From 42068b5d1f9bc5c07214a4d787bb406c85e74d1e Mon Sep 17 00:00:00 2001
From: rdingjin <rebekah.dingjin26@imperial.ac.uk>
Date: Tue, 26 May 2026 15:22:34 +0000
Subject: [PATCH] Delete 12.11H05_ChRmine_Red_ATR.ipynb

---
 12.11H05_ChRmine_Red_ATR.ipynb | 1028 --------------------------------
 1 file changed, 1028 deletions(-)
 delete mode 100644 12.11H05_ChRmine_Red_ATR.ipynb

diff --git a/12.11H05_ChRmine_Red_ATR.ipynb b/12.11H05_ChRmine_Red_ATR.ipynb
deleted file mode 100644
index ebfcdc2..0000000
--- a/12.11H05_ChRmine_Red_ATR.ipynb
+++ /dev/null
@@ -1,1028 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "082de01c-5271-479e-a491-c6849725dd1e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#Phase 7 ATR (11H05) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "272d85eb-2a89-4002-9dd5-b4cf35bfecd7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import ethoscopy as etho\n",
-    "import pandas as pd\n",
-    "from scipy.stats import mannwhitneyu\n",
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "import seaborn as sns\n",
-    "from scipy.stats import wilcoxon, shapiro, ttest_rel"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "bf4d6257-9a9c-44ab-8788-868423d472f9",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'2.1.0'"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "etho.__version__"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "id": "43fdfbf9-d164-4708-9943-8b0f89f9341f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "meta = '/home/rdingjin/UASxGal4_ATR_2026-05-10/metadata_phase7_11H_pulse.csv' \n",
-    "local = '/mnt/ethoscope_results'"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "id": "134f43e0-0b2c-4adb-b1c5-eb03dabe56d7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "metadata = etho.link_meta_index(meta, local)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "id": "15ade560-4ff5-4355-a634-649b23cf98c7",
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Loading ROI_1 from ETHOSCOPE_224\n",
-      "Loading ROI_2 from ETHOSCOPE_224\n",
-      "Loading ROI_3 from ETHOSCOPE_224\n",
-      "Loading ROI_4 from ETHOSCOPE_224\n",
-      "Loading ROI_5 from ETHOSCOPE_224\n",
-      "Loading ROI_6 from ETHOSCOPE_224\n",
-      "Loading ROI_7 from ETHOSCOPE_224\n",
-      "Loading ROI_8 from ETHOSCOPE_224\n",
-      "Loading ROI_9 from ETHOSCOPE_224\n",
-      "Loading ROI_10 from ETHOSCOPE_224\n",
-      "Loading ROI_11 from ETHOSCOPE_224\n",
-      "Loading ROI_12 from ETHOSCOPE_224\n",
-      "Loading ROI_13 from ETHOSCOPE_224\n",
-      "Loading ROI_14 from ETHOSCOPE_224\n",
-      "Loading ROI_15 from ETHOSCOPE_224\n",
-      "Loading ROI_16 from ETHOSCOPE_224\n",
-      "Loading ROI_17 from ETHOSCOPE_224\n",
-      "Loading ROI_18 from ETHOSCOPE_224\n",
-      "Loading ROI_19 from ETHOSCOPE_224\n",
-      "Loading ROI_20 from ETHOSCOPE_224\n",
-      "Loading ROI_1 from ETHOSCOPE_265\n",
-      "Loading ROI_2 from ETHOSCOPE_265\n",
-      "Loading ROI_3 from ETHOSCOPE_265\n",
-      "Loading ROI_4 from ETHOSCOPE_265\n",
-      "Loading ROI_5 from ETHOSCOPE_265\n",
-      "Loading ROI_6 from ETHOSCOPE_265\n",
-      "Loading ROI_7 from ETHOSCOPE_265\n",
-      "Loading ROI_8 from ETHOSCOPE_265\n",
-      "Loading ROI_9 from ETHOSCOPE_265\n",
-      "Loading ROI_10 from ETHOSCOPE_265\n",
-      "Loading ROI_11 from ETHOSCOPE_265\n",
-      "Loading ROI_12 from ETHOSCOPE_265\n",
-      "Loading ROI_13 from ETHOSCOPE_265\n",
-      "Loading ROI_14 from ETHOSCOPE_265\n",
-      "Loading ROI_15 from ETHOSCOPE_265\n",
-      "Loading ROI_16 from ETHOSCOPE_265\n",
-      "Loading ROI_17 from ETHOSCOPE_265\n",
-      "Loading ROI_18 from ETHOSCOPE_265\n",
-      "Loading ROI_19 from ETHOSCOPE_265\n",
-      "Loading ROI_20 from ETHOSCOPE_265\n"
-     ]
-    }
-   ],
-   "source": [
-    "data = etho.load_ethoscope(metadata, reference_hour = 9.0, FUN = etho.sleep_annotation)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "id": "fe07151b-0b01-4695-8c00-4ca3120f5735",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = etho.behavpy(data, metadata, check = True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "id": "50c5c0bc-5eb9-4c34-9d0a-7ee9429df571",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df.to_pickle('/home/rdingjin/UASxGal4_2026-05-05/phase7(11H)1.pkl')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "id": "94ee2ec0-407d-4dea-b746-98ca9ca1186e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import ethoscopy as etho\n",
-    "import pandas as pd\n",
-    "from scipy.stats import mannwhitneyu\n",
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "import seaborn as sns\n",
-    "from scipy.stats import wilcoxon, shapiro, ttest_rel\n",
-    "df = pd.read_pickle('/home/rdingjin/UASxGal4_2026-05-05/phase7(11H)1.pkl')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "id": "e02f49df-5062-497d-a068-5b25269bab1a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = df.baseline(column = 'baseline')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 49,
-   "id": "e469178c-93d4-4182-9d4f-6a58403eb0f8",
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      " ==== METADATA ====\n",
-      "\n",
-      "                                     date   machine_name  region_id  \\\n",
-      "id                                                                    \n",
-      "2026-05-11_13-46-01_22485e|01  2026-05-11  ETHOSCOPE_224          1   \n",
-      "2026-05-11_13-46-01_22485e|02  2026-05-11  ETHOSCOPE_224          2   \n",
-      "2026-05-11_13-46-01_22485e|03  2026-05-11  ETHOSCOPE_224          3   \n",
-      "2026-05-11_13-46-01_22485e|04  2026-05-11  ETHOSCOPE_224          4   \n",
-      "2026-05-11_13-46-01_22485e|05  2026-05-11  ETHOSCOPE_224          5   \n",
