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docs/chore(notebooks/readme): add times to notebooks and README, and correct images in README
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‎README.md‎

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![](outputs/occupancy_freq_asu.png)
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![](outputs/figure1_asu.png)
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**Figure 3**
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![](outputs/delay_prob_asu.png)
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![](outputs/figure3_asu.png)
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<br>
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## Run time and machine specification
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TBC
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The run time for this analysis (`notebooks/analysis.ipynb`) is 10 seconds. This was on an Intel Core i7-12700H, 32GB RAM, Ubuntu 24.04.1.
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<!-- State the run time, and give the specification of the machine used (which achieved that run time).
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**Example:** Intel Core i7-12700H with 32GB RAM running Ubuntu 24.04.1 Linux.
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To find this information:
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* **Linux:** Run `neofetch` on the terminal and record your CPU, memory and operating system.
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* **Windows:** Open "Task Manager" (Ctrl + Shift + Esc), go to the "Performance" tab, then select "CPU" and "Memory" for relevant information.
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* **Mac:** Click the "Apple Menu", select "About This Mac", then window will display the details.-->
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The other notebooks generate results for tests and illustrate other functionality (e.g. importing parameters from csv, running with logs), and these just take a second or two.
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<br>
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‎notebooks/analysis.ipynb‎

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"\n",
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"# pylint: disable=wrong-import-position\n",
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"import os\n",
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"import time\n",
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"\n",
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"from IPython.display import display\n",
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"import numpy as np\n",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Start timer\n",
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"start_time = time.time()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Path to the outputs folder\n",
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"OUTPUT_DIR = \"../outputs/\""
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},
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"cell_type": "code",
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},
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},
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},
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{
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"tab3.to_csv(\n",
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" os.path.join(OUTPUT_DIR, \"table3.csv\"), index=False)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Run time"
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]
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},
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{
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"cell_type": "code",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Notebook run time: 0m 10s\n"
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]
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}
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],
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"source": [
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"# Get run time in seconds\n",
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"end_time = time.time()\n",
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"runtime = round(end_time - start_time)\n",
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"\n",
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"# Display converted to minutes and seconds\n",
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"print(f'Notebook run time: {runtime // 60}m {runtime % 60}s')"
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]
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}
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],
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"metadata": {

‎notebooks/generate_exp_results.ipynb‎

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"\n",
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"# pylint: disable=wrong-import-position\n",
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"import os\n",
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"import time\n",
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"\n",
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"from IPython.display import display\n",
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"import pandas as pd\n",
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"# Start timer\n",
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"start_time = time.time()"
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]
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},
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"outputs": [],
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"# Define path to folder for expected results for tests\n",
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"TESTS = \"../tests/exp_results/\""
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"runner_df[\"rehab\"].to_csv(os.path.join(TESTS, \"rehab_occupancy.csv\"),\n",
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},
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{
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"cell_type": "markdown",
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"source": [
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"## Run time"
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]
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},
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{
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Notebook run time: 0m 0s\n"
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]
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}
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],
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"source": [
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"# Get run time in seconds\n",
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"end_time = time.time()\n",
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"runtime = round(end_time - start_time)\n",
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"\n",
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"# Display converted to minutes and seconds\n",
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"print(f'Notebook run time: {runtime // 60}m {runtime % 60}s')"
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]
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}
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],
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"metadata": {

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