{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Strain Mapping"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This tutorial demonstrates different routes to obtain strain maps from scanning electron diffraction data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code functionality is illustrated using synthetic data, which is first generated using pyxem. This synthetic data represents a simple cubic crystal that is distorted to a tetragonal stucture. The intention is for this to provide an easy to understand illustration of the code functionality rather than to model any physical system."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This functionaility has been checked to run in pyxem-0.15.0 (April 2023). Bugs are always possible, do not trust the code blindly, and if you experience any issues please report them here: https://github.com/pyxem/pyxem-demos/issues"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Contents"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. <a href='#gen'> Setting up & Creating Synthetic Data</a>\n",
    "2. <a href='#aff'> Image Affine Transform Based Mapping</a>\n",
    "3. <a href='#vec'> Vector Based Mapping</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <a id='gen'></a> 1. Setting up & Creating Synthetic Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import pyxem and other required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:silx.opencl.common:Unable to import pyOpenCl. Please install it from: https://pypi.org/project/pyopencl\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import pyxem as pxm\n",
    "import numpy as np\n",
    "import hyperspy.api as hs\n",
    "import diffpy.structure\n",
    "from matplotlib import pyplot as plt\n",
    "from pyxem.generators.indexation_generator import IndexationGenerator\n",
    "from diffsims.generators.diffraction_generator import DiffractionGenerator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hs.set_log_level('ERROR') # removes Warnings from hyperspy."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define a structure for the creation of synthetic data.  We will start by showing how changing\n",
    "the lattice parameter changes the diffraction spots. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "latt = diffpy.structure.lattice.Lattice(3,3,3,90,90,90)\n",
    "atom = diffpy.structure.atom.Atom(atype='Ni',xyz=[0,0,0],lattice=latt)\n",
    "structure = diffpy.structure.Structure(atoms=[atom],lattice=latt)\n",
    "\n",
    "latt = diffpy.structure.lattice.Lattice(3.2,3.2,3,90,90,90)\n",
    "atom = diffpy.structure.atom.Atom(atype='Ni',xyz=[0,0,0],lattice=latt)\n",
    "structure2 = diffpy.structure.Structure(atoms=[atom],lattice=latt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Simulate an electron diffraction pattern.  This just calculates the electron diffraction spots which should be visable based on the paramters given.  We simulate a 300 keV beam here. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ediff = DiffractionGenerator(300.)\n",
    "diffraction = ediff.calculate_ed_data(structure,\n",
    "                                      reciprocal_radius=5.,\n",
    "                                      max_excitation_error=0.025, shape_factor_width=5.0,\n",
    "                                      with_direct_beam=False)\n",
    "strained_diffraction = ediff.calculate_ed_data(structure2,\n",
    "                                               reciprocal_radius=5.,\n",
    "                                               max_excitation_error=0.025, shape_factor_width=5.0,\n",
    "                                               with_direct_beam=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check we have some spots. Notice that the material is strained in both x,y so the diffraction spots are all at smaller reciporical spacing. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x17d5fa2d0>"
      ]
     },
     "execution_count": null,
     "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"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "fig, ax = plt.subplots(1,1,)\n",
    "diffraction.plot(ax=ax, label=\"Unstrained Material\")\n",
    "strained_diffraction.plot(ax=ax, label=\"Strained Material\")\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We define a \"detector\" configuration here so that we can simulate the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "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 640x581.818 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "diffraction.calibration = 1e-2\n",
    "pattern = diffraction.get_diffraction_pattern(shape = (128,128),\n",
    "                                              sigma = 0)\n",
    "\n",
    "strained_diffraction.calibration = 1e-2\n",
    "pattern2 = strained_diffraction.get_diffraction_pattern(shape = (128,128),\n",
    "                                              sigma = 0)\n",
