{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6800da4f",
   "metadata": {},
   "source": [
    "# Mars Express Tracking Data Residuals Analysis\n",
    "\n",
    "This notebook analyzes tracking data residuals from Mars Express during the December 2013 Phobos flyby. We'll compare two tracking systems:\n",
    "\n",
    "- **IFMS (Closed-loop)**: Traditional ground station tracking from New Norcia\n",
    "- **FDETS (Open-loop)**: Advanced Doppler observations from HARTRAO and URUMQI\n",
    "\n",
    "By the end, you'll have computed residuals, visualized the results, and exported the data for further analysis."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bcc7d05",
   "metadata": {},
   "source": [
    "## Part 1: Setting Up the Environment\n",
    "\n",
    "Let's start by importing the tools we need and downloading the mission data from ESA's archives."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "27bf4bc8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Libraries imported successfully\n"
     ]
    }
   ],
   "source": [
    "import csv\n",
    "import numpy as np\n",
    "import random\n",
    "import os\n",
    "from datetime import datetime\n",
    "from collections import defaultdict\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from pathlib import Path\n",
    "\n",
    "# TudatPy imports for astrodynamics computations\n",
    "from tudatpy.astro import time_representation\n",
    "from tudatpy.math import interpolators\n",
    "from tudatpy.dynamics import environment_setup, environment\n",
    "from tudatpy.estimation.observations_setup.ancillary_settings import FrequencyBands\n",
    "from tudatpy.estimation.observable_models_setup import links\n",
    "from tudatpy.estimation import observable_models_setup, observations_setup, observations\n",
    "import tudatpy.data as data\n",
    "from tudatpy.data.mission_data_downloader import *\n",
    "from tudatpy.interface import spice\n",
    "\n",
    "print(\"✓ Libraries imported successfully\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4135380",
   "metadata": {},
   "source": [
    "### Downloading Mars Express Data\n",
    "\n",
    "We'll download tracking data from ESA's Planetary Science Archive for the period around the Phobos flyby (December 27-31, 2013). This includes:\n",
    "- **Meteorological data** for atmospheric corrections\n",
    "- **IFMS tracking files** with closed-loop Doppler measurements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "13a5bde4",
   "metadata": {
    "lines_to_next_cell": 1
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Mars Express mission data from ESA archives...\n",
      "Checking URL: https://archives.esac.esa.int/psa/ftp/MARS-EXPRESS/MRS/MEX-X-MRS-1-2-3-EXT4-3619-V1.0/CALIB/CLOSED_LOOP/IFMS/MET/\n"
     ]
    }
   ],
   "source": [
    "print(\"Downloading Mars Express mission data from ESA archives...\")\n",
    "\n",
    "# Initialize data loader\n",
    "object = LoadPDS()\n",
    "spice.clear_kernels()\n",
    "\n",
    "# Mission configuration\n",
    "input_mission = 'mex'\n",
    "local_path = './mex_archive'\n",
    "start_date_mex = datetime(2013, 12, 27)\n",
    "end_date_mex = datetime(2013, 12, 31)\n",
    "\n",
    "# Define URLs for meteorological and IFMS data\n",
    "custom_met_urls = [\n",
    "    'https://archives.esac.esa.int/psa/ftp/MARS-EXPRESS/MRS/MEX-X-MRS-1-2-3-EXT4-3619-V1.0/CALIB/CLOSED_LOOP/IFMS/MET/',\n",
    "    'https://archives.esac.esa.int/psa/ftp/MARS-EXPRESS/MRS/MEX-X-MRS-1-2-3-EXT4-3624-V1.0/CALIB/CLOSED_LOOP/IFMS/MET/',\n",
    "    'https://archives.esac.esa.int/psa/ftp/MARS-EXPRESS/MRS/MEX-X-MRS-1-2-3-EXT4-3628-V1.0/CALIB/CLOSED_LOOP/IFMS/MET/'\n",
    "]\n",
    "\n",
    "custom_ifms_urls = [\n",
    "    'https://archives.esac.esa.int/psa/ftp/MARS-EXPRESS/MRS/MEX-X-MRS-1-2-3-EXT4-3619-V1.0/DATA/LEVEL02/CLOSED_LOOP/IFMS/DP2',\n",
    "    'https://archives.esac.esa.int/psa/ftp/MARS-EXPRESS/MRS/MEX-X-MRS-1-2-3-EXT4-3624-V1.0/DATA/LEVEL02/CLOSED_LOOP/IFMS/DP2',\n",
    "    'https://archives.esac.esa.int/psa/ftp/MARS-EXPRESS/MRS/MEX-X-MRS-1-2-3-EXT4-3628-V1.0/DATA/LEVEL02/CLOSED_LOOP/IFMS/DP2'\n",
    "]\n",
    "\n",
    "# Download meteorological data\n",
    "for custom_met_url in custom_met_urls:\n",
    "    object.add_custom_mission_kernel_url(input_mission, custom_met_url)\n",
    "    custom_met_pattern = '^(?P<station>M32ICL3L1B)_(?P<type>[A-Z0-9]+)_(?P<date_file>\\d+)_(?P<number>\\d+)(?P<extension>\\.TAB)$'\n",
    "    object.add_custom_mission_kernel_pattern(input_mission, 'met', custom_met_pattern)\n",
    "    object.dynamic_download_url_files_single_time(input_mission, local_path, start_date_mex, end_date_mex, custom_met_url)\n",
    "\n",
    "# Download IFMS data\n",
    "for custom_ifms_url in custom_ifms_urls:\n",
    "    object.add_custom_mission_kernel_url(input_mission, custom_ifms_url)\n",
    "    custom_ifms_pattern = '^(?P<station>M32ICL3L02|M32ICL2L02)_(?P<type>D2X)_(?P<date_file>\\d+)_(?P<number>\\d+)(?P<extension>\\.TAB)$'\n",
    "    object.add_custom_mission_kernel_pattern(input_mission, 'ifms', custom_ifms_pattern)\n",
    "    object.dynamic_download_url_files_single_time(input_mission, local_path, start_date_mex, end_date_mex, custom_ifms_url)\n",
    "\n",
    "print(\"✓ Data download complete!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6227becd",
   "metadata": {},
   "source": [
    "### Configure Your Analysis\n",
    "\n",
    "**Important:** Update `BASE_DIR` to match your local directory structure. This is where your SPICE kernels, FDETS data, and other reference files are stored."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "58989556",
   "metadata": {
    "lines_to_next_cell": 1
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Configuration complete\n",
      "  Analysis period: 2013-12-28 to 2013-12-31\n"
     ]
    }
   ],
   "source": [
    "# =============================================================================\n",
    "# USER CONFIGURATION - UPDATE THESE PATHS\n",
    "# =============================================================================\n",
