Trying out panache

.github/ISSUE_TEMPLATE/development_task.md

@@ -1,33 +1,39 @@
 ---
 name: Multisignal Renewal Dev Task Template
-about: A template for writing specs following Multisignal Renewal project standards
-title: ''
+about: A template for writing specs following Multisignal Renewal project
+  standards
+title: ""
 labels: ["development task"]
-assignees: ''
+assignees: ""
 ---
 
-This template should be used as an outline. It may not be necessary to fill out every section. Delete this block of text and fill in anything in brackets.
+This template should be used as an outline.
+It may not be necessary to fill out every section.
+Delete this block of text and fill in anything in brackets.
 
 Make sure you follow the project's standards specified in [this adr doc](https://github.com/cdcent/cfa-multisignal-renewal/blob/main/ADR/model/development_standards.md) (private link)
 
 ## Goal
 
-[1-3 sentence summary of the issue or feature request. E.g. "We want to be able to ..."]
+\[1-3 sentence summary of the issue or feature request.
+E.g. "We want to be able to ..."\]
 
 ## Context
 
-[Short paragraph describing how the issue arose and constraints imposed by the existing code architecture]
+\[Short paragraph describing how the issue arose and constraints imposed by the existing code architecture\]
 
 ## Required features
 
-- [Describe each thing you need the code to do to achieve the goal]
-- [Example 1: Use a config to set input and output paths]
-- [Example 2: Read in some-dataset and output some-transformed-dataset]
+- \[Describe each thing you need the code to do to achieve the goal\]
+- \[Example 1: Use a config to set input and output paths\]
+- \[Example 2: Read in some-dataset and output some-transformed-dataset\]
 - etc...
 
 ## Specifications
 
-[A checklist to keep track of details for each feature. At least one specification per feature is recommended. Edit the example below:]
+\[A checklist to keep track of details for each feature.
+At least one specification per feature is recommended.
+Edit the example below:\]
 
 - [ ] EX2: A function that reads data from the `some-api` API and returns the dataset
 - [ ] EX2: Another function that inputs the dataset, performs $x$ transform, and outputs $y$
@@ -39,8 +45,8 @@ Make sure you follow the project's standards specified in [this adr doc](https:/
 
 ## Out of scope
 
-- [Things out of scope from this issue/PR]
+- \[Things out of scope from this issue/PR\]
 
 ## Related documents
 
-- [Link to related scripts, functions, issues, PRs, conversations, datasets, etc.]
+- \[Link to related scripts, functions, issues, PRs, conversations, datasets, etc.\]

.pre-commit-config.yaml

@@ -6,7 +6,7 @@ repos:
     hooks:
       - id: check-added-large-files
       - id: check-yaml
-        args: [--unsafe]
+        args: [ --unsafe ]
       - id: check-toml
       - id: end-of-file-fixer
       - id: mixed-line-ending
@@ -26,26 +26,24 @@ repos:
       - id: numpydoc-validation
   #####
   # Quarto
-  - repo: local
+  - repo: https://github.com/jolars/panache
+    rev: v2.41.0
+
     hooks:
-      - id: format-qmd-python
-        name: Format Python in QMD
-        entry: python docs_scripts/quarto_python_formatter.py "-q --line-length 79"
-        language: python
-        files: \.qmd$
-        additional_dependencies: [ruff]
+      - id: panache-format
+      - id: panache-lint
   #####
   # Secrets
   - repo: https://github.com/Yelp/detect-secrets
     rev: v1.5.0
     hooks:
       - id: detect-secrets
-        args: ["--baseline", ".secrets.baseline"]
+        args: [ "--baseline", ".secrets.baseline" ]
         exclude: package.lock.json
   ####
   # Typos
   - repo: https://github.com/crate-ci/typos
     rev: v1
     hooks:
       - id: typos
-        args: ["--force-exclude"]
+        args: [ "--force-exclude" ]

README.md

@@ -7,27 +7,29 @@ A renewal model estimates new infections from recent past infections using a gen
 From this, it infers $\mathcal{R}(t)$, the time-varying reproduction number, which indicates whether the number of infectious individuals is increasing or decreasing.
 The core renewal equation is:
 
-$$I(t) = \mathcal{R}(t) \sum_{s} I(t-s) \, w(s)$$
+$$
+I(t) = \mathcal{R}(t) \sum_{s} I(t-s) \, w(s)
+$$
 
 where $w(s)$ is the generation interval distribution: the probability that $s$ time units separate infection in an index case and a secondary case.
 
 However inference is complicated by the fact that observational data require their own models ([Bhatt et al., 2023, §2](https://doi.org/10.1093/jrsssa/qnad030)).
 The observation equation links infections to expected observations:
 
-$$\mu(t) = \alpha \sum_{s} I(t-s) \, \pi(s)$$
+$$
+\mu(t) = \alpha \sum_{s} I(t-s) \, \pi(s)
+$$
 
 where $\alpha$ is the ascertainment rate and $\pi(s)$ is the delay distribution from infection to observation.
 
