diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml index 8c40d97..ed94595 100644 --- a/.github/workflows/tests.yaml +++ b/.github/workflows/tests.yaml @@ -1,42 +1,47 @@ -# This file runs the tests in `tests/` -# They will run in parallel, and run on three operating systems: -# Ubuntu, Windows and Mac. - name: tests on: push: branches: [main] workflow_dispatch: + inputs: + operating_systems: + description: 'Operating systems to test on' + type: choice + default: 'all' + options: + - all + - ubuntu-latest + - windows-latest + - macos-latest jobs: - - # Run tests on Ubuntu - tests-on-ubuntu: + # Generate matrix based on input + setup-matrix: runs-on: ubuntu-latest + outputs: + matrix: ${{ steps.set-matrix.outputs.matrix }} steps: - - - name: Check out repository - uses: actions/checkout@v4 - - - name: Install python and dependencies - uses: actions/setup-python@v4 - with: - python-version: '3.13' - cache: 'pip' - - run: pip install -r requirements.txt - - - name: Run tests - run: pytest - - - name: List the environment variables - run: env - - # Run tests on Windows - tests-on-windows: - runs-on: windows-latest + - name: Set matrix + id: set-matrix + run: | + if [[ "${{ inputs.operating_systems }}" == "all" || "${{ github.event_name }}" == "push" ]]; then + echo 'matrix=["ubuntu-latest", "windows-latest", "macos-latest"]' >> $GITHUB_OUTPUT + else + echo 'matrix=["${{ inputs.operating_systems }}"]' >> $GITHUB_OUTPUT + fi + + # Run tests using matrix strategy + tests: + permissions: + contents: write + needs: setup-matrix + runs-on: ${{ matrix.os }} + strategy: + matrix: + os: ${{ fromJSON(needs.setup-matrix.outputs.matrix) }} + steps: - - name: Check out repository uses: actions/checkout@v4 @@ -45,31 +50,42 @@ jobs: with: python-version: '3.13' cache: 'pip' - - run: python -m pip install -r requirements.txt - - - name: Run tests - run: pytest - - - name: List the environment variables - run: env - - # Run tests on Mac - tests-on-macos: - runs-on: macos-latest - steps: - - - name: Check out repository - uses: actions/checkout@v4 - - - name: Install python and dependencies - uses: actions/setup-python@v4 + + - name: Install requirements (Windows) + if: runner.os == 'Windows' + run: python -m pip install -r requirements.txt + + - name: Install requirements (Unix) + if: runner.os != 'Windows' + run: pip install -r requirements.txt + + - name: Run tests (with coverage for linux) + run: | + if [ "${{ matrix.os }}" = "ubuntu-latest" ]; then + pytest --cov --cov-report=xml + else + pytest + fi + shell: bash + + - name: Generate coverage badge (for-the-badge style) + if: matrix.os == 'ubuntu-latest' + run: genbadge coverage -i coverage.xml -o images/coverage-badge.svg + + - name: Upload coverage badge + if: matrix.os == 'ubuntu-latest' + uses: actions/upload-artifact@v4 with: - python-version: '3.13' - cache: 'pip' - - run: pip install -r requirements.txt - - - name: Run tests - run: pytest - - - name: List the environment variables - run: env \ No newline at end of file + name: coverage-badge + path: images/coverage-badge.svg + + - name: Commit coverage badge + if: matrix.os == 'ubuntu-latest' + run: | + git config --local user.email "github-actions[bot]@users.noreply.github.com" + git config --local user.name "github-actions[bot]" + git add images/coverage-badge.svg + git commit -m "ci(tests): update coverage badge" || echo "No changes to commit" + git push + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} \ No newline at end of file diff --git a/CITATION.cff b/CITATION.cff index f63a922..b8a462d 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -14,6 +14,11 @@ authors: email: a.heather2@exeter.ac.uk affiliation: University of Exeter orcid: 'https://orcid.org/0000-0002-6596-3479' + - given-names: Thomas + family-names: Monks + email: t.m.w.monks@exeter.ac.uk + affiliation: University of Exeter + orcid: 'https://orcid.org/0000-0003-2631-4481' repository-code: >- https://github.com/pythonhealthdatascience/pydesrap_stroke abstract: >- diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md new file mode 100644 index 0000000..4455894 --- /dev/null +++ b/CODE_OF_CONDUCT.md @@ -0,0 +1,128 @@ + +# Contributor Covenant Code of Conduct + +## Our Pledge + +We as members, contributors, and leaders pledge to make participation in our +community a harassment-free experience for everyone, regardless of age, body +size, visible or invisible disability, ethnicity, sex characteristics, gender +identity and expression, level of experience, education, socio-economic status, +nationality, personal appearance, race, caste, color, religion, or sexual +identity and orientation. + +We pledge to act and interact in ways that contribute to an open, welcoming, +diverse, inclusive, and healthy community. + +## Our Standards + +Examples of behavior that contributes to a positive environment for our +community include: + +- Demonstrating empathy and kindness toward other people +- Being respectful of differing opinions, viewpoints, and experiences +- Giving and gracefully accepting constructive feedback +- Accepting responsibility and apologizing to those affected by our mistakes, + and learning from the experience +- Focusing on what is best not just for us as individuals, but for the overall + community + +Examples of unacceptable behavior include: + +- The use of sexualized language or imagery, and sexual attention or advances of + any kind +- Trolling, insulting or derogatory comments, and personal or political attacks +- Public or private harassment +- Publishing others' private information, such as a physical or email address, + without their explicit permission +- Other conduct which could reasonably be considered inappropriate in a + professional setting + +## Enforcement Responsibilities + +Community leaders are responsible for clarifying and enforcing our standards of +acceptable behavior and will take appropriate and fair corrective action in +response to any behavior that they deem inappropriate, threatening, offensive, +or harmful. + +Community leaders have the right and responsibility to remove, edit, or reject +comments, commits, code, wiki edits, issues, and other contributions that are +not aligned to this Code of Conduct, and will communicate reasons for moderation +decisions when appropriate. + +## Scope + +This Code of Conduct applies within all community spaces, and also applies when +an individual is officially representing the community in public spaces. +Examples of representing our community include using an official email address, +posting via an official social media account, or acting as an appointed +representative at an online or offline event. + +## Enforcement + +Instances of abusive, harassing, or otherwise unacceptable behavior may be +reported to the community leaders responsible for enforcement at +[INSERT CONTACT METHOD]. +All complaints will be reviewed and investigated promptly and fairly. + +All community leaders are obligated to respect the privacy and security of the +reporter of any incident. + +## Enforcement Guidelines + +Community leaders will follow these Community Impact Guidelines in determining +the consequences for any action they deem in violation of this Code of Conduct: + +### 1. Correction + +**Community Impact**: Use of inappropriate language or other behavior deemed +unprofessional or unwelcome in the community. + +**Consequence**: A private, written warning from community leaders, providing +clarity around the nature of the violation and an explanation of why the +behavior was inappropriate. A public apology may be requested. + +### 2. Warning + +**Community Impact**: A violation through a single incident or series of +actions. + +**Consequence**: A warning with consequences for continued behavior. No +interaction with the people involved, including unsolicited interaction with +those enforcing the Code of Conduct, for a specified period of time. This +includes avoiding interactions in community spaces as well as external channels +like social media. Violating these terms may lead to a temporary or permanent +ban. + +### 3. Temporary Ban + +**Community Impact**: A serious violation of community standards, including +sustained inappropriate behavior. + +**Consequence**: A temporary ban from any sort of interaction or public +communication with the community for a specified period of time. No public or +private interaction with the people involved, including unsolicited interaction +with those enforcing the Code of Conduct, is allowed during this period. +Violating these terms may lead to a permanent ban. + +### 4. Permanent Ban + +**Community Impact**: Demonstrating a pattern of violation of community +standards, including sustained inappropriate behavior, harassment of an +individual, or aggression toward or disparagement of classes of individuals. + +**Consequence**: A permanent ban from any sort of public interaction within the +community. + +## Attribution + +This Code of Conduct is adapted from the +[Contributor Covenant](https://www.contributor-covenant.org/), version 2.1, +available at +. + +Community Impact Guidelines were inspired by +[Mozilla's code of conduct enforcement ladder](https://github.com/mozilla/inclusion). + +For answers to common questions about this code of conduct, see the FAQ at +. Translations are available at +. diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 3c5dc47..6e69202 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -1,16 +1,143 @@ # Contributing -πŸŽ‰ Thank you for checking out our project! πŸŽ‰ +Thank you for your interest in contributing! πŸ€— -This file contains guidelines on how to get in touch with us and potentially contribute towards this repository. +This file covers: -## Email +* 🐞 Workflow for bug reports, feature requests and documentation improvements +* πŸš€ Workflow for code contributions (bug fixes, enhancements) +* πŸ› οΈ Development and testing +* πŸ“¦ Updating the package +* 🀝 Code of conduct -You can contact the researchers on this project using the provided email addresses in `CITATION.cff`. +
-## Suggesting changes +## 🐞 Workflow for bug reports, feature requests and documentation improvements -If you spot an issue, you are welcome to raise this either by: +Before opening an issue, please search [existing issues](https://github.com/pythonhealthdatascience/pydesrap_stroke/issues) to avoid duplicates. If an issue exists, you can add a comment with additional details and/or upvote (πŸ‘) the issue. If there is not an existing issue, please open one and provide as much detail as possible. -* Using **GitHub Issues**. -* **Forking** the repository, make your changes and submit a pull request for review. \ No newline at end of file +* **For feature requests or documentation improvements**, please describe your suggestion clearly. +* **For bugs**, include: + * Steps to reproduce. + * Expected and actual behaviour. + * Environment details (operating system, python version, dependencies). + * Relevant files (e.g. problematic `.qmd` files). + +### Handling bug reports (for maintainers): + +* Confirm reproducibility by following the reported steps. +* Label the issue appropriately (e.g. `bug`). +* Request additional information if necessary. +* Link related issues or pull requests. +* Once resolved, close the issue with a brief summary of the fix. + +
+ +## πŸš€ Workflow for code contributions (bug fixes, enhancements) + +1. Fork the repository and clone your fork. + +2. Create a new branch for your feature or fix: + +```{.bash} +git checkout -b my-feature +``` + +3. Make your changes and commit them with clear, descriptive messages using the [conventional commits standard](https://www.conventionalcommits.org/en/v1.0.0/). + +4. Push your branch to your fork: + +```{.bash} +git push origin my-feature +``` + +5. Open a pull request against the main branch. Describe your changes and reference any related issues. + +
+ +## πŸ› οΈ Development and testing + +### Dependencies + +Set up the Python environment using `conda` (recommended): + +``` +conda env create --file environment.yaml +conda activate +``` + +There is also a `requirements.txt` file which can be used to set up the environment with `virtualenv`, but this won't fetch a specific version of Python - so please note the version listed in `environment.yaml`. + +
+ +### Docstrings + +We follow the [numpydoc](https://numpydoc.readthedocs.io/en/latest/format.html) style for docstrings. + +
+ +### Tests + +Run all tests (with coverage): + +```{.bash} +pytest --cov +``` + +Run tests in parallel: + +```{.bash} +pytest -n auto +``` + +Run an individual test file: + +```{.bash} +pytest tests/testfile.py +``` + +Run a specific test: + +```{.bash} +pytest tests/testfile.py::testname +``` + +
+ +### Linting + +Lint all files: + +```{.bash} +bash lint.sh +``` + +Lint a specific `.py` file: + +```{.bash} +pylint simulation/model.py +``` + +Lint a specific `.ipynb` file: + +```{.bash} +nbqa pylint notebooks/analysis.ipynb +``` + +
+ +## πŸ“¦ Updating the package + +If you are a maintainer and need to publish a new release: + +1. Update the `CHANGELOG.md`. + +2. Update the version number in `simulation/__init__.py` and `CITATION.cff`, and update the date in `CITATION.cff`. + +3. Create a release on GitHub, which will automatically archive to Zenodo. + +
+ +## 🀝 Code of conduct + +Please be respectful and considerate. See the [code of conduct](https://github.com/pythonhealthdatascience/pydesrap_stroke/blob/main/CODE_OF_CONDUCT.md) for details. \ No newline at end of file diff --git a/README.md b/README.md index ca5fc19..eb1064b 100644 --- a/README.md +++ b/README.md @@ -7,11 +7,11 @@ [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.15574906.svg)](https://doi.org/10.5281/zenodo.15574906) [![Tests](https://github.com/pythonhealthdatascience/pydesrap_stroke/actions/workflows/tests.yaml/badge.svg)](https://github.com/pythonhealthdatascience/pydesrap_stroke/actions/workflows/tests.yaml) [![Linting](https://github.com/pythonhealthdatascience/pydesrap_stroke/actions/workflows/lint.yaml/badge.svg)](https://github.com/pythonhealthdatascience/pydesrap_stroke/actions/workflows/lint.yaml) -[![ORCID](https://img.shields.io/badge/ORCID_Amy_Heather-0000--0002--6596--3479-A6CE39?&logo=orcid&logoColor=white)](https://orcid.org/0000-0002-6596-3479) +[![Coverage](https://github.com/pythonhealthdatascience/pydesrap_stroke/raw/main/images/coverage-badge.svg)](https://github.com/pythonhealthdatascience/pydesrap_stroke/actions/workflows/tests.yaml) -This repository applies the [Python DES RAP Template](https://github.com/pythonhealthdatascience/pydesrap_mms) to a real-life example: +This repository provides a reproducible analytical pipeline (RAP) that implements a real-life stroke service capacity planning model in python. It serves as a practical example, fully reproducible and aligned with RAP principles, based on the following study: > Monks T, Worthington D, Allen M, Pitt M, Stein K, James MA. A modelling tool for capacity planning in acute and community stroke services. BMC Health Serv Res. 2016 Sep 29;16(1):530. doi: [10.1186/s12913-016-1789-4](https://doi.org/10.1186/s12913-016-1789-4). PMID: 27688152; PMCID: PMC5043535. @@ -30,16 +30,14 @@ git clone https://github.com/pythonhealthdatascience/pydesrap_stroke.git cd pydesrap_stroke ``` -Use the provided `environment.yaml` file to set up a Python environment with `conda`: +Set up the Python environment using `conda` (recommended): ``` conda env create --file environment.yaml conda activate ``` -The provided `environment.yaml` file is a snapshot of the environment used when creating the repository, including specific package versions. You can update this file if necessary, but be sure to test that everything continues to work as expected after any updates. Also note that some dependencies are not required for modelling, but instead served other purposes, like running `.ipynb` files and linting. - -As an alternative, a `requirements.txt` file is provided which can be used to set up the environment with `virtualenv`. This is used by GitHub actions, which run much faster with a virtual environment than a conda environment. However, we recommend locally installing the environment using conda, as it will also manage the Python version for you. If using `virtualenv`, it won't fetch a specific version of Python - so please note the version listed in `environment.yaml`. +There is also a `requirements.txt` file which can be used to set up the environment with `virtualenv`, but this won't fetch a specific version of Python - so please note the version listed in `environment.yaml`.
@@ -115,13 +113,19 @@ The other notebooks generate results for tests and illustrate other functionalit
+## Community + +Curious about contributing? Check out the [contributing guidelines](CONTRIBUTING.md) to learn how you can help. + +
+ ## Citation For this applied example, please cite either: -> Heather, A. (2025). Stroke capacity planning model: python DES RAP. GitHub. https://github.com/pythonhealthdatascience/pydesrap_stroke. +> Heather, A. Monks, T. (2025). Stroke capacity planning model: python DES RAP. GitHub. https://github.com/pythonhealthdatascience/pydesrap_stroke. > -> Heather, A. (2025). Stroke capacity planning model: python DES RAP. Zenodo. https://doi.org/10.5281/zenodo.15574906. +> Heather, A. Monks, T. (2025). Stroke capacity planning model: python DES RAP. Zenodo. https://doi.org/10.5281/zenodo.15574906. A `CITATION.cff` file is also provided. @@ -132,6 +136,11 @@ A `CITATION.cff` file is also provided. * [![ORCID](https://img.shields.io/badge/ORCID-0000--0002--6596--3479-A6CE39?style=for-the-badge&logo=orcid&logoColor=white)](https://orcid.org/0000-0002-6596-3479) * [![GitHub](https://img.shields.io/badge/GitHub-amyheather-181717?style=for-the-badge&logo=github&logoColor=white)](https://github.com/amyheather) +**Tom Monks** - peer review of the repository. + +* [![ORCID](https://img.shields.io/badge/ORCID-0000--0003--2631--4481-A6CE39?style=for-the-badge&logo=orcid&logoColor=white)](https://orcid.org/0000-0003-2631-4481) +* [![GitHub](https://img.shields.io/badge/GitHub-TomMonks-181717?style=for-the-badge&logo=github&logoColor=white)](https://github.com/TomMonks) +
## Licence diff --git a/docs/stress_des.md b/docs/stress_des.md index 7a149c3..d20335d 100644 --- a/docs/stress_des.md +++ b/docs/stress_des.md @@ -6,20 +6,20 @@ This checklist describes the study: > Monks T, Worthington D, Allen M, Pitt M, Stein K, James MA. A modelling tool for capacity planning in acute and community stroke services. BMC Health Serv Res. 2016 Sep 29;16(1):530. doi: [10.1186/s12913-016-1789-4](https://doi.org/10.1186/s12913-016-1789-4). PMID: 27688152; PMCID: PMC5043535. -Answers to this checklist, and the diagram used, are copied and/or adapted from [llm_simpy/notebooks/03_stroke/00_stress/](https://github.com/pythonhealthdatascience/llm_simpy/tree/main/notebooks/03_stroke/00_stress), which is shared under an MIT licence by: +Answers to this checklist are adapted from [llm_simpy/notebooks/03_stroke/00_stress/](https://github.com/pythonhealthdatascience/llm_simpy/tree/main/notebooks/03_stroke/00_stress), which is shared under an MIT licence by: > Monks, T., Harper, A., & Heather, A. (2025). Unlocking the Potential of Past Research: Using Generative AI to Reconstruct Healthcare Simulation Models. GitHub. https://github.com/pythonhealthdatascience/llm_simpy. | **Item** | **Description** | | - | - | | **Objectives** | -| **1.1 Purpose of the model**
Explain the background and objectives for the model | The simulation model provides capacity planning tools for acute stroke and rehabilitation units across a shared service that cares for Stroke, TIA, Complex Neurology and other types of neurological dependency patients. It guides users on the likelihood that a given capacity will cause admission delays. | -| **1.2 Model outputs**
Define all quantitative performance measures that are reported, using equations where necessary. Specify how and when they are calculated during the model run along with how any measures of error such as confidence intervals are calculated. | At the end of a model run the following is calculated:
・ The probability of delay - p(delay) - in admission to an Acute Stroke Unit by bed numbers.
