.221492525122201e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  5.0488867841621686e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  3.5099850865678246e-09\n",
+      "fitting image\n",
+      "measured charge:  4.109253688591977e-09\n",
+      "fitting image\n",
+      "measured charge:  4.166000016623704e-09\n",
+      "fitting image\n",
+      "measured charge:  5.2479933575084975e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  4.161421404788904e-09\n",
+      "fitting image\n",
+      "measured charge:  4.636991837509615e-09\n",
+      "fitting image\n",
+      "measured charge:  4.565396541749157e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 31/49\n",
+      "quad4 | skewquad3\n",
+      " -0.168 | 0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  5.026409798683384e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  5.082369008944937e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  5.48460780373013e-09\n",
+      "charge error 0.37 outside atol 0.2\n",
+      "measured charge:  4.958065641538939e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  4.5498415095674854e-09\n",
+      "fitting image\n",
+      "measured charge:  5.741002861741719e-09\n",
+      "charge error 0.44 outside atol 0.2\n",
+      "measured charge:  4.801168033470866e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.051116845872433e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6145330587713513e-09\n",
+      "fitting image\n",
+      "measured charge:  4.864461668355308e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.078701991525727e-09\n",
+      "fitting image\n",
+      "measured charge:  5.3827273862581925e-09\n",
+      "charge error 0.35 outside atol 0.2\n",
+      "measured charge:  4.559295928733988e-09\n",
+      "fitting image\n",
+      "measured charge:  4.378629885664903e-09\n",
+      "fitting image\n",
+      "measured charge:  5.2665581695391326e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  5.136096551203461e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  4.762352500409959e-09\n",
+      "fitting image\n",
+      "measured charge:  3.950643153751673e-09\n",
+      "fitting image\n",
+      "measured charge:  5.034322403636371e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  4.557510954568629e-09\n",
+      "fitting image\n",
+      "measured charge:  4.302659511955335e-09\n",
+      "fitting image\n",
+      "measured charge:  4.226170397014964e-09\n",
+      "fitting image\n",
+      "measured charge:  4.648391536291151e-09\n",
+      "fitting image\n",
+      "measured charge:  4.228601996533834e-09\n",
+      "fitting image\n",
+      "measured charge:  4.541556059355024e-09\n",
+      "fitting image\n",
+      "measured charge:  4.575618265652684e-09\n",
+      "fitting image\n",
+      "measured charge:  4.260832397860666e-09\n",
+      "fitting image\n",
+      "measured charge:  4.217760665049249e-09\n",
+      "fitting image\n",
+      "measured charge:  4.857024576197109e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  3.826662198430098e-09\n",
+      "fitting image\n",
+      "measured charge:  4.821242238387905e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.2512050649506555e-09\n",
+      "fitting image\n",
+      "measured charge:  4.3308498557110495e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 32/49\n",
+      "quad4 | skewquad3\n",
+      " 0 | 0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.663136035299779e-09\n",
+      "fitting image\n",
+      "measured charge:  5.085313946139951e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  3.488745515066601e-09\n",
+      "fitting image\n",
+      "measured charge:  4.731089335336258e-09\n",
+      "fitting image\n",
+      "measured charge:  5.221063843132957e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  4.088059146711428e-09\n",
+      "fitting image\n",
+      "measured charge:  4.18273302368338e-09\n",
+      "fitting image\n",
+      "measured charge:  4.885636397202833e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.278887474584608e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6971480033145437e-09\n",
+      "fitting image\n",
+      "measured charge:  4.119806830504034e-09\n",
+      "fitting image\n",
+      "measured charge:  4.002398398622827e-09\n",
+      "fitting image\n",
+      "measured charge:  4.145354836115879e-09\n",
+      "fitting image\n",
+      "measured charge:  4.320817256214455e-09\n",
+      "fitting image\n",
+      "measured charge:  3.7630209348738324e-09\n",
+      "fitting image\n",
+      "measured charge:  4.887451991510241e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.5042265037779146e-09\n",
+      "fitting image\n",
+      "measured charge:  5.2787629979391095e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  4.85184977218399e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  3.977378140165761e-09\n",
+      "fitting image\n",
+      "measured charge:  5.0669202466681705e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.357010264164632e-09\n",
+      "fitting image\n",
+      "measured charge:  5.663600546093234e-09\n",
+      "charge error 0.42 outside atol 0.2\n",
+      "measured charge:  4.7121570816006576e-09\n",
+      "fitting image\n",
+      "measured charge:  5.624165405451274e-09\n",
+      "charge error 0.41 outside atol 0.2\n",
+      "measured charge:  3.95638713217078e-09\n",
+      "fitting image\n",
+      "measured charge:  4.190069249491062e-09\n",
+      "fitting image\n",
+      "measured charge:  4.339583800945855e-09\n",
+      "fitting image\n",
+      "measured charge:  4.0608666593507685e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 33/49\n",
+      "quad4 | skewquad3\n",
+      " 0.168 | 0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.043820246130913e-09\n",
+      "fitting image\n",
+      "measured charge:  4.4237837881383104e-09\n",
+      "fitting image\n",
+      "measured charge:  3.8874557887721325e-09\n",
+      "fitting image\n",
+      "measured charge:  4.3144230500722474e-09\n",
+      "fitting image\n",
+      "measured charge:  4.111465543561727e-09\n",
+      "fitting image\n",
+      "measured charge:  4.4046948313226265e-09\n",
+      "fitting image\n",
+      "measured charge:  4.777322147522213e-09\n",
+      "fitting image\n",
+      "measured charge:  4.0383104217396656e-09\n",
+      "fitting image\n",
+      "measured charge:  4.5851411298425925e-09\n",
+      "fitting image\n",
+      "measured charge:  4.649093998374372e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9827943029460614e-09\n",
+      "fitting image\n",
+      "measured charge:  5.204303818300955e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  5.049374905250656e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  5.199175845093238e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  5.523608858828378e-09\n",
+      "charge error 0.38 outside atol 0.2\n",
+      "measured charge:  5.4978519157763234e-09\n",
+      "charge error 0.37 outside atol 0.2\n",
+      "measured charge:  3.726296577399158e-09\n",
+      "fitting image\n",
+      "measured charge:  4.776702539941163e-09\n",
+      "fitting image\n",
+      "measured charge:  3.521858496959358e-09\n",
+      "fitting image\n",
+      "measured charge:  3.7727779530914755e-09\n",
+      "fitting image\n",
+      "measured charge:  4.733627204760153e-09\n",
+      "fitting image\n",
+      "measured charge:  4.507843282914102e-09\n",
+      "fitting image\n",
+      "measured charge:  5.29820858935103e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  5.394687253521478e-09\n",
+      "charge error 0.35 outside atol 0.2\n",
+      "measured charge:  3.660724443706225e-09\n",
+      "fitting image\n",
+      "measured charge:  3.839119192706248e-09\n",
+      "fitting image\n",
+      "measured charge:  4.7188827057514e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 34/49\n",
+      "quad4 | skewquad3\n",
+      " 0.336 | 0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.077025088450061e-09\n",
+      "fitting image\n",
+      "measured charge:  4.285179013191639e-09\n",
+      "fitting image\n",
+      "measured charge:  4.656550903565578e-09\n",
+      "fitting image\n",
+      "measured charge:  4.319754557165457e-09\n",
+      "fitting image\n",
+      "measured charge:  4.7004133565167614e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9815334735658875e-09\n",
+      "fitting image\n",
+      "measured charge:  2.8973120670477772e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  4.358053150180491e-09\n",
+      "fitting image\n",
+      "measured charge:  4.612068843033337e-09\n",
+      "fitting image\n",
+      "measured charge:  3.1333555376786003e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.1501495901302e-09\n",
+      "fitting image\n",
+      "measured charge:  5.716135703995152e-09\n",
+      "charge error 0.43 outside atol 0.2\n",
+      "measured charge:  4.789460332083534e-09\n",
+      "fitting image\n",
+      "measured charge:  4.654306627268979e-09\n",
+      "fitting image\n",
+      "measured charge:  4.838355295446505e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  5.2375482866863405e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  4.72810477207495e-09\n",
+      "fitting image\n",
+      "measured charge:  4.071617931594e-09\n",
+      "fitting image\n",
+      "measured charge:  4.624046722144845e-09\n",
+      "fitting image\n",
+      "measured charge:  3.916546724942363e-09\n",
+      "fitting image\n",
+      "measured charge:  4.4878231135418475e-09\n",
+      "fitting image\n",
+      "measured charge:  4.086454291028898e-09\n",
+      "fitting image\n",
+      "measured charge:  4.0608522498721435e-09\n",
+      "fitting image\n",
+      "measured charge:  3.889721679286801e-09\n",
+      "fitting image\n",
+      "measured charge:  3.960036332633938e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 35/49\n",
+      "quad4 | skewquad3\n",
+      " 0.672 | 0.191\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  3.992727837276939e-09\n",
+      "fitting image\n",
+      "measured charge:  3.749580493681137e-09\n",
+      "fitting image\n",
+      "measured charge:  3.644211181195786e-09\n",
+      "fitting image\n",
+      "measured charge:  3.828589466197048e-09\n",
+      "fitting image\n",
+      "measured charge:  4.720918044608047e-09\n",
+      "fitting image\n",
+      "measured charge:  4.622674219305384e-09\n",
+      "fitting image\n",
+      "measured charge:  5.2575918714612535e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  4.983516383169993e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  4.0972974236984035e-09\n",
+      "fitting image\n",
+      "measured charge:  4.079710655029815e-09\n",
+      "fitting image\n",
+      "measured charge:  5.218574605699507e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  3.730441103690253e-09\n",
+      "fitting image\n",
+      "measured charge:  4.429848377456916e-09\n",
+      "fitting image\n",
+      "measured charge:  5.21272255619078e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.260245211606457e-09\n",
+      "fitting image\n",
+      "measured charge:  4.506876046661098e-09\n",
+      "fitting image\n",
+      "measured charge:  5.383889150472686e-09\n",
+      "charge error 0.35 outside atol 0.2\n",
+      "measured charge:  5.161469841886965e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  4.910838575327523e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  3.897854028788893e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6528874885160863e-09\n",
+      "fitting image\n",
+      "measured charge:  5.275074171409748e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  3.8437464365314455e-09\n",
+      "fitting image\n",
+      "measured charge:  3.754207737506458e-09\n",
+      "fitting image\n",
+      "measured charge:  4.3685342446994164e-09\n",
+      "fitting image\n",
+      "measured charge:  4.3147850882228235e-09\n",
+      "fitting image\n",
+      "measured charge:  5.432836348195646e-09\n",
+      "charge error 0.36 outside atol 0.2\n",
+      "measured charge:  5.295748170874824e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  4.253416919920413e-09\n",
+      "fitting image\n",
+      "measured charge:  3.953114379336822e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 36/49\n",
+      "quad4 | skewquad3\n",
+      " -0.672 | 0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.002738822555465e-09\n",
+      "fitting image\n",
+      "measured charge:  4.30587462687466e-09\n",
+      "fitting image\n",
+      "measured charge:  5.192922131367634e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  5.5470314663422245e-09\n",
+      "charge error 0.39 outside atol 0.2\n",
+      "measured charge:  4.683617307988195e-09\n",
+      "fitting image\n",
+      "measured charge:  4.707886472371523e-09\n",
+      "fitting image\n",
+      "measured charge:  5.076205354460746e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  5.507356768118111e-09\n",
+      "charge error 0.38 outside atol 0.2\n",
+      "measured charge:  5.025465977833114e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  4.085769840794029e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6190378220282284e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6728157974620697e-09\n",
+      "fitting image\n",
+      "measured charge:  4.489121767803509e-09\n",
+      "fitting image\n",
+      "measured charge:  4.823255963026614e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.294561384964878e-09\n",
+      "fitting image\n",
+      "measured charge:  5.494458483558939e-09\n",
+      "charge error 0.37 outside atol 0.2\n",
+      "measured charge:  4.903648245490897e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.56744989245402e-09\n",
+      "fitting image\n",
+      "measured charge:  4.564892209997111e-09\n",
+      "fitting image\n",
+      "measured charge:  4.614860679517984e-09\n",
+      "fitting image\n",
+      "measured charge:  3.475717545199794e-09\n",
+      "fitting image\n",
+      "measured charge:  3.872284408959111e-09\n",
+      "fitting image\n",
+      "measured charge:  4.9815458869672925e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  5.9384919711119244e-09\n",
+      "charge error 0.48 outside atol 0.2\n",
+      "measured charge:  4.278685741883842e-09\n",
