tests/testthat/test-sankeydiagram.R

In NumbersInternational/flipPlots: Creates Plots

library(stats)

context("Sankey Diagram")
test_that("Sankey diagrams",
          {

              data(phone, package = "flipExampleData")
              p <- phone[, c("q1", "q8", "q9", "q27")]
              expect_error(print(SankeyDiagram(as.list(p))), NA)
              p <- data.frame(p)
              expect_error(print(SankeyDiagram(p)), NA)
              p <- p[p$q1 == 1, ]
              expect_error(print(SankeyDiagram(p)), NA)
              data(colas, package = "flipExampleData")
              p <- colas[, c("d3", "d4")]
              expect_error(print(SankeyDiagram(as.list(p))), NA)
              p <- data.frame(p)
              expect_error(print(SankeyDiagram(p)), NA)
              p1 <- p[p$q1 == "Female", ]
              expect_error(print(SankeyDiagram(p1)))
              p <- p[p$d3 == "Female", ]
              expect_error(print(SankeyDiagram(p)), NA)
              p <- colas[, c("d1", "d2")]
              p <- data.frame(p)
              expect_error(print(SankeyDiagram(p, max.categories = 1)))
              for (i in 2:20)
                expect_error(print(SankeyDiagram(p, max.categories = i)), NA)
              p$d2 <- ordered(p$d2)
              for (i in 2:20)
              {
                  pm <- SankeyDiagram(p, max.categories = i)
                  expect_error(print(pm), NA)
              }
              SankeyDiagram(p, max.categories = 2)
              p <- colas[, c("d3", "d1")]
              SankeyDiagram(p, max.categories = 2)
})

expenses <- structure(list(Category = structure(c(4L, 2L, 1L, 2L, 1L, 3L,
2L, 2L, 3L, 5L, 2L, 2L, 1L, 1L, 5L, 3L, 3L, 3L, 1L, 3L, 1L, 2L,
1L, 1L, 5L, 2L, 4L, 3L, 5L, 1L, 3L, 5L, 5L, 5L, 1L, 3L, 1L, 1L,
3L, 5L, 1L, 5L, 5L, 1L, 3L, 1L, 5L, 3L, 2L, 3L, 1L, 1L, 5L, 2L,
3L, 3L, 4L, 3L, 5L, 3L, 2L, 5L, 5L, 3L, 5L, 5L, 1L), .Label = c("Development Assistance",
"Humanitarian Assistance", "Normative, Treaty-related and Knowledge creation activities",
"Peacekeeping Operations", "Technical Cooperation"), class = "factor"),
    Agency = structure(c(1L, 30L, 14L, 19L, 20L, 12L, 20L, 12L,
    31L, 11L, 25L, 8L, 17L, 12L, 8L, 15L, 6L, 3L, 2L, 2L, 16L,
    31L, 27L, 30L, 24L, 2L, 24L, 32L, 23L, 21L, 34L, 31L, 6L,
    12L, 13L, 10L, 5L, 31L, 16L, 16L, 24L, 4L, 33L, 9L, 26L,
    8L, 3L, 4L, 17L, 29L, 32L, 18L, 18L, 24L, 18L, 7L, 12L, 22L,
    34L, 28L, 18L, 10L, 7L, 8L, 28L, 29L, 10L), .Label = c("DPKO",
    "FAO", "IAEA", "ICAO", "IFAD", "ILO", "IMO", "IOM", "ITC",
    "ITU", "PAHO", "UN", "UNAIDS", "UNDP", "UNEP", "UNESCO",
    "UNFPA", "UN-HABITAT", "UNHCR", "UNICEF", "UNIDO", "UNITAR",
    "UNODC", "UNOPS", "UNRWA", "UNU", "UNWOMEN", "UNWTO", "UPU",
    "WFP", "WHO", "WIPO", "WMO", "WTO"), class = "factor")), .Names = c("Category",
"Agency"), row.names = c(NA, 67L), class = "data.frame", weights = c(8876176000,
5018199183, 4659525828, 3846924119, 2899073124, 2852121000, 2528181910,
1925690000, 1769674421, 1363470773, 1316762306, 936364827, 844803603,
709197000, 571246061, 561342000, 475664289, 463845188, 460742988,
426273315, 398210228, 340307917, 339801000, 337209860, 326506000,
314801837, 274471000, 273903334, 241906000, 235511425, 229931293,
208477657, 199272711, 188584000, 181750055, 170742371, 169727000,
152602283, 132736743, 132736743, 116733000, 108720761, 98226341,
91197000, 89986553, 86851769, 85799163, 83625879, 77714189, 74487892,
73133740, 61980404, 60104070, 52163000, 51875314, 47273818, 37442000,
23854000, 19303415, 18198766, 12473530, 11099580, 10547639, 7844760,
4972566, 2915644, 1762927))

test_that("Sankey diagrams: weights and filter",
          {
              data(phone, package = "flipExampleData")
              p <- phone[, c("q1", "q8", "q9", "q27")]
              subset <- rep(TRUE, nrow(p))
              subset[phone$q20h3 == "No"] <- FALSE
              expect_error(print(SankeyDiagram(p, subset = subset)), NA)
              weights <- sample(3, nrow(p), replace = TRUE)
              expect_error(print(SankeyDiagram(p, weights = weights)), NA)
              expect_error(print(SankeyDiagram(p, subset = subset, weights = weights)), NA)

              data(colas, package = "flipExampleData")
              p <- colas[, c("d1", "d2")]
              subset <- rep(TRUE, nrow(p))
              subset[colas$Q5_5_7 == "No"] <- FALSE
              expect_error(print(SankeyDiagram(p, subset = subset)), NA)
              weights <- rnorm(nrow(p))
              weights[weights < 0] <- 0
              expect_error(print(SankeyDiagram(p, weights = weights)), NA)
              expect_error(print(SankeyDiagram(p, subset = subset, weights = weights)), NA)

              # Large weights
              expect_error(SankeyDiagram(expenses, weights = attr(expenses, "weights")), NA)
})

datNumeric <- structure(list(Length = structure(c(0.455, 0.35, 0.53, 0.44,
0.33, 0.425, 0.53, 0.545, 0.475, 0.55, 0.525, 0.43, 0.49, 0.535,
0.47, 0.5, 0.355, 0.44, 0.365, 0.45, 0.355, 0.38, 0.565, 0.55,
0.615, 0.56, 0.58, 0.59, 0.605, 0.575, 0.58, 0.68, 0.665, 0.68,
0.705, 0.465, 0.54, 0.45, 0.575, 0.355, 0.45, 0.55, 0.24, 0.205,
0.21, 0.39, 0.47, 0.46, 0.325, 0.525, 0.52, 0.4, 0.485, 0.47,
0.405, 0.5, 0.445, 0.47, 0.245, 0.505, 0.45, 0.505, 0.53, 0.425,
0.52, 0.475, 0.565, 0.595, 0.475, 0.31, 0.555, 0.4, 0.595, 0.57,
0.605, 0.6, 0.595, 0.6, 0.555, 0.615, 0.575, 0.62, 0.52, 0.595,
0.58, 0.57, 0.625, 0.56, 0.46, 0.575, 0.565, 0.555, 0.595, 0.625,
0.695, 0.665, 0.535, 0.47, 0.47, 0.475, 0.36, 0.55, 0.53, 0.53,
0.605, 0.52, 0.545, 0.5, 0.51, 0.435, 0.495, 0.465, 0.435, 0.425,
0.545, 0.53, 0.49, 0.44, 0.56, 0.405, 0.47, 0.385, 0.515, 0.37,
0.36, 0.27, 0.375, 0.385, 0.7, 0.71, 0.595, 0.44, 0.325, 0.35,
0.265, 0.425, 0.305, 0.345, 0.405, 0.375, 0.565, 0.55, 0.65,
0.56, 0.475, 0.49, 0.46, 0.28, 0.175, 0.17, 0.59, 0.605, 0.635,
0.605, 0.565, 0.515, 0.575, 0.645, 0.58, 0.575, 0.605, 0.605,
0.61, 0.725, 0.65, 0.725, 0.725, 0.68, 0.705, 0.68, 0.695, 0.53,
0.525, 0.52, 0.235, 0.36, 0.315, 0.315, 0.225, 0.58, 0.57, 0.64,
0.56, 0.62, 0.645, 0.62, 0.63, 0.63, 0.63, 0.585, 0.615, 0.61,