    "\n",
    "BASE_DIR = '/Users/lgisolfi/Desktop/mex_phobos_flyby'  # ← Change this to your base directory\n",
    "\n",
    "# Subdirectories\n",
    "KERNELS_FOLDER = os.path.join(BASE_DIR, 'kernels')\n",
    "FDETS_FOLDER = os.path.join(BASE_DIR, 'fdets/complete')\n",
    "IFMS_FOLDER = './mex_archive/ifms_filtered'\n",
    "OUTPUT_DIR = os.path.join(BASE_DIR, 'output')\n",
    "\n",
    "# Reference data\n",
    "WEATHER_DATA_DIR = './mex_archive/met'\n",
    "VMF_FILE = os.path.join(BASE_DIR, 'VMF/y2013.vmf3_r.txt')\n",
    "\n",
    "# Analysis time window\n",
    "ANALYSIS_START = datetime(2013, 12, 28, 0, 0, 0)\n",
    "ANALYSIS_END = datetime(2013, 12, 31, 0, 0, 0)\n",
    "\n",
    "# Mission configuration\n",
    "SPACECRAFT_NAME = \"MEX\"\n",
    "SPACECRAFT_CENTRAL_BODY = \"Mars\"\n",
    "\n",
    "# FDETS files to process (these should be in your FDETS_FOLDER)\n",
    "FDETS_FILES_TO_PROCESS = [\n",
    "    'Fdets.mex2013.12.28.Ur.complete.r2i.txt',  # Urumqi\n",
    "    'Fdets.mex2013.12.28.Ht.complete.r2i.txt'   # HARTRAO\n",
    "]\n",
    "\n",
    "print(f\"✓ Configuration complete\")\n",
    "print(f\"  Analysis period: {ANALYSIS_START.date()} to {ANALYSIS_END.date()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3625db4f",
   "metadata": {},
   "source": [
    "### Helper Functions\n",
    "\n",
    "These utility functions help us organize data by ground station and map station codes to readable names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "56de8cd6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Helper functions defined\n"
     ]
    }
   ],
   "source": [
    "def get_weather_files_by_station(weather_data_dir):\n",
    "    \"\"\"Group weather files by station code\"\"\"\n",
    "    if not os.path.exists(weather_data_dir):\n",
    "        print(f\"Warning: Weather data directory not found at {weather_data_dir}\")\n",
    "        return {}\n",
    "\n",
    "    station_files = defaultdict(list)\n",
    "    for f in os.listdir(weather_data_dir):\n",
    "        if f.startswith('.'):\n",
    "            continue\n",
    "\n",
    "        filename = os.path.basename(f)\n",
    "        if len(filename) <= 3:\n",
    "            continue\n",
    "\n",
    "        station_code = filename[1:3]\n",
    "        full_path = os.path.join(weather_data_dir, f)\n",
    "\n",
    "        # Map station codes (60→63, 10→14, etc.)\n",
    "        if station_code == '60':\n",
    "            station_files['63'].append(full_path)\n",
    "        elif station_code == '10':\n",
    "            station_files['14'].append(full_path)\n",
    "        elif station_code == '32':\n",
    "            station_files['32'].append(full_path)\n",
    "\n",
    "    return dict(station_files)\n",
    "\n",
    "def get_ifms_files_by_station(ifms_data_dir):\n",
    "    \"\"\"Group IFMS files by station code\"\"\"\n",
    "    if not os.path.exists(ifms_data_dir):\n",
    "        return {}\n",
    "\n",
    "    station_files = defaultdict(list)\n",
    "    for f in os.listdir(ifms_data_dir):\n",
    "        if f.startswith('.'):\n",
    "            continue\n",
    "\n",
    "        filename = os.path.basename(f)\n",
    "        if len(filename) > 3:\n",
    "            station_code = filename[1:3]\n",
    "            if station_code in ['63', '14', '32']:\n",
    "                station_files[station_code].append(os.path.join(ifms_data_dir, f))\n",
    "\n",
    "    return dict(station_files)\n",
    "\n",
    "def code_to_site(site_ID):\n",
    "    \"\"\"Convert station code to name\"\"\"\n",
    "    mapping = {'32': 'NWNORCIA', '63': 'DSS64', '14': 'DSS14'}\n",
    "    return mapping.get(site_ID, None)\n",
    "\n",
    "def ID_to_site(site_ID):\n",
    "    \"\"\"Convert FDETS site ID to full station name\"\"\"\n",
    "    mapping = {\n",
    "        'Ur': 'URUMQI', 'Ht': 'HART15M', 'Hh': 'HARTRAO',\n",
    "        'Wz': 'WETTZELL', 'On': 'ONSALA60', 'Ys': 'YEBES40M'\n",
    "        # Add more as needed\n",
    "    }\n",
    "    return mapping.get(site_ID, None)\n",
    "\n",
    "def get_fdets_receiving_station_name(fdets_file):\n",
    "    \"\"\"Extract station name from FDETS filename\"\"\"\n",
    "    site_id = os.path.basename(fdets_file).split('.')[4]\n",
    "    return ID_to_site(site_id)\n",
    "\n",
    "def generate_random_color():\n",
    "    \"\"\"Generate random color for plotting\"\"\"\n",
    "    return \"#{:02x}{:02x}{:02x}\".format(\n",
    "        random.randint(0, 255), random.randint(0, 255), random.randint(0, 255)\n",
    "    )\n",
    "\n",
    "print(\"✓ Helper functions defined\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3238ed53",
   "metadata": {},
   "source": [
    "## Part 2: Creating the Solar System Environment\n",
    "\n",
    "Now we'll set up the physical environment needed for our analysis. This includes loading SPICE kernels (which contain precise ephemerides) and configuring the celestial bodies."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a89dd0c",
   "metadata": {},
   "source": [
    "### Loading SPICE Kernels\n",
    "\n",
    "SPICE kernels provide precise position and orientation data for spacecraft and celestial bodies. We'll load both standard kernels and Mars Express mission-specific kernels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "76af6331",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading SPICE kernels...\n",
      "✓ Loaded 5 mission-specific kernels\n"
     ]
    }
   ],
   "source": [
    "print(\"Loading SPICE kernels...\")\n",
    "\n",
    "# Load standard planetary ephemerides\n",
    "spice.load_standard_kernels()\n",
    "\n",
    "# Load Mars Express mission kernels\n",
    "kernel_count = 0\n",
    "for kernel in os.listdir(KERNELS_FOLDER):\n",
    "    if not kernel.startswith('.'):\n",
    "        kernel_path = os.path.join(KERNELS_FOLDER, kernel)\n",
    "        spice.load_kernel(kernel_path)\n",
    "        kernel_count += 1\n",
    "\n",
    "print(f\"✓ Loaded {kernel_count} mission-specific kernels\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30053c73",