-The Pyrenew package provides configurable classes which encapsulate these components and methods to orchestrate the configuration and composition of these processes
-resulting in programs which clearly express the model structure and choices, allowing for both ease of model specification and dissemination.
+The Pyrenew package provides configurable classes which encapsulate these components and methods to orchestrate the configuration and composition of these processes resulting in programs which clearly express the model structure and choices, allowing for both ease of model specification and dissemination.
 The fundamental building block is the `RandomVariable` abstract base class, which allows for sampling from distributions, computing a mechanistic equation, or simply returning a fixed value.
 
-We use `RandomVariable`s to build probabilistic models. We represent complete models as concrete subclasses of the `Model` abstract base class.
+We use `RandomVariable`s to build probabilistic models.
+We represent complete models as concrete subclasses of the `Model` abstract base class.
 The `PyrenewBuilder` class orchestrates the composition of `RandomVariables` into a `Model`.
 
-PyRenew's strength lies in multi-signal integration for information pooling across diverse observed data streams
-such as hospital admissions, wastewater concentrations, and emergency department visits
-where each signal has distinct observation delays, noise characteristics, and spatial resolutions.
+PyRenew's strength lies in multi-signal integration for information pooling across diverse observed data streams such as hospital admissions, wastewater concentrations, and emergency department visits where each signal has distinct observation delays, noise characteristics, and spatial resolutions.
 For single-signal renewal models, we recommend the excellent R package [EpiNow2](https://epiforecasts.io/EpiNow2/).
 
 ## Installation
@@ -40,77 +42,63 @@ pip install git+https://github.com/CDCgov/PyRenew@main
 
 ## Models Implemented With PyRenew
 
-- [CDCgov/pyrenew-covid-wastewater](https://github.com/CDCgov/pyrenew-covid-wastewater): _Models and infrastructure for forecasting COVID-19 hospitalizations using wastewater data with PyRenew._
-- [CDCgov/pyrenew-flu-light](https://github.com/CDCgov/pyrenew-flu-light/): _An instantiation in PyRenew of an influenza forecasting model used in the 2023-24 respiratory season._
+- [CDCgov/pyrenew-covid-wastewater](https://github.com/CDCgov/pyrenew-covid-wastewater): *Models and infrastructure for forecasting COVID-19 hospitalizations using wastewater data with PyRenew.*
+- [CDCgov/pyrenew-flu-light](https://github.com/CDCgov/pyrenew-flu-light/): *An instantiation in PyRenew of an influenza forecasting model used in the 2023-24 respiratory season.*
 
 ## Resources
 
-* [The PyRenew documentation suite](https://cdcgov.github.io/PyRenew) provides API reference documentation and  tutorials on implementing multisignal renewal models with PyRenew.
-* Additional reading on renewal processes in epidemiology
-  * [_Semi-mechanistic Bayesian modelling of COVID-19 with renewal processes_](https://academic.oup.com/jrsssa/article-pdf/186/4/601/54770289/qnad030.pdf)
-  * [_Unifying incidence and prevalence under a time-varying general branching process_](https://link.springer.com/content/pdf/10.1007/s00285-023-01958-w.pdf)
+- [The PyRenew documentation suite](https://cdcgov.github.io/PyRenew) provides API reference documentation and tutorials on implementing multisignal renewal models with PyRenew.
+- Additional reading on renewal processes in epidemiology
+  - [_Semi-mechanistic Bayesian modelling of COVID-19 with renewal processes_](https://academic.oup.com/jrsssa/article-pdf/186/4/601/54770289/qnad030.pdf)
+  - [_Unifying incidence and prevalence under a time-varying general branching process_](https://link.springer.com/content/pdf/10.1007/s00285-023-01958-w.pdf)
 
 ## General Disclaimer
 
-This repository was created for use by CDC programs to collaborate on public health related projects in support of the [CDC mission](https://www.cdc.gov/about/cdc/index.html#cdc_about_cio_mission-our-mission).  GitHub is not hosted by the CDC, but is a third party website used by CDC and its partners to share information and collaborate on software. CDC use of GitHub does not imply an endorsement of any one particular service, product, or enterprise.
+This repository was created for use by CDC programs to collaborate on public health related projects in support of the [CDC mission](https://www.cdc.gov/about/cdc/index.html#cdc_about_cio_mission-our-mission).
+GitHub is not hosted by the CDC, but is a third party website used by CDC and its partners to share information and collaborate on software.
+CDC use of GitHub does not imply an endorsement of any one particular service, product, or enterprise.
 
 ## Public Domain Standard Notice
 
-This repository constitutes a work of the United States Government and is not
-subject to domestic copyright protection under 17 USC § 105. This repository is in
-the public domain within the United States, and copyright and related rights in
-the work worldwide are waived through the [CC0 1.0 Universal public domain dedication](https://creativecommons.org/publicdomain/zero/1.0/).
-All contributions to this repository will be released under the CC0 dedication. By
-submitting a pull request you are agreeing to comply with this waiver of
-copyright interest.
+This repository constitutes a work of the United States Government and is not subject to domestic copyright protection under 17 USC § 105.
+This repository is in the public domain within the United States, and copyright and related rights in the work worldwide are waived through the [CC0 1.0 Universal public domain dedication](https://creativecommons.org/publicdomain/zero/1.0/).
+All contributions to this repository will be released under the CC0 dedication.
+By submitting a pull request you are agreeing to comply with this waiver of copyright interest.
 
