03_scio_analyse_devel.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4493f2ef-302d-4924-b8cf-72678d653dc7",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Python library for the analysis of raw data from the SCiO\n",
    "\n",
    "Note: The SCiO spectrometer is manufactured by Consumer Physics\n",
    "\n",
    "### Questions regarding decoding:\n",
    "\n",
    "- How many datapoints are there? 331 or 400? 400*4=\n",
    "- What are the remaining data bytes?\n",
    "- Is the data encrypted?\n",
    "- Is the data gzipped?\n",
    "\n",
    "\n",
    "### Calculate reflectance\n",
    "- $correctedSample  = sample - sampleDark$\n",
    "- $correctedGradient = sampleGradient - sampleDark$\n",
    "- $reflectanceRAW = correctedSample / correctedGradient$\n",
    "\n",
    "- $reflectance = reflectanceRAW / reflectanceWR$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "67005b5a-8221-45ef-ba05-24f187824037",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import struct\n",
    "import datetime\n",
    "import os\n",
    "import csv\n",
    "import base64\n",
    "import numpy as np\n",
    "\n",
    "from plotnine import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3f85d128-7847-45bb-bb74-13ca4695443f",
   "metadata": {},
   "outputs": [],
   "source": [
    "class scio_analyse:\n",
    "    def __init__(self):\n",
    "        self.device_info = {}\n",
    "        self.scan_rawdata = {}\n",
    "        self.scan_b64data = {}\n",
    "        self.temperature = {}\n",
    "        \n",
    "    def load_file(self, fn):\n",
    "        # Load the JSON file\n",
    "        with open(fn, 'r') as file:\n",
    "            json_data = json.load(file)\n",
    "\n",
    "        # Load the temperature object\n",
    "        self.temperature = json_data['temperature']\n",
    "        # Load the device information object\n",
    "        self.device_info = json_data['device']\n",
    "        # Load raw data as hex\n",
    "        self.scan_rawdata = json_data['raw_data']\n",
    "        # Load raw data as Base64\n",
    "        self.scan_b64data = json_data['b64_data']\n",
    "        return\n",
    "    \n",
    "    def encode_b64(self, bytestring):\n",
    "        urlSafeEncodedBytes = base64.b64encode(bytestring)\n",
    "        urlSafeEncodedStr = str(urlSafeEncodedBytes, 'utf-8')\n",
    "        return(urlSafeEncodedStr)\n",
    "    \n",
    "    def switch_byte_order(self, bytestring):\n",
    "        hex_str = bytestring.hex()\n",
    "        out_str = ''\n",
    "        for i in range(int(len(hex_str)/4)):\n",
    "            out_str += hex_str[i*4+2] + hex_str[i*4+3]\n",
    "            out_str += hex_str[i*4+0] + hex_str[i*4+1]\n",
    "        hex_bytes = bytes.fromhex(out_str)\n",
    "        return(hex_bytes)\n",
    "    \n",
    "    def b64_to_hex(self):\n",
    "        self.scan_hexdata = {}\n",
    "        for dict_key in self.scan_b64data.keys():\n",
    "            if(dict_key == 'sampled_at'):\n",
    "                self.scan_hexdata.update({dict_key: self.scan_b64data[dict_key]})\n",
    "                continue\n",
    "            if('numberOfCommandsPerSpectrum' in self.device_info.keys()):\n",
    "                self.scan_hexdata.update({dict_key: base64.b64decode(self.scan_b64data[dict_key]).hex()})\n",
    "            else:\n",
    "                self.scan_hexdata.update({dict_key: base64.urlsafe_b64decode(self.scan_b64data[dict_key]).hex()})\n",
    "        return\n",
    "    \n",
    "    def plot_hex_as_img(self, hex_str, silent=True):\n",
    "        # Try to interpret the hex bytes as an image, and if possible, plot them\n",
    "        # Note: Requires matplotlib and io\n",
    "        # Returns False if not an image, True if it is\n",
    "        import matplotlib.pyplot as plt\n",
    "        import matplotlib.image as mpimg\n",
    "        import io\n",
    "\n",
    "        fp = io.BytesIO(bytes.fromhex(hex_str))\n",
    "\n",
    "        with fp:\n",
    "            try:\n",
    "                img = mpimg.imread(fp, format='jpeg')\n",
    "            except:\n",
    "                if not silent: print('Error: Not an image!')\n",
    "                return(False)\n",
    "            else:\n",
