From b91e58239e5e1853bed565bb8ffe1379efc61de2 Mon Sep 17 00:00:00 2001
From: Jeff Carlin <jcarlin@lsst.org>
Date: Fri, 11 Oct 2024 23:50:43 +0000
Subject: [PATCH] Add LVV-T1750 and 1753 NB

---
 notebooks/test_LVV-T1750_1753.ipynb | 583 ++++++++++++++++++++++++++++
 1 file changed, 583 insertions(+)
 create mode 100644 notebooks/test_LVV-T1750_1753.ipynb

diff --git a/notebooks/test_LVV-T1750_1753.ipynb b/notebooks/test_LVV-T1750_1753.ipynb
new file mode 100644
index 0000000..44aca4e
--- /dev/null
+++ b/notebooks/test_LVV-T1750_1753.ipynb
@@ -0,0 +1,583 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fbc2a82e-c64a-4801-b3bc-4c3c0917500f",
+   "metadata": {},
+   "source": [
+    "### Test case LVV-T1753 - Verify calculation of RMS difference of separations relative to r-band\n",
+    "\n",
+    "Verify that the DM system has provided the code to calculate the separations measured relative to the r-band, and assess whether it meets the requirement that it shall be less than **AB1 = 10 milliarcseconds**.\n",
+    "\n",
+    "#### AND\n",
+    "\n",
+    "### Test case LVV-T1750 - Verify calculation of separations relative to r-band exceeding color difference outlier limit\n",
+    "\n",
+    "Verify that the DM system has provided the code to calculate the separations measured relative to the r-band that exceed the color difference outlier limit **AB2 = 20 milliarcseconds**, and assess whether it meets the requirement that it shall be less than **ABF1 = 10 percent**."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8e6183b9-0e34-4a99-a1b5-62d6b1f4db44",
+   "metadata": {},
+   "source": [
+    "#### Discussion:\n",
+    "These tests can be verified using data products produced during regular reprocessing campaigns executed by the Data Management pipelines team. In particular, we will use the regularly-reprocessed HSC RC2 data as reprocessed with weekly pipelines version w_2024_34, in Butler collection “HSC/runs/RC2/w_2024_34/DM-45857\".\n",
+    "\n",
+    "The `AB1` and `ABF1` metrics and related plots are created by tasks in the `analysis_tools` package (specifically, the [TargetRefCatDeltaColorMetrics](https://github.com/lsst/analysis_tools/blob/6903dfedeb0232d1cc74fffcbea35eeab1598c08/python/lsst/analysis/tools/atools/refCatMatchPlots.py#L649-L764) task). Thus verification of this requirement can be accomplished by simply retrieving the datasets produced by those tasks and confirming that they meet the required accuracy."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "93081372-0262-4f3e-8c3e-fa33ad9feaf9",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-11T23:48:24.491748Z",
+     "iopub.status.busy": "2024-10-11T23:48:24.491627Z",
+     "iopub.status.idle": "2024-10-11T23:48:25.495551Z",
+     "shell.execute_reply": "2024-10-11T23:48:25.495092Z",
+     "shell.execute_reply.started": "2024-10-11T23:48:24.491736Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "from astropy.table import Table\n",
+    "\n",
+    "from lsst.daf.butler import Butler\n",
+    "from IPython.display import Image"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "58da7a76-d3b9-4ac2-bd33-9f4593169062",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-11T23:48:25.496367Z",
+     "iopub.status.busy": "2024-10-11T23:48:25.496218Z",
+     "iopub.status.idle": "2024-10-11T23:48:25.938986Z",
+     "shell.execute_reply": "2024-10-11T23:48:25.938520Z",
+     "shell.execute_reply.started": "2024-10-11T23:48:25.496352Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Initialize the butler repo pointing to the DM-45857 (w_2024_34) collection\n",
+    "repo = '/repo/main'\n",
+    "collection = 'u/jcarlin/atools_visitQualityCore_AB1'\n",
+    "\n",
+    "butler = Butler(repo, collections=collection)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f3324897-0f45-4963-9653-4e7ed4bfef8d",
+   "metadata": {},
+   "source": [
+    "Retrieve results for a set of 5 visits in each of the g, r, i, and z bands:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "7e0f04f3-194e-4e73-82c4-7c24efcdb4a1",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-11T23:48:25.939700Z",
+     "iopub.status.busy": "2024-10-11T23:48:25.939574Z",
+     "iopub.status.idle": "2024-10-11T23:48:25.942514Z",
+     "shell.execute_reply": "2024-10-11T23:48:25.942163Z",
+     "shell.execute_reply.started": "2024-10-11T23:48:25.939687Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "visit_list = [26044,26046,26048,26050,26058,23884,23886,23888,23890,23898,1302,1306,1308,1310,1314,23250,23256,23258,27090,27094]\n",
+    "bands_list = ['g', 'g', 'g', 'g', 'g', 'r', 'r', 'r', 'r', 'r', 'i', 'i', 'i', 'i', 'i', 'z', 'z', 'z', 'z', 'z']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1d061638-033e-4e43-8cbd-2bf9368cfd93",
+   "metadata": {},
+   "source": [
+    "Loop over the visits and extract the metrics for each one:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "01e254e6-efe1-4bb4-8f6f-aa789e1061c4",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-11T23:48:25.943137Z",
+     "iopub.status.busy": "2024-10-11T23:48:25.943016Z",
+     "iopub.status.idle": "2024-10-11T23:48:30.098231Z",