-      "2026-05-11_13-46-01_22485e|06  2026-05-11  ETHOSCOPE_224          6   \n",
-      "2026-05-11_13-46-01_22485e|07  2026-05-11  ETHOSCOPE_224          7   \n",
-      "2026-05-11_13-46-01_22485e|08  2026-05-11  ETHOSCOPE_224          8   \n",
-      "2026-05-11_13-46-01_22485e|09  2026-05-11  ETHOSCOPE_224          9   \n",
-      "2026-05-11_13-46-01_22485e|10  2026-05-11  ETHOSCOPE_224         10   \n",
-      "2026-05-11_13-46-01_22485e|11  2026-05-11  ETHOSCOPE_224         11   \n",
-      "2026-05-11_13-46-01_22485e|12  2026-05-11  ETHOSCOPE_224         12   \n",
-      "2026-05-11_13-46-01_22485e|13  2026-05-11  ETHOSCOPE_224         13   \n",
-      "2026-05-11_13-46-01_22485e|14  2026-05-11  ETHOSCOPE_224         14   \n",
-      "2026-05-11_13-46-01_22485e|15  2026-05-11  ETHOSCOPE_224         15   \n",
-      "2026-05-11_13-46-01_22485e|16  2026-05-11  ETHOSCOPE_224         16   \n",
-      "2026-05-11_13-46-01_22485e|17  2026-05-11  ETHOSCOPE_224         17   \n",
-      "2026-05-11_13-46-01_22485e|18  2026-05-11  ETHOSCOPE_224         18   \n",
-      "2026-05-11_13-46-01_22485e|19  2026-05-11  ETHOSCOPE_224         19   \n",
-      "2026-05-11_13-46-01_22485e|20  2026-05-11  ETHOSCOPE_224         20   \n",
-      "2026-05-11_13-49-08_2650fe|01  2026-05-11  ETHOSCOPE_265          1   \n",
-      "2026-05-11_13-49-08_2650fe|02  2026-05-11  ETHOSCOPE_265          2   \n",
-      "2026-05-11_13-49-08_2650fe|03  2026-05-11  ETHOSCOPE_265          3   \n",
-      "2026-05-11_13-49-08_2650fe|04  2026-05-11  ETHOSCOPE_265          4   \n",
-      "2026-05-11_13-49-08_2650fe|05  2026-05-11  ETHOSCOPE_265          5   \n",
-      "2026-05-11_13-49-08_2650fe|06  2026-05-11  ETHOSCOPE_265          6   \n",
-      "2026-05-11_13-49-08_2650fe|07  2026-05-11  ETHOSCOPE_265          7   \n",
-      "2026-05-11_13-49-08_2650fe|08  2026-05-11  ETHOSCOPE_265          8   \n",
-      "2026-05-11_13-49-08_2650fe|09  2026-05-11  ETHOSCOPE_265          9   \n",
-      "2026-05-11_13-49-08_2650fe|10  2026-05-11  ETHOSCOPE_265         10   \n",
-      "2026-05-11_13-49-08_2650fe|11  2026-05-11  ETHOSCOPE_265         11   \n",
-      "2026-05-11_13-49-08_2650fe|12  2026-05-11  ETHOSCOPE_265         12   \n",
-      "2026-05-11_13-49-08_2650fe|13  2026-05-11  ETHOSCOPE_265         13   \n",
-      "2026-05-11_13-49-08_2650fe|14  2026-05-11  ETHOSCOPE_265         14   \n",
-      "2026-05-11_13-49-08_2650fe|15  2026-05-11  ETHOSCOPE_265         15   \n",
-      "2026-05-11_13-49-08_2650fe|16  2026-05-11  ETHOSCOPE_265         16   \n",
-      "2026-05-11_13-49-08_2650fe|17  2026-05-11  ETHOSCOPE_265         17   \n",
-      "2026-05-11_13-49-08_2650fe|18  2026-05-11  ETHOSCOPE_265         18   \n",
-      "2026-05-11_13-49-08_2650fe|19  2026-05-11  ETHOSCOPE_265         19   \n",
-      "2026-05-11_13-49-08_2650fe|20  2026-05-11  ETHOSCOPE_265         20   \n",
-      "\n",
-      "                               sleep_deprived                         species  \\\n",
-      "id                                                                              \n",
-      "2026-05-11_13-46-01_22485e|01            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|02            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|03            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|04            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|05            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|06            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|07            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|08            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|09            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|10            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|11            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|12            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|13            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|14            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|15            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|16            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|17            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|18            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|19            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-46-01_22485e|20            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|01            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|02            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|03            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|04            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|05            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|06            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|07            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|08            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|09            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|10            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|11            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|12            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|13            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|14            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|15            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|16            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|17            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|18            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|19            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "2026-05-11_13-49-08_2650fe|20            True  UAS_ChRmine_attP5 x 11H05_Gal4   \n",
