spa_queueingnetwork:

context("test-queueing_network.R")

test_that("Result is Data Frame", {
  expect_equal(class(queueing_network_poi_geom(10,10,0.3, 0.4, 2, 1, 0.6, 0.7)),"data.frame")
  expect_equal(class(queueing_network_poi_geom(1,1000,0.1, 0.9, 14, 2, 0.6, 0.7)),"data.frame")
  expect_equal(class(queueing_network_poi_geom(13,4,0.99, 0.99, 1, 2, 0.6, 0.7)),"data.frame")
})

test_that("Result is Data Frame with 4 Columns", {
  expect_equal(ncol(queueing_network_poi_geom(10,10,0.3, 0.4, 2, 1, 0.6, 0.7)),4)
  expect_equal(ncol(queueing_network_poi_geom(1,1000,0.1, 0.9, 14, 2, 0.6, 0.7)),4)
  expect_equal(ncol(queueing_network_poi_geom(13,4,0.99, 0.99, 1, 2, 0.6, 0.7)),4)
})


test_that("Result has predefined number of rows", {
  expect_equal(nrow(queueing_network_poi_geom(10,10,0.3, 0.4, 2, 1, 0.6, 0.7)),10)
  expect_equal(nrow(queueing_network_poi_geom(1,1000,0.1, 0.9, 14, 2, 0.6, 0.7)),1)
  expect_equal(nrow(queueing_network_poi_geom(13,4,0.99, 0.99, 1, 2, 0.6, 0.7)),13)
})

test_that("Number of exiting customers is almost that of entering customers", {
  qn_1 <- queueing_network_poi_geom(100,10,0.3, 0.4, 2, 1, 0.6, 0.7)
  qn_2 <- queueing_network_poi_geom(100,10,0.6, 0.1, 12, 1, 0.9, 0.7)
  qn_3 <- queueing_network_poi_geom(100,100,0.1, 0.1, 0.06, 2, 0.1, 0.3)
  
  expect_equal(sum(qn_1$arrival_1 + qn_1$arrival_2) > 0.7* sum(qn_1$departure_1 + qn_1$departure_2), TRUE)
  expect_equal(sum(qn_2$arrival_1 + qn_2$arrival_2) > 0.7* sum(qn_2$departure_1 + qn_2$departure_2), TRUE)
  expect_equal(sum(qn_3$arrival_1 + qn_3$arrival_2) > 0.7* sum(qn_3$departure_1 + qn_3$departure_2), TRUE)
  })

test_that("Number of arriving customers is Poisson distributed", {
  qn_1 <- queueing_network_poi_geom(100,10,0.3, 0.4, 2, 1, 0.6, 0.7)
  qn_2 <- queueing_network_poi_geom(1000,100,0.6, 0.1, 12, 1, 0.9, 0.7)
  qn_3 <- queueing_network_poi_geom(100,10,0.1, 0.1, 0.06, 2, 0.1, 0.3)
  
  expect_equal(sum(qn_1$arrival_1) >  0.5*(100)*2, TRUE)
  expect_equal(sum(qn_1$arrival_1) <  2*(100)*2, TRUE)
  expect_equal(sum(qn_1$arrival_2) >  0.5*(100)*1, TRUE)
  expect_equal(sum(qn_1$arrival_2) <  2*(100)*1, TRUE)
  expect_equal(sum(qn_2$arrival_1) <  2*(1000)*12, TRUE)
  expect_equal(sum(qn_2$arrival_1) >  0.5*(1000)*12, TRUE)
  expect_equal(sum(qn_2$arrival_2) <  2*(1000)*1, TRUE)
  expect_equal(sum(qn_2$arrival_2) >  0.5*(1000)*1, TRUE)
  expect_equal(sum(qn_3$arrival_1) >  0.5*(100)*0.06, TRUE)
  expect_equal(sum(qn_3$arrival_1) <  2*(100)*0.06, TRUE)
  expect_equal(sum(qn_3$arrival_2) >  0.5*(100)*2, TRUE)
  expect_equal(sum(qn_3$arrival_2) <  2*(100)*2, TRUE)
})


test_that("Lemma 1 in Wichelhaus, Edelmann is satisfied", {
  p_12 = 0.1
  p_21 = 0.2
  lambda_1 = 3
  lambda_2 = 1
  G_1 = 0.3
  G_2 = 0.2
  
  qn_1 <- queueing_network_poi_geom(10000, 1000, p_12 = p_12, p_21 = p_21,
                                    lambda_1 = lambda_1, lambda_2 = lambda_2, 
                                    G_1 = G_1, G_2 = G_2)
  
  
  expect_equal(sum(qn_1$departure_1) > 0.5*(1-p_12)/(1-p_12*p_21)*(sum(qn_1$arrival_1) + p_21*sum(qn_1$arrival_2)), TRUE)
  expect_equal(sum(qn_1$departure_1) < 1.5*(1-p_12)/(1-p_12*p_21)*(sum(qn_1$arrival_1) + p_21*sum(qn_1$arrival_2)), TRUE)
  expect_equal(sum(qn_1$departure_1) > 0.8*(1-p_12)/(1-p_12*p_21)*(sum(qn_1$arrival_1) + p_21*sum(qn_1$arrival_2)), TRUE)
  expect_equal(sum(qn_1$departure_1) < 1.2*(1-p_12)/(1-p_12*p_21)*(sum(qn_1$arrival_1) + p_21*sum(qn_1$arrival_2)), TRUE)
})