    "pxm.signals.Diffraction2D([pattern, pattern2]).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define a distorted structure and simulate diffraction.  Note that this structure is fairly unphysical but it does give us something to fit to."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x17d8c7dd0>"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhYAAAENCAYAAABTviwWAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAAATpklEQVR4nO3df4xUd90v8M+ylOGHy2rhgXRl+ZWnkcraQAFzW7Bq2tAINTYmjTag2FafolBAEqXYqikVNk1MQ2JlzRJDMMiPmMAjGrRiDW1JW0uX0labgEgtm1LCUzW7VJJtgXP/uLfcu7bADnxnZs/M65WcP3qyc+adBt55c2Z2pi7LsiwAABIYUOkAAED1MCwAgGQMCwAgGcMCAEjGsAAAkjEsAIBkDAsAIBnDAgBIZmC5n/Ds2bNx7NixaGhoiLq6unI/PdS8LMvi5MmT0dTUFAMG5OPfFnoDKq+v3VH2YXHs2LFobm4u99MC/6azszPGjBlT6Rh9ojeg/7hYd5R9WDQ0NERExKyYEwPjinI/PdS80/FO7I1d5/4u5oHegMrra3eUfVi8extzYFwRA+sUBJTd//12oDy9pKA3oB/oY3fk4wVWACAXDAsAIBnDAgBIxrAAAJK5pGGxbt26mDBhQgwePDimTZsWTz31VOpcQJXRG1Abih4W27Zti2XLlsX9998fL7zwQnziE5+Iz3zmM3H06NFS5AOqgN6A2lH0sHjkkUfi7rvvjq9+9atxzTXXxNq1a6O5uTna2tpKkQ+oAnoDakdRw+Ltt9+Ojo6OmD17dq/zs2fPjqeffvp9H9PT0xPd3d29DqB26A2oLUUNizfffDPOnDkTo0eP7nV+9OjRcfz48fd9TGtrazQ2Np47fCwv1Ba9AbXlkt68+e+fupVl2Xk/iWvlypXR1dV17ujs7LyUpwRyTm9AbSjqI71HjhwZ9fX17/lXxokTJ97zr5F3FQqFKBQKl54QyDW9AbWlqDsWgwYNimnTpsXu3bt7nd+9e3fccMMNSYMB1UFvQG0p+kvIli9fHl/60pdi+vTpcf3110d7e3scPXo0Fi5cWIp8QBXQG1A7ih4WX/jCF+Lvf/97rFq1Kt54441oaWmJXbt2xbhx40qRD6gCegNqR12WZVk5n7C7uzsaGxvjU/E5X38MFXA6eyf2xC+jq6srhg8fXuk4faI3oPL62h2+KwQASMawAACSMSwAgGQMCwAgGcMCAEjGsAAAkjEsAIBkDAsAIBnDAgBIxrAAAJIxLACAZAwLACAZwwIASMawAACSMSwAgGQMCwAgGcMCAEjGsAAAkjEsAIBkDAsAIBnDAgBIxrAAAJIxLACAZAwLACAZwwIASMawAACSGVjpAEQ8duxApSNwmW5pmlLpCNSYrl3/WZLrvvPf/1GS60ZEjGx/pmTXfvO/ri/Jda+47X9Kct2IiMY5h0t27UpyxwIASMawAACSMSwAgGQMCwAgGcMCAEjGsAAAkjEsAIBkihoWra2tMWPGjGhoaIhRo0bFbbfdFgcPHixVNqBK6A6oHUUNiyeeeCIWLVoUzz77bOzevTtOnz4ds2fPjn/961+lygdUAd0BtaOoT9787W9/2+u/N2zYEKNGjYqOjo648cYbkwYDqofugNpxWR/p3dXVFRERV1555Xl/pqenJ3p6es79d3d39+U8JVAFLtYdegPy65LfvJllWSxfvjxmzZoVLS0t5/251tbWaGxsPHc0Nzdf6lMCVaAv3aE3IL8ueVgsXrw4XnrppdiyZcsFf27lypXR1dV17ujs7LzUpwSqQF+6Q29Afl3SSyH33ntv7Ny5M5588skYM2bMBX+2UChEoVC4pHBAdelrd+gNyK+ihkWWZXHvvffGjh07Ys+ePTFhwoRS5QKqiO6A2lHUsFi0aFFs3rw5fvnLX0ZDQ0McP348IiIaGxtjyJAhJQkI5J/ugNpR1Hss2traoqurKz71qU/FVVddde7Ytm1bqfIBVUB3QO0o+qUQgGLpDqgdvisEAEjGsAAAkjEsAIBkDAsAIJnL+q6QWtK16z9Ldu3/daB016ZMdpXmso1zDpfmwpTFY8cOlOzaeiP/SvXn45amKSW5bl+5YwEAJGNYAADJGBYAQDKGBQCQjGEBACRjWAAAyRgWAEAyhgUAkIxhAQAkY1gAAMkYFgBAMoYFAJCMYQEAJGNYAADJGBYAQDKGBQCQjGEBACRjWAAAyRgWAEAyhgUAkIxhAQAkM7DSAfLinf/+j0pHoCYdrnQAgKK4YwEAJGNYAADJGBYAQDKGBQCQjGEBACRjWAAAyRgWAEAylzUsWltbo66uLpYtW5YoDlDt9AZUt0seFvv27Yv29va49tprU+YBqpjegOp3ScPirbfeinnz5sX69evjQx/6UOpMQBXSG1AbLmlYLFq0KObOnRs333zzRX+2p6cnuru7ex1A7dEbUBuK/q6QrVu3xv79+2Pfvn19+vnW1tZ48MEHiw4GVA+9AbWjqDsWnZ2dsXTp0ti0aVMMHjy4T49ZuXJldHV1nTs6OzsvKSiQT3oDaktRdyw6OjrixIkTMW3atHPnzpw5E08++WQ8+uij0dPTE/X19b0eUygUolAopEkL5I7egNpS1LC46aab4uWXX+517s4774xJkybFihUr3lMOAHoDaktRw6KhoSFaWlp6nRs2bFiMGDHiPecBIvQG1BqfvAkAJFP0b4X8uz179iSIAdQSvQHVyx0LACAZwwIASMawAACSMSwAgGQu+82btWJk+zOVjgAA/Z47FgBAMoYFAJCMYQEAJGNYAADJGBYAQDKGBQCQjGEBACRjWAAAyRgWAEAyhgUAkIxhAQAkY1gAAMkYFgBAMoYFAJCMYQEAJGNYAADJGBYAQDKGBQCQjGEBACRjWAAAyRgWAEAyhgUAkMzASgfIizf/6/pKR6AGjWx/ptIRAIrijgUAkIxhAQAkY1gAAMkYFgBAMoYFAJCMYQEAJFP0sHj99ddj/vz5MWLEiBg6dGhMmTIlOjo6SpENqCK6A2pDUZ9j8c9//jNmzpwZn/70p+M3v/lNjBo1Kv7617/GBz/4wRLFA6qB7oDaUdSwePjhh6O5uTk2bNhw7tz48eNTZwKqjO6A2lHUSyE7d+6M6dOnx+233x6jRo2KqVOnxvr16y/4mJ6enuju7u51ALWl2O7QG5BfRQ2LI0eORFtbW1x99dXx2GOPxcKFC2PJkiXxs5/97LyPaW1tjcbGxnNHc3PzZYcG8qXY7tAbkF9FDYuzZ8/GddddF2vWrImpU6fGPffcE1/72teira3tvI9ZuXJldHV1nTs6OzsvOzSQL8V2h96A/CpqWFx11VXx0Y9+tNe5a665Jo4ePXrexxQKhRg+fHivA6gtxXaH3oD8KmpYzJw5Mw4ePNjr3KFDh2LcuHFJQwHVRXdA7ShqWHzzm9+MZ599NtasWROHDx+OzZs3R3t7eyxatKhU+YAqoDugdhQ1LGbMmBE7duyILVu2REtLSzz00EOxdu3amDdvXqnyAVVAd0DtKOpzLCIibr311rj11ltLkQWoYroDaoPvCgEAkjEsAIBkDAsAIBnDAgBIpug3b9aqK277n0pHoBa1VzoAQHHcsQAAkjEsAIBkDAsAIBnDAgBIxrAAAJIxLACAZAwLACAZwwIASMawAACSMSwAgGQMCwAgGcMCAEjGsAAAkjEsAIBkDAsAIBnDAgBIxrAAAJIxLACAZAwLACAZwwIASMawAACSMSwAgGQGVjpAXjTOOVyyaz927EDJrk153NI0pdIR6IdK+udiV+kuTXlUa2+4YwEAJGNYAADJGBYAQDKGBQCQjGEBACRjWAAAyRQ1LE6fPh0PPPBATJgwIYYMGRITJ06MVatWxdmzZ0uVD6gCugNqR1GfY/Hwww/HT37yk9i4cWNMnjw5nn/++bjzzjujsbExli5dWqqMQM7pDqgdRQ2LZ555Jj73uc/F3LlzIyJi/PjxsWXLlnj++edLEg6oDroDakdRL4XMmjUrHn/88Th06FBERLz44ouxd+/emDNnznkf09PTE93d3b0OoLYU2x16A/KrqDsWK1asiK6urpg0aVLU19fHmTNnYvXq1XHHHXec9zGtra3x4IMPXnZQIL+K7Q69AflV1B2Lbdu2xaZNm2Lz5s2xf//+2LhxY/zwhz+MjRs3nvcxK1eujK6urnNHZ2fnZYcG8qXY7tAbkF9F3bH41re+Fffdd1988YtfjIiIj33sY/Haa69Fa2trLFiw4H0fUygUolAoXH5SILeK7Q69AflV1B2LU6dOxYABvR9SX1/vV8aAC9IdUDuKumPx2c9+NlavXh1jx46NyZMnxwsvvBCPPPJI3HXXXaXKB1QB3QG1o6hh8aMf/Si++93vxje+8Y04ceJENDU1xT333BPf+973SpUPqAK6A2pHUcOioaEh1q5dG2vXri1RHKAa6Q6oHb4rBABIxrAAAJIxLACAZAwLACCZot68SWnc0jSl0hGAnGmcc7hEVy7VdUtrZPszpblwe2kuW83csQAAkjEsAIBkDAsAIBnDAgBIxrAAAJIxLACAZAwLACAZwwIASMawAACSMSwAgGQMCwAgGcMCAEjGsAAAkjEsAIBkDAsAIBnDAgBIxrAAAJIxLACAZAwLACAZwwIASMawAACSGVjuJ8yyLCIiTsc7EVm5nx04He9ExP/7u5gHegMqr6/dUfZhcfLkyYiI2Bu7yv3UwP/n5MmT0djYWOkYfaI3oP+4WHfUZWX+Z8vZs2fj2LFj0dDQEHV1dRf82e7u7mhubo7Ozs4YPnx4mRJeHpnLQ+ZLl2VZnDx5MpqammLAgHy8GlrtvRGRz9wyl0d/ydzX7ij7HYsBAwbEmDFjinrM8OHDc/MH4F0yl4fMlyYvdyreVSu9EZHP3DKXR3/I3JfuyMc/VwCAXDAsAIBk+vWwKBQK8f3vfz8KhUKlo/SZzOUhM+eT1//Pecwtc3nkLXPZ37wJAFSvfn3HAgDIF8MCAEjGsAAAkjEsAIBk+u2wWLduXUyYMCEGDx4c06ZNi6eeeqrSkS6otbU1ZsyYEQ0NDTFq1Ki47bbb4uDBg5WO1Wetra1RV1cXy5Ytq3SUi3r99ddj/vz5MWLEiBg6dGhMmTIlOjo6Kh3rvE6fPh0PPPBATJgwIYYMGRITJ06MVatWxdmzZysdrSrlqTvy3hsR+ekOvVFGWT+0devW7IorrsjWr1+fvfLKK9nSpUuzYcOGZa+99lqlo53XLbfckm3YsCH705/+lB04cCCbO3duNnbs2Oytt96qdLSLeu6557Lx48dn1157bbZ06dJKx7mgf/zjH9m4ceOyr3zlK9kf//jH7NVXX81+//vfZ4cPH650tPP6wQ9+kI0YMSL79a9/nb366qvZL37xi+wDH/hAtnbt2kpHqzp5644890aW5ac79EZ59cth8fGPfzxbuHBhr3OTJk3K7rvvvgolKt6JEyeyiMieeOKJSke5oJMnT2ZXX311tnv37uyTn/xkvy6HLMuyFStWZLNmzap0jKLMnTs3u+uuu3qd+/znP5/Nnz+/QomqV967Iy+9kWX56g69UV797qWQt99+Ozo6OmL27Nm9zs+ePTuefvrpCqUqXldXV0REXHnllRVOcmGLFi2KuXPnxs0331zpKH2yc+fOmD59etx+++0xatSomDp1aqxfv77SsS5o1qxZ8fjjj8ehQ4ciIuLFF1+MvXv3xpw5cyqcrLpUQ3fkpTci8tUdeqO8yv4lZBfz5ptvxpkzZ2L06NG9zo8ePTqOHz9eoVTFybIsli