0.58, 0.355, 0.51, 0.5, 0.505, 0.64, 0.56, 0.585, 0.45, 0.5,
0.5, 0.53, 0.42, 0.44, 0.4, 0.435, 0.525, 0.37, 0.49, 0.335,
0.415, 0.5, 0.485, 0.55, 0.45, 0.405, 0.47, 0.415, 0.445, 0.47,
0.49, 0.445, 0.425, 0.5, 0.39, 0.365, 0.58, 0.53, 0.555, 0.565,
0.625, 0.275, 0.44, 0.295, 0.075, 0.13, 0.11, 0.16, 0.565, 0.27,
0.23, 0.3, 0.33, 0.35, 0.32, 0.36, 0.305, 0.345, 0.33, 0.59,
0.595, 0.575, 0.6, 0.56, 0.56, 0.545, 0.635, 0.59, 0.54, 0.57,
0.53, 0.245, 0.27, 0.46, 0.52, 0.35, 0.47, 0.45, 0.64, 0.59,
0.62, 0.63, 0.63, 0.655, 0.66, 0.61, 0.635, 0.515, 0.535, 0.36,
0.455, 0.485, 0.515, 0.535, 0.53, 0.495, 0.44, 0.535, 0.54, 0.565,
0.61, 0.565, 0.6, 0.295, 0.275, 0.28, 0.49, 0.37, 0.405, 0.54,
0.37, 0.36, 0.47, 0.2, 0.165, 0.645, 0.55, 0.57, 0.63, 0.56,
0.595, 0.62, 0.63, 0.45, 0.635, 0.45, 0.58, 0.33, 0.265, 0.19,
0.385, 0.265, 0.335, 0.355, 0.32, 0.51, 0.36, 0.36, 0.5, 0.4,
0.3, 0.235, 0.74, 0.62, 0.6, 0.59, 0.62, 0.565, 0.575, 0.62,
0.62, 0.505, 0.46, 0.49, 0.525, 0.34, 0.375, 0.61, 0.61, 0.585,
0.57, 0.58, 0.635, 0.7, 0.675, 0.645, 0.745, 0.685, 0.605, 0.59,
0.65, 0.6, 0.62, 0.63, 0.58, 0.58, 0.63, 0.69, 0.65, 0.66, 0.68,
0.7, 0.685, 0.675, 0.63, 0.585, 0.565, 0.61, 0.605, 0.535, 0.485,
0.47, 0.545, 0.455, 0.54, 0.46, 0.49, 0.465, 0.415, 0.475, 0.47,
0.365, 0.345, 0.39, 0.5, 0.47, 0.535, 0.585, 0.485, 0.515, 0.435,
0.515, 0.44, 0.525, 0.45, 0.59, 0.555, 0.57, 0.59, 0.585, 0.58,
0.545, 0.605, 0.62, 0.63, 0.63, 0.63, 0.545, 0.67, 0.49, 0.49,
0.29, 0.26, 0.58, 0.61, 0.6, 0.56, 0.575, 0.57, 0.6, 0.565, 0.545,
0.44, 0.5, 0.36, 0.385, 0.39, 0.5, 0.36, 0.335, 0.505, 0.395,
0.41, 0.56, 0.565, 0.565, 0.605, 0.565, 0.725, 0.675, 0.665,
0.565, 0.645, 0.575, 0.64, 0.36, 0.415, 0.525, 0.38, 0.585, 0.24,
0.22, 0.255, 0.175, 0.67, 0.655, 0.68, 0.675, 0.53, 0.515, 0.43,
0.52, 0.545, 0.53, 0.465, 0.665, 0.735, 0.66, 0.7, 0.575, 0.57,
0.58, 0.63, 0.585, 0.55, 0.625, 0.54, 0.57, 0.59, 0.58, 0.655,
0.655, 0.625, 0.625, 0.64, 0.605, 0.615, 0.555, 0.58, 0.62, 0.62,
0.6, 0.625, 0.6, 0.56, 0.585, 0.56, 0.56, 0.68, 0.455, 0.49,
0.31, 0.275, 0.27, 0.4, 0.28, 0.325, 0.345, 0.21, 0.36, 0.365,
0.2, 0.235, 0.175, 0.155, 0.57, 0.57, 0.385, 0.53, 0.46, 0.47,
0.435, 0.47, 0.465, 0.52, 0.29, 0.275, 0.375, 0.5, 0.44, 0.42,
0.445, 0.38, 0.32, 0.255, 0.205, 0.565, 0.555, 0.65, 0.615, 0.56,
0.48, 0.485, 0.5, 0.525, 0.66, 0.66, 0.52, 0.44, 0.515, 0.475,
0.545, 0.47, 0.35, 0.485, 0.435, 0.28, 0.41, 0.45, 0.45, 0.59,
0.57, 0.61, 0.61, 0.56, 0.585, 0.58, 0.63, 0.625, 0.55, 0.645,
0.46, 0.41, 0.495, 0.52, 0.55, 0.45, 0.405, 0.51, 0.37, 0.525,
0.66, 0.535, 0.575, 0.55, 0.605, 0.605, 0.56, 0.535, 0.385, 0.39,
0.47, 0.515, 0.425, 0.345, 0.485, 0.37, 0.35, 0.44, 0.195, 0.325,
0.495, 0.45, 0.415, 0.47, 0.32, 0.31, 0.235, 0.345, 0.485, 0.5,
0.5, 0.465, 0.525, 0.425, 0.38, 0.53, 0.34, 0.475, 0.43, 0.46,
0.47, 0.36, 0.355, 0.38, 0.355, 0.44, 0.51, 0.325, 0.62, 0.59,
0.33, 0.45, 0.445, 0.33, 0.48, 0.46, 0.475, 0.255, 0.335, 0.47,
0.31, 0.37, 0.295, 0.555, 0.615, 0.58, 0.585, 0.65, 0.535, 0.415,
0.38, 0.45, 0.395, 0.455, 0.485, 0.55, 0.45, 0.475, 0.5, 0.53,
0.49, 0.49, 0.52, 0.54, 0.5, 0.45, 0.37, 0.37, 0.485, 0.435,
0.535, 0.51, 0.565, 0.535, 0.535, 0.525, 0.59, 0.5, 0.255, 0.43,
0.38, 0.165, 0.315, 0.155, 0.28, 0.43, 0.395, 0.385, 0.48, 0.445,
0.395, 0.4, 0.415, 0.315, 0.345, 0.36, 0.295, 0.325, 0.375, 0.28,
0.355, 0.35, 0.275, 0.29, 0.25, 0.18, 0.15, 0.16, 0.555, 0.555,
0.525, 0.465, 0.49, 0.4, 0.48, 0.505, 0.52, 0.525, 0.545, 0.52,
0.505, 0.525, 0.51, 0.52, 0.52, 0.535, 0.445, 0.53, 0.36, 0.535,
0.52, 0.53, 0.53, 0.66, 0.52, 0.535, 0.695, 0.51, 0.485, 0.605,
0.58, 0.65, 0.62, 0.615, 0.605, 0.57, 0.57, 0.585, 0.55, 0.54,
0.64, 0.61, 0.545, 0.59, 0.345, 0.55, 0.53, 0.53, 0.485, 0.385,
0.455, 0.49, 0.53, 0.505, 0.49, 0.465, 0.47, 0.56, 0.505, 0.515,
0.385, 0.215, 0.55, 0.515, 0.495, 0.505, 0.6, 0.57, 0.485, 0.47,
0.575, 0.58, 0.515, 0.53, 0.44, 0.52, 0.425, 0.46, 0.45, 0.425,
0.37, 0.515, 0.405, 0.28, 0.48, 0.44, 0.52, 0.505, 0.49, 0.235,
0.255, 0.315, 0.325, 0.335, 0.35, 0.35, 0.36, 0.365, 0.37, 0.38,
0.385, 0.385, 0.395, 0.395, 0.4, 0.41, 0.415, 0.415, 0.425, 0.44,
0.445, 0.445, 0.45, 0.47, 0.475, 0.48, 0.485, 0.49, 0.495, 0.5,
0.505, 0.525, 0.54, 0.54, 0.545, 0.55, 0.55, 0.55, 0.555, 0.565,
0.57, 0.57, 0.575, 0.59, 0.59, 0.595, 0.595, 0.595, 0.595, 0.6,
0.6, 0.6, 0.605, 0.605, 0.615, 0.615, 0.615, 0.615, 0.62, 0.62,
0.625, 0.625, 0.63, 0.635, 0.635, 0.635, 0.64, 0.65, 0.655, 0.655,
0.66, 0.66, 0.67, 0.675, 0.675, 0.68, 0.685, 0.695, 0.73, 0.205,
0.24, 0.24, 0.255, 0.255, 0.265, 0.28, 0.295, 0.3, 0.3, 0.305,
0.315, 0.315, 0.32, 0.325, 0.33, 0.335, 0.335, 0.34, 0.34, 0.345,
0.37, 0.37, 0.375, 0.385, 0.41, 0.41, 0.41, 0.415, 0.42, 0.42,
0.425, 0.425, 0.43, 0.43, 0.435, 0.435, 0.44, 0.44, 0.445, 0.445,
0.45, 0.45, 0.45, 0.45, 0.455, 0.455, 0.46, 0.46, 0.465, 0.465,
0.465, 0.465, 0.47, 0.47, 0.475, 0.475, 0.48, 0.48, 0.48, 0.48,
0.485, 0.49, 0.495, 0.495, 0.5, 0.5, 0.5, 0.5, 0.505, 0.505,
0.505, 0.505, 0.51, 0.51, 0.51, 0.51, 0.51, 0.515, 0.515, 0.525,
0.525, 0.53, 0.53, 0.53, 0.535, 0.535, 0.535, 0.55, 0.55, 0.56,
0.565, 0.57, 0.57, 0.57, 0.57, 0.57, 0.575, 0.575, 0.58, 0.58,
0.58, 0.58, 0.58, 0.59, 0.59, 0.59, 0.595, 0.595, 0.595, 0.595,
0.595, 0.605, 0.605, 0.605, 0.61, 0.61, 0.615, 0.62, 0.625, 0.625,
0.625, 0.625, 0.625, 0.63, 0.63, 0.63, 0.635, 0.635, 0.64, 0.64,
0.64, 0.645, 0.645, 0.645, 0.645, 0.645, 0.645, 0.645, 0.65,
0.65, 0.65, 0.655, 0.655, 0.66, 0.66, 0.66, 0.66, 0.67, 0.675,
0.675, 0.68, 0.69, 0.69, 0.695, 0.705, 0.71, 0.715, 0.715, 0.735,
0.765, 0.185, 0.195, 0.195, 0.2, 0.225, 0.245, 0.25, 0.265, 0.275,
0.28, 0.285, 0.3, 0.315, 0.32, 0.34, 0.37, 0.375, 0.375, 0.385,
0.4, 0.405, 0.41, 0.41, 0.42, 0.42, 0.42, 0.425, 0.43, 0.435,
0.435, 0.44, 0.445, 0.445, 0.445, 0.45, 0.45, 0.45, 0.45, 0.45,
0.46, 0.47, 0.47, 0.475, 0.475, 0.48, 0.49, 0.5, 0.5, 0.5, 0.5,
0.505, 0.51, 0.51, 0.51, 0.51, 0.515, 0.52, 0.52, 0.52, 0.52,
0.525, 0.525, 0.525, 0.525, 0.53, 0.535, 0.54, 0.545, 0.545,
0.545, 0.55, 0.55, 0.55, 0.56, 0.56, 0.56, 0.56, 0.565, 0.565,
0.565, 0.57, 0.57, 0.57, 0.575, 0.575, 0.575, 0.575, 0.575, 0.575,
