Skip to content

Latest commit

 

History

History
58 lines (47 loc) · 1.54 KB

README.md

File metadata and controls

58 lines (47 loc) · 1.54 KB

Accelarousal Study (NAT1) Methods

Getting Started

Prerequisites

  • R (3.6.1)
  • RStudio (1.2.5019)
  • Required packages

Installing R Packages

To install required R packages, run script setup.R.

Folder Structure

  • data: Raw and processed data.
  • plots: Output plots of correlation matrices, clustering dendrogram, linear models, machine learning models.
  • outputs: CSV/Text outputs.
  • settings: Common setting of the project.
  • scripts: Main script for analysis and data modeling.
  • utils: Common ultility functions.

Configuration

All global settings are placed in settings/settings.R.

Analysis Timing Settings

The default time-series anlysis is using data of 30 seconds before to predict the class of next 5 seconds. You can change these values for different analysis.

TIME_PREV_SECONDS <- 30  # [5, 10, 15, 30]
TIME_NEXT_SECONDS <- 5

Plotly

As the project is using Plotly as a visualization tool, you can set up your Plotly account in settings/settings.R.

PLOTLY_USERNAME <- "<Your Plotly Username>"
PLOTLY_API_KEY <- "<Your Plotly API Key>"

Orca

The Plotly lib needs orca as an static image exporting backend. Follow instruction at https://github.com/plotly/orca for installation.

Script set

Correllation Analysis

  • Run scripts/correlation.R

Clustering

  • Run scripts/clustering.R

Linear Model

  • Run scripts/linearModel.R

Additional Tools

Style Guide

http://jef.works/R-style-guide/

Install Styler

In RStudio, run following commands:

install.packages("styler")