   "metadata": {},
   "source": [
    "### Defining the Time Window\n",
    "\n",
    "We'll convert our analysis dates into TudatPy's time format (seconds since J2000 epoch)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4061cdaf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Time window established:\n",
      "  Start: 441460800.0 seconds since J2000\n",
      "  End: 441720000.0 seconds since J2000\n"
     ]
    }
   ],
   "source": [
    "start_time = time_representation.Time(\n",
    "    time_representation.DateTime.to_epoch(\n",
    "        time_representation.DateTime.from_python_datetime(ANALYSIS_START)\n",
    "    )\n",
    ")\n",
    "end_time = time_representation.Time(\n",
    "    time_representation.DateTime.to_epoch(\n",
    "        time_representation.DateTime.from_python_datetime(ANALYSIS_END)\n",
    "    )\n",
    ")\n",
    "\n",
    "start_time_seconds = time_representation.DateTime.to_epoch(\n",
    "    time_representation.DateTime.from_python_datetime(ANALYSIS_START)\n",
    ")\n",
    "end_time_seconds = time_representation.DateTime.to_epoch(\n",
    "    time_representation.DateTime.from_python_datetime(ANALYSIS_END)\n",
    ")\n",
    "\n",
    "print(f\"✓ Time window established:\")\n",
    "print(f\"  Start: {start_time_seconds:.1f} seconds since J2000\")\n",
    "print(f\"  End: {end_time_seconds:.1f} seconds since J2000\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "066820fb",
   "metadata": {},
   "source": [
    "### Building the Celestial Bodies System\n",
    "\n",
    "We'll create a system of bodies including the planets needed for accurate gravitational modeling and light-time corrections. We'll also configure Mars Express and the ground stations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ae3e9210",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Building solar system environment...\n",
      "✓ Earth configured with IAU 2006 rotation model\n"
     ]
    }
   ],
   "source": [
    "print(\"Building solar system environment...\")\n",
    "\n",
    "# Define which celestial bodies to include\n",
    "bodies_to_create = [\"Earth\", \"Sun\", \"Mercury\", \"Venus\", \"Mars\", \"Jupiter\", \"Saturn\", \"Moon\"]\n",
    "global_frame_origin = \"SSB\"  # Solar System Barycenter\n",
    "global_frame_orientation = \"J2000\"\n",
    "\n",
    "# Create default settings for these bodies\n",
    "body_settings = environment_setup.get_default_body_settings_time_limited(\n",
    "    bodies_to_create, start_time, end_time, global_frame_origin, global_frame_orientation\n",
    ")\n",
    "\n",
    "# Configure Earth with high-precision rotation model\n",
    "body_settings.get('Earth').shape_settings = environment_setup.shape.oblate_spherical_spice()\n",
    "body_settings.get('Earth').rotation_model_settings = environment_setup.rotation_model.gcrs_to_itrs(\n",
    "    environment_setup.rotation_model.iau_2006, global_frame_orientation,\n",
    "    interpolators.interpolator_generation_settings(\n",
    "        interpolators.cubic_spline_interpolation(), start_time, end_time, 3600.0),\n",
    "    interpolators.interpolator_generation_settings(\n",
    "        interpolators.cubic_spline_interpolation(), start_time, end_time, 3600.0),\n",
    "    interpolators.interpolator_generation_settings(\n",
    "        interpolators.cubic_spline_interpolation(), start_time, end_time, 60.0)\n",
    ")\n",
    "body_settings.get('Earth').gravity_field_settings.associated_reference_frame = \"ITRS\"\n",
    "\n",
    "print(\"✓ Earth configured with IAU 2006 rotation model\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "047448ca",
   "metadata": {},
   "source": [
    "### Adding Mars Express Spacecraft\n",
    "\n",
    "We'll add Mars Express to our system with its ephemeris interpolated from SPICE data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "67fc6130",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Mars Express spacecraft configured\n",
      "✓ Ground stations added to Earth\n"
     ]
    }
   ],
   "source": [
    "# Add spacecraft with interpolated ephemeris\n",
    "body_settings.add_empty_settings(SPACECRAFT_NAME)\n",
    "body_settings.get(SPACECRAFT_NAME).ephemeris_settings = environment_setup.ephemeris.interpolated_spice(\n",
    "    start_time, end_time, 10.0, SPACECRAFT_CENTRAL_BODY, global_frame_orientation\n",
    ")\n",
    "body_settings.get(SPACECRAFT_NAME).rotation_model_settings = environment_setup.rotation_model.spice(\n",
    "    global_frame_orientation, SPACECRAFT_NAME + \"_SPACECRAFT\", \"\"\n",
    ")\n",
    "\n",
    "# Add ground stations\n",
    "body_settings.get(\"Earth\").ground_station_settings = environment_setup.ground_station.radio_telescope_stations()\n",
    "\n",
    "# Create the complete system\n",
    "bodies = environment_setup.create_system_of_bodies(body_settings)\n",
    "\n",
    "# Configure spacecraft transponder\n",
    "vehicle_sys = environment.VehicleSystems()\n",
    "vehicle_sys.set_default_transponder_turnaround_ratio_function()\n",
    "bodies.get_body(SPACECRAFT_NAME).system_models = vehicle_sys\n",
    "\n",
    "print(\"✓ Mars Express spacecraft configured\")\n",
    "print(\"✓ Ground stations added to Earth\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2c734c7",
   "metadata": {},
   "source": [
    "## Part 3: Processing Tracking Data\n",
    "\n",
    "Now comes the core analysis. We'll process both IFMS (closed-loop) and FDETS (open-loop) observations, computing residuals between observed and predicted Doppler measurements."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78441ad6",
   "metadata": {},
   "source": [
    "### Setting Up for IFMS Processing\n",
    "\n",
    "Before processing, we need to configure the antenna position on Mars Express and load weather data for tropospheric corrections."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2b1599dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Preparing for IFMS data processing...\n",
      "✓ Found 7 IFMS files to process\n",
      "✓ Antenna ephemeris configured\n",
