ProcData Installation Instructions

ProcData is an R package for process data analysis. This page provides instructions on the installation of ProcData. If you need help during the installation process, please post your issue on our GitHub page. We will respond as soon as possible.

ProcData can be installed through the following three steps.

Step 1 Preparation

ProcData depends on R packages Rcpp for incorporating C++ code in R code and keras for training neural networks. If you would like to install ProcData from source, then compiler tools are needed. ProcData calls Python library Keras for building and training neural networks in Python. Some functions in ProcData require Python to work. Note that the following two steps do not have to be performed before installing ProcData. You will be prompted if R detects a missing component.

• Install compiler tools.
  • For Windows users, Rtools provides tools for building R packages from source. One can download Rtools and find its installation guide here.
  • For Mac users, Xcode provides tools necessary for compiling ProcData. Xcode can be obtained from Apple AppStore and the Xcode developer page. An Apple developer account is needed. More information about compiling R packages for macOS can be found at here.
• Install Python. We recommend using Anaconda for creating and managing Python environments. An installer can be found on its official website.

Step 2 Install ProcData and dependent R packages.

ProcData is available on CRAN. The package and its dependent packages can be installed by executing the following command in R.

install.packages("ProcData", dependencies=T)

The development version of ProcData can be installed from Github in R by the following command.

devtools::install_github("xytangtang/ProcData", dependencies=T)

Step 3 Install dependent Python libraries.

To finish installing R package keras, run the following commands in R.

library(keras)
install_keras(tensorflow="1.13.1")

Note:

• This step installs Python libraries Keras and Tensorflow. You will be asked if you would like to install Miniconda if R could not find an appropriate Python environment. Miniconda is a light-weight version of Anaconda. We recommend selecting yes to let R installs Miniconda if you have little experience with Anaconda or Python.

• The argument tensorflow="1.13.1" selects the version of Tensorflow to be installed. If nothing specified, the most recent version will be installed. The most recent version of Tensorflow is 2.2.0. However, there is some incompatibility between Tensorflow 2.x.x and the R package keras. For the most stable performance of ProcData, we highly recommend specifying tensorflow="1.13.1" when running install_keras.

• You can test whether keras is installed properly by running

mnist <- dataset_mnist()

More detailed information on installing keras can be found on keras website.