From 05468bafbf72d67ad97d08a4b7673e1ecc053f66 Mon Sep 17 00:00:00 2001 From: Alessandro Felder Date: Thu, 14 Dec 2023 14:52:05 +0100 Subject: [PATCH 1/2] Apply suggestions from code review Co-authored-by: sfmig <33267254+sfmig@users.noreply.github.com> --- README.md | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/README.md b/README.md index 8d4e8c00..df8ff773 100644 --- a/README.md +++ b/README.md @@ -15,6 +15,7 @@ # BrainGlobe Workflows +<<<<<<< HEAD `brainglobe-workflows` is a package that provides users with a number of out-of-the-box data analysis workflows employed in neuroscience, implemented using BrainGlobe tools. You can view the [full documentation for each workflow](https://brainglobe.info/documentation/brainglobe-workflows/index.html) online. You can also find the documentation for the backend BrainGlobe tools these workflows use [on our website](https://brainglobe.info/). @@ -22,6 +23,21 @@ You can also find the documentation for the backend BrainGlobe tools these workf At present, the package offers the following workflows: - [cellfinder](#cellfinder): Whole-brain detection, registration, and analysis. +======= +The main purpose of this repository is to host Python scripts and Command Line Interfaces that capture typical workflows of the BrainGlobe tools. + +These workflows should be representative of the most common use-cases and are meant to be easy to reuse. They also serve as an example of how to combine several BrainGlobe tools to achieve a goal, such as whole brain cell detection and atlas registration. +These workflows typically combine several BrainGlobe tools (possibly together with other tools) to achieve a goal, +such as whole brain cell detection and atlas registration. + +## Secondary purposes of brainglobe-workflows, for developers + +Secondarily, this repository further has related purposes for BrainGlobe code development itself. +* It contains benchmarks for these workflows to ensure performance is stable as the code changes + * (default) run benchmarks on CI with small data + * (optionally) specify a configuration (as a json file) to run benchmarks on locally available, typically "real", data + * these configurations are not intended to be user-facing +>>>>>>> af7935f (Apply suggestions from code review) ## Installation From fb32f5ee00cbe847cbf1fbb87452f06b04d8e930 Mon Sep 17 00:00:00 2001 From: alessandrofelder Date: Thu, 14 Dec 2023 15:02:25 +0100 Subject: [PATCH 2/2] [skip ci] Flesh out secondary purposes of repo Co-authored-by: sfmig <33267254+sfmig@users.noreply.github.com> --- README.md | 15 +++++---------- 1 file changed, 5 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index df8ff773..12eb85aa 100644 --- a/README.md +++ b/README.md @@ -15,7 +15,6 @@ # BrainGlobe Workflows -<<<<<<< HEAD `brainglobe-workflows` is a package that provides users with a number of out-of-the-box data analysis workflows employed in neuroscience, implemented using BrainGlobe tools. You can view the [full documentation for each workflow](https://brainglobe.info/documentation/brainglobe-workflows/index.html) online. You can also find the documentation for the backend BrainGlobe tools these workflows use [on our website](https://brainglobe.info/). @@ -23,21 +22,17 @@ You can also find the documentation for the backend BrainGlobe tools these workf At present, the package offers the following workflows: - [cellfinder](#cellfinder): Whole-brain detection, registration, and analysis. -======= -The main purpose of this repository is to host Python scripts and Command Line Interfaces that capture typical workflows of the BrainGlobe tools. These workflows should be representative of the most common use-cases and are meant to be easy to reuse. They also serve as an example of how to combine several BrainGlobe tools to achieve a goal, such as whole brain cell detection and atlas registration. -These workflows typically combine several BrainGlobe tools (possibly together with other tools) to achieve a goal, +These workflows typically combine several BrainGlobe tools (possibly together with other tools) to achieve a goal, such as whole brain cell detection and atlas registration. ## Secondary purposes of brainglobe-workflows, for developers -Secondarily, this repository further has related purposes for BrainGlobe code development itself. -* It contains benchmarks for these workflows to ensure performance is stable as the code changes - * (default) run benchmarks on CI with small data - * (optionally) specify a configuration (as a json file) to run benchmarks on locally available, typically "real", data - * these configurations are not intended to be user-facing ->>>>>>> af7935f (Apply suggestions from code review) +We also use these workflows to support code development. We do this by regularly benchmarking the time they take to complete to ensure performance is stable as the code changes. +* Developers can install these benchmarks locally via `pip install [dev]`. By executing `asv run`, the benchmarks will run with default parameters on a small dataset that is downloaded from [GIN](https://gin.g-node.org/G-Node/info/wiki). See [the asv docs](https://asv.readthedocs.io/en/v0.6.1/using.html#running-benchmarks) for further details on how to run benchmarks. +* Developers can also run these benchmarks on data available locally, by specifying the relevant paths in an input configuration file (JSON file). +* We additionally run and benchmark the workflows locally on a internal desktop machine with large example datasets. These benchmarks are run periodically and the results are made publicly available. ## Installation