9fHrNmzYqWlpZKxzmvrVu3xv79+2Pfvn2VjtJnR44ciba2tli+fHl85zvfieeeey6WLFkShUIhvvzlL1c63vtasWJFdHV1xaRJk6K+vj7OnDkTq1evjjvuuKPS0apK3rsjL70Rkb/u0Bvl1e+Gxbv+/auRsyy76Ncl9xeLFy+Ol156Kfbu3VvpKOfV2dkZS5cujd/97ncxePDgSsfps7Nnz8b06dNjzZo1ERExderU+POf/xxtbW39tiC2bdsWmzZtis2bN8fkyZPjwIEDsWzZsmhqaooFCxZUOl7VyWt35KE3IvLZHXqjzCr7Ssx79fT0ZPX19dn27dt7nV+yZEl24403VihV3y1evDgbM2ZMduTIkUpHuaAdO3ZkEZHV19efOyIiq6ury+rr67PTp09XOuL7Gjt2bHb33Xf3Ordu3bqsqampQokubsyYMdmjjz7a69xDDz2UfeQjH6lQouqU5+7IS29kWT67Q2+UV797j8WgQYNi2rRpsXv37l7nd+/eHTfccEOFUl1clmWxePHi2L59e/zhD3+ICRMmVDrSBd10003x8ssvx4EDB84d06dPj3nz5sWBAweivr6+0hHf18yZM9/z63iHDh2KcePGVSjRxZ06dSoGDOj9V62+vj4fvzaWI3nsjrz1RkQ+u0NvlFmll837efdXxn76059mr7zySrZs2bJs2LBh2d/+9rdKRzuvr3/961ljY2O2Z8+e7I033jh3nDp1qtLR+qy/v7M7y/7Pr7cNHDgwW716dfaXv/wl+/nPf54NHTo027RpU6WjndeCBQuyD3/4w+d+bWz79u3ZyJEjs29/+9uVjlZ18tYd1dAbWdb/u0NvlFe/HBZZlmU//vGPs3HjxmWDBg3Krrvuun7/61cR8b7Hhg0bKh2tz/p7ObzrV7/6VdbS0pIVCoVs0qRJWXt7e6UjXVB3d3e2dOnSbOzYsdngwYOziRMnZvfff3/W09NT6WhVKU/dUQ29kWX56A69UT6+Nh0ASKbfvccCAMgvwwIASMawAACSMSwAgGQMCwAgGcMCAEjGsAAAkjEsAIBkDAsAIBnDAgBIxrAAAJIxLACAZP43tQaPoFCiiHQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from skimage.draw import disk\n",
    "distortion_x = np.zeros((10, 10))\n",
    "distortion_y = np.zeros((10, 10))\n",
    "\n",
    "xx, yy = disk(center=(5, 5), radius=4, shape=(20, 20))\n",
    "\n",
    "distortion_x[xx,yy]= np.abs(np.abs(xx-10)-5)\n",
    "distortion_y[xx,yy]= np.abs(np.abs(yy-10)-5)\n",
    "\n",
    "fig, axs = plt.subplots(1, 2)\n",
    "axs[0].imshow(distortion_x)\n",
    "axs[1].imshow(distortion_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed | 107.51 ms\n"
     ]
    }
   ],
   "source": [
    "data = np.empty((10,10,128,128))\n",
    "\n",
    "for ind in np.ndindex((10,10)):\n",
    "    dx = distortion_x[ind]*.1\n",
    "    dy = distortion_y[ind]*.1\n",
    "    latt = diffpy.structure.lattice.Lattice(3+dx,3+dy,3,90,90,90)\n",
    "    atom = diffpy.structure.atom.Atom(atype='Ni',xyz=[0,0,0],lattice=latt)\n",
    "    structure = diffpy.structure.Structure(atoms=[atom],lattice=latt)\n",
    "    diffraction = ediff.calculate_ed_data(structure, reciprocal_radius=5.,\n",
    "                                          max_excitation_error=0.025,\n",
    "                                          with_direct_beam=True)\n",
    "    diffraction.calibration = 1e-2\n",
    "    data[ind] = diffraction.get_diffraction_pattern((128,128),sigma=4)\n",
    "\n",
    "dp = pxm.signals.ElectronDiffraction2D(data)\n",
    "\n",
    "dp = dp.shift_diffraction(7,8) #shifting diffraction patterns to simulate real_effects\n",
    "\n",
    "dp = dp+np.random.random((10,10,128,128))*.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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GAABgESz+BwAAhpGYmYPEDAAAwCJIzAAAgGEkZuYgMQMAALAIEjMAAGAYiZk5SMwAAAAsgsQMAAAYRmJmDhIzAAAAiyAxAwAAhpGYmYPEDAAAwCJozAAAACyCqUwAAGAYU5nmIDEDAACwCBIzAABgGImZOUjMAAAALILEDAAAmKK2p1k1gcQMAADAIkjMAACAYawxMweJGQAAgEWQmAEAAMNIzMxBYgYAAGARJGYAAMAwEjNzkJgBAABYBIkZAAAwjMTMHCRmAAAAFkFjBgAAYBFMZQIAAMOYyjQHiRkAAIBFkJgBAADDSMzMQWIGAABgESRmAADAMBIzc7icmGVkZOibb75xvE9NTdVdd92lJ598UmfOnDG1OAAAgLrE5cZs+PDh2rdvnyTpxx9/1L333qvAwEAtWrRIycnJphcIAACs71xiVhOv2szlxmzfvn1q27atJGnRokXq1KmT3nvvPc2bN0+LFy82uz4AAIA6w+U1Zna7XeXl5ZKkVatWqVevXpKkiIgI5eXlmVsdAADwCqwxM4fLidl1112nF154Qe+8847Wrl2r22+/XZKUlZWl8PBw0wsEAACoK1xOzKZOnar7779fS5cu1VNPPaWWLVtKkj766CN17NjR9AIBAID1kZiZw+XGLC4uzumuzHNefvll+fr6mlIUAABAXWTac8wCAgLMuhQAAECdVKXGrFGjRtq3b5/CwsLUsGFD2Wy28x57/Phx04oDAADegalMc1SpMXvttdcUHBzs+PWFGjMAAAC4p0qN2YABAxy/HjhwYHXVAgAAvBSJmTlcflzGnDlzKt1+9uxZjR8/3nBBAAAAdZXLjdmYMWPUp08fp7Vke/fuVfv27fXhhx+aWhwAAPAOfCWTOVxuzLZv364jR47o6quv1hdffKHXX39d1157ra666irt2LGjGkoEAACoG1x+XMbll1+uL7/8UklJSerevbt8fX319ttv695773XpOmVlZa4ObRne/Ly2801Fe4v9+/d7ugS3bdmyxdMluO3IkSOeLsGQkJAQT5fgtsDAQE+X4LZzN415q9qezJiNNWbmcDkxk6S0tDS9//776tixoxo0aKA333xTOTk5ZtcGAABQp7jcmA0fPlx9+/ZVcnKyvvzyS+3atUv16tXT1VdfzRozAADqKNaYmcPlqcwNGzZoy5YtuuaaayRJTZo00bJly/T666/rwQcfVN++fU0vEgAAoC5wuTH7+uuvVa9evQrbH3nkEXXp0sWUogAAgHdhjZk5XJ7KrKwpO6dVq1aGigEAAKjL3PoS848++kgffvihDh48qDNnzjjty8jIMKUwAADgPUjMzOFyYjZt2jQNGjRIjRs31vbt29W+fXtdcskl+vHHH9WjR4/qqBEAAKBOcLkxe+ONNzR79mzNmDFD/v7+Sk5O1hdffKFRo0apsLCwOmoEAACoE1xuzA4ePKiOHTtKkurXr6+TJ09KkhITE/X++++bWx0AAPAaPCrDOJcbsyZNmig/P1+S1KJFC23evFmSlJWVVSd+YAAAANXF5cbs1ltv1aeffipJGjx4sJKSknTbbbepX79+uvvuu00vEAAAWB8PmDWHy3dlzp49W+Xl5ZKkhx56SI0aNdL69ev1P//zP3rooYdMLxAAAKCucLkx8/HxkY/P/wVtffv25Wn/AADUcTwuwxxufYk5AAAAzOfWA2YBAAB+j8TMHCRmAAAAFkFiBgAADCMxM4dbj8s4ceJEhe1FRUW69dZbzagJAACgTnK5MUtPT6/wxeWSdPr0aa1bt86UogAAgHex6nPMpk+frvDwcPn6+spms2n8+PGOfSUlJerQoYMCAgJks9nk6+urmJgYZWRkOF2jqKhIcXFx8vHxkc1mU5MmTbR161anY7KyshQdHS2bzSabzabo6GgdOHDA5Z9jlacyd+3a5fj17t27lZub63hfVlamFStWqFmzZi4XAAAAUF0KCgoUGxurAQMG6OWXX3bal5eXp/379+vhhx9W165dlZ2drdGjR+umm25ScXGx47j4+Hjt3btXL730kiIiIjRixAh16tRJhYWF8vf3lyS1b99eJ0+e1KxZsyRJo0aNUvv27XXkyBGX6q1yY9a2bVtHF1jZlGX9+vU1ffp0lwYHAACoThMmTNCECRMkqUJjFhkZ6fiayXP8/Pw0cOBAbdq0SfHx8Tp48KB2796tUaNGKTk5WZLUqlUr/fWvf9XLL7+sp556SmlpacrLy1NKSooGDx4s6bfnvg4dOlTLly9Xjx49qlxvlacys7KylJmZKbvdrq+++kpZWVmOV3Z2toqKivTggw9WeWAAAFB71PRUZnZ2tg4fPux4FRUVmfI5ziVcERERkqRFixZJkkaPHu045tprr1VAQIBWrlwpSVq8eLEkOZoySRoyZIjT+VVV5cSsRYsWkuT4OiYAAABPadOmjdP7zp07Kz093dA1T5w4oYkTJyoqKkrNmzeXJP3444+SpMsvv9zp2MDAQB09elTSb02in59fhev5+fkpOzvbpRpcXvw/f/58ffbZZ473ycnJatCggTp27OjWIjcAAOD9ajox2717tw4dOuR4ffLJJ4bqLykpUevWrWW326t8M6PNZjPlmN9zuTF78cUXVb9+fUnSpk2bNGPGDE2ZMkVhYWFKSkpy9XIAAAAua9asmZo3b+54hYSEuH2tkpIStWzZUidOnNDOnTsdaZkkRUdHS