-      "\n",
-      "                              food  baseline   sex      time  \n",
-      "id                                                            \n",
-      "2026-05-11_13-46-01_22485e|01  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|02  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|03  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|04  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|05  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|06  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|07  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|08  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|09  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|10  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|11  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|12  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|13  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|14  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|15  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|16  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|17  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|18  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|19  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-46-01_22485e|20  ATR         0  male  13-46-01  \n",
-      "2026-05-11_13-49-08_2650fe|01  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|02  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|03  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|04  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|05  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|06  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|07  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|08  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|09  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|10  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|11  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|12  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|13  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|14  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|15  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|16  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|17  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|18  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|19  ATR         0  male  13-49-08  \n",
-      "2026-05-11_13-49-08_2650fe|20  ATR         0  male  13-49-08  \n",
-      " ====== DATA ======\n",
-      "\n",
-      "                                    t           x          y          w  \\\n",
-      "id                                                                        \n",
-      "2026-05-11_13-46-01_22485e|01   21480  168.368421  52.631579  25.736842   \n",
-      "2026-05-11_13-46-01_22485e|01   21490   92.689655  52.068966  24.275862   \n",
-      "2026-05-11_13-46-01_22485e|01   21500   94.758621  52.034483  24.275862   \n",
-      "2026-05-11_13-46-01_22485e|01   21510  253.586207  54.172414  25.482759   \n",
-      "2026-05-11_13-46-01_22485e|01   21520  376.636364  54.151515  20.909091   \n",
-      "...                               ...         ...        ...        ...   \n",
-      "2026-05-11_13-49-08_2650fe|20  378100  203.823529  26.352941  19.235294   \n",
-      "2026-05-11_13-49-08_2650fe|20  378110  204.083333  26.388889  20.805556   \n",
-      "2026-05-11_13-49-08_2650fe|20  378120  204.756757  26.270270  21.513514   \n",
-      "2026-05-11_13-49-08_2650fe|20  378130  203.648649  25.891892  20.081081   \n",
-      "2026-05-11_13-49-08_2650fe|20  378140  202.888889  27.000000  19.222222   \n",
-      "\n",
-      "                                       h        phi  max_velocity  \\\n",
-      "id                                                                  \n",
-      "2026-05-11_13-46-01_22485e|01   7.789474  12.526316    116.112438   \n",
-      "2026-05-11_13-46-01_22485e|01   6.137931   0.000000     41.103494   \n",
-      "2026-05-11_13-46-01_22485e|01   6.344828   6.137931     41.103494   \n",
-      "2026-05-11_13-46-01_22485e|01   7.896552  52.137931     14.923777   \n",
-      "2026-05-11_13-46-01_22485e|01   9.939394  43.242424      5.295156   \n",
-      "...                                  ...        ...           ...   \n",
-      "2026-05-11_13-49-08_2650fe|20  12.470588  31.588235      1.376825   \n",
-      "2026-05-11_13-49-08_2650fe|20  12.444444  89.694444      1.949300   \n",
-      "2026-05-11_13-49-08_2650fe|20  12.351351  86.540541      1.020654   \n",
-      "2026-05-11_13-49-08_2650fe|20  12.567568  43.675676      1.323972   \n",
-      "2026-05-11_13-49-08_2650fe|20  12.444444  82.666667      1.485521   \n",
-      "\n",
-      "                               mean_velocity      dist  has_interacted  \\\n",
-      "id                                                                       \n",
-      "2026-05-11_13-46-01_22485e|01      10.280101  0.585966             0.0   \n",
-      "2026-05-11_13-46-01_22485e|01      38.628115  3.360646             0.0   \n",
-      "2026-05-11_13-46-01_22485e|01      36.959691  3.215493             0.0   \n",
-      "2026-05-11_13-46-01_22485e|01       5.729631  0.498478             0.0   \n",
-      "2026-05-11_13-46-01_22485e|01       1.136167  0.112481             0.0   \n",
-      "...                                      ...       ...             ...   \n",
-      "2026-05-11_13-49-08_2650fe|20       0.836552  0.085328             0.0   \n",
-      "2026-05-11_13-49-08_2650fe|20       0.982569  0.106117             0.0   \n",
