diff --git "a/utils/hubble_downloading.ipynb" "b/utils/hubble_downloading.ipynb"
new file mode 100644--- /dev/null
+++ "b/utils/hubble_downloading.ipynb"
@@ -0,0 +1,3234 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 354,
+   "id": "09ca516e-3bbb-4a2b-9c6e-984c9a7e801a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Symmetric?\n",
+      "True\n",
+      "6555\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from astropy.coordinates import SkyCoord\n",
+    "from astropy import units as u\n",
+    "from sklearn.cluster import AgglomerativeClustering\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.patches as patches\n",
+    "import os\n",
+    "import numpy as np\n",
+    "from astropy.io import fits\n",
+    "from astropy.wcs import WCS\n",
+    "from tqdm import tqdm\n",
+    "\n",
+    "df = pd.read_csv(\"~/hst_FINAL.csv\")\n",
+    "\n",
+    "df = df.rename(columns={'sci_data_set_name': 'obs_id'})\n",
+    "\n",
+    "# Create a shortened identifier.\n",
+    "\n",
+    "\"\"\"\n",
+    "The data downloading process looks like the following:\n",
+    "\n",
+    "1. Use MastMissions to query the list of observations and their metadata, like ra/dec\n",
+    "\n",
+    "2. Filtering process to make sure there are no overlapping observations.\n",
+    "\n",
+    "3. Use Observations to pull the names of the data files associated with each observation.\n",
+    "\n",
+    "4. Pull the data by wget all those file links.\n",
+    "\n",
+    "5. Preprocess.\n",
+    "\n",
+    "Note that the data file names use the first 6 chars of obs_id from this observations array\n",
+    "that we have created. That's why we create the shortened identifier, to match\n",
+    "observations to product file names. This will be used later.\n",
+    "\"\"\"\n",
+    "\n",
+    "df['obs_id_short'] = df['obs_id'].str[:6]\n",
+    "\n",
+    "RA_NAME = 'sci_ra'\n",
+    "DEC_NAME = 'sci_dec'\n",
+    "\n",
+    "assert df[RA_NAME].isna().sum() < 10\n",
+    "assert df[DEC_NAME].isna().sum() < 10\n",
+    "\n",
+    "df = df.dropna(subset=[RA_NAME, DEC_NAME])\n",
+    "\n",
+    "# Sample data: let's create an example array of latitudes and longitudes\n",
+    "# MAKE SURE TO PUT RA=LON, DEC=LAT\n",
+    "latitudes = np.array(df[DEC_NAME])  # Example latitudes\n",
+    "longitudes = np.array(df[RA_NAME])  # Example longitudes\n",
+    "\n",
+    "n_points = len(latitudes)\n",
+    "\n",
+    "# Repeat each point n_points times for lat1, lon1\n",
+    "lat1 = np.repeat(latitudes, n_points)\n",
+    "lon1 = np.repeat(longitudes, n_points)\n",
+    "\n",
+    "# Tile the whole array n_points times for lat2, lon2\n",
+    "lat2 = np.tile(latitudes, n_points)\n",
+    "lon2 = np.tile(longitudes, n_points)\n",
+    "\n",
+    "# Calculates angular separation between two spherical coords\n",
+    "# This can be lat/lon or ra/dec\n",
+    "# Taken from astropy\n",
+    "def angular_separation_deg(lon1, lat1, lon2, lat2):\n",
+    "    lon1 = np.deg2rad(lon1)\n",
+    "    lon2 = np.deg2rad(lon2)\n",
+    "    lat1 = np.deg2rad(lat1)\n",
+    "    lat2 = np.deg2rad(lat2)\n",
+    "    \n",
+    "    sdlon = np.sin(lon2 - lon1)\n",
+    "    cdlon = np.cos(lon2 - lon1)\n",
+    "    slat1 = np.sin(lat1)\n",
+    "    slat2 = np.sin(lat2)\n",
+    "    clat1 = np.cos(lat1)\n",
+    "    clat2 = np.cos(lat2)\n",
+    "\n",
+    "    num1 = clat2 * sdlon\n",
+    "    num2 = clat1 * slat2 - slat1 * clat2 * cdlon\n",
+    "    denominator = slat1 * slat2 + clat1 * clat2 * cdlon\n",
+    "\n",
+    "    return np.rad2deg(np.arctan2(np.hypot(num1, num2), denominator))\n",
+    "\n",
+    "# Compute the pairwise angular separations\n",
+    "angular_separations = angular_separation_deg(lon1, lat1, lon2, lat2)\n",
+    "\n",
+    "# Reshape the result into a matrix form\n",
+    "angular_separations_matrix = angular_separations.reshape(n_points, n_points)\n",
+    "\n",
+    "def check_symmetric(a, rtol=1e-05, atol=1e-07):\n",
+    "    return np.allclose(a, a.T, rtol=rtol, atol=atol)\n",
+    "\n",
+    "print(\"Symmetric?\")\n",
+    "print(check_symmetric(angular_separations_matrix))\n",
+    "print(len(angular_separations_matrix))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 355,
+   "id": "d143cb03-8501-4a02-b77f-8efb6ce99a7d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "6555\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(len(angular_separations_matrix))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 356,
+   "id": "85edd94e-5591-4c7c-8251-b8c976962f72",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "128     369\n",
+      "60      284\n",
+      "156     198\n",
+      "99      163\n",
+      "78      118\n",
+      "       ... \n",
+      "2025      1\n",
+      "605       1\n",
+      "731       1\n",
+      "1129      1\n",
+      "561       1\n",
+      "Length: 2215, dtype: int64\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|█████████████████████████████████████| 2215/2215 [00:00<00:00, 3215.33it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Max subset with minimum distance: 2367\n"
+     ]
+    }
+   ],
+   "source": [
+    "HUBBLE_FOV = 0.057\n",
+    "#JWST_FOV = 0.0172222\n",
+    "\n",
+    "THRESH = 2 * HUBBLE_FOV\n",
+    "\n",
+    "clustering = AgglomerativeClustering(n_clusters=None, metric='precomputed', linkage='single', distance_threshold=THRESH)\n",
+    "labels = clustering.fit_predict(angular_separations_matrix)\n",
+    "\n",
+    "df['label'] = labels\n",
+    "\n",
+    "print(pd.Series(labels).value_counts())\n",
+    "\n",
+    "def max_subset_with_min_distance(points, min_distance):\n",
+    "    subset = []\n",
+    "    for i, row in points.iterrows():\n",
+    "        if all(angular_separation_deg(row[RA_NAME], row[DEC_NAME], existing_point[RA_NAME], existing_point[DEC_NAME]) >= min_distance for existing_point in subset):\n",
+    "            subset.append(row)\n",
+    "    return subset\n",
+    "\n",
+    "all_subsets = []\n",
+    "\n",
+    "for label in tqdm(np.unique(labels)):\n",
+    "    cds = df[labels == label]\n",
+    "    subset = max_subset_with_min_distance(cds, THRESH)\n",
+    "    all_subsets.extend(subset)\n",
+    "\n",
+    "print(\"Max subset with minimum distance:\", len(all_subsets))\n",
+    "\n",
+    "df = pd.DataFrame(all_subsets)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 357,
+   "id": "55ae58fc-5c2f-46ec-8fa7-d7229fd61b5f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from astroquery.mast import Observations\n",
+    "\n",
+    "# Query for data with the specified obs_id\n",
+    "result = Observations.query_criteria(obs_id=df[\"obs_id\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 358,
+   "id": "5a29aaf9-dd68-4fa2-910a-8d399f4580cd",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|███████████████████████████████████████| 2143/2143 [07:54<00:00,  4.52it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from astropy.table import unique, vstack, Table\n",
+    "\n",
+    "matched_obs = result\n",
+    "\n",
+    "# Split the observations into \"chunks\"\n",
+    "sz_chunk = 1\n",
+    "chunks = [matched_obs[i:i+sz_chunk] for i in range(0,len(matched_obs), sz_chunk)]\n",
+    "\n",
+    "# Get the list of products for each chunk\n",
+    "t = []\n",
+    "for chunk in tqdm(chunks):\n",
+    "    out = Observations.get_product_list(chunk)\n",
+    "    out = out[out['productSubGroupDescription'] == 'RAW']\n",
+    "    out = out[out['dataRights'] == 'PUBLIC']\n",
+    "    out = out.to_pandas()\n",
+    "    if len(out) > 0:\n",
+    "        t.append(out.iloc[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 359,
+   "id": "7ab7dd7d-189f-402a-a796-22d859fe15ac",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "There are 2118 unique files, which are 72.9 GB in size.\n"
+     ]
+    }
+   ],
+   "source": [
+    "files = pd.DataFrame(t)\n",
+    "\n",
+    "'''\n",
+    "# Ensure we only keep raw data files\n",
+    "files = files[files['productSubGroupDescription'] == 'RAW']\n",
+    "\n",
+    "# Create a shortened identified\n",
+    "files['obs_id_short'] = files['obs_id'].str[:6]\n",
+    "files = files.drop_duplicates(subset='obs_id_short')\n",
+    "'''\n",
+    "\n",
+    "print(f\"There are {len(files)} unique files, which are {sum(files['size'])/10**9:.1f} GB in size.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 360,
+   "id": "94c7dc65-9002-458f-b53f-1120fd8c7be1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>obsID</th>\n",
+       "      <th>obs_collection</th>\n",
+       "      <th>dataproduct_type</th>\n",