/ptSdcfz7n00ksdtZSWlla4bmlpqZo2bepSLS43ZocOHVLLli0lSUuXLtU999yjYcOGadKkSTwuAwCAOsqqj8v4M+easuPHjysjI0OxsbFO+xMSEiRJ06ZNc2zbsWOHTp8+ra5du0qS+vTpI0maO3eu45g5c+Y4nV9VLj/5PygoSPn5+YqMjNTKlSsdKVlAQIBOnTrl6uUAAACqTW5urtauXet4v2fPHi1cuFCRkZFq166dYmJidOzYMb333nsqLS11PB4sOjpaQUFBioyMVJs2bTR9+nQ1bdpUzZs31yOPPKKAgACNHTtWktSrVy+FhYVpxIgRKisrkySNHDlSjRs3dumOTMmNxuy2227TkCFD1K5dO+3bt0+33367JOm7775TVFSUq5cDAAC1gFW/kumDDz5wWmqVmpqq1NRUxcTEaN68eY7nsvbr18/pvNdee81xJ+aGDRvUqVMnjRs3Tna7XY0bN9by5csdzzCTpM2bN6tLly4aOnSoJCkqKsqtmxFcbsxef/11Pf300zp06JAWL16sSy65RJL09ddf67777nO5AAAAgOoyevRop0dd/FFVGr0GDRo4PWi/MjExMRXWobnD5casQYMGmjFjRoXtEydONFwMAADwTlZNzLyNy4v/z6ekpERffvmlWZcDAACoc1xOzM7nhx9+0C233OJY9AYAAOoOEjNzmJaYAQAAwJgqJ2aNGjW64H6SMgAA6i4SM3NUuTH79ddf9fDDD+vqq6+udP+BAwe4AQAAAMCAKjdmbdu2VUREhAYMGFDp/p07d9KYAQAAGFDlxuz222/XiRMnzru/UaNG6t+/vxk1AQAAL8NUpjmq3Jg9+eSTF9wfERHh9B1RAAAAcI1pj8sAAAB1F4mZOXhcBgAAgEWQmAEAAMNIzMxBYgYAAGARJGYAAMAwEjNzkJgBAABYRJUSs4YNG8pms1XpgsePHzdUEAAA8D4kZuaoUmM2depUx6/z8/P1wgsvqFu3boqPj5ckbdq0SZ9//rn+8Y9/VEuRAAAAdUGVGrPffw1Tnz599Nxzz+nRRx91bBs1apRmzJihVatWKSkpqUoDN2zY0MVSreOXX37xdAluy8/P93QJhhQXF3u6BLd5c5rs4+Pdqx5OnTrl6RLcVlpa6ukS3Pbzzz97ugRDvP3PvSfU9jSrJrj8p+7zzz9X9+7dK2zv1q2bVq1aZUpRAAAAdZHLjdkll1yijz/+uML2pUuX6pJLLjGlKAAAgLrI5cdlTJw4UYMHD1Z6erpjjdnmzZu1YsUKpaSkmF4gAACwPhb/m8PlxmzgwIFq3bq1pk2bpiVLlshut6tNmzbasGGDOnToUB01AgAA1AluPWC2Q4cOWrBggdm1AAAAL0ViZg63bjnJzMzU008/rb///e86evSoJGnFihX67rvvTC0OAACgLnG5MVu7dq2uvvpqbdmyRYsXL3Y8OmLXrl165plnTC8QAABY37nErCZetZnLjdkTTzyhF154QV988YX8/f0d22+55RZt2rTJ1OIAAADqEpfXmH3zzTd67733Kmy/9NJLvf7hpQAAwD2sMTOHy4lZgwYNKn2a8/bt29WsWTNTigIAAKiLXG7M/v73v2vcuHHKzc2VzWZTeXm5NmzYoP/93/9V//79q6NGAABgcawxM4fLjdk///lPRUZGqlmzZvrll1/Upk0bderUSR07dtTTTz9dHTUCAADUCS6vMfPz89OCBQv03HPPafv27SovL1e7du0UGxtbHfUBAAAvwBozc7j1gFlJiomJUUxMjJm1AAAA1GkuN2Z2u10fffSR1qxZo6NHj6q8vNxp/5IlS0wrDgAAeAcSM3O43Jg99thjmj17tm655RaFh4fLZrNVR10AAAB1jsuN2bvvvqslS5aoZ8+e1VEPAABAneVyYxYaGqro6OjqqAUAAHgppjLN4fLjMp599llNnDhRp06dqo56AAAA6iyXE7OEhAS9//77aty4saKiouTn5+e0PyMjw7TiAACAdyAxM4fLjdnAgQP19ddf64EHHmDxPwAAgIlcbsw+++wzff7557rxxhurox4AAOCFSMzM4fIas4iICIWEhFRHLQAAAHWay43ZK6+8ouTkZP3000/VUA4AAPBGfIm5OVyeynzggQdUUlKimJgYBQYGVlj8f/z4cdOKAwAAqEtcbsymTp1aDWUAAABvxhozc7jcmA0YMKA66gAAAKjzXG7Mfu/UqVMqLS112saNAQAA1D0kZuZwefF/cXGxHn30UTVu3FhBQUFq2LCh0wsAAADucbkxS05O1urVq/XGG2+oXr16SklJ0cSJE9W0aVO9/fbb1VEjAABAneDyVOann36qt99+WzfffLMefPBB3XTTTWrZsqVatGihBQsW6P7776+OOgEAgIUxlWkOlxOz48eP6/LLL5f023qyc4/HuPHGG/Xll1+aWx0AAEAd4nJjFh0d7Xi4bJs2bfThhx9K+i1Ja9CggZm1AQAAL8EDZs3hcmM2aNAg7dy5U5I0fvx4x1qzpKQkjR071vQCAQAA6gqX15glJSU5fn3LLbdo79692rZtm2JiYnTNNdeYWhwAAPAOrDEzh6HnmElSZGSkIiMjzagFAACgTnOrMfvvf/+r//73vzp69KjKy8ud9r311lumFAYAALwHiZk5XG7MJk6cqOeee07XXXedLrvsMtlstuqoCwAAoM5xuTGbOXOm5s2bp8TExOqoBwAAeKnanmbVBJfvyjxz5ow6duxYHbUAAADUaS43ZkOGDNF7771XHbUAAAAvxXPMzOHyVObp06c1e/ZsrVq1SnFxcfLz83Pa/+qrr5pWHAAAQF3icmO2a9cutW3bVpL07bffOu3jRgAAAOom7so0h8uN2Zo1a6qjDgAAgDrP5TVmAAAAqB4uJ2bFxcV66aWXzvuA2R9//NG04gAAgHdgKtMcLjdmQ4YM0dq1a5WYmMgDZgEAAEzkcmO2fPlyffbZZ/p//+//GRr49OnThs73pHr16nm6BLeFhIR4ugRDLrvsMk+X4Lb69et7ugS3lZaWeroEQ7y5/j/OSniT1q1be7oEQw4cOODpErwKiZk5XF5j1rBhQzVq1Kg6agEAAKjTXG7Mnn/+eU2YMEElJSXVUQ8AAPBCPGDWHC5PZb7yyivKzMxUeHi4oqKiKjxgNiMjw7TiAAAA6hKXG7O77rqrGsoAAADejDVm5nC5MXvmmWeqow4AAIA6z+XGDAAA4I9IzMxR5cX/Pj4+8vX1rfBq2LChbrjhBi1ZsqQ66wQAAKj1qpyYffzxx5VuP3HihL766is98MADmj9/vhISEkwrDgAAeAcSM3NUuTG78847z7tvwIABatOmjf71r3/RmAEAALjJtC8x79q1q/bt22fW5QAAAOoc0xb/nzp1SgEBAWZdDgAAeBGmMs1hWmL25ptvql27dmZdDgAAoM6pcmL2+OOPV7q9sLBQ27ZtU2ZmptatW2daYQAAwHuQmJmjyo3Z9u3bK90eEhKi7t27a8SIEWrRooVphQEAANQ1VW7M1qxZU511AAAAL0ZiZg7T1pgBAADAGL6SCQAAGEZiZg4SMwAAAIsgMQMAAIaRmJmDxAwAANRa06dPV3h4uHx9fWWz2TR+/Hin/cnJyQoLC5OPj49sNpsWLlxY4Rq7du1SdHS04xqBgYEaM2aM0zFZWVmKjo6WzWaTzWZTdHS0Dhw44HK9NGYAAMCwc4lZTbxcUVBQoNjY2AqN1DlFRUWKi4tTYmLiea9xyy236OjRo0pJSdGaNWvUsWNHvfrqq3r//fcdx7Rv3145OTmaNWuWZs2apZycHLVv396lWiUaMwAAUItNmDBB69ev15QpUyrdP3PmTK1evVpDhw497zWOHz+uBx54QIMGDdLNN9+sVatWyWaz6fPPP5ckpaWlKS8vT6+//rqGDRumYcOGacaMGTp69KiWL1/uUr00ZgAAwDCrJmZmuOSSS/Txxx8rMzNTZ8+e1ahRo2S329W/f39J0uLFiyVJgwcPdpwzZMgQSdKiRYtcGovF/wAAwOtkZ2erqKjI8T4kJEQhISHVMlZGRoauvfZatWzZ0rFt0qRJuvXWWx21+Pn5VTjPz89P2dnZLo1FYwYAALxOmzZtnN537txZ6enp1TJWr169dPr0aU2ZMkUtWrTQf/7zH40fP16xsbHq06fPBc+12WwujUVjBgAADKvpx2Xs3r1bwcHBju3VlZatXr1a33zzjZYuXao777xTktS3b181atRI//jHP9SnTx81a9ZMpaWlFc4tLS1V06ZNXRqPNWYAAMDrNGvWTM2bN3e8qqsxKygokCT5+vo6bffx8XE0iedSs7lz5zr2z5kzR5KUkJDg0ngkZgAAwDCrPmA2NzdXa9eudbzfs2ePFi5cqMjISMXHxyszM1Pbtm3T3r17JUkbN26UJLVu3VpxcXHq0aOH/Pz8dP/992vq1Klq0aKFXnvtNeXn52vkyJGSfpvqDAsL04gRI1RWViZJGjlypBo3bqwePXq4VC+NGQAAqLU++OADJSUlOd6npqYqNTVVMTEx2r9/vyZNmuRItyRp2rRpmjZtmmPNWmBgoD777DMNHDhQgwcPlt1uV0BAgIYPH65nnnnGcd7mzZvVpUsXx2M3oqKi3FrzRmMGAABMYcWvSxo9erRGjx593v0pKSlKSUm54DVuu+22P727MiYmRllZWe6U6IQ1ZgAAABZBYgYAAAyz6hozb0NiBgAAYBEkZgAAwDASM3OQmAEAAFgEiRkAADCMxMwcJGYAAAAWQWMGAABgEUxlAgAAw5jKNAeJGQAAgEWQmAEAAMNIzMxBYgYAAGARJGYAAMAwEjNzkJgBAABYBIkZAAAwjMTMHCRmAAAAFuGxxCwsLMxTQxtWVFTk6RLcNnz4cE+XYMi3337r6RLcVlpa6ukS3Hb27FlPl2CIv7+/p0twW//+/T1dgttCQkI8XYIhrVq18nQJXoXEzBwkZgAAABbBGjMAAGAYiZk5SMwAAAAsgsQMAAAYRmJmDhIzAAAAi6AxAwAAsAimMgEAgGFMZZqDxAwAAMAiSMwAAIBhJGbmIDEDAACwCBIzAABgGImZOUjMAAAALILEDAAAGEZiZg4SMwAAAIsgMQMAAIaRmJmDxAwAAMAiSMwAAIBhJGbmIDEDAACwCBIzAABgGImZOUjMAAAALILGDAAAwCKYygQAAIYxlWkOEjMAAACLIDEDAACmqO1pVk0gMQMAALAIEjMAAGAYa8zMQWIGAABgESRmAADAMBIzc5CYAQAAWASJGQAAMIzEzBwkZgAAABZBYgYAAAwjMTMHiRkAAIBF0JgBAABYBFOZAADAMKYyzUFiBgAAYBEkZgAAwDASM3OQmAEAAFgEiRkAADCMxMwcJGYAAAAWQWIGAAAMIzEzB4kZAACARZCYAQAAw0jMzEFiBgAAYBEkZgAAwDASM3OQmAEAAFiExxKzvLw8Tw1tWGlpqadLcFtUVJSnSzBk+/btni7BbREREZ4uwW0FBQWeLsGQJk2aeLoEt/n7+3u6BLddc801ni7BkJMnT3q6BK9CYmYOEjMAAACLoDEDAACwCBb/AwAAw5jKNAeJGQAAgEWQmAEAAMNIzMxBYgYAAGARJGYAAMAwEjNzkJgBAABYBIkZAAAwjMTMHCRmAAAAFkFiBgAADCMxMweJGQAAgEWQmAEAAMNIzMxBYgYAAGARNGYAAAAWwVQmAAAwRW2fZqwJJGYAAAAWQWIGAAAMY/G/OUjMAAAALILEDAAAGEZiZg4SMwAAAIsgMQMAAIaRmJmDxAwAANRa06dPV3h4uHx9fWWz2TR+/Hin/cnJyQoLC5OPj49sNpsWLlxY6XVmz56thg0bymazyWazqUGDBjp+/Lhjf1ZWlqKjox37o6OjdeDAAZfrpTEDAACGnUvMauLlioKCAsXGxmrMmDGV7i8qKlJcXJwSExPPe43Zs2dr+PDh6tChg5YuXaqVK1dq8ODBuuii/5t4bN++vXJycjRr1izNmjVLOTk5at++vUu1SkxlAgCAWmzChAmaMGGCJOnll1+usH/mzJmSpPXr1+vtt9+u9BqPP/64brzxRq1YscKx7bbbbnP8Oi0tTXl5eUpJSdHgwYMlST4+Pho6dKiWL1+uHj16VLleEjMAAGBYTSdm2dnZOnz4sONVVFRULZ/ru+++U3FxscLDwxUcHCwfHx81aNBAb7zxhuOYxYsXS5KjKZOkIUOGSJIWLVrk0ng0ZgAAwOu0adNGERERjtcdd9xRLeNs2rRJkrRkyRIlJCRowYIFio6O1iOPPKIvvvhC0m9Nop+fX4Vz/fz8lJ2d7dJ4TGUCAADDavquzN27dys4ONixPSQkpFrGKysrkyTdcMMNeuuttyRJ9913n+rXr68JEyY4TWlWxmazuTQejRkAAPA6zZo1q7Zm7Pdat24tSbrmmmuctl966aX6+eefHbWUlpZWOLe0tFRNmzZ1aTymMgEAAM7jxhtvlI+Pj7799lun7Xl5eY6mq0+fPpKkuXPnOvbPmTNHkpSQkODSeCRmAADAMKs+YDY3N1dr1651vN+zZ48WLlyoyMhIxcfHKzMzU9u2bdPevXslSRs3bpT0W1IWFxcnHx8f3XHHHVq6dKnGjBmjnj176tlnn9WpU6f0wgsvSJJ69eqlsLAwjRgxwjH1OXLkSDVu3NilOzIlyWb3wCN0i4qKHNGgN6osrvQW9evX93QJhmzfvt3TJbgtNTXV0yW4raCgwNMlGNKkSRNPl+C2Ll26eLoEt3Xo0MHTJRhy8uRJT5fgth9//LFGpvmk3/5NDw0N1VVXXSVfX99qH6+srEzffvutCgsLq/QZp06dqqSkpArbY2JitH//fg0ZMsSRbv1e586dlZ6e7njfvXt3rVq1SmVlZQoKCtLkyZM1YsQIx/7MzEx16dJFP/30kyQpKipK6enpatGihUufj8QMAAAYZtXEbPTo0Ro9evR596ekpCglJeVPr/P7Z5hVJiYmRllZWS7VVhnWmAEAAFgEiRkAADDMqomZtyExAwAAsAgSMwAAYBiJmTlIzAAAACyCxAwAABhGYmYOEjMAAACLIDEDAACGkZiZg8QMAADAImjMAAAALIKpTAAAYBhTmeYgMQMAALAIEjMAAGAYiZk5SMwAAAAswmOJ2dmzZz01tGGhoaGeLsFtPj7e3Ytfe+21ni7BbYWFhZ4uwW3BwcGeLsEQm83m6RLcNmnSJE+X4LZTp055ugRDvP3PfU0jMTOHd/8rDQAAUIuwxgwAABhGYmYOEjMAAACLIDEDAACGkZiZg8QMAADAIkjMAACAKWp7mlUTSMw86N1339VTTz3l0jnPP/+8tm7dqh9++EGtW7d26xruePvtt/Xkk09W+zgAANRltSYxGzVqlHr27KnY2FidPn1aW7du1fPPP6/MzExPl2aaTp06qXfv3nrggQd06NAhFRQU6JFHHvHqZ8IBAGoH1piZo9YkZvHx8Zo7d6569uyphIQEXXTRRVq4cKECAwNdvlZoaKhb51W3yMhIHTt2TNu3b1deXp7KyspUWFio4uLiGq+lcePG8vX1rfFxAQCozWpNY3bfffdp4cKF+v7777V792499thjioiIUFxcXJXO9/X1VZcuXTR79mzt2rVLUVFRkqStW7dq2LBhTsd+8sknGjlypOP9u+++q3/84x9KTk7W1q1btXHjRqf9klS/fn1NmTJFO3bs0IYNG/Tggw9WWsfQoUO1evVqffPNN/rkk0/UvXt3SdLkyZP1zDPPqFmzZvrhhx+0Zs0ax9i/n8qsSi2SNGTIEK1atUo7d+5UamqqunXr5lTr5MmTlZGRoXXr1mnQoEEVzk9ISNDatWs1btw4XXHFFRf60QIAgCqqNVOZf3TuqzROnDhxweNat26tvn376p577tFFF12kTz75RH369NHu3btdGu/uu+/WW2+9pXvuuUft2rVzNDYbNmyQJI0bN0433HCDHnnkER07dkxjxozRlVdeqT179jiukZSUpG7dumnChAk6cOCArr/+ev3rX//S8ePH9fzzz+vgwYPq16+fevfurfLycrdrGT16tLp27apnn31WP/30k66//nq9/PLLOn78uLZu3ark5GR16NBBjz76qPLy8pSUlKSrrrpKe/fudYzx5ptv6scff9Sdd96pJUuWaN++fVq6dKk+/fRTFRQUuPSzAwB4P6YyzVFrG7PnnntOmzdvdmomzmnYsKH69Omjfv36qVWrVlq9erXGjRunL774QqWlpW6Nt3fvXs2YMUOSdODAAT3wwAOKj4/Xhg0bFBgYqISEBI0dO9bRHCUnJ2vdunWO8+vXr68HH3xQiYmJ2rFjhyTp0KFD+utf/6p7771Xjz/+uIqLi1VWVqa8vDy3a6lfv74GDRqkAQMGOMY5fPiw/vrXv6pfv3767rvvdM899yg5OVkbN26UJD3xxBNau3at0xhnzpzR8uXLtXz5cjVq1Ej/8z//o7vuuktjx47Vl19+qY8//lhr1qxRWVmZWz9PAADqolrZmE2aNEmtW7fWHXfcUen+wYMHa+zYsdq0aZNuuOEG5eTkGB7z+++/d3p/7NgxXXLJJZJ+Wxvm7++v7du3O/YXFhYqKyvL8b5ly5YKCAjQvHnznK7j5+fnlKoZreXcOG+99Val40RERMjf39/RtFVW6x8dP35c8+fP1/z589WpUydNmjRJXbp00Z133llpYwwAqH1IzMxR6xqzF198Ud26ddNdd92ln3/+udJj3nnnHZ09e1Z9+/bVunXrlJaWpo8++kjr16+v8Btut9tls9mctl10UcUf2x/vjLTb7fLx+W0J3x/Pr8y5Y4cNG6bc3FynfWfOnPnT812tZfjw4Tpy5EiFcRo0aODSWJJ08cUXq1u3brrzzjt13XXXaevWrZoyZUqtuiMWAICaUKsasxdffFE9e/bU3XffrYMHD573uCNHjmjq1KmaOnWqrrvuOvXr109z5szRL7/8oiVLlmjRokWO1Ck/P1+NGzd2nBsUFKTmzZu7VNeBAwd05swZtW3b1tEshoSEKCoqSl999ZUkaf/+/fr111912WWXObZVh8zMTP36669q2rSptm7dWmF/UVHReWv9/fE+Pj668cYbdccdd6hLly7Kzc1VamqqnnjiifM2xACA2ovEzBy1pjF76aWX1Lt3bw0YMEC//PKLLr30UknSyZMndfr06fOet23bNm3btk1PP/20evToob59+2r16tXq0qWL9uzZo/Xr16tfv35auXKlCgsLNW7cOJfXTZWUlOijjz7SuHHjdOLECeXl5enxxx93WsBfXFysOXPm6Mknn5SPj4++/vprBQUFqV27diopKdHHH3/s3g/mD4qLi/XWW29p/PjxstlsFcZZunSpFi9erLFjx6qgoED5+flKSkqq8B/CQw89pEGDBmn58uUaNGiQ0zQtAABwT61pzM490mHp0qVO20eNGqWFCxf+6fm//vqrli5dqqVLlyo8PNzxbLB///vfatGihd59910VFRVp8uTJuvzyy12ub/LkyQoMDNTMmTMdzdG5O0fPee2115Sfn6/hw4crIiJCJ0+e1HfffaeZM2e6PN6FTJ061TFO8+bNdfLkSe3evdsxzpQpUxQYGKj//Oc/Ki4u1ty5cxUUFOR0jdTUVKWkpLg8zQoAqJ1IzMxhs3vgExYVFSk2NramhzVNSEiIp0tw27m1Zt7q119/9XQJbissLPR0CW774/9EeJuqrPO0Km/+++bYsWOeLsGQ+vXre7oEt+3cubPG/uwUFRUpNDRUERERNfJvTHl5uQ4dOqTCwkKv/u/jfGpNYgYAADyHxMwc3h2fAAAA1CIkZgAAwDASM3PUusbs888/d3q8RXXw9nVa1S0vL099+vTxdBkAAHidWteYNW7cWE2bNvV0GQAAAC6rdY3Z0aNHq30MErML+7Pv8gQA1D5MZZqj1jVm3bp1q/YxvPn2XJpKAACsq9Y1ZgAAoOaRmJmD+AQAAMAiSMwAAIBhJGbmIDEDAACwCBIzAABgGImZOUjMAAAALILEDAAAGEZiZg4SMwAAAIsgMQMAAIaRmJmDxAwAAMAiSMwAAIBhJGbmIDEDAACwCBozAAAAi2AqEwAAGMZUpjlIzAAAACyCxAwAABhGYmYOEjMAAACLIDEDAACGkZiZg8QMAADAIkjMAACAKWp7mlUTPJKY8RsHAED14d9Z7+WRxOzkyZM6evSoJ4Y2hTfXDrjjxIkTni4BgAtOnjyp0NDQGh2zpprB2t50eqQxa9q0qQ4dOqTg4GDZbDZPlAAAQK1jt9t18uRJNW3a1NOlwE0eacx8fHzUvHlzTwwNAECtVtNJ2TkkZubgrkwAAACLoDEDAACwCBozAH9q3rx5atCgQbVc++abb9bo0aOr5dpWHBeorc49YLYmXrUZjRlQRef7h3zp0qXcxCKpoKBAiYmJCg0NVWhoqBITE53u5kxPT5fNZrPMHZ5LlizR888/7+kyAMAJjRkAU/z973/Xjh07tGLFCq1YsUI7duxQYmKip8s6r0aNGik4ONjTZQC1BomZOWjMAJM9++yzatu2rd555x1FRUUpNDRU9957r06ePOk45uabb9aoUaOUnJysRo0aqUmTJnr22WedrvPqq6/q6quv1sUXX6yIiAiNGDFCv/zyi2P/uenFtLQ0tWrVSoGBgbrnnntUXFys+fPnKyoqSg0bNtTIkSNVVlbmOO/MmTNKTk5Ws2bNdPHFF6tDhw5KT093GnvevHmKjIxUYGCg7r77buXn51/wM+/Zs0crVqxQSkqK4uPjFR8frzfffFNpaWn6/vvv9dNPP+mWW26RJDVs2FA2m00DBw50nF9eXn7Bn8Ufbd26VbfddpvCwsIUGhqqzp07KyMjw7E/PT1d/v7+WrdunWPbK6+8orCwMP3888+O34PfJ6BvvPGGYmNjFRAQoPDwcN1zzz0XrAEAqgONGVANMjMztXTpUqWlpSktLU1r167VSy+95HTM/PnzdfHFF2vLli2aMmWKnnvuOX3xxReO/T4+Ppo2bZq+/fZbzZ8/X6tXr1ZycrLTNUpKSjRt2jR98MEHWrFihdLT09W7d28tW7ZMy5Yt0zvvvKPZs2fro48+cpwzaNAgbdiwQR988IF27dqlhIQEde/eXT/88IMkacuWLXrwwQc1YsQI7dixQ7fccoteeOGFC37eTZs2KTQ0VB06dHBsu+GGGxQaGqqNGzcqIiJCixcvliR9//33+vnnn/Xvf/+7yj+LPzp58qQGDBigdevWafPmzYqNjVXPnj0dze+5pisxMVGFhYXauXOnnnrqKb355pu67LLLKlxv27ZtGjVqlJ577jl9//33WrFihTp16nTBzwzAGYmZSewAqqRz5872xx57rML2jz/+2P77/5SeeeYZe2BgoL2oqMixbezYsfYOHTo4XevGG290us71119vHzdu3HnH//DDD+2XXHKJ4/3cuXPtkuz79+93bBs+fLg9MDDQfvLkSce2bt262YcPH2632+32/fv32202mz07O9vp2n/729/s48ePt9vtdvt9991n7969u9P+fv362UNDQ89b2z//+U97bGxshe2xsbH2F1980W632+1r1qyxS7IXFBQ4HePOz+KPzp49aw8ODrZ/+umnjm2//vqrvV27dva+ffvar7zySvuQIUMqjHvu93Px4sX2kJAQp98zAFVTWFhol2QPCgqyBwcHV/srKCjILsleWFjo6Y9eLUjMgGoQFRXltH7psssuq/BVXnFxcU7v/3jMmjVrdNttt6lZs2YKDg5W//79lZ+fr+LiYscxgYGBiomJcbwPDw9XVFSUgoKCnLadu25GRobsdruuuOIKBQUFOV5r165VZmampN+mJePj451q++P7ylR2A4Tdbq/SjRF/9rP4o6NHj+qhhx7SFVdc4bjZ4JdfftHBgwcdx/j7++vdd9/V4sWLderUKU2dOvW817vtttvUokULRUdHKzExUQsWLFBJScmf1g3g/9hJzEzhkSf/A94oJCREhYWFFbafOHFCISEhTtv8/Pyc3ttsNpWXl1f5mAMHDqhnz5566KGH9Pzzz6tRo0Zav369Bg8erNLS0gte40LXLS8vl6+vr77++mv5+vo6HXeumXPnL70mTZroyJEjFbYfO3ZM4eHhf3p+VX5evzdw4EAdO3ZMU6dOVYsWLVSvXj3Fx8frzJkzTsdt3LhRknT8+HEdP35cF198caXXCw4OVkZGhtLT07Vy5UpNmDBBzz77rLZu3VptjwkBgMqQmAFV9Je//EXbtm2rsH3r1q1q1aqVqWNt27ZNZ8+e1SuvvKIbbrhBV1xxhXJycgxft127diorK9PRo0fVsmVLp1eTJk0kSW3atNHmzZudzvvj+z+Kj49XYWGhvvrqK8e2LVu2qLCwUB07dpT0W4IlyelGBHetW7dOo0aNUs+ePXXllVeqXr16ysvLczomMzNTSUlJevPNN3XDDTeof//+F2z2LrroInXp0kVTpkzRrl279NNPP2n16tWGawXqChIzc9CYAVU0YsQIZWZm6pFHHtHOnTu1b98+vf7665ozZ47Gjh1r6lgxMTE6e/aspk+frh9//FHvvPOOZs6cafi6V1xxhe6//371799fS5YsUVZWlrZu3arJkydr2bJlkqRRo0ZpxYoVmjJlivbt26cZM2ZoxYoVF7xu69at1b17dw0dOlSbN2/W5s2bNXToUPXq1cvRtLZo0UI2m01paWk6duyY0x2mrmrZsqXeeecd7dmzR1u2bNH999+v+vXrO/aXlZUpMTFRXbt21aBBgzR37lx9++23euWVVyq9XlpamqZNm6YdO3bowIEDevvtt1VeXm56ww0Af4bGDKiiqKgorVu3TpmZmeratauuv/56zZs3T/PmzVNCQoKpY7Vt21avvvqqJk+erKuuukoLFizQpEmTTLn23Llz1b9/f40ZM0atWrXSHXfcoS1btigiIkLSb3dTpqSkaPr06Wrbtq1Wrlypp59++k+vu2DBAl199dXq2rWrunbtqri4OL3zzjuO/c2aNdPEiRP1xBNPKDw8XI8++qjbn+Gtt95SQUGB2rVrp8TERI0aNUqNGzd27P/nP/+pn376SbNnz5b021RrSkqKnn76ae3YsaPC9Ro0aKAlS5bo1ltvVevWrTVz5ky9//77uvLKK92uEahrSMzMYbPX9k8IAACqTVFRkUJDQ1W/fv0a+RYUu92uU6dOqbCwsML63tqAxf8AAMCwmsp5anuexFQmAACARdCYAQAAWARTmQAAwDCmMs1BYgYAAGARJGYAAMAwEjNzkJgBAABYBIkZAAAwjMTMHCRmAACg1po+fbrCw8Pl6+srm82m8ePHO+1PTk5WWFiYfHx8ZLPZtHDhwvNeq7y8XJdeemml18nKylJ0dLRsNptsNpuio6N14MABl+ulMQMAAIZZ9SuZCgoKFBsbqzFjxlS6v6ioSHFxcUpMTPzTa/Xu3fu8327Qvn175eTkaNasWZo1a5ZycnLUvn17l2qVaMwAAEAtNmHCBK1fv15TpkypdP/MmTO1evVqDR069ILX+fDDD5WWlqZVq1ZV2JeWlqa8vDy9/vrrGjZsmIYNG6YZM2bo6NGjWr58uUv10pgBAADDajoxy87O1uHDhx2voqKiavtseXl5SkxMVHJysuLi4irsX7x4sSRp8ODBjm1DhgyRJC1atMilsVj8DwAAvE6bNm2c3nfu3Fnp6enVMtZNN92kqKgovfjii5Xuz87Olp+fX4Xtfn5+ys7OdmksGjMAAGBYTd+VuXv3bgUHBzu2h4SEVMt4Tz31lDIzM3Xw4EG3zj/fmrTzYSoTAAB4nWbNmql58+aOV3U1ZsuWLVNpaakuu+wyxx2XkvTSSy+pQYMGjlpKS0srnFtaWqqmTZu6NB6NGQAAwHnMnz9fS5YscXpJv92h+cknn0iS+vTpI0maO3eu47w5c+ZIkhISElwaj6lMAABgmFUfMJubm6u1a9c63u/Zs0cLFy5UZGSk4uPjlZmZqW3btmnv3r2SpI0bN0qSWrdurbi4OMfrj6644gp16tRJktSrVy+FhYVpxIgRKisrkySNHDlSjRs3Vo8ePVyq12av7Y/QBQAA1aaoqEihoaFO03zV6dydmYWFhVWavpw6daqSkpIqbI+JidH+/fs1ZMgQR7r1exe6mcBms+mJJ57QpEmTHNsyMzPVpUsX/fTTT5KkqKgopaenq0WLFlX7YOeuTWMGAADcda4xk1xf6O6Oc21LVRszb8MaMwAAAItgjRkAADAFk3DGkZgBAABYBI0ZAABwm7+/v5o0aVKjYzZp0kT+/v41OmZNYfE/AAAw5PTp0zpz5kyNjefv76+AgIAaG68m0ZgBAABYBFOZAAAAFkFjBgAAYBE0ZgAAABZBYwYAAGARNGYAAAAWQWMGAABgETRmAAAAFvH/AclbmLBkno+ZAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x581.818 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x581.818 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "dp.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calibrating the Diffraction Pattern\n",
    "\n",
    "It is important that we keep track of the center of the diffraction pattern as well as the calibration. Lets consider the diffraction pattern above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dp.set_diffraction_calibration(1e-2) # known from simulation\n",
    "dp.beam_energy = 300 #kEv\n",
    "dp.unit = \"k_A^-1\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed | 106.20 ms\n",
      "[########################################] | 100% Completed | 110.89 ms\n"
     ]
    }
   ],
   "source": [
    "shifts, aligned = dp.center_direct_beam(method=\"blur\",half_square_width=20,sigma=5, return_shifts=True, inplace=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "table, th, td {\n",
       "\tborder: 1px solid black;\n",
       "\tborder-collapse: collapse;\n",
       "}\n",
       "th, td {\n",
       "\tpadding: 5px;\n",
       "}\n",
       "</style>\n",
       "<p><b>< Axes manager, axes: (10, 10|128, 128) ></b></p>\n",
       "<table style='width:100%'>\n",
       "\n",
       "<tr> \n",
       "<th>Navigation axis name</th> \n",
       "<th>size</th> \n",
       "<th>index</th> \n",
       "<th>offset</th> \n",
       "<th>scale</th> \n",
       "<th>units</th> </tr>\n",
       "<tr> \n",
       "<td><undefined></td> \n",
       "<td>10</td> \n",
       "<td>0</td> \n",
       "<td>0.0</td> \n",
       "<td>1.0</td> \n",
       "<td><undefined></td> </tr>\n",
       "<tr> \n",
       "<td><undefined></td> \n",
       "<td>10</td> \n",
       "<td>0</td> \n",
       "<td>0.0</td> \n",
       "<td>1.0</td> \n",
       "<td><undefined></td> </tr></table>\n",
       "<table style='width:100%'>\n",
       "\n",
       "<tr> \n",
       "<th>Signal axis name</th> \n",
       "<th>size</th> \n",
       "<th></th> \n",