・ The probability of delay - p(delay) - in admission to a Rehabilitation Unit by bed numbers.
・ The reciprocal of p(delay) for both ASU and Rehab. Interpreted as 1 in every n patients is delayed.
・ The occupancy distribution of the Acute Stroke Unit.
・ The occupancy distribution of the Rehabilitation Unit
The probability of delay is calculated as follows: `P(N=n)/P(<=n)` | -| **1.3 Experimentation aims**
If the model has been used for experimentation, state the objectives that it was used to investigate.
(A) Scenario based analysis – Provide a name and description for each scenario, providing a rationale for the choice of scenarios and ensure that item 2.3 (below) is completed.
(B) Design of experiments – Provide details of the overall design of the experiments with reference to performance measures and their parameters (provide further details in data below).
(C) Simulation Optimisation – (if appropriate) Provide full details of what is to be optimised, the parameters that were included and the algorithm(s) that was be used. Where possible provide a citation of the algorithm(s). | This is an infinite server model. A single scenario is run, given set of arrival and length of stay parameters, to produce a distribution of outputs. | +| **1.1 Purpose of the model**
Explain the background and objectives for the model | The simulation model helps plan bed capacity for acute stroke and rehabilitation units by showing how different patient groups (stroke, TIA, complex neurology, and others) use beds and how changes in capacity or patient flow affect admission delays. | +| **1.2 Model outputs**
Define all quantitative performance measures that are reported, using equations where necessary. Specify how and when they are calculated during the model run along with how any measures of error such as confidence intervals are calculated. | At the end of each simulation run, the model calculates:
・ **Probability of admission delay** to the Acute Stroke Unit and Rehabilitation Unit for each tested bed capacity (p(delay)).
・ **"1 in n" metric**: how often a delay occurs (reciprocal of probability).
・ **Occupancy distributions** for both units (frequency of different occupancy levels over time).
Delay probability is calculated as `P(N=n)/P(<=n)`, where N is the number of occupied beds. | +| **1.3 Experimentation aims**
If the model has been used for experimentation, state the objectives that it was used to investigate.
(A) Scenario based analysis – Provide a name and description for each scenario, providing a rationale for the choice of scenarios and ensure that item 2.3 (below) is completed.
(B) Design of experiments – Provide details of the overall design of the experiments with reference to performance measures and their parameters (provide further details in data below).
(C) Simulation Optimisation – (if appropriate) Provide full details of what is to be optimised, the parameters that were included and the algorithm(s) that was be used. Where possible provide a citation of the algorithm(s). | This is an infinite server simulation, where every patient is admitted immediately and there is no queue. Each scenario uses set arrival and length-of-stay parameters to generate occupancy distributions. Users can explore different scenarios - like increased demand, bed pooling, or subgroup removal - by adjusting these inputs and analysing key outcomes. | | **Logic** | | **2.1 Base model overview diagram**
Describe the base model using appropriate diagrams and description. This could include one or more process flow, activity cycle or equivalent diagrams sufficient to describe the model to readers. Avoid complicated diagrams in the main text. The goal is to describe the breadth and depth of the model with respect to the system being studied. | ![Logic diagram](../images/stroke_rehab_design.png) | -| **2.2 Base model logic**
Give details of the base model logic. Give additional model logic details sufficient to communicate to the reader how the model works. | The model allows users to specify a population of stroke, transient ischaemic attack (TIA; or mini-stroke), complex neurological, and other patient types that use acute and rehabilitation services. The patient classes have their own external inter-arrival distributions to acute and rehabilitation services, transfer probabilities between services and length of stay distributions (where first sub division occurs to model ESD versus non-ESD patients). The model takes an infinite capacity approach to capacity planning and estimates the probability of delay. A warm-up period and multiple replications are employed. The ESD modelling is not documented in the article we therefore chose to simplify the design and focus on the acute stroke and rehabilitation units; although we aimed for model setup to be simple to extend for ESD capacity modelling. | -| **2.3 Scenario logic**
Give details of the logical difference between the base case model and scenarios (if any). This could be incorporated as text or where differences are substantial could be incorporated in the same manner as 2.2. | Only a single scenario is included in this recreation experiment. To recreate the original paper’s increased demand scenarios the inter-arrival times could be increased in the `Experiment` class. | +| **2.2 Base model logic**
Give details of the base model logic. Give additional model logic details sufficient to communicate to the reader how the model works. | The model lets users define populations of stroke, TIA, complex neurology, and other patients, each with their own arrival patterns, transfer probabilities, and length-of-stay distributions for acute and rehab services. It uses an infinite capacity approach to estimate admission delay probability. The design focuses on acute and rehab units, with a warm-up period and multiple replications; ESD pathways are simplified but the model can be extended to include them. | +| **2.3 Scenario logic**
Give details of the logical difference between the base case model and scenarios (if any). This could be incorporated as text or where differences are substantial could be incorporated in the same manner as 2.2. | Scenarios are defined by changing input parameters (e.g., admissions rates, bed numbers, patient groups) and re-running the model; no code changes are required. All scenarios from the original publication are implemented:
・**Base Case:** Default parameter values.
・ **Increased Demand:** 5% higher acute admissions.
・ **Pooling Beds:** Combines/reallocates bed numbers between acute and rehab units.
・ **Patient Group Removal:** Runs without complex neurological patients to isolate impact. | | **2.4 Algorithms**
Provide further detail on any algorithms in the model that (for example) mimic complex or manual processes in the real world (i.e. scheduling of arrivals/ appointments/ operations/ maintenance, operation of a conveyor system, machine breakdowns, etc.). Sufficient detail should be included (or referred to in other published work) for the algorithms to be reproducible. Pseudo-code may be used to describe an algorithm. | There are no algorithms used in this model. | | **2.5.1 Components - entities**
Give details of all entities within the simulation including a description of their role in the model and a description of all their attributes. | ・ Stroke
・ Transient Ischemic Attack (TIA - minor strokes with rapidly resolving symptoms)
・ Complex Neurological
・ Other (including medical outliers) | | **2.5.2 Components - activities**
Describe the activities that entities engage in within the model. Provide details of entity routing into and out of the activity. | ASU + rehab treatment activities:
・ Stroke patients who are eligible for Early Supported Discharge
・ Stroke patients who are **NOT** eligible for Early Supported Discharge
・ TIA
・ Other | @@ -27,18 +27,18 @@ Answers to this checklist, and the diagram used, are copied and/or adapted from | **2.5.4 Components - queues**
Give details of the assumed queuing discipline used in the model (e.g. First in First Out, Last in First Out, prioritisation, etc.). Where one or more queues have a different discipline from the rest, provide a list of queues, indicating the queuing discipline used for each. If reneging, balking or jockeying occur, etc., provide details of the rules. Detail any delays or capacity constraints on the queues. | ・ None | | **2.5.5 Components - entry/exit points**
Give details of the model boundaries i.e. all arrival and exit points of entities. Detail the arrival mechanism (e.g. β€˜thinning’ to mimic a non-homogenous Poisson process or balking) | ・ Each patient class has an ASU arrival process with its own distribution and parameters.
・ A proportion of ASU patients exit the model after acute treatment is complete.
・ Stroke, Complex Neurological and Other patients have an additional external Rehab arrival process with its own distribution and parameters.
・ All rehab patients exit the model when rehab is completed. | | **Data** | -| **3.1 Data sources**
List and detail all data sources. Sources may include:
β€’ Interviews with stakeholders,
β€’ Samples of routinely collected data,
β€’ Prospectively collected samples for the purpose of the simulation study,
β€’ Public domain data published in either academic or organisational literature. Provide, where possible, the link and DOI to the data or reference to published literature.
All data source descriptions should include details of the sample size, sample date ranges and use within the study. | All data is sourced from the 2016 publication in the Health Services Research: Monks T, Worthington D, Allen M, Pitt M, Stein K, James MA. A modelling tool for capacity planning in acute and community stroke services. BMC Health Serv Res. 2016 Sep 29;16(1):530. doi: 10.1186/s12913-016-1789-4. PMID: 27688152; PMCID: PMC5043535.
In [Monks et al. (2016)](http://doi.org/10.1186/s12913-016-1789-4) they state: "*The model was constructed using anonymised administrative data collected routinely by the healthcare provider in the acute and community settings.*" | -| **3.2 Pre-processing**
Provide details of any data manipulation that has taken place before its use in the simulation, e.g. interpolation to account for missing data or the removal of outliers. | No additional pre-processing of data was undertaken. This was conducted in the original study.
In [Monks et al. (2016)](http://doi.org/10.1186/s12913-016-1789-4) they state: "*All patients had a recorded primary diagnosis using ICD-10 coding. These codes were grouped into a simpler coding scheme of stroke (ischemic or haemorrhagic), TIA, complex neurological and other. The β€˜other’ category represents medical patients who are displaced into the stroke units due to capacity constraints elsewhere in the hospital.*" | +| **3.1 Data sources**
List and detail all data sources. Sources may include:
β€’ Interviews with stakeholders,
β€’ Samples of routinely collected data,
β€’ Prospectively collected samples for the purpose of the simulation study,
β€’ Public domain data published in either academic or organisational literature. Provide, where possible, the link and DOI to the data or reference to published literature.
All data source descriptions should include details of the sample size, sample date ranges and use within the study. | All base-case parameter values (arrival rates, length-of-stay, routing probabilities) are sourced from Monks T. et al. (2016, BMC Health Serv Res). They state: "*The model was constructed using anonymised administrative data collected routinely by the healthcare provider in the acute and community settings.*" | +| **3.2 Pre-processing**
Provide details of any data manipulation that has taken place before its use in the simulation, e.g. interpolation to account for missing data or the removal of outliers. | No additional pre-processing of data was undertaken. This was conducted in Monks T. et al. (2016, BMC Health Serv Res). They state: "*All patients had a recorded primary diagnosis using ICD-10 coding. These codes were grouped into a simpler coding scheme of stroke (ischemic or haemorrhagic), TIA, complex neurological and other. The β€˜other’ category represents medical patients who are displaced into the stroke units due to capacity constraints elsewhere in the hospital.*" | | **3.3 Input parameters**
List all input variables in the model. Provide a description of their use and include parameter values. For stochastic inputs provide details of any continuous, discrete or empirical distributions used along with all associated parameters. Give details of all time dependent parameters and correlation.
Clearly state:
β€’ Base case data
β€’ Data use in experimentation, where different from the base case.
β€’ Where optimisation or design of experiments has been used, state the range of values that parameters can take.
β€’ Where theoretical distributions are used, state how these were selected and prioritised above other candidate distributions. | All sampling distributions are reported in the original paper. We did not make any additional assumptions.

**Arrivals and length of stay parameters**
β€’ ASU Arrivals: Stroke - Exponential(1.2 days)
β€’ ASU Arrivals: TIA - Exponential(9.3 days)
β€’ ASU Arrivals: Complex Neuro - Exponential(3.6 days)
β€’ ASU Arrivals: Other - Exponential(3.2 days)
β€’ Rehab Arrivals: Stroke - Exponential(21.8 days)
β€’ Rehab Arrivals: Complex Neuro - Exponential(31.7 days)
β€’ Rehab Arrivals: Other - Exponential(28.6 days)
β€’ ASU Length of Stay: Stroke No ESD - LogNormal(mean=7.4, sd=8.61)
β€’ ASU Length of Stay: Stroke ESD - LogNormal(mean=4.6, sd=4.8)
β€’ ASU Length of Stay: TIA - LogNormal(mean=1.8, sd=2.3)
β€’ ASU Length of Stay: Complex Neuro - LogNormal(mean=4.0, sd=5.0)
β€’ ASU Length of Stay: Other - LogNormal(mean=3.8, sd=5.2)
β€’ Rehab Length of Stay: Stroke No ESD - LogNormal(mean=28.4, sd=27.2)
β€’ Rehab Length of Stay: Stroke ESD - LogNormal(mean=30.3, sd=23.1)
β€’ Rehab Length of Stay: TIA - LogNormal(mean=18.7, sd=23.5)
β€’ Rehab Length of Stay: Complex Neuro - LogNormal(mean=27.6, sd=28.4)
β€’ Rehab Length of Stay: Other - LogNormal(mean=16.1, sd=14.1)

**Patient routing out of ASU**
A discrete distribution was used for each patient type with the following probabilities:
β€’ Rehab - stroke 24%, TIA 1%, complex neuro 11%, other 5%.
β€’ ESD - stroke 13%, TIA 1%, complex neuro 5%, other 10%
β€’ Other - stroke 63%, TIA 98%, complex neuro 84%, other 85%

**Patient routing out of rehab**
A discrete distribution was used for each patient type with the following probabilities:
β€’ ESD stroke 40%, TIA 0%, complex neuro 9%, other 13%
β€’ Other - stroke 60%, TIA 100%, complex neuro 91%, other 88%| -| **3.4 Assumptions**
Where data or knowledge of the real system is unavailable what assumptions are included in the model? This might include parameter values, distributions or routing logic within the model. | β€’ Monks et al. report that the model can be used to report results for ESD probability of delay and capacity.
β€’ No data are given for Length of stay in this service. Therefore we simplified the model to use ESD as an exit point. | +| **3.4 Assumptions**
Where data or knowledge of the real system is unavailable what assumptions are included in the model? This might include parameter values, distributions or routing logic within the model. | No additional model structure assumptions are made beyond those described in the main article for the subset of care steps implemented. ESD is modeled as an exit point as there are no LOS data for this service in the original publication. | | **Experimentation** | | **4.1 Initialisation**
Report if the system modelled is terminating or non-terminating. State if a warm-up period has been used, its length and the analysis method used to select it. For terminating systems state the stopping condition.
State what if any initial model conditions have been included, e.g., pre-loaded queues and activities. Report whether initialisation of these variables is deterministic or stochastic. | The model is a non-terminating system. It has a default warm-up of 3 years (365 days * 3). | | **4.2 Run length**
Detail the run length of the simulation model and time units. | The time units used in the model are days and a results collection period of 5 years (365 days * 5). | -| **4.3 Estimation approach**
State the method used to account for the stochasticity: For example, two common methods are multiple replications or batch means. Where multiple replications have been used, state the number of replications and for batch means, indicate the batch length and whether the batch means procedure is standard, spaced or overlapping. For both procedures provide a justification for the methods used and the number of replications/size of batches. | Multiple independent replications are employed to account for lack of independence. Common random numbers are employed between scenarios. A total of 150 replications are run for each experiment, but this number can be varied. | +| **4.3 Estimation approach**
State the method used to account for the stochasticity: For example, two common methods are multiple replications or batch means. Where multiple replications have been used, state the number of replications and for batch means, indicate the batch length and whether the batch means procedure is standard, spaced or overlapping. For both procedures provide a justification for the methods used and the number of replications/size of batches. | Multiple independent replications (n=150) are run, each with its own random seed. | | **Implementation** | -| **5.1 Software or programming language**
State the operating system and version and build number.
State the name, version and build number of commercial or open source DES software that the model is implemented in.
State the name and version of general-purpose programming languages used (e.g. Python 3.5).
Where frameworks and libraries have been used provide all details including version numbers. | The simulation model was developed using python 3.10 and simpy 4.1.1. Simpy details are here: https://simpy.readthedocs.io/en/latest/. A conda virtual environment is provided to manage versions on a local machine. | -| **5.2 Random sampling**
State the algorithm used to generate random samples in the software/programming language used e.g. Mersenne Twister.