+       "      <th>obs_id</th>\n",
+       "      <th>description</th>\n",
+       "      <th>type</th>\n",
+       "      <th>dataURI</th>\n",
+       "      <th>productType</th>\n",
+       "      <th>productGroupDescription</th>\n",
+       "      <th>productSubGroupDescription</th>\n",
+       "      <th>productDocumentationURL</th>\n",
+       "      <th>project</th>\n",
+       "      <th>prvversion</th>\n",
+       "      <th>proposal_id</th>\n",
+       "      <th>productFilename</th>\n",
+       "      <th>size</th>\n",
+       "      <th>parent_obsid</th>\n",
+       "      <th>dataRights</th>\n",
+       "      <th>calib_level</th>\n",
+       "      <th>filters</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>26113888</td>\n",
+       "      <td>HST</td>\n",
+       "      <td>image</td>\n",
+       "      <td>jdq318n8q</td>\n",
+       "      <td>DADS RAW file - Raw exposure COS/NICMOS/STIS/W...</td>\n",
+       "      <td>S</td>\n",
+       "      <td>mast:HST/product/jdq318n8q_raw.fits</td>\n",
+       "      <td>SCIENCE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>RAW</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CALACS</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>15213</td>\n",
+       "      <td>jdq318n8q_raw.fits</td>\n",
+       "      <td>34344000</td>\n",
+       "      <td>26114025</td>\n",
+       "      <td>PUBLIC</td>\n",
+       "      <td>1</td>\n",
+       "      <td>F606W</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>24979066</td>\n",
+       "      <td>HST</td>\n",
+       "      <td>image</td>\n",
+       "      <td>jcoz32dvq</td>\n",
+       "      <td>DADS RAW file - Raw exposure COS/NICMOS/STIS/W...</td>\n",
+       "      <td>S</td>\n",
+       "      <td>mast:HST/product/jcoz32dvq_raw.fits</td>\n",
+       "      <td>SCIENCE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>RAW</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CALACS</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13671</td>\n",
+       "      <td>jcoz32dvq_raw.fits</td>\n",
+       "      <td>34344000</td>\n",
+       "      <td>24981158</td>\n",
+       "      <td>PUBLIC</td>\n",
+       "      <td>1</td>\n",
+       "      <td>F606W</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>25874266</td>\n",
+       "      <td>HST</td>\n",
+       "      <td>image</td>\n",
+       "      <td>jdba3nvyq</td>\n",
+       "      <td>DADS RAW file - Raw exposure COS/NICMOS/STIS/W...</td>\n",
+       "      <td>S</td>\n",
+       "      <td>mast:HST/product/jdba3nvyq_raw.fits</td>\n",
+       "      <td>SCIENCE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>RAW</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CALACS</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14840</td>\n",
+       "      <td>jdba3nvyq_raw.fits</td>\n",
+       "      <td>34344000</td>\n",
+       "      <td>25874435</td>\n",
+       "      <td>PUBLIC</td>\n",
+       "      <td>1</td>\n",
+       "      <td>F606W</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>24042703</td>\n",
+       "      <td>HST</td>\n",
+       "      <td>image</td>\n",
+       "      <td>j96l03bcq</td>\n",
+       "      <td>DADS RAW file - Raw exposure COS/NICMOS/STIS/W...</td>\n",
+       "      <td>S</td>\n",
+       "      <td>mast:HST/product/j96l03bcq_raw.fits</td>\n",
+       "      <td>SCIENCE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>RAW</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CALACS</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10438</td>\n",
+       "      <td>j96l03bcq_raw.fits</td>\n",
+       "      <td>34344000</td>\n",
+       "      <td>24825269</td>\n",
+       "      <td>PUBLIC</td>\n",
+       "      <td>1</td>\n",
+       "      <td>F606W</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>26270229</td>\n",
+       "      <td>HST</td>\n",
+       "      <td>image</td>\n",
+       "      <td>jdrz3ytfq</td>\n",
+       "      <td>DADS RAW file - Raw exposure COS/NICMOS/STIS/W...</td>\n",
+       "      <td>S</td>\n",
+       "      <td>mast:HST/product/jdrz3ytfq_raw.fits</td>\n",
+       "      <td>SCIENCE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>RAW</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CALACS</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>15446</td>\n",
+       "      <td>jdrz3ytfq_raw.fits</td>\n",
+       "      <td>34344000</td>\n",
+       "      <td>26270246</td>\n",
+       "      <td>PUBLIC</td>\n",
+       "      <td>1</td>\n",
+       "      <td>F606W</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>24085175</td>\n",
+       "      <td>HST</td>\n",
+       "      <td>image</td>\n",
+       "      <td>jb2p31fnq</td>\n",
+       "      <td>DADS RAW file - Raw exposure COS/NICMOS/STIS/W...</td>\n",
+       "      <td>S</td>\n",
+       "      <td>mast:HST/product/jb2p31fnq_raw.fits</td>\n",
+       "      <td>SCIENCE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>RAW</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CALACS</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>11613</td>\n",
+       "      <td>jb2p31fnq_raw.fits</td>\n",
+       "      <td>34344000</td>\n",
+       "      <td>24831290</td>\n",
+       "      <td>PUBLIC</td>\n",
+       "      <td>1</td>\n",
+       "      <td>F606W</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>68563813</td>\n",
+       "      <td>HST</td>\n",
+       "      <td>image</td>\n",
+       "      <td>jenm44ygq</td>\n",
+       "      <td>DADS RAW file - Raw exposure COS/NICMOS/STIS/W...</td>\n",
+       "      <td>S</td>\n",
+       "      <td>mast:HST/product/jenm44ygq_raw.fits</td>\n",
+       "      <td>SCIENCE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>RAW</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CALACS</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>16711</td>\n",
+       "      <td>jenm44ygq_raw.fits</td>\n",
+       "      <td>34344000</td>\n",
+       "      <td>68565137</td>\n",
+       "      <td>PUBLIC</td>\n",
+       "      <td>1</td>\n",
+       "      <td>F606W</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>25857452</td>\n",
+       "      <td>HST</td>\n",
+       "      <td>image</td>\n",
+       "      <td>jd9r08r2q</td>\n",
+       "      <td>DADS RAW file - Raw exposure COS/NICMOS/STIS/W...</td>\n",
+       "      <td>S</td>\n",
+       "      <td>mast:HST/product/jd9r08r2q_raw.fits</td>\n",
+       "      <td>SCIENCE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>RAW</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CALACS</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14658</td>\n",
+       "      <td>jd9r08r2q_raw.fits</td>\n",
+       "      <td>34344000</td>\n",
+       "      <td>25857751</td>\n",
+       "      <td>PUBLIC</td>\n",
+       "      <td>1</td>\n",
+       "      <td>F606W</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>24127301</td>\n",
+       "      <td>HST</td>\n",
+       "      <td>image</td>\n",
+       "      <td>jcdm96g1q</td>\n",
+       "      <td>DADS RAW file - Raw exposure COS/NICMOS/STIS/W...</td>\n",
+       "      <td>S</td>\n",
+       "      <td>mast:HST/product/jcdm96g1q_raw.fits</td>\n",
+       "      <td>SCIENCE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>RAW</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CALACS</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>13364</td>\n",
+       "      <td>jcdm96g1q_raw.fits</td>\n",
+       "      <td>34344000</td>\n",
+       "      <td>24839150</td>\n",
+       "      <td>PUBLIC</td>\n",
+       "      <td>1</td>\n",
+       "      <td>F606W</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>24035175</td>\n",
+       "      <td>HST</td>\n",
+       "      <td>image</td>\n",
+       "      <td>j94se5qmq</td>\n",
+       "      <td>DADS RAW file - Raw exposure COS/NICMOS/STIS/W...</td>\n",
+       "      <td>S</td>\n",
+       "      <td>mast:HST/product/j94se5qmq_raw.fits</td>\n",
+       "      <td>SCIENCE</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>RAW</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>CALACS</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>10189</td>\n",
+       "      <td>j94se5qmq_raw.fits</td>\n",
+       "      <td>34344000</td>\n",
+       "      <td>24035175</td>\n",
+       "      <td>PUBLIC</td>\n",
+       "      <td>1</td>\n",
+       "      <td>F606W</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>2118 rows × 20 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       obsID obs_collection dataproduct_type     obs_id  \\\n",