+      "fitting image\n",
+      "measured charge:  6.382851473119054e-09\n",
+      "charge error 0.6 outside atol 0.2\n",
+      "measured charge:  4.761889595909001e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6920812703909988e-09\n",
+      "fitting image\n",
+      "measured charge:  4.2923045003744505e-09\n",
+      "fitting image\n",
+      "measured charge:  4.989629604478995e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  5.242575393543532e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  4.739353171330918e-09\n",
+      "fitting image\n",
+      "measured charge:  4.3033619740385495e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 37/49\n",
+      "quad4 | skewquad3\n",
+      " -0.336 | 0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  5.163787966761594e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  4.397083024235992e-09\n",
+      "fitting image\n",
+      "measured charge:  3.475584257522445e-09\n",
+      "fitting image\n",
+      "measured charge:  3.1987781730307508e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  3.906015197248245e-09\n",
+      "fitting image\n",
+      "measured charge:  4.526750320062172e-09\n",
+      "fitting image\n",
+      "measured charge:  4.680267104206595e-09\n",
+      "fitting image\n",
+      "measured charge:  4.529462904414377e-09\n",
+      "fitting image\n",
+      "measured charge:  4.1432168297240495e-09\n",
+      "fitting image\n",
+      "measured charge:  4.5269736669808745e-09\n",
+      "fitting image\n",
+      "measured charge:  5.3135492805380126e-09\n",
+      "charge error 0.33 outside atol 0.2\n",
+      "measured charge:  4.570621778937467e-09\n",
+      "fitting image\n",
+      "measured charge:  4.228715471178046e-09\n",
+      "fitting image\n",
+      "measured charge:  4.686475788311457e-09\n",
+      "fitting image\n",
+      "measured charge:  6.017783729645846e-09\n",
+      "charge error 0.5 outside atol 0.2\n",
+      "measured charge:  3.84815573699233e-09\n",
+      "fitting image\n",
+      "measured charge:  5.486581902302615e-09\n",
+      "charge error 0.37 outside atol 0.2\n",
+      "measured charge:  3.893878813871721e-09\n",
+      "fitting image\n",
+      "measured charge:  3.756563687262473e-09\n",
+      "fitting image\n",
+      "measured charge:  4.008250448131632e-09\n",
+      "fitting image\n",
+      "measured charge:  4.6460193758715885e-09\n",
+      "fitting image\n",
+      "measured charge:  3.940999610178238e-09\n",
+      "fitting image\n",
+      "measured charge:  5.374904840546596e-09\n",
+      "charge error 0.34 outside atol 0.2\n",
+      "measured charge:  5.4856344790826235e-09\n",
+      "charge error 0.37 outside atol 0.2\n",
+      "measured charge:  5.104302036605261e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  4.59125795352118e-09\n",
+      "fitting image\n",
+      "measured charge:  4.753207885034054e-09\n",
+      "fitting image\n",
+      "measured charge:  4.186769478884774e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 38/49\n",
+      "quad4 | skewquad3\n",
+      " -0.168 | 0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.018745952129059e-09\n",
+      "fitting image\n",
+      "measured charge:  4.209781416257654e-09\n",
+      "fitting image\n",
+      "measured charge:  4.793990311928073e-09\n",
+      "fitting image\n",
+      "measured charge:  3.755279442479569e-09\n",
+      "fitting image\n",
+      "measured charge:  4.568898045056332e-09\n",
+      "fitting image\n",
+      "measured charge:  4.101953486480857e-09\n",
+      "fitting image\n",
+      "measured charge:  4.7021280844739175e-09\n",
+      "fitting image\n",
+      "measured charge:  5.11088176478494e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  4.4295493807753615e-09\n",
+      "fitting image\n",
+      "measured charge:  3.918711749106525e-09\n",
+      "fitting image\n",
+      "measured charge:  4.258616940521194e-09\n",
+      "fitting image\n",
+      "measured charge:  4.360275812259277e-09\n",
+      "fitting image\n",
+      "measured charge:  4.726770094116852e-09\n",
+      "fitting image\n",
+      "measured charge:  3.963404548263889e-09\n",
+      "fitting image\n",
+      "measured charge:  5.62582429667869e-09\n",
+      "charge error 0.41 outside atol 0.2\n",
+      "measured charge:  4.1486690162009204e-09\n",
+      "fitting image\n",
+      "measured charge:  4.8795772114386156e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.331208291491905e-09\n",
+      "fitting image\n",
+      "measured charge:  4.201312245192508e-09\n",
+      "fitting image\n",
+      "measured charge:  4.660529720852472e-09\n",
+      "fitting image\n",
+      "measured charge:  4.643177106211745e-09\n",
+      "fitting image\n",
+      "measured charge:  3.8249492716579946e-09\n",
+      "fitting image\n",
+      "measured charge:  5.1362532542835806e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  4.765697300637048e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 39/49\n",
+      "quad4 | skewquad3\n",
+      " 0 | 0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.451042919337592e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9641538411525814e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9973947071683e-09\n",
+      "fitting image\n",
+      "measured charge:  4.250338695047909e-09\n",
+      "fitting image\n",
+      "measured charge:  5.502979888984074e-09\n",
+      "charge error 0.38 outside atol 0.2\n",
+      "measured charge:  4.621908715753146e-09\n",
+      "fitting image\n",
+      "measured charge:  4.39541692826936e-09\n",
+      "fitting image\n",
+      "measured charge:  4.148054812174253e-09\n",
+      "fitting image\n",
+      "measured charge:  4.6271249470173505e-09\n",
+      "fitting image\n",
+      "measured charge:  4.257898267774424e-09\n",
+      "fitting image\n",
+      "measured charge:  4.598804917953868e-09\n",
+      "fitting image\n",
+      "measured charge:  5.0610483841262174e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.790650915255503e-09\n",
+      "fitting image\n",
+      "measured charge:  4.0146482566435626e-09\n",
+      "fitting image\n",
+      "measured charge:  4.244906321604313e-09\n",
+      "fitting image\n",
+      "measured charge:  4.815777443617337e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.456205115056879e-09\n",
+      "fitting image\n",
+      "measured charge:  5.1810469197912485e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.57072985002729e-09\n",
+      "fitting image\n",
+      "measured charge:  3.987688122125848e-09\n",
+      "fitting image\n",
+      "measured charge:  3.31210331890497e-09\n",
+      "fitting image\n",
+      "measured charge:  5.396852277685584e-09\n",
+      "charge error 0.35 outside atol 0.2\n",
+      "measured charge:  4.236610064282809e-09\n",
+      "fitting image\n",
+      "measured charge:  3.757006778730418e-09\n",
+      "fitting image\n",
+      "measured charge:  4.777948959842709e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 40/49\n",
+      "quad4 | skewquad3\n",
+      " 0.168 | 0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  5.479398777205303e-09\n",
+      "charge error 0.37 outside atol 0.2\n",
+      "measured charge:  5.743079627849322e-09\n",
+      "charge error 0.44 outside atol 0.2\n",
+      "measured charge:  5.252336014130769e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  4.630381489187752e-09\n",
+      "fitting image\n",
+      "measured charge:  4.940111431165383e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  4.3157144995944635e-09\n",
+      "fitting image\n",
+      "measured charge:  5.357708928985964e-09\n",
+      "charge error 0.34 outside atol 0.2\n",
+      "measured charge:  4.376376603444067e-09\n",
+      "fitting image\n",
+      "measured charge:  4.561988700053048e-09\n",
+      "fitting image\n",
+      "measured charge:  4.663498073450356e-09\n",
+      "fitting image\n",
+      "measured charge:  4.894395559025296e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.737117900958299e-09\n",
+      "fitting image\n",
+      "measured charge:  3.834643248406621e-09\n",
+      "fitting image\n",
+      "measured charge:  4.329522382492133e-09\n",
+      "fitting image\n",
+      "measured charge:  4.71676991594723e-09\n",
+      "fitting image\n",
+      "measured charge:  4.824831999751764e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.796400297228998e-09\n",
+      "fitting image\n",
+      "measured charge:  4.675843394266956e-09\n",
+      "fitting image\n",
+      "measured charge:  4.545754621190899e-09\n",
+      "fitting image\n",
+      "measured charge:  4.601268938799705e-09\n",
+      "fitting image\n",
+      "measured charge:  5.372102196952912e-09\n",
+      "charge error 0.34 outside atol 0.2\n",
+      "measured charge:  5.430750576163937e-09\n",
+      "charge error 0.36 outside atol 0.2\n",
+      "measured charge:  4.483846097439878e-09\n",
+      "fitting image\n",
+      "measured charge:  4.4092536301242865e-09\n",
+      "fitting image\n",
+      "measured charge:  4.9585051306371645e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  4.914673297828029e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.500348552841406e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9848944844564e-09\n",
+      "fitting image\n",
+      "measured charge:  4.720179558828136e-09\n",
+      "fitting image\n",
+      "measured charge:  3.769510603812038e-09\n",
+      "fitting image\n",
+      "measured charge:  5.396263290246581e-09\n",
+      "charge error 0.35 outside atol 0.2\n",
+      "measured charge:  4.950581718575281e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  4.434915110380344e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 41/49\n",
+      "quad4 | skewquad3\n",
+      " 0.336 | 0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.357633474115406e-09\n",
+      "fitting image\n",
+      "measured charge:  3.885496099678466e-09\n",
+      "fitting image\n",
+      "measured charge:  5.041460499112877e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  5.1237134055053756e-09\n",
+      "charge error 0.28 outside atol 0.2\n",
+      "measured charge:  5.429932838251579e-09\n",
+      "charge error 0.36 outside atol 0.2\n",
+      "measured charge:  4.736921571812049e-09\n",
+      "fitting image\n",
+      "measured charge:  4.72189969033968e-09\n",
+      "fitting image\n",
+      "measured charge:  4.030767059676576e-09\n",
+      "fitting image\n",
+      "measured charge:  4.846291315802224e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.9874519720210116e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  4.252842341960036e-09\n",
+      "fitting image\n",
+      "measured charge:  4.296308534248872e-09\n",
+      "fitting image\n",
+      "measured charge:  4.272806674602585e-09\n",
+      "fitting image\n",
+      "measured charge:  4.096848928675944e-09\n",
+      "fitting image\n",
+      "measured charge:  4.8968865976435926e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  5.348364382094e-09\n",
+      "charge error 0.34 outside atol 0.2\n",
+      "measured charge:  3.7435177055474475e-09\n",
+      "fitting image\n",
+      "measured charge:  4.73354435025799e-09\n",
+      "fitting image\n",
+      "measured charge:  5.0719257393073664e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.234371191540599e-09\n",
+      "fitting image\n",
+      "measured charge:  4.9638816673511806e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  5.271163799146309e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  3.9690746781049466e-09\n",
+      "fitting image\n",
+      "measured charge:  3.7576263863114724e-09\n",
+      "fitting image\n",
+      "measured charge:  4.8441623153346355e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  5.149297434813777e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  5.620139757358812e-09\n",
+      "charge error 0.41 outside atol 0.2\n",
+      "measured charge:  4.243398729902574e-09\n",
+      "fitting image\n",
+      "measured charge:  4.329304439127819e-09\n",
+      "fitting image\n",
+      "measured charge:  5.05145527372798e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  5.472257079358975e-09\n",
+      "charge error 0.37 outside atol 0.2\n",
+      "measured charge:  4.616515968375581e-09\n",
+      "fitting image\n",
+      "measured charge:  4.934812345399016e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.5097867613444796e-09\n",
+      "fitting image\n",
+      "measured charge:  4.113264927205713e-09\n",
+      "fitting image\n",
+      "measured charge:  4.235785121631142e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 42/49\n",
+      "quad4 | skewquad3\n",
+      " 0.672 | 0.381\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.004721927051996e-09\n",
+      "fitting image\n",
+      "measured charge:  4.85884737524383e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.506202403535135e-09\n",
+      "fitting image\n",
+      "measured charge:  4.2312227204597605e-09\n",
+      "fitting image\n",
+      "measured charge:  5.670407223561341e-09\n",
+      "charge error 0.42 outside atol 0.2\n",
+      "measured charge:  4.1162963212726175e-09\n",
+      "fitting image\n",
+      "measured charge:  4.062296800104863e-09\n",
+      "fitting image\n",
+      "measured charge:  4.819259133891504e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  3.648820413172639e-09\n",
+      "fitting image\n",
+      "measured charge:  4.795225924720585e-09\n",
+      "fitting image\n",
+      "measured charge:  3.5692044413695054e-09\n",
+      "fitting image\n",
+      "measured charge:  5.275837873777189e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  4.92551823168233e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  5.5885073493953175e-09\n",
+      "charge error 0.4 outside atol 0.2\n",
+      "measured charge:  4.905793456622041e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  5.030352592273581e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  4.06820108397378e-09\n",
+      "fitting image\n",
+      "measured charge:  5.193383234683851e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.73957291588003e-09\n",
+      "fitting image\n",
+      "measured charge:  5.291183968518651e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  4.300822303429858e-09\n",