-      "2026-05-11_13-49-08_2650fe|20       0.794445  0.088183             0.0   \n",
-      "2026-05-11_13-49-08_2650fe|20       0.915130  0.101579             0.0   \n",
-      "2026-05-11_13-49-08_2650fe|20       0.886143  0.023926             0.0   \n",
-      "\n",
-      "                               beam_cross moving  micro   walk  \\\n",
-      "id                                                               \n",
-      "2026-05-11_13-46-01_22485e|01         0.0   True  False   True   \n",
-      "2026-05-11_13-46-01_22485e|01         0.0   True  False   True   \n",
-      "2026-05-11_13-46-01_22485e|01         0.0   True  False   True   \n",
-      "2026-05-11_13-46-01_22485e|01         0.0   True  False   True   \n",
-      "2026-05-11_13-46-01_22485e|01         0.0   True  False   True   \n",
-      "...                                   ...    ...    ...    ...   \n",
-      "2026-05-11_13-49-08_2650fe|20         0.0   True   True  False   \n",
-      "2026-05-11_13-49-08_2650fe|20         0.0   True   True  False   \n",
-      "2026-05-11_13-49-08_2650fe|20         0.0   True   True  False   \n",
-      "2026-05-11_13-49-08_2650fe|20         0.0   True   True  False   \n",
-      "2026-05-11_13-49-08_2650fe|20         0.0   True   True  False   \n",
-      "\n",
-      "                               is_interpolated  asleep  \n",
-      "id                                                      \n",
-      "2026-05-11_13-46-01_22485e|01            False   False  \n",
-      "2026-05-11_13-46-01_22485e|01            False   False  \n",
-      "2026-05-11_13-46-01_22485e|01            False   False  \n",
-      "2026-05-11_13-46-01_22485e|01            False   False  \n",
-      "2026-05-11_13-46-01_22485e|01            False   False  \n",
-      "...                                        ...     ...  \n",
-      "2026-05-11_13-49-08_2650fe|20            False   False  \n",
-      "2026-05-11_13-49-08_2650fe|20            False   False  \n",
-      "2026-05-11_13-49-08_2650fe|20            False   False  \n",
-      "2026-05-11_13-49-08_2650fe|20            False   False  \n",
-      "2026-05-11_13-49-08_2650fe|20            False   False  \n",
-      "\n",
-      "[1420897 rows x 16 columns]\n"
-     ]
-    }
-   ],
-   "source": [
-    "df.display()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "id": "596ea36d-2ce7-4b10-904c-eb869eaae6ae",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#define dead and/or escaped flies\n",
-    "dead_flies = ['2026-05-11_13-46-01_22485e|06', '2026-05-11_13-46-01_22485e|11','2026-05-11_13-46-01_22485e|08','2026-05-11_13-46-01_22485e|17','2026-05-11_13-49-08_2650fe|02']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 58,
-   "id": "3e536fd1-fcae-4d5c-a8fb-b5b7ebc0be66",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/srv/venv/lib/python3.12/site-packages/ethoscopy/behavpy_core.py:1611: FutureWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
-      "  tdf.groupby(\"id\", group_keys=False).apply(\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 800x350 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "start_hour = 0\n",
-    "end_hour = 96\n",
-    "fig = df.remove('id', *dead_flies).t_filter(start_time=start_hour, end_time=end_hour).heatmap(variable = 'asleep')\n",
-    "fig.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 60,
-   "id": "5c084cf8-92d7-4579-8c93-cd761ed821f7",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1133.33x466.667 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "start_hour = 0\n",
-    "end_hour = 96\n",
-    "\n",
-    "# Generate plot from Ethoscopy\n",
-    "fig = df.remove('id', *dead_flies).t_filter(start_time=start_hour, end_time=end_hour).plot_overtime(variable='asleep', avg_window=30, grids=True)\n",
-    "\n",
-    "# Extract the main axis from the figure\n",
-    "ax = fig.axes[0]\n",
-    "\n",
-    "# Add shading stimulus shading\n",
-    "# Draw a vertical span from ZT 48 to ZT 72\n",
-    "ax.axvspan(48, 72, color='#ff4c4c', alpha=0.3, zorder=1)\n",
-    "\n",
-    "# Set custom labels\n",
-    "ax.set_xlabel(\"Zeitgeber Time (Hours)\", fontsize=12)\n",
-    "ax.set_ylabel(\"Fraction of Time Asleep\", fontsize=12)\n",
-    "\n",
-    "# Show plot\n",
-    "fig.show()\n",
-    "\n",
-    "# Save as a high-resolution PNG\n",
-    "plt.savefig(\"atr_11H_pulse.png\", dpi=600, bbox_inches='tight')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 54,
-   "id": "86582021-e83b-4c8a-a1c5-cb10dc051bec",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "--- Individual Fly Sleep (Baseline: 0h to 48h, Averaged per day) ---\n",
-      "             Fly_Label  Base_Sleep_24h  Base_Day_12h  Base_Night_12h\n",
-      "ETHOSCOPE_224 - Fly 01       12.676389      5.140481        8.813889\n",
-      "ETHOSCOPE_224 - Fly 02       11.891667      5.734593        7.465278\n",
-      "ETHOSCOPE_224 - Fly 03       10.370833      4.681125        6.673611\n",
-      "ETHOSCOPE_224 - Fly 04       10.215278      4.525229        6.665278\n",
-      "ETHOSCOPE_224 - Fly 05        9.781944      4.152022        6.620833\n",
-      "ETHOSCOPE_224 - Fly 07       14.823611      7.239939        9.284722\n",
-      "ETHOSCOPE_224 - Fly 09       14.679167      8.252289        8.106944\n",
-      "ETHOSCOPE_224 - Fly 10        6.626389      2.196664        4.888889\n",
-      "ETHOSCOPE_224 - Fly 12        7.359722      4.452710        3.812500\n",
-      "ETHOSCOPE_224 - Fly 13        5.411111      1.362994        4.340278\n",
-      "ETHOSCOPE_224 - Fly 14       10.252778      4.700173        6.486111\n",
-      "ETHOSCOPE_224 - Fly 15        6.815278      1.468362        5.638889\n",