+       "0   26113888            HST            image  jdq318n8q   \n",
+       "0   24979066            HST            image  jcoz32dvq   \n",
+       "0   25874266            HST            image  jdba3nvyq   \n",
+       "0   24042703            HST            image  j96l03bcq   \n",
+       "0   26270229            HST            image  jdrz3ytfq   \n",
+       "..       ...            ...              ...        ...   \n",
+       "0   24085175            HST            image  jb2p31fnq   \n",
+       "0   68563813            HST            image  jenm44ygq   \n",
+       "0   25857452            HST            image  jd9r08r2q   \n",
+       "0   24127301            HST            image  jcdm96g1q   \n",
+       "0   24035175            HST            image  j94se5qmq   \n",
+       "\n",
+       "                                          description type  \\\n",
+       "0   DADS RAW file - Raw exposure COS/NICMOS/STIS/W...    S   \n",
+       "0   DADS RAW file - Raw exposure COS/NICMOS/STIS/W...    S   \n",
+       "0   DADS RAW file - Raw exposure COS/NICMOS/STIS/W...    S   \n",
+       "0   DADS RAW file - Raw exposure COS/NICMOS/STIS/W...    S   \n",
+       "0   DADS RAW file - Raw exposure COS/NICMOS/STIS/W...    S   \n",
+       "..                                                ...  ...   \n",
+       "0   DADS RAW file - Raw exposure COS/NICMOS/STIS/W...    S   \n",
+       "0   DADS RAW file - Raw exposure COS/NICMOS/STIS/W...    S   \n",
+       "0   DADS RAW file - Raw exposure COS/NICMOS/STIS/W...    S   \n",
+       "0   DADS RAW file - Raw exposure COS/NICMOS/STIS/W...    S   \n",
+       "0   DADS RAW file - Raw exposure COS/NICMOS/STIS/W...    S   \n",
+       "\n",
+       "                                dataURI productType  productGroupDescription  \\\n",
+       "0   mast:HST/product/jdq318n8q_raw.fits     SCIENCE                      NaN   \n",
+       "0   mast:HST/product/jcoz32dvq_raw.fits     SCIENCE                      NaN   \n",
+       "0   mast:HST/product/jdba3nvyq_raw.fits     SCIENCE                      NaN   \n",
+       "0   mast:HST/product/j96l03bcq_raw.fits     SCIENCE                      NaN   \n",
+       "0   mast:HST/product/jdrz3ytfq_raw.fits     SCIENCE                      NaN   \n",
+       "..                                  ...         ...                      ...   \n",
+       "0   mast:HST/product/jb2p31fnq_raw.fits     SCIENCE                      NaN   \n",
+       "0   mast:HST/product/jenm44ygq_raw.fits     SCIENCE                      NaN   \n",
+       "0   mast:HST/product/jd9r08r2q_raw.fits     SCIENCE                      NaN   \n",
+       "0   mast:HST/product/jcdm96g1q_raw.fits     SCIENCE                      NaN   \n",
+       "0   mast:HST/product/j94se5qmq_raw.fits     SCIENCE                      NaN   \n",
+       "\n",
+       "   productSubGroupDescription  productDocumentationURL project  prvversion  \\\n",
+       "0                         RAW                      NaN  CALACS         NaN   \n",
+       "0                         RAW                      NaN  CALACS         NaN   \n",
+       "0                         RAW                      NaN  CALACS         NaN   \n",
+       "0                         RAW                      NaN  CALACS         NaN   \n",
+       "0                         RAW                      NaN  CALACS         NaN   \n",
+       "..                        ...                      ...     ...         ...   \n",
+       "0                         RAW                      NaN  CALACS         NaN   \n",
+       "0                         RAW                      NaN  CALACS         NaN   \n",
+       "0                         RAW                      NaN  CALACS         NaN   \n",
+       "0                         RAW                      NaN  CALACS         NaN   \n",
+       "0                         RAW                      NaN  CALACS         NaN   \n",
+       "\n",
+       "   proposal_id     productFilename      size parent_obsid dataRights  \\\n",
+       "0        15213  jdq318n8q_raw.fits  34344000     26114025     PUBLIC   \n",
+       "0        13671  jcoz32dvq_raw.fits  34344000     24981158     PUBLIC   \n",
+       "0        14840  jdba3nvyq_raw.fits  34344000     25874435     PUBLIC   \n",
+       "0        10438  j96l03bcq_raw.fits  34344000     24825269     PUBLIC   \n",
+       "0        15446  jdrz3ytfq_raw.fits  34344000     26270246     PUBLIC   \n",
+       "..         ...                 ...       ...          ...        ...   \n",
+       "0        11613  jb2p31fnq_raw.fits  34344000     24831290     PUBLIC   \n",
+       "0        16711  jenm44ygq_raw.fits  34344000     68565137     PUBLIC   \n",
+       "0        14658  jd9r08r2q_raw.fits  34344000     25857751     PUBLIC   \n",
+       "0        13364  jcdm96g1q_raw.fits  34344000     24839150     PUBLIC   \n",
+       "0        10189  j94se5qmq_raw.fits  34344000     24035175     PUBLIC   \n",
+       "\n",
+       "    calib_level filters  \n",
+       "0             1   F606W  \n",
+       "0             1   F606W  \n",
+       "0             1   F606W  \n",
+       "0             1   F606W  \n",
+       "0             1   F606W  \n",
+       "..          ...     ...  \n",
+       "0             1   F606W  \n",
+       "0             1   F606W  \n",
+       "0             1   F606W  \n",
+       "0             1   F606W  \n",
+       "0             1   F606W  \n",
+       "\n",
+       "[2118 rows x 20 columns]"
+      ]
+     },
+     "execution_count": 360,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "files"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "56bffaa5-711b-42e9-934b-80061d5a6cb3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  0%|                                                    | 0/87 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160410.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160420.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160430.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160445.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160455.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160505.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160514.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160523.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160537.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160548.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160558.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160609.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160618.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160626.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160636.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160645.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 18%|███████▉                                   | 16/87 [02:44<11:12,  9.47s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160654.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160703.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160713.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
+      " 22%|█████████▍                                 | 19/87 [03:11<10:25,  9.19s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160721.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160730.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 24%|██████████▍                                | 21/87 [03:30<10:13,  9.29s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160740.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "text": [
+      " 25%|██████████▊                                | 22/87 [03:44<11:37, 10.73s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160754.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 26%|███████████▎                               | 23/87 [03:55<11:25, 10.71s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160805.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160814.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160824.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160833.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 31%|█████████████▎                             | 27/87 [04:32<09:39,  9.66s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160842.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 32%|█████████████▊                             | 28/87 [04:43<09:44,  9.91s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160853.sh ... [Done]\n"
+     ]
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160902.sh ... [Done]\n"
+     ]
