1_Convert_To_Rinex.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "38167795-6ac4-478a-9d99-33910e6f83cc",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Convert To RINEX\n",
    "\n",
    "This python script converts between two file formats that are vital in the field of satellite navigation.\n",
    "\n",
    "The script rely on two specific tools for handling **.T04** file(Trimble Format).\n",
    "\n",
    "The first tool is *runpkr00* that allows to extract **.TGD** files from **.T04** logged by Trimble GNSS receivers.\n",
    "\n",
    "The second tool is *teqc*, it takes the output of *runpkr00* and convert it into **RINEX** (Receiver Independent Exchange Format) files with **.YYo** or **.obs** for observation and **.YYn** or **.nav** for navigation.\n",
    "\n",
    "For open-source processing, this conversion is necessary.\n",
    "\n",
    "N.B: The two tools are Open-source."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f56c0f1c-0deb-4622-97e3-066f86a36b33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython import display\n",
    "display.Image(\"D:/3CI/PFE/PFE_Allemagne/Updates/Workflow of conversion.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "590e059d-d0f3-42dc-92cf-5d3c05fba73a",
   "metadata": {
    "tags": [],
    "toc-hr-collapsed": true
   },
   "source": [
    "## Importing the packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9e8dfb4e-5c14-4ae9-a104-f2fb2f5a7dd0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os,sys,subprocess,glob,shutil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "95adc81b-0b7f-4a94-9064-f3f1be3cbda7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Specify the directories\n",
    "\n",
    "#Of Raw Measurements\n",
    "Raw_GNSS='C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/'\n",
    "#Of the runpkr tool\n",
    "runpkr='C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Result/runpkr00'\n",
    "#Of the teqc tool\n",
    "teqc='C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Result/teqc'\n",
    "#Where to put the result (.obs & .nav)\n",
    "Result='C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Result/'\n",
    "#Where to put the final merged (.obs & .nav) \n",
    "rover_files='C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Result/Rover/'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ab9db07-d638-430b-a893-9002bab85d1e",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Specify directories and getting files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "da572a29-c484-4ec4-acac-d1de43c711f1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Result Path Already exist\n",
      "\n",
      "Rover Path Already exist\n"
     ]
    }
   ],
   "source": [
    "#Create the Directory of Results if doesn't exist\n",
    "\n",
    "if not os.path.exists(Result):\n",
    "    os.makedirs(Result)\n",
    "else:\n",
    "    print(\"Result Path Already exist\")\n",
    "if not os.path.exists(rover_files):\n",
    "    os.makedirs(rover_files)\n",
    "else:\n",
    "    print(\"\\nRover Path Already exist\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "359ed579-9f9a-4062-86df-3557dfe32f4f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030934.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030936.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030938.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030940.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030942.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030944.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030946.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030948.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030950.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030952.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030954.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030956.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112030958.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112031000.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112031002.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112031004.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112031006.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112031008.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112031010.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112031012.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112031014.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112031016.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112031018.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112031020.T04', 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Applanix/1/5905C00224202112031022.T04']\n"