+      "fitting image\n",
+      "measured charge:  4.718144219971616e-09\n",
+      "fitting image\n",
+      "measured charge:  4.013097436505948e-09\n",
+      "fitting image\n",
+      "measured charge:  3.816361222394126e-09\n",
+      "fitting image\n",
+      "measured charge:  4.459985802012599e-09\n",
+      "fitting image\n",
+      "measured charge:  4.79507462519501e-09\n",
+      "fitting image\n",
+      "measured charge:  5.189272930904543e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  3.843863513545252e-09\n",
+      "fitting image\n",
+      "measured charge:  4.812953185805715e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  5.013974418625302e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  5.0139996352128315e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  3.998830251476908e-09\n",
+      "fitting image\n",
+      "measured charge:  4.410339744576146e-09\n",
+      "fitting image\n",
+      "measured charge:  4.681228936905207e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 43/49\n",
+      "quad4 | skewquad3\n",
+      " -0.672 | 0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  5.162359627192351e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  4.759450791650819e-09\n",
+      "fitting image\n",
+      "measured charge:  4.269087227931089e-09\n",
+      "fitting image\n",
+      "measured charge:  4.442775480973342e-09\n",
+      "fitting image\n",
+      "measured charge:  3.4580263078112265e-09\n",
+      "fitting image\n",
+      "measured charge:  3.1887239593162314e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.730743507849231e-09\n",
+      "fitting image\n",
+      "measured charge:  5.433292047957387e-09\n",
+      "charge error 0.36 outside atol 0.2\n",
+      "measured charge:  4.768575593993582e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9026938124238966e-09\n",
+      "fitting image\n",
+      "measured charge:  3.516901636310553e-09\n",
+      "fitting image\n",
+      "measured charge:  5.2424349011268636e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  4.325783122787498e-09\n",
+      "fitting image\n",
+      "measured charge:  4.395467361444556e-09\n",
+      "fitting image\n",
+      "measured charge:  4.7344341355634755e-09\n",
+      "fitting image\n",
+      "measured charge:  3.885479889015039e-09\n",
+      "fitting image\n",
+      "measured charge:  4.918518827437564e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  4.985515698330078e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  4.045351253235388e-09\n",
+      "fitting image\n",
+      "measured charge:  4.043677952529443e-09\n",
+      "fitting image\n",
+      "measured charge:  5.023740442767053e-09\n",
+      "charge error 0.26 outside atol 0.2\n",
+      "measured charge:  4.549153456962896e-09\n",
+      "fitting image\n",
+      "measured charge:  3.443108895058965e-09\n",
+      "fitting image\n",
+      "measured charge:  4.545208862187773e-09\n",
+      "fitting image\n",
+      "measured charge:  5.871896764436383e-09\n",
+      "charge error 0.47 outside atol 0.2\n",
+      "measured charge:  4.026799049498718e-09\n",
+      "fitting image\n",
+      "measured charge:  4.116440416059004e-09\n",
+      "fitting image\n",
+      "measured charge:  5.1822050816362386e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.930017591384688e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  3.6979891566295123e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 44/49\n",
+      "quad4 | skewquad3\n",
+      " -0.336 | 0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  5.26445798802874e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  3.964804068875807e-09\n",
+      "fitting image\n",
+      "measured charge:  3.315633641169526e-09\n",
+      "fitting image\n",
+      "measured charge:  4.036453400181179e-09\n",
+      "fitting image\n",
+      "measured charge:  3.3701068739472695e-09\n",
+      "fitting image\n",
+      "measured charge:  4.1530837202163176e-09\n",
+      "fitting image\n",
+      "measured charge:  3.8087512164924185e-09\n",
+      "fitting image\n",
+      "measured charge:  4.788743460521692e-09\n",
+      "fitting image\n",
+      "measured charge:  3.735032323818886e-09\n",
+      "fitting image\n",
+      "measured charge:  4.476661171157772e-09\n",
+      "fitting image\n",
+      "measured charge:  4.629320591323678e-09\n",
+      "fitting image\n",
+      "measured charge:  4.985782273684662e-09\n",
+      "charge error 0.25 outside atol 0.2\n",
+      "measured charge:  4.462529074990882e-09\n",
+      "fitting image\n",
+      "measured charge:  3.877866280743614e-09\n",
+      "fitting image\n",
+      "measured charge:  3.828973118565565e-09\n",
+      "fitting image\n",
+      "measured charge:  3.947847714897431e-09\n",
+      "fitting image\n",
+      "measured charge:  4.707522633036149e-09\n",
+      "fitting image\n",
+      "measured charge:  4.1300321567771535e-09\n",
+      "fitting image\n",
+      "measured charge:  3.7012474999848368e-09\n",
+      "fitting image\n",
+      "measured charge:  3.726945003937466e-09\n",
+      "fitting image\n",
+      "measured charge:  3.426613644396745e-09\n",
+      "fitting image\n",
+      "measured charge:  4.806305012602623e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.863379156273162e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.523349683105376e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 45/49\n",
+      "quad4 | skewquad3\n",
+      " -0.168 | 0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.156435725182716e-09\n",
+      "fitting image\n",
+      "measured charge:  4.6580927177790876e-09\n",
+      "fitting image\n",
+      "measured charge:  5.202711570912177e-09\n",
+      "charge error 0.3 outside atol 0.2\n",
+      "measured charge:  4.297194717184637e-09\n",
+      "fitting image\n",
+      "measured charge:  3.855726116827877e-09\n",
+      "fitting image\n",
+      "measured charge:  4.83679727056957e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.951541750088963e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  3.4552398748809692e-09\n",
+      "fitting image\n",
+      "measured charge:  4.041152691399511e-09\n",
+      "fitting image\n",
+      "measured charge:  5.666830070491412e-09\n",
+      "charge error 0.42 outside atol 0.2\n",
+      "measured charge:  4.57502567584396e-09\n",
+      "fitting image\n",
+      "measured charge:  3.994842428265903e-09\n",
+      "fitting image\n",
+      "measured charge:  4.000840373745893e-09\n",
+      "fitting image\n",
+      "measured charge:  3.5600346094060647e-09\n",
+      "fitting image\n",
+      "measured charge:  4.28806451128736e-09\n",
+      "fitting image\n",
+      "measured charge:  4.321896165927009e-09\n",
+      "fitting image\n",
+      "measured charge:  4.088372552871615e-09\n",
+      "fitting image\n",
+      "measured charge:  3.941658843825575e-09\n",
+      "fitting image\n",
+      "measured charge:  4.149870406481663e-09\n",
+      "fitting image\n",
+      "measured charge:  4.589336089308877e-09\n",
+      "fitting image\n",
+      "measured charge:  4.4028125931764726e-09\n",
+      "fitting image\n",
+      "measured charge:  4.4540472956320404e-09\n",
+      "fitting image\n",
+      "measured charge:  3.8774808271902986e-09\n",
+      "fitting image\n",
+      "measured charge:  5.093869574076858e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  5.760531307655842e-09\n",
+      "charge error 0.44 outside atol 0.2\n",
+      "measured charge:  4.819006968015418e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.600978948042262e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 46/49\n",
+      "quad4 | skewquad3\n",
+      " 0 | 0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.067878671889361e-09\n",
+      "fitting image\n",
+      "measured charge:  4.12799861910543e-09\n",
+      "fitting image\n",
+      "measured charge:  4.652274890782049e-09\n",
+      "fitting image\n",
+      "measured charge:  4.084854838900886e-09\n",
+      "fitting image\n",
+      "measured charge:  4.548119576871149e-09\n",
+      "fitting image\n",
+      "measured charge:  4.394231748652044e-09\n",
+      "fitting image\n",
+      "measured charge:  4.931912437824671e-09\n",
+      "charge error 0.23 outside atol 0.2\n",
+      "measured charge:  3.4517473774978987e-09\n",
+      "fitting image\n",
+      "measured charge:  4.736058804279022e-09\n",
+      "fitting image\n",
+      "measured charge:  5.868276382930367e-09\n",
+      "charge error 0.47 outside atol 0.2\n",
+      "measured charge:  6.014066084159281e-09\n",
+      "charge error 0.5 outside atol 0.2\n",
+      "measured charge:  4.460738697271009e-09\n",
+      "fitting image\n",
+      "measured charge:  4.548967934925555e-09\n",
+      "fitting image\n",
+      "measured charge:  4.638940719494375e-09\n",
+      "fitting image\n",
+      "measured charge:  4.776652106765971e-09\n",
+      "fitting image\n",
+      "measured charge:  4.329005442446259e-09\n",
+      "fitting image\n",
+      "measured charge:  4.670643373666175e-09\n",
+      "fitting image\n",
+      "measured charge:  4.09984610023108e-09\n",
+      "fitting image\n",
+      "measured charge:  4.438629153497448e-09\n",
+      "fitting image\n",
+      "measured charge:  4.0511582731235166e-09\n",
+      "fitting image\n",
+      "measured charge:  4.640959847687473e-09\n",
+      "fitting image\n",
+      "measured charge:  3.6321594535061016e-09\n",
+      "fitting image\n",
+      "measured charge:  4.763894314623473e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 47/49\n",
+      "quad4 | skewquad3\n",
+      " 0.168 | 0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  5.249059658927142e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  3.821400937545222e-09\n",
+      "fitting image\n",
+      "measured charge:  4.396303111205128e-09\n",
+      "fitting image\n",
+      "measured charge:  5.572939708919952e-09\n",
+      "charge error 0.39 outside atol 0.2\n",
+      "measured charge:  4.5678443519314435e-09\n",
+      "fitting image\n",
+      "measured charge:  3.894109365529868e-09\n",
+      "fitting image\n",
+      "measured charge:  4.139830602245879e-09\n",
+      "fitting image\n",
+      "measured charge:  4.681358622212845e-09\n",
+      "fitting image\n",
+      "measured charge:  3.873952306110538e-09\n",
+      "fitting image\n",
+      "measured charge:  5.7387910067719685e-09\n",
+      "charge error 0.43 outside atol 0.2\n",
+      "measured charge:  4.961178088923084e-09\n",
+      "charge error 0.24 outside atol 0.2\n",
+      "measured charge:  4.771158493038021e-09\n",
+      "fitting image\n",
+      "measured charge:  4.808590716150433e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.3902619372893854e-09\n",
+      "fitting image\n",
+      "measured charge:  3.7640944410317386e-09\n",
+      "fitting image\n",
+      "measured charge:  3.490454839469113e-09\n",
+      "fitting image\n",
+      "measured charge:  4.104930845002847e-09\n",
+      "fitting image\n",
+      "measured charge:  5.297167504519883e-09\n",
+      "charge error 0.32 outside atol 0.2\n",
+      "measured charge:  5.089800697548615e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.378678517655301e-09\n",
+      "fitting image\n",
+      "measured charge:  4.423093934348928e-09\n",
+      "fitting image\n",
+      "measured charge:  4.565151580612383e-09\n",
+      "fitting image\n",
+      "measured charge:  4.44908863379831e-09\n",
+      "fitting image\n",
+      "measured charge:  4.6176272994149714e-09\n",
+      "fitting image\n",
+      "measured charge:  4.144926154126559e-09\n",
+      "fitting image\n",
+      "measured charge:  5.066588828659637e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.713796159794831e-09\n",
+      "fitting image\n",
+      "measured charge:  4.4347007693857455e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 48/49\n",
+      "quad4 | skewquad3\n",
+      " 0.336 | 0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.541393952720414e-09\n",
+      "fitting image\n",
+      "measured charge:  4.6731470205783036e-09\n",
+      "fitting image\n",
+      "measured charge:  4.239338859298441e-09\n",
+      "fitting image\n",
+      "measured charge:  4.5398557408766255e-09\n",
+      "fitting image\n",
+      "measured charge:  4.847107252529655e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.628400185876149e-09\n",
+      "fitting image\n",
+      "measured charge:  5.820998883543864e-09\n",
+      "charge error 0.46 outside atol 0.2\n",
+      "measured charge:  3.845034283684069e-09\n",
+      "fitting image\n",
+      "measured charge:  3.923454268760855e-09\n",
+      "fitting image\n",
+      "measured charge:  4.2527270661310244e-09\n",
+      "fitting image\n",
+      "measured charge:  4.605834942340809e-09\n",
+      "fitting image\n",
+      "measured charge:  5.158085415593626e-09\n",
+      "charge error 0.29 outside atol 0.2\n",
+      "measured charge:  4.280101473159183e-09\n",
+      "fitting image\n",
+      "measured charge:  3.773925307827436e-09\n",
+      "fitting image\n",
+      "measured charge:  4.372673367435997e-09\n",
+      "fitting image\n",
+      "measured charge:  4.207416460577399e-09\n",
+      "fitting image\n",
+      "measured charge:  4.842463798041036e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  3.4063755316601773e-09\n",
+      "fitting image\n",
+      "measured charge:  3.958103661312604e-09\n",
+      "fitting image\n",
+      "measured charge:  4.2782012231648125e-09\n",
+      "fitting image\n",
+      "measured charge:  4.3773366349577585e-09\n",
+      "fitting image\n",
+      "measured charge:  4.58573552083611e-09\n",
+      "fitting image\n",
+      "measured charge:  4.577291566358628e-09\n",
+      "fitting image\n",
+      "measured charge:  4.82066225687314e-09\n",
+      "charge error 0.21 outside atol 0.2\n",
+      "measured charge:  4.720510976836663e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 49/49\n",
+      "quad4 | skewquad3\n",
+      " 0.672 | 0.762\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  4.892709650025524e-09\n",
+      "charge error 0.22 outside atol 0.2\n",
+      "measured charge:  4.800732146742231e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.716906805994311e-09\n",