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160912.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520160922.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161002.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161011.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161018.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161029.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161038.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161046.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161054.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161103.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161112.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161119.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161128.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161138.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161151.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161209.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161218.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161226.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161235.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161245.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161254.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161304.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161314.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161323.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161332.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161341.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161350.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161359.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161409.sh ... [Done]\n"
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161419.sh ... [Done]\n"
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+     "output_type": "stream",
+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161549.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161558.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161607.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+    {
+     "name": "stdout",
+     "output_type": "stream",
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161615.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161624.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+    {
+     "name": "stdout",
+     "output_type": "stream",
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161633.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+    {
+     "name": "stdout",
+     "output_type": "stream",
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161641.sh ... [Done]\n"
+     ]
+    },
+    {
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+     "name": "stdout",
+     "output_type": "stream",
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161650.sh ... [Done]\n"
+     ]
+    },
+    {
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+    {
+     "name": "stdout",
+     "output_type": "stream",
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161657.sh ... [Done]\n"
+     ]
+    },
+    {
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+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161706.sh ... [Done]\n"
+     ]
+    },
+    {
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+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161715.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
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+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
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+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161723.sh ... [Done]\n"
+     ]
+    },
+    {
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+     "output_type": "stream",
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161732.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 99%|██████████████████████████████████████████▌| 86/87 [13:30<00:08,  8.59s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/bundle.sh to ./mastDownload_20240520161740.sh ... [Done]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|███████████████████████████████████████████| 87/87 [13:39<00:00,  9.42s/it]\n"
+     ]
+    }
+   ],
+   "source": [
+    "sz_chunk = 25\n",
+    "chunks = [files[i:i+sz_chunk] for i in range(0,len(files), sz_chunk)]\n",
+    "\n",
+    "# Get the list of products for each chunk\n",
+    "t = []\n",
+    "for chunk in tqdm(chunks):\n",
+    "    manifest = Observations.download_products(chunk['obsID'], curl_flag=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "id": "556fdab2-517e-466c-a9ee-c7b629df5276",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "New FITS files created successfully.\n"
+     ]
+    }
+   ],
+   "source": [
+    "'''\n",
+    "\n",
+    "import numpy as np\n",
+    "from astropy.io import fits\n",
+    "from astropy.table import Table\n",
+    "import glob\n",
+    "\n",
+    "def create_combined_hubble_file(short_obs_id):\n",
+    "    \n",
+    "    file_list = list(files[files['obs_id_short'] == short_obs_id]['productFilename'])\n",
+    "    \n",
+    "    ccd1_data = []\n",
+    "    ccd2_data = []\n",
+    "    ccd1_times = []\n",
+    "    ccd2_times = []\n",
+    "    ccd1_headers = []\n",
+    "    ccd2_headers = []\n",
+    "\n",
+    "    for file in file_list:\n",
+    "        with fits.open(file) as hdul:\n",
+    "            # Extract TIME-OBS from the primary header\n",
+    "            time_obs = hdul[0].header['TIME-OBS']\n",
+    "\n",
+    "            # Extract data and headers from HDUs\n",
+    "            for hdu in [hdul[1], hdul[4]]:\n",
+    "                if hdu.header['CCDCHIP'] == 1:\n",
+    "                    ccd1_data.append(hdu.data)\n",
+    "                    ccd1_times.append(time_obs)\n",
+    "                    ccd1_headers.append(hdul[0].header.copy())\n",
+    "                elif hdu.header['CCDCHIP'] == 2:\n",
+    "                    ccd2_data.append(hdu.data)\n",
+    "                    ccd2_times.append(time_obs)\n",
+    "                    ccd2_headers.append(hdul[0].header.copy())\n",
+    "\n",
+    "    # Sort the data based on TIME-OBS\n",
+    "    ccd1_times, ccd1_data, ccd1_headers = zip(*sorted(zip(ccd1_times, ccd1_data, ccd1_headers)))\n",
+    "    ccd2_times, ccd2_data, ccd2_headers = zip(*sorted(zip(ccd2_times, ccd2_data, ccd2_headers)))\n",
+    "\n",
+    "    # Concatenate the data for each CCDCHIP\n",
+    "    ccd1_concat = np.stack(ccd1_data)\n",
+    "    ccd2_concat = np.stack(ccd2_data)\n",
+    "\n",
+    "    # Function to create a new FITS file for a given CCDCHIP\n",
+    "    def create_fits_file(output_file, ccd_data, ccd_headers, ccd_chip):\n",
+    "\n",
+    "        primary_hdu = fits.PrimaryHDU()\n",
+    "        primary_hdu.header['EXTEND'] = True\n",
+    "        primary_hdu.header['CCDCHIP'] = ccd_chip\n",
+    "\n",
+    "        metadata_hdus = [fits.ImageHDU(header=header) for header in ccd_headers]\n",
+    "\n",
+    "        # Create ImageHDU with concatenated data\n",
+    "        image_hdu = fits.ImageHDU(data=ccd_data, header=fits.Header({'CCDCHIP': ccd_chip}))\n",
+    "\n",
+    "        # Create HDUList and write to a new FITS file\n",
+    "        hdulist = fits.HDUList([primary_hdu] + [image_hdu] + metadata_hdus)\n",
+    "        hdulist.writeto(output_file, overwrite=True)\n",
+    "\n",
+    "    # Create FITS files for CCDCHIP 1 and 2\n",
+    "    create_fits_file(f'{short_obs_id}_ccd1.fits', ccd1_concat, ccd1_headers, 1)\n",
+    "    create_fits_file(f'{short_obs_id}_ccd2.fits', ccd2_concat, ccd2_headers, 2)\n",
+    "\n",
+    "    print(\"New FITS files created successfully.\")\n",
+    "    \n",
+    "'''"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 166,
+   "id": "d09be044-ce2e-4cb5-ae1f-9562f9ac6fa3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "251\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def visualize_label(df, LABEL=None):\n",
+    "    \n",
+    "    cds = df\n",
+    "    \n",
+    "    if LABEL is not None:\n",
+    "        cds = cds[labels == LABEL]\n",
+    "\n",
+    "    ras, decs = [], []\n",
+    "    cmap = []\n",
+    "    \n",
+    "    print(len(cds))\n",
+    "\n",
+    "    for i, cd in cds.iterrows():\n",
+    "        ras.append(cd[RA_NAME])\n",
+    "        decs.append(cd[DEC_NAME])\n",
+    "\n",
+    "    if LABEL is None:\n",
+    "        # No gridlines, will be overwhelming\n",
+    "\n",
+    "        # Compute the 2D histogram\n",