      "✓ Weather data loaded into ground stations\n"
     ]
    }
   ],
   "source": [
    "print(\"Preparing for IFMS data processing...\")\n",
    "\n",
    "# Initialize results storage\n",
    "ifms_station_residuals = {}\n",
    "processed_ifms_count = 0\n",
    "\n",
    "# Frequency bands used\n",
    "reception_band = FrequencyBands.x_band\n",
    "transmission_band = FrequencyBands.x_band\n",
    "\n",
    "# Get IFMS files\n",
    "ifms_files = []\n",
    "if os.path.exists(IFMS_FOLDER):\n",
    "    for file in os.listdir(IFMS_FOLDER):\n",
    "        if not file.startswith('.'):\n",
    "            ifms_files.append(os.path.join(IFMS_FOLDER, file))\n",
    "\n",
    "print(f\"✓ Found {len(ifms_files)} IFMS files to process\")\n",
    "\n",
    "# Configure MEX antenna position (offset from center of mass)\n",
    "com_position = [-1.3, 0.0, 0.0]\n",
    "antenna_state = np.zeros((6, 1))\n",
    "antenna_state[:3, 0] = spice.get_body_cartesian_position_at_epoch(\n",
    "    \"-41020\", \"-41000\", \"MEX_SPACECRAFT\", \"none\", start_time\n",
    ")\n",
    "antenna_state[:3, 0] = antenna_state[:3, 0] - com_position\n",
    "\n",
    "antenna_ephemeris_settings = environment_setup.ephemeris.constant(\n",
    "    antenna_state, \"-41000\", \"MEX_SPACECRAFT\"\n",
    ")\n",
    "antenna_ephemeris = environment_setup.ephemeris.create_ephemeris(\n",
    "    antenna_ephemeris_settings, \"Antenna\"\n",
    ")\n",
    "\n",
    "time_scale_converter = time_representation.default_time_scale_converter()\n",
    "\n",
    "# Load weather data into ground stations\n",
    "weather_dict = get_weather_files_by_station(WEATHER_DATA_DIR)\n",
    "for station_code in weather_dict.keys():\n",
    "    weather_files = weather_dict[station_code]\n",
    "    data.set_estrack_weather_data_in_ground_stations(bodies, weather_files, code_to_site(station_code))\n",
    "\n",
    "print(\"✓ Antenna ephemeris configured\")\n",
    "print(\"✓ Weather data loaded into ground stations\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e9c1ad0",
   "metadata": {},
   "source": [
    "### Processing IFMS and FDETS Files\n",
    "\n",
    "This is where the heavy lifting happens. For each IFMS file:\n",
    "1. Load the observations\n",
    "2. Create observation models with tropospheric corrections\n",
    "3. Simulate expected observations\n",
    "4. Compute residuals (observed - simulated)\n",
    "5. Process corresponding FDETS files if available\n",
    "\n",
    "This may take a few minutes depending on data volume."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6fb08fdd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing IFMS and FDETS data...\n",
      "This may take several minutes...\n",
      "\n",
      "[1/7] Processing NWNORCIA...\n",
      "  Processing FDETS: URUMQI...\n",
      "  Processing FDETS: HART15M...\n",
      "[2/7] Processing NWNORCIA...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning when setting reference point (MEX, Antenna), the reference point already exists. Its ephemeris will be overwritten."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Processing FDETS: URUMQI...\n",
      "  Processing FDETS: HART15M...\n",
      "[3/7] Processing NWNORCIA...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning when setting reference point (MEX, Antenna), the reference point already exists. Its ephemeris will be overwritten."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Processing FDETS: URUMQI...\n",
      "  Processing FDETS: HART15M...\n",
      "[4/7] Processing NWNORCIA...\n",
      "  Processing FDETS: URUMQI...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning when setting reference point (MEX, Antenna), the reference point already exists. Its ephemeris will be overwritten."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Processing FDETS: HART15M...\n",
      "[5/7] Processing NWNORCIA...\n",
      "  Processing FDETS: URUMQI...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning when setting reference point (MEX, Antenna), the reference point already exists. Its ephemeris will be overwritten.Warning when setting reference point (MEX, Antenna), the reference point already exists. Its ephemeris will be overwritten."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Processing FDETS: HART15M...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning when setting reference point (MEX, Antenna), the reference point already exists. Its ephemeris will be overwritten."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6/7] Processing NWNORCIA...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning when setting reference point (MEX, Antenna), the reference point already exists. Its ephemeris will be overwritten."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Processing FDETS: URUMQI...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning when setting reference point (MEX, Antenna), the reference point already exists. Its ephemeris will be overwritten."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Processing FDETS: HART15M...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning when setting reference point (MEX, Antenna), the reference point already exists. Its ephemeris will be overwritten."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[7/7] Processing NWNORCIA...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning when setting reference point (MEX, Antenna), the reference point already exists. Its ephemeris will be overwritten."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Processing FDETS: URUMQI...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning when setting reference point (MEX, Antenna), the reference point already exists. Its ephemeris will be overwritten."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Processing FDETS: HART15M...\n",
      "\n",
      "✓ Processing complete!\n",
      "  IFMS files processed: 7\n",
      "  FDETS files processed: 6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning when setting reference point (MEX, Antenna), the reference point already exists. Its ephemeris will be overwritten."