+      "fitting image\n",
+      "measured charge:  4.810375690315793e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  4.706440120954006e-09\n",
+      "fitting image\n",
+      "measured charge:  5.086879175756198e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.534135177860249e-09\n",
+      "fitting image\n",
+      "measured charge:  5.081716980036778e-09\n",
+      "charge error 0.27 outside atol 0.2\n",
+      "measured charge:  4.162557952415824e-09\n",
+      "fitting image\n",
+      "measured charge:  5.634243034568546e-09\n",
+      "charge error 0.41 outside atol 0.2\n",
+      "measured charge:  3.632564720092678e-09\n",
+      "fitting image\n",
+      "measured charge:  4.804973937014115e-09\n",
+      "charge error 0.2 outside atol 0.2\n",
+      "measured charge:  5.3649352825191545e-09\n",
+      "charge error 0.34 outside atol 0.2\n",
+      "measured charge:  3.962709290919988e-09\n",
+      "fitting image\n",
+      "measured charge:  4.616973469322155e-09\n",
+      "fitting image\n",
+      "measured charge:  4.472487825909426e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9198717121363106e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9136396126285826e-09\n",
+      "fitting image\n",
+      "measured charge:  4.099087801418154e-09\n",
+      "fitting image\n",
+      "measured charge:  5.363137700059963e-09\n",
+      "charge error 0.34 outside atol 0.2\n",
+      "measured charge:  3.904723747726026e-09\n",
+      "fitting image\n",
+      "measured charge:  4.076549575655271e-09\n",
+      "fitting image\n",
+      "measured charge:  3.382237853769283e-09\n",
+      "fitting image\n",
+      "measured charge:  4.203062996846096e-09\n",
+      "fitting image\n",
+      "measured charge:  4.221330613379968e-09\n",
+      "fitting image\n",
+      "measured charge:  3.87689003856637e-09\n",
+      "fitting image\n",
+      "measured charge:  4.003914996248676e-09\n",
+      "fitting image\n",
+      "measured charge:  3.8614502822138444e-09\n",
+      "fitting image\n",
+      "measured charge:  4.234915149358804e-09\n",
+      "fitting image\n"
+     ]
+    }
+   ],
+   "source": [
+    "##Quad Scan at Yag7##\n",
+    "quads = [-0.672, -0.336, -0.168, 0, 0.168, 0.336, 0.672]\n",
+    "skews = [-0.762, -0.381, -0.191 ,0, 0.191, 0.381, 0.762]\n",
+    "\n",
+    "i = 0\n",
+    "end = 7*7\n",
+    "\n",
+    "screen = \"DYG7\"\n",
+    "target_charge = 4e-9\n",
+    "n_shots = 20\n",
+    "\n",
+    "for s in skews:\n",
+    "    for q in quads:\n",
+    "        i = i+1\n",
+    "        print('\\033[1m')\n",
+    "        print(f\"Step {i}/{end}\\nquad4 | skewquad3\\n {q} | {s}\") \n",
+    "        print(\"-----------------------------\")\n",
+    "        print('\\033[0m')\n",
+    "        Datafolder = f\"./Data/2024_07_11/DYG7_Scan/q_{q}_s_{s}/\"\n",
+    "        if os.path.exists(Datafolder):\n",
+    "            continue    \n",
+    "        else:\n",
+    "            os.system(\"mkdir \"+Datafolder)\n",
+    "        caput(\"AWA:Bira3Ctrl:Ch02\",s)\n",
+    "        caput(\"AWA:Bira3Ctrl:Ch03\",q)\n",
+    "        time.sleep(1)\n",
+    "        TakeScreenData(screen, Datafolder,target_charge, n_shots)\n",
+    "        \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "2c30231a-30db-43b9-a381-508b205051bc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Sx',\n",
+       " 'Sy',\n",
+       " 'Cx',\n",
+       " 'Cy',\n",
+       " 'correlation',\n",
+       " 'total_size',\n",
+       " 'bb_penalty',\n",
+       " 'log10_total_intensity',\n",
+       " 'K1_phase_readback']"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "awa_env.observables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "97145b5f-ccda-4eae-93cf-3c59015e0cee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def TakeScreenData(screenname: str, dumpfolder: str, target_charge: float ,n_shots: int):\n",
+    "    if os.path.exists(dumpfolder)!=True:\n",
+    "        os.system(\"mkdir \"+dumpfolder)\n",
+    "        \n",
+    "    if screenname == 'DYG7':\n",
+    "        awa_env.screen_name = 'DYG7'\n",
+    "        awa_env.image_diagnostic.resolution = 25/500 #Yag7\n",
+    "    elif screenname == 'DYG4':\n",
+    "        awa_env.screen_name = 'DYG4'\n",
+    "        awa_env.image_diagnostic.resolution = 50/460 #Yag4\n",
+    "    elif screenname == 'DYG5':\n",
+    "        awa_env.screen_name = 'DYG5'\n",
+    "        awa_env.image_diagnostic.resolution = 25/206.9578032921999 #Yag5\n",
+    "    elif screenname == 'DYG6':\n",
+    "        awa_env.screen_name = 'DYG6'\n",
+    "        awa_env.image_diagnostic.resolution = 47/420 #Yag6\n",
+    "    else:\n",
+    "        print(\"screen not recognized\")\n",
+    "        return\n",
+    "        \n",
+    "    awa_env.image_diagnostic.save_image_location = dumpfolder\n",
+    "    awa_env.image_diagnostic.target_charge = target_charge\n",
+    "    awa_env.image_diagnostic.charge_atol = 0.2\n",
+    "    awa_env.image_diagnostic.target_charge_pv = \"AWAVXI11ICT:Ch1\"\n",
+    "    awa_env.image_diagnostic.extra_pvs = [\"AWA:Drive:DS3:RB\",\n",
+    "                                          \"AWAVXI11ICT:Ch2\",\n",
+    "                                          \"AWA:Bira3RB:Ch02\",\n",
+    "                                          \"AWA:Bira3RB:Ch03\",\n",
+    "                                          \"AWA:EEXBL:ET1H_B_N:RB\",\n",
+    "                                          \"AWA:EEXBL:ET1V_B_N:RB\",\n",
+    "                                          \"AWA:Drive:DT7H_B_S:RB\",\n",
+    "                                          \"AWA:Drive:DT7V_B_S:RB\"]\n",
+    "    awa_env.image_diagnostic.measure_beamsize(n_shots)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "id": "b3bc0ca9-a2c8-4fd0-a65a-5082550662e1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "measured charge:  4.710037087057182e-09\n",
+      "fitting image\n",
+      "measured charge:  3.912214875429001e-09\n",
+      "fitting image\n",
+      "measured charge:  4.359144668186742e-09\n",
+      "fitting image\n",
+      "measured charge:  3.9653102018127745e-09\n",
+      "fitting image\n",
+      "measured charge:  5.2275517108863635e-09\n",
+      "charge error 0.31 outside atol 0.2\n",
+      "measured charge:  3.725361762472999e-09\n",
+      "fitting image\n",
+      "measured charge:  3.708635960152636e-09\n",
+      "fitting image\n",
+      "measured charge:  4.088939926092678e-09\n",
+      "fitting image\n",
+      "measured charge:  4.611780653460686e-09\n",
+      "fitting image\n",
+      "measured charge:  4.149935249135477e-09\n",
+      "fitting image\n",
+      "measured charge:  3.5724970072366e-09\n",
+      "fitting image\n",
+      "done\n"
+     ]
+    }
+   ],
+   "source": [
+    "TakeScreenData(\"DYG7\",\"./Data/2024_07_11/VerticalSlit_17300/\", 4e-9, 10)\n",
+    "print(\"done\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "9e7804e6-7cc1-45a1-b5b9-3ffe072cecea",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m\n",
+      "Step 1/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | -0.5 | 0.74 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4427148253660166e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4306648988613077e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1521278757491131e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.3146397769285983e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2911108995098252e-09\n",
+      "fitting image\n",
+      "measured charge:  1.8717894729157762e-09\n",
+      "charge error 0.34 outside atol 0.1\n",
+      "measured charge:  1.514875693162677e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 2/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | -0.5 | 0.74 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.2795022632881365e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4429777983510587e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3433362536212173e-09\n",
+      "fitting image\n",
+      "measured charge:  1.530877419181878e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3054483307471576e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 3/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | -0.5 | 0.74 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.6143983596938572e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.5952733791815383e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.4763897769255007e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6193894428544883e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.5990054341468024e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.1829245339521013e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.3503410614204448e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7192471297637947e-09\n",
+      "charge error 0.23 outside atol 0.1\n",
+      "measured charge:  1.2968566791137377e-09\n",
+      "fitting image\n",
+      "measured charge:  1.9073178436640977e-09\n",
+      "charge error 0.36 outside atol 0.1\n",
+      "measured charge:  1.4039857491769294e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5618235757256773e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.2939981987904294e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 4/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | -0.5 | 0.94 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4590443670240295e-09\n",
+      "fitting image\n",
+      "measured charge:  1.862185555408564e-09\n",
+      "charge error 0.33 outside atol 0.1\n",
+      "measured charge:  1.0688032643834475e-09\n",
+      "charge error 0.24 outside atol 0.1\n",
+      "measured charge:  1.2926599184626087e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3650189165904453e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4053222283199402e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2635293562262491e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 5/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | -0.5 | 0.94 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4976563661992438e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4324732884294087e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6267652947284622e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.269912755259554e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4603610331339038e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1466937011205618e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.37760919854382e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 6/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | -0.5 | 0.94 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3491342675851613e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2044036630356714e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.4496025561514227e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3284332503476402e-09\n",
+      "fitting image\n",
+      "measured charge:  1.552356548265421e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.6756620592761666e-09\n",
+      "charge error 0.2 outside atol 0.1\n",
+      "measured charge:  1.534359109455972e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4162139929797298e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 7/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | -0.5 | 1.14 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.6926022025911811e-09\n",
+      "charge error 0.21 outside atol 0.1\n",
+      "measured charge:  1.407863700113372e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3950212522839666e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3984038773924316e-09\n",
+      "fitting image\n",
+      "measured charge:  1.842637296461505e-09\n",
+      "charge error 0.32 outside atol 0.1\n",
+      "measured charge:  1.4690589546722124e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5713248256976418e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.398724488291984e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 8/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | -0.5 | 1.14 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.590329126826435e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.3717949739164406e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2468179633845464e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.155204299436691e-09\n",
+      "charge error 0.17 outside atol 0.1\n",
+      "measured charge:  1.679932668505301e-09\n",
+      "charge error 0.2 outside atol 0.1\n",
+      "measured charge:  1.5015091005480889e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4689724978004491e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4485416582872262e-09\n",
+      "fitting image\n",
+      "measured charge:  1.49350103279918e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 9/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | -0.5 | 1.14 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4275308372591593e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3434443247109273e-09\n",
+      "fitting image\n",
+      "measured charge:  1.396307298251733e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6687274976852812e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.660598750552839e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.157317089240891e-09\n",
+      "charge error 0.17 outside atol 0.1\n",
+      "measured charge:  1.1169345253789436e-09\n",
+      "charge error 0.2 outside atol 0.1\n",
+      "measured charge:  1.309346094716694e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2064101829349708e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.4811431036887427e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 10/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0 | 0.74 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.435855913537914e-09\n",
+      "fitting image\n",
+      "measured charge:  1.586402543899653e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.4059670524886526e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2859451014208039e-09\n",
+      "fitting image\n",
+      "measured charge:  1.926821072990479e-09\n",
+      "charge error 0.38 outside atol 0.1\n",