 ## License Standard Notice
 
 This repository is licensed under ASL v2 or later.
 
-This source code in this repository is free: you can redistribute it and/or modify it under
-the terms of the Apache Software License version 2, or (at your option) any
-later version.
+This source code in this repository is free: you can redistribute it and/or modify it under the terms of the Apache Software License version 2, or (at your option) any later version.
 
-This source code in this repository is distributed in the hope that it will be useful, but WITHOUT ANY
-WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
-PARTICULAR PURPOSE. See the Apache Software License for more details.
+This source code in this repository is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+See the Apache Software License for more details.
 
-You should have received a copy of the Apache Software License along with this
-program. If not, see [http://www.apache.org/licenses/LICENSE-2.0.html](http://www.apache.org/licenses/LICENSE-2.0.html).
+You should have received a copy of the Apache Software License along with this program.
+If not, see [http://www.apache.org/licenses/LICENSE-2.0.html](http://www.apache.org/licenses/LICENSE-2.0.html).
 
 The source code forked from other open source projects will inherit its license.
 
 ## Privacy Standard Notice
 
-This repository contains only non-sensitive, publicly available data and
-information. All material and community participation is covered by the
-[Disclaimer](https://github.com/CDCgov/template/blob/master/DISCLAIMER.md)
-and [Code of Conduct](https://github.com/CDCgov/template/blob/master/code-of-conduct.md).
+This repository contains only non-sensitive, publicly available data and information.
+All material and community participation is covered by the [Disclaimer](https://github.com/CDCgov/template/blob/master/DISCLAIMER.md) and [Code of Conduct](https://github.com/CDCgov/template/blob/master/code-of-conduct.md).
 For more information about CDC's privacy policy, please visit [http://www.cdc.gov/other/privacy.html](https://www.cdc.gov/other/privacy.html).
 
 ## Contributing Standard Notice
 
-Anyone is encouraged to contribute to the repository by [forking](https://help.github.com/articles/fork-a-repo)
-and submitting a pull request. (If you are new to GitHub, you might start with a
-[basic tutorial](https://help.github.com/articles/set-up-git).) By contributing
-to this project, you grant a world-wide, royalty-free, perpetual, irrevocable,
-non-exclusive, transferable license to all users under the terms of the
-[Apache Software License v2](http://www.apache.org/licenses/LICENSE-2.0.html) or
-later.
+Anyone is encouraged to contribute to the repository by [forking](https://help.github.com/articles/fork-a-repo) and submitting a pull request.
+(If you are new to GitHub, you might start with a [basic tutorial](https://help.github.com/articles/set-up-git).)
+By contributing to this project, you grant a world-wide, royalty-free, perpetual, irrevocable, non-exclusive, transferable license to all users under the terms of the [Apache Software License v2](http://www.apache.org/licenses/LICENSE-2.0.html) or later.
 
-All comments, messages, pull requests, and other submissions received through
-CDC including this GitHub page may be subject to applicable federal law, including but not limited to the Federal Records Act, and may be archived. Learn more at [http://www.cdc.gov/other/privacy.html](http://www.cdc.gov/other/privacy.html).
+All comments, messages, pull requests, and other submissions received through CDC including this GitHub page may be subject to applicable federal law, including but not limited to the Federal Records Act, and may be archived.
+Learn more at [http://www.cdc.gov/other/privacy.html](http://www.cdc.gov/other/privacy.html).
 
 ## Records Management Standard Notice
 
-This repository is not a source of government records but is a copy to increase
-collaboration and collaborative potential. All government records will be
-published through the [CDC web site](http://www.cdc.gov).
+This repository is not a source of government records but is a copy to increase collaboration and collaborative potential.
+All government records will be published through the [CDC web site](http://www.cdc.gov).
 
 ## Additional Standard Notices
 
-Please refer to [CDC's Template Repository](https://github.com/CDCgov/template)
-for more information about [contributing to this repository](https://github.com/CDCgov/template/blob/master/CONTRIBUTING.md),
-[public domain notices and disclaimers](https://github.com/CDCgov/template/blob/master/DISCLAIMER.md),
-and [code of conduct](https://github.com/CDCgov/template/blob/master/code-of-conduct.md).
+Please refer to [CDC's Template Repository](https://github.com/CDCgov/template) for more information about [contributing to this repository](https://github.com/CDCgov/template/blob/master/CONTRIBUTING.md), [public domain notices and disclaimers](https://github.com/CDCgov/template/blob/master/DISCLAIMER.md), and [code of conduct](https://github.com/CDCgov/template/blob/master/code-of-conduct.md).