     ]
    }
   ],
   "source": [
    "print(\"Processing IFMS and FDETS data...\")\n",
    "print(\"This may take several minutes...\\n\")\n",
    "\n",
    "# Storage for FDETS results\n",
    "fdets_station_residuals = {}\n",
    "processed_fdets_count = 0\n",
    "\n",
    "# FDETS configuration\n",
    "base_frequency = 8412e6\n",
    "column_types = [\n",
    "    \"utc_datetime_string\", \"signal_to_noise_ratio\", \"normalised_spectral_max\",\n",
    "    \"doppler_measured_frequency_hz\", \"doppler_noise_hz\"\n",
    "]\n",
    "\n",
    "# Station name mapping\n",
    "station_mapping = {\n",
    "    '14': 'DSS14',\n",
    "    '63': 'DSS63',\n",
    "    '32': 'NWNORCIA'\n",
    "}\n",
    "\n",
    "# Process each IFMS file\n",
    "for ifms_idx, ifms_file in enumerate(ifms_files, 1):\n",
    "    filename = os.path.basename(ifms_file)\n",
    "\n",
    "    # Extract station code\n",
    "    if len(filename) <= 3:\n",
    "        continue\n",
    "    station_code = filename[1:3]\n",
    "\n",
    "    if station_code not in station_mapping:\n",
    "        continue\n",
    "\n",
    "    transmitting_station_name = station_mapping[station_code]\n",
    "    print(f\"[{ifms_idx}/{len(ifms_files)}] Processing {transmitting_station_name}...\")\n",
    "\n",
    "    # Load IFMS observations\n",
    "    ifms_collection = observations_setup.observations_wrapper.observations_from_ifms_files(\n",
    "        [ifms_file], bodies, SPACECRAFT_NAME, transmitting_station_name,\n",
    "        reception_band, transmission_band\n",
    "    )\n",
    "\n",
    "    # Filter by time window\n",
    "    time_filter = observations.observations_processing.observation_filter(\n",
    "        observations.observations_processing.ObservationFilterType.time_bounds_filtering,\n",
    "        start_time, end_time, use_opposite_condition=True\n",
    "    )\n",
    "\n",
    "    ifms_collection.filter_observations(time_filter)\n",
    "    ifms_collection.remove_empty_observation_sets()\n",
    "\n",
    "    if len(ifms_collection.get_concatenated_observations()) == 0:\n",
    "        print(f\"  No observations in time window, skipping\")\n",
    "        continue\n",
    "\n",
    "    # Set reference point to antenna\n",
    "    ifms_collection.set_reference_point(\n",
    "        bodies, antenna_ephemeris, \"Antenna\", \"MEX\", links.retransmitter\n",
    "    )\n",
    "\n",
    "    # Configure troposphere corrections\n",
    "    observable_models_setup.light_time_corrections.set_vmf_troposphere_data(\n",
    "        [VMF_FILE], True, False, bodies, False, True\n",
    "    )\n",
    "\n",
    "    # Define light-time corrections\n",
    "    light_time_corrections = [\n",
    "        observable_models_setup.light_time_corrections.first_order_relativistic_light_time_correction([\"Sun\"]),\n",
    "        observable_models_setup.light_time_corrections.saastamoinen_tropospheric_light_time_correction()\n",
    "    ]\n",
    "\n",
    "    # Create observation models\n",
    "    doppler_link_ends = ifms_collection.link_definitions_per_observable[\n",
    "        observable_models_setup.model_settings.dsn_n_way_averaged_doppler_type\n",
    "    ]\n",
    "\n",
    "    observation_model_settings = []\n",
    "    for link_definition in doppler_link_ends:\n",
    "        observation_model_settings.append(\n",
    "            observable_models_setup.model_settings.dsn_n_way_doppler_averaged(\n",
    "                link_definition, light_time_corrections, subtract_doppler_signature=False\n",
    "            )\n",
    "        )\n",
    "\n",
    "    # Create simulators\n",
    "    observation_simulators = observations_setup.observations_simulation_settings.create_observation_simulators(\n",
    "        observation_model_settings, bodies\n",
    "    )\n",
    "\n",
    "    # Compute residuals\n",
    "    observations.compute_residuals_and_dependent_variables(\n",
    "        ifms_collection, observation_simulators, bodies\n",
    "    )\n",
    "\n",
    "    # Filter outliers\n",
    "    residual_filter = observations.observations_processing.observation_filter(\n",
    "        observations.observations_processing.ObservationFilterType.residual_filtering, 0.1\n",
    "    )\n",
    "    ifms_collection.filter_observations(residual_filter)\n",
    "    ifms_collection.remove_empty_observation_sets()\n",
    "\n",
    "    if len(ifms_collection.get_concatenated_observations()) == 0:\n",
    "        print(f\"  All observations filtered out, skipping\")\n",
    "        continue\n",
    "\n",
    "    # Extract results\n",
    "    times = ifms_collection.get_concatenated_observation_times()\n",
    "    times_utc = [time_scale_converter.convert_time(\n",
    "        input_scale=time_representation.tdb_scale,\n",
    "        output_scale=time_representation.utc_scale,\n",
    "        input_value=t) for t in times]\n",
    "    utc_times = [time_representation.DateTime.to_python_datetime(\n",
    "        time_representation.DateTime.from_epoch(t)) for t in times_utc]\n",
    "\n",
    "    residuals = ifms_collection.get_concatenated_residuals()\n",
    "    mean_residuals = ifms_collection.get_mean_residuals()\n",
    "    rms_residuals = ifms_collection.get_rms_residuals()\n",
    "\n",
    "    # Store IFMS results\n",
    "    if transmitting_station_name not in ifms_station_residuals:\n",
    "        ifms_station_residuals[transmitting_station_name] = {\n",
    "            'times': [], 'utc_times': [], 'residuals': [], 'mean': [], 'rms': []\n",
    "        }\n",
    "\n",
    "    ifms_station_residuals[transmitting_station_name]['times'].extend(times)\n",
    "    ifms_station_residuals[transmitting_station_name]['utc_times'].extend(utc_times)\n",
    "    ifms_station_residuals[transmitting_station_name]['residuals'].extend(residuals)\n",
    "    ifms_station_residuals[transmitting_station_name]['mean'].append(mean_residuals)\n",
    "    ifms_station_residuals[transmitting_station_name]['rms'].append(rms_residuals)\n",
    "\n",
    "    processed_ifms_count += 1\n",
    "\n",
    "    # Define time filter based on IFMS coverage\n",
    "    start_time_ifms = time_representation.Time(times[0])\n",
    "    end_time_ifms = time_representation.Time(times[-1])\n",
    "    time_filter_based_on_ifms = observations.observations_processing.observation_filter(\n",