       "<th>offset</th> \n",
       "<th>scale</th> \n",
       "<th>units</th> </tr>\n",
       "<tr> \n",
       "<td>kx</td> \n",
       "<td>128</td> \n",
       "<td></td> \n",
       "<td>-0.64</td> \n",
       "<td>0.01</td> \n",
       "<td>k_A^-1</td> </tr>\n",
       "<tr> \n",
       "<td>ky</td> \n",
       "<td>128</td> \n",
       "<td></td> \n",
       "<td>-0.64</td> \n",
       "<td>0.01</td> \n",
       "<td>k_A^-1</td> </tr></table>\n"
      ],
      "text/plain": [
       "<Axes manager, axes: (10, 10|128, 128)>\n",
       "            Name |   size |  index |  offset |   scale |  units \n",
       "================ | ====== | ====== | ======= | ======= | ====== \n",
       "     <undefined> |     10 |      0 |       0 |       1 | <undefined> \n",
       "     <undefined> |     10 |      0 |       0 |       1 | <undefined> \n",
       "---------------- | ------ | ------ | ------- | ------- | ------ \n",
       "              kx |    128 |      0 |   -0.64 |    0.01 | k_A^-1 \n",
       "              ky |    128 |      0 |   -0.64 |    0.01 | k_A^-1 "
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x581.818 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x581.818 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "aligned.plot()\n",
    "aligned.axes_manager"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Template Matching\n",
    "\n",
    "A common way to find spots in a diffraction pattern is through template matching.  Template matching involves creating a template of one of the diffraction spots and convolving it with the entire dataset.  Usually this is done using a flat disk or a summed image of the zero beam.  Often times reducing the noise in the dataset is useful as it \n",
    "\n",
    "There are a couple of ways to acomplish this is pyxem. \n",
    "\n",
    "The first is to use the `template_match_disk` function which uses the normalized_cross_correlation to find shere some diffraction spot is.  We can think of this as the template being slid across the image and multiplied at every point.  The result is that objects similar to the template are very visable in the filtered dataset. \n",
    "\n",
    "There are multiple ways to do this:\n",
    "\n",
    "1. Use the vaccum probe as a template and convolve the vaccum probe with the image\n",
    "2. Use the "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed | 310.78 ms\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x581.818 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x581.818 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matched = aligned.template_match_disk(disk_r=5) # the disk_r should be equal to the size of the diffraction spots. \n",
    "matched.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Peak Finding\n",
    "We can then find the position of the peaks using the `hyperspy.Signal2D.find_peaks()` method.  There is an interactive form of this method as well which makes defining the proper settings a little bit easier. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "ename": "ImportError",
     "evalue": "No toolkit registered. Install hyperspy_gui_ipywidgets or hyperspy_gui_traitsui GUI elements.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[14], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m get_ipython()\u001b[38;5;241m.\u001b[39mrun_line_magic(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmatplotlib\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnotebook\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m----> 2\u001b[0m \u001b[43mmatched\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfind_peaks\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/mambaforge/envs/pyxem-demos/lib/python3.11/site-packages/hyperspy/_signals/signal2d.py:1023\u001b[0m, in \u001b[0;36mSignal2D.find_peaks\u001b[0;34m(self, method, interactive, current_index, show_progressbar, parallel, max_workers, display, toolkit, **kwargs)\u001b[0m\n\u001b[1;32m   1020\u001b[0m     peaks \u001b[38;5;241m=\u001b[39m BaseSignal(np\u001b[38;5;241m.\u001b[39mempty(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxes_manager\u001b[38;5;241m.\u001b[39mnavigation_shape),\n\u001b[1;32m   1021\u001b[0m                        axes\u001b[38;5;241m=\u001b[39maxes_dict)\n\u001b[1;32m   1022\u001b[0m     pf2D \u001b[38;5;241m=\u001b[39m PeaksFinder2D(\u001b[38;5;28mself\u001b[39m, method\u001b[38;5;241m=\u001b[39mmethod, peaks\u001b[38;5;241m=\u001b[39mpeaks, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m-> 1023\u001b[0m     \u001b[43mpf2D\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgui\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdisplay\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdisplay\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtoolkit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoolkit\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1024\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m current_index:\n\u001b[1;32m   1025\u001b[0m     peaks \u001b[38;5;241m=\u001b[39m method_func(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__call__\u001b[39m(), \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[0;32m~/mambaforge/envs/pyxem-demos/lib/python3.11/site-packages/hyperspy/ui_registry.py:162\u001b[0m, in \u001b[0;36mget_partial_gui.