comments

utils/jwst_downloading.ipynb

@@ -9,8 +9,6 @@
    "source": [
     "\"\"\"\n",
     "\n",
-    "FULLY UNCLEANED CODE\n",
-    "\n",
     "Contains the necessary scripts to actually download the FITS files that are in your JWST csv.\n",
     "\n",
     "\n",
@@ -644,6 +642,11 @@
     "\n",
     "THRESH = JWST_FOV\n",
     "\n",
+    "\"\"\"\n",
+    "Initial clustering and filtering using single RA DEC value.\n",
+    "\n",
+    "\"\"\"\n",
+    "\n",
     "clustering = AgglomerativeClustering(n_clusters=None, metric='precomputed', linkage='single', distance_threshold=THRESH)\n",
     "labels = clustering.fit_predict(angular_separations_matrix)\n",
     "\n",
@@ -740,6 +743,11 @@
    "source": [
     "from astropy.table import unique, vstack, Table\n",
     "\n",
+    "\"\"\"\n",
+    "Call API that gives the file URLs for each observations.\n",
+    "\n",
+    "\"\"\"\n",
+    "\n",
     "matched_obs = result\n",
     "\n",
     "# Split the observations into \"chunks\" of size five\n",
@@ -782,17 +790,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "manifest = Observations.download_products(files['obsID'], curl_flag=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b8b7937f-ca1d-4b4c-abef-1055cdf115ef",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "wi"
+    "manifest = Observations.download_products(files['obsID'], curl_flag=True)\n",
+    "# Creates .sh scripts that have to then be run to actually download data"
    ]
   },
   {
@@ -807,6 +806,12 @@
     "from astropy.table import Table\n",
     "import glob\n",
     "\n",
+    "\"\"\"\n",
+    "This code allows us to combine multiple exposures of the same observation into one FITS file.\n",
+    "\n",
+    "This code was NOT used; we only used a single exposure for our dataset.\n",
+    "\"\"\"\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",
@@ -1005,6 +1010,7 @@
    "source": [
     "\"\"\"\n",
     "Code to verify test/train pollution.\n",
+    "Prints images which are nearby and might overlap.\n",
     "\"\"\"\n",
     "\n",
     "\n",

utils/jwst_filtering.ipynb

@@ -265,6 +265,8 @@
     "# This is 6 arcmin; both detectors are 5.1 by 2.2 arcmin\n",
     "JWST_FOV = 0.085 # 5.1 arcmin\n",
     "\n",
+    "# Initial clustering from RA DEC only\n",
+    "\n",
     "THRESH = JWST_FOV * 2\n",
     "\n",
     "clustering = AgglomerativeClustering(n_clusters=None, metric='precomputed', linkage='single', distance_threshold=THRESH)\n",
@@ -3182,6 +3184,8 @@
     "failed_labels = []\n",
     "failed_paths = []\n",
     "\n",
+    "# Compute spherical polygon overlaps to verify overlap and remove ones that overlap\n",
+    "\n",
     "for label in tqdm(np.unique(labels)):\n",
     "    polys = [(all_polys[i], confirmed_fits_paths[i]) for i in range(len(labels)) if labels[i] == label]\n",
     "    if len(polys) > 1:\n",