    "        observations.observations_processing.ObservationFilterType.time_bounds_filtering,\n",
    "        start_time_ifms, end_time_ifms, use_opposite_condition=True\n",
    "    )\n",
    "\n",
    "    # Process corresponding FDETS files\n",
    "    for fdets_filename in FDETS_FILES_TO_PROCESS:\n",
    "        fdets_file = os.path.join(FDETS_FOLDER, fdets_filename)\n",
    "\n",
    "        if not os.path.exists(fdets_file):\n",
    "            continue\n",
    "\n",
    "        site_name = get_fdets_receiving_station_name(fdets_file)\n",
    "        if site_name is None:\n",
    "            continue\n",
    "\n",
    "        # Check if station is available\n",
    "        available_stations = [station[1] for station in environment_setup.get_ground_station_list(bodies.get_body(\"Earth\"))]\n",
    "        if site_name not in available_stations:\n",
    "            continue\n",
    "\n",
    "        print(f\"  Processing FDETS: {site_name}...\")\n",
    "\n",
    "        # Load FDETS observations\n",
    "        fdets_collection = observations_setup.observations_wrapper.observations_from_fdets_files(\n",
    "            fdets_file, base_frequency, column_types, SPACECRAFT_NAME,\n",
    "            transmitting_station_name, site_name, reception_band, transmission_band\n",
    "        )\n",
    "\n",
    "        fdets_collection.filter_observations(time_filter_based_on_ifms)\n",
    "        fdets_collection.remove_empty_observation_sets()\n",
    "\n",
    "        if len(fdets_collection.get_concatenated_observations()) == 0:\n",
    "            continue\n",
    "\n",
    "        # Define link\n",
    "        link_ends_fdets = {\n",
    "            links.receiver: links.body_reference_point_link_end_id('Earth', site_name),\n",
    "            links.retransmitter: links.body_reference_point_link_end_id('MEX', 'Antenna'),\n",
    "            links.transmitter: links.body_reference_point_link_end_id('Earth', transmitting_station_name),\n",
    "        }\n",
    "        link_definition_fdets = links.LinkDefinition(link_ends_fdets)\n",
    "\n",
    "        fdets_collection.set_reference_point(\n",
    "            bodies, antenna_ephemeris, \"Antenna\", \"MEX\", links.retransmitter\n",
    "        )\n",
    "\n",
    "        # Create observation model\n",
    "        observation_model_settings_fdets = [\n",
    "            observable_models_setup.model_settings.doppler_measured_frequency(\n",
    "                link_definition_fdets, light_time_corrections\n",
    "            )\n",
    "        ]\n",
    "\n",
    "        observation_simulators_fdets = observations_setup.observations_simulation_settings.create_observation_simulators(\n",
    "            observation_model_settings_fdets, bodies\n",
    "        )\n",
    "\n",
    "        # Compute residuals\n",
    "        observations.compute_residuals_and_dependent_variables(\n",
    "            fdets_collection, observation_simulators_fdets, bodies\n",
    "        )\n",
    "\n",
    "        fdets_collection.filter_observations(residual_filter)\n",
    "        fdets_collection.remove_empty_observation_sets()\n",
    "\n",
    "        if len(fdets_collection.get_concatenated_observations()) == 0:\n",
    "            continue\n",
    "\n",
    "        # Extract FDETS results\n",
    "        times_fdets = fdets_collection.get_concatenated_observation_times()\n",
    "        times_utc_fdets = [time_scale_converter.convert_time(\n",
    "            input_scale=time_representation.tdb_scale,\n",
    "            output_scale=time_representation.utc_scale,\n",
    "            input_value=t) for t in times_fdets]\n",
    "        utc_times_fdets = [time_representation.DateTime.to_python_datetime(\n",
    "            time_representation.DateTime.from_epoch(t)) for t in times_utc_fdets]\n",
    "\n",
    "        residuals_fdets = fdets_collection.get_concatenated_residuals()\n",
    "        mean_residuals_fdets = fdets_collection.get_mean_residuals()\n",
    "        rms_residuals_fdets = fdets_collection.get_rms_residuals()\n",
    "\n",
    "        # Store FDETS results\n",
    "        if site_name not in fdets_station_residuals:\n",
    "            fdets_station_residuals[site_name] = {\n",
    "                'times': [], 'utc_times': [], 'residuals': [], 'mean': [], 'rms': [],\n",
    "                'start_time': [], 'end_time': [], 'transmitting_station': []\n",
    "            }\n",
    "\n",
    "        fdets_station_residuals[site_name]['times'].extend(times_fdets)\n",
    "        fdets_station_residuals[site_name]['utc_times'].extend(utc_times_fdets)\n",
    "        fdets_station_residuals[site_name]['residuals'].extend(residuals_fdets)\n",
    "        fdets_station_residuals[site_name]['mean'].append(mean_residuals_fdets)\n",
    "        fdets_station_residuals[site_name]['rms'].append(rms_residuals_fdets)\n",
    "        fdets_station_residuals[site_name]['transmitting_station'].append(transmitting_station_name)\n",
    "\n",
    "        processed_fdets_count += 1\n",
    "\n",
    "print(f\"\\n✓ Processing complete!\")\n",
    "print(f\"  IFMS files processed: {processed_ifms_count}\")\n",
    "print(f\"  FDETS files processed: {processed_fdets_count}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ccd97e6b",
   "metadata": {},
   "source": [
    "## Part 4: Visualizing the Results\n",
    "\n",
    "Now let's see what the residuals look like! We'll create two visualizations:\n",
    "1. **Full timeline view** - All residuals across the entire analysis period\n",
    "2. **Detailed subset** - A closer look at a specific time window with distribution plots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5d91629",
   "metadata": {},
   "source": [
    "### Combined Residuals Plot\n",
    "\n",
    "This plot shows all IFMS and FDETS observations together. Different stations are color-coded, and you can see the RMS (root-mean-square) value for each station in the legend."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e4b973bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating combined residuals visualization...\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Overall RMS across all stations: 20.31 mHz\n"
     ]
    }
   ],
   "source": [
    "print(\"Creating combined residuals visualization...\")\n",
    "\n",
    "plt.figure(figsize=(14, 8))\n",
    "\n",
    "# Color scheme for different stations\n",