If common random numbers are used, state how seeds (or random number streams) are distributed among sampling processes. | All sampling uses `numpy.random.Generator`. A `numpy` generator object implements the Permuted Congruential Generator 64-bit (PCG64; period = 2^128; maximum number of streams = 2^63).
Repeatable experiments and common random number streams are used in the model. A simple method is used to create streams are creating using multiple seeds. This does not guarantee, that streams are non overlapping. | -| **5.3 Model execution**
State the event processing mechanism used e.g. three phase, event, activity, process interaction.
*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.*
State all priority rules included if entities/activities compete for resources.
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**
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. | +| **5.1 Software or programming language**
State the operating system and version and build number.
State the name, version and build number of commercial or open source DES software that the model is implemented in.
State the name and version of general-purpose programming languages used (e.g. Python 3.5).
Where frameworks and libraries have been used provide all details including version numbers. | The simulation model was developed using python 3.13.1, `simpy` for DES logic, `sim-tools` for distributions, among others. All requirements are pinned in `environment.yaml` and `requirements.txt`, to support full reproducibility. Runs on Linux, macOS, and Windows. | +| **5.2 Random sampling**
State the algorithm used to generate random samples in the software/programming language used e.g. Mersenne Twister.
If common random numbers are used, state how seeds (or random number streams) are distributed among sampling processes. | All random sampling uses `numpy.random.Generator` (PCG64). Each replication and each distribution stream are assigned separate, deterministic seeds based on the run number to ensure repeatability and enable common random numbers. Streams are initialised with different seeds. | +| **5.3 Model execution**
State the event processing mechanism used e.g. three phase, event, activity, process interaction.
*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.*
State all priority rules included if entities/activities compete for resources.
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. Multiple replications are handled either sequentially or with parallelism (`Runner`, via `joblib.Parallel`). | +| **5.4 System specification**
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.) | Saved results and run times are from execution on Intel Core i7-12700H with 32GB RAM running Ubuntu 24.04.1 Linux. Hardware requirements are minimal; model is platform-agnostic. | | **Code access** | -| **6.1 Computer model sharing statement**
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 | +| **6.1 Computer model sharing statement**
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. | All simulation code is provided in on GitHub in [pythonhealthdatascience/pydesrap_stroke](https://github.com/pythonhealthdatascience/pydesrap_stroke), and archived on Zenodo: [10.5281/zenodo.15574906](https://doi.org/10.5281/zenodo.15574906). | diff --git a/environment.yaml b/environment.yaml index 610ced8..99af64c 100644 --- a/environment.yaml +++ b/environment.yaml @@ -14,11 +14,13 @@ dependencies: - plotly_express=0.4.1 - pylint=3.3.4 - pytest=8.3.4 + - pytest-cov=6.2.1 - pytest-xdist=3.6.1 - python=3.13.1 - rich=13.9.4 - simpy=4.1.1 - pip: + - genbadge==1.1.2 - kaleido==1.0.0 - - sim-tools==0.9.1 + - sim-tools==0.10.0 - -e .[dev] diff --git a/inputs/data_dictionary.md b/inputs/data_dictionary.md new file mode 100644 index 0000000..2748567 --- /dev/null +++ b/inputs/data_dictionary.md @@ -0,0 +1,59 @@ +# Data Dictionary: `parameters` JSON + +## Top-level key: `simulation_parameters` + +Type: `object` + +Description: Maps parameter names (str) to a specification describing how to sample from a statistical distribution for this metric in the simulation. + +## Structure summary + +Each item under `simulation_parameters` is itself an object with: + +* `class_name`: The name of the distribution class to use. +* `params`: An object containing parameters required by that distribution. + +## Parameter specification table + +| Field | Data type | Description | Example/Allowed values | +| - | - | - | - | +| Parameter name | str (object key) | Description name for the parameter: `__` | `asu_arrival_stroke`, `rehab_los_other`, `asu_routing_tia` | +| `class_name` | str | Statistical distribution for the parameter | `Exponential`, `Lognormal`, `DiscreteEmpricial` | +| `params ` | Object | Dictionary of parameters required to instantiate the distribution | See subsequent rows per distribution type | + +## Distribution-specific `params` field + +| `class_name` | Parameter key(s) | Data type | Description | Example values | +| - | - | - | - | - | +| `Exponential` | mean | float | Mean of exponential distribution | `1.2`, `9.3` | +| `Lognormal` | mean, stdev | float | Mean and standard deviation of lognormal distribution | `mean: 7.4`, `stdev: 8.61` | +| `DiscreteEmpirical` | values, freq | list (str/float) | Possible discrete values; corresponding probabilities or frequencies | `values: ["rehab", "esd", "other"]`, `freq: [0.24, 0.13, 0.63]` | + +## Glossary + +### Unit + +* `asu`: Acute Stroke Unit +* `rehab`: Rehabilitation Unit + +### Metric + +* `arrival`: Interarrival time (days between admissions) +* `los`: Length of stay (days in unit) +* `routing`: Probabilities of routing/discharge + +### Type + +For `iat`/`los`: + +* `stroke`: Stroke patients +* `tia`: Transient ischaemic attack patients +* `neuro`: Complex neurological patients +* `other`: Other patient types +* `stroke_noesd`, `stroke_esd`: Stroke patients split by whether they were transferred to early supported discharge (ESD). + +For `routing`: + +* `[diagnosis]_rehab`: Probability of transferring to rehabilitation unit +* `[diagnosis]_esd`: Probability of early supported discharge (ESD). +* `[diagnosis]_other`: Probability of other discharge pathways \ No newline at end of file diff --git a/notebooks/analysis.ipynb b/notebooks/analysis.ipynb index 6d8f109..f5120dd 100644 --- a/notebooks/analysis.ipynb +++ b/notebooks/analysis.ipynb @@ -189,12 +189,12 @@ "textposition": "auto", "type": "bar", "x": { - "bdata": "AAECAwQFBgcICQoLDA0ODxAREhMUFRYX", + "bdata": "AAECAwQFBgcICQoLDA0ODxAREhMUFRYXGA==", "dtype": "i1" }, "xaxis": "x", "y": { - "bdata": "YJBlozdkMz/1ed4Loq1kPwrPxZpANoM/vXVOZvyOmj8a9gZizGmrP8OheCrkZbY/9MZxHYN7vj/ROAVIv4DBP7fd04Y408E/tU7X9mLtvz+l0+tlZmm6P70Hgkf1K7M/u9Ne2QlKqj9TPAkivrKgPzwbXaH0PJM/6RW32pw1hT8WgTKPx6J1P4M5qbNPnmQ/89fufq9oVD/N3gFI1Ow9PzR5lLh9RzA/X7mIVs/lGD+YjpBC7ibzPibkgGqwpO4+", + "bdata": 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23.0\n", " \n", " \n", " 5\n", " asu\n", " 14\n", - " 0.019175\n", - " 52.0\n", - " 0.025806\n", + " 0.018720\n", + " 53.0\n", + " 0.025733\n", " 39.0\n", " \n", " \n", " 6\n", " rehab\n", " 10\n", - " 0.200564\n", + " 0.199945\n", " 5.0\n", - " 0.227341\n", + " 0.225089\n", " 4.0\n", " \n", " \n", " 7\n", " rehab\n", " 11\n", - " 0.150457\n", + " 0.149822\n", " 7.0\n", - " 0.172294\n", + " 0.171326\n", " 6.0\n", " \n", " \n", " 8\n", " rehab\n", " 12\n", - " 0.109370\n", + " 0.110139\n", " 9.0\n", - " 0.129282\n", + " 0.128463\n", " 8.0\n", " \n", " \n", " 9\n", " rehab\n", " 13\n", - " 0.076178\n", + " 0.076476\n", " 13.0\n", - " 0.092611\n", + " 0.093579\n", " 11.0\n", " \n", " \n", " 10\n", " rehab\n", " 14\n", - " 0.048879\n", - " 20.0\n", - " 0.062321\n", + " 0.051961\n", + " 19.0\n", + " 0.064323\n", " 16.0\n", " \n", " \n", " 11\n", " rehab\n", " 15\n", - " 0.029580\n", - " 34.0\n", - " 0.039036\n", - " 26.0\n", + " 0.032949\n", + " 30.0\n", + " 0.042301\n", + " 24.0\n", " \n", " \n", " 12\n", " rehab\n", " 16\n", - " 0.017972\n", - " 56.0\n", - " 0.024886\n", - " 40.0\n", + " 0.019671\n", + " 51.0\n", + " 0.026988\n", + " 37.0\n", " \n", " \n", "\n", @@ -4064,25 +4064,25 @@ ], "text/plain": [ " unit beds prob_delay_current 1_in_n_delay_current prob_delay_5% \\\n", - "0 asu 9 0.178431 6.0 0.201086 \n", - "1 asu 10 0.128621 8.0 0.146767 \n", - "2 asu 11 0.085391 12.0 0.102962 \n", - "3 asu 12 0.055308 18.0 0.069172 \n", - "4 asu 13 0.033938 29.0 0.043366 \n", - "5 asu 14 0.019175 52.0 0.025806 \n", - "6 rehab 10 0.200564 5.0 0.227341 \n", - "7 rehab 11 0.150457 7.0 0.172294 \n", - "8 rehab 12 0.109370 9.0 0.129282 \n", - "9 rehab 13 0.076178 13.0 0.092611 \n", - "10 rehab 14 0.048879 20.0 0.062321 \n", - "11 rehab 15 0.029580 34.0 0.039036 \n", - "12 rehab 16 0.017972 56.0 0.024886 \n", + "0 asu 9 0.181806 6.0 0.206046 \n", + "1 asu 10 0.127787 8.0 0.148402 \n", + "2 asu 11 0.084944 12.0 0.102303 \n", + "3 asu 12 0.055565 18.0 0.068525 \n", + "4 asu 13 0.032653 31.0 0.043014 \n", + "5 asu 14 0.018720 53.0 0.025733 \n", + "6 rehab 10 0.199945 5.0 0.225089 \n", + "7 rehab 11 0.149822 7.0 0.171326 \n", + "8 rehab 12 0.110139 9.0 0.128463 \n", + "9 rehab 13 0.076476 13.0 0.093579 \n", + "10 rehab 14 0.051961 19.0 0.064323 \n", + "11 rehab 15 0.032949 30.0 0.042301 \n", + "12 rehab 16 0.019671 51.0 0.026988 \n", "\n", " 1_in_n_delay_5% \n", "0 5.0 \n", "1 7.0 \n", "2 10.0 \n", - "3 14.0 \n", + "3 15.0 \n", "4 23.0 \n", "5 39.0 \n", "6 4.0 \n", @@ -4090,8 +4090,8 @@ "8 8.0 \n", "9 11.0 \n", "10 16.0 \n", - "11 26.0 \n", - "12 40.0 " + "11 24.0 \n", + "12 37.0 " ] }, "metadata": {}, @@ -4174,7 +4174,7 @@ " 2\n", " asu\n", " 11\n", - " 0.09\n", + " 0.08\n", " 12.0\n", " 0.10\n", " 10.0\n", @@ -4186,14 +4186,14 @@ " 0.06\n", " 18.0\n", " 0.07\n", - " 14.0\n", + " 15.0\n", " \n", " \n", " 4\n", " asu\n", " 13\n", " 0.03\n", - " 29.0\n", + " 31.0\n", " 0.04\n", " 23.0\n", " \n", @@ -4202,7 +4202,7 @@ " asu\n", " 14\n", " 0.02\n", - " 52.0\n", + " 53.0\n", " 0.03\n", " 39.0\n", " \n", @@ -4238,7 +4238,7 @@ " rehab\n", " 14\n", " 0.05\n", - " 20.0\n", + " 19.0\n", " 0.06\n", " 16.0\n", " \n", @@ -4247,18 +4247,18 @@ " rehab\n", " 15\n", " 0.03\n", - " 34.0\n", + " 30.0\n", " 0.04\n", - " 26.0\n", + " 24.0\n", " \n", " \n", " 12\n", " rehab\n", " 16\n", " 0.02\n", - " 56.0\n", - " 0.02\n", - " 40.0\n", + " 51.0\n", + " 0.03\n", + " 37.0\n", " \n", " \n", "\n", @@ -4268,30 +4268,30 @@ " unit beds prob_delay_current 1_in_n_delay_current prob_delay_5% \\\n", "0 asu 9 0.18 6.0 NaN \n", "1 asu 10 0.13 8.0 0.15 \n", - "2 asu 11 0.09 12.0 0.10 \n", + "2 asu 11 0.08 12.0 0.10 \n", "3 asu 12 0.06 18.0 0.07 \n", - "4 asu 13 0.03 29.0 0.04 \n", - "5 asu 14 0.02 52.0 0.03 \n", + "4 asu 13 0.03 31.0 0.04 \n", + "5 asu 14 0.02 53.0 0.03 \n", "6 rehab 10 0.20 5.0 NaN \n", "8 rehab 12 0.11 9.0 0.13 \n", "9 rehab 13 0.08 13.0 0.09 \n", - "10 rehab 14 0.05 20.0 0.06 \n", - "11 rehab 15 0.03 34.0 0.04 \n", - "12 rehab 16 0.02 56.0 0.02 \n", + "10 rehab 14 0.05 19.0 0.06 \n", + "11 rehab 15 0.03 30.0 0.04 \n", + "12 rehab 16 0.02 51.0 0.03 \n", "\n", " 1_in_n_delay_5% \n", "0 NaN \n", "1 7.0 \n", "2 10.0 \n", - "3 14.0 \n", + "3 15.0 \n", "4 23.0 \n", "5 39.0 \n", "6 NaN \n", "8 8.0 \n", "9 11.0 \n", "10 16.0 \n", - "11 26.0 \n", - "12 40.0 " + "11 24.0 \n", + "12 37.0 " ] }, "metadata": {}, @@ -4414,10 +4414,10 @@ " 1\n", " asu\n", " 11\n", - " 0.09\n", + " 0.08\n", " 12.0\n", " 0.05\n", - " 20.0\n", + " 21.0\n", " \n", " \n", " 2\n", @@ -4426,34 +4426,34 @@ " 0.06\n", " 18.0\n", " 0.03\n", - " 36.0\n", + " 37.0\n", " \n", " \n", " 3\n", " asu\n", " 13\n", " 0.03\n", - " 29.0\n", - " 0.02\n", - " 66.0\n", + " 31.0\n", + " 0.01\n", + " 67.0\n", " \n", " \n", " 4\n", " asu\n", " 14\n", " 0.02\n", - " 52.0\n", + " 53.0\n", " 0.01\n", - " 128.0\n", + " 139.0\n", " \n", " \n", " 5\n", " asu\n", " 15\n", " 0.01\n", - " 96.0\n", + " 97.0\n", " 0.00\n", - " 284.0\n", + " 290.0\n", " \n", " \n", " 6\n", @@ -4461,8 +4461,8 @@ " 12\n", " 0.11\n", " 9.0\n", - " 0.05\n", - " 19.0\n", + " 0.06\n", + " 18.0\n", " \n", " \n", " 7\n", @@ -4471,34 +4471,34 @@ " 0.08\n", " 13.0\n", " 0.03\n", - " 33.0\n", + " 30.0\n", " \n", " \n", " 8\n", " rehab\n", " 14\n", " 0.05\n", - " 20.0\n", + " 19.0\n", " 0.02\n", - " 61.0\n", + " 54.0\n", " \n", " \n", " 9\n", " rehab\n", " 15\n", " 0.03\n", - " 34.0\n", + " 30.0\n", " 0.01\n", - " 119.0\n", + " 105.0\n", " \n", " \n", " 10\n", " rehab\n", " 16\n", " 0.02\n", - " 56.0\n", - " 0.00\n", - " 231.0\n", + " 