tests/testthat/testTimeShift.R

In aleblancbio/timescale: A package for development time calculation and other time scalings

test_that("Composition timeScale on timeShift return initial values of scaledPeriod (non zero rate)", {
  conditions <- data.frame(time = seq(0,30,length.out = 10), temp = 30 + rnorm(10, 10, 5))
  model <- "modelLinear"
  param = list(a = 1, T0 = 10)
  
  #Initial time
  x1 = rep(0,10,length.out = 10)
  scaledPeriod = rep(10,10)
  
  #Compute x2 scaled period
  x2 <- timeShift(x1, scaledPeriod = scaledPeriod, model = model, conditions = conditions, param = param)
  scaledPeriodCalc <- timeScale(x1, x2, model = model, conditions = conditions, param = param)
  
  #Equality given some rounding
  expect_equal(scaledPeriod, scaledPeriodCalc, tolerance=1e-3)
})

test_that("Composition timeScale on timeShift return initial values of scaledPeriod (zero rate)", {
  conditions <- data.frame(time = seq(0,30,length.out = 10), temp = rnorm(10, 15, 5))
  model <- "modelLinear"
  param = list(a = 1, T0 = 10)
  
  #Initial time
  x1 = rep(0,10,length.out = 10)
  scaledPeriod = rep(10,10)
  
  #Compute x2 scaled period
  x2 <- timeShift(x1, scaledPeriod = scaledPeriod, model = model, conditions = conditions, param = param)
  scaledPeriodCalc <- timeScale(x1, x2, model = model, conditions = conditions, param = param)
  
  #Equality given some rounding
  expect_equal(scaledPeriod, scaledPeriodCalc, tolerance=1e-3)
})

test_that("timeShift return proper values for a simple case (with zero rate)", {
#to be written (important)
  
  conditions <- data.frame(time = seq(0,5), temp = c(0,15,10,20,20,0))
  model <- "modelLinear"
  param = list(a = 1, T0 = 10)
  
  #Initial time
  x1 = rep(0,6)
  scaledPeriod = c(0,5,10,15,20,25)
  
  #Compute x2 scaled period
  x2 <- timeShift(x1, scaledPeriod = scaledPeriod, model = model, conditions = conditions, param = param)
  answer <- c(0,2,3.5,4,4.5,5) #Careful check at the second number
  
  #Equality given some rounding
  expect_equal(x2, answer, tolerance=1e-3)
  
})

test_that("timeScale inverse return lower and upper bounds encompassing initial values (with zero rate)", {
  set.seed(6)
  conditions <- data.frame(time = seq(0,30,length.out = 10), temp = rnorm(10, 10, 5))
  model <- "modelLinear"
  param = list(a = 1, T0 = 10)
  
  #Initial time
  x1 = rep(0,10,length.out = 10)
  x2 = seq(0,30,length.out = 10)
  
  #Scaled time
  y1 <- rep(0,10,length.out = 10)
  y2 <- timeScale(x1, x2, model = model, conditions = conditions, param = param)
  y2
  #Scaling back to original time
  x2CalcUpper <- timeShift(x1, y2, model = model, conditions = conditions, param = param, assignConstant = c("upper"))
  x2CalcLower <- timeShift(x1, y2, model = model, conditions = conditions, param = param, assignConstant = c("lower"))
 
  #Within bounds given some rounding
  expect_true(all(x2 >= x2CalcLower - 1e-3 & x2 <= x2CalcUpper + 1e-3))
  #Seems not to work with integrate (timeScale estimate seem to be inconsistent as bounds change)
})

test_that("timeShift can deal with NA in conditions", {
  conditions <- data.frame(time = seq(0,30,length.out = 10), temp = 30 + rnorm(10, 10, 5))
  conditions$temp[3] <- NA
  model <- "modelLinear"
  param = list(a = 1, T0 = 10)
  
  #Initial time
  x1 = rep(0,10,length.out = 10)
  scaledPeriod = rep(10,10)
  
  #Compute x2 scaled period (expect error)
  expect_error(timeShift(x1, scaledPeriod = scaledPeriod, model = model, conditions = conditions, param = param))
})