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add schedule duration live monitoring notebook
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‎docs/user-guide/teacher-content/UU-ocean-of-future/schedule_monitor.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "623b96d7-7c2d-4797-a18d-6a34c79a5296",
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"metadata": {},
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"source": [
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"### Schedule duration monitor\n",
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"\n",
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"This notebook will monitor - in live time - the duration of the expeditions in directories GROUP1, GROUP2, ... , GROUP66.\n",
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"\n",
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"The resultant plot once all cells of the notebook are run will be refreshed every n seconds (prescribable in the `REFRESH` constant below).\n",
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"\n",
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"CTDs are assumed to take approx. 20 minutes each. 3 days sailing time is added to all groups for the outbound journey from Texel to the first waypoint.\n",
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"\n",
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"<div class=\"alert alert-warning\">\n",
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"This script uses an infinite `while` loop to refresh the plotting indefinitely. To stop the running, the \"Interupt the kernel\" button (square button) should be pressed.\n",
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"</div>\n"
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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": 1,
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"id": "64a8edb1-46c3-488f-a0dc-d104d47bbaa5",
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"metadata": {},
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"outputs": [],
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"source": [
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"import time\n",
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"import os\n",
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"import sys\n",
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"import yaml\n",
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"import numpy as np\n",
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"from pathlib import Path\n",
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"from matplotlib import pyplot as plt\n",
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"from IPython.display import clear_output"
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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": 2,
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"id": "d93d52a2-b55d-43b6-bc2e-a56aecbe8fa7",
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"metadata": {},
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"outputs": [],
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"source": [
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"# plot refresh rate\n",
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"REFRESH = 30 # [seconds]"
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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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"id": "2c61c6b5-e729-46d0-bc9e-2f87a447ee76",
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"metadata": {},
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"outputs": [],
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"source": [
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"# config\n",
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"BASE_DIR = Path(\"/home/shared/data/virtualship_storage/\")\n",
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"SAIL_OUT_TIME = np.timedelta64(3, \"D\") # [days]\n",
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"CTD_TIME = np.timedelta64(200, \"m\") # [minutes]\n",
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"SHIP_TIME_THRESHOLD = 9 # [days]\n",
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"ROTATION_CHANGE = 18 # when to change from 45 to 90 degree rotation in x axis labels"
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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": 4,
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"id": "4a91fae1-46d1-4e49-855a-b0bec7b127d9",
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"metadata": {
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"jupyter": {
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"source_hidden": true
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}
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},
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"outputs": [],
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"source": [
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"def preprocess(\n",
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" base_dir: Path, sail_out_time: np.timedelta64, ctd_time: np.timedelta64\n",
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") -> dict:\n",
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" \"\"\"\n",
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" Reads schedule data from YAML files, calculates the total expedition duration\n",
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" for each group, and returns a dictionary of valid groups and their durations.\n",
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" \"\"\"\n",
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" groups = {}\n",
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"\n",
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" # group directories 1 to 66 (inclusive)\n",
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" for i in range(1, 67):\n",
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" group_name = f\"GROUP{i}\"\n",
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" group_dir = base_dir / group_name\n",
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" schedule_file = group_dir / \"schedule.yaml\"\n",
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"\n",
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" if not schedule_file.exists():\n",
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" groups[group_name] = np.nan\n",
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" continue\n",
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"\n",
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" try:\n",
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" with open(schedule_file, \"r\", encoding=\"utf-8\") as f:\n",
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" schedule_data = yaml.safe_load(f)\n",
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"\n",
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" waypoints = schedule_data.get(\"waypoints\", [])\n",
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"\n",
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" if not waypoints:\n",
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" groups[group_name] = np.nan\n",
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" continue\n",
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"\n",
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" start_time_str = waypoints[0].get(\"time\")\n",
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" end_time_str = waypoints[-1].get(\"time\")\n",
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"\n",
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" if not start_time_str or not end_time_str:\n",
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" groups[group_name] = np.nan\n",
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" else:\n",
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" start_time, end_time = (\n",
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" np.datetime64(start_time_str),\n",
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" np.datetime64(end_time_str),\n",
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" )\n",
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"\n",
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" difference = end_time - start_time\n",
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" difference_days = difference.astype(\"timedelta64[D]\") # [days]\n",
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"\n",
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" total_time_timedelta = difference_days + sail_out_time + ctd_time\n",
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" total_time_days = total_time_timedelta.astype(\n",
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" \"timedelta64[h]\"\n",
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" ) / np.timedelta64(24, \"h\")\n",
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"\n",
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" groups[group_name] = total_time_days.item()\n",
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"\n",
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" except Exception as e:\n",
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" groups[group_name] = np.nan\n",
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" print(f\"Error processing {group_name}: {e}\", file=sys.stderr)\n",
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"\n",
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" # filter dict to remove groups with NaN\n",
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" filter_groups = {key: value for key, value in groups.items() if not np.isnan(value)}\n",
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"\n",
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" return filter_groups"
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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": null,
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"id": "786e2cb8-1dc0-46c0-a454-37ac9e603329",
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"metadata": {
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"jupyter": {
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"source_hidden": true
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}
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},
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"outputs": [],
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"source": [
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"def plot(filter_groups: dict, ship_time_threshold: float, rotation_change: int):\n",
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" \"\"\"\n",
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" Generates a bar plot showing the expedition duration for each group\n",