    "station_colors = {\n",
    "    'NWNORCIA': 'lightgray',\n",
    "    'HART15M': 'orchid',\n",
    "    'URUMQI': 'royalblue',\n",
    "    'DSS14': 'red',\n",
    "    'DSS63': 'green',\n",
    "    'ONSALA60': 'orange'\n",
    "}\n",
    "\n",
    "added_labels = set()\n",
    "all_residuals = []\n",
    "\n",
    "# Plot IFMS residuals (circles)\n",
    "for station_name, ifms_data in ifms_station_residuals.items():\n",
    "    color = station_colors.get(station_name, generate_random_color())\n",
    "\n",
    "    utc_times = np.array(ifms_data['utc_times'])\n",
    "    residuals = np.array(ifms_data['residuals'])\n",
    "    station_rms = np.sqrt(np.mean(residuals**2))\n",
    "\n",
    "    plt.scatter(\n",
    "        utc_times, residuals,\n",
    "        color=color, marker='o', s=15, alpha=0.7,\n",
    "        label=f\"{station_name} (IFMS) - RMS: {station_rms*1000:.2f} mHz\"\n",
    "        if f\"{station_name}_IFMS\" not in added_labels else None\n",
    "    )\n",
    "    added_labels.add(f\"{station_name}_IFMS\")\n",
    "    all_residuals.append(residuals)\n",
    "\n",
    "# Plot FDETS residuals (plus signs)\n",
    "for station_name, fdets_data in fdets_station_residuals.items():\n",
    "    color = station_colors.get(station_name, generate_random_color())\n",
    "\n",
    "    utc_times = np.array(fdets_data['utc_times'])\n",
    "    residuals = np.array(fdets_data['residuals'])\n",
    "    station_rms = np.sqrt(np.mean(residuals**2))\n",
    "\n",
    "    plt.scatter(\n",
    "        utc_times, residuals,\n",
    "        color=color, marker='+', s=20, alpha=0.8,\n",
    "        label=f\"{station_name} (FDETS) - RMS: {station_rms*1000:.2f} mHz\"\n",
    "        if f\"{station_name}_FDETS\" not in added_labels else None\n",
    "    )\n",
    "    added_labels.add(f\"{station_name}_FDETS\")\n",
    "    all_residuals.append(residuals)\n",
    "\n",
    "# Calculate and display overall statistics\n",
    "if all_residuals:\n",
    "    all_residuals_array = np.concatenate([np.array(r) for r in all_residuals])\n",
    "    overall_rms = np.sqrt(np.mean(all_residuals_array**2))\n",
    "\n",
    "    plt.xlabel(\"UTC Time\", fontsize=14)\n",
    "    plt.ylabel(\"Residuals (Hz)\", fontsize=14)\n",
    "    plt.title(f\"Mars Express Residual Analysis - Overall RMS: {overall_rms*1000:.2f} mHz\", fontsize=16)\n",
    "    plt.grid(True, linestyle=\"--\", alpha=0.3)\n",
    "\n",
    "    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%m-%d %H:%M'))\n",
    "    plt.gca().xaxis.set_major_locator(mdates.HourLocator(interval=6))\n",
    "    plt.gcf().autofmt_xdate()\n",
    "\n",
    "    plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "    print(f\"✓ Overall RMS across all stations: {overall_rms*1000:.2f} mHz\")\n",
    "else:\n",
    "    print(\"⚠ No residual data available for plotting\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "025d5245",
   "metadata": {},
   "source": [
    "### Focused Analysis: Subset with Distribution\n",
    "\n",
    "Let's zoom in on a specific time window to see the residuals in more detail. The left panel shows the time series, while the right panel shows the distribution of residuals for each station."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7d5a36b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating subset analysis for:\n",
      "  2013-12-28 19:00:00 to 2013-12-29 00:00:00\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Subset RMS: 9.93 mHz\n"
     ]
    }
   ],
   "source": [
    "# Define a focused time window (adjust these as needed)\n",
    "ANALYSIS_TO_AVOID_START_SCAN = datetime(2013, 12, 28, 19, 0, 0)\n",
    "ANALYSIS_TO_AVOID_END_SCAN = datetime(2013, 12, 29, 0, 0)\n",
    "\n",
    "print(f\"Creating subset analysis for:\")\n",
    "print(f\"  {ANALYSIS_TO_AVOID_START_SCAN} to {ANALYSIS_TO_AVOID_END_SCAN}\")\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 6), gridspec_kw={'width_ratios': [4, 1]})\n",
    "ax_main, ax_hist = axes\n",
    "\n",
    "added_labels = set()\n",
    "subset_all_residuals = []\n",
    "\n",
    "# Plot IFMS residuals for subset\n",
    "for station_name, ifms_data in ifms_station_residuals.items():\n",
    "    color = station_colors.get(station_name, generate_random_color())\n",
    "\n",
    "    utc_times = np.array(ifms_data['utc_times'])\n",
    "    residuals = np.array(ifms_data['residuals'])\n",
    "\n",
    "    # Filter to subset time window\n",
    "    mask = (utc_times >= ANALYSIS_TO_AVOID_START_SCAN) & (utc_times <= ANALYSIS_TO_AVOID_END_SCAN)\n",
    "    subset_times = utc_times[mask]\n",
    "    subset_residuals = residuals[mask]\n",
    "\n",
    "    if len(subset_residuals) == 0:\n",
    "        continue\n",
    "\n",
    "    station_rms = np.sqrt(np.mean(subset_residuals**2))\n",
    "\n",
    "    # Time series plot\n",
    "    ax_main.scatter(\n",
    "        subset_times, subset_residuals,\n",
    "        color=color, marker='o', s=20, alpha=0.8,\n",
    "        label=f\"{station_name} (IFMS) - RMS: {station_rms*1000:.2f} mHz\"\n",
    "        if f\"{station_name}_IFMS\" not in added_labels else None\n",
    "    )\n",
    "    added_labels.add(f\"{station_name}_IFMS\")\n",
    "    subset_all_residuals.append(subset_residuals)\n",
    "\n",
    "    # Distribution histogram\n",
    "    ax_hist.hist(\n",
    "        subset_residuals,\n",
    "        bins=30,\n",
    "        orientation='horizontal',\n",
    "        alpha=0.6,\n",
    "        color=color\n",
    "    )\n",
    "\n",
    "# Plot FDETS residuals for subset\n",
    "for station_name, fdets_data in fdets_station_residuals.items():\n",
    "    color = station_colors.get(station_name, generate_random_color())\n",
    "\n",
    "    utc_times = np.array(fdets_data['utc_times'])\n",
    "    residuals = np.array(fdets_data['residuals'])\n",
    "\n",
    "    mask = (utc_times >= ANALYSIS_TO_AVOID_START_SCAN) & (utc_times <= ANALYSIS_TO_AVOID_END_SCAN)\n",
    "    subset_times = utc_times[mask]\n",
    "    subset_residuals = residuals[mask]\n",
    "\n",
    "    if len(subset_residuals) == 0:\n",
    "        continue\n",
    "\n",
    "    station_rms = np.sqrt(np.mean(subset_residuals**2))\n",
    "\n",
    "    ax_main.scatter(\n",
    "        subset_times, subset_residuals,\n",
    "        color=color, marker='o', s=20, alpha=0.8,\n",