+     "shell.execute_reply": "2024-10-11T23:48:30.097821Z",
+     "shell.execute_reply.started": "2024-10-11T23:48:25.943125Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "ab1_ra_list = []\n",
+    "ab1_dec_list = []\n",
+    "ab1_tot_list = []\n",
+    "abf1_ra_list = []\n",
+    "abf1_dec_list = []\n",
+    "abf1_tot_list = []\n",
+    "dataids_list = []\n",
+    "\n",
+    "for vis in visit_list:\n",
+    "    did0 = {'instrument':'HSC', 'skymap':'hsc_rings_v1', 'visit':vis}\n",
+    "    dataids_list.append(did0)\n",
+    "    metric_extract0 = butler.get('sourceObjectTable_metrics', collections=collection, dataId=did0)\n",
+    "    ab1_ra_list.append(metric_extract0['astromColorDiffMetrics'][0].quantity.value)\n",
+    "    ab1_dec_list.append(metric_extract0['astromColorDiffMetrics'][2].quantity.value)\n",
+    "    ab1_tot_list.append(metric_extract0['astromColorDiffMetrics'][4].quantity.value)\n",
+    "    abf1_ra_list.append(metric_extract0['astromColorDiffMetrics'][1].quantity.value)\n",
+    "    abf1_dec_list.append(metric_extract0['astromColorDiffMetrics'][3].quantity.value)\n",
+    "    abf1_tot_list.append(metric_extract0['astromColorDiffMetrics'][5].quantity.value)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5213b86a-e2fa-48b9-9ba5-c06f9b1ec946",
+   "metadata": {},
+   "source": [
+    "Place the results into a table:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "6ab0cc5d-f497-4a45-bfb4-37ad6ba08be9",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-11T23:48:30.098970Z",
+     "iopub.status.busy": "2024-10-11T23:48:30.098834Z",
+     "iopub.status.idle": "2024-10-11T23:48:30.102373Z",
+     "shell.execute_reply": "2024-10-11T23:48:30.102021Z",
+     "shell.execute_reply.started": "2024-10-11T23:48:30.098957Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "tab = Table([visit_list, bands_list, ab1_ra_list, ab1_dec_list, ab1_tot_list, abf1_ra_list, abf1_dec_list, abf1_tot_list],\n",
+    "            names=['visit', 'band', 'ab1_ra', 'ab1_dec', 'ab1_tot', 'abf1_ra', 'abf1_dec', 'abf1_tot'],\n",
+    "            units=['', '', 'mas', 'mas', 'mas', '%', '%', '%'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "90f65536-9bfe-4f94-a4c6-8bcbcfd50771",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-11T23:48:30.103102Z",
+     "iopub.status.busy": "2024-10-11T23:48:30.102983Z",
+     "iopub.status.idle": "2024-10-11T23:48:30.109615Z",
+     "shell.execute_reply": "2024-10-11T23:48:30.109270Z",
+     "shell.execute_reply.started": "2024-10-11T23:48:30.103091Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><i>Table length=20</i>\n",
+       "<table id=\"table140662480844944\" class=\"table-striped table-bordered table-condensed\">\n",
+       "<thead><tr><th>visit</th><th>band</th><th>ab1_ra</th><th>ab1_dec</th><th>ab1_tot</th><th>abf1_ra</th><th>abf1_dec</th><th>abf1_tot</th></tr></thead>\n",
+       "<thead><tr><th></th><th></th><th>mas</th><th>mas</th><th>mas</th><th>%</th><th>%</th><th>%</th></tr></thead>\n",
+       "<thead><tr><th>int64</th><th>str1</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
+       "<tr><td>26044</td><td>g</td><td>3.650680062795275</td><td>4.468768783736823</td><td>5.791720739321608</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
+       "<tr><td>26046</td><td>g</td><td>3.874667532283035</td><td>4.3043317473923075</td><td>5.806685942591208</td><td>0.1037344398340249</td><td>0.1037344398340249</td><td>0.3112033195020747</td></tr>\n",
+       "<tr><td>26048</td><td>g</td><td>3.8739086880001152</td><td>4.306863632466594</td><td>5.877020866531886</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
+       "<tr><td>26050</td><td>g</td><td>3.6644363819592027</td><td>3.9277900932699463</td><td>5.425082016769175</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
+       "<tr><td>26058</td><td>g</td><td>3.310385930618475</td><td>4.9969414923627085</td><td>5.996188715224293</td><td>0.0</td><td>0.3058103975535168</td><td>0.3058103975535168</td></tr>\n",
+       "<tr><td>23884</td><td>r</td><td>2.2559941503047463</td><td>2.630665847355618</td><td>3.458239026023966</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
+       "<tr><td>23886</td><td>r</td><td>7.207078930705799</td><td>3.9436877745769348</td><td>8.248137855284496</td><td>0.09250693802035154</td><td>0.09250693802035154</td><td>0.09250693802035154</td></tr>\n",
+       "<tr><td>23888</td><td>r</td><td>3.0737077667113493</td><td>2.9005950728762193</td><td>4.2141520451041385</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
+       "<tr><td>23890</td><td>r</td><td>2.4985530670612732</td><td>2.4891825481319927</td><td>3.5154437137447</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
+       "<tr><td>23898</td><td>r</td><td>2.9199918805533662</td><td>2.725426775953169</td><td>4.0001023200545545</td><td>0.14306151645207438</td><td>0.0</td><td>0.14306151645207438</td></tr>\n",
+       "<tr><td>1302</td><td>i</td><td>12.289221865781066</td><td>10.727916790395557</td><td>15.255017898489715</td><td>3.9552880481513326</td><td>3.52536543422184</td><td>8.25451418744626</td></tr>\n",