0.575, 0.575, 0.58, 0.58, 0.58, 0.58, 0.58, 0.58, 0.585, 0.585,
0.59, 0.6, 0.6, 0.6, 0.6, 0.605, 0.605, 0.605, 0.605, 0.61, 0.61,
0.61, 0.615, 0.615, 0.615, 0.62, 0.62, 0.62, 0.625, 0.625, 0.63,
0.63, 0.635, 0.64, 0.645, 0.645, 0.65, 0.65, 0.655, 0.655, 0.66,
0.665, 0.665, 0.67, 0.685, 0.685, 0.69, 0.69, 0.69, 0.695, 0.7,
0.7, 0.7, 0.705, 0.71, 0.715, 0.715, 0.72, 0.72, 0.72, 0.725,
0.73, 0.735, 0.745, 0.75, 0.755, 0.755, 0.78, 0.185, 0.245, 0.25,
0.25, 0.275, 0.305, 0.31, 0.315, 0.315, 0.325, 0.33, 0.33, 0.335,
0.34, 0.345, 0.345, 0.35, 0.35, 0.36, 0.365, 0.365, 0.365, 0.37,
0.37, 0.375, 0.375, 0.375, 0.375, 0.375, 0.375, 0.38, 0.38, 0.385,
0.385, 0.385, 0.385, 0.39, 0.395, 0.395, 0.395, 0.4, 0.405, 0.41,
0.42, 0.425, 0.425, 0.425, 0.43, 0.43, 0.435, 0.44, 0.45, 0.455,
0.455, 0.455, 0.46, 0.46, 0.46, 0.465, 0.47, 0.47, 0.47, 0.475,
0.475, 0.475, 0.48, 0.48, 0.48, 0.495, 0.495, 0.495, 0.5, 0.5,
0.5, 0.5, 0.5, 0.5, 0.505, 0.505, 0.505, 0.515, 0.515, 0.515,
0.52, 0.52, 0.525, 0.525, 0.53, 0.53, 0.53, 0.53, 0.535, 0.535,
0.535, 0.535, 0.54, 0.54, 0.545, 0.545, 0.545, 0.545, 0.55, 0.55,
0.55, 0.55, 0.55, 0.555, 0.555, 0.555, 0.555, 0.56, 0.56, 0.56,
0.56, 0.565, 0.565, 0.565, 0.565, 0.57, 0.57, 0.57, 0.57, 0.57,
0.57, 0.575, 0.575, 0.575, 0.58, 0.58, 0.58, 0.585, 0.585, 0.585,
0.585, 0.585, 0.585, 0.585, 0.59, 0.59, 0.59, 0.595, 0.595, 0.6,
0.6, 0.6, 0.6, 0.6, 0.6, 0.605, 0.605, 0.605, 0.605, 0.605, 0.61,
0.61, 0.61, 0.61, 0.61, 0.61, 0.615, 0.615, 0.615, 0.615, 0.615,
0.615, 0.615, 0.62, 0.62, 0.62, 0.62, 0.625, 0.625, 0.625, 0.625,
0.63, 0.63, 0.63, 0.63, 0.63, 0.635, 0.635, 0.635, 0.635, 0.635,
0.64, 0.64, 0.645, 0.645, 0.645, 0.65, 0.65, 0.65, 0.65, 0.65,
0.655, 0.655, 0.655, 0.655, 0.66, 0.66, 0.665, 0.67, 0.67, 0.675,
0.685, 0.695, 0.7, 0.705, 0.705, 0.705, 0.71, 0.72, 0.72, 0.725,
0.73, 0.735, 0.745, 0.75, 0.815, 0.14, 0.23, 0.365, 0.365, 0.37,
0.375, 0.385, 0.395, 0.4, 0.4, 0.405, 0.405, 0.405, 0.41, 0.415,
0.425, 0.43, 0.44, 0.44, 0.44, 0.45, 0.455, 0.46, 0.47, 0.47,
0.47, 0.475, 0.475, 0.475, 0.48, 0.485, 0.485, 0.485, 0.495,
0.505, 0.505, 0.515, 0.515, 0.515, 0.52, 0.525, 0.53, 0.53, 0.545,
0.55, 0.55, 0.56, 0.56, 0.57, 0.575, 0.575, 0.58, 0.58, 0.585,
0.59, 0.59, 0.59, 0.595, 0.6, 0.6, 0.605, 0.605, 0.605, 0.61,
0.615, 0.62, 0.62, 0.62, 0.625, 0.625, 0.63, 0.63, 0.63, 0.63,
0.63, 0.635, 0.635, 0.64, 0.645, 0.645, 0.645, 0.65, 0.65, 0.65,
0.65, 0.655, 0.655, 0.66, 0.665, 0.67, 0.67, 0.67, 0.68, 0.68,
0.69, 0.7, 0.7, 0.705, 0.72, 0.725, 0.74, 0.75, 0.21, 0.285,
0.295, 0.3, 0.305, 0.335, 0.35, 0.355, 0.355, 0.36, 0.36, 0.36,
0.365, 0.37, 0.375, 0.38, 0.38, 0.385, 0.385, 0.385, 0.39, 0.39,
0.39, 0.41, 0.41, 0.415, 0.425, 0.425, 0.435, 0.435, 0.45, 0.45,
0.455, 0.46, 0.46, 0.465, 0.465, 0.47, 0.475, 0.475, 0.475, 0.48,
0.48, 0.48, 0.485, 0.49, 0.49, 0.495, 0.495, 0.5, 0.5, 0.5, 0.51,
0.515, 0.515, 0.515, 0.515, 0.515, 0.52, 0.52, 0.525, 0.525,
0.525, 0.525, 0.525, 0.53, 0.53, 0.53, 0.53, 0.535, 0.54, 0.54,
0.54, 0.54, 0.54, 0.54, 0.54, 0.545, 0.545, 0.545, 0.55, 0.55,
0.55, 0.55, 0.55, 0.555, 0.555, 0.555, 0.56, 0.56, 0.56, 0.565,
0.565, 0.565, 0.565, 0.57, 0.57, 0.57, 0.57, 0.57, 0.57, 0.575,
0.575, 0.575, 0.575, 0.575, 0.575, 0.575, 0.575, 0.575, 0.575,
0.575, 0.58, 0.58, 0.58, 0.58, 0.585, 0.59, 0.59, 0.59, 0.595,
0.595, 0.595, 0.595, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.605,
0.605, 0.605, 0.605, 0.605, 0.605, 0.61, 0.61, 0.61, 0.61, 0.61,
0.61, 0.61, 0.61, 0.615, 0.615, 0.62, 0.62, 0.62, 0.62, 0.62,
0.62, 0.62, 0.62, 0.62, 0.62, 0.625, 0.625, 0.625, 0.625, 0.625,
0.625, 0.63, 0.63, 0.63, 0.63, 0.63, 0.635, 0.635, 0.635, 0.635,
0.64, 0.64, 0.64, 0.645, 0.645, 0.645, 0.645, 0.645, 0.645, 0.645,
0.645, 0.645, 0.645, 0.645, 0.65, 0.65, 0.65, 0.65, 0.655, 0.655,
0.655, 0.655, 0.66, 0.66, 0.66, 0.66, 0.665, 0.665, 0.665, 0.665,
0.665, 0.67, 0.67, 0.67, 0.67, 0.67, 0.675, 0.675, 0.68, 0.68,
0.685, 0.685, 0.69, 0.7, 0.7, 0.705, 0.71, 0.71, 0.71, 0.71,
0.72, 0.72, 0.72, 0.725, 0.73, 0.735, 0.74, 0.75, 0.75, 0.77,
0.775, 0.275, 0.375, 0.375, 0.39, 0.435, 0.445, 0.455, 0.455,
0.455, 0.465, 0.465, 0.485, 0.485, 0.485, 0.49, 0.5, 0.515, 0.515,
0.525, 0.525, 0.53, 0.535, 0.535, 0.545, 0.545, 0.545, 0.55,
0.55, 0.57, 0.575, 0.575, 0.58, 0.585, 0.585, 0.6, 0.6, 0.605,
0.605, 0.61, 0.615, 0.62, 0.625, 0.625, 0.635, 0.635, 0.64, 0.645,
0.65, 0.65, 0.655, 0.655, 0.665, 0.675, 0.685, 0.695, 0.695,
0.705, 0.72, 0.72, 0.73, 0.185, 0.24, 0.31, 0.34, 0.35, 0.365,
0.365, 0.365, 0.39, 0.405, 0.41, 0.41, 0.415, 0.415, 0.415, 0.42,
0.43, 0.435, 0.435, 0.435, 0.435, 0.445, 0.465, 0.47, 0.475,
0.485, 0.485, 0.485, 0.495, 0.495, 0.495, 0.5, 0.505, 0.505,
0.51, 0.515, 0.515, 0.515, 0.52, 0.52, 0.52, 0.52, 0.52, 0.525,
0.525, 0.525, 0.53, 0.53, 0.53, 0.53, 0.535, 0.54, 0.54, 0.54,
0.545, 0.545, 0.55, 0.55, 0.555, 0.555, 0.555, 0.555, 0.555,
0.56, 0.565, 0.565, 0.565, 0.565, 0.565, 0.565, 0.57, 0.57, 0.57,
0.57, 0.57, 0.575, 0.575, 0.575, 0.575, 0.575, 0.575, 0.575,
0.575, 0.575, 0.575, 0.58, 0.58, 0.58, 0.58, 0.58, 0.595, 0.6,
0.6, 0.6, 0.6, 0.605, 0.605, 0.605, 0.61, 0.61, 0.61, 0.61, 0.615,
0.615, 0.615, 0.615, 0.62, 0.62, 0.62, 0.62, 0.62, 0.62, 0.625,
0.625, 0.625, 0.625, 0.625, 0.625, 0.63, 0.635, 0.635, 0.635,
0.635, 0.635, 0.635, 0.64, 0.64, 0.64, 0.64, 0.64, 0.64, 0.645,
0.645, 0.645, 0.65, 0.65, 0.65, 0.655, 0.655, 0.655, 0.66, 0.66,
0.665, 0.665, 0.665, 0.67, 0.675, 0.675, 0.68, 0.68, 0.685, 0.69,
0.695, 0.7, 0.7, 0.7, 0.705, 0.72, 0.72, 0.725, 0.75, 0.76, 0.135,
0.16, 0.21, 0.28, 0.28, 0.285, 0.29, 0.29, 0.29, 0.32, 0.325,
0.335, 0.35, 0.35, 0.355, 0.36, 0.36, 0.375, 0.375, 0.395, 0.405,
0.415, 0.425, 0.43, 0.435, 0.45, 0.46, 0.47, 0.47, 0.475, 0.505,
0.505, 0.505, 0.51, 0.515, 0.525, 0.53, 0.53, 0.545, 0.55, 0.56,
0.565, 0.57, 0.58, 0.59, 0.6, 0.605, 0.61, 0.625, 0.66, 0.255,
0.27, 0.28, 0.285, 0.32, 0.325, 0.385, 0.395, 0.4, 0.405, 0.415,
0.42, 0.44, 0.445, 0.45, 0.455, 0.46, 0.46, 0.465, 0.465, 0.475,
0.48, 0.485, 0.49, 0.5, 0.5, 0.505, 0.525, 0.535, 0.535, 0.54,
0.54, 0.545, 0.55, 0.55, 0.565, 0.58, 0.58, 0.585, 0.595, 0.6,
0.61, 0.61, 0.62, 0.645, 0.65, 0.665, 0.685, 0.69, 0.705, 0.71,