    "        label=f\"{station_name} (FDETS) - RMS: {station_rms*1000:.2f} mHz\"\n",
    "        if f\"{station_name}_FDETS\" not in added_labels else None\n",
    "    )\n",
    "    added_labels.add(f\"{station_name}_FDETS\")\n",
    "    subset_all_residuals.append(subset_residuals)\n",
    "\n",
    "    ax_hist.hist(\n",
    "        subset_residuals,\n",
    "        bins=30,\n",
    "        orientation='horizontal',\n",
    "        alpha=0.6,\n",
    "        color=color\n",
    "    )\n",
    "\n",
    "# Format plots\n",
    "if subset_all_residuals:\n",
    "    all_subset_residuals_array = np.concatenate([np.array(r) for r in subset_all_residuals])\n",
    "    overall_subset_rms = np.sqrt(np.mean(all_subset_residuals_array**2))\n",
    "\n",
    "    ax_main.set_xlabel(\"UTC Time\", fontsize=15)\n",
    "    ax_main.set_ylabel(\"Residuals (Hz)\", fontsize=15)\n",
    "    ax_main.set_title(f\"Overall Subset RMS: {overall_subset_rms*1000:.2f} mHz\", fontsize=15)\n",
    "    ax_main.grid(True, linestyle=\"--\", alpha=0.5)\n",
    "    ax_main.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d %H:%M:%S'))\n",
    "    ax_main.xaxis.set_major_locator(mdates.AutoDateLocator())\n",
    "    ax_main.tick_params(axis='x', labelsize=11)\n",
    "    ax_main.tick_params(axis='y', labelsize=11)\n",
    "    ax_main.legend(fontsize=12)\n",
    "\n",
    "    ax_hist.set_xlabel(\"Count\", fontsize=15)\n",
    "    ax_hist.set_ylabel(\"Residuals (Hz)\", fontsize=15)\n",
    "    ax_hist.grid(True, linestyle='--', alpha=0.3)\n",
    "\n",
    "    fig.autofmt_xdate()\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "    print(f\"✓ Subset RMS: {overall_subset_rms*1000:.2f} mHz\")\n",
    "else:\n",
    "    print(\"⚠ No subset data available for plotting\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c271ce8e",
   "metadata": {},
   "source": [
    "## Part 5: Exporting Results\n",
    "\n",
    "Finally, let's save all our computed residuals to CSV files for further analysis or sharing with colleagues."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4eee821a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exporting results to CSV files...\n",
      "✓ Created 1 IFMS CSV files in /Users/lgisolfi/Desktop/mex_phobos_flyby/output/ifms_residuals\n",
      "✓ Created 2 FDETS CSV files in /Users/lgisolfi/Desktop/mex_phobos_flyby/output/fdets_residuals\n",
      "\n",
      "============================================================\n",
      "Analysis Complete!\n",
      "============================================================\n",
      "Total output directory: /Users/lgisolfi/Desktop/mex_phobos_flyby/output\n",
      "You can now use these CSV files for further analysis.\n"
     ]
    }
   ],
   "source": [
    "print(\"Exporting results to CSV files...\")\n",
    "\n",
    "# Create output directories\n",
    "os.makedirs(OUTPUT_DIR, exist_ok=True)\n",
    "ifms_output_dir = os.path.join(OUTPUT_DIR, 'ifms_residuals')\n",
    "fdets_output_dir = os.path.join(OUTPUT_DIR, 'fdets_residuals')\n",
    "os.makedirs(ifms_output_dir, exist_ok=True)\n",
    "os.makedirs(fdets_output_dir, exist_ok=True)\n",
    "\n",
    "# Export IFMS residuals\n",
    "ifms_files_created = 0\n",
    "for station_name, data in ifms_station_residuals.items():\n",
    "    filename = f\"{station_name}_residuals_ifms.csv\"\n",
    "    file_path = os.path.join(ifms_output_dir, filename)\n",
    "\n",
    "    with open(file_path, mode=\"w\", newline=\"\") as file:\n",
    "        writer = csv.writer(file)\n",
    "\n",
    "        # Write header with metadata\n",
    "        writer.writerow([f'# Station: {station_name}'])\n",
    "        writer.writerow(['# Data Type: IFMS (Closed-Loop)'])\n",
    "        writer.writerow(['# Time (seconds since J2000)', 'UTC Time', 'Residuals (Hz)'])\n",
    "\n",
    "        # Write data rows\n",
    "        times = data['times']\n",
    "        utc_times = data['utc_times']\n",
    "        residuals = data['residuals']\n",
    "\n",
    "        for time, utc_time, residual in zip(times, utc_times, residuals):\n",
    "            writer.writerow([\n",
    "                f\"{time:.6f}\",\n",
    "                utc_time.strftime(\"%Y-%m-%d %H:%M:%S.%f\")[:-3],\n",
    "                f\"{residual:.8e}\"\n",
    "            ])\n",
    "\n",
    "    ifms_files_created += 1\n",
    "\n",
    "print(f\"✓ Created {ifms_files_created} IFMS CSV files in {ifms_output_dir}\")\n",
    "\n",
    "# Export FDETS residuals\n",
    "fdets_files_created = 0\n",
    "for station_name, data in fdets_station_residuals.items():\n",
    "    filename = f\"{station_name}_residuals_fdets.csv\"\n",
    "    file_path = os.path.join(fdets_output_dir, filename)\n",
    "\n",
    "    with open(file_path, mode=\"w\", newline=\"\") as file:\n",
    "        writer = csv.writer(file)\n",
    "\n",
    "        # Write header with metadata\n",
    "        writer.writerow([f'# Station: {station_name}'])\n",
    "        writer.writerow(['# Data Type: FDETS (Open-Loop)'])\n",
    "        writer.writerow(['# Time (seconds since J2000)', 'UTC Time', 'Residuals (Hz)', 'Transmitting Station'])\n",
    "\n",
    "        # Write data rows\n",
    "        times = data['times']\n",
    "        utc_times = data['utc_times']\n",
    "        residuals = data['residuals']\n",
    "        transmitting_stations = data.get('transmitting_station', ['Unknown'] * len(times))\n",
    "\n",
    "        for i, (time, utc_time, residual) in enumerate(zip(times, utc_times, residuals)):\n",
    "            tx_station = transmitting_stations[min(i, len(transmitting_stations)-1)] if transmitting_stations else 'Unknown'\n",
    "\n",
    "            writer.writerow([\n",
    "                f\"{time:.6f}\",\n",
    "                utc_time.strftime(\"%Y-%m-%d %H:%M:%S.%f\")[:-3],\n",
    "                f\"{residual:.8e}\",\n",
    "                tx_station\n",
    "            ])\n",
    "\n",
    "    fdets_files_created += 1\n",
    "\n",
    "print(f\"✓ Created {fdets_files_created} FDETS CSV files in {fdets_output_dir}\")\n",
    "print(f\"\\n{'='*60}\")\n",
    "print(f\"Analysis Complete!\")\n",
    "print(f\"{'='*60}\")\n",
    "print(f\"Total output directory: {OUTPUT_DIR}\")\n",
    "print(f\"You can now use these CSV files for further analysis.\")"
   ]
  }
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