+       "<tr><td>1306</td><td>i</td><td>8.512366820540022</td><td>11.953670876039922</td><td>11.620625358020009</td><td>3.2520325203252036</td><td>4.878048780487805</td><td>6.178861788617886</td></tr>\n",
+       "<tr><td>1308</td><td>i</td><td>7.096249842850177</td><td>10.15639925583551</td><td>9.936511697765795</td><td>2.022417153996101</td><td>3.557504873294347</td><td>3.898635477582846</td></tr>\n",
+       "<tr><td>1310</td><td>i</td><td>6.063287903801438</td><td>10.185135839304518</td><td>8.352796284423063</td><td>0.6116207951070336</td><td>3.3639143730886847</td><td>2.4464831804281344</td></tr>\n",
+       "<tr><td>1314</td><td>i</td><td>9.128779598350288</td><td>10.609799622852263</td><td>12.921235199791969</td><td>3.7356321839080464</td><td>3.0172413793103448</td><td>8.117816091954024</td></tr>\n",
+       "<tr><td>23250</td><td>z</td><td>6.362360646339276</td><td>7.36767984288997</td><td>9.731409447469229</td><td>0.6734006734006733</td><td>0.8978675645342313</td><td>2.525252525252525</td></tr>\n",
+       "<tr><td>23256</td><td>z</td><td>5.587071582571456</td><td>5.418434890678499</td><td>7.681504304110495</td><td>0.0</td><td>0.8264462809917356</td><td>1.6528925619834711</td></tr>\n",
+       "<tr><td>23258</td><td>z</td><td>21.27946534475339</td><td>17.724677931118322</td><td>27.762207972427824</td><td>0.34403669724770647</td><td>0.4396024464831804</td><td>0.8792048929663608</td></tr>\n",
+       "<tr><td>27090</td><td>z</td><td>8.24464980334419</td><td>20.40273026428511</td><td>21.97937420618622</td><td>0.4368546465448769</td><td>0.3574265289912629</td><td>1.0325655281969817</td></tr>\n",
+       "<tr><td>27094</td><td>z</td><td>20.12296464701037</td><td>5.447986573621286</td><td>20.850010500823355</td><td>0.425531914893617</td><td>0.851063829787234</td><td>1.276595744680851</td></tr>\n",
+       "</table></div>"
+      ],
+      "text/plain": [
+       "<Table length=20>\n",
+       "visit band       ab1_ra       ...       abf1_dec            abf1_tot     \n",
+       "                  mas         ...          %                   %         \n",
+       "int64 str1      float64       ...       float64             float64      \n",
+       "----- ---- ------------------ ... ------------------- -------------------\n",
+       "26044    g  3.650680062795275 ...                 0.0                 0.0\n",
+       "26046    g  3.874667532283035 ...  0.1037344398340249  0.3112033195020747\n",
+       "26048    g 3.8739086880001152 ...                 0.0                 0.0\n",
+       "26050    g 3.6644363819592027 ...                 0.0                 0.0\n",
+       "26058    g  3.310385930618475 ...  0.3058103975535168  0.3058103975535168\n",
+       "23884    r 2.2559941503047463 ...                 0.0                 0.0\n",
+       "23886    r  7.207078930705799 ... 0.09250693802035154 0.09250693802035154\n",
+       "23888    r 3.0737077667113493 ...                 0.0                 0.0\n",
+       "23890    r 2.4985530670612732 ...                 0.0                 0.0\n",
+       "23898    r 2.9199918805533662 ...                 0.0 0.14306151645207438\n",
+       " 1302    i 12.289221865781066 ...    3.52536543422184    8.25451418744626\n",
+       " 1306    i  8.512366820540022 ...   4.878048780487805   6.178861788617886\n",
+       " 1308    i  7.096249842850177 ...   3.557504873294347   3.898635477582846\n",
+       " 1310    i  6.063287903801438 ...  3.3639143730886847  2.4464831804281344\n",
+       " 1314    i  9.128779598350288 ...  3.0172413793103448   8.117816091954024\n",
+       "23250    z  6.362360646339276 ...  0.8978675645342313   2.525252525252525\n",
+       "23256    z  5.587071582571456 ...  0.8264462809917356  1.6528925619834711\n",
+       "23258    z  21.27946534475339 ...  0.4396024464831804  0.8792048929663608\n",
+       "27090    z   8.24464980334419 ...  0.3574265289912629  1.0325655281969817\n",
+       "27094    z  20.12296464701037 ...   0.851063829787234   1.276595744680851"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tab"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "18160f59-6d9a-41dc-916f-a132dea8d922",
+   "metadata": {},
+   "source": [
+    "Calculate mean values for each metric in each band:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "a9119ff3-0728-433c-86a9-03f29325ce70",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-11T23:48:30.110177Z",
+     "iopub.status.busy": "2024-10-11T23:48:30.110064Z",
+     "iopub.status.idle": "2024-10-11T23:48:30.116939Z",
+     "shell.execute_reply": "2024-10-11T23:48:30.116571Z",
+     "shell.execute_reply.started": "2024-10-11T23:48:30.110166Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "bands = ['g', 'i', 'z']\n",
+    "from collections import defaultdict\n",
+    "\n",
+    "avg_values = defaultdict(list)\n",
+    "\n",
+    "metrics_list = ['ab1_ra', 'ab1_dec', 'ab1_tot', 'abf1_ra', 'abf1_dec', 'abf1_tot']\n",
+    "units_list = ['mas', 'mas', 'mas', '%', '%', '%']\n",
+    "\n",
+    "for band in bands:\n",
+    "    inband = (tab['band']==band)\n",
+    "    for metric in metrics_list:\n",