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" relative to the ship time threshold.\n",
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" \"\"\"\n",
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" groups_keys = list(filter_groups.keys())\n",
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" groups_values = list(filter_groups.values())\n",
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"\n",
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" # bar colors dependent on whether above or below ship time threshold\n",
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" bar_colors = [\n",
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" \"crimson\" if value > ship_time_threshold else \"mediumseagreen\"\n",
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" for value in groups_values\n",
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" ]\n",
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"\n",
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" # fig\n",
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" fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(16, 8), dpi=300)\n",
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"\n",
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" # bars\n",
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" ax.bar(\n",
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" groups_keys,\n",
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" groups_values,\n",
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" color=bar_colors,\n",
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" edgecolor=\"k\",\n",
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" linewidth=1.5,\n",
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" zorder=3,\n",
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" width=0.7,\n",
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" )\n",
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"\n",
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" # labels and title\n",
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" ax.set_ylabel(\"Days\", fontsize=15)\n",
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" ax.set_title(\"Expedition Duration\", fontsize=20)\n",
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"\n",
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" # customise ticks\n",
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" ax.set_xticks(ax.get_xticks())\n",
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" rotation = 45 if len(groups_values) <= rotation_change else 90\n",
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" ax.set_xticklabels(groups_keys, rotation=rotation, ha=\"center\", fontsize=15)\n",
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" ax.tick_params(axis=\"y\", labelsize=15)\n",
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"\n",
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" # set y-limit based on the maximum valid value\n",
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" max_duration = np.nanmax(groups_values) if groups_values else 0\n",
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" ax.set_ylim(0, max_duration + 0.5)\n",
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"\n",
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" # grid\n",
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" ax.set_facecolor(\"gainsboro\")\n",
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" ax.grid(axis=\"y\", linestyle=\"-\", alpha=1.0, color=\"white\")\n",
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"\n",
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" # horizontal line for threshold days\n",
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" ax.axhline(\n",
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" y=ship_time_threshold,\n",
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" color=\"r\",\n",
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" linestyle=\"--\",\n",
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" linewidth=2.5,\n",
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" label=\"Ship-time limit\",\n",
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" zorder=2,\n",
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" )\n",
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"\n",
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" plt.legend(fontsize=15, loc=\"upper left\")\n",
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" plt.tight_layout()\n",
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" plt.show()"
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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": 6,
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"id": "73a78ef2-1b58-48be-802f-0a447c9549a2",
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"metadata": {
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"jupyter": {
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"source_hidden": true
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}
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},
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"outputs": [],
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"source": [
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"def periodic_task(interval_seconds: int):\n",
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" \"\"\"\n",
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" Loop that runs the preprocessing and plotting functions periodically.\n",
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" :param interval_seconds: The number of seconds to wait between runs.\n",
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" \"\"\"\n",
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" while True:\n",
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" try:\n",
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" clear_output(wait=True)\n",
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" print(f\"--- Running task at {time.ctime()} ---\")\n",
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"\n",
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" data = preprocess(BASE_DIR, SAIL_OUT_TIME, CTD_TIME)\n",
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"\n",
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" if data:\n",
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" plot(data, SHIP_TIME_THRESHOLD, ROTATION_CHANGE)\n",
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" else:\n",
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" print(\"No valid data found to plot.\")\n",
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"\n",
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" except KeyboardInterrupt:\n",
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" print(\"\\nPeriodic task interrupted by user.\")\n",
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" break\n",
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" except Exception as e:\n",
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" print(f\"\\nAn error occurred during the periodic run: {e}\")\n",
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"\n",
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" time.sleep(interval_seconds)"
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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": 7,
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"id": "939a0a6b-9261-4e34-80f0-168e9bb133dd",
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"metadata": {
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"collapsed": true,
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"jupyter": {
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"outputs_hidden": true
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},
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"scrolled": true
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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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"--- Running task at Wed Nov 12 21:45:02 2025 ---\n",
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"No valid data found to plot.\n"
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]
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},
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{
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"ename": "KeyboardInterrupt",
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"evalue": "",
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"output_type": "error",
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"traceback": [
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"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
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"\u001b[31mKeyboardInterrupt\u001b[39m Traceback (most recent call last)",
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"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[7]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[43mperiodic_task\u001b[49m\u001b[43m(\u001b[49m\u001b[43minterval_seconds\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43mREFRESH\u001b[49m\u001b[43m)\u001b[49m\n",
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"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[6]\u001b[39m\u001b[32m, line 24\u001b[39m, in \u001b[36mperiodic_task\u001b[39m\u001b[34m(interval_seconds)\u001b[39m\n\u001b[32m 21\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 22\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33mAn error occurred during the periodic run: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00me\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m)\n\u001b[32m---> \u001b[39m\u001b[32m24\u001b[39m \u001b[43mtime\u001b[49m\u001b[43m.\u001b[49m\u001b[43msleep\u001b[49m\u001b[43m(\u001b[49m\u001b[43minterval_seconds\u001b[49m\u001b[43m)\u001b[49m\n",
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"\u001b[31mKeyboardInterrupt\u001b[39m: "
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]
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}
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],
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"source": [
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"periodic_task(interval_seconds=REFRESH)"
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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": null,
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"id": "be0a7bfd-dc2a-437a-8fa6-ffb78cdd2687",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "virtualship",
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"language": "python",
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"name": "virtualship"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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