tests/testthat/test_createMeasurementsVariables.R

In saezlab/CARNIVAL: A CAusal Reasoning tool for Network Identification (from gene expression data) using Integer VALue programming

### This script is a unit test for the function createMeasurementsVariables
#
# Matteo Spatuzzi 2021

#Create Dummy Data
nodenames = c(paste("Node", seq(1, 5), sep = ""))
measurements_1 = c(5)
names(measurements_1) = c(nodenames[5])

priorKnowledgeNetwork_1 = matrix(c(nodenames[1], 1, nodenames[4], 
                                   nodenames[2], 1, nodenames[4],
                                   nodenames[3], -1, nodenames[1],
                                   nodenames[3], -1, nodenames[2],
                                   nodenames[4], 1, nodenames[5]), byrow = T, ncol = 3) %>% as.data.frame()
colnames(priorKnowledgeNetwork_1) = c("Node1", "sign", "Node2")

nodes <- data.frame( nodes = c(paste("Node", seq(1,5), sep = "")), 
                     nodesVars = c(paste("n", seq(1,5), sep = "")), 
                     nodesUpVars = c(paste("nU", seq(1,5), sep = "")),
                     nodesDownVars = c(paste("nD", seq(1,5), sep = "")),
                     nodesActStateVars = c(paste("nAc", seq(1,5), sep = "")),
                     nodesDistanceVars = c(paste("nDs", seq(1,5), sep = "")),
                     nodesType = c("P", "P", "P", "", "M") )

measurementsVariables <- createMeasurementsVariables(measurements_1, nodes, priorKnowledgeNetwork_1)

measurementsVariables_expected <- data.frame(nodes = c("Node5"), 
                                             value = c("5"), 
                                             measurementsVars = c("aD1"), 
                                             nodesVars = c("n5"))

test_that("Measurements variables check", {
  expect_equal(measurementsVariables_expected, measurementsVariables)
})