{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a6919f84",
   "metadata": {},
   "source": [
    "# Sample code (eds)\n",
    "\n",
    "This page contains sample code to start an EDS analysis with a specified detector and acquire Spectrum data.\n",
    "\n",
    "The packages used are eds, detectorext."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49909ccc",
   "metadata": {},
   "source": [
    "The functions to be introduced are as follows\n",
    "\n",
    "- Get a list of detectors that can be controlled\n",
    "- Get or set a detector information\n",
    "- Image capturing\n",
    "\n",
    "Prerequisites\n",
    "\n",
    "- DetectorService is running (in the case of online)\n",
    "- Femtus is running (in the case of online)\n",
    "- Ver.1.3.0 (Operation check environment)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa96f044",
   "metadata": {},
   "source": [
    "## 0. Import TEM3\n",
    "*** "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b4c41d08",
   "metadata": {},
   "outputs": [],
   "source": [
    "from PyJEM import detectorext\n",
    "from PyJEM import eds\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "367c0818",
   "metadata": {},
   "source": [
    "## 1. Select a detector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8370ffa0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'status': 'OK'}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "detectorext.function.assign_channel('HAADF', 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a62d6ff",
   "metadata": {},
   "source": [
    "## 2. Place annotations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "893fba41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'status': 'OK'}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "args = {'LUTScanSetting': {'LookUpTable': '[]',\n",
    "  'Shape': 2,# Line=2, Square=3  \n",
    "  'Position': [[-1, -1], [1, 1]],\n",
    "  'PixelResolution': 2,\n",
    "  'IgnorePixelCount': 0,\n",
    "  'BlankingCount': 0}}\n",
    "\n",
    "detectorext.set_LUTscansetting(args)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ed5a57b",
   "metadata": {},
   "source": [
    "## 3. Set EDS parameter setting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0722c15f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'ProcessTime': ['T1', None, None, None],\n",
       " 'DwellTime': 1000.0,\n",
       " 'CollectionMode': 3,\n",
       " 'SweepCount': 0,\n",
       " 'EnableScanSync': False,\n",
       " 'EDSSelected': True}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "args2 = {'ProcessTime': ['T1', None, None, None],\n",
    " 'DwellTime': 4700.0,\n",
    " 'CollectionMode': 3,\n",
    " 'SweepCount': 1,\n",
    " 'EnableScanSync': False,\n",
    " 'EDSSelected': True}\n",
    "\n",
    "eds.set_acquisition_settings(args2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7bbff16",
   "metadata": {},
   "source": [
    "## 4. Start acquisition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4048655b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Version': '08', 'DataID': 'e6b698ec-4209-44ba-a0ea-be3ebb507993'}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_id = eds.start_acquisition()\n",
    "data_id"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0da796e1",
   "metadata": {},
   "source": [
    "## 5. get_spectrum_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0f248400",
   "metadata": {},
   "outputs": [],
   "source": [
    "binary = eds.get_spectrum_data({\"TargetDataID\" : data_id[\"DataID\"]})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d494461",
   "metadata": {},
   "source": [
    "## 6. Output as graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9f91f605",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2a68fc035e0>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Divide binary data into 4-byte units\n",
    "binary_intensity_list = [binary[i:i+4] for i in range(0, len(binary), 4)]\n",
    "\n",
    "# Transfer binary data to int.\n",
    "intnum = []\n",
    "for intensity in binary_intensity_list:\n",
    "    intnum.append( int.from_bytes(intensity, byteorder=\"little\"))\n",
    "\n",
    "# Drawing on graphs (EDS Spectrum)\n",
    "%matplotlib inline\n",
    "plt.plot(intnum)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}