0.72, 0.72, 0.73, 0.775, 0.505, 0.53, 0.505, 0.405, 0.415, 0.5,
0.425, 0.47, 0.4, 0.37, 0.5, 0.41, 0.375, 0.49, 0.585, 0.595,
0.675, 0.665, 0.62, 0.325, 0.455, 0.525, 0.385, 0.13, 0.18, 0.31,
0.375, 0.48, 0.455, 0.425, 0.475, 0.435, 0.29, 0.385, 0.47, 0.5,
0.4, 0.62, 0.595, 0.585, 0.32, 0.52, 0.44, 0.44, 0.565, 0.56,
0.59, 0.57, 0.68, 0.45, 0.32, 0.46, 0.47, 0.455, 0.415, 0.465,
0.46, 0.415, 0.27, 0.445, 0.745, 0.4, 0.28, 0.55, 0.58, 0.61,
0.62, 0.56, 0.64, 0.69, 0.715, 0.71, 0.55, 0.375, 0.61, 0.38,
0.37, 0.335, 0.165, 0.285, 0.19, 0.215, 0.595, 0.645, 0.575,
0.57, 0.58, 0.595, 0.595, 0.625, 0.535, 0.55, 0.495, 0.32, 0.445,
0.52, 0.495, 0.47, 0.49, 0.58, 0.645, 0.575, 0.215, 0.43, 0.26,
0.37, 0.405, 0.27, 0.68, 0.65, 0.645, 0.57, 0.615, 0.42, 0.275,
0.29, 0.42, 0.625, 0.55, 0.66, 0.565, 0.595, 0.63, 0.43, 0.455,
0.33, 0.515, 0.495, 0.485, 0.535, 0.58, 0.625, 0.555, 0.55, 0.59,
0.355, 0.275, 0.505, 0.37, 0.555, 0.505, 0.56, 0.595, 0.57, 0.6,
0.56, 0.585, 0.46, 0.46, 0.415, 0.435, 0.475, 0.465, 0.355, 0.46,
0.38, 0.47, 0.36, 0.585, 0.655, 0.6, 0.57, 0.645, 0.65, 0.51,
0.52, 0.495, 0.43, 0.59, 0.55, 0.585, 0.58, 0.62, 0.59, 0.72,
0.635, 0.61, 0.545, 0.57, 0.6, 0.52, 0.635, 0.67, 0.695, 0.655,
0.62, 0.6, 0.51, 0.525, 0.44, 0.485, 0.495, 0.435, 0.405, 0.42,
0.5, 0.385, 0.33, 0.58, 0.325, 0.475, 0.38, 0.34, 0.525, 0.52,
0.535, 0.475, 0.415, 0.495, 0.48, 0.52, 0.46, 0.58, 0.59, 0.55,
0.65, 0.465, 0.455, 0.47, 0.435, 0.35, 0.315, 0.595, 0.58, 0.575,
0.535, 0.515, 0.505, 0.505, 0.4, 0.49, 0.53, 0.395, 0.665, 0.415,
0.43, 0.475, 0.525, 0.48, 0.42, 0.59, 0.515, 0.695, 0.8, 0.61,
0.565, 0.56, 0.655, 0.64, 0.59, 0.31, 0.255, 0.17, 0.67, 0.71,
0.56, 0.505, 0.525, 0.45, 0.515, 0.59, 0.7, 0.72, 0.635, 0.555,
0.575, 0.585, 0.61, 0.645, 0.545, 0.55, 0.66, 0.57, 0.6, 0.63,
0.695, 0.65, 0.72, 0.56, 0.42, 0.18, 0.405, 0.5, 0.435, 0.34,
0.43, 0.535, 0.415, 0.36, 0.175, 0.155, 0.525, 0.525, 0.44, 0.45,
0.485, 0.47, 0.515, 0.42, 0.455, 0.37, 0.33, 0.3, 0.625, 0.61,
0.625, 0.635, 0.5, 0.53, 0.445, 0.585, 0.44, 0.29, 0.555, 0.655,
0.58, 0.625, 0.62, 0.64, 0.505, 0.5, 0.31, 0.505, 0.42, 0.4,
0.425, 0.31, 0.465, 0.465, 0.35, 0.52, 0.475, 0.41, 0.26, 0.575,
0.565, 0.26, 0.53, 0.34, 0.52, 0.635, 0.61, 0.66, 0.635, 0.465,
0.515, 0.335, 0.515, 0.345, 0.465, 0.54, 0.475, 0.445, 0.5, 0.5,
0.55, 0.275, 0.35, 0.37, 0.42, 0.35, 0.395, 0.325, 0.275, 0.235,
0.25, 0.25, 0.2, 0.585, 0.445, 0.5, 0.44, 0.515, 0.52, 0.5, 0.425,
0.51, 0.37, 0.54, 0.615, 0.565, 0.645, 0.615, 0.605, 0.59, 0.645,
0.57, 0.47, 0.5, 0.52, 0.39, 0.52, 0.54, 0.46, 0.355, 0.49, 0.63,
0.5, 0.49, 0.44, 0.515, 0.475, 0.42, 0.4, 0.45, 0.52, 0.505,
0.495, 0.54, 0.48, 0.33, 0.285, 0.3, 0.31, 0.34, 0.375, 0.415,
0.415, 0.415, 0.42, 0.425, 0.465, 0.465, 0.47, 0.47, 0.475, 0.48,
0.5, 0.505, 0.525, 0.54, 0.545, 0.565, 0.58, 0.59, 0.59, 0.595,
0.6, 0.6, 0.6, 0.605, 0.625, 0.63, 0.64, 0.64, 0.655, 0.66, 0.66,
0.675, 0.675, 0.69, 0.695, 0.7, 0.73, 0.205, 0.225, 0.23, 0.275,
0.28, 0.28, 0.295, 0.31, 0.315, 0.34, 0.37, 0.38, 0.39, 0.405,
0.415, 0.44, 0.44, 0.44, 0.44, 0.45, 0.45, 0.455, 0.46, 0.46,
0.46, 0.465, 0.465, 0.475, 0.475, 0.48, 0.5, 0.5, 0.505, 0.515,
0.525, 0.525, 0.53, 0.53, 0.53, 0.54, 0.55, 0.555, 0.57, 0.57,
0.575, 0.58, 0.585, 0.59, 0.595, 0.595, 0.595, 0.6, 0.6, 0.6,
0.61, 0.615, 0.615, 0.615, 0.62, 0.62, 0.62, 0.625, 0.625, 0.625,
0.63, 0.63, 0.63, 0.635, 0.635, 0.645, 0.645, 0.65, 0.67, 0.69,
0.69, 0.695, 0.695, 0.7, 0.705, 0.765, 0.77, 0.22, 0.275, 0.29,
0.33, 0.355, 0.375, 0.415, 0.425, 0.425, 0.43, 0.44, 0.44, 0.46,
0.46, 0.465, 0.475, 0.475, 0.485, 0.49, 0.49, 0.495, 0.5, 0.5,
0.505, 0.51, 0.51, 0.515, 0.52, 0.545, 0.545, 0.545, 0.545, 0.55,
0.55, 0.555, 0.565, 0.57, 0.57, 0.57, 0.575, 0.58, 0.585, 0.585,
0.59, 0.59, 0.59, 0.595, 0.595, 0.595, 0.6, 0.605, 0.615, 0.615,
0.615, 0.615, 0.62, 0.62, 0.625, 0.625, 0.625, 0.63, 0.63, 0.63,
0.645, 0.645, 0.645, 0.65, 0.65, 0.65, 0.65, 0.65, 0.66, 0.665,
0.67, 0.67, 0.675, 0.68, 0.68, 0.7, 0.7, 0.725, 0.725, 0.735,
0.74, 0.75, 0.19, 0.21, 0.25, 0.29, 0.335, 0.34, 0.345, 0.355,
0.36, 0.37, 0.375, 0.375, 0.385, 0.385, 0.395, 0.4, 0.405, 0.405,
0.405, 0.405, 0.41, 0.41, 0.415, 0.42, 0.42, 0.43, 0.445, 0.45,
0.45, 0.455, 0.46, 0.46, 0.475, 0.48, 0.485, 0.485, 0.49, 0.505,
0.505, 0.51, 0.515, 0.515, 0.515, 0.525, 0.525, 0.525, 0.525,
0.535, 0.545, 0.55, 0.55, 0.55, 0.55, 0.55, 0.555, 0.555, 0.56,
0.56, 0.565, 0.57, 0.575, 0.58, 0.58, 0.58, 0.585, 0.585, 0.585,
0.585, 0.59, 0.59, 0.595, 0.6, 0.6, 0.6, 0.6, 0.61, 0.61, 0.615,
0.62, 0.62, 0.625, 0.625, 0.63, 0.63, 0.63, 0.63, 0.64, 0.64,
0.64, 0.64, 0.64, 0.65, 0.65, 0.66, 0.66, 0.675, 0.7, 0.705,
0.71, 0.72, 0.725, 0.24, 0.255, 0.275, 0.32, 0.325, 0.33, 0.36,
0.375, 0.375, 0.39, 0.45, 0.455, 0.46, 0.495, 0.5, 0.5, 0.52,
0.52, 0.525, 0.535, 0.54, 0.54, 0.57, 0.57, 0.58, 0.58, 0.59,
0.59, 0.59, 0.595, 0.6, 0.6, 0.605, 0.62, 0.625, 0.625, 0.625,
0.63, 0.63, 0.635, 0.645, 0.645, 0.65, 0.655, 0.655, 0.665, 0.695,
0.72, 0.72, 0.72, 0.735, 0.74, 0.31, 0.315, 0.32, 0.325, 0.335,
0.37, 0.37, 0.375, 0.4, 0.41, 0.425, 0.435, 0.445, 0.46, 0.465,
0.47, 0.475, 0.495, 0.5, 0.5, 0.505, 0.505, 0.505, 0.51, 0.51,
0.52, 0.52, 0.53, 0.53, 0.535, 0.54, 0.54, 0.545, 0.545, 0.55,
0.55, 0.55, 0.56, 0.56, 0.575, 0.575, 0.575, 0.58, 0.58, 0.58,
0.58, 0.58, 0.58, 0.585, 0.59, 0.59, 0.59, 0.595, 0.595, 0.6,
0.6, 0.6, 0.6, 0.6, 0.605, 0.605, 0.605, 0.61, 0.61, 0.61, 0.61,
0.615, 0.615, 0.615, 0.615, 0.62, 0.62, 0.625, 0.625, 0.625,
0.625, 0.625, 0.63, 0.63, 0.63, 0.63, 0.635, 0.635, 0.635, 0.635,
0.635, 0.64, 0.64, 0.645, 0.645, 0.645, 0.65, 0.65, 0.655, 0.655,
0.66, 0.66, 0.665, 0.67, 0.67, 0.67, 0.67, 0.67, 0.68, 0.68,
0.685, 0.69, 0.715, 0.72, 0.735, 0.745, 0.32, 0.43, 0.43, 0.485,
0.49, 0.5, 0.505, 0.51, 0.525, 0.535, 0.535, 0.535, 0.555, 0.555,
0.56, 0.59, 0.595, 0.595, 0.595, 0.61, 0.61, 0.62, 0.625, 0.635,
0.635, 0.64, 0.64, 0.645, 0.655, 0.67, 0.68, 0.7, 0.73, 0.75,
0.255, 0.375, 0.375, 0.39, 0.39, 0.395, 0.42, 0.435, 0.435, 0.44,
0.45, 0.45, 0.455, 0.46, 0.47, 0.475, 0.495, 0.495, 0.5, 0.515,
0.52, 0.52, 0.525, 0.535, 0.535, 0.54, 0.55, 0.55, 0.56, 0.565,