+      "measured charge:  1.5319076969039618e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4682051930633578e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 11/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0 | 0.74 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.26676248299395e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4789366522734412e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6297354485111435e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.5293518156318527e-09\n",
+      "fitting image\n",
+      "measured charge:  1.601366787457395e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.299372934319582e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3353678119385431e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 12/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0 | 0.74 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4085625598269393e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4217976659490769e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3630556251270474e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4526105348155267e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2443467377993934e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.224735437383315e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.2365025778699137e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.7784826952289009e-09\n",
+      "charge error 0.27 outside atol 0.1\n",
+      "measured charge:  1.609027226534296e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.4886738574579993e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 13/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0 | 0.94 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.2294851617768665e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.2348094641308615e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.2159780767456147e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.1732755868241853e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.1300489521175378e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.3719534781813832e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1616453363845327e-09\n",
+      "charge error 0.17 outside atol 0.1\n",
+      "measured charge:  1.255184466914351e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.2681818166390751e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5928579903260934e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.2369348622288592e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.5173235033450863e-09\n",
+      "fitting image\n",
+      "measured charge:  1.655647293458428e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.5439756352569578e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.4769481442224507e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5802154740126662e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.312065883808216e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 14/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0 | 0.94 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.37329896324847e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5472700023088526e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.5017036285096066e-09\n",
+      "fitting image\n",
+      "measured charge:  1.920583569928298e-09\n",
+      "charge error 0.37 outside atol 0.1\n",
+      "measured charge:  1.4669137435411302e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4221110721092663e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5051763128595378e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 15/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0 | 0.94 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.25961177922358e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.2465730022478047e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.245467074762929e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.4092362029529045e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2590408036328588e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.5369275990218555e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7324516157437719e-09\n",
+      "charge error 0.24 outside atol 0.1\n",
+      "measured charge:  1.4989280026883849e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6223668013764838e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.3420952372741765e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3945655525222636e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 16/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0 | 1.14 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3934019871228257e-09\n",
+      "fitting image\n",
+      "measured charge:  1.324472444909081e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4756963207663927e-09\n",
+      "fitting image\n",
+      "measured charge:  1.382058125070988e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6315096155675285e-09\n",
+      "charge error 0.17 outside atol 0.1\n",
+      "measured charge:  1.336907824967173e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 17/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0 | 1.14 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.5342744537690173e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1537921705309124e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.1109509893776422e-09\n",
+      "charge error 0.21 outside atol 0.1\n",
+      "measured charge:  1.4529491575633637e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4987496853903492e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3222515840151505e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5149081144896412e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 18/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0 | 1.14 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.0378300900672243e-09\n",
+      "charge error 0.26 outside atol 0.1\n",
+      "measured charge:  1.4593992004352946e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1410830103788402e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.1096991659216119e-09\n",
+      "charge error 0.21 outside atol 0.1\n",
+      "measured charge:  1.3492513445990337e-09\n",
+      "fitting image\n",
+      "measured charge:  1.318715858196205e-09\n",
+      "fitting image\n",
+      "measured charge:  1.36140573982385e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5350903904964453e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 19/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0.5 | 0.74 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4480679466772832e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4563065660842282e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4700207873708222e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5477833399850692e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.1341862736693183e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.4191139005541319e-09\n",
+      "fitting image\n",
+      "measured charge:  1.660364596525101e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.1310540132519983e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.5662346773714182e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.5311241815033865e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 20/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0.5 | 0.74 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.97011975509026e-09\n",
+      "charge error 0.41 outside atol 0.1\n",
+      "measured charge:  1.3770310182137861e-09\n",
+      "fitting image\n",
+      "measured charge:  1.649143215041593e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.4862872875598139e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3977662579630335e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4349228997966152e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4664922662911872e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 21/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0.5 | 0.74 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3402544263791214e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2003924244219322e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.3499556078671107e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4474627485747988e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2633168164164493e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5334729265201528e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 22/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0.5 | 0.94 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4203657240101396e-09\n",
+      "fitting image\n",
+      "measured charge:  1.0142525806580805e-09\n",
+      "charge error 0.28 outside atol 0.1\n",
+      "measured charge:  1.2329092141364619e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.3363170363433208e-09\n",
+      "fitting image\n",
+      "measured charge:  1.565683514813836e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.3889332475625708e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2608798133430656e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2933263568492592e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 23/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0.5 | 0.94 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.2843564564017937e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1864908799131623e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.371319461121641e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7007507627567045e-09\n",
+      "charge error 0.21 outside atol 0.1\n",
+      "measured charge:  1.2963433414375385e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5049871884525331e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1645938759493058e-09\n",
+      "charge error 0.17 outside atol 0.1\n",
+      "measured charge:  1.144734012026829e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.228970022915854e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.6449266413573694e-09\n",
+      "charge error 0.17 outside atol 0.1\n",
+      "measured charge:  1.3043261925988102e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 24/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0.5 | 0.94 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4274317720935725e-09\n",
+      "fitting image\n",
+      "measured charge:  1.382106757061384e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3855794414113098e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5100629273001305e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5875769164080078e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.4819842570037664e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 25/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0.5 | 1.14 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4721497878384758e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2723641678115633e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3438820126243423e-09\n",
+      "fitting image\n",
+      "measured charge:  1.8575943352799317e-09\n",
+      "charge error 0.33 outside atol 0.1\n",
+      "measured charge:  1.581306992018916e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.3431885564652343e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2266302838232293e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.4948501202359698e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 26/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0.5 | 1.14 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.1399122402401133e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.5288582909887805e-09\n",
+      "fitting image\n",
+      "measured charge:  1.154714377163275e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.1740158737887968e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.3095784475596256e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3799453352668125e-09\n",
+      "fitting image\n",
+      "measured charge:  1.416440942268158e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6986902073125282e-09\n",
+      "charge error 0.21 outside atol 0.1\n",
+      "measured charge:  1.432417451699749e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 27/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " -0.5 | 0.5 | 1.14 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3880362575178276e-09\n",
+      "fitting image\n",
+      "measured charge:  1.863851651375195e-09\n",
+      "charge error 0.33 outside atol 0.1\n",
+      "measured charge:  1.4652476475744421e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4209853315912458e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5112192879602043e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2475132207284494e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.4718724053748527e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 28/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | -0.5 | 0.74 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.6053510082987374e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.5670398069898837e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.3019378215158043e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2442350643400076e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.5549142307223295e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.4581275639461512e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4032868894633652e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6872256658771709e-09\n",
+      "charge error 0.21 outside atol 0.1\n",
+      "measured charge:  1.5571927295308166e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.5186707895970194e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5376804942802698e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 29/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | -0.5 | 0.74 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3741779414449683e-09\n",
+      "fitting image\n",
+      "measured charge:  1.294743889309537e-09\n",
+      "fitting image\n",
+      "measured charge:  8.996972255456859e-10\n",
+      "charge error 0.36 outside atol 0.1\n",
+      "measured charge:  1.2128584246221253e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.1109059597569353e-09\n",
+      "charge error 0.21 outside atol 0.1\n",
+      "measured charge:  1.3804352575402385e-09\n",
+      "fitting image\n",