-      "ETHOSCOPE_224 - Fly 16        7.209722      3.682567        4.261111\n",
-      "ETHOSCOPE_224 - Fly 18        3.643056      1.045061        2.805556\n",
-      "ETHOSCOPE_224 - Fly 19        7.534722      1.709272        6.181944\n",
-      "ETHOSCOPE_224 - Fly 20        7.212500      2.892921        4.961111\n",
-      "ETHOSCOPE_265 - Fly 01        6.137500      4.040210        2.927778\n",
-      "ETHOSCOPE_265 - Fly 03        6.841667      1.611007        5.554167\n",
-      "ETHOSCOPE_265 - Fly 04        7.765278      3.349650        5.104167\n",
-      "ETHOSCOPE_265 - Fly 05        6.188889      1.035921        5.361111\n",
-      "... (Showing first 20 rows)\n",
-      "\n",
-      "--- Grand Summary Statistics (Baseline: 0h to 48h) ---\n",
-      "Total Flies Analyzed: n = 35\n",
-      "\n",
-      "[ OVERALL SLEEP (Scaled to 24h Baseline Average) ]\n",
-      "Mean ± SEM:   7.27 ± 0.55 hours\n",
-      "Median:       6.82 hours\n",
-      "\n",
-      "[ DAY TIME (ZT 0-12, Averaged to 12h blocks) ]\n",
-      "Mean ± SEM:   2.97 ± 0.32 hours\n",
-      "Median:       2.75 hours\n",
-      "\n",
-      "[ NIGHT TIME (ZT 12-24, Averaged to 12h blocks) ]\n",
-      "Mean ± SEM:   4.93 ± 0.35 hours\n",
-      "Median:       4.96 hours\n"
-     ]
-    }
-   ],
-   "source": [
-    "# BASELINE\n",
-    "\n",
-    "# Define baseline time period\n",
-    "start_hour = 0\n",
-    "end_hour = 48\n",
-    "\n",
-    "# Filter the dataset to ONLY include data within specific baseline window\n",
-    "base_df = df.t_filter(start_time=start_hour, end_time=end_hour).copy()\n",
-    "\n",
-    "# Exclude dead flies\n",
-    "base_df = base_df[~base_df.index.get_level_values('id').isin(dead_flies)]\n",
-    "\n",
-    "# Calculate Overall 24h Baseline Average\n",
-    "sleep_hours = (base_df.groupby('id')['asleep'].sum() * 10) / 3600\n",
-    "\n",
-    "# (72 - 0) / 24 evaluates to exactly 3 days. \n",
-    "# Dividing total sleep by 3 to average the 72 hours into a single 24-hour metric\n",
-    "days_tracked = (end_hour - start_hour) / 24 \n",
-    "base_overall = (sleep_hours / days_tracked).reset_index(name='Base_Sleep_24h')\n",
-    "\n",
-    "# Calculate Day/Night 12h Baseline Averages\n",
-    "base_df['zt_hour'] = (base_df['t'] / 3600) % 24\n",
-    "base_df['Phase'] = np.where(base_df['zt_hour'] < 12, 'Day', 'Night')\n",
-    "\n",
-    "base_phase = base_df.groupby(['id', 'Phase']).agg(\n",
-    "    total_sleep_epochs=('asleep', 'sum'),\n",
-    "    total_tracking_epochs=('t', 'count')\n",
-    ").reset_index()\n",
-    "\n",
-    "# Tracking_Hours will be ~24 for Day and ~24 for Night \n",
-    "# Dividing sleep by tracking hours and multiplying by 12 averages it to a single 12h block.\n",
-    "base_phase['Sleep_Hours'] = (base_phase['total_sleep_epochs'] * 10) / 3600\n",
-    "base_phase['Tracking_Hours'] = (base_phase['total_tracking_epochs'] * 10) / 3600\n",
-    "base_phase['Base_Sleep_12h'] = (base_phase['Sleep_Hours'] / base_phase['Tracking_Hours']) * 12\n",
-    "\n",
-    "base_pivot = base_phase.pivot(index='id', columns='Phase', values='Base_Sleep_12h').reset_index()\n",
-    "# Rename columns\n",
-    "base_pivot.columns = ['id', 'Base_Day_12h', 'Base_Night_12h']\n",
-    "\n",
-    "# Merge and clean up data\n",
-    "merged_df = pd.merge(base_overall, base_pivot, on='id')\n",
-    "\n",
-    "merged_df['Machine'] = merged_df['id'].map(df.meta['machine_name'])\n",
-    "merged_df['Tube'] = merged_df['id'].apply(lambda x: str(x).split('|')[-1])\n",
-    "merged_df['Fly_Label'] = merged_df['Machine'] + \" - Fly \" + merged_df['Tube']\n",
-    "\n",
-    "clean_table = merged_df.dropna(subset=['Machine']).sort_values(by=['Machine', 'Tube'])\n",
-    "baseline_stats = clean_table[['Fly_Label', 'Base_Sleep_24h', 'Base_Day_12h', 'Base_Night_12h']]\n",
-    "\n",
-    "# PRINT RESULTS\n",
-    "print(f\"--- Individual Fly Sleep (Baseline: {start_hour}h to {end_hour}h, Averaged per day) ---\")\n",
-    "print(baseline_stats.head(20).to_string(index=False)) \n",
-    "print(\"... (Showing first 20 rows)\\n\")\n",
-    "\n",
-    "print(f\"--- Grand Summary Statistics (Baseline: {start_hour}h to {end_hour}h) ---\")\n",
-    "print(f\"Total Flies Analyzed: n = {len(baseline_stats)}\")\n",
-    "\n",
-    "# 1. OVERALL 24H STATS\n",
-    "print(\"\\n[ OVERALL SLEEP (Scaled to 24h Baseline Average) ]\")\n",
-    "print(f\"Mean ± SEM:   {baseline_stats['Base_Sleep_24h'].mean():.2f} ± {baseline_stats['Base_Sleep_24h'].sem():.2f} hours\")\n",
-    "print(f\"Median:       {baseline_stats['Base_Sleep_24h'].median():.2f} hours\")\n",
-    "\n",
-    "# 2. DAY TIME STATS\n",
-    "print(f\"\\n[ DAY TIME (ZT 0-12, Averaged to 12h blocks) ]\")\n",
-    "print(f\"Mean ± SEM:   {baseline_stats['Base_Day_12h'].mean():.2f} ± {baseline_stats['Base_Day_12h'].sem():.2f} hours\")\n",
-    "print(f\"Median:       {baseline_stats['Base_Day_12h'].median():.2f} hours\")\n",
-    "\n",
-    "# 3. NIGHT TIME STATS\n",
-    "print(f\"\\n[ NIGHT TIME (ZT 12-24, Averaged to 12h blocks) ]\")\n",
-    "print(f\"Mean ± SEM:   {baseline_stats['Base_Night_12h'].mean():.2f} ± {baseline_stats['Base_Night_12h'].sem():.2f} hours\")\n",
-    "print(f\"Median:       {baseline_stats['Base_Night_12h'].median():.2f} hours\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 55,
-   "id": "9e18111e-18d4-4001-8685-cc5f0e69170f",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "--- Individual Fly Sleep (Stimulus: 48h to 72h) ---\n",
-      "             Fly_Label  Stim_Sleep_24h  Stim_Day_12h  Stim_Night_12h\n",
-      "ETHOSCOPE_224 - Fly 01        2.788889      2.016667        0.772222\n",
-      "ETHOSCOPE_224 - Fly 02        9.238889      4.141667        5.097222\n",