+    "        # Number of bins for x and y; adjust these based on your dataset\n",
+    "        bins = (30, 30)\n",
+    "\n",
+    "        # Compute the histogram\n",
+    "        hist, xedges, yedges = np.histogram2d(ras, decs, bins=bins)\n",
+    "        \n",
+    "        N_cutoff = 50\n",
+    "        hist = np.clip(hist, 0, N_cutoff)\n",
+    "\n",
+    "        # Generate a 2D histogram plot\n",
+    "        plt.figure(figsize=(8, 6))\n",
+    "        plt.imshow(hist, interpolation='nearest', origin='lower',\n",
+    "                   extent=[xedges[0], xedges[-1], yedges[0], yedges[-1]],\n",
+    "                   cmap='viridis')  # Choose a colormap (e.g., 'viridis', 'plasma', 'inferno')\n",
+    "\n",
+    "        # Add labels and title if necessary\n",
+    "        plt.colorbar(label='Number of points in bin')\n",
+    "        plt.xlabel('RA')\n",
+    "        plt.ylabel('DEC')\n",
+    "        plt.title(f'2D Histogram of Point Density, clipped to {N_cutoff} points')\n",
+    "\n",
+    "        # Show the plot\n",
+    "        plt.show()\n",
+    "\n",
+    "        return\n",
+    "    else:\n",
+    "        fig = plt.figure()\n",
+    "        ax = fig.gca()\n",
+    "        ax.set_xticks(np.arange(np.min(ras), np.max(ras), THRESH))\n",
+    "        ax.set_yticks(np.arange(np.min(decs), np.max(decs), THRESH))\n",
+    "        plt.scatter(ras, decs, alpha=0.1)\n",
+    "        plt.grid()\n",
+    "        plt.show()\n",
+    "\n",
+    "visualize_label(df, 4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "35a648ab-07cd-409e-be32-125ead927bdf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "data = list(range(len(labels)))\n",
+    "\n",
+    "# Perform the train-test split with an 80-20 ratio\n",
+    "train_indices, test_indices = train_test_split(data, test_size=0.2, random_state=42)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8f6a0472-b8fc-4989-a506-39019914c853",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sdss_test = all_sdss_data[all_sdss_data['cluster_label'].isin(test_indices)]\n",
+    "sdss_train = all_sdss_data[all_sdss_data['cluster_label'].isin(train_indices)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bfbe8686-e580-4285-bd8f-43154d18182b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "len(sdss_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cacb74dd-0d54-43d7-a301-ea4eb7b3e07e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "len(sdss_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f0fb157d-1307-42d9-ac57-7e6aa3cecd84",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sdss_test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "62fb160e-74e5-4f50-96ee-109a6261370f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_data = pd.DataFrame(test_data)\n",
+    "train_data = pd.DataFrame(train_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e7b1379c-d5a9-4f3a-ac68-e8b5a46f4c8a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"\n",
+    "Code to verify test/train pollution.\n",
+    "\"\"\"\n",
+    "\n",
+    "\n",
+    "import json\n",
+    "from math import radians, sin, cos, sqrt, atan2, degrees\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "\n",
+    "# Function to load data from file\n",
+    "def load_data(file_path):\n",
+    "    data = []\n",
+    "    with open(file_path, 'r') as f:\n",
+    "        for line in f:\n",
+    "            data.append(json.loads(line))\n",
+    "    return data\n",
+    "\n",
+    "# Load data\n",
+    "train_file_path = '/Users/rithwik/Desktop/full_train.jsonl.txt'\n",
+    "test_file_path = '/Users/rithwik/Desktop/full_test.jsonl.txt'\n",
+    "#train_data = sdss_train\n",
+    "#test_data = sdss_test\n",
+    "\n",
+    "# Define the threshold\n",
+    "threshold = 0.09*3\n",
+    "\n",
+    "# Find test dataset rows with a minimum great circle distance less than the threshold\n",
+    "close_pairs = []\n",
+    "\n",
+    "for i, test_point in test_data.iterrows():\n",
+    "    ra_test, dec_test = test_point['ra'], test_point['dec']\n",
+    "    distances = [(train_point, angular_separation_deg(ra_test, dec_test, train_point['ra'], train_point['dec'])) for i, train_point in train_data.iterrows()]\n",
+    "    closest_train_point, min_distance = min(distances, key=lambda x: x[1])\n",
+    "    if min_distance < threshold:\n",
+    "        close_pairs.append((test_point, closest_train_point, min_distance))\n",
+    "\n",
+    "close_pairs_summary = [\n",
+    "    {\n",
+    "        \"test_image_id\": test_point['image_id'],\n",
+    "        \"test_ra\": test_point['ra'],\n",
+    "        \"test_dec\": test_point['dec'],\n",
+    "        \"train_image_id\": closest_train_point['image_id'],\n",
+    "        \"train_ra\": closest_train_point['ra'],\n",
+    "        \"train_dec\": closest_train_point['dec'],\n",
+    "        \"min_distance_deg\": min_distance\n",
+    "    }\n",
+    "    for test_point, closest_train_point, min_distance in close_pairs\n",
+    "]\n",
+    "\n",
+    "# Print the results\n",
+    "result = \"Success\"\n",
+    "for pair in close_pairs_summary:\n",
+    "    print(pair)\n",
+    "    result = \"FAIL\"\n",
+    "    \n",
+    "print(f\"Done. result is {result}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "93cf2978-0799-4d6c-93ec-921f4f41e10c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sdss_test.to_json('full_test1.jsonl', orient='records', lines=True)\n",
+    "sdss_train.to_json('full_train1.jsonl', orient='records', lines=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "23efe470-c037-432a-9f7b-9276b89b94b9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import huggingface_hub\n",
+    "token = ''\n",
+    "huggingface_hub.login(token=token)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c208823b-1354-49c4-816d-17d4d1272930",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_dataset\n",
+    "dataset = load_dataset(\"AstroCompress/GBI-16-4D\", \"tiny\")\n",
+    "ds = dataset.with_format(\"np\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "22c589af-08d2-4227-99a5-16240f2cd390",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_jwst = pd.read_csv(\"/Users/rithwik/Desktop/jwst_all.csv\")\n",
+    "df_jwst['opticalElementsList'] = df_jwst['opticalElements'].apply(lambda x: x.split(', '))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4eeef9b8-0327-4452-8dbb-f4f83c7d4b7c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pd.Series(sum(df_jwst['opticalElementsList'], [])).value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "e9eac4d9-db7b-463d-803a-5ec5702ae95b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Filename: /Users/rithwik/Desktop/cube_center_run1752_camcol1_f164_82-5-800-800.fits\n",
+      "No.    Name      Ver    Type      Cards   Dimensions   Format\n",
+      "  0  PRIMARY       1 PrimaryHDU     174   (800, 800, 5, 82)   int16 (rescales to uint16)   \n",
+      "None\n",
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+      "{'JPEG_2K_BYTES': 1.8317073170731708, 'JPEG_2K_WRITE_RUNTIME': 0.00013184547424316406, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8463414634146342, 'JPEG_2K_WRITE_RUNTIME': 0.0001289844512939453, 'JPEG_2K_READ_RUNTIME': 8.988380432128906e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8219512195121952, 'JPEG_2K_WRITE_RUNTIME': 0.0001556873321533203, 'JPEG_2K_READ_RUNTIME': 6.914138793945312e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8439024390243903, 'JPEG_2K_WRITE_RUNTIME': 0.00013303756713867188, 'JPEG_2K_READ_RUNTIME': 7.414817810058594e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8317073170731708, 'JPEG_2K_WRITE_RUNTIME': 0.00012373924255371094, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8390243902439025, 'JPEG_2K_WRITE_RUNTIME': 8.082389831542969e-05, 'JPEG_2K_READ_RUNTIME': 7.128715515136719e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8731707317073172, 'JPEG_2K_WRITE_RUNTIME': 0.00012636184692382812, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8390243902439025, 'JPEG_2K_WRITE_RUNTIME': 0.00013113021850585938, 'JPEG_2K_READ_RUNTIME': 7.200241088867188e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8463414634146342, 'JPEG_2K_WRITE_RUNTIME': 0.00015091896057128906, 'JPEG_2K_READ_RUNTIME': 6.890296936035156e-05}\n",