    "                plt.imshow(img)\n",
    "                plt.show()\n",
    "        return(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f74aabf0-4327-4ecc-8baf-dc840f34d252",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_fn        = './01_rawdata/scan_json/scan_dark1.json'\n",
    "# Create an instance and load data\n",
    "scio = scio_analyse()\n",
    "scio.load_file(data_fn)\n",
    "\n",
    "# If you want to convert Base64 data to hex, for example to extract the white reference (WR) data, use the following.\n",
    "# Note that the data will be stored in a new dict, called scio.scan_hexdata\n",
    "scio.b64_to_hex()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "571a3cd7-750f-4586-a276-eeb8bbc36efa",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "data_fn        = './01_rawdata/scan_json/scan_dark1.json'\n",
    "# Create an instance and load data\n",
    "scio = scio_analyse()\n",
    "scio.load_file(data_fn)\n",
    "\n",
    "smp = bytearray.fromhex(scio.scan_rawdata['sample_gradient'])\n",
    "\n",
    "format_str = '<' + 332*'x' + 331*'I'\n",
    "format_str = '<' + 300*'x' + 331*'I' + 32*'x'\n",
    "\n",
    "\n",
    "sample_list = np.array(struct.unpack(format_str, smp))\n",
    "\n",
    "\n",
    "#print('Bytes:', sample_bytes.hex())\n",
    "#print('Data: ', sample_list)\n",
    "\n",
    "plt = ggplot()\n",
    "plt = plt + geom_point(aes(x=np.arange(len(sample_list))+740, y=sample_list), size=0.5)\n",
    "plt = plt + theme_bw()\n",
    "plt = plt + ggtitle('Sample values')\n",
    "print(plt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "693766a4-8d24-4aba-b8de-91be315ec9f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Try to interpret the hex bytes as an image, and if possible, plot them\n",
    "# Note: Requires matplotlib and io\n",
    "# Returns False if not an image, True if it is\n",
    "scio.plot_hex_as_img(scio.scan_rawdata['sample'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "a11fc268-4300-4bcd-9718-bef9cd099530",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 1  2  6  8  7  7  0  2  1  0 -1  1]\n",
      "[  6  54 123  46  79  61  28  14   6   4   4   6]\n",
      "[ 0.16666667  0.07407407  0.15384615  0.33333333  0.19444444  0.31818182\n",
      "  0.          0.4         0.2         0.         -0.2         0.14285714]\n"
     ]
    }
   ],
   "source": [
    "sample_hex         = '06 36 7b 2e 4f 3d 1c 0e 06 04 04 06'\n",
    "sampleDark_hex     = '05 34 75 26 48 36 1c 0c 05 04 05 05'\n",
    "sampleGradient_hex = '0b 4f 9c 3e 6c 4c 28 11 0a 09 0a 0c'\n",
    "\n",
    "sample = np.array([int(x, 16) for x in sample_hex.split(' ')])\n",
    "sampleDark = np.array([int(x, 16) for x in sampleDark_hex.split(' ')])\n",
    "sampleGradient = np.array([int(x, 16) for x in sampleGradient_hex.split(' ')])\n",
    "\n",
    "correctedSample = sample - sampleDark\n",
    "correctedGradient = sampleGradient - sampleDark\n",
    "reflectance = correctedSample / correctedGradient\n",
    "\n",
    "print(correctedSample)\n",
    "print(sample)\n",
    "print(reflectance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e8b3431b-63bf-49f1-8cf2-5baf00200891",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16\n",
      "{'deviceBleId': '01665900004c99b4', 'bleFWVersion': 125, 'serial_number': 'CPPCA0031C6PF0516009W6404386A1DF1816004A', 'device_name': 'myScio', 'i2s_tag_config': '20150812-e:PRODUCTION', 'deviceDspId': 'e24da26b2304c2c0', 'aptinaId': '00004c8e3238c8e18032ab45611198f1', 'firmwareVersion': 147}\n",
      "1800.0\n"
     ]
    }
   ],
   "source": [
    "# Show some data\n",
    "print(len('8032AB45611198F1'))\n",
    "print(scio.device_info)\n",
    "print(len(scio.scan_rawdata['sample'])/2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "09f24b4f-38f1-4b3a-8bbe-7503f57d742f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "bytes per region: 138.0\n",
      "Not JPEG\n",
      "Decrypted ints: 412.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "from Crypto.Cipher import AES\n",
    "\n",
    "key = bytearray.fromhex(scio.device_info['aptinaId'])\n",
    "cipher = AES.new(key, AES.MODE_ECB)\n",
    "\n",
    "print('bytes per region:', len(smp)/12)\n",