-      "ETHOSCOPE_224 - Fly 03        0.922222      0.413889        0.508333\n",
-      "ETHOSCOPE_224 - Fly 04        2.800000      0.763889        2.036111\n",
-      "ETHOSCOPE_224 - Fly 05        1.997222      1.350000        0.647222\n",
-      "ETHOSCOPE_224 - Fly 07        4.438889      2.255556        2.183333\n",
-      "ETHOSCOPE_224 - Fly 09        4.100000      2.297222        1.802778\n",
-      "ETHOSCOPE_224 - Fly 10        2.197222      0.605556        1.591667\n",
-      "ETHOSCOPE_224 - Fly 12        1.291667      0.725000        0.566667\n",
-      "ETHOSCOPE_224 - Fly 13        3.580556      0.611111        2.969444\n",
-      "ETHOSCOPE_224 - Fly 14        0.130556      0.130556        0.000000\n",
-      "ETHOSCOPE_224 - Fly 15        1.750000      0.000000        1.750000\n",
-      "ETHOSCOPE_224 - Fly 16        0.197222      0.100000        0.097222\n",
-      "ETHOSCOPE_224 - Fly 18        0.200000      0.000000        0.200000\n",
-      "ETHOSCOPE_224 - Fly 19        4.405556      0.980556        3.425000\n",
-      "ETHOSCOPE_224 - Fly 20        1.016667      0.197222        0.819444\n",
-      "ETHOSCOPE_265 - Fly 01        0.391667      0.308333        0.083333\n",
-      "ETHOSCOPE_265 - Fly 03        0.097222      0.097222        0.000000\n",
-      "ETHOSCOPE_265 - Fly 04        1.163889      0.644444        0.519444\n",
-      "ETHOSCOPE_265 - Fly 05        0.208333      0.000000        0.208333\n",
-      "... (Showing first 20 rows)\n",
-      "\n",
-      "--- Grand Summary Statistics (Stimulus: 48h to 72h) ---\n",
-      "Total Flies Analyzed: n = 35\n",
-      "\n",
-      "[ OVERALL SLEEP (24h Stimulus Block) ]\n",
-      "Mean ± SEM:   1.60 ± 0.32 hours\n",
-      "Median:       1.02 hours\n",
-      "\n",
-      "[ DAY TIME (ZT 0-12 during Stimulus) ]\n",
-      "Mean ± SEM:   0.69 ± 0.15 hours\n",
-      "Median:       0.41 hours\n",
-      "\n",
-      "[ NIGHT TIME (ZT 12-24 during Stimulus) ]\n",
-      "Mean ± SEM:   0.91 ± 0.19 hours\n",
-      "Median:       0.57 hours\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Define stimulus time period\n",
-    "start_hour = 48\n",
-    "end_hour = 72\n",
-    "\n",
-    "# Filter the dataset to ONLY include data within specific stimulus window\n",
-    "stim_df = df.t_filter(start_time=start_hour, end_time=end_hour).copy()\n",
-    "\n",
-    "# Exclude dead flies\n",
-    "stim_df = stim_df[~stim_df.index.get_level_values('id').isin(dead_flies)]\n",
-    "\n",
-    "# Calculate Overall 24h Stimulus Average\n",
-    "sleep_hours = (stim_df.groupby('id')['asleep'].sum() * 10) / 3600\n",
-    "days_tracked = (end_hour - start_hour) / 24 \n",
-    "stim_overall = (sleep_hours / days_tracked).reset_index(name='Stim_Sleep_24h')\n",
-    "\n",
-    "# Calculate Day/Night 12h Stimulus Averages\n",
-    "stim_df['zt_hour'] = (stim_df['t'] / 3600) % 24\n",
-    "stim_df['Phase'] = np.where(stim_df['zt_hour'] < 12, 'Day', 'Night')\n",
-    "\n",
-    "stim_phase = stim_df.groupby(['id', 'Phase']).agg(\n",
-    "    total_sleep_epochs=('asleep', 'sum'),\n",
-    "    total_tracking_epochs=('t', 'count')\n",
-    ").reset_index()\n",
-    "\n",
-    "# Tracking_Hours will now be ~12 for Day and ~12 for Night\n",
-    "# Dividing sleep by tracking hours and multiplying by 12 averages it to a single 12h block.\n",
-    "stim_phase['Sleep_Hours'] = (stim_phase['total_sleep_epochs'] * 10) / 3600\n",
-    "stim_phase['Tracking_Hours'] = (stim_phase['total_tracking_epochs'] * 10) / 3600\n",
-    "stim_phase['Stim_Sleep_12h'] = (stim_phase['Sleep_Hours'] / stim_phase['Tracking_Hours']) * 12\n",
-    "\n",
-    "stim_pivot = stim_phase.pivot(index='id', columns='Phase', values='Stim_Sleep_12h').reset_index()\n",
-    "# Rename columns \n",
-    "stim_pivot.columns = ['id', 'Stim_Day_12h', 'Stim_Night_12h']\n",
-    "\n",
-    "# Merge and clean up data\n",
-    "merged_df = pd.merge(stim_overall, stim_pivot, on='id')\n",
-    "\n",
-    "merged_df['Machine'] = merged_df['id'].map(df.meta['machine_name'])\n",
-    "merged_df['Tube'] = merged_df['id'].apply(lambda x: str(x).split('|')[-1])\n",
-    "merged_df['Fly_Label'] = merged_df['Machine'] + \" - Fly \" + merged_df['Tube']\n",
-    "\n",
-    "clean_table = merged_df.dropna(subset=['Machine']).sort_values(by=['Machine', 'Tube'])\n",
-    "stim_stats = clean_table[['Fly_Label', 'Stim_Sleep_24h', 'Stim_Day_12h', 'Stim_Night_12h']]\n",
-    "\n",
-    "# PRINT RESULTS\n",
-    "print(f\"--- Individual Fly Sleep (Stimulus: {start_hour}h to {end_hour}h) ---\")\n",
-    "print(stim_stats.head(20).to_string(index=False)) \n",
-    "print(\"... (Showing first 20 rows)\\n\")\n",
-    "\n",
-    "print(f\"--- Grand Summary Statistics (Stimulus: {start_hour}h to {end_hour}h) ---\")\n",
-    "print(f\"Total Flies Analyzed: n = {len(stim_stats)}\")\n",
-    "\n",
-    "# 1. OVERALL 24H STATS\n",
-    "print(\"\\n[ OVERALL SLEEP (24h Stimulus Block) ]\")\n",
-    "print(f\"Mean ± SEM:   {stim_stats['Stim_Sleep_24h'].mean():.2f} ± {stim_stats['Stim_Sleep_24h'].sem():.2f} hours\")\n",
-    "print(f\"Median:       {stim_stats['Stim_Sleep_24h'].median():.2f} hours\")\n",
-    "\n",
-    "# 2. DAY TIME STATS\n",
-    "print(f\"\\n[ DAY TIME (ZT 0-12 during Stimulus) ]\")\n",
-    "print(f\"Mean ± SEM:   {stim_stats['Stim_Day_12h'].mean():.2f} ± {stim_stats['Stim_Day_12h'].sem():.2f} hours\")\n",
-    "print(f\"Median:       {stim_stats['Stim_Day_12h'].median():.2f} hours\")\n",
-    "\n",
-    "# 3. NIGHT TIME STATS\n",
-    "print(f\"\\n[ NIGHT TIME (ZT 12-24 during Stimulus) ]\")\n",
-    "print(f\"Mean ± SEM:   {stim_stats['Stim_Night_12h'].mean():.2f} ± {stim_stats['Stim_Night_12h'].sem():.2f} hours\")\n",