+      "measured charge:  1.383500874118856e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2478086150403825e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.4354218279941994e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 30/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | -0.5 | 0.74 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.282213046455513e-09\n",
+      "fitting image\n",
+      "measured charge:  1.324859699647267e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5302776246338444e-09\n",
+      "fitting image\n",
+      "measured charge:  1.484540138275882e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4418376483544192e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 31/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | -0.5 | 0.94 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.2945331506845842e-09\n",
+      "fitting image\n",
+      "measured charge:  1.460047626973715e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3165112079657127e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6644118588354654e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.213458219170131e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.4191697372838317e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5962694343918582e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.7512145581055135e-09\n",
+      "charge error 0.25 outside atol 0.1\n",
+      "measured charge:  1.872927821727622e-09\n",
+      "charge error 0.34 outside atol 0.1\n",
+      "measured charge:  1.2770994827265195e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 32/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | -0.5 | 0.94 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3592371132899609e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2957957812495525e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4111256458383587e-09\n",
+      "fitting image\n",
+      "measured charge:  9.381110943897593e-10\n",
+      "charge error 0.33 outside atol 0.1\n",
+      "measured charge:  1.8423473057040612e-09\n",
+      "charge error 0.32 outside atol 0.1\n",
+      "measured charge:  1.2658132585891651e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4408938275040938e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 33/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | -0.5 | 0.94 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.8191354368151509e-09\n",
+      "charge error 0.3 outside atol 0.1\n",
+      "measured charge:  1.7709195201327233e-09\n",
+      "charge error 0.26 outside atol 0.1\n",
+      "measured charge:  1.3436568645207234e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3526411744468597e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4341862152016288e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4696371350022988e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2458291129135053e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.4163112569605094e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 34/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | -0.5 | 1.14 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.2160573288780901e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.2719589012250742e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4961541780520195e-09\n",
+      "fitting image\n",
+      "measured charge:  1.256778515487849e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.6582572102753854e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.8270660536164195e-09\n",
+      "charge error 0.31 outside atol 0.1\n",
+      "measured charge:  1.4726793361781196e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7048304463939786e-09\n",
+      "charge error 0.22 outside atol 0.1\n",
+      "measured charge:  1.4972168771010189e-09\n",
+      "fitting image\n",
+      "measured charge:  1.240758777620426e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.465629498758165e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 35/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | -0.5 | 1.14 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3187680925562174e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1434371589500924e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.1877084808574235e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.5775191003239428e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.3611337609146854e-09\n",
+      "fitting image\n",
+      "measured charge:  1.390042777417104e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6534714621852352e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.4889188185947146e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4468935741688738e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 36/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | -0.5 | 1.14 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.367844975586854e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2764906822543667e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6949959772286283e-09\n",
+      "charge error 0.21 outside atol 0.1\n",
+      "measured charge:  1.0720526018146362e-09\n",
+      "charge error 0.23 outside atol 0.1\n",
+      "measured charge:  1.5832108443830015e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.1969305471809433e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.3990036719404617e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3384802593227312e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2716905246855983e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 37/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0 | 0.74 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.07592154682691e-09\n",
+      "charge error 0.23 outside atol 0.1\n",
+      "measured charge:  1.352081005965106e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2264501653403386e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.0056861456122739e-09\n",
+      "charge error 0.28 outside atol 0.1\n",
+      "measured charge:  9.845888677123935e-10\n",
+      "charge error 0.3 outside atol 0.1\n",
+      "measured charge:  9.780883916652194e-10\n",
+      "charge error 0.3 outside atol 0.1\n",
+      "measured charge:  1.3491036474430612e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1734503017525585e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.1415639267281153e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.292159189080198e-09\n",
+      "fitting image\n",
+      "measured charge:  1.231365598738155e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.7027824992436291e-09\n",
+      "charge error 0.22 outside atol 0.1\n",
+      "measured charge:  1.1415837397612269e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.4604582971146375e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3641921727540356e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 38/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0 | 0.74 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.160415127146472e-09\n",
+      "charge error 0.17 outside atol 0.1\n",
+      "measured charge:  1.4737078127154086e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1556221743169784e-09\n",
+      "charge error 0.17 outside atol 0.1\n",
+      "measured charge:  1.5826218569439356e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.434867063066906e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2931120158546377e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2008229075960176e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.1825300744746142e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.3097315482700711e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4062084112557042e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 39/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0 | 0.74 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3546747121185871e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5035246263715302e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5262519765414746e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7619135959886324e-09\n",
+      "charge error 0.26 outside atol 0.1\n",
+      "measured charge:  1.7915376828680953e-09\n",
+      "charge error 0.28 outside atol 0.1\n",
+      "measured charge:  1.6106284798471663e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.4253820237583696e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2046342146937855e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.308409478605727e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 40/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0 | 0.94 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.148475072916263e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.3390098076624264e-09\n",
+      "fitting image\n",
+      "measured charge:  1.502152123532e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1832739638089134e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.5391700741337235e-09\n",
+      "fitting image\n",
+      "measured charge:  1.781332169628052e-09\n",
+      "charge error 0.27 outside atol 0.1\n",
+      "measured charge:  1.5905632808541732e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.611347152593812e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.3432155742376907e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6251730473397638e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.6307603226787736e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.4301245434126337e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 41/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0 | 0.94 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3044036435464414e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3269724894514495e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5034633860873698e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3506778829834293e-09\n",
+      "fitting image\n",
+      "measured charge:  1.515844730600601e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 42/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0 | 0.94 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.5529653487375613e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.5339682523480873e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3201604084288902e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2192220106223197e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.5230404639916836e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2156808812488869e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.4108914918106164e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2261583733980617e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.2907254459564714e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 43/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0 | 1.14 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.2181827269760874e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.2618236341933668e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4256017683074836e-09\n",
+      "fitting image\n",
+      "measured charge:  1.64693136007184e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.3169524982487996e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2223488674851217e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.376301538358113e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2130367419201878e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.2137013791220115e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.5517405430539603e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.1852084363150505e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.2200199355014662e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.3846950596603488e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 44/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0 | 1.14 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.1991279926721045e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.2110248184664044e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.0343952305986911e-09\n",
+      "charge error 0.26 outside atol 0.1\n",
+      "measured charge:  1.305464541410629e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7353875470147467e-09\n",
+      "charge error 0.24 outside atol 0.1\n",
+      "measured charge:  1.4400580777435191e-09\n",
+      "fitting image\n",
+      "measured charge:  1.0467855810360642e-09\n",
+      "charge error 0.25 outside atol 0.1\n",
+      "measured charge:  1.256036427338378e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.3161095437489132e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5217778334267112e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4167903721249604e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 45/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0 | 1.14 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.1984579519157658e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.5205007933830571e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4823751141116565e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3646911009515815e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2838899495311112e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1775732138257146e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.3273615453744676e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 46/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0.5 | 0.74 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.5987082386500412e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.8070368783200507e-09\n",
+      "charge error 0.29 outside atol 0.1\n",
+      "measured charge:  1.4254720829998406e-09\n",
+      "fitting image\n",
+      "measured charge:  1.647781519311039e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.3148198954114746e-09\n",
+      "fitting image\n",
+      "measured charge:  1.466897532877645e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3812043634621325e-09\n",
+      "fitting image\n",
+      "measured charge:  8.811594312875739e-10\n",
+      "charge error 0.37 outside atol 0.1\n",
+      "measured charge:  1.5945727182831169e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.3656799514226336e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 47/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0.5 | 0.74 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4377921872289113e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2980022326648534e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3171001954047338e-09\n",