51.0\n", + " 0.01\n", + " 193.0\n", " \n", " \n", "\n", @@ -4507,29 +4507,29 @@ "text/plain": [ " unit beds prob_delay_current 1_in_n_delay_current \\\n", "0 asu 10 0.13 8.0 \n", - "1 asu 11 0.09 12.0 \n", + "1 asu 11 0.08 12.0 \n", "2 asu 12 0.06 18.0 \n", - "3 asu 13 0.03 29.0 \n", - "4 asu 14 0.02 52.0 \n", - "5 asu 15 0.01 96.0 \n", + "3 asu 13 0.03 31.0 \n", + "4 asu 14 0.02 53.0 \n", + "5 asu 15 0.01 97.0 \n", "6 rehab 12 0.11 9.0 \n", "7 rehab 13 0.08 13.0 \n", - "8 rehab 14 0.05 20.0 \n", - "9 rehab 15 0.03 34.0 \n", - "10 rehab 16 0.02 56.0 \n", + "8 rehab 14 0.05 19.0 \n", + "9 rehab 15 0.03 30.0 \n", + "10 rehab 16 0.02 51.0 \n", "\n", " prob_delay_no_complex_neuro 1_in_n_delay_no_complex_neuro \n", "0 0.08 13.0 \n", - "1 0.05 20.0 \n", - "2 0.03 36.0 \n", - "3 0.02 66.0 \n", - "4 0.01 128.0 \n", - "5 0.00 284.0 \n", - "6 0.05 19.0 \n", - "7 0.03 33.0 \n", - "8 0.02 61.0 \n", - "9 0.01 119.0 \n", - "10 0.00 231.0 " + "1 0.05 21.0 \n", + "2 0.03 37.0 \n", + "3 0.01 67.0 \n", + "4 0.01 139.0 \n", + "5 0.00 290.0 \n", + "6 0.06 18.0 \n", + "7 0.03 30.0 \n", + "8 0.02 54.0 \n", + "9 0.01 105.0 \n", + "10 0.01 193.0 " ] }, "metadata": {}, @@ -4604,326 +4604,353 @@ " \n", " 0\n", " 3\n", - " 1\n", - " 0.000004\n", - " 0.000004\n", + " 2\n", + " 0.000007\n", + " 0.000007\n", " 1.000000\n", " 1.0\n", " \n", " \n", " 1\n", " 4\n", - " 22\n", - " 0.000080\n", - " 0.000084\n", - " 0.956522\n", + " 18\n", + " 0.000066\n", + " 0.000073\n", + " 0.900000\n", " 1.0\n", " \n", " \n", " 2\n", " 5\n", - " 75\n", - " 0.000274\n", - " 0.000358\n", - " 0.765306\n", + " 43\n", + " 0.000157\n", + " 0.000230\n", + " 0.682540\n", " 1.0\n", " \n", " \n", " 3\n", " 6\n", - " 207\n", - " 0.000756\n", - " 0.001114\n", - " 0.678689\n", + " 177\n", + " 0.000647\n", + " 0.000877\n", + " 0.737500\n", " 1.0\n", " \n", " \n", " 4\n", " 7\n", - " 542\n", - " 0.001980\n", - " 0.003094\n", - " 0.639906\n", - " 2.0\n", + " 521\n", + " 0.001903\n", + " 0.002780\n", + " 0.684625\n", + " 1.0\n", " \n", " \n", " 5\n", " 8\n", - " 1273\n", - " 0.004650\n", - " 0.007744\n", - " 0.600472\n", + " 1217\n", + " 0.004446\n", + " 0.007226\n", + " 0.615268\n", " 2.0\n", " \n", " \n", " 6\n", " 9\n", - " 2493\n", - " 0.009107\n", - " 0.016851\n", - " 0.540429\n", + " 2456\n", + " 0.008972\n", + " 0.016197\n", + " 0.553902\n", " 2.0\n", " \n", " \n", " 7\n", " 10\n", - " 4420\n", - " 0.016146\n", - " 0.032997\n", - " 0.489317\n", + " 4343\n", + " 0.015865\n", + " 0.032062\n", + " 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0.089180\n", + " 0.384796\n", + " 0.231759\n", " 4.0\n", " \n", " \n", " 14\n", " 17\n", - " 25954\n", - " 0.094809\n", - " 0.485867\n", - " 0.195134\n", + " 25441\n", + " 0.092935\n", + " 0.477732\n", + " 0.194534\n", " 5.0\n", " \n", " \n", " 15\n", " 18\n", - " 25739\n", - " 0.094024\n", - " 0.579890\n", - " 0.162141\n", + " 25539\n", + " 0.093293\n", + " 0.571025\n", + " 0.163378\n", " 6.0\n", " \n", " \n", " 16\n", " 19\n", - " 23537\n", - " 0.085980\n", - " 0.665870\n", - " 0.129124\n", - " 8.0\n", + " 24105\n", + " 0.088055\n", + " 0.659079\n", + " 0.133603\n", + " 7.0\n", " \n", " \n", " 17\n", " 20\n", - " 21404\n", - " 0.078188\n", - " 0.744058\n", - " 0.105083\n", - " 10.0\n", + " 21591\n", + " 0.078871\n", + " 0.737951\n", + " 0.106879\n", + " 9.0\n", " \n", " \n", " 18\n", " 21\n", - " 18305\n", - " 0.066868\n", - " 0.810926\n", - " 0.082458\n", + " 18340\n", + " 0.066995\n", + " 0.804946\n", + " 0.083230\n", " 12.0\n", " \n", " \n", " 19\n", " 22\n", - " 14763\n", - " 0.053929\n", - " 0.864855\n", - " 0.062356\n", - " 16.0\n", + " 15235\n", + " 0.055653\n", + " 0.860599\n", + " 0.064668\n", + " 15.0\n", " \n", " \n", " 20\n", " 23\n", - " 11270\n", - " 0.041169\n", - " 0.906024\n", - " 0.045439\n", - " 22.0\n", + " 11811\n", + " 0.043145\n", + " 0.903744\n", + " 0.047741\n", + " 21.0\n", " \n", " \n", " 21\n", " 24\n", - " 8441\n", - " 0.030835\n", - " 0.936858\n", - " 0.032913\n", + " 8574\n", + " 0.031321\n", + " 0.935065\n", + " 0.033496\n", " 30.0\n", " \n", " \n", " 22\n", " 25\n", - " 5969\n", - " 0.021805\n", - " 0.958663\n", - " 0.022745\n", - " 44.0\n", + " 6222\n", + " 0.022729\n", + " 0.957794\n", + " 0.023730\n", + " 42.0\n", " \n", " \n", " 23\n", " 26\n", - " 4157\n", - " 0.015185\n", - " 0.973848\n", - " 0.015593\n", - " 64.0\n", + " 4346\n", + " 0.015876\n", + " 0.973669\n", + " 0.016305\n", + " 61.0\n", " \n", " \n", " 24\n", " 27\n", - " 2874\n", - " 0.010499\n", - " 0.984347\n", - " 0.010666\n", - " 94.0\n", + " 2908\n", + " 0.010623\n", + " 0.984292\n", + " 0.010792\n", + " 93.0\n", " \n", " \n", " 25\n", " 28\n", - " 1797\n", - " 0.006564\n", - " 0.990911\n", - " 0.006625\n", + " 1799\n", + " 0.006572\n", + " 0.990864\n", + " 0.006632\n", " 151.0\n", " \n", " \n", " 26\n", " 29\n", - " 1087\n", - " 0.003971\n", - " 0.994882\n", - " 0.003991\n", + " 1084\n", + " 0.003960\n", + " 0.994824\n", + " 0.003980\n", " 251.0\n", " \n", " \n", " 27\n", " 30\n", - " 649\n", - " 0.002371\n", - " 0.997253\n", - " 0.002377\n", - " 421.0\n", + " 611\n", + " 0.002232\n", + " 0.997056\n", + " 0.002239\n", + " 447.0\n", " \n", " \n", " 28\n", " 31\n", - " 367\n", - " 0.001341\n", - " 0.998594\n", - " 0.001343\n", - " 745.0\n", + " 377\n", + " 0.001377\n", + " 0.998433\n", + " 0.001379\n", + " 725.0\n", " \n", " \n", " 29\n", " 32\n", - " 199\n", - " 0.000727\n", - " 0.999321\n", - " 0.000727\n", - " 1375.0\n", + " 211\n", + " 0.000771\n", + " 0.999204\n", + " 0.000771\n", + " 1296.0\n", " \n", " \n", " 30\n", " 33\n", - " 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0.999978\n", + " 0.000018\n", + " 54749.0\n", + " \n", + " \n", + " 36\n", + " 39\n", + " 5\n", + " 0.000018\n", + " 0.999996\n", + " 0.000018\n", + " 54750.0\n", + " \n", + " \n", + " 37\n", + " 40\n", + " 0\n", + " 0.000000\n", + " 0.999996\n", + " 0.000000\n", + " inf\n", + " \n", + " \n", + " 38\n", + " 41\n", + " 1\n", + " 0.000004\n", " 1.000000\n", - " 0.000007\n", - " 136875.0\n", + " 0.000004\n", + " 273750.0\n", " \n", " \n", "\n", @@ -4931,42 +4958,45 @@ ], "text/plain": [ " beds freq pct c_pct prob_delay 1_in_n_delay\n", - "0 3 1 0.000004 0.000004 1.000000 1.0\n", - "1 4 22 0.000080 0.000084 0.956522 1.0\n", - "2 5 75 0.000274 0.000358 0.765306 1.0\n", - "3 6 207 0.000756 0.001114 0.678689 1.0\n", - "4 7 542 0.001980 0.003094 0.639906 2.0\n", - "5 8 1273 0.004650 0.007744 0.600472 2.0\n", - "6 9 2493 0.009107 0.016851 0.540429 2.0\n", - "7 10 4420 0.016146 0.032997 0.489317 2.0\n", - "8 11 7231 0.026415 0.059412 0.444602 2.0\n", - "9 12 10638 0.038860 0.098272 0.395435 3.0\n", - "10 13 14429 0.052709 0.150981 0.349108 3.0\n", - "11 14 18782 0.068610 0.219591 0.312445 3.0\n", - "12 15 22341 0.081611 0.301202 0.270951 4.0\n", - "13 16 24598 0.089856 0.391058 0.229776 4.0\n", - "14 17 25954 0.094809 0.485867 0.195134 5.0\n", - "15 18 25739 0.094024 0.579890 0.162141 6.0\n", - "16 19 23537 0.085980 0.665870 0.129124 8.0\n", - "17 20 21404 0.078188 0.744058 0.105083 10.0\n", - "18 21 18305 0.066868 0.810926 0.082458 12.0\n", - "19 22 14763 0.053929 0.864855 0.062356 16.0\n", - "20 23 11270 0.041169 0.906024 0.045439 22.0\n", - "21 24 8441 0.030835 0.936858 0.032913 30.0\n", - "22 25 5969 0.021805 0.958663 0.022745 44.0\n", - "23 26 4157 0.015185 0.973848 0.015593 64.0\n", - "24 27 2874 0.010499 0.984347 0.010666 94.0\n", - "25 28 1797 0.006564 0.990911 0.006625 151.0\n", - "26 29 1087 0.003971 0.994882 0.003991 251.0\n", - "27 30 649 0.002371 0.997253 0.002377 421.0\n", - "28 31 367 0.001341 0.998594 0.001343 745.0\n", - "29 32 199 0.000727 0.999321 0.000727 1375.0\n", - "30 33 101 0.000369 0.999689 0.000369 2710.0\n", - "31 34 47 0.000172 0.999861 0.000172 5824.0\n", - "32 35 20 0.000073 0.999934 0.000073 13687.0\n", - "33 36 13 0.000047 0.999982 0.000047 21057.0\n", - "34 37 3 0.000011 0.999993 0.000011 91249.0\n", - "35 38 2 0.000007 1.000000 0.000007 136875.0" + "0 3 2 0.000007 0.000007 1.000000 1.0\n", + "1 4 18 0.000066 0.000073 0.900000 1.0\n", + "2 5 43 0.000157 0.000230 0.682540 1.0\n", + "3 6 177 0.000647 0.000877 0.737500 1.0\n", + "4 7 521 0.001903 0.002780 0.684625 1.0\n", + "5 8 1217 0.004446 0.007226 0.615268 2.0\n", + "6 9 2456 0.008972 0.016197 0.553902 2.0\n", + "7 10 4343 0.015865 0.032062 0.494816 2.0\n", + "8 11 7056 0.025775 0.057837 0.445651 2.0\n", + "9 12 10420 0.038064 0.095901 0.396907 3.0\n", + "10 13 14455 0.052804 0.148705 0.355090 3.0\n", + "11 14 18318 0.066915 0.215620 0.310338 3.0\n", + "12 15 21899 0.079996 0.295616 0.270609 4.0\n", + "13 16 24413 0.089180 0.384796 0.231759 4.0\n", + "14 17 25441 0.092935 0.477732 0.194534 5.0\n", + "15 18 25539 0.093293 0.571025 0.163378 6.0\n", + "16 19 24105 0.088055 0.659079 0.133603 7.0\n", + "17 20 21591 0.078871 0.737951 0.106879 9.0\n", + "18 21 18340 0.066995 0.804946 0.083230 12.0\n", + "19 22 15235 0.055653 0.860599 0.064668 15.0\n", + "20 23 11811 0.043145 0.903744 0.047741 21.0\n", + "21 24 8574 0.031321 0.935065 0.033496 30.0\n", + "22 25 6222 0.022729 0.957794 0.023730 42.0\n", + "23 26 4346 0.015876 0.973669 0.016305 61.0\n", + "24 27 2908 0.010623 0.984292 0.010792 93.0\n", + "25 28 1799 0.006572 0.990864 0.006632 151.0\n", + "26 29 1084 0.003960 0.994824 0.003980 251.0\n", + "27 30 611 0.002232 0.997056 0.002239 447.0\n", + "28 31 377 0.001377 0.998433 0.001379 725.0\n", + "29 32 211 0.000771 0.999204 0.000771 1296.0\n", + "30 33 98 0.000358 0.999562 0.000358 2792.0\n", + "31 34 53 0.000194 0.999755 0.000194 5164.0\n", + "32 35 22 0.000080 0.999836 0.000080 12441.0\n", + "33 36 23 0.000084 0.999920 0.000084 11901.0\n", + "34 37 11 0.000040 0.999960 0.000040 24885.0\n", + "35 38 5 0.000018 0.999978 0.000018 54749.0\n", + "36 39 5 0.000018 0.999996 0.000018 54750.0\n", + "37 40 0 0.000000 0.999996 0.000000 inf\n", + "38 41 1 0.000004 1.000000 0.000004 273750.0" ] }, "metadata": {}, @@ -5001,7 +5031,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.06235586304772043 16.0\n" + "0.06466770519846003 15.0\n" ] } ], @@ -5022,7 +5052,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.015593174563282334 64.0\n" + "0.01630512264483646 61.0\n" ] } ], @@ -5461,10 +5491,10 @@ " 0\n", " 0\n", " 22\n", - " 0.062\n", - " 0.062\n", - " 16\n", - " 16\n", + " 0.065\n", + " 0.065\n", + " 15\n", + " 15\n", " \n", " \n", " 1\n", @@ -5473,8 +5503,8 @@ " 26\n", " 0.016\n", " 0.016\n", - " 64\n", - " 64\n", + " 61\n", + " 61\n", " \n", " \n", " 2\n", @@ -5482,8 +5512,8 @@ " 12\n", " 0\n", " 0.019\n", - " 0.109\n", - " 52\n", + " 0.110\n", + " 53\n", " 9\n", " \n", " \n", @@ -5491,60 +5521,60 @@ " 11\n", " 11\n", " 4\n", - " 0.042\n", - " 0.082\n", + " 0.043\n", + " 0.090\n", " 24\n", - " 12\n", + " 11\n", " \n", " \n", " 4\n", " 11\n", " 10\n", " 5\n", - " 0.035\n", - " 0.083\n", + " 0.036\n", + " 0.091\n", " 28\n", - " 12\n", + " 11\n", " \n", " \n", " 5\n", " 10\n", " 10\n", " 6\n", - " 0.039\n", - " 0.061\n", + " 0.041\n", + " 0.066\n", " 25\n", - " 17\n", + " 15\n", " \n", " \n", " 6\n", " 10\n", " 9\n", " 7\n", - " 0.037\n", - " 0.061\n", - " 27\n", - " 16\n", + " 0.038\n", + " 0.066\n", + " 26\n", + " 15\n", " \n", " \n", " 7\n", " 9\n", " 9\n", " 8\n", - " 0.039\n", - " 0.049\n", - " 26\n", - " 20\n", + " 0.041\n", + " 0.053\n", + " 24\n", + " 19\n", " \n", " \n", " 8\n", " 9\n", " 8\n", " 9\n", - " 0.038\n", - " 0.049\n", - " 26\n", - " 20\n", + " 0.040\n", + " 0.053\n", + " 25\n", + " 19\n", " \n", " \n", "\n", @@ -5552,26 +5582,26 @@ ], "text/plain": [ " dedicated_acute dedicated_rehab pooled pdelay_acute pdelay_rehab \\\n", - "0 0 0 22 0.062 0.062 \n", + "0 0 0 22 0.065 0.065 \n", "1 0 0 26 0.016 0.016 \n", - "2 14 12 0 0.019 0.109 \n", - "3 11 11 4 0.042 0.082 \n", - "4 11 10 5 0.035 0.083 \n", - "5 10 10 6 0.039 0.061 \n", - "6 10 9 7 0.037 0.061 \n", - "7 9 9 8 0.039 0.049 \n", - "8 9 8 9 0.038 0.049 \n", + "2 14 12 0 0.019 0.110 \n", + "3 11 11 4 0.043 0.090 \n", + "4 11 10 5 0.036 0.091 \n", + "5 10 10 6 0.041 0.066 \n", + "6 10 9 7 0.038 0.066 \n", + "7 9 9 8 0.041 0.053 \n", + "8 9 8 9 0.040 0.053 \n", "\n", " 1_in_n_delay_acute 1_in_n_delay_rehab \n", - "0 16 16 \n", - "1 64 64 \n", - "2 52 9 \n", - "3 24 12 \n", - "4 28 12 \n", - "5 25 17 \n", - "6 27 16 \n", - "7 26 20 \n", - "8 26 20 " + "0 15 15 \n", + "1 61 61 \n", + "2 53 9 \n", + "3 24 11 \n", + "4 28 11 \n", + "5 25 15 \n", + "6 26 15 \n", + "7 24 19 \n", + "8 25 19 " ] }, "metadata": {}, @@ -5611,7 +5641,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Notebook