+    "        avg_values[band].append({metric:np.mean(tab[inband][metric])})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "5046e3e5-a8f5-4b59-9c0b-e1f0b92b5d9e",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-11T23:48:30.117517Z",
+     "iopub.status.busy": "2024-10-11T23:48:30.117400Z",
+     "iopub.status.idle": "2024-10-11T23:48:30.122104Z",
+     "shell.execute_reply": "2024-10-11T23:48:30.121739Z",
+     "shell.execute_reply.started": "2024-10-11T23:48:30.117506Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "g\n",
+      "ab1_ra = 3.67 mas\n",
+      "ab1_dec = 4.40 mas\n",
+      "ab1_tot = 5.78 mas\n",
+      "abf1_ra = 0.02 %\n",
+      "abf1_dec = 0.08 %\n",
+      "abf1_tot = 0.12 %\n",
+      "\n",
+      "i\n",
+      "ab1_ra = 8.62 mas\n",
+      "ab1_dec = 10.73 mas\n",
+      "ab1_tot = 11.62 mas\n",
+      "abf1_ra = 2.72 %\n",
+      "abf1_dec = 3.67 %\n",
+      "abf1_tot = 5.78 %\n",
+      "\n",
+      "z\n",
+      "ab1_ra = 12.32 mas\n",
+      "ab1_dec = 11.27 mas\n",
+      "ab1_tot = 17.60 mas\n",
+      "abf1_ra = 0.38 %\n",
+      "abf1_dec = 0.67 %\n",
+      "abf1_tot = 1.47 %\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for band in bands:\n",
+    "    print(band)\n",
+    "    for i in range(len(metrics_list)):\n",
+    "        print(metrics_list[i], '=', \"%.2F\" % avg_values[band][i][metrics_list[i]], units_list[i])\n",
+    "    print('')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b81c67c9-0a85-422b-955c-9a6154337fb5",
+   "metadata": {},
+   "source": [
+    "Looking at the metrics from _total_ offsets, we see that AB1 is less than the required 10 mas in g-band, but does not meet this threshold in i- or z-band. ABF1 is well below the required 10% value. Note, however, that these tests are meant solely to confirm that the tools exist to _measure_ the metrics; clearly more work must be done in the future for these metrics to meet the thresholds."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "eda41610-779f-46dc-88e2-ccb6c6277462",
+   "metadata": {},
+   "source": [
+    "### Plots associated with the metrics\n",
+    "\n",
+    "Retrieve the plots that are created alongside the metrics by `analysis_tools`, and display them in the notebook."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ede1f22b-84a2-49d6-934d-3fbf1ed7ee38",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-07-26T22:42:33.056444Z",
+     "iopub.status.busy": "2024-07-26T22:42:33.056097Z",
+     "iopub.status.idle": "2024-07-26T22:42:33.058611Z",
+     "shell.execute_reply": "2024-07-26T22:42:33.058210Z",
+     "shell.execute_reply.started": "2024-07-26T22:42:33.056429Z"
+    }
+   },
+   "source": [
+    "Extract the byte-level data for the images into a dict, which we will then use to display the plots:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "14bff142-30d9-4b5c-83ec-e9d232ef0201",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-11T23:48:30.122705Z",
+     "iopub.status.busy": "2024-10-11T23:48:30.122588Z",
+     "iopub.status.idle": "2024-10-11T23:48:30.658777Z",
+     "shell.execute_reply": "2024-10-11T23:48:30.658287Z",
+     "shell.execute_reply.started": "2024-10-11T23:48:30.122695Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "plot_dict = {}\n",
+    "\n",
+    "for band in ['g', 'i', 'z']:\n",
+    "    plot_name = f\"sourceObjectTable_{band}_astromColorDiffMetrics_HistPlot\"\n",
+    "    # Select just one dataId for each band:\n",
+    "    did_number = {'g':2, 'i':12, 'z':17}\n",
+    "    ref = butler.registry.findDataset(plot_name, dataids_list[did_number[band]], collections=collection)\n",
+    "    uri = butler.getURI(ref)\n",
+    "    image_bytes = uri.read()\n",
+    "    plot_dict[plot_name] = image_bytes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1b87a2fc-3d1d-416c-a5d2-e7a2cd343235",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-07-26T21:36:07.480626Z",
+     "iopub.status.busy": "2024-07-26T21:36:07.480359Z",
+     "iopub.status.idle": "2024-07-26T21:36:07.483427Z",
+     "shell.execute_reply": "2024-07-26T21:36:07.483127Z",
+     "shell.execute_reply.started": "2024-07-26T21:36:07.480613Z"
+    }
+   },
+   "source": [
+    "Display the plots. Note that I manually entered the key to the plot dict in each of the following 3 cells. For some reason they don't display if I loop over them..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "21e7538b-7092-4083-bb17-a9c9a71c4685",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-11T23:48:30.659566Z",
+     "iopub.status.busy": "2024-10-11T23:48:30.659419Z",
+     "iopub.status.idle": "2024-10-11T23:48:30.665062Z",
+     "shell.execute_reply": "2024-10-11T23:48:30.664632Z",
