From a2a532ed813c101c1762fa8278efa96b568e741d Mon Sep 17 00:00:00 2001 From: JulioV Date: Fri, 4 Dec 2020 15:33:30 -0500 Subject: [PATCH] Adjust figure width --- docs/file-structure.md | 2 +- docs/workflow-examples/analysis.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/file-structure.md b/docs/file-structure.md index 5664b4cb..767fa2d5 100644 --- a/docs/file-structure.md +++ b/docs/file-structure.md @@ -14,7 +14,7 @@ RAPIDS source code is saved in `src/`. The `src/data/` folder stores scripts to In the figure below, we represent the interactions between users and files. After a user modifies the configuration files mentioned above, the `Snakefile` file will search for and execute the Snakemake rules that contain the Python or R scripts necessary to generate or update the required output files (behavioral features, plots, etc.).
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Interaction diagram between the user, and important files in RAPIDS
diff --git a/docs/workflow-examples/analysis.md b/docs/workflow-examples/analysis.md index fe4b9fae..bb8260ec 100644 --- a/docs/workflow-examples/analysis.md +++ b/docs/workflow-examples/analysis.md @@ -28,7 +28,7 @@ The goal of this workflow is to find out if we can predict the daily symptom bur In total, our example workflow has nine steps that are in charge of sensor data preprocessing, feature extraction, feature cleaning, machine learning model training and model evaluation (see figure below). We ship this workflow with RAPIDS and share a database with [test data](https://osf.io/skqfv/files/) in an Open Science Framework repository.
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Modules of RAPIDS example workflow, from raw data to model evaluation