    "decrypted_bytes = cipher.decrypt(smp[2:-6])\n",
    "\n",
    "if decrypted_bytes[:2] == b'\\xff\\xd8' and decrypted_bytes[-2:] == b'\\xff\\xd9':\n",
    "    print('Found JPEG')\n",
    "else:\n",
    "    print('Not JPEG')\n",
    "\n",
    "#print(decrypted_bytes.hex())\n",
    "\n",
    "format_str = '<' + 412*'I'\n",
    "\n",
    "print('Decrypted ints:', len(decrypted_bytes)/4)\n",
    "\n",
    "sample_list = np.array(struct.unpack(format_str, decrypted_bytes))\n",
    "\n",
    "plt = ggplot()\n",
    "plt = plt + geom_point(aes(x=np.arange(len(sample_list))+740, y=sample_list), size=0.5)\n",
    "plt = plt + theme_bw()\n",
    "plt = plt + ggtitle('Sample values')\n",
    "print(plt)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca22148b-f833-445e-a8c9-e45cec191dae",
   "metadata": {},
   "source": [
    "# Convert old scans to new format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "681529cf-35ec-4cad-a5b4-2b99f8325631",
   "metadata": {},
   "outputs": [],
   "source": [
    "class scio_update_old_scan_file:\n",
    "    def __init__(self):\n",
    "        self.device_info = {}\n",
    "        self.scan_rawdata = {}\n",
    "        self.scan_b64data = {}\n",
    "        self.temperature = {}\n",
    "        \n",
    "    def load_file(self, fn):\n",
    "        # Load the JSON file\n",
    "        with open(fn, 'r') as file:\n",
    "            json_data = json.load(file)\n",
    "\n",
    "        # Load the \"scan\" object\n",
    "        data = json_data['scan']\n",
    "        # Load the device information object\n",
    "        info = json_data['device']\n",
    "        return(info, data)\n",
    "    \n",
    "    def store_data(self, info, data):\n",
    "        # Store info\n",
    "        self.device_info = info\n",
    "        \n",
    "        # Now temperature\n",
    "        selected_keys = ['t_cmos_before', 't_chip_before', 't_obj_before', 't_cmos_after', 't_chip_after', 't_obj_after']\n",
    "        self.temperature = {key: data[key] for key in selected_keys}\n",
    "        self.temperature.update({'sampled_at': data['timestamp']})\n",
    "        \n",
    "        # Hex data\n",
    "        selected_keys = ['sample', 'sample_dark', 'sample_gradient']\n",
    "        self.scan_rawdata = {'sampled_at': data['timestamp']}\n",
    "        self.scan_rawdata.update({key: base64.urlsafe_b64decode(data[key]).hex()  for key in selected_keys})\n",
    "        \n",
    "        # Base64 data\n",
    "        selected_keys = ['sample', 'sample_dark', 'sample_gradient']\n",
    "        self.scan_b64data = {'sampled_at': data['timestamp']}\n",
    "        self.scan_b64data.update({key: data[key] for key in selected_keys})\n",
    "        return\n",
    "    \n",
    "    # Saves a single scan as raw data to JSON\n",
    "    def write_data_file(self, output_fn):\n",
    "        # Create the json string\n",
    "        jsondata = {}\n",
    "        jsondata['device'] = self.device_info\n",
    "        # Add temperature\n",
    "        jsondata['temperature'] = self.temperature\n",
    "        # Data, as hex and base64\n",
    "        jsondata['raw_data'] = self.scan_rawdata\n",
    "        jsondata['b64_data'] = self.scan_b64data\n",
    "        \n",
    "        # Write data to JSON file\n",
    "        with open(output_fn, 'w') as outfile:\n",
    "            json.dump(jsondata, outfile, indent=4)\n",
    "        return\n",
    "    \n",
    "    def convert_file(self, input_fn, output_fn):\n",
    "        info, data = self.load_file(input_fn)\n",
    "        self.store_data(info, data)\n",
    "        self.write_data_file(output_fn)\n",
    "        return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "a7fbe354-61bd-4613-9f25-9114800f5293",
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "directory = './01_rawdata/scan_json/'\n",
    "# Now set up the instance\n",
    "scio = scio_update_old_scan_file()\n",
    "\n",
    "file_list = sorted(glob.glob(directory + '**/*.json', recursive=True))\n",
    "data_list = []\n",
    "for idx, fn in enumerate(file_list):\n",
    "    print('    -', fn.split('\\\\')[-1])\n",
    "    #scio.convert_file(fn, fn) # Already done"
   ]
  }
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