0.57, 0.57, 0.575, 0.575, 0.575, 0.575, 0.58, 0.585, 0.59, 0.59,
0.59, 0.595, 0.595, 0.595, 0.6, 0.6, 0.61, 0.615, 0.615, 0.62,
0.625, 0.63, 0.63, 0.635, 0.635, 0.635, 0.64, 0.64, 0.65, 0.65,
0.655, 0.655, 0.655, 0.66, 0.665, 0.675, 0.68, 0.68, 0.685, 0.695,
0.7, 0.71, 0.73, 0.755, 0.225, 0.23, 0.255, 0.355, 0.425, 0.425,
0.455, 0.46, 0.495, 0.51, 0.52, 0.525, 0.53, 0.53, 0.545, 0.55,
0.575, 0.58, 0.595, 0.6, 0.645, 0.66, 0.29, 0.3, 0.37, 0.375,
0.38, 0.395, 0.41, 0.415, 0.425, 0.44, 0.44, 0.465, 0.47, 0.51,
0.525, 0.525, 0.55, 0.56, 0.575, 0.575, 0.585, 0.615, 0.62, 0.63,
0.63, 0.67, 0.675, 0.685, 0.485, 0.46, 0.46, 0.535, 0.465, 0.51,
0.335, 0.55, 0.18, 0.215, 0.2, 0.625, 0.55, 0.585, 0.645, 0.71,
0.7, 0.655, 0.665, 0.47, 0.425, 0.54, 0.505, 0.535, 0.43, 0.55,
0.34, 0.275, 0.335, 0.64, 0.55, 0.64, 0.545, 0.64, 0.605, 0.605,
0.56, 0.57, 0.525, 0.505, 0.35, 0.45, 0.51, 0.49, 0.505, 0.38,
0.27, 0.37, 0.5, 0.645, 0.565, 0.67, 0.59, 0.47, 0.51, 0.72,
0.55, 0.2, 0.65, 0.525, 0.565, 0.61, 0.545, 0.325, 0.31, 0.45,
0.49, 0.505, 0.385, 0.62, 0.635, 0.665, 0.335, 0.295, 0.48, 0.32,
0.43, 0.565, 0.6, 0.585, 0.555, 0.57, 0.62, 0.63, 0.425, 0.64,
0.675, 0.5, 0.385, 0.52, 0.52, 0.64, 0.44, 0.42, 0.45, 0.42,
0.64, 0.57, 0.41, 0.485, 0.61, 0.59, 0.665, 0.345, 0.635, 0.695,
0.69, 0.555, 0.65, 0.635, 0.655, 0.69, 0.695, 0.55, 0.61, 0.595,
0.3, 0.435, 0.455, 0.48, 0.43, 0.435, 0.3, 0.575, 0.505, 0.455,
0.64, 0.56, 0.645, 0.595, 0.565, 0.655, 0.48, 0.495, 0.4, 0.41,
0.595, 0.625, 0.52, 0.465, 0.475, 0.5, 0.46, 0.485, 0.465, 0.525,
0.655, 0.69, 0.55, 0.58, 0.59, 0.565, 0.665, 0.62, 0.55, 0.605,
0.535, 0.51, 0.53, 0.495, 0.575, 0.63, 0.59, 0.605, 0.645, 0.62,
0.605, 0.615, 0.66, 0.71, 0.565, 0.57, 0.6, 0.41, 0.45, 0.275,
0.485, 0.62, 0.48, 0.505, 0.4, 0.45, 0.35, 0.44, 0.265, 0.165,
0.705, 0.535, 0.49, 0.48, 0.395, 0.375, 0.345, 0.55, 0.635, 0.575,
0.545, 0.385, 0.51, 0.44, 0.45, 0.39, 0.425, 0.45, 0.66, 0.685,
0.585, 0.54, 0.49, 0.43, 0.455, 0.495, 0.48, 0.47, 0.415, 0.49,
0.47, 0.445, 0.51, 0.52, 0.475, 0.455, 0.435, 0.39, 0.375, 0.285,
0.58, 0.58, 0.41, 0.41, 0.54, 0.33, 0.44, 0.28, 0.59, 0.61, 0.61,
0.455, 0.33, 0.44, 0.54, 0.475, 0.46, 0.31, 0.255, 0.335, 0.295,
0.19, 0.545, 0.495, 0.5, 0.305, 0.475, 0.515, 0.545, 0.74, 0.565,
0.56, 0.545, 0.645, 0.575, 0.62, 0.605, 0.605, 0.475, 0.365,
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    0.39, 0.39, 0.405, 0.4, 0.4, 0.38, 0.385, 0.4, 0.38, 0.38,
    0.46, 0.4, 0.4, 0.405, 0.395, 0.4, 0.39, 0.42, 0.39, 0.41,
    0.415, 0.415, 0.43, 0.425, 0.43, 0.445, 0.44, 0.415, 0.455,
    0.435, 0.45, 0.46, 0.445, 0.44, 0.46, 0.45, 0.435, 0.47,
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    0.45, 0.46, 0.465, 0.47, 0.475, 0.455, 0.465, 0.465, 0.47,
    0.475, 0.48, 0.475, 0.485, 0.485, 0.47, 0.46, 0.465, 0.475,
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    0.27, 0.29, 0.28, 0.3, 0.28, 0.3, 0.305, 0.295, 0.27, 0.29,
    0.285, 0.335, 0.305, 0.325, 0.32, 0.31, 0.34, 0.315, 0.315,
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    0.325, 0.315, 0.335, 0.325, 0.34, 0.335, 0.36, 0.35, 0.355,
    0.37, 0.345, 0.355, 0.36, 0.36, 0.36, 0.37, 0.37, 0.355,
    0.375, 0.375, 0.4, 0.37, 0.4, 0.4, 0.39, 0.375, 0.395, 0.375,
    0.36, 0.35, 0.395, 0.39, 0.41, 0.39, 0.415, 0.39, 0.38, 0.4,
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    0.44, 0.44, 0.43, 0.45, 0.45, 0.435, 0.43, 0.445, 0.445,
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    0.55, 0.525, 0.565, 0.56, 0.59, 0.565, 0.565, 0.595, 0.62,
    0.63, 0.175, 0.245, 0.27, 0.28, 0.3, 0.32, 0.335, 0.325,
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    0.55, 0.605, 0.13, 0.11, 0.15, 0.21, 0.2, 0.215, 0.21, 0.21,
    0.21, 0.24, 0.25, 0.25, 0.235, 0.25, 0.27, 0.27, 0.27, 0.28,
    0.275, 0.29, 0.25, 0.325, 0.315, 0.32, 0.325, 0.33, 0.35,
    0.365, 0.375, 0.365, 0.39, 0.395, 0.385, 0.455, 0.4, 0.41,
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    0.45, 0.445, 0.49, 0.515, 0.515, 0.19, 0.195, 0.215, 0.215,
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    0.47, 0.43, 0.48, 0.49, 0.495, 0.5, 0.525, 0.55, 0.54, 0.57,
    0.5, 0.585, 0.575, 0.555, 0.57, 0.39, 0.425, 0.385, 0.305,
    0.3, 0.39, 0.33, 0.35, 0.31, 0.29, 0.38, 0.31, 0.29, 0.385,
    0.48, 0.455, 0.55, 0.535, 0.49, 0.25, 0.355, 0.405, 0.29,
    0.095, 0.13, 0.225, 0.29, 0.38, 0.37, 0.325, 0.36, 0.35,
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    0.35, 0.33, 0.425, 0.425, 0.455, 0.465, 0.53, 0.36, 0.24,
    0.35, 0.37, 0.35, 0.325, 0.35, 0.375, 0.31, 0.195, 0.355,
    0.585, 0.3, 0.2, 0.44, 0.46, 0.5, 0.495, 0.42, 0.51, 0.55,
    0.565, 0.565, 0.47, 0.305, 0.45, 0.28, 0.275, 0.235, 0.115,
    0.21, 0.13, 0.15, 0.465, 0.5, 0.45, 0.45, 0.45, 0.48, 0.47,
    0.42, 0.42, 0.43, 0.4, 0.235, 0.34, 0.4, 0.385, 0.37, 0.37,
    0.47, 0.495, 0.485, 0.17, 0.325, 0.215, 0.28, 0.305, 0.19,
    0.55, 0.515, 0.49, 0.405, 0.48, 0.345, 0.22, 0.225, 0.34,
    0.525, 0.465, 0.505, 0.47, 0.495, 0.51, 0.325, 0.35, 0.26,
    0.415, 0.39, 0.375, 0.46, 0.465, 0.525, 0.455, 0.425, 0.475,
    0.28, 0.2, 0.39, 0.28, 0.43, 0.4, 0.445, 0.475, 0.45, 0.48,
    0.435, 0.465, 0.335, 0.36, 0.315, 0.32, 0.38, 0.36, 0.28,
    0.375, 0.325, 0.365, 0.27, 0.455, 0.59, 0.485, 0.46, 0.5,
    0.495, 0.395, 0.38, 0.415, 0.335, 0.465, 0.46, 0.43, 0.455,
    0.51, 0.45, 0.575, 0.51, 0.48, 0.445, 0.45, 0.475, 0.41,
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    0.415, 0.385, 0.345, 0.315, 0.33, 0.395, 0.305, 0.265, 0.475,
    0.27, 0.375, 0.3, 0.26, 0.425, 0.415, 0.45, 0.36, 0.325,
    0.385, 0.405, 0.425, 0.375, 0.455, 0.49, 0.415, 0.5, 0.375,
    0.355, 0.375, 0.35, 0.265, 0.24, 0.47, 0.475, 0.435, 0.435,
    0.42, 0.385, 0.395, 0.31, 0.395, 0.435, 0.325, 0.535, 0.305,
    0.345, 0.395, 0.425, 0.39, 0.345, 0.46, 0.42, 0.55, 0.63,
    0.49, 0.48, 0.455, 0.485, 0.52, 0.47, 0.24, 0.185, 0.125,
    0.55, 0.565, 0.43, 0.4, 0.43, 0.36, 0.435, 0.475, 0.53, 0.56,
    0.495, 0.44, 0.47, 0.455, 0.485, 0.525, 0.44, 0.45, 0.525,
    0.475, 0.47, 0.505, 0.57, 0.545, 0.595, 0.44, 0.325, 0.125,
    0.325, 0.405, 0.335, 0.275, 0.34, 0.41, 0.325, 0.265, 0.135,
