Dev

CITATION.cff

@@ -17,8 +17,8 @@ authors:
 repository-code: >-
   https://github.com/pythonhealthdatascience/pydesrap_stroke
 abstract: >-
-  Applying the Python DES RAP Template to the Stroke Capacity Planning Model
-  from Monks et al. 2016.
+  Reproducible analytical pipeline (RAP) for python discrete-event simulation
+  (DES) implementing the Stroke Capacity Planning Model from Monks et al. 2016.
 license: MIT
 version: '0.1.0'
 date-released: '2025-06-02'

docs/stress_des.md

@@ -41,4 +41,4 @@ Answers to this checklist, and the diagram used, are copied and/or adapted from
 | **5.3 Model execution**<br>State the event processing mechanism used e.g. three phase, event, activity, process interaction.<br>*Note that in some commercial software the event processing mechanism may not be published. In these cases authors should adhere to item 5.1 software recommendations.*<br>State all priority rules included if entities/activities compete for resources.<br>If the model is parallel, distributed and/or use grid or cloud computing, etc., state and preferably reference the technology used.  For parallel and distributed simulations the time management algorithms used.  If the HLA is used then state the version of the standard, which run-time infrastructure (and version), and any supporting documents (FOMs, etc.) | `simpy` implements a process based simulation worldview. |
 | **5.4 System specification**<br>State the model run time and specification of hardware used.  This is particularly important for large scale models that require substantial computing power.  For parallel, distributed and/or use grid or cloud computing, etc. state the details of all systems used in the implementation (processors, network, etc.) | Intel Core i7-12700H with 32GB RAM running Ubuntu 24.04.1 Linux.  |
 | **Code access** |
-| **6.1 Computer model sharing statement**<br>Describe how someone could obtain the model described in the paper, the simulation software and any other associated software (or hardware) needed to reproduce the results.  Provide, where possible, the link and DOIs to these. | TODO. |
+| **6.1 Computer model sharing statement**<br>Describe how someone could obtain the model described in the paper, the simulation software and any other associated software (or hardware) needed to reproduce the results.  Provide, where possible, the link and DOIs to these. | Code is provided in https://github.com/pythonhealthdatascience/pydesrap_stroke, and archived on Zenodo: https://doi.org/10.5281/zenodo.15574906 |

environment.yaml

@@ -1,4 +1,4 @@
-name: stroke-rap-python
+name: pydesrapstroke
 channels:
   - conda-forge
 dependencies:
@@ -19,6 +19,6 @@ dependencies:
   - rich=13.9.4
   - simpy=4.1.1
   - pip:
-    - kaleido==0.2.1
+    - kaleido==1.0.0
     - sim-tools==0.8.0
     - -e .[dev]

notebooks/analysis.ipynb

@@ -5649,7 +5649,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Notebook run time: 0m 10s\n"
+      "Notebook run time: 0m 16s\n"
      ]
     }
    ],
@@ -5665,7 +5665,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "stroke-rap-python",
+   "display_name": "pydesrapstroke",
    "language": "python",
    "name": "python3"
   },