makeFlow-package {makeFlow}

Visualizing Sequential Classifications

Description

A user-friendly tool for visualizing categorical or group movement.

Details

The DESCRIPTION file:

Package:	makeFlow
Type:	Package
Title:	Visualizing Sequential Classifications
Version:	1.0.2
Date:	2016-08-22
Author:	Alex J. Krebs
Maintainer:	Alex J. Krebs <[e-mail]>
Description:	A user-friendly tool for visualizing categorical or group movement.
License:	GPL (>= 2)
Imports:	dplyr, RColorBrewer
Copyright:	Copyright Notice GENERAL DISCLAIMER This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2, or (at your option) any later version. This program 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 GNU General Public License for more details. In short: You may use it any way you like, as long as you do not charge money for it, remove this notice, or hold anyone liable for its results. Also, please acknowledge the source and communicate changes to the author. If this software is used in work presented for publication, kindly reference it using for example: Krebs AJ (2016): makeFlow: Visualizing Sequential Classifications. Be sure to reference R itself and other libraries used.
RoxygenNote:	5.0.1

Index of help topics:

FlowSummaries           FlowSummaries()
GateSummaries           GateSummaries()
addAlpha                addAlpha()
colorCount              colorCount()
makeFlow                makeFlow()
makeFlow-package        Visualizing Sequential Classifications
shelters                shelters

Users should ensure all classFields (columns) are explicitly defined in the same dataset. colorCount(), FlowSummaries(), GateSummaries(), and makeFlow() can all operate with the same two basic inputs: data and classFields. Graphical parameters can be defined with additional makeFlow() arguments.

Author(s)

Alex J. Krebs

Maintainer: Alex J. Krebs <[e-mail]>

Examples

##  Data:
##  carData <- mtcars
##  carData$car <- "All Cars"
##  carData$speedclass <- ifelse(carData$qsec < 15, "Fast",
##                          ifelse(carData$qsec < 18, "Mid-Speed","Slow"))
##  carData$speedclass <- factor(x = carData$speedclass, levels = c("Slow","Mid-Speed","Fast"))
##  
##  Create Diagram:
##  makeFlow(data = carData, classFields = c("car","cyl","speedclass"),
##    gateWidth = 20, minVerticalBtwnGates = .15, distanceBtwnGates = 70,
##    fieldLabels = c("", "Cylinders","Speed"), gateBorder = "black")

##  Generate underlying tables using GateSummaries() and FlowSummaries()