From 8a8452f04d977e2b4d4a18cb3670bcb186828d37 Mon Sep 17 00:00:00 2001
From: Josh Dillon <jsdillon@berkeley.edu>
Date: Sat, 20 Apr 2024 09:39:54 -0700
Subject: [PATCH] avoid infinite loop with ping-ponging convergence

---
 notebooks/file_calibration.ipynb | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/notebooks/file_calibration.ipynb b/notebooks/file_calibration.ipynb
index d52476f..908d752 100644
--- a/notebooks/file_calibration.ipynb
+++ b/notebooks/file_calibration.ipynb
@@ -493,6 +493,7 @@
     "# Iteratively develop RFI mask, excess RFI classification, and autocorrelation shape classification\n",
     "stage = 1\n",
     "rfi_flags = np.array(array_flags)\n",
+    "prior_end_states = set()\n",
     "while True:\n",
     "    # compute DPSS-filtered z-scores with current array-wide RFI mask\n",
     "    zscores = auto_bl_zscores(data, rfi_flags)\n",
@@ -504,7 +505,6 @@
     "        # use best half of the unflagged antennas\n",
     "        med_rms = np.nanmedian([rms[bl] for bl in candidate_autos])\n",
     "        autos_to_use = [bl for bl in candidate_autos if rms[bl] <= med_rms]\n",
-    "        stage += 1  # advance to stage 2\n",
     "    elif stage == 2:\n",
     "        # use all unflagged antennas which are auto RFI good, or the best half, whichever is larger\n",
     "        med_rms = np.nanmedian([rms[bl] for bl in candidate_autos])\n",
@@ -512,7 +512,6 @@
     "        good_autos = [bl for bl in candidate_autos if (overall_class[utils.split_bl(bl)[0]] != 'bad')\n",
     "                      and (auto_rfi_class[utils.split_bl(bl)[0]] == 'good')]\n",
     "        autos_to_use = (best_half_autos if len(best_half_autos) > len(good_autos) else good_autos)\n",
-    "        stage += 1  # advance to stage 3\n",
     "    elif stage == 3:\n",
     "        # use all unflagged antennas which are auto RFI good or suspect\n",
     "        autos_to_use = [bl for bl in candidate_autos if (overall_class[utils.split_bl(bl)[0]] != 'bad')]\n",
@@ -529,12 +528,13 @@
     "                                                    antenna_class=overall_class)\n",
     "    overall_class += auto_shape_class\n",
     "    \n",
-    "    # check for convergence on flagged antennas and channels \n",
+    "    # check for convergence by seeing whether we've previously gotten to this number of flagged antennas and channels\n",
     "    if stage == 3:\n",
-    "        if (len(overall_class.bad_ants) == n_current_bad_ants) and (np.sum(rfi_flags) == current_flagged_chan_times):\n",
+    "        if (len(overall_class.bad_ants), np.sum(rfi_flags)) in prior_end_states:\n",
     "            break\n",
-    "    current_flagged_chan_times = np.sum(rfi_flags)\n",
-    "    n_current_bad_ants = len(overall_class.bad_ants)"
+    "        prior_end_states.add((len(overall_class.bad_ants), np.sum(rfi_flags)))\n",
+    "    else:\n",
+    "        stage += 1"
    ]
   },
   {