run time: 0m 15s\n" + "Notebook run time: 0m 14s\n" ] } ], diff --git a/notebooks/generate_exp_results.ipynb b/notebooks/generate_exp_results.ipynb index 780d571..6fb2168 100644 --- a/notebooks/generate_exp_results.ipynb +++ b/notebooks/generate_exp_results.ipynb @@ -93,31 +93,31 @@ " 0\n", " 1095\n", " 8\n", - " 13\n", + " 16\n", " \n", " \n", " 1\n", " 1096\n", " 7\n", - " 14\n", + " 16\n", " \n", " \n", " 2\n", " 1097\n", - " 8\n", - " 14\n", + " 5\n", + " 16\n", " \n", " \n", " 3\n", " 1098\n", - " 8\n", - " 14\n", + " 3\n", + " 15\n", " \n", " \n", " 4\n", " 1099\n", - " 8\n", - " 14\n", + " 6\n", + " 15\n", " \n", " \n", "\n", @@ -125,11 +125,11 @@ ], "text/plain": [ " time asu_occupancy rehab_occupancy\n", - "0 1095 8 13\n", - "1 1096 7 14\n", - "2 1097 8 14\n", - "3 1098 8 14\n", - "4 1099 8 14" + "0 1095 8 16\n", + "1 1096 7 16\n", + "2 1097 5 16\n", + "3 1098 3 15\n", + "4 1099 6 15" ] }, "metadata": {}, @@ -203,37 +203,37 @@ " \n", " 1\n", " 2\n", - " 12\n", - " 0.006575\n", + " 14\n", " 0.007671\n", - " 0.857143\n", + " 0.008767\n", + " 0.875000\n", " 1.0\n", " \n", " \n", " 2\n", " 3\n", - " 57\n", - " 0.031233\n", - " 0.038904\n", - " 0.802817\n", + " 72\n", + " 0.039452\n", + " 0.048219\n", + " 0.818182\n", " 1.0\n", " \n", " \n", " 3\n", " 4\n", - " 104\n", - " 0.056986\n", - " 0.095890\n", - " 0.594286\n", + " 101\n", + " 0.055342\n", + " 0.103562\n", + " 0.534392\n", " 2.0\n", " \n", " \n", " 4\n", " 5\n", - " 162\n", - " 0.088767\n", - " 0.184658\n", - " 0.480712\n", + " 185\n", + " 0.101370\n", + " 0.204932\n", + " 0.494652\n", " 2.0\n", " \n", " \n", @@ -243,10 +243,10 @@ "text/plain": [ " beds freq pct c_pct prob_delay 1_in_n_delay\n", "0 1 2 0.001096 0.001096 1.000000 1.0\n", - "1 2 12 0.006575 0.007671 0.857143 1.0\n", - "2 3 57 0.031233 0.038904 0.802817 1.0\n", - "3 4 104 0.056986 0.095890 0.594286 2.0\n", - "4 5 162 0.088767 0.184658 0.480712 2.0" + "1 2 14 0.007671 0.008767 0.875000 1.0\n", + "2 3 72 0.039452 0.048219 0.818182 1.0\n", + "3 4 101 0.055342 0.103562 0.534392 2.0\n", + "4 5 185 0.101370 0.204932 0.494652 2.0" ] }, "metadata": {}, @@ -284,47 +284,47 @@ " \n", " \n", " 0\n", - " 2\n", " 1\n", - " 0.000548\n", - " 0.000548\n", + " 7\n", + " 0.003836\n", + " 0.003836\n", " 1.000000\n", " 1.0\n", " \n", " \n", " 1\n", - " 3\n", - " 8\n", - " 0.004384\n", - " 0.004932\n", - " 0.888889\n", - " 1.0\n", + " 2\n", + " 5\n", + " 0.002740\n", + " 0.006575\n", + " 0.416667\n", + " 2.0\n", " \n", " \n", " 2\n", - " 4\n", - " 35\n", - " 0.019178\n", - " 0.024110\n", - " 0.795455\n", + " 3\n", + " 26\n", + " 0.014247\n", + " 0.020822\n", + " 0.684211\n", " 1.0\n", " \n", " \n", " 3\n", - " 5\n", - " 47\n", - " 0.025753\n", - " 0.049863\n", - " 0.516484\n", + " 4\n", + " 64\n", + " 0.035068\n", + " 0.055890\n", + " 0.627451\n", " 2.0\n", " \n", " \n", " 4\n", - " 6\n", - " 129\n", - " 0.070685\n", - " 0.120548\n", - " 0.586364\n", + " 5\n", + " 113\n", + " 0.061918\n", + " 0.117808\n", + " 0.525581\n", " 2.0\n", " \n", " \n", @@ -333,11 +333,11 @@ ], "text/plain": [ " beds freq pct c_pct prob_delay 1_in_n_delay\n", - "0 2 1 0.000548 0.000548 1.000000 1.0\n", - "1 3 8 0.004384 0.004932 0.888889 1.0\n", - "2 4 35 0.019178 0.024110 0.795455 1.0\n", - "3 5 47 0.025753 0.049863 0.516484 2.0\n", - "4 6 129 0.070685 0.120548 0.586364 2.0" + "0 1 7 0.003836 0.003836 1.000000 1.0\n", + "1 2 5 0.002740 0.006575 0.416667 2.0\n", + "2 3 26 0.014247 0.020822 0.684211 1.0\n", + "3 4 64 0.035068 0.055890 0.627451 2.0\n", + "4 5 113 0.061918 0.117808 0.525581 2.0" ] }, "metadata": {}, diff --git a/notebooks/logs.ipynb b/notebooks/logs.ipynb index c457789..38ad03a 100644 --- a/notebooks/logs.ipynb +++ b/notebooks/logs.ipynb @@ -88,8 +88,8 @@ " \u001b[32m'other'\u001b[0m: \u001b[1;35mDiscrete\u001b[0m\u001b[1m(\u001b[0m\u001b[33mvalues\u001b[0m=\u001b[1m[\u001b[0m\u001b[32m'esd'\u001b[0m, \u001b[32m'other'\u001b[0m\u001b[1m]\u001b[0m, \u001b[33mfreq\u001b[0m=\u001b[1m[\u001b[0m\u001b[1;36m0.13\u001b[0m, \u001b[1;36m0.88\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m, \n", " \u001b[32m'stroke'\u001b[0m: \u001b[1;35mDiscrete\u001b[0m\u001b[1m(\u001b[0m\u001b[33mvalues\u001b[0m=\u001b[1m[\u001b[0m\u001b[32m'esd'\u001b[0m, \u001b[32m'other'\u001b[0m\u001b[1m]\u001b[0m, \u001b[33mfreq\u001b[0m=\u001b[1m[\u001b[0m\u001b[1;36m0.4\u001b[0m, \u001b[1;36m0.6\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m, \n", " \u001b[32m'tia'\u001b[0m: \u001b[1;35mDiscrete\u001b[0m\u001b[1m(\u001b[0m\u001b[33mvalues\u001b[0m=\u001b[1m[\u001b[0m\u001b[32m'other'\u001b[0m\u001b[1m]\u001b[0m, \u001b[33mfreq\u001b[0m=\u001b[1m[\u001b[0m\u001b[1;36m1.0\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m\u001b[1m}\u001b[0m\u001b[1m}\u001b[0m\u001b[1m}\u001b[0m, \n", - " \u001b[32m'env'\u001b[0m: \u001b[1m<\u001b[0m\u001b[1;95msimpy.core.Environment\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7a6b97a856a0\u001b[0m\u001b[39m>,\u001b[0m \n", - "\u001b[39m \u001b[0m\u001b[32m'param'\u001b[0m\u001b[39m: \u001b[0m, \n", + " \u001b[32m'env'\u001b[0m: \u001b[1m<\u001b[0m\u001b[1;95msimpy.core.Environment\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x73560a6756a0\u001b[0m\u001b[39m>,\u001b[0m \n", + "\u001b[39m \u001b[0m\u001b[32m'param'\u001b[0m\u001b[39m: \u001b[0m, \n", " \u001b[32m'patients'\u001b[0m: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m, \n", " \u001b[32m'rehab_occupancy'\u001b[0m: \u001b[1;36m0\u001b[0m, \n", " \u001b[32m'run_number'\u001b[0m: \u001b[1;36m0\u001b[0m\u001b[1m}\u001b[0m \n" @@ -204,7 +204,7 @@ " \u001b[32m'rehab_routing_tia'\u001b[0m: \u001b[1m{\u001b[0m \u001b[32m'class_name'\u001b[0m: \u001b[32m'DiscreteEmpirical'\u001b[0m, \n", " \u001b[32m'params'\u001b[0m: \u001b[1m{\u001b[0m \u001b[32m'freq'\u001b[0m: \u001b[1m[\u001b[0m\u001b[1;36m1.0\u001b[0m\u001b[1m]\u001b[0m, \n", " \u001b[32m'values'\u001b[0m: \u001b[1m[\u001b[0m \u001b[32m'other'\u001b[0m\u001b[1m]\u001b[0m\u001b[1m}\u001b[0m\u001b[1m}\u001b[0m\u001b[1m}\u001b[0m, \n", - " \u001b[32m'logger'\u001b[0m: \u001b[1m<\u001b[0m\u001b[1;95msimulation.logging.SimLogger\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x7a6b97d0b0e0\u001b[0m\u001b[1m>\u001b[0m, \n", + " \u001b[32m'logger'\u001b[0m: \u001b[1m<\u001b[0m\u001b[1;95msimulation.logging.SimLogger\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x73560a8eb0e0\u001b[0m\u001b[1m>\u001b[0m, \n", " \u001b[32m'number_of_runs'\u001b[0m: \u001b[1;36m150\u001b[0m, \n", " \u001b[32m'warm_up_period'\u001b[0m: \u001b[1;36m15\u001b[0m\u001b[1m}\u001b[0m \n" ] @@ -232,588 +232,588 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[1;36m3.952\u001b[0m: Patient \u001b[1;36m1\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m arrive at ASU. \n" + "\u001b[1;36m1.836\u001b[0m: Patient \u001b[1;36m1\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m arrive at ASU. \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "\u001b[1;36m3.952\u001b[0m: Patient \u001b[1;36m1\u001b[0m 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"\u001b[1;36m49.597\u001b[0m: Patient \u001b[1;36m53\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m arrive at ASU. \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m49.597\u001b[0m: Patient \u001b[1;36m53\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m post-ASU: other \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m49.597\u001b[0m: Patient \u001b[1;36m53\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m LOS on ASU: \u001b[1;36m2.952\u001b[0m \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m50.429\u001b[0m: Patient \u001b[1;36m54\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m arrive at ASU. \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m50.429\u001b[0m: Patient \u001b[1;36m54\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m post-ASU: other \n" - ] - }, - { - "name": "stdout", - 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\u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m arrive at ASU. \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m50.992\u001b[0m: Patient \u001b[1;36m55\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m post-ASU: rehab \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m50.992\u001b[0m: Patient \u001b[1;36m55\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m LOS on ASU: \u001b[1;36m7.385\u001b[0m \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m51.220\u001b[0m: Patient \u001b[1;36m56\u001b[0m \u001b[1m(\u001b[0mother\u001b[1m)\u001b[0m arrive at ASU. \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m51.220\u001b[0m: Patient \u001b[1;36m56\u001b[0m \u001b[1m(\u001b[0mother\u001b[1m)\u001b[0m post-ASU: other \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m51.220\u001b[0m: Patient \u001b[1;36m56\u001b[0m \u001b[1m(\u001b[0mother\u001b[1m)\u001b[0m LOS on ASU: \u001b[1;36m0.913\u001b[0m \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m52.180\u001b[0m: Patient \u001b[1;36m57\u001b[0m \u001b[1m(\u001b[0mneuro\u001b[1m)\u001b[0m arrive at ASU. \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m52.180\u001b[0m: Patient \u001b[1;36m57\u001b[0m \u001b[1m(\u001b[0mneuro\u001b[1m)\u001b[0m post-ASU: rehab \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m52.180\u001b[0m: Patient \u001b[1;36m57\u001b[0m \u001b[1m(\u001b[0mneuro\u001b[1m)\u001b[0m LOS on ASU: \u001b[1;36m1.372\u001b[0m \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m52.441\u001b[0m: Patient \u001b[1;36m58\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m arrive at ASU. \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m52.441\u001b[0m: Patient \u001b[1;36m58\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m post-ASU: esd \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m52.441\u001b[0m: Patient \u001b[1;36m58\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m LOS on ASU: \u001b[1;36m1.935\u001b[0m \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m52.544\u001b[0m: Patient \u001b[1;36m59\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m arrive at ASU. \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m52.544\u001b[0m: Patient \u001b[1;36m59\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m post-ASU: other \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m52.544\u001b[0m: Patient \u001b[1;36m59\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m LOS on ASU: \u001b[1;36m3.531\u001b[0m \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m52.946\u001b[0m: Patient \u001b[1;36m60\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m arrive at ASU. \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m52.946\u001b[0m: Patient \u001b[1;36m60\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m post-ASU: other \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m52.946\u001b[0m: Patient \u001b[1;36m60\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m LOS on ASU: \u001b[1;36m10.057\u001b[0m \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m53.210\u001b[0m: Patient \u001b[1;36m61\u001b[0m \u001b[1m(\u001b[0mother\u001b[1m)\u001b[0m arrive at ASU. \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m53.210\u001b[0m: Patient \u001b[1;36m61\u001b[0m \u001b[1m(\u001b[0mother\u001b[1m)\u001b[0m post-ASU: other \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m53.210\u001b[0m: Patient \u001b[1;36m61\u001b[0m \u001b[1m(\u001b[0mother\u001b[1m)\u001b[0m LOS on ASU: \u001b[1;36m1.259\u001b[0m \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m53.552\u001b[0m: Patient \u001b[1;36m57\u001b[0m \u001b[1m(\u001b[0mneuro\u001b[1m)\u001b[0m arrive at rehab. \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m53.552\u001b[0m: Patient \u001b[1;36m57\u001b[0m \u001b[1m(\u001b[0mneuro\u001b[1m)\u001b[0m post-rehab: other \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m53.552\u001b[0m: Patient \u001b[1;36m57\u001b[0m \u001b[1m(\u001b[0mneuro\u001b[1m)\u001b[0m LOS on rehab unit: \u001b[1;36m49.465\u001b[0m \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m54.155\u001b[0m: Patient \u001b[1;36m62\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m arrive at ASU. \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m54.155\u001b[0m: Patient \u001b[1;36m62\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m post-ASU: other \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m54.155\u001b[0m: Patient \u001b[1;36m62\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m LOS on ASU: \u001b[1;36m5.558\u001b[0m \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m54.435\u001b[0m: Patient \u001b[1;36m63\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m arrive at ASU. \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m54.435\u001b[0m: Patient \u001b[1;36m63\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m post-ASU: other \n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;36m54.435\u001b[0m: Patient \u001b[1;36m63\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m LOS on ASU: \u001b[1;36m4.576\u001b[0m \n" + "\u001b[1;36m53.122\u001b[0m: Patient \u001b[1;36m40\u001b[0m \u001b[1m(\u001b[0mstroke\u001b[1m)\u001b[0m LOS on rehab unit: \u001b[1;36m26.316\u001b[0m \n" ] } ], diff --git a/outputs/figure1_asu.png b/outputs/figure1_asu.png index 67c56ba..f32b4cf 100644 Binary files a/outputs/figure1_asu.png and b/outputs/figure1_asu.png differ diff --git a/outputs/figure1_rehab.png b/outputs/figure1_rehab.png index e65094b..14d0f7c 100644 Binary files a/outputs/figure1_rehab.png and b/outputs/figure1_rehab.png differ diff --git a/outputs/figure3_asu.png b/outputs/figure3_asu.png index b1cd782..61cd0b0 100644 Binary files a/outputs/figure3_asu.png and b/outputs/figure3_asu.png differ diff --git a/outputs/figure3_rehab.png b/outputs/figure3_rehab.png index b6d893e..b3ae054 100644 Binary files a/outputs/figure3_rehab.png and b/outputs/figure3_rehab.png differ diff --git a/outputs/logs/log_example.log b/outputs/logs/log_example.log index 6d0c486..0cb79e9 100644 --- a/outputs/logs/log_example.log +++ b/outputs/logs/log_example.log @@ -29,8 +29,8 @@ 'other': Discrete(values=['esd', 'other'], freq=[0.13, 0.88]), 'stroke': Discrete(values=['esd', 'other'], freq=[0.4, 0.6]), 'tia': Discrete(values=['other'], freq=[1.0])}}}, - 'env': , - 'param': , + 'env': , + 'param': , 'patients': [], 'rehab_occupancy': 0, 'run_number': 0} @@ -133,7 +133,7 @@ Parameters: 'rehab_routing_tia': { 'class_name': 'DiscreteEmpirical', 'params': { 'freq': [1.0], 'values': [ 'other']}}}, - 'logger': , + 'logger': , 'number_of_runs': 150, 'warm_up_period': 15} Logger: @@ -143,303 +143,243 @@ Logger: 'log_to_file': True, 'logger': , 'sanitise': False} -3.952: Patient 1 (stroke) arrive at ASU. -3.952: Patient 1 (stroke) post-ASU: rehab -3.952: Patient 1 (stroke) LOS on ASU: 3.359 -4.635: Patient 2 (other) arrive at ASU. -4.635: Patient 2 (other) post-ASU: other -4.635: Patient 2 (other) LOS on ASU: 3.146 -4.868: Patient 3 (stroke) arrive at ASU. -4.868: Patient 3 (stroke) post-ASU: other -4.868: Patient 3 (stroke) LOS on ASU: 3.029 -4.946: Patient 4 (other) arrive at ASU. -4.946: Patient 4 (other) post-ASU: other -4.946: Patient 4 (other) LOS on ASU: 1.923 -5.509: Patient 5 (neuro) arrive at ASU. -5.509: Patient 5 (neuro) post-ASU: other -5.509: Patient 5 (neuro) LOS on ASU: 1.946 -5.923: Patient 6 (neuro) arrive at ASU. -5.923: Patient 6 (neuro) post-ASU: other -5.923: Patient 6 (neuro) LOS on ASU: 2.286 -6.371: Patient 7 (stroke) arrive at ASU. -6.371: Patient 7 (stroke) post-ASU: rehab -6.371: Patient 7 (stroke) LOS on ASU: 4.517 -6.642: Patient 8 (stroke) arrive at ASU. -6.642: Patient 8 (stroke) post-ASU: other -6.642: Patient 8 (stroke) LOS on ASU: 4.448 -6.907: Patient 9 (stroke) arrive at ASU. -6.907: Patient 9 (stroke) post-ASU: other -6.907: Patient 9 (stroke) LOS on ASU: 3.626 -7.311: Patient 1 (stroke) arrive at rehab. -7.311: Patient 1 (stroke) post-rehab: other -7.311: Patient 1 (stroke) LOS on rehab unit: 15.766 -7.469: Patient 10 (tia) arrive at ASU. -7.469: Patient 10 (tia) post-ASU: other -7.469: Patient 10 (tia) LOS on ASU: 1.139 -9.067: Patient 11 (stroke) arrive at ASU. -9.067: Patient 11 (stroke) post-ASU: rehab -9.067: Patient 11 (stroke) LOS on ASU: 1.097 -9.115: Patient 12 (other) arrive at ASU. -9.115: Patient 12 (other) post-ASU: esd -9.115: Patient 12 (other) LOS on ASU: 4.978 -9.146: Patient 13 (stroke) arrive at ASU. -9.146: Patient 13 (stroke) post-ASU: other -9.146: Patient 13 (stroke) LOS on ASU: 2.444 -9.344: Patient 14 (other) arrive at ASU. -9.344: Patient 14 (other) post-ASU: other -9.344: Patient 14 (other) LOS on ASU: 20.820 -9.832: Patient 15 (other) arrive at ASU. -9.832: Patient 15 (other) post-ASU: other -9.832: Patient 15 (other) LOS on ASU: 0.312 -10.163: Patient 11 (stroke) arrive at rehab. -10.163: Patient 11 (stroke) post-rehab: other -10.163: Patient 11 (stroke) LOS on rehab unit: 72.573 -10.164: Patient 16 (neuro) arrive at ASU. -10.164: Patient 16 (neuro) post-ASU: other -10.164: Patient 16 (neuro) LOS on ASU: 4.549 -10.227: Patient 17 (stroke) arrive at ASU. -10.227: Patient 17 (stroke) post-ASU: other -10.227: Patient 17 (stroke) LOS on ASU: 5.184 -10.440: Patient 18 (other) arrive at ASU. -10.440: Patient 18 (other) post-ASU: other -10.440: Patient 18 (other) LOS on ASU: 3.021 -10.581: Patient 19 (stroke) arrive at ASU. -10.581: Patient 19 (stroke) post-ASU: rehab -10.581: Patient 19 (stroke) LOS on ASU: 3.627 -10.864: Patient 20 (neuro) arrive at rehab. -10.864: Patient 20 (neuro) post-rehab: other -10.864: Patient 20 (neuro) LOS on rehab unit: 8.403 -10.888: Patient 7 (stroke) arrive at rehab. -10.888: Patient 7 (stroke) post-rehab: esd -10.888: Patient 7 (stroke) LOS on rehab unit: 12.702 -11.021: Patient 21 (tia) arrive at ASU. -11.021: Patient 21 (tia) post-ASU: other -11.021: Patient 21 (tia) LOS on ASU: 1.765 -11.649: Patient 22 (other) arrive at rehab. -11.649: Patient 22 (other) post-rehab: other -11.649: Patient 22 (other) LOS on rehab unit: 8.100 -13.341: Patient 23 (stroke) arrive at ASU. -13.341: Patient 23 (stroke) post-ASU: other -13.341: Patient 23 (stroke) LOS on ASU: 7.131 -14.208: Patient 19 (stroke) arrive at rehab. -14.208: Patient 19 (stroke) post-rehab: esd -14.208: Patient 19 (stroke) LOS on rehab unit: 13.151 -14.408: Patient 24 (tia) arrive at ASU. -14.408: Patient 24 (tia) post-ASU: other -14.408: Patient 24 (tia) LOS on ASU: 3.846 +1.836: Patient 1 (stroke) arrive at ASU. +1.836: Patient 1 (stroke) post-ASU: other +1.836: Patient 1 (stroke) LOS on ASU: 3.007 +1.974: Patient 2 (stroke) arrive at ASU. +1.974: Patient 2 (stroke) post-ASU: esd +1.974: Patient 2 (stroke) LOS on ASU: 31.512 +2.570: Patient 3 (other) arrive at ASU. +2.570: Patient 3 (other) post-ASU: esd +2.570: Patient 3 (other) LOS on ASU: 2.130 +3.388: Patient 4 (stroke) arrive at ASU. +3.388: Patient 4 (stroke) post-ASU: other +3.388: Patient 4 (stroke) LOS on ASU: 4.097 +3.792: Patient 5 (other) arrive at ASU. +3.792: Patient 5 (other) post-ASU: other +3.792: Patient 5 (other) LOS on ASU: 0.597 +4.958: Patient 6 (other) arrive at ASU. +4.958: Patient 6 (other) post-ASU: other +4.958: Patient 6 (other) LOS on ASU: 0.714 +5.984: Patient 7 (stroke) arrive at ASU. +5.984: Patient 7 (stroke) post-ASU: other +5.984: Patient 7 (stroke) LOS on ASU: 0.934 +6.445: Patient 8 (stroke) arrive at ASU. +6.445: Patient 8 (stroke) post-ASU: rehab +6.445: Patient 8 (stroke) LOS on ASU: 19.183 +6.652: Patient 9 (other) arrive at ASU. +6.652: Patient 9 (other) post-ASU: other +6.652: Patient 9 (other) LOS on ASU: 2.329 +7.044: Patient 10 (stroke) arrive at ASU. +7.044: Patient 10 (stroke) post-ASU: rehab +7.044: Patient 10 (stroke) LOS on ASU: 7.705 +7.452: Patient 11 (stroke) arrive at ASU. +7.452: Patient 11 (stroke) post-ASU: other +7.452: Patient 11 (stroke) LOS on ASU: 3.258 +8.593: Patient 12 (stroke) arrive at ASU. +8.593: Patient 12 (stroke) post-ASU: rehab +8.593: Patient 12 (stroke) LOS on ASU: 13.352 +9.668: Patient 13 (stroke) arrive at ASU. +9.668: Patient 13 (stroke) post-ASU: esd +9.668: Patient 13 (stroke) LOS on ASU: 3.429 +9.961: Patient 14 (stroke) arrive at ASU. +9.961: Patient 14 (stroke) post-ASU: rehab +9.961: Patient 14 (stroke) LOS on ASU: 2.821 +9.970: Patient 15 (stroke) arrive at ASU. +9.970: Patient 15 (stroke) post-ASU: rehab +9.970: Patient 15 (stroke) LOS on ASU: 4.992 +10.476: Patient 16 (stroke) arrive at ASU. +10.476: Patient 16 (stroke) post-ASU: other +10.476: Patient 16 (stroke) LOS on ASU: 5.733 +11.511: Patient 17 (stroke) arrive at ASU. +11.511: Patient 17 (stroke) post-ASU: rehab +11.511: Patient 17 (stroke) LOS on ASU: 1.189 +11.857: Patient 18 (neuro) arrive at ASU. +11.857: Patient 18 (neuro) post-ASU: other +11.857: Patient 18 (neuro) LOS on ASU: 2.989 +12.144: Patient 19 (stroke) arrive at ASU. +12.144: Patient 19 (stroke) post-ASU: other +12.144: Patient 19 (stroke) LOS on ASU: 0.491 +12.700: Patient 17 (stroke) arrive at rehab. +12.700: Patient 17 (stroke) post-rehab: other +12.700: Patient 17 (stroke) LOS on rehab unit: 18.910 +12.782: Patient 14 (stroke) arrive at rehab. +12.782: Patient 14 (stroke) post-rehab: other +12.782: Patient 14 (stroke) LOS on rehab unit: 27.797 +13.471: Patient 20 (tia) arrive at ASU. +13.471: Patient 20 (tia) post-ASU: other +13.471: Patient 20 (tia) LOS on ASU: 0.761 +13.921: Patient 21 (stroke) arrive at ASU. +13.921: Patient 21 (stroke) post-ASU: other +13.921: Patient 21 (stroke) LOS on ASU: 6.463 +14.261: Patient 22 (stroke) arrive at ASU. +14.261: Patient 22 (stroke) post-ASU: other +14.261: Patient 22 (stroke) LOS on ASU: 11.640 +14.374: Patient 23 (tia) arrive at ASU. +14.374: Patient 23 (tia) post-ASU: other +14.374: Patient 23 (tia) LOS on ASU: 1.125 +14.604: Patient 24 (neuro) arrive at ASU. +14.604: Patient 24 (neuro) post-ASU: other +14.604: Patient 24 (neuro) LOS on ASU: 0.643 +14.748: Patient 10 (stroke) arrive at rehab. +14.748: Patient 10 (stroke) post-rehab: other +14.748: Patient 10 (stroke) LOS on rehab unit: 17.002 +14.962: Patient 15 (stroke) arrive at rehab. +14.962: Patient 15 (stroke) post-rehab: other +14.962: Patient 15 (stroke) LOS on rehab unit: 17.096 15.000: ────────── 15.000: Warm up complete. 15.000: ────────── -15.571: Patient 1 (stroke) arrive at ASU. -15.571: Patient 1 (stroke) post-ASU: other -15.571: Patient 1 (stroke) LOS on ASU: 17.022 -15.589: Patient 2 (stroke) arrive at ASU. -15.589: Patient 2 (stroke) post-ASU: other -15.589: Patient 2 (stroke) LOS on ASU: 5.836 -17.953: Patient 3 (neuro) arrive at ASU. -17.953: Patient 3 (neuro) post-ASU: other -17.953: Patient 3 (neuro) LOS on ASU: 20.251 -19.171: Patient 4 (other) arrive at ASU. -19.171: Patient 4 (other) post-ASU: other -19.171: Patient 4 (other) LOS on ASU: 8.514 -19.332: Patient 5 (tia) arrive at ASU. -19.332: Patient 5 (tia) post-ASU: other -19.332: Patient 5 (tia) LOS on ASU: 0.294 -19.335: Patient 6 (neuro) arrive at ASU. -19.335: Patient 6 (neuro) post-ASU: other -19.335: Patient 6 (neuro) LOS on ASU: 0.244 -21.132: Patient 7 (neuro) arrive at ASU. -21.132: Patient 7 (neuro) post-ASU: other -21.132: Patient 7 (neuro) LOS on ASU: 3.261 -22.305: Patient 8 (stroke) arrive at ASU. -22.305: Patient 8 (stroke) post-ASU: other -22.305: Patient 8 (stroke) LOS on ASU: 1.150 -22.357: Patient 9 (neuro) arrive at ASU. -22.357: Patient 9 (neuro) post-ASU: other -22.357: Patient 9 (neuro) LOS on ASU: 19.862 -23.260: Patient 10 (stroke) arrive at ASU. -23.260: Patient 10 (stroke) post-ASU: rehab -23.260: Patient 10 (stroke) LOS on ASU: 6.230 -23.680: Patient 11 (stroke) arrive at ASU. -23.680: Patient 11 (stroke) post-ASU: other -23.680: Patient 11 (stroke) LOS on ASU: 8.540 -24.497: Patient 12 (stroke) arrive at rehab. -24.497: Patient 12 (stroke) post-rehab: other -24.497: Patient 12 (stroke) LOS on rehab unit: 25.030 -25.780: Patient 13 (neuro) arrive at ASU. -25.780: Patient 13 (neuro) post-ASU: other -25.780: Patient 13 (neuro) LOS on ASU: 0.969 -26.044: Patient 14 (stroke) arrive at ASU. -26.044: Patient 14 (stroke) post-ASU: esd -26.044: Patient 14 (stroke) LOS on ASU: 11.455 -26.815: Patient 15 (other) arrive at ASU. -26.815: Patient 15 (other) post-ASU: esd -26.815: Patient 15 (other) LOS on ASU: 0.819 -26.935: Patient 16 (stroke) arrive at ASU. -26.935: Patient 16 (stroke) post-ASU: rehab -26.935: Patient 16 (stroke) LOS on ASU: 0.593 -26.942: Patient 17 (stroke) arrive at ASU. -26.942: Patient 17 (stroke) post-ASU: esd -26.942: Patient 17 (stroke) LOS on ASU: 4.915 -26.988: Patient 18 (other) arrive at ASU. -26.988: Patient 18 (other) post-ASU: other -26.988: Patient 18 (other) LOS on ASU: 0.668 -27.528: Patient 16 (stroke) arrive at rehab. -27.528: Patient 16 (stroke) post-rehab: other -27.528: Patient 16 (stroke) LOS on rehab unit: 13.826 -27.935: Patient 19 (stroke) arrive at ASU. -27.935: Patient 19 (stroke) post-ASU: esd -27.935: Patient 19 (stroke) LOS on ASU: 8.185 -28.679: Patient 20 (stroke) arrive at ASU. -28.679: Patient 20 (stroke) post-ASU: other -28.679: Patient 20 (stroke) LOS on ASU: 4.248 -29.004: Patient 21 (neuro) arrive at ASU. -29.004: Patient 21 (neuro) post-ASU: other -29.004: Patient 21 (neuro) LOS on ASU: 0.510 -29.406: Patient 22 (stroke) arrive at ASU. -29.406: Patient 22 (stroke) post-ASU: rehab -29.406: Patient 22 (stroke) LOS on ASU: 6.987 -29.490: Patient 10 (stroke) arrive at rehab. -29.490: Patient 10 (stroke) post-rehab: esd -29.490: Patient 10 (stroke) LOS on rehab unit: 75.543 -29.884: Patient 23 (neuro) arrive at ASU. -29.884: Patient 23 (neuro) post-ASU: other -29.884: Patient 23 (neuro) LOS on ASU: 3.903 -29.911: Patient 24 (neuro) arrive at ASU. -29.911: Patient 24 (neuro) post-ASU: other -29.911: Patient 24 (neuro) LOS on ASU: 8.592 -30.200: Patient 25 (other) arrive at ASU. -30.200: Patient 25 (other) post-ASU: other -30.200: Patient 25 (other) LOS on ASU: 1.908 -31.428: Patient 26 (neuro) arrive at ASU. -31.428: Patient 26 (neuro) post-ASU: rehab -31.428: Patient 26 (neuro) LOS on ASU: 2.587 -32.814: Patient 27 (stroke) arrive at ASU. -32.814: Patient 27 (stroke) post-ASU: other -32.814: Patient 27 (stroke) LOS on ASU: 6.870 -32.884: Patient 28 (other) arrive at rehab. -32.884: Patient 28 (other) post-rehab: other -32.884: Patient 28 (other) LOS on rehab unit: 60.723 -33.097: Patient 29 (stroke) arrive at ASU. -33.097: Patient 29 (stroke) post-ASU: other -33.097: Patient 29 (stroke) LOS on ASU: 1.270 -34.015: Patient 26 (neuro) arrive at rehab. -34.015: Patient 26 (neuro) post-rehab: other -34.015: Patient 26 (neuro) LOS on rehab unit: 13.694 -34.534: Patient 30 (neuro) arrive at ASU. -34.534: Patient 30 (neuro) post-ASU: other -34.534: Patient 30 (neuro) LOS on ASU: 4.013 -36.102: Patient 31 (stroke) arrive at ASU. -36.102: Patient 31 (stroke) post-ASU: other -36.102: Patient 31 (stroke) LOS on ASU: 24.260 -36.393: Patient 22 (stroke) arrive at rehab. -36.393: Patient 22 (stroke) post-rehab: other -36.393: Patient 22 (stroke) LOS on rehab unit: 19.051 -36.433: Patient 32 (neuro) arrive at ASU. -36.433: Patient 32 (neuro) post-ASU: other -36.433: Patient 32 (neuro) LOS on ASU: 3.052 -36.493: Patient 33 (stroke) arrive at ASU. -36.493: Patient 33 (stroke) post-ASU: other -36.493: Patient 33 (stroke) LOS on ASU: 19.224 -37.456: Patient 34 (other) arrive at ASU. -37.456: Patient 34 (other) post-ASU: other -37.456: Patient 34 (other) LOS on ASU: 7.962 -38.034: Patient 35 (other) arrive at ASU. -38.034: Patient 35 (other) post-ASU: other -38.034: Patient 35 (other) LOS on ASU: 3.243 -38.348: Patient 36 (stroke) arrive at ASU. -38.348: Patient 36 (stroke) post-ASU: rehab -38.348: Patient 36 (stroke) LOS on ASU: 12.273 -39.617: Patient 37 (stroke) arrive at ASU. -39.617: Patient 37 (stroke) post-ASU: rehab -39.617: Patient 37 (stroke) LOS on ASU: 8.563 -40.085: Patient 38 (stroke) arrive at ASU. -40.085: Patient 38 (stroke) post-ASU: rehab -40.085: Patient 38 (stroke) LOS on ASU: 1.374 -40.221: Patient 39 (other) arrive at ASU. -40.221: Patient 39 (other) post-ASU: other -40.221: Patient 39 (other) LOS on ASU: 2.006 -40.904: Patient 40 (stroke) arrive at ASU. -40.904: Patient 40 (stroke) post-ASU: other -40.904: Patient 40 (stroke) LOS on ASU: 22.662 -41.230: Patient 41 (other) arrive at ASU. -41.230: Patient 41 (other) post-ASU: other -41.230: Patient 41 (other) LOS on ASU: 1.914 -41.459: Patient 38 (stroke) arrive at rehab. -41.459: Patient 38 (stroke) post-rehab: esd -41.459: Patient 38 (stroke) LOS on rehab unit: 18.808 -41.478: Patient 42 (other) arrive at rehab. -41.478: Patient 42 (other) post-rehab: other -41.478: Patient 42 (other) LOS on rehab unit: 6.542 -41.763: Patient 43 (neuro) arrive at ASU. -41.763: Patient 43 (neuro) post-ASU: esd -41.763: Patient 43 (neuro) LOS on ASU: 0.483 -42.784: Patient 44 (neuro) arrive at ASU. -42.784: Patient 44 (neuro) post-ASU: other -42.784: Patient 44 (neuro) LOS on ASU: 3.828 -43.243: Patient 45 (stroke) arrive at ASU. -43.243: Patient 45 (stroke) post-ASU: other -43.243: Patient 45 (stroke) LOS on ASU: 3.136 -45.264: Patient 46 (tia) arrive at ASU. -45.264: Patient 46 (tia) post-ASU: other -45.264: Patient 46 (tia) LOS on ASU: 1.267 -45.922: Patient 47 (other) arrive at rehab. -45.922: Patient 47 (other) post-rehab: other -45.922: Patient 47 (other) LOS on rehab unit: 27.789 -46.096: Patient 48 (stroke) arrive at ASU. -46.096: Patient 48 (stroke) post-ASU: rehab -46.096: Patient 48 (stroke) LOS on ASU: 9.104 -46.285: Patient 49 (other) arrive at ASU. -46.285: Patient 49 (other) post-ASU: other -46.285: Patient 49 (other) LOS on ASU: 2.034 -46.634: Patient 50 (other) arrive at ASU. -46.634: Patient 50 (other) post-ASU: other -46.634: Patient 50 (other) LOS on ASU: 12.043 -47.097: Patient 51 (stroke) arrive at ASU. -47.097: Patient 51 (stroke) post-ASU: other -47.097: Patient 51 (stroke) LOS on ASU: 8.175 -48.179: Patient 37 (stroke) arrive at rehab. -48.179: Patient 37 (stroke) post-rehab: other -48.179: Patient 37 (stroke) LOS on rehab unit: 12.860 -48.916: Patient 52 (neuro) arrive at ASU. -48.916: Patient 52 (neuro) post-ASU: other -48.916: Patient 52 (neuro) LOS on ASU: 2.062 -49.597: Patient 53 (stroke) arrive at ASU. -49.597: Patient 53 (stroke) post-ASU: other -49.597: Patient 53 (stroke) LOS on ASU: 2.952 -50.429: Patient 54 (stroke) arrive at ASU. -50.429: Patient 54 (stroke) post-ASU: other -50.429: Patient 54 (stroke) LOS on ASU: 2.426 -50.621: Patient 36 (stroke) arrive at rehab. -50.621: Patient 36 (stroke) post-rehab: other -50.621: Patient 36 (stroke) LOS on rehab unit: 20.802 -50.992: Patient 55 (stroke) arrive at ASU. -50.992: Patient 55 (stroke) post-ASU: rehab -50.992: Patient 55 (stroke) LOS on ASU: 7.385 -51.220: Patient 56 (other) arrive at ASU. -51.220: Patient 56 (other) post-ASU: other -51.220: Patient 56 (other) LOS on ASU: 0.913 -52.180: Patient 57 (neuro) arrive at ASU. -52.180: Patient 57 (neuro) post-ASU: rehab -52.180: Patient 57 (neuro) LOS on ASU: 1.372 -52.441: Patient 58 (stroke) arrive at ASU. -52.441: Patient 58 (stroke) post-ASU: esd -52.441: Patient 58 (stroke) LOS on ASU: 1.935 -52.544: Patient 59 (stroke) arrive at ASU. -52.544: Patient 59 (stroke) post-ASU: other -52.544: Patient 59 (stroke) LOS on ASU: 3.531 -52.946: Patient 60 (stroke) arrive at ASU. -52.946: Patient 60 (stroke) post-ASU: other -52.946: Patient 60 (stroke) LOS on ASU: 10.057 -53.210: Patient 61 (other) arrive at ASU. -53.210: Patient 61 (other) post-ASU: other -53.210: Patient 61 (other) LOS on ASU: 1.259 -53.552: Patient 57 (neuro) arrive at rehab. -53.552: Patient 57 (neuro) post-rehab: other -53.552: Patient 57 (neuro) LOS on rehab unit: 49.465 -54.155: Patient 62 (stroke) arrive at ASU. -54.155: Patient 62 (stroke) post-ASU: other -54.155: Patient 62 (stroke) LOS on ASU: 5.558 -54.435: Patient 63 (stroke) arrive at ASU. -54.435: Patient 63 (stroke) post-ASU: other -54.435: Patient 63 (stroke) LOS on ASU: 4.576 +15.575: Patient 1 (other) arrive at ASU. +15.575: Patient 1 (other) post-ASU: other +15.575: Patient 1 (other) LOS on ASU: 9.067 +16.305: Patient 2 (stroke) arrive at ASU. +16.305: Patient 2 (stroke) post-ASU: other +16.305: Patient 2 (stroke) LOS on ASU: 7.992 +16.344: Patient 3 (stroke) arrive at rehab. +16.344: Patient 3 (stroke) post-rehab: esd +16.344: Patient 3 (stroke) LOS on rehab unit: 8.934 +17.393: Patient 4 (stroke) arrive at ASU. +17.393: Patient 4 (stroke) post-ASU: other +17.393: Patient 4 (stroke) LOS on ASU: 1.182 +19.112: Patient 5 (neuro) arrive at ASU. +19.112: Patient 5 (neuro) post-ASU: other +19.112: Patient 5 (neuro) LOS on ASU: 4.792 +19.926: Patient 6 (neuro) arrive at ASU. +19.926: Patient 6 (neuro) post-ASU: other +19.926: Patient 6 (neuro) LOS on ASU: 0.403 +20.721: Patient 7 (neuro) arrive at ASU. +20.721: Patient 7 (neuro) post-ASU: other +20.721: Patient 7 (neuro) LOS on ASU: 4.662 +21.850: Patient 8 (other) arrive at ASU. +21.850: Patient 8 (other) post-ASU: rehab +21.850: Patient 8 (other) LOS on ASU: 1.690 +21.945: Patient 12 (stroke) arrive at rehab. +21.945: Patient 12 (stroke) post-rehab: other +21.945: Patient 12 (stroke) LOS on rehab unit: 57.854 +22.650: Patient 9 (stroke) arrive at ASU. +22.650: Patient 9 (stroke) post-ASU: esd +22.650: Patient 9 (stroke) LOS on ASU: 3.327 +22.881: Patient 10 (stroke) arrive at ASU. +22.881: Patient 10 (stroke) post-ASU: other +22.881: Patient 10 (stroke) LOS on ASU: 8.521 +23.232: Patient 11 (stroke) arrive at ASU. +23.232: Patient 11 (stroke) post-ASU: other +23.232: Patient 11 (stroke) LOS on ASU: 6.847 +23.265: Patient 12 (stroke) arrive at ASU. +23.265: Patient 12 (stroke) post-ASU: other +23.265: Patient 12 (stroke) LOS on ASU: 3.668 +23.540: Patient 8 (other) arrive at rehab. +23.540: Patient 8 (other) post-rehab: other +23.540: Patient 8 (other) LOS on rehab unit: 8.140 +24.034: Patient 13 (stroke) arrive at ASU. +24.034: Patient 13 (stroke) post-ASU: other +24.034: Patient 13 (stroke) LOS on ASU: 3.320 +24.887: Patient 14 (other) arrive at ASU. +24.887: Patient 14 (other) post-ASU: other +24.887: Patient 14 (other) LOS on ASU: 7.381 +25.628: Patient 8 (stroke) arrive at rehab. +25.628: Patient 8 (stroke) post-rehab: other +25.628: Patient 8 (stroke) LOS on rehab unit: 20.442 +26.491: Patient 15 (tia) arrive at ASU. +26.491: Patient 15 (tia) post-ASU: other +26.491: Patient 15 (tia) LOS on ASU: 0.913 +27.156: Patient 16 (tia) arrive at ASU. +27.156: Patient 16 (tia) post-ASU: other +27.156: Patient 16 (tia) LOS on ASU: 0.611 +27.165: Patient 17 (stroke) arrive at ASU. +27.165: Patient 17 (stroke) post-ASU: rehab +27.165: Patient 17 (stroke) LOS on ASU: 10.474 +27.200: Patient 18 (neuro) arrive at ASU. +27.200: Patient 18 (neuro) post-ASU: rehab +27.200: Patient 18 (neuro) LOS on ASU: 1.272 +27.438: Patient 19 (neuro) arrive at ASU. +27.438: Patient 19 (neuro) post-ASU: other +27.438: Patient 19 (neuro) LOS on ASU: 22.218 +28.472: Patient 18 (neuro) arrive at rehab. +28.472: Patient 18 (neuro) post-rehab: other +28.472: Patient 18 (neuro) LOS on rehab unit: 12.227 +28.573: Patient 20 (tia) arrive at ASU. +28.573: Patient 20 (tia) post-ASU: other +28.573: Patient 20 (tia) LOS on ASU: 1.315 +29.643: Patient 21 (stroke) arrive at ASU. +29.643: Patient 21 (stroke) post-ASU: esd +29.643: Patient 21 (stroke) LOS on ASU: 0.740 +29.924: Patient 22 (stroke) arrive at ASU. +29.924: Patient 22 (stroke) post-ASU: other +29.924: Patient 22 (stroke) LOS on ASU: 5.570 +30.341: Patient 23 (tia) arrive at ASU. +30.341: Patient 23 (tia) post-ASU: other +30.341: Patient 23 (tia) LOS on ASU: 1.819 +30.350: Patient 24 (stroke) arrive at ASU. +30.350: Patient 24 (stroke) post-ASU: other +30.350: Patient 24 (stroke) LOS on ASU: 1.364 +30.680: Patient 25 (neuro) arrive at ASU. +30.680: Patient 25 (neuro) post-ASU: other +30.680: Patient 25 (neuro) LOS on ASU: 5.272 +31.743: Patient 26 (neuro) arrive at ASU. +31.743: Patient 26 (neuro) post-ASU: rehab +31.743: Patient 26 (neuro) LOS on ASU: 6.138 +32.085: Patient 27 (stroke) arrive at ASU. +32.085: Patient 27 (stroke) post-ASU: rehab +32.085: Patient 27 (stroke) LOS on ASU: 5.326 +33.475: Patient 28 (stroke) arrive at ASU. +33.475: Patient 28 (stroke) post-ASU: other +33.475: Patient 28 (stroke) LOS on ASU: 3.993 +37.411: Patient 27 (stroke) arrive at rehab. +37.411: Patient 27 (stroke) post-rehab: esd +37.411: Patient 27 (stroke) LOS on rehab unit: 21.042 +37.638: Patient 17 (stroke) arrive at rehab. +37.638: Patient 17 (stroke) post-rehab: other +37.638: Patient 17 (stroke) LOS on rehab unit: 22.310 +37.881: Patient 26 (neuro) arrive at rehab. +37.881: Patient 26 (neuro) post-rehab: other +37.881: Patient 26 (neuro) LOS on rehab unit: 118.211 +38.220: Patient 29 (other) arrive at ASU. +38.220: Patient 29 (other) post-ASU: other +38.220: Patient 29 (other) LOS on ASU: 3.916 +39.150: Patient 30 (stroke) arrive at ASU. +39.150: Patient 30 (stroke) post-ASU: esd +39.150: Patient 30 (stroke) LOS on ASU: 16.195 +39.412: Patient 31 (stroke) arrive at ASU. +39.412: Patient 31 (stroke) post-ASU: other +39.412: Patient 31 (stroke) LOS on ASU: 2.613 +39.788: Patient 32 (stroke) arrive at ASU. +39.788: Patient 32 (stroke) post-ASU: esd +39.788: Patient 32 (stroke) LOS on ASU: 26.878 +40.023: Patient 33 (neuro) arrive at ASU. +40.023: Patient 33 (neuro) post-ASU: other +40.023: Patient 33 (neuro) LOS