+      "{'JPEG_2K_BYTES': 1.824390243902439, 'JPEG_2K_WRITE_RUNTIME': 8.893013000488281e-05, 'JPEG_2K_READ_RUNTIME': 9.202957153320312e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8463414634146342, 'JPEG_2K_WRITE_RUNTIME': 9.799003601074219e-05, 'JPEG_2K_READ_RUNTIME': 7.009506225585938e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8414634146341464, 'JPEG_2K_WRITE_RUNTIME': 0.00012183189392089844, 'JPEG_2K_READ_RUNTIME': 7.390975952148438e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8414634146341464, 'JPEG_2K_WRITE_RUNTIME': 0.0001270771026611328, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8487804878048781, 'JPEG_2K_WRITE_RUNTIME': 0.00013017654418945312, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8439024390243903, 'JPEG_2K_WRITE_RUNTIME': 0.0001227855682373047, 'JPEG_2K_READ_RUNTIME': 7.343292236328125e-05}\n",
+      "{'JPEG_2K_BYTES': 1.853658536585366, 'JPEG_2K_WRITE_RUNTIME': 0.0001220703125, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8365853658536586, 'JPEG_2K_WRITE_RUNTIME': 0.00012302398681640625, 'JPEG_2K_READ_RUNTIME': 7.390975952148438e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8390243902439025, 'JPEG_2K_WRITE_RUNTIME': 0.00012087821960449219, 'JPEG_2K_READ_RUNTIME': 7.414817810058594e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8609756097560977, 'JPEG_2K_WRITE_RUNTIME': 0.0001232624053955078, 'JPEG_2K_READ_RUNTIME': 7.390975952148438e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8317073170731708, 'JPEG_2K_WRITE_RUNTIME': 0.00012230873107910156, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8390243902439025, 'JPEG_2K_WRITE_RUNTIME': 0.00015807151794433594, 'JPEG_2K_READ_RUNTIME': 6.890296936035156e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8414634146341464, 'JPEG_2K_WRITE_RUNTIME': 0.00012302398681640625, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.851219512195122, 'JPEG_2K_WRITE_RUNTIME': 0.00012612342834472656, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8634146341463416, 'JPEG_2K_WRITE_RUNTIME': 8.20159912109375e-05, 'JPEG_2K_READ_RUNTIME': 9.393692016601562e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8390243902439025, 'JPEG_2K_WRITE_RUNTIME': 0.00013685226440429688, 'JPEG_2K_READ_RUNTIME': 7.200241088867188e-05}\n",
+      "{'JPEG_2K_BYTES': 1.851219512195122, 'JPEG_2K_WRITE_RUNTIME': 0.00012803077697753906, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8487804878048781, 'JPEG_2K_WRITE_RUNTIME': 0.0001220703125, 'JPEG_2K_READ_RUNTIME': 7.390975952148438e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8463414634146342, 'JPEG_2K_WRITE_RUNTIME': 0.00012230873107910156, 'JPEG_2K_READ_RUNTIME': 7.390975952148438e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8390243902439025, 'JPEG_2K_WRITE_RUNTIME': 0.00012087821960449219, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8463414634146342, 'JPEG_2K_WRITE_RUNTIME': 0.00012493133544921875, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8585365853658538, 'JPEG_2K_WRITE_RUNTIME': 0.00012111663818359375, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8439024390243903, 'JPEG_2K_WRITE_RUNTIME': 0.0001239776611328125, 'JPEG_2K_READ_RUNTIME': 8.988380432128906e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8487804878048781, 'JPEG_2K_WRITE_RUNTIME': 0.000148773193359375, 'JPEG_2K_READ_RUNTIME': 7.009506225585938e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8487804878048781, 'JPEG_2K_WRITE_RUNTIME': 0.00015997886657714844, 'JPEG_2K_READ_RUNTIME': 6.985664367675781e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8341463414634147, 'JPEG_2K_WRITE_RUNTIME': 0.000125885009765625, 'JPEG_2K_READ_RUNTIME': 7.390975952148438e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8341463414634147, 'JPEG_2K_WRITE_RUNTIME': 9.202957153320312e-05, 'JPEG_2K_READ_RUNTIME': 6.914138793945312e-05}\n",
+      "{'JPEG_2K_BYTES': 1.826829268292683, 'JPEG_2K_WRITE_RUNTIME': 0.00012302398681640625, 'JPEG_2K_READ_RUNTIME': 9.179115295410156e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8439024390243903, 'JPEG_2K_WRITE_RUNTIME': 8.296966552734375e-05, 'JPEG_2K_READ_RUNTIME': 0.00010395050048828125}\n",
+      "{'JPEG_2K_BYTES': 1.851219512195122, 'JPEG_2K_WRITE_RUNTIME': 0.0001289844512939453, 'JPEG_2K_READ_RUNTIME': 7.200241088867188e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8146341463414635, 'JPEG_2K_WRITE_RUNTIME': 0.00012421607971191406, 'JPEG_2K_READ_RUNTIME': 7.581710815429688e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8439024390243903, 'JPEG_2K_WRITE_RUNTIME': 0.00011682510375976562, 'JPEG_2K_READ_RUNTIME': 7.128715515136719e-05}\n",
+      "{'JPEG_2K_BYTES': 1.853658536585366, 'JPEG_2K_WRITE_RUNTIME': 0.00011920928955078125, 'JPEG_2K_READ_RUNTIME': 7.486343383789062e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8121951219512196, 'JPEG_2K_WRITE_RUNTIME': 8.320808410644531e-05, 'JPEG_2K_READ_RUNTIME': 9.894371032714844e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8365853658536586, 'JPEG_2K_WRITE_RUNTIME': 9.775161743164062e-05, 'JPEG_2K_READ_RUNTIME': 8.916854858398438e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8439024390243903, 'JPEG_2K_WRITE_RUNTIME': 0.0001270771026611328, 'JPEG_2K_READ_RUNTIME': 7.390975952148438e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8414634146341464, 'JPEG_2K_WRITE_RUNTIME': 0.0001220703125, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n",
+      "{'JPEG_2K_BYTES': 1.829268292682927, 'JPEG_2K_WRITE_RUNTIME': 8.177757263183594e-05, 'JPEG_2K_READ_RUNTIME': 9.608268737792969e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8463414634146342, 'JPEG_2K_WRITE_RUNTIME': 9.083747863769531e-05, 'JPEG_2K_READ_RUNTIME': 9.012222290039062e-05}\n",
+      "{'JPEG_2K_BYTES': 1.8365853658536586, 'JPEG_2K_WRITE_RUNTIME': 0.00014019012451171875, 'JPEG_2K_READ_RUNTIME': 6.794929504394531e-05}\n",
+      "{'JPEG_2K_BYTES': 1.853658536585366, 'JPEG_2K_WRITE_RUNTIME': 8.177757263183594e-05, 'JPEG_2K_READ_RUNTIME': 7.295608520507812e-05}\n"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "from time import time\n",
+    "import pandas as pd\n",
+    "\n",
+    "from imagecodecs import (\n",
+    "    imwrite, \n",
+    "    imread, \n",
+    "    jpeg2k_encode, \n",
+    "    jpeg2k_decode, \n",
+    "    jpegls_encode, \n",
+    "    jpegls_decode, \n",
+    "    jpegxl_encode,\n",
+    "    jpegxl_decode,\n",
+    ")\n",
+    "\n",
+    "\n",
+    "ALGORITHMS = [\"JPEG_XL\", \"JPEG_2K\", \"JPEG_LS\"]\n",
+    "\n",
+    "\n",
+    "ALGORITHMS = [\"JPEG_2K\"]\n",
+    "\n",
+    "JPEG_ALGOS = {\n",
+    "    \"JPEG_XL\": [jpegxl_encode, jpegxl_decode, 101], \n",
+    "    \"JPEG_2K\": [jpeg2k_encode, jpeg2k_decode, 0], \n",
+    "    \"JPEG_LS\": [jpegls_encode, jpegls_decode, 0],\n",
+    "}\n",
+    "\n",
+    "def benchmark_imagecodec_compression_algos(arr, compression_type, residual=-1):\n",
+    "\n",
+    "    if compression_type in JPEG_ALGOS.keys():\n",
+    "        encoder, decoder, level = JPEG_ALGOS[compression_type]\n",
+    "\n",
+    "        write_start_time = time()\n",
+    "        encoded = encoder(arr, level=level)\n",
+    "        write_time = time() - write_start_time\n",
+    "        \n",
+    "        read_start_time = time()\n",
+    "        decoded = decoder(encoded)\n",
+    "        read_time = time() - read_start_time\n",
+    "        \n",
+    "        assert np.array_equal(arr, decoded)\n",
+    "\n",
+    "    buflength = len(encoded)\n",
+    "    \n",
+    "    \n",
+    "    return {compression_type + \"_BYTES\": buflength / arr.size,\n",
+    "            compression_type + \"_WRITE_RUNTIME\": write_time,\n",
+    "            compression_type + \"_READ_RUNTIME\": read_time\n",
+    "           }\n",
+    "\n",
+    "\n",
+    "\n",
+    "file_paths = [\"/Users/rithwik/Desktop/cube_center_run1752_camcol1_f164_82-5-800-800.fits\"]\n",
+    "\n",
+    "for path in file_paths:\n",
+    "    with fits.open(path) as hdul:  \n",
+    "        print(hdul.info())\n",
+    "        arr = hdul[0].data\n",
+    "    for algo in ALGORITHMS:\n",
+    "        for i in range(arr.shape[2]):  # Loop through the 5 sets\n",
+    "            for j in range(arr.shape[3]):  # Loop through the 82 images in each set\n",
+    "                image = arr[:, :, i, j]  # Extract the 800x800 image\n",
+    "        \n",
+    "                test_results = benchmark_imagecodec_compression_algos(image, algo, residual=1)\n",
+    "                print(test_results)\n",
+    "                break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 177,
+   "id": "2dd1aad4-25a0-4a97-a61c-46e4bfa02e9d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Filename: /Users/rithwik/Desktop/hubble2im/MAST_2024-05-10T07_48_45.055Z/HST/jw04498038001_0310a_00002_nrcb1_uncal.fits\n",
+      "No.    Name      Ver    Type      Cards   Dimensions   Format\n",
+      "  0  PRIMARY       1 PrimaryHDU     202   ()      \n",