+      "fitting image\n",
+      "measured charge:  9.931571039430592e-10\n",
+      "charge error 0.29 outside atol 0.1\n",
+      "measured charge:  1.42495694413877e-09\n",
+      "fitting image\n",
+      "measured charge:  9.145083683930196e-10\n",
+      "charge error 0.35 outside atol 0.1\n",
+      "measured charge:  1.2600512683218049e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 48/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0.5 | 0.74 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.6226675992429016e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.1891224109480622e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.4404291218182641e-09\n",
+      "fitting image\n",
+      "measured charge:  1.384958032645389e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6206286580167224e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.5846680029094902e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.3091713797883093e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4431939405305148e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5626377112683057e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.2562075398971278e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.087771541815675e-09\n",
+      "charge error 0.22 outside atol 0.1\n",
+      "measured charge:  1.3709195980896364e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 49/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0.5 | 0.94 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.6023646438525714e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.4905236742771824e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2051673654031137e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.4663337620262348e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2486371600616414e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.2730756358189539e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4171343984272548e-09\n",
+      "fitting image\n",
+      "measured charge:  1.516305833916766e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 50/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0.5 | 0.94 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.6988144890657102e-09\n",
+      "charge error 0.21 outside atol 0.1\n",
+      "measured charge:  1.3866223274272224e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4191661349141749e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1530536847510979e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.088220036838041e-09\n",
+      "charge error 0.22 outside atol 0.1\n",
+      "measured charge:  1.1770508702253564e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.840239919454346e-09\n",
+      "charge error 0.31 outside atol 0.1\n",
+      "measured charge:  1.3666922172963986e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3366088282856073e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6574790984293212e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.4736555783553559e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 51/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0.5 | 0.94 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.8004247288134624e-09\n",
+      "charge error 0.29 outside atol 0.1\n",
+      "measured charge:  1.5200793161331133e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4657105520754618e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1362450279286375e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.2196020606211792e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.3938576868845287e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2090182985671043e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.4096126505821574e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3915539714885021e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 52/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0.5 | 1.14 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4086976486890932e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6217435914257162e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.603892048587396e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.4565695390692716e-09\n",
+      "fitting image\n",
+      "measured charge:  9.199245311732257e-10\n",
+      "charge error 0.34 outside atol 0.1\n",
+      "measured charge:  1.198339073717066e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.5921429199490455e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.2454724783174138e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.3169074686280594e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3572269910209933e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3618740478793269e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 53/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0.5 | 1.14 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.7576519926836645e-09\n",
+      "charge error 0.26 outside atol 0.1\n",
+      "measured charge:  1.2213420051658321e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.2535579970139441e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.5083842230396723e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4737600470754538e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3856586935438094e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7789636115782052e-09\n",
+      "charge error 0.27 outside atol 0.1\n",
+      "measured charge:  1.3690049386165876e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4752496269288538e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 54/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0 | 0.5 | 1.14 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.5733943870659362e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.4379524926786585e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3715734281824716e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1023449282655815e-09\n",
+      "charge error 0.21 outside atol 0.1\n",
+      "measured charge:  1.1496296323915356e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.3703378153899027e-09\n",
+      "fitting image\n",
+      "measured charge:  1.442579736503865e-09\n",
+      "fitting image\n",
+      "measured charge:  1.313782412950085e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 55/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | -0.5 | 0.74 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4401535405394505e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3976041513284733e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3754621862278833e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5592280683873403e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.4654745968629214e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4401301251367083e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 56/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | -0.5 | 0.74 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.8155816991479214e-09\n",
+      "charge error 0.3 outside atol 0.1\n",
+      "measured charge:  1.4929894963078182e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2447303901679429e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.3107366094045548e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2739996436361112e-09\n",
+      "fitting image\n",
+      "measured charge:  1.464186749710299e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3118641511073886e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 57/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | -0.5 | 0.74 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4012641589006113e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3337917752133162e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5569747861665043e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.255903139661054e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.5427436248340908e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.7522790583393098e-09\n",
+      "charge error 0.25 outside atol 0.1\n",
+      "measured charge:  1.3503914945956796e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5918259114192031e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.4380137329628267e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4214500372770768e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 58/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | -0.5 | 0.94 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.7721461270011297e-09\n",
+      "charge error 0.27 outside atol 0.1\n",
+      "measured charge:  1.2714905931695965e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5260574485799573e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5056248078819322e-09\n",
+      "fitting image\n",
+      "measured charge:  1.0048161733399334e-09\n",
+      "charge error 0.28 outside atol 0.1\n",
+      "measured charge:  1.305352867951227e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3718472082764825e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 59/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | -0.5 | 0.94 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4792644679122555e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2039245478712241e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.3259458140990535e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5116767889067126e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2749038384201716e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5434046596662307e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.2221111110877258e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.4342330460071637e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 60/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | -0.5 | 0.94 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.306255261550478e-09\n",
+      "fitting image\n",
+      "measured charge:  1.058475270575049e-09\n",
+      "charge error 0.24 outside atol 0.1\n",
+      "measured charge:  1.6405335515599049e-09\n",
+      "charge error 0.17 outside atol 0.1\n",
+      "measured charge:  1.5177647936281115e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6155907440504936e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.3938955117659555e-09\n",
+      "fitting image\n",
+      "measured charge:  1.173967241798432e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.5117740528874986e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4569910163192158e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 61/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | -0.5 | 1.14 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.369287724634722e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5188689199281936e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1903634272950919e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.3842123421262378e-09\n",
+      "fitting image\n",
+      "measured charge:  1.351138986299635e-09\n",
+      "fitting image\n",
+      "measured charge:  1.315036037590932e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 62/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | -0.5 | 1.14 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.340241818085301e-09\n",
+      "fitting image\n",
+      "measured charge:  1.0299643159198064e-09\n",
+      "charge error 0.26 outside atol 0.1\n",
+      "measured charge:  1.2265942601266303e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.5247696014273888e-09\n",
+      "fitting image\n",
+      "measured charge:  1.470665611539534e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3132636717193676e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4170515439251488e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 63/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | -0.5 | 1.14 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.668545578017591e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.4606510238913512e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6282440674728905e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.4751595676874338e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1799669884631892e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.3785133933278754e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2018675947967332e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.257068506245296e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.3480859780147923e-09\n",
+      "fitting image\n",
+      "measured charge:  1.159988246342015e-09\n",
+      "charge error 0.17 outside atol 0.1\n",
+      "measured charge:  1.210722219415159e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.4158663643077704e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 64/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0 | 0.74 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3741221047152625e-09\n",
+      "fitting image\n",
+      "measured charge:  1.313018710582652e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5472501892757695e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.2179827954600854e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.327810040396867e-09\n",
+      "fitting image\n",
+      "measured charge:  1.415027012177541e-09\n",
+      "fitting image\n",
+      "measured charge:  1.313209636174504e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 65/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0 | 0.74 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.289949135295239e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3238150124465506e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2122009921596156e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.2176477750819318e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.1876238251704946e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.088585677358308e-09\n",
+      "charge error 0.22 outside atol 0.1\n",
+      "measured charge:  1.4789906878182884e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7219290939738875e-09\n",
+      "charge error 0.23 outside atol 0.1\n",
+      "measured charge:  1.3102538918704389e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2955976509184005e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 66/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0 | 0.74 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.1395574068288151e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.4359855988456136e-09\n",