+     "shell.execute_reply.started": "2024-10-11T23:48:30.659552Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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uOVNQUFCq+1esWGFxjg0bNjSdPn061bJnzpwx1ahRw1y2dOnSpps3b6Za1sfHx1yuWbNmppCQkHTP7cyZM6aRI0dm+j0pI/Hx8SZXV1dzDDNmzMh03eTXI2nI5+HDh5uioqJSlD116pSpePHi5vI+Pj6mnj17miSZWrdunepwv3fu3DE9+uij5jr29vam0NDQNOPZtWuXqVGjRqYffvgh1RiShIeHm1577TWL+D/55JN0z/XB9wzp/nDcmZm6YNOmTRZDYhcrVizdIZQTExNNv//+u6ljx44p9j3YM3/YsGGm2NjYdNvy8/MzvfHGG2mWycvvA2FhYRbDNEsyDR06NN0hvQMDA03vvPOO6aeffkqzTPL2k1/bZcuWZVgHAAAAAAoTEsAAABQxLVq0SPGfzY0aNTLNmjXLdOLEiRwnwwYNGmSRgMnMPMPPP/+8uU7lypXTTL6m9h/lP/74Y7ptL1myxKK8r69vmmWjo6MzjDXJg//53KtXr3TLP5gArl69errzuuYktq+++sriWKdOnUqzbH4kgOfPn29xjFGjRqXb7qVLl0yenp4Wifu0ki4PJoAlmdasWZNu+8mHpZUyPy9pZuRWAthkMpnatm1r0daZM2dSLZeZBPDjjz9uLjN69Ohsx5RcdhPAcXFxWXqfeffdd83HcXR0TPdHHA8OUW1nZ2c6ePBguu1/8MEHFnXOnj2bZtlmzZpZvL/9+uuvmT6P1ISFhVkMBV+rVq0M5469dOmSRcLzo48+SlHmwoULFud08uTJHMWZHSdOnLCIYfv27Zmu++Br+oUXXki3/Jw5c1LUqVatWrrvsUePHrUov3jx4jTLZuX912QymV588UVzu2XKlEl3OOMH3zPs7e3Tfc9OEhcXZzGvtbOzs+nYsWNZijO5pUuXmtsqVapUpodgTk9efh947733LK7b+++/n+N4H1S1alWLhDgAAAAAFCU2AgAARcrChQvl6upqse3EiRMaO3asGjVqpGLFiql169YaPXq01qxZk6khHpMEBwdr1apV5vXXXntNXbp0ybDe3LlzZW9vL0kKCgrSli1bMnW8jh07qk+fPumWee2119SsWTPz+sqVK83DhT7IyckpU8eVpGLFimn8+PHm9d9++02JiYmZrj9jxgy5ubllunxWYnv99ddVpUoV8/rWrVszXTcvLFiwwLxctmxZTZ48Od3yFStW1MSJE83rt2/f1o8//pipY3Xu3FkvvPBCumX69u1rMSRr8iFPCxIfHx+L9dDQ0Gy3FRwcbF5+5JFHst1ObrC3t5etrW2my3/yySfm5ys2NlY7d+7MdN3BgwerRYsW6ZYZPny4xfqRI0dSLbdnzx6LfW+++aaefvrpTMeSmq+//lphYWHm9aVLl6pYsWLp1qlYsaI+/PBD8/qSJUtSvPckf74l6zznx48ft1ivV69ettqxs7PTl19+mW6ZV199NcWw+dOnT0/3PbZx48aqU6eOeT2994GsvP9K0rRp08zLISEhKa5Fet544w01aNAgw3I//PCDrly5Yl6fNGmSHnvssSzFmVzye6ZKlSrmz+SctJdX3wfCw8O1aNEi8/qjjz6qSZMm5Sje1NSvX9+8fOzYsVxvHwAAAACsiQQwAABFzKOPPqodO3aocuXKqe6PiorSgQMH9OWXX+rFF19U2bJl1alTJ61bty7DtteuXWsxb6ivr2+mYipXrpyeeOIJ8/rvv/+eqXoPJm7SMnToUPPyrVu3dODAgUzVy0jymCMjIzM9h6anp2ea83bmBhsbG3Xo0MG8/scff+TZsTJy8eJFnT592rw+YMCAFD9ASM3AgQMtyiWfSzQ9gwYNyrCMi4uLRYIlL+Y+zQ0lSpSwWL99+3a220qe8M6t+z+/uLm5WSRxs3I/Z+Z+qFy5ssW8wmndDz/99JN52cbGRmPHjs10HP+vvXuPrunO/z/+CnGJIIIkoiQSl8Y91WoERVXrXlSrjJZiOlS1U0Njqko77bQadekYS6mpMoxbqzGtoqPu2rjfQhpU6pJSUUTRNsj5/WFl//ZOTnJ2knOE830+1rLW3slnf/bnnPM5O8d57/f7k5f//Oc/xnZMTIxatmxp67gBAwYY2z/99JP2799v+X3ONWeL4zU3r31cqlSpAq3dbNahQwdVr1493zbBwcGqUaOGsV+xYkX16NHDZd/mgOl3331XqPE5ExERocjISGPf3XNWss7HgIAADRs2zP4AnTDPmeTkZMu6uoXhyc8Da9assdw4MXr0aI+sXR8WFmZs21nLGwAAAADuJASAAQDwQjExMUpOTtaUKVNcZoY5HA6tW7dOjz/+uB544AGlpaXl2Xbz5s3GdmRkpKKiomyPyZylazcj85FHHrHVLmfWkbsCoqGhoZb9/J4bs/vvv98jX1abmcdmd1yekPO17Ny5s63j/P391a5duzz7yYurbM9sd911l7Fd1ECHp+TMXrx06VKh+zIHuhYsWKA333xTV65cKXR/t1ph5nOpUqV077332mprZz6Yr2/Nmze3BIcK4/Lly9q7d6+x37VrV9vHhoSEWG7iyfn+qF+/vvz8/Iz9gQMH2r6xxl1OnDhhbIeEhKhEicL91zImJsZWu5CQEGO7WbNmtq6x5qC0u68DhZmz5cuXt5X9m5WVpa1btxr7nTp1yhX0LyjzNeKXX35Rjx49lJKSUuj+PPl5wNx3yZIl1bNnz8IN0gXzjQcZGRmWoDMAAAAA3OkIAAMA4KX8/Pw0cuRIpaSkaO/evZoyZYoef/xxRUZG5iqlmW3Lli2KiYnRjz/+6PT3+/btM7YbNmxYoPGYv7w3l7XMS82aNVWpUiVbfdeoUcPS1lWmV2Zmpj7//HMNHTpUsbGxqlatmvz9/eXj42P5l7NEpt0AQp06dWy1c+bYsWN655131KNHD9WtW1eVK1dWqVKlco3NXGa5OAOchw8ftuw3bdrU9rHmQEhaWpquXr3q8hi7WYbm4OrtGgj95ZdfLPsBAQGF7utPf/qT5X09fvx4VatWTX369NGsWbN06NAhORyOQvdfWElJSRo/fry6dOmiiIgIVapUSSVLlsw1n82lZO3O5+z3hh125oM5M/i+++6z1W9+kpKSLKWb3XnNLFOmjJ555hljPy0tTY888ojq1KmjkSNHKiEhQenp6YUbuE3m16lChQqF7sfue9pcMcD83Ng9xu51YNu2bYqLi1OHDh0UFhamihUrqkSJErnmrDlAa3fORkRE2AqUnz592tKnO+Zj69atLXNw06ZNql+/vmJjY/XGG29o/fr1tq7B2Tz5ecBcVSIqKspWVYnCyHkTDgFgAAAAAN7Es6kpAADgttC0aVM1bdrUKNGYkZGhrVu3KiEhQYsXL7YEotLS0vLMJvv555+N7c8//zzPQLIrFy5ccNkmODi4QH0GBQUZX5jn1/9nn32mP//5zzp58mSB+pek3377zVY7V2t8OvPzzz9r1KhRmj9/foEDdXbH5Qnm57p06dIFCmLmDOJcuHDBZZZbQdfqlFQsgU87cgaNKleuXOi+WrRooXfeeUd//etfjZ9dvnxZy5Yt07JlyyTdfI+0b99effv2VdeuXYu8Bmh+jh8/rhEjRtgu7W1mdz4XZi5IzufDpUuXdO3aNWM/Z/Z/YZivl5LUu3fvQvfl7JoWHx+vXbt2WdYt/v777zVt2jRNmzZNPj4+atSokTp37qynn3660Gv05uXXX381tgv7WhT2WE9cBw4cOKBhw4YVqpy2u/825Jw77piPJUqU0KJFi9ShQwedPXtW0s3nJDExUYmJiZJuZtW3aNFCPXr0UP/+/fMNznvy84C5b3c89rzk/HtTkAA4AAAAANzuyAAGAOD/oICAAHXp0kWzZ89WamqqHnvsMcvv165da3whbOauTFM7X7Kay5vaYc4Qunz5stM2M2bM0GOPPeY0+FuhQgVVr15dkZGRql27tvHPzG4gsaDln9PT09WmTRvNmzcv1zlKliyp4OBg1axZ0zIu8/qxxRngND/XBS1RmjOrK6/XzVsdO3bMsl+1atUi9TdmzBh99dVXlvKqZunp6VqyZIl69eqlqKgoffnll0U6X16OHDmili1bOg3+lipVSiEhIQoLC7PMZ3MGaXHM55zZ2DkzAwvDnZn5zq6Z5cuX18aNG/XWW285nTsOh0MHDhxQfHy8GjdurF69eun06dNuG5P5BoLr16+7rd/i8O2336pVq1ZOg79ly5ZVtWrVVKtWLcucNQeh3f23wRPzUZIaN26svXv3asiQIU6D6NeuXdPmzZs1evRoRUREaMyYMZZ1fs08+XnA/Pjd9didyfnYPHlTDAAAAADcamQAAwDwf1yVKlW0dOlStWnTxvLl98qVK3Ott1quXDljndLAwMAiZSy6Ys4us8Nc3tPZF8aHDh0yMqCz2wwfPlzdunVTdHS00xKmDoej0OtaFsRLL71kKXkZGxur5557Tq1bt1ZYWJhKliyZ65gJEybob3/7m8fH5or5uS5o9lTOkqye/KL/dnPt2jXt2rXL2K9UqVKRSodne/jhh/Xwww/r4MGDWr16tTZt2qRvvvlG586ds7Q7duyYunXrpjlz5mjw4MFFPm82h8OhQYMGWcrId+7cWYMHD1ZsbKyqV6/uNFNw4MCBmj9/vtvGUVA55547bkbIeUNEWFhYoQNMeVVEKFu2rF599VXFxcXp66+/1tdff60tW7Zo165dloxmSUpISNCOHTuUmJioGjVqFGocZuYbOAp6vb6d/Pbbb3r66actQcd+/fqpf//+at68eZ7Pfdu2bbVp0yaPjMkT8zFbaGio5syZo0mTJmn16tVav369tmzZYimBLt18XuLj47V7926tWrUqV/Dak58HzI/fkzcG5Zy3nio1DQAAAADFgQAwAABQyZIl9Ze//MUSAHa2jm7VqlWNL3yfeOIJzZo1y2Njyi5RaZd5vUtzdmy26dOnGwERPz8/bdmyxeV6tbdibd0zZ85o0aJFxv5TTz2lefPmuQw8F+e6v2bm5zozM1MZGRm2y0DnfI2dvW7eauPGjZbgwwMPPODWmw0aNmyohg0batSoUUYm6IoVK/TRRx/phx9+kHQzWPvCCy+oW7duBS65npft27db1kYdO3asZb3qvBT3fA4ICJCvr6+RyeqOTNmcWbmLFy9WbGxskft1plSpUurUqZM6deok6ebNFRs3btTSpUu1ZMkSo0RxWlqaRo4caZQFLwpzeWBPrzfsSStWrND3339v7M+ePVvPPvusy+M8OWerVKli2Xdn5na2wMBA9evXT/369ZN083q8evVqLVy4UF999ZXRbu3atZo1a5aef/55y/Ge/DxgfvyeeOzZzPPW19dXQUFBHjsXAAAAANxqlIAGAACSbgaMzDIyMnK1iYqKMrYPHjzo0fGcPHnS9hfsaWlplrZ33313rjZff/21sT1