+      "  1  SCI           1 ImageHDU        80   (64, 64, 5, 2)   int16 (rescales to uint16)   \n",
+      "  2  GROUP         1 BinTableHDU     38   1R x 13C   [I, I, I, J, I, 26A, I, I, I, I, 36A, D, D]   \n",
+      "  3  INT_TIMES     1 BinTableHDU     24   2R x 7C   [J, D, D, D, D, D, D]   \n",
+      "  4  ASDF          1 BinTableHDU     11   1R x 1C   [8163B]   \n",
+      "None\n",
+      "SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  DATE    = '2024-05-05T09:46:11.157' / UTC date file created                     ORIGIN  = 'STSCI   '           / Organization responsible for creating file     TIMESYS = 'UTC     '           / principal time system for time-related keywordsTIMEUNIT= 's       '           / Default unit applicable to all time values     FILENAME= 'jw04498038001_0310a_00002_nrcb1_uncal.fits' / Name of the file       SDP_VER = '2023_4a '           / Data processing (DP) Software Version          PRD_VER = 'PRDOPSSOC-065'      / S&OC Project Reference Database (PRD) Version  OSS_VER = '009.002.000.000'    / Observatory Scheduling Software (OSS) Version  GSC_VER = 'GSC30   '           / Guide Star Catalog (GSC) Version               DATAMODL= 'Level1bModel'       / Type of data model                             TELESCOP= 'JWST    '           / Telescope used to acquire the data             HGA_MOVE=                    F / High Gain Antenna moved during data collection PWFSEET =    60434.53219585648 / Previous WFS exposure end time                 NWFSEST =                  0.0 / Next WFS exposure start time                   COMPRESS=                    F / On-board data compression was used (T/F)                                                                                               Program information                                                                                                                                     TITLE   = 'Absolute Flux Calibration (Solar Analogs)' / Proposal title          PI_NAME = 'Gordon, Karl D.'    / Principal investigator name                    CATEGORY= 'CAL     '           / Program category                               SUBCAT  = 'CROSS   '           / Program sub-category                                                                                                                   Observation identifiers                                                                                                                                 DATE-OBS= '2024-05-05'         / [yyyy-mm-dd] UTC date at start of exposure     TIME-OBS= '03:33:39.660'       / [hh:mm:ss.sss] UTC time at start of exposure   DATE-BEG= '2024-05-05T03:33:39.660' / Date-time start of exposure               DATE-END= '2024-05-05T03:33:40.262' / Date-time end of exposure                 OBS_ID  = 'V04498038001P000000000310A' / Programmatic observation identifier    VISIT_ID= '04498038001'        / Visit identifier                               PROGRAM = '04498   '           / Program number                                 OBSERVTN= '038     '           / Observation number                             VISIT   = '001     '           / Visit number                                   VISITGRP= '03      '           / Visit group identifier                         SEQ_ID  = '1       '           / Parallel sequence identifier                   ACT_ID  = '0A      '           / Activity identifier                            EXPOSURE= '2       '           / Exposure request number                        BKGDTARG=                    F / Background target                              TEMPLATE= 'NIRCam Imaging'     / Observation template used                      OBSLABEL= 'NIRCam Imaging Sub64P Module B' / Proposer label for the observation OBSFOLDR= 'P330-E  '           / Name of the APT observation folder                                                                                                     Visit information                                                                                                                                       ENG_QUAL= 'OK      '           / Engineering data quality indicator from EngDB  ENGQLPTG= 'CALCULATED_TRACK_TR_202111' / Quality of pointing information from EnVISITYPE= 'PRIME_TARGETED_FIXED' / Visit type                                   VSTSTART= '2024-05-05 02:43:09.5450000' / UTC visit start time                  VISITSTA= 'SUCCESSFUL'         / Status of a visit                              NEXPOSUR=                   24 / Total number of planned exposures in visit     INTARGET=                    F / At least one exposure in visit is internal     TARGOOPP=                    F / Visit scheduled as target of opportunity       TSOVISIT=                    F / Time Series Observation visit indicator        EXP_ONLY=                    F / Special commanding without SI configuration    CROWDFLD=                    F / Are the FGSes in a crowded field?                                                                                                      Target information                                                                                                                                      TARGPROP= 'P330-E  '           / Proposer's name for the target                 TARGNAME= 'GSPC P330-E'        / Standard astronomical catalog name for target  TARGTYPE= 'FIXED   '           / Type of target (fixed, moving, generic)        TARGCAT = 'Star    '           / Target category from APT                       TARGDESC= 'G dwarfs'           / Target description from APT                    TARG_RA =   247.89081554763152 / Target RA at mid time of exposure              TARG_DEC=   30.145960505058927 / Target Dec at mid time of exposure             TARGURA =                  0.1 / Target RA uncertainty                          TARGUDEC=                  0.1 / Target Dec uncertainty                         MU_RA   =            -0.008882 / Target proper motion in RA                     MU_DEC  = -0.03870499999999999 / Target proper motion in Dec                    MU_EPOCH= '2000-01-01 00:00:00.0000000' / Target proper motion epoch            PROP_RA =   247.89088499999997 / Proposer's target RA                           PROP_DEC=    30.14622222222222 / Proposer's target Dec                                                                                                                  Instrument configuration information                                                                                                                    INSTRUME= 'NIRCAM  '           / Instrument used to acquire the data            DETECTOR= 'NRCB1   '           / Name of detector used to acquire the data      MODULE  = 'B       '           / NIRCam module: A, B, or MULTIPLE               CHANNEL = 'SHORT   '           / Instrument channel                             FILTER  = 'F200W   '           / Name of the filter element used                PUPIL   = 'CLEAR   '           / Name of the pupil element used                 PILIN   =                    F / Pupil imaging lens in the optical path?                                                                                                Exposure parameters                                                                                                                                     EXPCOUNT=                   18 / Running count of exposures in visit            EXPRIPAR= 'PRIME   '           / Prime or parallel exposure                     EXP_TYPE= 'NRC_IMAGE'          / Type of data in the exposure                   EXPSTART=    60435.14837569537 / [d] exposure start time in MJD                 EXPMID  =     60435.1483791787 / [d] exposure mid time in MJD                   EXPEND  =    60435.14838266204 / [d] exposure end time in MJD                   OSF_FILE= '2024126T091026166_001_osf.xml' / Observatory Status File name coverinREADPATT= 'RAPID   '           / Readout pattern                                NOUTPUTS=                    1 / Number of detector outputs used                NINTS   =                    2 / Number of integrations in exposure             NGROUPS =                    5 / Number of groups in integration                NFRAMES =                    1 / Number of frames per group                     FRMDIVSR=                    1 / Divisor applied to frame-averaged groups       GROUPGAP=                    0 / Number of frames dropped between groups        DRPFRMS1=                    0 / Frames dropped prior to first integration      DRPFRMS3=                    0 / Frames dropped