+      "fitting image\n",
+      "measured charge:  1.211633618938518e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.37230290803814e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4027339257209264e-09\n",
+      "fitting image\n",
+      "measured charge:  1.418180886812825e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3650297236994147e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 67/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0 | 0.94 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3273453347110325e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4715373849966717e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5021088950960686e-09\n",
+      "fitting image\n",
+      "measured charge:  1.0294437735042762e-09\n",
+      "charge error 0.26 outside atol 0.1\n",
+      "measured charge:  1.1213276151764353e-09\n",
+      "charge error 0.2 outside atol 0.1\n",
+      "measured charge:  2.0798083087951996e-09\n",
+      "charge error 0.49 outside atol 0.1\n",
+      "measured charge:  1.5791779915512623e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.515574552876298e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5292113232151894e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 68/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0 | 0.94 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4776488051208175e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1624756825906216e-09\n",
+      "charge error 0.17 outside atol 0.1\n",
+      "measured charge:  1.1893331495730336e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.2077664751110727e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.6542819953582136e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.2527240484381993e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.417554074492396e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6147351812568385e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.6162968085034234e-09\n",
+      "charge error 0.15 outside atol 0.1\n",
+      "measured charge:  1.5313511307918666e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7968007449378977e-09\n",
+      "charge error 0.28 outside atol 0.1\n",
+      "measured charge:  1.302287251372618e-09\n",
+      "fitting image\n",
+      "measured charge:  1.104747708827228e-09\n",
+      "charge error 0.21 outside atol 0.1\n",
+      "measured charge:  1.2361927740793888e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.732179636834611e-09\n",
+      "charge error 0.24 outside atol 0.1\n",
+      "measured charge:  1.4869645330554345e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 69/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0 | 0.94 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.275004704770606e-09\n",
+      "fitting image\n",
+      "measured charge:  1.402625854631174e-09\n",
+      "fitting image\n",
+      "measured charge:  1.552374560113702e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.5476248357201722e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.3075124885609933e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5150233903186548e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4185123048212967e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 70/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0 | 1.14 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.2007652696814796e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.417997165960277e-09\n",
+      "fitting image\n",
+      "measured charge:  1.0655791435398856e-09\n",
+      "charge error 0.24 outside atol 0.1\n",
+      "measured charge:  9.665265862490735e-10\n",
+      "charge error 0.31 outside atol 0.1\n",
+      "measured charge:  1.3063597302705307e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5691652050878808e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.1146848455277632e-09\n",
+      "charge error 0.2 outside atol 0.1\n",
+      "measured charge:  1.371450947614137e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4026222522615165e-09\n",
+      "fitting image\n",
+      "measured charge:  1.397571730001564e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 71/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0 | 1.14 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3148379072597708e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2822832926638173e-09\n",
+      "fitting image\n",
+      "measured charge:  1.380071418204799e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5002446687982607e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7288168247592376e-09\n",
+      "charge error 0.23 outside atol 0.1\n",
+      "measured charge:  1.8441502917176982e-09\n",
+      "charge error 0.32 outside atol 0.1\n",
+      "measured charge:  1.4322427367713187e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 72/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0 | 1.14 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.2858514398097045e-09\n",
+      "fitting image\n",
+      "measured charge:  1.47347726105732e-09\n",
+      "fitting image\n",
+      "measured charge:  1.173154907440627e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.3712870397946904e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5443556852558723e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.4511803940614405e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4094343332840789e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 73/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0.5 | 0.74 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.2021107547486135e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.5914044341692597e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.2851093516602314e-09\n",
+      "fitting image\n",
+      "measured charge:  1.166454499877451e-09\n",
+      "charge error 0.17 outside atol 0.1\n",
+      "measured charge:  1.2583851723551443e-09\n",
+      "charge error 0.1 outside atol 0.1\n",
+      "measured charge:  1.5583815115177985e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.601768451674198e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.3115597508713166e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4895816546117092e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3670470507076624e-09\n",
+      "fitting image\n",
+      "measured charge:  1.1716923453596566e-09\n",
+      "charge error 0.16 outside atol 0.1\n",
+      "measured charge:  1.4234673642853695e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 74/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0.5 | 0.74 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.2640985306321406e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4662256909365331e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3456075476903352e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3008751224668058e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5790501074284242e-09\n",
+      "charge error 0.13 outside atol 0.1\n",
+      "measured charge:  1.1997385943290789e-09\n",
+      "charge error 0.14 outside atol 0.1\n",
+      "measured charge:  1.5585256063041246e-09\n",
+      "charge error 0.11 outside atol 0.1\n",
+      "measured charge:  1.3255513546215136e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 75/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0.5 | 0.74 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3430192450913226e-09\n",
+      "fitting image\n",
+      "measured charge:  1.0473061234515944e-09\n",
+      "charge error 0.25 outside atol 0.1\n",
+      "measured charge:  1.3498115130807951e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3761142151359078e-09\n",
+      "fitting image\n",
+      "measured charge:  1.132323848556312e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.0465208068662464e-09\n",
+      "charge error 0.25 outside atol 0.1\n",
+      "measured charge:  1.4430624540380182e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3565713597433038e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 76/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0.5 | 0.94 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.348750615216605e-09\n",
+      "fitting image\n",
+      "measured charge:  1.040373363045508e-09\n",
+      "charge error 0.26 outside atol 0.1\n",
+      "measured charge:  1.2833964248880389e-09\n",
+      "fitting image\n",
+      "measured charge:  1.411887547020941e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3470737121409946e-09\n",
+      "fitting image\n",
+      "measured charge:  1.332024812896281e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 77/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0.5 | 0.94 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3142831423324715e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5150882329724776e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3004842653589769e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7046107018448663e-09\n",
+      "charge error 0.22 outside atol 0.1\n",
+      "measured charge:  1.352707818285493e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2984597336113834e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 78/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0.5 | 0.94 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.4215995356179025e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4224767126295057e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5695416527171403e-09\n",
+      "charge error 0.12 outside atol 0.1\n",
+      "measured charge:  1.3742842113498676e-09\n",
+      "fitting image\n",
+      "measured charge:  1.518344775143007e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3195786257291817e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 79/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0.5 | 1.14 | -0.809\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.669049909769638e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.7359783356386115e-09\n",
+      "charge error 0.24 outside atol 0.1\n",
+      "measured charge:  1.4478500033129724e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4154845131240566e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4228279436711168e-09\n",
+      "fitting image\n",
+      "measured charge:  1.0058572581709915e-09\n",
+      "charge error 0.28 outside atol 0.1\n",
+      "measured charge:  1.3540857246795377e-09\n",
+      "fitting image\n",
+      "measured charge:  1.293540697843899e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 80/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0.5 | 1.14 | -0.609\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.1354471030494908e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.6527257716661375e-09\n",
+      "charge error 0.18 outside atol 0.1\n",
+      "measured charge:  1.456394824140845e-09\n",
+      "fitting image\n",
+      "measured charge:  1.6907433798478354e-09\n",
+      "charge error 0.21 outside atol 0.1\n",
+      "measured charge:  1.3596153621039834e-09\n",
+      "fitting image\n",
+      "measured charge:  1.8492476447832352e-09\n",
+      "charge error 0.32 outside atol 0.1\n",
+      "measured charge:  1.4095424043738314e-09\n",
+      "fitting image\n",
+      "measured charge:  1.4671767165261206e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7964801340383395e-09\n",
+      "charge error 0.28 outside atol 0.1\n",
+      "measured charge:  1.363161895031947e-09\n",
+      "fitting image\n",
+      "\u001b[1m\n",
+      "Step 81/81\n",
+      "et1h | et1v | dt7h | dt7v\n",
+      " 0.5 | 0.5 | 1.14 | -0.409\n",
+      "-----------------------------\n",
+      "\u001b[0m\n",
+      "measured charge:  1.3847725106079976e-09\n",
+      "fitting image\n",
+      "measured charge:  1.7575763429208795e-09\n",
+      "charge error 0.26 outside atol 0.1\n",
+      "measured charge:  1.6683996820464113e-09\n",
+      "charge error 0.19 outside atol 0.1\n",
+      "measured charge:  1.9456326473425512e-09\n",
+      "charge error 0.39 outside atol 0.1\n",
+      "measured charge:  1.5030022827711989e-09\n",
+      "fitting image\n",
+      "measured charge:  1.5076187194874337e-09\n",
+      "fitting image\n",
+      "measured charge:  1.2724164021715825e-09\n",
+      "fitting image\n",
+      "measured charge:  1.3246471598374672e-09\n",
+      "fitting image\n"
+     ]
+    }
+   ],
+   "source": [
+    "##Transfer Matrix##\n",
+    "\n",
+    "et1hs = [-0.5, 0, 0.5]\n",
+    "et1vs = [-0.5, 0, 0.5]\n",
+    "dt7hs = [0.74, 0.94, 1.14]\n",
+    "dt7vs = [-.809, -0.609, -0.409]\n",
+    "i = 0\n",
+    "end = 3*3*3*3\n",
+    "\n",
+    "screen = \"DYG7\"\n",
+    "target_charge = 1.4e-9\n",
+    "n_shots = 5\n",
+    "\n",
+    "for et1h in et1hs:\n",
+    "    for et1v in et1vs:\n",
+    "        for dt7h in dt7hs:\n",
+    "            for dt7v in dt7vs:\n",
+    "                i = i+1\n",
+    "                print('\\033[1m')\n",
+    "                print(f\"Step {i}/{end}\\net1h | et1v | dt7h | dt7v\\n {et1h} | {et1v} | {dt7h} | {dt7v}\") \n",
+    "                print(\"-----------------------------\")\n",
+    "                print('\\033[0m')\n",
+    "                Datafolder = f\"./Data/2024_07_11/{screen}/e1h_{et1h}_et1v_{et1v}_dt7h_{dt7h}_dt7v_{dt7v}/\"\n",
+    "                if os.path.exists(Datafolder):\n",
+    "                    continue    \n",
+    "                else:\n",
+    "                    os.system(\"mkdir \"+Datafolder)\n",
+    "                caput(\"AWA:EEXBL:ET1H_B_N:Ctrl\",et1h)\n",
+    "                caput(\"AWA:EEXBL:ET1V_B_N:Ctrl\",et1v)\n",
+    "                caput(\"AWA:Drive:DT7H_B_S:Ctrl\",dt7h)\n",
+    "                caput(\"AWA:Drive:DT7V_B_S:Ctrl\",dt7v)\n",
+    "                time.sleep(1)\n",
+    "                TakeScreenData(screen, Datafolder,target_charge, n_shots)\n",
+    "            "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
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+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
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+ },
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+ "nbformat_minor": 5
+}