on ASU: 2.265 +40.100: Patient 34 (other) arrive at ASU. +40.100: Patient 34 (other) post-ASU: other +40.100: Patient 34 (other) LOS on ASU: 5.739 +41.177: Patient 35 (stroke) arrive at ASU. +41.177: Patient 35 (stroke) post-ASU: other +41.177: Patient 35 (stroke) LOS on ASU: 3.195 +42.937: Patient 36 (stroke) arrive at ASU. +42.937: Patient 36 (stroke) post-ASU: other +42.937: Patient 36 (stroke) LOS on ASU: 6.028 +46.714: Patient 37 (neuro) arrive at ASU. +46.714: Patient 37 (neuro) post-ASU: other +46.714: Patient 37 (neuro) LOS on ASU: 3.221 +46.767: Patient 38 (neuro) arrive at ASU. +46.767: Patient 38 (neuro) post-ASU: other +46.767: Patient 38 (neuro) LOS on ASU: 7.771 +47.236: Patient 39 (stroke) arrive at ASU. +47.236: Patient 39 (stroke) post-ASU: other +47.236: Patient 39 (stroke) LOS on ASU: 2.514 +47.902: Patient 40 (stroke) arrive at ASU. +47.902: Patient 40 (stroke) post-ASU: rehab +47.902: Patient 40 (stroke) LOS on ASU: 5.220 +49.022: Patient 41 (other) arrive at ASU. +49.022: Patient 41 (other) post-ASU: other +49.022: Patient 41 (other) LOS on ASU: 1.885 +49.181: Patient 42 (stroke) arrive at ASU. +49.181: Patient 42 (stroke) post-ASU: other +49.181: Patient 42 (stroke) LOS on ASU: 9.292 +49.838: Patient 43 (stroke) arrive at ASU. +49.838: Patient 43 (stroke) post-ASU: other +49.838: Patient 43 (stroke) LOS on ASU: 7.459 +53.122: Patient 40 (stroke) arrive at rehab. +53.122: Patient 40 (stroke) post-rehab: esd +53.122: Patient 40 (stroke) LOS on rehab unit: 26.316 diff --git a/outputs/suptable1.csv b/outputs/suptable1.csv index 01a33a1..868de76 100644 --- a/outputs/suptable1.csv +++ b/outputs/suptable1.csv @@ -1,12 +1,12 @@ unit,beds,prob_delay_current,1_in_n_delay_current,prob_delay_no_complex_neuro,1_in_n_delay_no_complex_neuro asu,10,0.13,8.0,0.08,13.0 -asu,11,0.09,12.0,0.05,20.0 -asu,12,0.06,18.0,0.03,36.0 -asu,13,0.03,29.0,0.02,66.0 -asu,14,0.02,52.0,0.01,128.0 -asu,15,0.01,96.0,0.0,284.0 -rehab,12,0.11,9.0,0.05,19.0 -rehab,13,0.08,13.0,0.03,33.0 -rehab,14,0.05,20.0,0.02,61.0 -rehab,15,0.03,34.0,0.01,119.0 -rehab,16,0.02,56.0,0.0,231.0 +asu,11,0.08,12.0,0.05,21.0 +asu,12,0.06,18.0,0.03,37.0 +asu,13,0.03,31.0,0.01,67.0 +asu,14,0.02,53.0,0.01,139.0 +asu,15,0.01,97.0,0.0,290.0 +rehab,12,0.11,9.0,0.06,18.0 +rehab,13,0.08,13.0,0.03,30.0 +rehab,14,0.05,19.0,0.02,54.0 +rehab,15,0.03,30.0,0.01,105.0 +rehab,16,0.02,51.0,0.01,193.0 diff --git a/outputs/table2.csv b/outputs/table2.csv index b91626e..1211d1b 100644 --- a/outputs/table2.csv +++ b/outputs/table2.csv @@ -1,13 +1,13 @@ unit,beds,prob_delay_current,1_in_n_delay_current,prob_delay_5%,1_in_n_delay_5% asu,9,0.18,6.0,, asu,10,0.13,8.0,0.15,7.0 -asu,11,0.09,12.0,0.1,10.0 -asu,12,0.06,18.0,0.07,14.0 -asu,13,0.03,29.0,0.04,23.0 -asu,14,0.02,52.0,0.03,39.0 +asu,11,0.08,12.0,0.1,10.0 +asu,12,0.06,18.0,0.07,15.0 +asu,13,0.03,31.0,0.04,23.0 +asu,14,0.02,53.0,0.03,39.0 rehab,10,0.2,5.0,, rehab,12,0.11,9.0,0.13,8.0 rehab,13,0.08,13.0,0.09,11.0 -rehab,14,0.05,20.0,0.06,16.0 -rehab,15,0.03,34.0,0.04,26.0 -rehab,16,0.02,56.0,0.02,40.0 +rehab,14,0.05,19.0,0.06,16.0 +rehab,15,0.03,30.0,0.04,24.0 +rehab,16,0.02,51.0,0.03,37.0 diff --git a/outputs/table3.csv b/outputs/table3.csv index 65c6bfc..641f05d 100644 --- a/outputs/table3.csv +++ b/outputs/table3.csv @@ -1,10 +1,10 @@ dedicated_acute,dedicated_rehab,pooled,pdelay_acute,pdelay_rehab,1_in_n_delay_acute,1_in_n_delay_rehab -0,0,22,0.062,0.062,16,16 -0,0,26,0.016,0.016,64,64 -14,12,0,0.019,0.109,52,9 -11,11,4,0.042,0.082,24,12 -11,10,5,0.035,0.083,28,12 -10,10,6,0.039,0.061,25,17 -10,9,7,0.037,0.061,27,16 -9,9,8,0.039,0.049,26,20 -9,8,9,0.038,0.049,26,20 +0,0,22,0.065,0.065,15,15 +0,0,26,0.016,0.016,61,61 +14,12,0,0.019,0.11,53,9 +11,11,4,0.043,0.09,24,11 +11,10,5,0.036,0.091,28,11 +10,10,6,0.041,0.066,25,15 +10,9,7,0.038,0.066,26,15 +9,9,8,0.041,0.053,24,19 +9,8,9,0.04,0.053,25,19 diff --git a/requirements.txt b/requirements.txt index 7d3dc9f..d12ed1c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,3 +1,4 @@ +genbadge==1.1.2 ipykernel==6.29.5 jinja2==3.1.5 joblib==1.4.2 @@ -11,8 +12,9 @@ pip==25.0 plotly_express==0.4.1 pylint==3.3.4 pytest==8.3.4 +pytest-cov==6.2.1 pytest-xdist==3.6.1 rich==13.9.4 simpy==4.1.1 -sim-tools==0.9.1 +sim-tools==0.10.0 -e .[dev] \ No newline at end of file diff --git a/tests/exp_results/asu_occupancy.csv b/tests/exp_results/asu_occupancy.csv index ed78367..c559484 100644 --- a/tests/exp_results/asu_occupancy.csv +++ b/tests/exp_results/asu_occupancy.csv @@ -1,22 +1,20 @@ beds,freq,pct,c_pct,prob_delay,1_in_n_delay 1,2,0.001095890410958904,0.001095890410958904,1.0,1.0 -2,12,0.006575342465753425,0.0076712328767123295,0.8571428571428571,1.0 -3,57,0.03123287671232877,0.0389041095890411,0.8028169014084506,1.0 -4,104,0.05698630136986301,0.0958904109589041,0.5942857142857143,2.0 -5,162,0.08876712328767124,0.18465753424657533,0.4807121661721069,2.0 -6,258,0.14136986301369864,0.32602739726027397,0.4336134453781513,2.0 -7,279,0.15287671232876712,0.47890410958904106,0.31922196796338675,3.0 -8,264,0.14465753424657535,0.6235616438356164,0.2319859402460457,4.0 -9,235,0.12876712328767123,0.7523287671232877,0.17115804806991988,6.0 -10,159,0.08712328767123288,0.8394520547945206,0.10378590078328982,10.0 -11,114,0.06246575342465754,0.9019178082191781,0.0692588092345079,14.0 -12,87,0.04767123287671233,0.9495890410958905,0.050201961915753025,20.0 -13,36,0.019726027397260273,0.9693150684931507,0.020350480497456188,49.0 -14,27,0.014794520547945205,0.9841095890410959,0.015033407572383074,67.0 -15,14,0.007671232876712329,0.9917808219178083,0.007734806629834254,129.0 -16,6,0.0032876712328767125,0.995068493150685,0.003303964757709251,303.0 -17,5,0.0027397260273972603,0.9978082191780823,0.002745744096650192,364.0 -18,1,0.000547945205479452,0.9983561643835617,0.000548847420417124,1822.0 -19,0,0.0,0.9983561643835617,0.0,inf -20,2,0.001095890410958904,0.9994520547945206,0.0010964912280701754,912.0 -21,1,0.000547945205479452,1.0,0.000547945205479452,1825.0 +2,14,0.007671232876712329,0.008767123287671232,0.875,1.0 +3,72,0.03945205479452055,0.04821917808219178,0.8181818181818181,1.0 +4,101,0.055342465753424656,0.10356164383561645,0.5343915343915343,2.0 +5,185,0.10136986301369863,0.20493150684931508,0.4946524064171123,2.0 +6,244,0.1336986301369863,0.3386301369863014,0.3948220064724919,3.0 +7,277,0.15178082191780823,0.49041095890410963,0.3094972067039106,3.0 +8,271,0.14849315068493152,0.6389041095890411,0.2324185248713551,4.0 +9,236,0.1293150684931507,0.7682191780821918,0.1683309557774608,6.0 +10,168,0.09205479452054795,0.8602739726027397,0.1070063694267516,9.0 +11,109,0.059726027397260274,0.92,0.06491959499702203,15.0 +12,66,0.03616438356164384,0.9561643835616439,0.03782234957020057,26.0 +13,33,0.01808219178082192,0.9742465753424658,0.01856017997750281,54.0 +14,17,0.009315068493150684,0.9835616438356165,0.009470752089136489,106.0 +15,15,0.00821917808219178,0.9917808219178083,0.008287292817679558,121.0 +16,8,0.004383561643835616,0.9961643835616438,0.0044004400440044,227.0 +17,6,0.0032876712328767125,0.9994520547945206,0.0032894736842105266,304.0 +18,0,0.0,0.9994520547945206,0.0,inf +19,1,0.000547945205479452,1.0,0.000547945205479452,1825.0 diff --git a/tests/exp_results/audit_list.csv b/tests/exp_results/audit_list.csv index 404f695..277c0a2 100644 --- a/tests/exp_results/audit_list.csv +++ b/tests/exp_results/audit_list.csv @@ -1,1826 +1,1826 @@ time,asu_occupancy,rehab_occupancy -1095,8,13 -1096,7,14 -1097,8,14 -1098,8,14 -1099,8,14 -1100,10,15 -1101,10,15 -1102,5,14 -1103,3,13 -1104,2,13 -1105,1,13 -1106,4,13 -1107,3,13 -1108,6,13 -1109,4,11 -1110,4,10 -1111,8,8 -1112,9,7 -1113,8,7 -1114,7,8 -1115,7,8 -1116,7,8 -1117,7,8 -1118,7,8 -1119,8,7 -1120,7,7 -1121,7,8 -1122,9,8 -1123,9,8 -1124,10,8 -1125,14,8 -1126,16,8 -1127,12,9 -1128,12,10 -1129,12,11 -1130,9,11 -1131,7,12 -1132,8,11 -1133,9,11 -1134,10,9 -1135,11,9 -1136,9,8 -1137,9,8 -1138,7,7 -1139,10,7 -1140,8,7 -1141,4,9 -1142,4,9 -1143,8,9 -1144,8,9 -1145,8,10 -1146,9,10 -1147,6,11 -1148,6,10 -1149,5,10 -1150,4,10 -1151,5,10 -1152,6,10 -1153,7,10 -1154,9,9 -1155,8,9 -1156,9,9 -1157,9,9 -1158,12,9 -1159,12,10 -1160,13,10 -1161,15,9 -1162,12,9 -1163,13,10 -1164,15,11 -1165,12,11 -1166,16,11 -1167,15,12 -1168,16,11 -1169,15,11 -1170,13,11 -1171,14,11 -1172,11,11 -1173,13,11 -1174,13,10 -1175,13,10 -1176,11,9 -1177,9,11 -1178,10,11 -1179,10,11 -1180,12,11 -1181,13,11 -1182,12,11 -1183,13,12 -1184,12,13 -1185,15,13 -1186,13,13 -1187,11,14 -1188,13,14 -1189,14,12 -1190,16,11 -1191,17,11 -1192,17,12 -1193,17,13 -1194,14,13 -1195,9,13 -1196,10,12 -1197,8,11 -1198,9,11 -1199,9,9 -1200,8,7 -1201,8,7 -1202,7,7 -1203,7,6 -1204,7,7 -1205,10,7 -1206,9,7 -1207,9,9 -1208,7,10 -1209,7,11 -1210,6,10 -1211,7,11 -1212,8,11 -1213,9,10 -1214,11,10 -1215,12,9 -1216,11,10 -1217,8,12 -1218,8,11 -1219,7,11 -1220,8,10 -1221,8,10 -1222,7,7 -1223,9,8 -1224,7,7 -1225,5,7 -1226,6,6 -1227,8,5 -1228,6,5 -1229,8,6 -1230,8,5 -1231,10,5 -1232,8,6 -1233,6,7 -1234,5,7 -1235,6,8 -1236,5,9 -1237,4,9 -1238,4,8 -1239,3,9 -1240,4,9 -1241,6,9 -1242,6,9 -1243,4,9 -1244,4,9 -1245,6,9 -1246,7,10 -1247,8,10 -1248,9,11 -1249,9,11 -1250,10,8 -1251,9,8 -1252,8,8 -1253,7,8 -1254,7,8 -1255,3,8 -1256,4,8 -1257,6,8 -1258,6,7 +1095,8,16 +1096,7,16 +1097,5,16 +1098,3,15 +1099,6,15 +1100,6,13 +1101,5,12 +1102,7,12 +1103,7,13 +1104,7,12 +1105,8,12 +1106,7,13 +1107,8,13 +1108,10,11 +1109,12,11 +1110,13,11 +1111,12,11 +1112,10,11 +1113,7,12 +1114,9,14 +1115,9,14 +1116,10,14 +1117,7,15 +1118,6,15 +1119,7,15 +1120,8,13 +1121,9,13 +1122,8,12 +1123,12,13 +1124,11,14 +1125,12,14 +1126,9,15 +1127,4,16 +1128,3,16 +1129,2,16 +1130,5,16 +1131,6,14 +1132,6,13 +1133,7,13 +1134,8,13 +1135,7,12 +1136,7,13 +1137,7,13 +1138,6,11 +1139,4,11 +1140,3,11 +1141,3,11 +1142,3,10 +1143,4,10 +1144,3,10 +1145,5,9 +1146,5,9 +1147,6,9 +1148,3,9 +1149,2,10 +1150,4,11 +1151,4,11 +1152,4,11 +1153,3,10 +1154,4,9 +1155,5,7 +1156,6,7 +1157,8,7 +1158,8,7 +1159,7,7 +1160,6,7 +1161,5,7 +1162,3,7 +1163,3,8 +1164,4,8 +1165,8,7 +1166,10,7 +1167,9,7 +1168,7,8 +1169,6,9 +1170,5,9 +1171,5,8 +1172,5,8 +1173,5,8 +1174,7,8 +1175,6,8 +1176,6,8 +1177,8,6 +1178,6,8 +1179,7,8 +1180,7,8 +1181,6,9 +1182,7,10 +1183,6,10 +1184,6,11 +1185,2,12 +1186,4,12 +1187,4,12 +1188,2,12 +1189,4,12 +1190,3,12 +1191,4,11 +1192,6,10 +1193,7,10 +1194,7,10 +1195,6,11 +1196,9,10 +1197,7,11 +1198,10,12 +1199,9,13 +1200,8,12 +1201,11,11 +1202,7,13 +1203,8,13 +1204,10,13 +1205,10,13 +1206,11,14 +1207,13,14 +1208,9,14 +1209,8,14 +1210,8,14 +1211,8,15 +1212,9,15 +1213,7,16 +1214,8,17 +1215,5,17 +1216,8,17 +1217,6,17 +1218,3,16 +1219,4,16 +1220,7,14 +1221,5,14 +1222,3,13 +1223,2,14 +1224,3,13 +1225,4,13 +1226,5,12 +1227,5,11 +1228,4,10 +1229,6,10 +1230,7,9 +1231,5,9 +1232,7,9 +1233,7,9 +1234,9,9 +1235,7,10 +1236,7,10 +1237,6,10 +1238,5,9 +1239,6,8 +1240,5,6 +1241,9,6 +1242,7,6 +1243,6,6 +1244,8,6 +1245,6,6 +1246,4,5 +1247,5,5 +1248,6,5 +1249,8,5 +1250,10,5 +1251,10,4 +1252,9,4 +1253,9,5 +1254,8,6 +1255,6,6 +1256,4,6 +1257,7,6 +1258,6,6 1259,7,6 -1260,7,6 -1261,10,6 -1262,9,7 -1263,9,7 -1264,9,7 -1265,9,5 -1266,10,5 -1267,10,5 -1268,8,6 -1269,8,6 -1270,10,6 -1271,9,6 -1272,11,6 -1273,9,7 -1274,9,7 -1275,11,8 -1276,11,9 -1277,7,12 -1278,7,11 -1279,9,11 -1280,7,12 -1281,6,13 -1282,7,12 -1283,9,11 -1284,9,11 -1285,7,11 -1286,7,14 -1287,5,13 -1288,3,13 -1289,4,13 -1290,9,14 -1291,10,14 -1292,10,15 -1293,7,16 -1294,6,18 -1295,7,18 -1296,6,19 -1297,7,18 -1298,10,18 -1299,9,18 -1300,7,17 -1301,6,16 -1302,8,14 -1303,6,14 -1304,7,13 -1305,6,13 -1306,8,13 -1307,5,13 -1308,5,13 -1309,9,12 -1310,9,12 -1311,5,12 -1312,5,12 -1313,5,11 -1314,5,12 -1315,6,10 -1316,6,10 -1317,6,11 -1318,5,10 -1319,6,10 -1320,8,10 -1321,6,10 -1322,5,10 -1323,4,10 -1324,4,10 -1325,4,10 -1326,3,10 -1327,3,10 -1328,2,10 -1329,3,11 -1330,2,12 -1331,3,11 -1332,4,9 -1333,5,10 -1334,6,10 -1335,8,9 -1336,7,9 -1337,8,9 -1338,6,10 -1339,7,10 -1340,5,9 -1341,5,8 +1260,7,7 +1261,6,7 +1262,7,6 +1263,9,5 +1264,8,4 +1265,6,4 +1266,8,4 +1267,8,4 +1268,7,3 +1269,11,3 +1270,12,4 +1271,10,5 +1272,12,5 +1273,13,5 +1274,9,6 +1275,7,5 +1276,6,5 +1277,8,6 +1278,8,7 +1279,7,7 +1280,5,6 +1281,4,6 +1282,5,6 +1283,5,6 +1284,8,5 +1285,6,5 +1286,7,5 +1287,7,5 +1288,6,5 +1289,5,5 +1290,5,5 +1291,8,4 +1292,6,5 +1293,6,5 +1294,6,4 +1295,6,4 +1296,5,5 +1297,5,4 +1298,4,5 +1299,3,5 +1300,5,5 +1301,4,5 +1302,5,4 +1303,6,4 +1304,6,4 +1305,6,4 +1306,8,3 +1307,7,3 +1308,7,3 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