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Oct 10, 2024
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4 changes: 2 additions & 2 deletions content/02_basic_simpy.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -53,7 +53,7 @@
"\n",
"In this first example, let's assume (unrealistically) that prescriptions arrive **exactly** 5 minutes apart.\n",
"\n",
"![Pharmacy with prescriptions every 5 minutes](../img/pharmacy.png)\n",
"![Pharmacy with prescriptions every 5 minutes](./img/pharmacy.png)\n",
"\n",
"## 4. The model building blocks\n",
"\n",
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.1.undefined"
"version": "3.12.6"
}
},
"nbformat": 4,
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4 changes: 2 additions & 2 deletions content/04_111_model.ipynb
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Expand Up @@ -39,7 +39,7 @@
"\n",
"Call operators in an 111 (urgent care) service receive calls at a rate of 100 per hour. Call length can be represented by a triangular distribution. Calls last between 5 minutes and 15 minutes. Most calls last 7 minutes. There are 13 call operators.\n",
"\n",
"![Call Centre Diagram](../img/callcentre.png)"
"![Call Centre Diagram](./img/callcentre.png)"
]
},
{
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.10"
"version": "3.12.6"
}
},
"nbformat": 4,
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4 changes: 2 additions & 2 deletions content/05_basic_results.ipynb
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Expand Up @@ -52,7 +52,7 @@
"* 😊 An advantage of this strategy is that it is very **simple**, captures all data, and has minimal computational overhead during a model run!\n",
"* 😢 A potential disadvantage is that for complex simulation you may end up storing a **large amount of data in memory**. In these circumstances, it may be worth exploring event driven strategies to reduce memory requirements.\n",
"\n",
"![](../img/callcentre_waittime.png)\n",
"![](./img/callcentre_waittime.png)\n",
"\n",
"In our example, we will:\n",
"\n",
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.10"
"version": "3.12.6"
}
},
"nbformat": 4,
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