gwACXwV8pd4leT1i3bp1RPtTHx0fvvvuurUDgrRibHfXq1bPs79u3z/ax+/fvN7bvuuuuApeQvpNNnTrVst+xY0ePncvHx0dNmjTRa6+9ppSUFD355JPG765evarPPvvMbecyv88qVqyo8ePH2zrudpjP5mvgzp07i9xfzuuQp6+ZZv7+/urSpYs+/vhjHThwwBLYSkhIcEtWZUREhLGdkZFxx5ZwN8/Zu+++21bwNysry7iRwhPuuusuyw0x7piPrgQHB2vAgAFas2aNPvvsM8vfoQULFuRq78nPA+b1qr/77rtc1SLcJS0tzdiuUaOG02obAAAAAHCnIgAMAAAkycgQy+asnOODDz5obCcmJuYqK+tu5iyk/Kxevdqy37x581xtzF/02gn+StbAgKeYxxUUFKTq1au7POb333/Xli1bbPWfs+RsVlZWwQboQs4y4atWrbJ13NWrV7Vhw4Y8+/Fmq1atsjxPwcHBGjRo0C05d+nSpTVz5kxLGWZz+XEzc8lXu/PGPJ+joqJUpkwZl8ecOXPmlgZH89KmTRtje8eOHTpx4kSR+gsODrYElT///PMi9VdYderU0dixY43969ev68iRI0Xu1xykk+SWPotDYf427Ny508h+9QQfHx+1bt3a2F+9enWBS+wXRc+ePdW9e3dj39k1wpOfB8zvxRs3bighIcFtfZsdPnzY2G7cuLFHzgEAAAAAxYUAMAAAkCRL2VZJTtcjffzxx42g0I0bNzRp0iSPjunDDz+01W7OnDnGdpUqVdSqVatcbbKzbKXcwW5nMjMzNXPmTFvnLwrzuH7//Xdbx8ybN892dnTOtSSdZXYXRUREhCXINX/+fFuBinnz5lkyBrt16+bWcd2u9u/fr/79+1te97i4uFua/RwYGGjJCM25Vmw289yxO28K+j6TpH/84x+W44pL3759je2srCy99957bu3ziy++KLZAd85s5Lxe84K47777LPvmjP47SWHm7LRp0zw0mv/PPHcyMjL0wQcfePycZuY542y+ePLzQMeOHS0Z0JMnT9aNGzfc1r9083VPSkoy9nPOZwAAAAC40xEABgDAi6xYsUJTpkyxrC1qx88//6yJEydafuYsIFerVi1jvUBJmjJliu0s3WwOh0OZmZm22q5du1affPJJvm3mzp2rxMREY3/AgAFOsw7DwsKM7S+++MLluePi4jxa4jObeVwZGRnavHlzvu1TU1M1ZswY2/3XqlXLsm/+wttdhg8fbmz/+OOPLsv+njp1ytKmcuXKlmCHN8rMzNSMGTPUokULXbhwwfh5165d9dJLLxW5/4LM1bS0NEu2Xs454uzndueNeT4nJSW5HNf27dvdEmh1h5YtW1rW6J0xY4a+/PLLIvU5YsQIVaxYUdLNoHK/fv0KfBOGs6DkmTNnbN8wIuUuzR4eHl6gMThTtWpVy80f27dvL3KfxcE8Zzdt2uQyszchIcGybrun9OnTxzK21157Tbt37y50f8ePHy9Qe/OccXaN8OTnAX9/fw0bNszY37Nnj1599dUC9e1KcnKy5Sakdu3aubV/AAAAAChuBIABAPAi6enpGjVqlGrVqqUxY8bYCtp8++23at26tU6dOmX87MEHH8yzJG98fLxCQ0Ml3Swl2r17d02ePNll5tTp06c1ffp0RUVF2foSO3v9wYEDB2rFihVO2yxatMjyJXHlypX1yiuvOG1rXmN13bp1evvtt522u3Llil544QW9//77ttbiLar27dtbSu0OHjw4z6DZ1q1b1aZNG128eNH22AICAixrNcbHx7t9vdUhQ4ZYAkGTJ0/WG2+84TRjKyUlRR07drQEIN9++22VLVvWrWO6HZw7d06rVq3SK6+8ovDwcI0YMcJyc0ZMTIyWLFnilnUn69atq6eeekrr16/Pt1zz+fPn9dRTTxltfHx81KNHD6dtzdeAJUuWaN26dS7HYX6fZQc88yoN+9///lePPPKIrl27dkvea3bMnDnTuIEkKytLvXr10j//+c98sw937dqlJ554wmnJ6EqVKmn69OnG/oEDBxQTE+OyhLvD4dCOHTs0YsQISyngbKtXr1atWrX097//3WWQfcOGDZbrXWxsrEJCQvI9xq4uXboY2+vXr3dLn7eaec5evHhRAwYMcFrFwOFw6F//+pexhran56yvr69mzZpllGu/evWq2rdvr8WLF+d5jMPh0IYNG/Twww/n+t2ECRMUHR2tjz76KN8KEg6HQ1OnTtWaNWuMn/Xs2dNpW09+Hhg7dqzq1q1r7L/77rsaOnRovmM/efKkXn75ZS1btizf80vW+RoQEKCWLVu6PAYAAAAA7iS+rpsAAIA7zdmzZxUfH6/4+HiFh4crJiZGDRs2VNWqVeXv769ffvlFR48e1caNG7V3717LsdWqVdPs2bPz7LtatWr69NNP1alTJ126dEmZmZkaPXq0Jk6cqI4dOyo6OlqVK1fWjRs3dPHiRR0+fFi7d+/Wnj17ClTmtVWrVvL19dX69evVs2dPtW3bVp07d1ZQUJB++uknffHFF/rmm2+M9j4+PpoxY4altK3ZyJEjNXv2bOOL6VdffVXLli1Tr169VLNmTV29elVJSUlavny5zp49K0l66623LGtnekJwcLCGDBmiWbNmSZKOHj2qhg0bqk+fPmrevLnKli2r06dPa+3atcaauTVq1FD37t1tl6gePHiw4uLiJN3Myqxdu7Zq1qypwMBAy1qwOeeCXWXKlNG///1vtWnTxsioev3117Vw4UI98cQTioiI0JUrV5SYmKiEhARLcKBnz54aOnRooc57O2jXrp0lgO9wOHT58mVdvHgxz0z3kiVLavjw4YqPj3db4Pv69etauHChFi5cqJCQELVs2VLR0dEKDg6Wn5+fzp8/r7179yohIcGS4Ths2LBc5YGzDRo0SLNmzZLD4dCVK1f00EMPqUqVKgoNDbUErefMmWOUT73nnnvUsWNHI3iUmJioevXqqW/fvmratKl8fX118uRJrVy5Ujt37pQkRUdHq27duraCNp7WtGlTzZw5U3/84x+VlZWlzMxMvfDCC5o0aZK6d++uevXqqWLFirp48aKSk5O1ceNGpaSkSFKeJXAHDBigpKQk4/cpKSl64IEHFB0drfbt2ysyMlLly5fX5cuXlZ6ergMHDigxMVE//vijpNzlm7OdOXNG48aN07hx49SkSRPFxMSoXr16qly5shwOh06dOqUNGzZY1touWbKkJk+e7Lbnq3fv3sbjSk5O1okTJyxZq3eCRx99VA0aNDDWuV2xYoXq1q2rvn37qn79+srKylJqaqpWrFih5ORkSVKnTp105coVlxUbiqpTp056/fXXNWHCBEk3q0T069dPr7/+urp27arIyEiVK1dO58+fV1JSktatW5fv2tX79u3TkCFD9NxzzykmJkbNmzdXWFiYKlWqpN9++01Hjx7VypUrjccpSdWrVzf+fuTkyc8D5cuX19KlS9W+fXujasLs2bO1ZMkSdenSRc2aNVOVKlV09epVpaamKjExUd98840cDofmzp3r8rk1B7gfffRRy3UcAAAAALyCAwAAeI2FCxc6JBX63z333ONISUmxda5Dhw456tWrV6jzbN++3WmfAwcONNq0bdvWcfr0aUfDhg1d9leiRAnH9OnTXY558eLFDl9fX1tjHDZsmMPhcFh+Nnfu3Dz7Dg8PN9pNmDDB1nOY7cqVK46YmBhb46pevbpj165djgkTJhg/Cw8Pz7f/a9euOTp37uyy75xyvh6ubNu2zVG1alXb86Bv376OzMzMfPucO3duvmPMS0HHXph+C/qvQoUKjiFDhjgOHjxYoHPamVuFGU///v1dPv9vvvmmw8fHJ99+1q9fbznmzJkzjtq1a9saQ1RUlCM1NdX261WQeW/Wtm1b47iBAwe6bP/pp586/P39C/R8pqam5tvnjBkzHKVLly7w69SgQYNcfeV8X9j55+fn5/jkk09sP2d2mf8OTJ061dYx5nHld101K+hr6HDYny/JycmOoKAgW89jbGys4/z587bH445r0fTp0x2lSpUq0Oud3zjs/gsLC3McOnTI5fg88XnA3HdkZGSB+nQ1py5duuQoU6aM0f6rr75y+RgBAAAA4E5ze9RaAwAAbvGHP/xBqampmjp1qjp37qxKlSq5PKZEiRJq166dPv74Y+3cuVP16tWzda769esrKSlJH3zwgRo0aOCyfYMGDTRq1Cjt2bNHzZs3t3WOatWqadu2bXr++edVvnx5p23uuecebdq0SSNGjHDZ35NPPqn169fr3nvvzbNNo0aNtGzZMtvZte5Qrlw5bdiwQaNHj1a5cuWctvH399egQYO0f/9+NWvWrED9+/r6auXKlfrkk0/Up08f1a1bVxUqVLBk/7rD/fffr5SUFL344ovGuqfONGnSRMuXL9eiRYtUqlQpt46huJUoUUJ+fn4KDQ1VdHS0evfurQkTJuh///uf0tPTNWfOHFvvl4JauHCh+vXrZ6u0b4sWLbR8+XItWLDA5fM/btw4JSYmaujQoWratKkqVarkMlMuJCREO3bs0ODBg/PsPzAwUCNHjtSuXbvyXIO4OD322GM6evSohg8fnu911MfHR9HR0Zo6daqqV6+eb5/Dhw83+gwMDMy3rZ+fnzp06KAZM2Y4zTLt1KmTJk6cqDZt2rjMIi9XrpwGDBigQ4cOqXfv3vm2LYxnn33W2L4Va+N6QnYp4l69euV5XQwNDdWbb76pTZs2uXz93G3EiBFKTk5W//798/wbId3M8G7VqpU+/PDDXL8bOXKkXn75ZTVu3Nhl+erQ0FCNGzdOBw8eVP369V2Oz5OfB+rXr6+DBw9q0qRJLrPLw8LC9PLLL1vKejuzfPlyYw3tyMhIPfTQQy7HDAAAAAB3Gh+HowC1GAEAwB0lKytL33//vY4cOaITJ04YJRrLly+vgIAA1atXT02aNFGFChWKfK60tDQlJibqp59+0oULF1S6dGkFBgaqdu3aatSoUZ6lmc2eeeYZzZs3T5LUtm1bS+nSy5cva8OGDTp58qQyMjJUrVo1NW/e3LL2bEEcPHhQ27Zt09mzZ1WmTBmFhoaqSZMmHgnOFcSlS5e0efNmHTlyRFevXlVQUJBq1Kihtm3b5vvF/+3