<locals>.pg\u001b[0;34m(self, display, toolkit, **kwargs)\u001b[0m\n\u001b[1;32m    161\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpg\u001b[39m(\u001b[38;5;28mself\u001b[39m, display\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, toolkit\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m--> 162\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mget_gui\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtoolkey\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoolkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdisplay\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdisplay\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    163\u001b[0m \u001b[43m                   \u001b[49m\u001b[43mtoolkit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoolkit\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/mambaforge/envs/pyxem-demos/lib/python3.11/site-packages/hyperspy/ui_registry.py:69\u001b[0m, in \u001b[0;36mget_gui\u001b[0;34m(self, toolkey, display, toolkit, **kwargs)\u001b[0m\n\u001b[1;32m     67\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_gui\u001b[39m(\u001b[38;5;28mself\u001b[39m, toolkey, display\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, toolkit\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m     68\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m TOOLKIT_REGISTRY:\n\u001b[0;32m---> 69\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(\n\u001b[1;32m     70\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNo toolkit registered. Install hyperspy_gui_ipywidgets or \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     71\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhyperspy_gui_traitsui GUI elements.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     72\u001b[0m         )\n\u001b[1;32m     73\u001b[0m     \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mhyperspy\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdefaults_parser\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m preferences\n\u001b[1;32m     74\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(toolkit, \u001b[38;5;28mstr\u001b[39m):\n",
      "\u001b[0;31mImportError\u001b[0m: No toolkit registered. Install hyperspy_gui_ipywidgets or hyperspy_gui_traitsui GUI elements."
     ]
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "matched.find_peaks()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "peaks = matched.find_peaks(threshold=1.0, distance=5, interactive=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Converting Peaks to Diffraction Vectors\n",
    "\n",
    "We then need to take the peaks identified and transform them into diffraction Vectors. We can construct the signal using the following code.  Note that the center of the diffraction pattern and the calibration need to be passed once again. We can take these from the diffraction signal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "center = [a.offset/a.scale*-1 for a in matched.axes_manager.signal_axes] # should be the center of the pattern now...\n",
    "\n",
    "calibration = matched.axes_manager.signal_axes[0].scale\n",
    "\n",
    "vectors = pxm.signals.DiffractionVectors.from_peaks(peaks,center = center, calibration=calibration)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter the Diffraction Vectors\n",
    "\n",
    "We want to only return the diffraction vectors which are within some distance of a basis set of diffraction vectors.  This basis set can be just be a single set of diffraction spots but ideally more than 2 spots will be used.  This allows for the least squares fitting to also return a residual.  In many cases this is prefered as it allows outliers to be identified as points with high residuals.  Note that in some cases, using too many spots can also be probalematic as low intensity spots are harder to fit.  In those cases a weight parameter is also allowed to help refine the fitting. \n",
    "\n",
    "Defining the basis set of vectors can be done in multiple different ways.  \n",
    "\n",
    "1. Define a basis from a known basis set of vectors.  Using the known lattice parameter for the material it is possible to define the proper basis set for the material.\n",
    "\n",
    "2. Define the basis from an unstrained part of the material. \n",
    "\n",
    "\n",
    "In most cases the secound way is easier and prefered over the first.  It is less dependent on the calibration and things like elliptical distortion in the diffraction pattern will show up as strains in the first case and a very high quality of experiment is necessary.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the basis vectors from an unstrained part of the material. \n",
    "basis = vectors.inav[1:2,1:2]\n",
    "basis.filter_magnitude(min_magnitude =0.1, max_magnitude=1)# remove the zero_beam\n",
    "basis_array = basis.data[0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_vectors = vectors.filter_basis(basis_array, distance =.2, inplace= False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyxem.generators.displacement_gradient_tensor_generator import get_DisplacementGradientMap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "strain_map = get_DisplacementGradientMap(filtered_vectors, basis_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "maps = strain_map.get_strain_maps()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "f= plt.figure(figsize=(7,7))\n",
    "hs.plot.plot_images(maps,per_row=2,fig=f,\n",
    "                    label=[\"e11\",\"e22\", \"e12\", \"theta\"],tight_layout=True)\n",
    "plt.show()"
   ]
  }
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