-    "print(f\"Median:       {stim_stats['Stim_Night_12h'].median():.2f} hours\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 56,
-   "id": "18d0e98f-6db2-4ffd-a20f-798737e82a06",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "--- 24h Total Statistical Analysis ---\n",
-      "Shapiro-Wilk P-value (Normality of differences): 0.6430\n",
-      "Result: Data is normal. Used Paired T-test.\n",
-      "P-value: 1.4158e-14\n",
-      "Significance: ****\n",
-      "\n",
-      "--- Daytime Statistical Analysis ---\n",
-      "Shapiro-Wilk P-value (Normality of differences): 0.1891\n",
-      "Result: Data is normal. Used Paired T-test.\n",
-      "P-value: 5.9464e-11\n",
-      "Significance: ****\n",
-      "\n",
-      "--- Nighttime Statistical Analysis ---\n",
-      "Shapiro-Wilk P-value (Normality of differences): 0.8569\n",
-      "Result: Data is normal. Used Paired T-test.\n",
-      "P-value: 1.7105e-14\n",
-      "Significance: ****\n"
-     ]
-    }
-   ],
-   "source": [
-    "# STATISTICS\n",
-    "\n",
-    "# Merge Baseline and Stimulus data on Fly_Label\n",
-    "paired_df = pd.merge(baseline_stats, stim_stats, on='Fly_Label')\n",
-    "\n",
-    "def run_paired_stats(df, base_col, stim_col, label):\n",
-    "    # Calculate the differences for the paired test\n",
-    "    diffs = df[stim_col] - df[base_col]\n",
-    "    \n",
-    "    # 2. Shapiro-Wilk Test for Normality\n",
-    "    _, p_shapiro = shapiro(diffs)\n",
-    "    \n",
-    "    print(f\"\\n--- {label} Statistical Analysis ---\")\n",
-    "    print(f\"Shapiro-Wilk P-value (Normality of differences): {p_shapiro:.4f}\")\n",
-    "    \n",
-    "    # 3. Determine Test: If P > 0.05, data is normal (use t-test). If P < 0.05, use Wilcoxon.\n",
-    "    if p_shapiro > 0.05:\n",
-    "        stat, p_val = ttest_rel(df[base_col], df[stim_col])\n",
-    "        print(f\"Result: Data is normal. Used Paired T-test.\")\n",
-    "    else:\n",
-    "        stat, p_val = wilcoxon(df[base_col], df[stim_col])\n",
-    "        print(f\"Result: Data is not normal. Used Wilcoxon Signed-Rank test.\")\n",
-    "        \n",
-    "    print(f\"P-value: {p_val:.4e}\")\n",
-    "    if p_val < 0.0001: print(\"Significance: ****\")\n",
-    "    elif p_val < 0.001: print(\"Significance: ***\")\n",
-    "    elif p_val < 0.01: print(\"Significance: **\")\n",
-    "    elif p_val < 0.05: print(\"Significance: *\")\n",
-    "    else: print(\"Significance: ns\")\n",
-    "\n",
-    "# Run for all three metrics\n",
-    "run_paired_stats(paired_df, 'Base_Sleep_24h', 'Stim_Sleep_24h', '24h Total')\n",
-    "run_paired_stats(paired_df, 'Base_Day_12h', 'Stim_Day_12h', 'Daytime')\n",
-    "run_paired_stats(paired_df, 'Base_Night_12h', 'Stim_Night_12h', 'Nighttime')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 67,
-   "id": "0a1c639b-6e43-48ba-9334-cb98ae7bd72d",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 700x600 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# 1. PREPARE DATA & CALCULATE STATS\n",
-    "combined = pd.merge(baseline_stats, stim_stats, on='Fly_Label')\n",
-    "\n",
-    "# Calculate the paired statistics for the brackets\n",
-    "p_values = {}\n",
-    "metrics = {\n",
-    "    '24h': ('Base_Sleep_24h', 'Stim_Sleep_24h'),\n",
-    "    'Day': ('Base_Day_12h', 'Stim_Day_12h'),\n",
-    "    'Night': ('Base_Night_12h', 'Stim_Night_12h')\n",
-    "}\n",
-    "\n",
-    "for phase, (base_col, stim_col) in metrics.items():\n",
-    "    diffs = combined[stim_col] - combined[base_col]\n",
-    "    _, p_shapiro = shapiro(diffs)\n",
-    "    \n",
-    "    if p_shapiro > 0.05:\n",
-    "        _, p_val = ttest_rel(combined[base_col], combined[stim_col])\n",
-    "    else:\n",
-    "        _, p_val = wilcoxon(combined[base_col], combined[stim_col])\n",
-    "    p_values[phase] = p_val\n",
-    "\n",
-    "plot_df = combined.melt(id_vars=['Fly_Label'], var_name='Variable', value_name='Hours')\n",
-    "plot_df['Condition'] = plot_df['Variable'].apply(lambda x: '24h' if '24h' in x else ('Day' if 'Day' in x else 'Night'))\n",
-    "plot_df['State'] = plot_df['Variable'].apply(lambda x: 'Baseline' if 'Base' in x else 'Stimulus')\n",
-    "\n",
-    "# 2. GENERATE PLOT\n",
-    "plt.figure(figsize=(7, 6))\n",
-    "sns.set_theme(style=\"ticks\")\n",
-    "\n",
-    "order = ['24h', 'Day', 'Night']\n",
-    "hue_order = ['Baseline', 'Stimulus']\n",
-    "palette = {'Baseline': '#cccccc', 'Stimulus': '#ff4c4c'}\n",
-    "\n",
-    "# Boxplot \n",
-    "sns.boxplot(\n",
-    "    data=plot_df, x='Condition', y='Hours', hue='State', \n",
-    "    order=order, hue_order=hue_order, palette=palette,\n",
-    "    width=0.6, gap=0.2, boxprops={'edgecolor': 'black', 'alpha': 0.7},\n",
-    "    medianprops={'color': 'black', 'linewidth': 1.5}, showfliers=False\n",
-    ")\n",
-    "\n",
-    "# Stripplot\n",
-    "sns.stripplot(\n",
-    "    data=plot_df, x='Condition', y='Hours', hue='State', \n",
-    "    order=order, hue_order=hue_order, dodge=True,\n",
-    "    palette=['black', 'black'], alpha=0.5, size=4, jitter=0.05,\n",
-    "    legend=False\n",
-    ")\n",
-    "\n",
-    "# 3. ADD MEDIAN LABELS\n",
-    "ax = plt.gca()\n",
-    "medians = plot_df.groupby(['Condition', 'State'], sort=False)['Hours'].median()\n",
-    "\n",
-    "offsets = {'Baseline': -0.4, 'Stimulus': 0.4}\n",
-    "\n",
-    "for i, cond in enumerate(order):\n",
-    "    for state in hue_order:\n",
-    "        val = medians[(cond, state)]\n",
-    "        ax.text(i + offsets[state], val, f\"{val:.1f}h\", \n",
-    "                ha='center', va='bottom', fontsize=10)\n",
-    "\n",
-    "# 4. ADD SIGNIFICANCE BRACKETS\n",
-    "y_max = plot_df['Hours'].max()\n",
-    "y_line = y_max + 1.0  \n",
-    "h = 0.4               \n",