    0.115, 0.43, 0.39, 0.345, 0.345, 0.365, 0.35, 0.375, 0.34,
    0.35, 0.29, 0.25, 0.22, 0.46, 0.475, 0.465, 0.505, 0.385,
    0.43, 0.33, 0.415, 0.355, 0.225, 0.455, 0.515, 0.46, 0.43,
    0.485, 0.5, 0.375, 0.395, 0.245, 0.38, 0.305, 0.315, 0.315,
    0.235, 0.35, 0.36, 0.255, 0.415, 0.365, 0.315, 0.2, 0.45,
    0.435, 0.19, 0.385, 0.255, 0.38, 0.5, 0.485, 0.515, 0.5,
    0.38, 0.4, 0.24, 0.4, 0.255, 0.355, 0.415, 0.355, 0.335,
    0.355, 0.38, 0.435, 0.205, 0.265, 0.285, 0.33, 0.26, 0.305,
    0.2, 0.2, 0.17, 0.18, 0.185, 0.145, 0.47, 0.35, 0.385, 0.325,
    0.405, 0.405, 0.39, 0.325, 0.415, 0.275, 0.415, 0.475, 0.44,
    0.515, 0.47, 0.49, 0.455, 0.485, 0.42, 0.355, 0.44, 0.425,
    0.285, 0.4, 0.415, 0.36, 0.26, 0.4, 0.51, 0.385, 0.39, 0.325,
    0.395, 0.38, 0.31, 0.305, 0.36, 0.4, 0.4, 0.4, 0.41, 0.39,
    0.26, 0.21, 0.23, 0.24, 0.255, 0.3, 0.325, 0.315, 0.315,
    0.32, 0.31, 0.375, 0.35, 0.37, 0.375, 0.365, 0.37, 0.4, 0.39,
    0.425, 0.42, 0.45, 0.44, 0.46, 0.455, 0.48, 0.49, 0.475,
    0.5, 0.485, 0.475, 0.49, 0.5, 0.585, 0.5, 0.545, 0.525, 0.535,
    0.555, 0.55, 0.55, 0.53, 0.525, 0.57, 0.15, 0.17, 0.18, 0.195,
    0.21, 0.22, 0.22, 0.225, 0.235, 0.265, 0.29, 0.285, 0.295,
    0.31, 0.325, 0.335, 0.345, 0.325, 0.355, 0.35, 0.35, 0.35,
    0.35, 0.345, 0.345, 0.355, 0.34, 0.385, 0.355, 0.37, 0.375,
    0.38, 0.385, 0.395, 0.415, 0.425, 0.42, 0.41, 0.405, 0.435,
    0.425, 0.425, 0.445, 0.435, 0.45, 0.445, 0.45, 0.465, 0.47,
    0.465, 0.465, 0.46, 0.46, 0.46, 0.48, 0.485, 0.5, 0.47, 0.51,
    0.485, 0.475, 0.48, 0.49, 0.49, 0.495, 0.495, 0.48, 0.495,
    0.495, 0.49, 0.5, 0.5, 0.52, 0.545, 0.54, 0.55, 0.525, 0.575,
    0.56, 0.585, 0.6, 0.16, 0.205, 0.21, 0.24, 0.285, 0.29, 0.315,
    0.33, 0.34, 0.32, 0.34, 0.335, 0.345, 0.37, 0.355, 0.365,
    0.375, 0.375, 0.375, 0.38, 0.38, 0.39, 0.38, 0.4, 0.395,
    0.385, 0.4, 0.395, 0.43, 0.42, 0.42, 0.4, 0.42, 0.44, 0.425,
    0.43, 0.45, 0.45, 0.43, 0.48, 0.455, 0.45, 0.435, 0.47, 0.46,
    0.46, 0.465, 0.47, 0.46, 0.49, 0.48, 0.475, 0.45, 0.47, 0.475,
    0.49, 0.48, 0.495, 0.49, 0.48, 0.505, 0.51, 0.465, 0.515,
    0.48, 0.52, 0.515, 0.52, 0.535, 0.51, 0.49, 0.515, 0.505,
    0.5, 0.51, 0.55, 0.52, 0.53, 0.525, 0.55, 0.53, 0.55, 0.57,
    0.575, 0.555, 0.14, 0.15, 0.175, 0.215, 0.25, 0.245, 0.255,
    0.255, 0.26, 0.275, 0.29, 0.275, 0.3, 0.285, 0.32, 0.305,
    0.305, 0.31, 0.305, 0.3, 0.315, 0.325, 0.335, 0.325, 0.315,
    0.34, 0.36, 0.325, 0.335, 0.34, 0.35, 0.345, 0.355, 0.375,
    0.38, 0.365, 0.365, 0.385, 0.38, 0.385, 0.395, 0.41, 0.39,
    0.385, 0.415, 0.4, 0.375, 0.43, 0.44, 0.43, 0.425, 0.42,
    0.425, 0.465, 0.435, 0.445, 0.44, 0.435, 0.43, 0.445, 0.435,
    0.44, 0.465, 0.425, 0.46, 0.465, 0.42, 0.455, 0.47, 0.475,
    0.475, 0.48, 0.495, 0.45, 0.51, 0.48, 0.45, 0.46, 0.465,
    0.48, 0.5, 0.49, 0.505, 0.475, 0.47, 0.525, 0.505, 0.485,
    0.495, 0.495, 0.515, 0.52, 0.51, 0.505, 0.525, 0.525, 0.54,
    0.54, 0.565, 0.55, 0.57, 0.17, 0.195, 0.2, 0.235, 0.24, 0.225,
    0.27, 0.265, 0.285, 0.29, 0.335, 0.35, 0.365, 0.375, 0.365,
    0.375, 0.4, 0.395, 0.43, 0.405, 0.42, 0.415, 0.425, 0.42,
    0.445, 0.445, 0.47, 0.455, 0.485, 0.435, 0.475, 0.45, 0.475,
    0.48, 0.475, 0.5, 0.485, 0.49, 0.485, 0.51, 0.49, 0.49, 0.525,
    0.515, 0.515, 0.515, 0.54, 0.565, 0.55, 0.565, 0.57, 0.595,
    0.23, 0.235, 0.205, 0.25, 0.26, 0.28, 0.27, 0.28, 0.315,
    0.305, 0.34, 0.335, 0.31, 0.36, 0.35, 0.385, 0.375, 0.375,
    0.39, 0.37, 0.425, 0.4, 0.365, 0.4, 0.4, 0.4, 0.465, 0.38,
    0.405, 0.445, 0.425, 0.415, 0.43, 0.43, 0.435, 0.425, 0.435,
    0.43, 0.435, 0.425, 0.455, 0.45, 0.465, 0.46, 0.45, 0.45,
    0.445, 0.44, 0.45, 0.5, 0.46, 0.475, 0.47, 0.46, 0.445, 0.48,
    0.45, 0.45, 0.465, 0.495, 0.49, 0.48, 0.425, 0.47, 0.48,
    0.49, 0.475, 0.515, 0.455, 0.495, 0.475, 0.475, 0.495, 0.515,
    0.5, 0.49, 0.49, 0.48, 0.53, 0.485, 0.51, 0.485, 0.52, 0.485,
    0.5, 0.515, 0.505, 0.575, 0.485, 0.52, 0.495, 0.52, 0.565,
    0.5, 0.515, 0.525, 0.525, 0.51, 0.485, 0.525, 0.525, 0.525,
    0.54, 0.515, 0.505, 0.505, 0.515, 0.55, 0.58, 0.59, 0.575,
    0.215, 0.345, 0.33, 0.365, 0.355, 0.37, 0.38, 0.37, 0.41,
    0.4, 0.4, 0.405, 0.405, 0.425, 0.425, 0.44, 0.485, 0.43,
    0.43, 0.475, 0.485, 0.5, 0.49, 0.51, 0.525, 0.485, 0.495,
    0.505, 0.505, 0.515, 0.54, 0.545, 0.585, 0.615, 0.185, 0.26,
    0.285, 0.3, 0.28, 0.3, 0.32, 0.335, 0.325, 0.32, 0.33, 0.34,
    0.355, 0.37, 0.375, 0.375, 0.33, 0.375, 0.38, 0.385, 0.41,
    0.395, 0.4, 0.42, 0.41, 0.42, 0.405, 0.445, 0.45, 0.44, 0.45,
    0.47, 0.47, 0.43, 0.445, 0.445, 0.435, 0.45, 0.435, 0.47,
    0.405, 0.47, 0.48, 0.46, 0.45, 0.45, 0.495, 0.485, 0.49,
    0.475, 0.515, 0.515, 0.495, 0.505, 0.49, 0.5, 0.485, 0.5,
    0.505, 0.51, 0.54, 0.49, 0.455, 0.53, 0.525, 0.52, 0.52,
    0.56, 0.51, 0.535, 0.555, 0.56, 0.55, 0.575, 0.17, 0.17,
    0.185, 0.27, 0.31, 0.32, 0.35, 0.355, 0.38, 0.395, 0.43,
    0.4, 0.415, 0.395, 0.435, 0.43, 0.48, 0.43, 0.455, 0.465,
    0.5, 0.525, 0.215, 0.22, 0.275, 0.285, 0.29, 0.3, 0.325,
    0.32, 0.325, 0.34, 0.34, 0.405, 0.36, 0.415, 0.4, 0.4, 0.425,
    0.42, 0.45, 0.45, 0.46, 0.495, 0.485, 0.495, 0.49, 0.515,
    0.505, 0.53, 0.39, 0.36, 0.35, 0.42, 0.36, 0.4, 0.26, 0.425,
    0.135, 0.165, 0.15, 0.48, 0.42, 0.45, 0.5, 0.53, 0.54, 0.505,
    0.5, 0.375, 0.335, 0.41, 0.395, 0.44, 0.35, 0.435, 0.255,
    0.2, 0.22, 0.49, 0.44, 0.475, 0.41, 0.54, 0.49, 0.47, 0.45,
    0.465, 0.405, 0.405, 0.265, 0.355, 0.405, 0.38, 0.41, 0.3,
    0.195, 0.295, 0.385, 0.505, 0.44, 0.545, 0.415, 0.36, 0.385,
    0.575, 0.405, 0.145, 0.515, 0.405, 0.435, 0.47, 0.405, 0.245,
    0.235, 0.335, 0.38, 0.405, 0.3, 0.485, 0.505, 0.53, 0.265,
    0.215, 0.38, 0.25, 0.34, 0.45, 0.48, 0.46, 0.42, 0.495, 0.485,
    0.51, 0.34, 0.505, 0.525, 0.4, 0.305, 0.435, 0.415, 0.525,
    0.35, 0.32, 0.35, 0.325, 0.505, 0.455, 0.325, 0.41, 0.48,
    0.485, 0.535, 0.285, 0.51, 0.53, 0.54, 0.435, 0.525, 0.48,
    0.51, 0.555, 0.55, 0.435, 0.495, 0.5, 0.24, 0.35, 0.375,
    0.38, 0.35, 0.35, 0.23, 0.48, 0.385, 0.375, 0.505, 0.435,
    0.52, 0.485, 0.45, 0.5, 0.38, 0.385, 0.335, 0.31, 0.465,