     ]
    }
   ],
   "source": [
    "#Getting list of files\n",
    "\n",
    "files=[]\n",
    "for file in glob.glob(Raw_GNSS+'*.T04'):\n",
    "    file=file.replace('\\\\','/')\n",
    "    files.append(file)\n",
    "print(files)   "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1aad5948-f5fc-4795-a61c-0c9223cc4e10",
   "metadata": {},
   "source": [
    "## Converting to TGD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1e30865d-8e77-49f2-b685-8c5dc9c46e81",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5905C00224202112030934 already converted \n",
      "5905C00224202112030936 already converted \n",
      "5905C00224202112030938 already converted \n",
      "5905C00224202112030940 already converted \n",
      "5905C00224202112030942 already converted \n",
      "5905C00224202112030944 already converted \n",
      "5905C00224202112030946 already converted \n",
      "5905C00224202112030948 already converted \n",
      "5905C00224202112030950 already converted \n",
      "5905C00224202112030952 already converted \n",
      "5905C00224202112030954 already converted \n",
      "5905C00224202112030956 already converted \n",
      "5905C00224202112030958 already converted \n",
      "5905C00224202112031000 already converted \n",
      "5905C00224202112031002 already converted \n",
      "5905C00224202112031004 already converted \n",
      "5905C00224202112031006 already converted \n",
      "5905C00224202112031008 already converted \n",
      "5905C00224202112031010 already converted \n",
      "5905C00224202112031012 already converted \n",
      "5905C00224202112031014 already converted \n",
      "5905C00224202112031016 already converted \n",
      "5905C00224202112031018 already converted \n",
      "5905C00224202112031020 already converted \n",
      "5905C00224202112031022 already converted \n"
     ]
    }
   ],
   "source": [
    "#Getting the Raw files and convert them to TGD using a specific cmd\n",
    "\n",
    "for file in files:\n",
    "    filename=file.split('/')[-1].split('.T04')[0]\n",
    "    if not os.path.exists(Raw_GNSS + filename +'.tgd'):\n",
    "        print(f'Converting {filename} to TGD')\n",
    "        cmd = runpkr + ' -g ' + ' -d ' + Raw_GNSS + filename + '.T04'\n",
    "        subprocess.call(cmd, shell=False)\n",
    "    else:\n",
    "       print(f'{filename} already converted ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "52e79bac-3d86-4b3e-bedb-74f5649425ab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "List of TGD files to convert to RINEX:\n",
      "['5905C00224202112030934', '5905C00224202112030936', '5905C00224202112030938', '5905C00224202112030940', '5905C00224202112030942', '5905C00224202112030944', '5905C00224202112030946', '5905C00224202112030948', '5905C00224202112030950', '5905C00224202112030952', '5905C00224202112030954', '5905C00224202112030956', '5905C00224202112030958', '5905C00224202112031000', '5905C00224202112031002', '5905C00224202112031004', '5905C00224202112031006', '5905C00224202112031008', '5905C00224202112031010', '5905C00224202112031012', '5905C00224202112031014', '5905C00224202112031016', '5905C00224202112031018', '5905C00224202112031020', '5905C00224202112031022']\n"
     ]
    }
   ],
   "source": [
    "#List of files to convert to RINEX\n",
    "\n",
    "files_tocopy=[]\n",
    "\n",
    "for file in os.listdir(Raw_GNSS):\n",
    "    if file.endswith('.tgd'):\n",
    "        files_tocopy.append(file)\n",
    "        source_path = os.path.join(Raw_GNSS, file)\n",
    "        destination_path = os.path.join(Result, file)\n",
    "        shutil.copy2(source_path, destination_path)\n",
    "print(\"\\nList of TGD files to convert to RINEX:\")\n",
    "\n",
    "TGD_files=[]\n",
    "\n",
    "for file in os.listdir(Result):\n",
    "    if file.endswith('.tgd'):\n",
    "      TGD_files.append(file.split('.tgd')[0])\n",
    "print(TGD_files)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aca9681b-ef1f-405b-92e8-ea79828b2a1d",
   "metadata": {},
   "source": [
    "## Converting to RINEX "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2307a348-c4f4-4855-87a5-d89d6d2f4b9a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5905C00224202112030934 already converted to obs file\n",