-    "\n",
-    "for i, cond in enumerate(order):\n",
-    "    p = p_values[cond]\n",
-    "    \n",
-    "    if p < 0.0001: star = '****'\n",
-    "    elif p < 0.001: star = '***'\n",
-    "    elif p < 0.01: star = '**'\n",
-    "    elif p < 0.05: star = '*'\n",
-    "    else: star = 'ns'\n",
-    "    \n",
-    "    x1, x2 = i - 0.2, i + 0.2\n",
-    "    plt.plot([x1, x1, x2, x2], [y_line, y_line+h, y_line+h, y_line], lw=1.5, c='k')\n",
-    "    plt.text((x1+x2)*.5, y_line+h, star, ha='center', va='bottom', fontsize=12)\n",
-    "\n",
-    "# 5. FORMATTING\n",
-    "sns.despine()\n",
-    "plt.ylabel('Average time spent asleep (hours)', fontsize=12)\n",
-    "plt.xlabel('')\n",
-    "plt.xlim(-0.6, 2.5) \n",
-    "\n",
-    "plt.ylim(0, max(18, y_line + h + 1.5)) \n",
-    "\n",
-    "# Legend moved outside the plot to the right\n",
-    "plt.legend(title='', frameon=False, loc='center left', bbox_to_anchor=(1, 0.5))\n",
-    "plt.tight_layout()\n",
-    "\n",
-    "plt.savefig(\"plot_atr_11H_pulse.png\", dpi=600, bbox_inches='tight')\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 63,
-   "id": "556f947b-929f-4f61-a87c-ccbba753e4f8",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "--- Delta Sleep (Stimulus - Baseline) per Fly ---\n",
-      "             Fly_Label  Delta_24h  Delta_Day  Delta_Night\n",
-      "ETHOSCOPE_224 - Fly 01  -9.887500  -3.123814    -8.041667\n",
-      "ETHOSCOPE_224 - Fly 02  -2.652778  -1.592926    -2.368056\n",
-      "ETHOSCOPE_224 - Fly 03  -9.448611  -4.267237    -6.165278\n",
-      "ETHOSCOPE_224 - Fly 04  -7.415278  -3.761340    -4.629167\n",
-      "ETHOSCOPE_224 - Fly 05  -7.784722  -2.802022    -5.973611\n",
-      "ETHOSCOPE_224 - Fly 07 -10.384722  -4.984384    -7.101389\n",
-      "ETHOSCOPE_224 - Fly 09 -10.579167  -5.955067    -6.304167\n",
-      "ETHOSCOPE_224 - Fly 10  -4.429167  -1.591108    -3.297222\n",
-      "ETHOSCOPE_224 - Fly 12  -6.068056  -3.727710    -3.245833\n",
-      "ETHOSCOPE_224 - Fly 13  -1.830556  -0.751882    -1.370833\n",
-      "ETHOSCOPE_224 - Fly 14 -10.122222  -4.569618    -6.486111\n",
-      "ETHOSCOPE_224 - Fly 15  -5.065278  -1.468362    -3.888889\n",
-      "ETHOSCOPE_224 - Fly 16  -7.012500  -3.582567    -4.163889\n",
-      "ETHOSCOPE_224 - Fly 18  -3.443056  -1.045061    -2.605556\n",
-      "ETHOSCOPE_224 - Fly 19  -3.129167  -0.728716    -2.756944\n",
-      "ETHOSCOPE_224 - Fly 20  -6.195833  -2.695699    -4.141667\n",
-      "ETHOSCOPE_265 - Fly 01  -5.745833  -3.731876    -2.844444\n",
-      "ETHOSCOPE_265 - Fly 03  -6.744444  -1.513784    -5.554167\n",
-      "ETHOSCOPE_265 - Fly 04  -6.601389  -2.705206    -4.584722\n",
-      "ETHOSCOPE_265 - Fly 05  -5.980556  -1.035921    -5.152778\n",
-      "ETHOSCOPE_265 - Fly 06  -0.175000   0.000000    -0.175000\n",
-      "ETHOSCOPE_265 - Fly 07  -3.862500  -1.190212    -2.934722\n",
-      "ETHOSCOPE_265 - Fly 08  -6.659722  -1.438364    -5.668056\n",
-      "ETHOSCOPE_265 - Fly 09  -4.736111  -2.015068    -3.126389\n",
-      "ETHOSCOPE_265 - Fly 10  -1.263889  -2.007641     0.261111\n",
-      "ETHOSCOPE_265 - Fly 11  -2.248611   0.001890    -2.311111\n",
-      "ETHOSCOPE_265 - Fly 12  -6.448611  -0.777681    -5.829167\n",
-      "ETHOSCOPE_265 - Fly 13  -4.466667  -0.902489    -3.868056\n",
-      "ETHOSCOPE_265 - Fly 14  -5.847222  -2.799916    -3.695833\n",
-      "ETHOSCOPE_265 - Fly 15  -2.855556  -0.815367    -2.288889\n",
-      "ETHOSCOPE_265 - Fly 16  -3.769444  -1.270384    -2.754167\n",
-      "ETHOSCOPE_265 - Fly 17  -7.488889  -2.724903    -5.615278\n",
-      "ETHOSCOPE_265 - Fly 18  -5.056944  -2.559725    -3.048611\n",
-      "ETHOSCOPE_265 - Fly 19  -6.900000  -2.819823    -4.912500\n",
-      "ETHOSCOPE_265 - Fly 20  -6.101389  -2.808998    -4.070833\n",
-      "\n",
-      "==================================================\n",
-      "\n",
-      "--- Average Change (Delta) across all flies ---\n",
-      "Delta_24h: -5.67 ± 0.44 hours\n",
-      "Delta_Day: -2.28 ± 0.24 hours\n",
-      "Delta_Night: -4.02 ± 0.32 hours\n"
-     ]
-    }
-   ],
-   "source": [
-    "#DELTA\n",
-    "\n",
-    "# 1. Ensure have the merged paired data\n",
-    "combined = pd.merge(baseline_stats, stim_stats, on='Fly_Label')\n",
-    "\n",
-    "# 2. Calculate the Delta (Stimulus - Baseline) for each fly\n",
-    "combined['Delta_24h'] = combined['Stim_Sleep_24h'] - combined['Base_Sleep_24h']\n",
-    "combined['Delta_Day'] = combined['Stim_Day_12h'] - combined['Base_Day_12h']\n",
-    "combined['Delta_Night'] = combined['Stim_Night_12h'] - combined['Base_Night_12h']\n",
-    "\n",
-    "# 3. Print the Delta for each individual fly\n",
-    "print(\"--- Delta Sleep (Stimulus - Baseline) per Fly ---\")\n",
-    "delta_table = combined[['Fly_Label', 'Delta_24h', 'Delta_Day', 'Delta_Night']]\n",
-    "print(delta_table.to_string(index=False))\n",
-    "print(\"\\n\" + \"=\"*50 + \"\\n\")\n",
-    "\n",
-    "# 4. Calculate and print the group averages\n",
-    "print(\"--- Average Change (Delta) across all flies ---\")\n",
-    "avg_delta = delta_table[['Delta_24h', 'Delta_Day', 'Delta_Night']].mean()\n",
-    "sem_delta = delta_table[['Delta_24h', 'Delta_Day', 'Delta_Night']].sem()\n",
-    "\n",
-    "for metric in ['Delta_24h', 'Delta_Day', 'Delta_Night']:\n",
-    "    print(f\"{metric}: {avg_delta[metric]:.2f} ± {sem_delta[metric]:.2f} hours\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 68,
-   "id": "abf4c87b-df8f-4d43-9b47-e55d2c1f26df",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#export to csv\n",
-    "delta_table['Condition'] = 'Red'\n",
-    "delta_table.to_csv('delta_11H_phase7.csv', index=False)"
-   ]
-  }
- ],
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