    0.475, 0.425, 0.36, 0.375, 0.405, 0.355, 0.385, 0.39, 0.415,
    0.53, 0.54, 0.45, 0.475, 0.475, 0.44, 0.57, 0.51, 0.46, 0.475,
    0.42, 0.395, 0.405, 0.375, 0.455, 0.5, 0.45, 0.485, 0.5,
    0.5, 0.485, 0.5, 0.525, 0.575, 0.45, 0.435, 0.445, 0.3, 0.325,
    0.2, 0.355, 0.485, 0.38, 0.41, 0.31, 0.355, 0.26, 0.35, 0.2,
    0.125, 0.555, 0.425, 0.385, 0.37, 0.3, 0.28, 0.265, 0.415,
    0.48, 0.475, 0.435, 0.305, 0.34, 0.34, 0.36, 0.3, 0.325,
    0.35, 0.525, 0.525, 0.475, 0.435, 0.39, 0.33, 0.365, 0.38,
    0.38, 0.4, 0.32, 0.385, 0.375, 0.345, 0.38, 0.405, 0.365,
    0.36, 0.34, 0.3, 0.285, 0.215, 0.445, 0.44, 0.315, 0.3, 0.405,
    0.245, 0.31, 0.21, 0.465, 0.48, 0.46, 0.345, 0.235, 0.33,
    0.405, 0.375, 0.33, 0.235, 0.19, 0.255, 0.21, 0.13, 0.435,
    0.4, 0.375, 0.225, 0.35, 0.4, 0.41, 0.535, 0.465, 0.44, 0.42,
    0.515, 0.435, 0.48, 0.45, 0.475, 0.375, 0.285, 0.35, 0.43,
    0.395, 0.345, 0.265, 0.28, 0.25, 0.28, 0.265, 0.315, 0.31,
    0.31, 0.32, 0.355, 0.395, 0.37, 0.465, 0.45, 0.46, 0.48,
    0.47, 0.475, 0.475, 0.47, 0.475, 0.51, 0.545, 0.55, 0.605,
    0.18, 0.21, 0.24, 0.265, 0.27, 0.27, 0.28, 0.285, 0.275,
    0.3, 0.335, 0.35, 0.37, 0.355, 0.37, 0.37, 0.4, 0.4, 0.385,
    0.39, 0.39, 0.395, 0.44, 0.44, 0.44, 0.42, 0.46, 0.475, 0.48,
    0.495, 0.47, 0.505, 0.485, 0.495, 0.47, 0.485, 0.495, 0.48,
    0.5, 0.525, 0.52, 0.585, 0.565, 0.58, 0.12, 0.15, 0.265,
    0.315, 0.29, 0.3, 0.335, 0.33, 0.34, 0.345, 0.355, 0.355,
    0.42, 0.37, 0.475, 0.405, 0.38, 0.42, 0.42, 0.44, 0.44, 0.44,
    0.43, 0.415, 0.44, 0.45, 0.46, 0.47, 0.41, 0.475, 0.47, 0.49,
    0.51, 0.495, 0.47, 0.5, 0.475, 0.52, 0.505, 0.52, 0.54, 0.5,
    0.525, 0.525, 0.575, 0.56, 0.57, 0.545, 0.545, 0.15, 0.185,
    0.205, 0.24, 0.23, 0.26, 0.26, 0.265, 0.265, 0.265, 0.275,
    0.285, 0.31, 0.315, 0.265, 0.325, 0.325, 0.335, 0.34, 0.355,
    0.35, 0.435, 0.34, 0.355, 0.36, 0.35, 0.355, 0.37, 0.365,
    0.39, 0.4, 0.39, 0.405, 0.42, 0.415, 0.41, 0.41, 0.425, 0.45,
    0.47, 0.42, 0.42, 0.455, 0.44, 0.475, 0.45, 0.46, 0.46, 0.47,
    0.47, 0.465, 0.46, 0.465, 0.47, 0.47, 0.475, 0.475, 0.475,
    0.485, 0.48, 0.48, 0.475, 0.5, 0.49, 0.485, 0.465, 0.495,
    0.515, 0.515, 0.52, 0.475, 0.525, 0.53, 0.5, 0.515, 0.515,
    0.53, 0.52, 0.555, 0.125, 0.285, 0.3, 0.325, 0.37, 0.375,
    0.375, 0.39, 0.43, 0.405, 0.45, 0.465, 0.46, 0.49, 0.475,
    0.475, 0.495, 0.46, 0.515, 0.5, 0.5, 0.455, 0.505, 0.53,
    0.5, 0.525, 0.53, 0.525, 0.565, 0.205, 0.225, 0.22, 0.225,
    0.22, 0.265, 0.275, 0.29, 0.325, 0.34, 0.32, 0.345, 0.37,
    0.355, 0.345, 0.365, 0.335, 0.35, 0.365, 0.39, 0.405, 0.415,
    0.405, 0.425, 0.425, 0.42, 0.41, 0.395, 0.405, 0.45, 0.41,
    0.41, 0.415, 0.45, 0.4, 0.43, 0.45, 0.44, 0.42, 0.465, 0.46,
    0.465, 0.47, 0.44, 0.46, 0.45, 0.47, 0.5, 0.49, 0.49, 0.45,
    0.495, 0.47, 0.5, 0.525, 0.47, 0.48, 0.485, 0.485, 0.49,
    0.505, 0.5, 0.51, 0.52, 0.495, 0.495, 0.52, 0.525, 0.51,
    0.51, 0.525, 0.53, 0.51, 0.54, 0.51, 0.54, 0.54, 0.535, 0.51,
    0.53, 0.55, 0.535, 0.55, 0.53, 0.555, 0.56, 0.6, 0.13, 0.25,
    0.25, 0.28, 0.32, 0.31, 0.36, 0.355, 0.365, 0.375, 0.395,
    0.4, 0.375, 0.38, 0.37, 0.415, 0.42, 0.455, 0.505, 0.475,
    0.48, 0.47, 0.505, 0.525, 0.5, 0.525, 0.525, 0.555, 0.205,
    0.205, 0.265, 0.29, 0.315, 0.33, 0.375, 0.335, 0.355, 0.36,
    0.37, 0.395, 0.39, 0.41, 0.4, 0.425, 0.425, 0.42, 0.395,
    0.41, 0.4, 0.45, 0.44, 0.46, 0.465, 0.43, 0.43, 0.45, 0.465,
    0.46, 0.42, 0.45, 0.42, 0.47, 0.45, 0.48, 0.48, 0.455, 0.5,
    0.48, 0.48, 0.495, 0.5, 0.49, 0.475, 0.51, 0.505, 0.495,
    0.52, 0.525, 0.52, 0.54, 0.54, 0.58, 0.535, 0.56, 0.58, 0.155,
    0.23, 0.23, 0.27, 0.305, 0.31, 0.365, 0.385, 0.375, 0.4,
    0.445, 0.49, 0.26, 0.275, 0.34, 0.355, 0.385, 0.445, 0.45,
    0.44, 0.46, 0.48, 0.455, 0.46, 0.47, 0.52, 0.54, 0.52, 0.555,
    0.385, 0.42, 0.365, 0.41, 0.26, 0.35, 0.325, 0.105, 0.25,
    0.425, 0.41, 0.42, 0.475, 0.45, 0.45, 0.35, 0.275, 0.37,
    0.535, 0.3, 0.295, 0.44, 0.41, 0.465, 0.4, 0.335, 0.255,
    0.515, 0.45, 0.44, 0.465, 0.475, 0.37, 0.5, 0.235, 0.395,
    0.43, 0.39, 0.34, 0.385, 0.44, 0.36, 0.4, 0.25, 0.41, 0.225,
    0.45, 0.5, 0.355, 0.49, 0.3, 0.455, 0.545, 0.425, 0.225,
    0.33, 0.375, 0.44, 0.45, 0.5, 0.4, 0.46, 0.4, 0.355, 0.38,
    0.5, 0.575, 0.5, 0.46, 0.105, 0.345, 0.43, 0.12, 0.48, 0.47,
    0.27, 0.18, 0.39, 0.365, 0.375, 0.355, 0.27, 0.405, 0.4,
    0.39, 0.445, 0.41, 0.46, 0.49, 0.43, 0.23, 0.28, 0.4, 0.28,
    0.4, 0.35, 0.42, 0.38, 0.55, 0.515, 0.535, 0.44, 0.37, 0.18,
    0.175, 0.41, 0.4, 0.425, 0.275, 0.42, 0.39, 0.44, 0.4, 0.45,
    0.44, 0.175, 0.41, 0.365, 0.4, 0.415, 0.425, 0.39, 0.235,
    0.355, 0.385, 0.385, 0.395, 0.44, 0.5, 0.55, 0.55, 0.55,
    0.575, 0.205, 0.19, 0.22, 0.22, 0.23, 0.29, 0.3, 0.285, 0.295,
    0.315, 0.33, 0.32, 0.33, 0.35, 0.35, 0.39, 0.375, 0.41, 0.455,
    0.435, 0.45, 0.465, 0.48, 0.525, 0.545, 0.515, 0.52, 0.51,
    0.51, 0.6, 0.6, 0.135, 0.175, 0.23, 0.27, 0.28, 0.31, 0.35,
    0.35, 0.375, 0.39, 0.395, 0.43, 0.465, 0.46, 0.455, 0.49,
    0.475, 0.53, 0.465, 0.505, 0.48, 0.48, 0.525, 0.505, 0.485,
    0.515, 0.55, 0.58, 0.545, 0.2, 0.245, 0.26, 0.28, 0.27, 0.31,
    0.335, 0.325, 0.325, 0.365, 0.385, 0.405, 0.41, 0.42, 0.415,
    0.445, 0.44, 0.45, 0.45, 0.46, 0.46, 0.425, 0.45, 0.46, 0.485,
    0.495, 0.495, 0.495, 0.5, 0.47, 0.485, 0.5, 0.5, 0.51, 0.535,
    0.56, 0.39, 0.405, 0.465, 0.49, 0.515, 0.49, 0.275, 0.31,
    0.3, 0.305, 0.335, 0.335, 0.375, 0.36, 0.395, 0.4, 0.45,
    0.43, 0.435, 0.43, 0.385, 0.43, 0.45, 0.465, 0.445, 0.48,
    0.51, 0.45, 0.475, 0.47, 0.365, 0.475, 0.5, 0.49, 0.485,
    0.53, 0.485, 0.5, 0.5, 0.495, 0.525, 0.52, 0.51, 0.545, 0.545,
    0.545, 0.565, 0.59, 0.305, 0.35, 0.365, 0.41, 0.4, 0.42,
    0.42, 0.45, 0.465, 0.48, 0.505, 0.525, 0.215, 0.265, 0.35,
    0.365, 0.375, 0.385, 0.415, 0.42, 0.445, 0.435, 0.425, 0.45,
    0.425, 0.47, 0.45, 0.455, 0.5, 0.495, 0.505, 0.49, 0.495,
    0.535, 0.505, 0.525, 0.5, 0.535, 0.525, 0.53, 0.55, 0.605,
    0.215, 0.23, 0.25, 0.28, 0.315, 0.33, 0.35, 0.37, 0.36, 0.355,
    0.44, 0.475, 0.455, 0.255, 0.31, 0.29, 0.3, 0.365, 0.38,