      "5905C00224202112030936 already converted to obs file\n",
      "5905C00224202112030938 already converted to obs file\n",
      "5905C00224202112030940 already converted to obs file\n",
      "5905C00224202112030942 already converted to obs file\n",
      "5905C00224202112030944 already converted to obs file\n",
      "5905C00224202112030946 already converted to obs file\n",
      "5905C00224202112030948 already converted to obs file\n",
      "5905C00224202112030950 already converted to obs file\n",
      "5905C00224202112030952 already converted to obs file\n",
      "5905C00224202112030954 already converted to obs file\n",
      "5905C00224202112030956 already converted to obs file\n",
      "5905C00224202112030958 already converted to obs file\n",
      "5905C00224202112031000 already converted to obs file\n",
      "5905C00224202112031002 already converted to obs file\n",
      "5905C00224202112031004 already converted to obs file\n",
      "5905C00224202112031006 already converted to obs file\n",
      "5905C00224202112031008 already converted to obs file\n",
      "5905C00224202112031010 already converted to obs file\n",
      "5905C00224202112031012 already converted to obs file\n",
      "5905C00224202112031014 already converted to obs file\n",
      "5905C00224202112031016 already converted to obs file\n",
      "5905C00224202112031018 already converted to obs file\n",
      "5905C00224202112031020 already converted to obs file\n",
      "5905C00224202112031022 already converted to obs file\n"
     ]
    }
   ],
   "source": [
    "#Getting the TGD files and convert them to Rinex using a specific cmd\n",
    "#For the observation file\n",
    "\n",
    "for file in TGD_files:\n",
    "    filename=file\n",
    "    if not os.path.exists(Result + filename +'.obs'):\n",
    "        print(f'Converting {filename} to Observation file')\n",
    "        command = teqc + ' +C2 '+' +L5 '+ ' +L8 ' + ' -week '+ ' 2186 ' + ' -tr ' + ' d  ' + ' +obs ' + Result + filename + '.obs ' + \\\n",
    "              Result + filename + '.tgd' #Week to modify (add it automaticly)\n",
    "        subprocess.run(command, shell=False,stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)\n",
    "    else:\n",
    "        print(f'{filename} already converted to obs file')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "355235b6-a98e-47f0-8663-a70dfe4c872b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5905C00224202112030934 already converted to nav file\n",
      "5905C00224202112030936 already converted to nav file\n",
      "5905C00224202112030938 already converted to nav file\n",
      "5905C00224202112030940 already converted to nav file\n",
      "5905C00224202112030942 already converted to nav file\n",
      "5905C00224202112030944 already converted to nav file\n",
      "5905C00224202112030946 already converted to nav file\n",
      "5905C00224202112030948 already converted to nav file\n",
      "5905C00224202112030950 already converted to nav file\n",
      "5905C00224202112030952 already converted to nav file\n",
      "5905C00224202112030954 already converted to nav file\n",
      "5905C00224202112030956 already converted to nav file\n",
      "5905C00224202112030958 already converted to nav file\n",
      "5905C00224202112031000 already converted to nav file\n",
      "5905C00224202112031002 already converted to nav file\n",
      "5905C00224202112031004 already converted to nav file\n",
      "5905C00224202112031006 already converted to nav file\n",
      "5905C00224202112031008 already converted to nav file\n",
      "5905C00224202112031010 already converted to nav file\n",
      "5905C00224202112031012 already converted to nav file\n",
      "5905C00224202112031014 already converted to nav file\n",
      "5905C00224202112031016 already converted to nav file\n",
      "5905C00224202112031018 already converted to nav file\n",
      "5905C00224202112031020 already converted to nav file\n",
      "5905C00224202112031022 already converted to nav file\n"
     ]
    }
   ],
   "source": [
    "#For the navigation file\n",
    "for file in TGD_files:\n",
    "    filename=file\n",
    "    if not os.path.exists(Result + filename +'.nav'):\n",
    "        print(f'Converting {filename} to Navigation file')\n",
    "        command = teqc +  ' +nav ' + Result + filename + '.nav ' + \\\n",
    "              Result + filename + '.tgd' #Week to modify (add it automaticly)\n",