m2rVr2rp1q44ePapz586pbNmyCgkJUWxs7G0Z8PMmqampSk5O1vHjx5WRkaEbN26oYsWKCg8P13333ecyUOlO586d06ZNm/TDDz8oMzNTwcHBCg8PV5s2be6Y4P/169e1bds2HT58WOnp6bp+/boCAgIUGRmpZs2aFWo93aysLO3evVvJyck6d+6crly5ovLlyyskJER33323GjZsaKxF7EpmZqaSkpJ05MgRnT59WpcvXzauv/Xr11ezZs08eu3IyMhQjRo1jPLve/fuVdOmTT12Pk9LS0vT5s2bderUKWVlZSkkJES1a9dWy5Ytb4u1qn///Xdt3bpVqampSk9Pl3Rzrek6dero3nvvtRWcvnTpkvbt26djx44pPT1dv/76q/z9/RUUFKQmTZqoUaNGRVqb3B2fB/Jy6NAh7dmzR2fPnjXeNzVr1lSTJk0sawbnp3Xr1tq6dask6f3339eLL75Y6PEAAAAAwO2KADAAALht5BcABgDcnuLi4oy1gJ999tl815EHitP+/fuNGxSCgoKUmpoqf3//Yh4VAAAAALhf8d/CDAAAAAC4Y40ZM8aoJDF//nydPn26mEcEODdx4kRj+5VXXiH4CwAAAMBrEQAGAAAAABRalSpVFBcXJ+lmieL33nuvmEcE5Hb06FEtXbpUkhQeHq7nnnuumEcEAAAAAJ5DABgAAAAAUCSjR49WZGSkJGnGjBk6fvx4MY8IsBo7dqxu3LghSZo2bZrKli1bzCMCAAAAAM/xLe4BAAAAAADubGXLltWCBQu0Zs0aSVJqaqrCw8OLeVTATb/++qsaNWqkBg0aKDAwUD179izuIQEAAACARxEABgAAAAAUWWxsrGJjY4t7GEAufn5+Gj9+fHEPAwAAAABuGUpAAwAAAAAAAAAAAICX8HE4HI7iHgQAAAAAAAAAAAAAoOjIAAYAAAAAAAAAAAAAL0EAGAAAAAAAAAAAAAC8BAFgAAAAAAAAAAAAAPASBIABAAAAAAAAAAAAwEsQAAYAAAAAAAAAAAAAL0EAGAAAAAAAAAAAAAC8BAFgAAAAAAAAAAAAAPASBIABAAAAAAAAAAAAwEsQAAYAAAAAAAAAAAAAL0EAGAAAAAAAAAAAAAC8BAFgAAAAAAAAAAAAAPASBIABAAAAAAAAAAAAwEsQAAYAAAAAAAAAAAAAL0EAGAAAAAAAAAAAAAC8BAFgAAAAAAAAAAAAAPASBIABAAAAAAAAAAAAwEsQAAYAAAAAAAAAAAAAL0EAGAAAAAAAAAAAAAC8BAFgAAAAAAAAAAAAAPASBIABAAAAAAAAAAAAwEsQAAYAAAAAAAAAAAAAL0EAGAAAAAAAAAAAAAC8BAFgAAAAAAAAAAAAAPASBIABAAAAAAAAAAAAwEsQAAYAAAAAAAAAAAAAL0EAGAAAAAAAAAAAAAC8BAFgAAAAAAAAAAAAAPASBIABAAAAAAAAAAAAwEsQAAYAAAAAAAAAAAAAL0EAGAAAAAAAAAAAAAC8BAFgAAAAAAAAAAAAAPASBIABAAAAAAAAAAAAwEsQAAYAAAAAAAAAAAAAL/H/ACQEKLtNRa8JAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<IPython.core.display.Image object>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {
+      "image/png": {
+       "width": 600
+      }
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Image(plot_dict['sourceObjectTable_g_astromColorDiffMetrics_HistPlot'], width=600)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "774b7f8e-a0a6-4718-85b0-a9ce7f2e0d30",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-11T23:48:30.665690Z",
+     "iopub.status.busy": "2024-10-11T23:48:30.665570Z",
+     "iopub.status.idle": "2024-10-11T23:48:30.669627Z",
+     "shell.execute_reply": "2024-10-11T23:48:30.669288Z",
+     "shell.execute_reply.started": "2024-10-11T23:48:30.665679Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<IPython.core.display.Image object>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {
+      "image/png": {
+       "width": 600
+      }
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Image(plot_dict['sourceObjectTable_i_astromColorDiffMetrics_HistPlot'], width=600)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "893cc79e-a815-4998-9ae0-9cca8a381055",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-11T23:48:30.670255Z",
+     "iopub.status.busy": "2024-10-11T23:48:30.670134Z",
+     "iopub.status.idle": "2024-10-11T23:48:30.674145Z",
+     "shell.execute_reply": "2024-10-11T23:48:30.673798Z",
+     "shell.execute_reply.started": "2024-10-11T23:48:30.670245Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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p2bJlYVbvggULcumll67Qmih+nTp1KgRqb7/9dtZbb71svvnmOfnkk9O7d++88847S1xufM6cOTnllFOSJDfddFMuueSSdOzYsbDE8brrrpv77rsv++67b6ZMmZKrrrqqynFmzJiRbbfdNn379k379u2TJA0bNky3bt1yww03JEkefPDBvP7665X6/fjHP06fPn2y1157pW3btoUwu2XLlvntb39bmKFZ8YWH6qy//vp56KGHst566xWOVXzZIknOP//8/PnPf86mm26axo0bJ1k4C3eDDTbIXXfdlb333jvTp09fIaHf559/nmuuuSbJwoD9wgsvTPPmzZMkLVq0yF/+8pfCTNOrrroqX375ZZXjTJw4MTfffHNOO+20NG3aNEnSqlWr9OrVK1tssUWSFALNCi+//HKSZJdddsmZZ55Z6c+SVq1aZbfddsttt92W1VZbreZu+BvU+02NHDkyJ5xwQiFY/vnPf17tl3/uv//+TJkyJWuttVa23377wvGDDz44ZWVlGTJkSF599dUarQ8AAAAAgB82AfC3YObMmXnkkUeSLAzSFl2K9qsqZkgmSb9+/RY7v+ixRdt+1W677VZYrvnhhx/OzJkzV1hN/DD07Nkz5513Xho3bpzy8vIMHjw4PXv2zPHHH5+NNtooq6yySk4//fSMHj16sb6PP/54Pv/887Rt2zZdu3at9hoVMyQrZlZW5dxzz61ymeauXbtm9dVXT5L07dt3me5t7733TrJwf+LqgtEk+cMf/pA6deos09hVXefFF2t+2e4HHngg8+bNS8OGDXP22WdX2ebcc89NgwYNMnfu3Nx///1Vtmnfvn2lmaqL2nfffZNksVUFKoLmsWPHLnEp5BVheepdVqusskrh0bhx43Ts2LEw83u99dZLz549q+1b8eWCo446qtLxlVZaKQcccEClNgAAAAAAUBMEwN+CN954I9OnT0+S7LTTToXZh1XZeeedC88HDhy42PlFj/3sZz+rdpySkpLC+WnTpuW///3vCquJH4a6devmwgsvzOeff54777wzv/rVr7LJJpsUlvUdM2ZM/va3v2XDDTfMa6+9VqlvReA5ceLErLrqqpUCtUUfv/71r5MkI0aMqLaGHXbYocpzpaWl6dKlS5KFn++vmjp1aq644orsuOOOadOmTerXr1+YgdyoUaNCu88//7za12C77bar9lyFt956KyeddFI23njjNG3aNKWlpYXrnHTSSUkW7qNc0yrueauttirMhP2qFi1aZMstt6zU/qu22mqravdBrpjBO2HChErHd9lllzRs2DCDBw/ODjvskH/84x/55JNPlus+ltXy1LusRo8eXXjMmDGjcPzoo4/O4MGD065duyr7DRs2LM8//3xKSkoWC4CT/78MdN++fSuNCwAAAAAA34QAeBkMHTo02267bVq0aJH69eunbdu26dKlSy666KLCnrxVGTJkSOH5BhtssMRrdOjQIU2aNEmSvPvuu9WO1aRJk3To0GGJY62//vqF518dqyZr4oelWbNm+eUvf5levXrlzTffzOTJk/Ovf/0rP//5z5Mk48aNy4EHHphZs2YV+lTseTtnzpxKYdpXHxMnTkySxWasV2jdunUaNGhQbW0VQdxXfx8/+OCDrL/++jnzzDPz/PPPZ+zYsalXr15WXnnltG3bNm3bti20rfhiRFXatGmzpJcm119/fTbffPPceOONefvttzNt2rQ0a9ascI2KYHZJ11heFfdcXRhZoWKWdHV/Zq20UvX7StetWzdJMnfu3ErH11xzzfz9739PkyZN8sorr+RXv/pV1lxzzbRp0yaHHnpo/vnPfy5xifBvYnnqXVbl5eUpLy/PggUL8sUXX+Smm25K8+bNc8cddxSW269KxVLf2223XdZcc83Fzu+yyy5p165dpk6danUFAAAAAABqjAB4GYwePTqvvPJKJk2alLlz52bMmDF57rnnct5556VTp0655ZZbquy36GzGrwttkxT2Nv3yyy8rBRezZ88uLK+7NOMs2uarMyprqqblNWbMmAwZMmSZHsOGDfvG16XmNWzYMLvsskseeuihwozGzz77LE888UShTcWywHvssUchTPu6R1WWNFN9Sbp27ZrPPvssnTp1Sr9+/TJ+/PhMnz49Y8aMyahRoyrN+l1SULmk5Z/fe++9nHrqqVmwYEEOPvjgvPbaa5k1a1YmTpyYUaNGZdSoUYW9jVdUGJos/Wu0vK9ldY488siMGDEiN910Uw499NC0b98+Y8eOzX333Zf9998/O+64Y6ZMmVKj1/y2lZSUZNVVV023bt3y4IMPpqSkJGeddVZhL+BFzZ8/P7fffnuShTPgK2aBL/qoU6dO4bNnGWgAAAAAAGpK3dou4PugXr162WOPPbLbbrtlo402SqtWrTJr1qy89957uffee/PUU09l5syZ6datW6ZPn57TTjutUv+pU6cWni9ptlpVbaZOnZqWLVvWyDgroqbl1bNnz1xwwQXfaAy+e0444YRC6PX+++8Xjq+yyipJkrfffvsbjT927NjMnj272lnAFWHaojN1P/3007z88stJknvuuSfbbLPNYv1GjRr1jepKkvvvvz/z589P586d07dv3yqXJa6J61Sn4p4//fTTJbarWH565ZVXrvEaWrZsmW7duqVbt25JFu6p/Pe//z2XXXZZXnjhhfTo0aMQgn/fdenSJUcddVTuuOOOnHLKKXn77bcrfUHg8ccfL8x8XxovvPBCPvzww6yzzjorolyAWjNz+tS8O+DKhT/MW5BGH03Myuttm7r1Fm4h0fTn+6S0YcNarBAAAACg+AiAl8Jrr72WFi1aLHb8Jz/5SY477rjcfffdOfroozN//vyceeaZ2WuvvbLuuusW2i26nG3FfqlLsmi4NWPGjELY+k3HWVRN1VTMvhw/9esb1bLvWo0VS4UnlT8z2223Xa655pp8/vnnefHFF7P99tsv1/jz5s3Liy++WGlf6grl5eV5/vnnk6Swz21SORDdbLPNqhz36aefXq56FlVxnU022aTaPWmXdJ2KPss7O3jLLbfMnXfemTfeeCOTJ09Os2bNFmszadKkSnsFr2hrrbVWLrnkknz66afp06dP/vWvf63wa36b/vSnP6VPnz557733cvvtt+e4444rnKuY0XvAAQfkjjvuWOI4O+64YwYNGpTevXvnkksuWaE1A3zb5syYlh+NeSBJsmBunUz+YIPM+OCRwvmVdt8tEQADAAAA1CgB8FKoKvxd1BFHHJH33nsvF110UebNm5drr702N9xwQ+F8WVlZ4fmcOXO+9nqzZ88uPG/UqFGNj1PTYxWri+96sbZL+M745JNPMnfu3PzoRz9aYruK2b9Jsvnmmxee//znP8+qq66aL7/8Mr/73e/ywgsvLPFzNGHChGq/ZPCXv/wlO+2002Ih6+23356RI0cmSQ499NDC8UWD0Lfeeitbb711pX5Tp07NRRddtMT7WhoV13n77bdTXl6+2BLLjz/+eAYOHFht/4r9gSdNmrRc1z/wwANzxhlnZNasWbnsssty8cUXL9bm4osvzuzZs1OvXr0ceOCBy3WdqixpVnby//+8WdIS2t9Ha621Vg499NDcfffd+fOf/5yjjjoq9erVy+jRo/PIIwvDjUMPPbTSFyOqcvDBB2fQoEG5/fbbc9FFFxXd6wQAAAAAwLfLHsA15KSTTio8f+aZZyqdW9JSzFWZNm1alX1rapyaHmt5nHTSSXnnnXeW6TFgwIBvfF2Wz5AhQ9K5c+fsvffeueOOOzJ8+PDCublz52bw4MHp2rVrYXnfrbfeutIs34YNG6Znz54pKSnJoEGDst122+XJJ5+s9OWDTz75JDfffHO23nrr9OzZs8o6GjVqlBdffDFHHHFEYSnjWbNmpVevXjnxxBOTJPvtt1+lkHf99dcv7HN93HHH5b///W/h3CuvvJIuXbpk4sSJ3/AVWri/cbLwtTr55JMzYcKEJMn06dNz880356CDDkqrVq2q7b/hhhsmWbgU8NChQ5f5+u3atcvvfve7JMmll16a888/vxAmT5o0Keedd16uuOKKJMnpp5+eVVdddZmvUZ1TTjklhxxySB544IGMGTOmcHzatGm56aabCjNg99prrxq75nfFH//4x5SUlGT48OGFWb933HFH5s2bl7Kysuyzzz5fO8YhhxySZOEe648//vgKrRcAAAAAgOJnBnANWXXVVdO6deuMGzeuEExVqAifkhRmKC5JRZtVVlkl9erVKxxv0KBB2rRpkzFjxnztPp9JMmLEiCprqMmallebNm0q7dPKd1u9evWyYMGCPPbYY3nssceSLFw6vEmTJpk4cWKlZYs333zzPPjgg4vN0N1///1z55135oQTTsibb76ZPfbYI3Xr1k2zZs0ybdq0SrPM99tvvyrrWHnllfOHP/wh3bt3z7333psWLVpk2rRpmTt3bpKFyy9XhHAVSkpKcsMNN+SAAw7IkCFDsuWWWxZmH8+YMSONGjXKQw89lF122eUbvUY777xzDjvssPTt2zc33nhjbrzxxjRv3jxTp07N/Pnzs8UWW+TYY49N9+7dq+x/4IEH5pxzzsnYsWPTuXPntG7dOo0bN06S9O3bt8q9i7/q4osvzqeffpr77rsvF154YS666KI0a9YskydPzoIFC5Ikhx9+eP785z9/o3v9qrlz56Zfv37p169fkoVLgdetW7fSbObtt98+//d//1ej1/0u2HDDDbPvvvvmn//8Z/7yl7+ka9eu6d27d5KFgXfFe7gka665ZjbffPMMGjQo//jHP5YqNAYAAAAAgOqYAVyDvrrka4WKmX3JwtmBSzJy5MjCbNsNNtig2rGmTp36tcHtu+++W3j+1bFqsiaK3+67754PP/ww11xzTQ4++OB07tw5DRo0yKRJk9KoUaOss846OeSQQ9K3b9+8/vrrWW211aoc58gjj8ywYcNy7rnnZsstt0yTJk0yadKkNGzYMJtuuml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+      "text/plain": [
+       "<IPython.core.display.Image object>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {
+      "image/png": {
+       "width": 600
+      }
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Image(plot_dict['sourceObjectTable_z_astromColorDiffMetrics_HistPlot'], width=600)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7e366484-df4a-47f4-8e20-a73580a3f560",
+   "metadata": {},
+   "source": [
+    "### Thresholds\n",
+    "\n",
+    "To demonstrate that the AB2 threshold is applied, we inspect the relevant lines of `analysis_tools` [code that sets the AB2 threshold](https://github.com/lsst/analysis_tools/blob/6903dfedeb0232d1cc74fffcbea35eeab1598c08/python/lsst/analysis/tools/atools/refCatMatchPlots.py#L654-L660). We see the following, indicating that the threshold is being applied as required:\n",
+    "```\n",
+    "    AB2 = Field[float](\n",
+    "        doc=(\n",
+    "            \"Separation in milliarcseconds used to calculate the ABF1 metric. ABF1 is the percentage of\"\n",
+    "            \" sources whose distance from the reference is greater than AB2 mas from the mean.\"\n",
+    "        ),\n",
+    "        default=20,\n",
+    "    )\n",
+    "\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "61eaafa4-c290-4b74-9628-2f967816034d",
+   "metadata": {},
+   "source": [
+    "## Results\n",
+    "We have demonstrated that there is software within the Rubin Science Pipelines to calculate `AB1`, the maximum astrometric separations measured relative to the r-band positions, and`ABF1` the percentage of separations relative to r-band that exceed the outlier threshold `AB2`. Additionally we have shown the metrics and plots that are produced by `analysis_tools` each time the DRP pipeline is executed. Thus the result of this test is a \"**Pass**\"."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "27289b57-353a-47f1-b5a6-f54eac1afb93",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "LSST",
+   "language": "python",
+   "name": "lsst"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}