{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4cffd6c5",
   "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RA List: [np.float64(24.1741435187182), np.float64(25.759787769012984), np.float64(49.32806570275772), np.float64(55.50613654382996), np.float64(60.97590646798826), np.float64(63.018113741788355), np.float64(143.0416839498853), np.float64(161.69014062163393), np.float64(176.53216723085026), np.float64(183.45178780664702), np.float64(191.28607761407375), np.float64(194.20387680952962), np.float64(204.38304472867193), np.float64(339.2669893687885), np.float64(0.8130105246497964), np.float64(164.03825008738184)]\n",
      "Dec List: [np.float64(15.783869592105441), np.float64(13.645005280982105), np.float64(-41.10817408896737), np.float64(-47.22221653992977), np.float64(-43.34878852480052), np.float64(-32.87392378612486), np.float64(21.501827494459036), np.float64(11.819887017791151), np.float64(47.49512808371984), np.float64(14.900261322222237), np.float64(-0.4622668171007003), np.float64(-8.524938659400307), np.float64(8.885499320910338), np.float64(34.4157929700228), np.float64(16.14532447253357), np.float64(6.1729868291531)]\n"
     ]
    }
   ],
   "source": [
    "import csv\n",
    "from astropy.coordinates import SkyCoord\n",
    "import astropy.units as u\n",
    "\n",
    "# Initialize empty lists for RA and Dec\n",
    "ra_list = []\n",
    "dec_list = []\n",
    "\n",
    "# Define the path to your CSV file\n",
    "csv_file_path = \"GeVgal.csv\"\n",
    "\n",
    "# Open and read the CSV file\n",
    "with open(csv_file_path, 'r') as csvfile:\n",
    "    # Use csv.reader to handle the file, skipping the header row\n",
    "    csv_reader = csv.reader(csvfile)\n",
    "    next(csv_reader)  # Skip the header row\n",
    "\n",
    "    # Loop through each row in the CSV\n",
    "    for row in csv_reader:\n",
    "        try:\n",
    "            # Extract l and b, which are in the second and third columns (index 1 and 2)\n",
    "            l = float(row[1])\n",
    "            b = float(row[2])\n",
    "\n",
    "            # Create a SkyCoord object with galactic coordinates\n",
    "            galactic_coord = SkyCoord(l=l*u.degree, b=b*u.degree, frame='galactic')\n",
    "\n",
    "            # Convert to ICRS (equatorial) coordinates\n",
    "            icrs_coord = galactic_coord.icrs\n",
    "\n",
    "            # Append the RA and Dec values to the lists\n",
    "            ra_list.append(icrs_coord.ra.deg)\n",
    "            dec_list.append(icrs_coord.dec.deg)\n",
    "\n",
    "        except (ValueError, IndexError) as e:\n",
    "            # Handle potential errors if a row is malformed\n",
    "            print(f\"Skipping a malformed row: {row} - Error: {e}\")\n",
    "\n",
    "# Now, ra_list and dec_list contain the converted coordinates\n",
    "print(\"RA List:\", ra_list)\n",
    "print(\"Dec List:\", dec_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ff1d339a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Request successful!\n",
      "{\n",
      "    \"Status\": 0,\n",
      "    \"ErrorMessage\": \"\",\n",
      "    \"ClassicUpperLimit\": 36.99647944311798,\n",
      "    \"ClassicLowerLimit\": 0.0,\n",
      "    \"ClassicOneSideUL\": 33.54440898622437,\n",
      "    \"ClassicCountRateUpperLimit\": 0.022452965897451615,\n",
      "    \"ClassicCountRateLowerLimit\": 0.0,\n",
      "    \"ClassicCountRateOneSideUL\": 0.020357922763323065,\n",
      "    \"ClassicFluxUpperLimit\": 7.504496105362505e-13,\n",
      "    \"ClassicFluxLowerLimit\": 0.0,\n",
      "    \"ClassicFluxOneSideUL\": 6.804265983763352e-13,\n",
      "    \"BayesianUpperLimit\": 33.83295926177776,\n",
      "    \"BayesianLowerLimit\": 0.10792639479099073,\n",
      "    \"BayesianOneSideUL\": 33.727107645421896,\n",
      "    \"BayesianCountRateUpperLimit\": 0.020533042385357955,\n",
      "    \"BayesianCountRateLowerLimit\": 6.549995291856849e-05,\n",
      "    \"BayesianCountRateOneSideUL\": 0.020468801604397097,\n",
      "    \"BayesianFluxUpperLimit\": 6.862796537256179e-13,\n",
      "    \"BayesianFluxLowerLimit\": 2.189216978388652e-15,\n",
      "    \"BayesianFluxOneSideUL\": 6.841325222832595e-13,\n",
      "    \"FluxEstimate\": 3.2382519031831067e-13,\n",
      "    \"ApertureCounts\": 94,\n",
      "    \"ApertureBackgroundCounts\": 78.03571428571428,\n",
      "    \"SourceCounts\": 15.964285714285722,\n",
      "    \"Exposure\": 2057.325295693534,\n",
      "    \"SourceRate\": 0.009688639787230046,\n",
      "    \"BackgroundRate\": 0.03793066388142964,\n",
      "    \"NormalizedBackgroundRate\": 1.6914547063541448e-05,\n",
      "    \"Contamination\": false,\n",
      "    \"CountMap\": {\n",
      "        \"healpix\": [],\n",
      "        \"counts\": [],\n",
      "        \"exposure\": [],\n",
      "        \"nside\": 4096,\n",
      "        \"order\": \"ring\",\n",
      "        \"radius_as\": 0.0\n",
      "    }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "import json\n",
    "\n",
    "# Define the URL of your Django API endpoint\n",
    "url = \"http://localhost:8000/api/stacked-upper-limit/\"\n",
    "\n",
    "payload = {\n",
    "    \"ra\": ra_list,  # List of RA values\n",
    "    \"dec\": dec_list,  # List of Dec values\n",
    "    \"cl\": 0.95,                # A numeric confidence level\n",
    "    \"survey\": \"1-4\",       # A string for the survey parameter\n",
    "    \"mr\": 0                  # A numeric value for map_radius\n",
    "}\n",
    "\n",
    "try:\n",
    "    # Send the PUT request with the JSON payload\n",
    "    response = requests.put(url, json=payload)\n",
    "\n",
    "    # Check the response status code\n",
    "    response.raise_for_status()  # This will raise an HTTPError for bad responses (4xx or 5xx)\n",
    "\n",
    "    # Print the JSON response from the server\n",
    "    print(\"Request successful!\")\n",
    "    print(json.dumps(response.json(), indent=4))\n",
    "\n",
    "except requests.exceptions.HTTPError as err:\n",
    "    print(f\"HTTP Error: {err}\")\n",
    "    print(f\"Response body: {err.response.text}\")\n",
    "except requests.exceptions.RequestException as err:\n",
    "    print(f\"An error occurred: {err}\")"
   ]
  }
 ],
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