    "        subprocess.run(command, shell=False,stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)\n",
    "    else:\n",
    "        print(f'{filename} already converted to nav file')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7b7d81f-0a8d-4244-8e49-badb85f1f4f1",
   "metadata": {},
   "source": [
    "## Merging RINEX files"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09d57f62-0dbe-4b8b-bbaa-de4148c9863b",
   "metadata": {},
   "source": [
    "The rover records the observation separatly every 2 min, that why we need to merge the observations files in one file, the same thing for the navigation files  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "91779262-bd0e-4d27-b9f1-db7cf492e5e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Result/Rover/5905C00224202112030934-5905C00224202112031022'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rover_files+str(TGD_files[0]+'-'+TGD_files[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7c7066e8-b905-4da3-a807-dd01e87079c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Defining a fct for merge navigation files\n",
    "\n",
    "def merge_nav(nav_files,output):\n",
    "   #Input:\n",
    "   #nav_files: navigation files of the rover\n",
    "   #output: Path of the output\n",
    "   #Output:\n",
    "   #Merged navigation file\n",
    "   cmd = teqc + \" -O.s M {} > {}{}\\n\".format(' '.join(nav_files), output,'.nav')\n",
    "   print(cmd)\n",
    "   result=subprocess.run(cmd,capture_output=True,text=True)\n",
    "   with open (output+'.nav','w') as f:\n",
    "    f.write(result.stdout)\n",
    "    f.close() \n",
    "   return print('navigation merging done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0e706c16-ef39-4aeb-bf46-3241b82265ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Defining a fct for merge observation files\n",
    "\n",
    "def merge_obs(obs_files,output):\n",
    "   #Input:\n",
    "   #Obs_files: Observation files of the rover\n",
    "   #output: Path of the output\n",
    "   #Output:\n",
    "   #Merged Observation file\n",
    "   cmd = teqc +\" -O.s M {} > {}{}\\n\".format(' '.join(obs_files), output,'.obs')\n",
    "   print(cmd)\n",
    "   result=subprocess.run(cmd,capture_output=True,text=True)\n",
    "   with open (output+'.obs','w') as f:\n",
    "    f.write(result.stdout)\n",
    "    f.close() \n",
    "   return print('observation merging done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "19e4dae3-4141-46f3-a06b-642a22944ae2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Observation file already merged\n"
     ]
    }
   ],
   "source": [
    "# Merge the obs files\n",
    "\n",
    "obs_files=[]\n",
    "merged_observation=rover_files+str(TGD_files[0]+'-'+TGD_files[-1])\n",
    "for file in os.listdir(Result):\n",
    "  if file.endswith('.obs'):\n",
    "     obs=file\n",
    "     obs_files.append(obs)\n",
    "if not os.path.exists(merged_observation+'.obs'):\n",
    "  merge_obs(obs_files,merged_observation)# fct for merge\n",
    "else:\n",
    "  print('Observation file already merged')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f9de02c1-0d79-42f6-b16b-ce748628cbd2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Navigation file already merged\n"
     ]
    }
   ],
   "source": [
    "#Merge the nav files\n",
    "\n",
    "nav_files=[]\n",
    "merged_navigation=rover_files+str(TGD_files[0]+'-'+TGD_files[-1])\n",
    "for file in os.listdir(Result):\n",
    "    if file.endswith('.nav'):\n",
    "        navigation=file\n",
    "        nav_files.append(navigation)\n",
    "if not os.path.exists(merged_navigation+'.nav'):\n",
    "  merge_nav(nav_files,merged_navigation) #fct for merge\n",
    "else:\n",
    "    print('Navigation file already merged')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "332b2396-4cee-41d6-a70f-c8e227ca4323",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Result/Rover/5905C00224202112030934-5905C00224202112031022.obs',\n",
       " 'C:/Users/bourriz/GNSS_INS_Processing/UIS_PosPac_HyspexNav_processing/Result/Rover/5905C00224202112030934-5905C00224202112031022.nav')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "observation_path=os.path.join(rover_files,str(TGD_files[0]+'-'+TGD_files[-1])+ '.obs')\n",
    "navigation_path=os.path.join(rover_files,str(TGD_files[0]+'-'+TGD_files[-1])+ '.nav')\n",
    "#get the path of the obs and nav files\n",
    "observation_path, navigation_path"
   ]
  }
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