between integrations            NSAMPLES=                    1 / Number of A/D samples per pixel                TSAMPLE =                 10.0 / [us] Time between samples                      TFRAME  =              0.05016 / [s] Time between frames                        TGROUP  =              0.05016 / [s] Time between groups                        EFFINTTM=               0.2508 / [s] Effective integration time                 EFFEXPTM=                0.502 / [s] Effective exposure time                    DURATION=                0.607 / [s] Total duration of exposure                 NRSTSTRT=                    1 / Number of resets at start of exposure          NRESETS =                    1 / Number of resets between integrations          ZEROFRAM=                    F / Zero frame was downlinked separately           DATAPROB=                    F / Science telemetry indicated a problem          SCA_NUM =                  486 / Sensor Chip Assembly number                    DATAMODE=                   33 / post-processing method used in FPAP            SCTARATE=                  0.0 / [ms/s] Spacecraft Clock Time Adjust RATE                                                                                               Subarray parameters                                                                                                                                     SUBARRAY= 'SUB64P  '           / Subarray used                                  SUBSTRT1=                 1851 / Starting pixel in axis 1 direction             SUBSTRT2=                 1817 / Starting pixel in axis 2 direction             SUBSIZE1=                   64 / Number of pixels in axis 1 direction           SUBSIZE2=                   64 / Number of pixels in axis 2 direction           FASTAXIS=                    1 / Fast readout axis direction                    SLOWAXIS=                   -2 / Slow readout axis direction                                                                                                            Dither information                                                                                                                                      PATTTYPE= 'SUBARRAY_DITHER'    / Primary dither pattern type                    PRIDTYPE= '4       '           / Primary dither points and packing              PRIDTPTS=                    4 / Number of points in primary dither pattern     PATT_NUM=                    2 / Position number within dither pattern          NUMDTHPT=                    4 / Total number of points in pattern              SUBPXPTS=                    1 / Number of points in subpixel dither pattern    SUBPXPAT= 'STANDARD'           / Subpixel dither pattern type                   XOFFSET =            0.3350007 / x offset from pattern starting position        YOFFSET =            0.3349999 / y offset from pattern starting position                                                                                                Aperture information                                                                                                                                    APERNAME= 'NRCB1_SUB64P'       / PRD science aperture used                      PPS_APER= 'NRCB5_SUB64P'       / original AperName supplied by PPS                                                                                                      Time information                                                                                                                                        BARTDELT=   380.69275945890695 / [s] Barycentric correction at exposure start   BSTRTIME=   60435.152781861565 / [d] Barycentric exposure start time in MJD     BENDTIME=   60435.152788828345 / [d] Barycentric exposure end time in MJD       BMIDTIME=    60435.15278534495 / [d] Barycentric exposure mid time in MJD       HELIDELT=   378.43239214271307 / [s] Heliocentric correction at exposure start  HSTRTIME=   60435.152755699906 / [d] Heliocentric exposure start time in MJD    HENDTIME=    60435.15276266669 / [d] Heliocentric exposure end time in MJD      HMIDTIME=     60435.1527591833 / [d] Heliocentric exposure mid time in MJD                                                                                              NIRCam Focus Adjust Mechanism parameters                                                                                                                FAM_LA1 =                    0 / position in steps of linear actuator 1         FASTEP1 =                    0 / requested focus actuator 1 starting steps      FAUNIT1 =                  0.0 / requested focus actuator 1 starting units      FAPHASE1= 'NULL    '           / requested focus actuator 1 starting phase      FA1VALUE=                    0 / requested focus actuator 1 position value      FAM_LA2 =                    0 / position in steps of linear actuator 2         FASTEP2 =                    0 / requested focus actuator 2 starting steps      FAUNIT2 =                  0.0 / requested focus actuator 2 starting units      FAPHASE2= 'NULL    '           / requested focus actuator 2 starting phase      FA2VALUE=                    0 / requested focus actuator 2 position value      FAM_LA3 =                    0 / position in steps of linear actuator 3         FASTEP3 =                    0 / requested focus actuator 3 starting steps      FAUNIT3 =                  0.0 / requested focus actuator 3 starting units      FAPHASE3= 'NULL    '           / requested focus actuator 3 starting phase      FA3VALUE=                    0 / requested focus actuator 3 position value                                                                                              Guide star information                                                                                                                                  GS_ORDER=                    1 / index of guide star within list of selected guiGSSTRTTM= '2024-05-05 02:55:08.3920000' / UTC time when guide star activity starGSENDTIM= '2024-05-05 02:59:11.0800000' / UTC time when guide star activity compGDSTARID= 'N62G002475'         / guide star identifier                          GS_RA   =     247.887317487359 / guide star right ascension                     GS_DEC  =    30.23942786320166 / guide star declination                         GS_URA  =         0.0381623022 / guide star right ascension uncertainty         GS_UDEC =           0.04689268 / guide star declination uncertainty             GS_MAG  =    15.00238132476807 / guide star magnitude in FGS detector           GS_UMAG =  0.02401826716959476 / guide star magnitude uncertainty               GS_V3_PA=    210.9691490535722 / V3 Position Angle of guide star for science    PCS_MODE= 'FINEGUIDE'          / Pointing Control System mode                   VISITEND= '2024-05-05 03:46:17.3170000' / Observatory UTC time when the visit coNEXTEND =                    3 / Number of file extensions                      VA_RA   =   247.89666010132925                                                  VA_DEC  =    30.14366511305928                                                  COMMENT /Exposure parameters                                                    COMMENT / Program information                                                   COMMENT / Observation identifiers                                               COMMENT / Visit information                                                     COMMENT / Target information                                                    COMMENT / Exposure times                                                        COMMENT / NIRCam Focus Adjust Mechanism                                         END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             \n",
+      "[(1, 60435.14838266, 60435.14838266, 60435.14838266, 60435.15278883, 60435.15278883, 60435.15278883)\n",
+      " (2, 60435.14838266, 60435.14838266, 60435.14838266, 60435.15278883, 60435.15278883, 60435.15278883)]\n"
+     ]
+    }
+   ],
+   "source": [
+    "path = \"~/Desktop/hubble2im/MAST_2024-05-10T07_48_45.055Z/HST/jw04498038001_0310a_00002_nrcb1_uncal.fits\"\n",
+    "\n",
+    "path2 = \"~/Desktop/hubble2im/MAST_2024-05-10T07_48_45.055Z/HST/jw04498038001_0310a_00002_nrcblong_uncal.fits\"\n",
+    "\n",
+    "with fits.open(path) as hdul:  \n",
+    "    print(hdul.info())\n",
+    "    print(hdul[0].header)\n",
+    "    arr = hdul[3].data\n",
+    "    print(arr)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ec59e584-248f-4ad3-9f00-09a2a6d69086",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}