    0.4, 0.385, 0.43, 0.43, NA, 0.385, 0.45, 0.44, 0.475, 0.485,
    0.555), questiontype = "Number", name = "Diameter", label = "Diameter", question = "Diameter")), .Names = c("Length",
"Diameter"), row.names = c(NA, 4179L), class = "data.frame")

test_that("Numeric variables",
{
    expect_error(SankeyDiagram(datNumeric, link.color = "Source", variables.share.values = TRUE), NA)
})

datText <- structure(list(Q1_Gender = structure(c(2L, 2L, 1L, 1L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L,
2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L,
1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L,
1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L,
1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L,
2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L,
1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L,
1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = c("Male", "Female"), class = "factor", questiontype = "PickOne", name = "Q1", label = "Q1_Gender", question = "Q1_Gender"),
    structure.c..2713356459....4697558946....3572816992....7169244672... = structure(c(57L,
    141L, 88L, 217L, 210L, 93L, 262L, 127L, 243L, 91L, 37L, 187L,
    44L, 34L, 133L, 230L, 38L, 97L, 35L, 309L, 110L, 148L, 282L,
    244L, 193L, 311L, 25L, 165L, 46L, 161L, 283L, 216L, 131L,
    64L, 20L, 209L, 206L, 304L, 307L, 112L, 276L, 50L, 246L,
    211L, 180L, 5L, 125L, 6L, 250L, 278L, 171L, 139L, 272L, 106L,
    196L, 237L, 290L, 2L, 42L, 160L, 137L, 301L, 152L, 119L,
    294L, 159L, 234L, 197L, 101L, 82L, 162L, 13L, 308L, 94L,
    232L, 24L, 14L, 8L, 129L, 253L, 154L, 238L, 166L, 28L, 233L,
    149L, 202L, 132L, 49L, 66L, 270L, 103L, 10L, 22L, 45L, 65L,
    287L, 195L, 90L, 105L, 274L, 142L, 179L, 236L, 163L, 134L,
    252L, 255L, 231L, 223L, 84L, 89L, 123L, 279L, 228L, 27L,
    296L, 111L, 157L, 305L, 55L, 260L, 172L, 189L, 168L, 130L,
    32L, 41L, 75L, 118L, 258L, 164L, 288L, 73L, 297L, 302L, 277L,
    102L, 78L, 100L, 201L, 54L, 81L, 240L, 224L, 167L, 222L,
    60L, 11L, 70L, 275L, 312L, 310L, 31L, 266L, 51L, 184L, 269L,
    86L, 147L, 241L, 169L, 174L, 265L, 256L, 284L, 121L, 194L,
    21L, 268L, 300L, 245L, 185L, 263L, 128L, 156L, 95L, 235L,
    170L, 158L, 36L, 226L, 108L, 175L, 181L, 204L, 136L, 221L,
    52L, 126L, 192L, 249L, 98L, 280L, 124L, 39L, 299L, 68L, 15L,
    30L, 87L, 122L, 85L, 69L, 199L, 80L, 48L, 291L, 143L, 190L,
    92L, 115L, 23L, 155L, 218L, 71L, 248L, 183L, 198L, 220L,
    267L, 273L, 40L, 239L, 229L, 29L, 200L, 17L, 208L, 26L, 59L,
    4L, 205L, 207L, 3L, 117L, 264L, 254L, 173L, 212L, 77L, 18L,
    43L, 62L, 251L, 306L, 109L, 298L, 145L, 96L, 138L, 227L,
    213L, 281L, 303L, 144L, 176L, 178L, 1L, 242L, 140L, 12L,
    16L, 257L, 63L, 150L, 120L, 61L, 151L, 19L, 47L, 135L, 292L,
    271L, 104L, 261L, 113L, 289L, 153L, 116L, 182L, 74L, 76L,
    191L, 146L, 293L, 247L, 67L, 259L, 53L, 79L, 186L, 107L,
    99L, 114L, 215L, 72L, 214L, 219L, 188L, 203L, 56L, 58L, 225L,
    9L, 177L, 286L, 285L, 7L, 295L, 83L, 33L), .Label = c("1128637539",
    "1143433625", "1145887988", "1157196216", "1245671145", "1321456183",
    "1333137162", "1344191275", "1344724413", "1367235791", "1381633594",
    "1385528814", "1425374126", "1512498786", "1533575946", "1548245329",
    "1564692622", "1652884653", "1666526718", "1681384926", "1688116566",
    "1755417713", "1835325182", "1838371469", "1875733825", "1884993736",
    "1923676331", "1972149783", "2123398582", "2144572322", "2145885693",
    "2149648869", "2159149469", "2163255157", "2193321246", "2214394433",
    "2224255615", "2259721885", "2265818188", "2286474582", "2294387349",
    "2323674471", "2344371915", "2348229151", "2428374753", "2468175142",
    "2479832822", "2496122341", "2553835174", "2577372339", "2597649268",
    "2598529283", "2626973414", "2654723718", "2662821434", "2696983597",
    "2713356459", "2758284479", "2843214666", "2844794626", "2845318915",
    "2873586171", "2875768771", "2892938652", "2927568293", "2941763832",
    "2966234434", "3113661991", "3133478894", "3137412761", "3163694627",
    "3166245879", "3218363763", "3261871846", "3269988321", "3278329965",
    "3323245446", "3329656493", "3334469163", "3345942152", "3378396544",
    "3412791947", "3432459194", "3465426121", "3523565131", "3562838538",
    "3566258747", "3572816992", "3591659876", "3629824718", "3653289161",
    "3685385524", "3714771246", "3716959587", "3719657677", "3726984923",
    "3735292658", "3761428749", "3768686173", "3769863826", "3798948431",
    "3811791483", "3833994262", "3838897262", "3839245644", "3842329534",
    "3875297863", "3956476577", "3984945782", "3997893199", "4113986861",
    "4138939635", "4142577887", "4144656431", "4146577588", "4158627531",
    "4221853949", "4233198932", "4239133487", "4241244483", "4242819518",
    "4258714293", "4264942384", "4281791681", "4284156287", "4293635835",
    "4315372837", "4315742337", "4317265363", "4379293694", "4392178233",
    "4434371676", "4443376862", "4458513996", "4472892736", "4497584676",
    "4564781289", "4638913231", "4644556998", "4657411685", "4697558946",
    "4752765125", "4765987715", "4794929625", "4828622485", "4861263979",
    "4863626775", "4924655652", "4932586431", "4959815485", "4992699135",
    "5145971723", "5161778319", "5184256819", "5278157779", "5278189828",
    "5285314352", "5289313291", "5323489619", "5331979766", "5362875422",
    "5383137272", "5456282327", "5485222297", "5543348984", "5552142259",
    "5633357864", "5635349861", "5658841831", "5689537285", "5721851261",
    "5728411187", "5767742626", "5775977279", "5793818688", "5872828747",
    "5915973755", "5916718856", "5919577679", "5922431364", "5965683166",
    "5986471173", "5994675585", "6125198849", "6165716397", "6174265959",
    "6179746498", "6185469911", "6189591612", "6234147966", "6235693912",
    "6246953239", "6369426484", "6514299123", "6568638267", "6574681822",
    "6616152959", "6642182639", "6661658383", "6671914877", "6684347758",
    "6685181658", "6691474917", "6716784334", "6718143715", "6724725643",
    "6748286747", "6789128283", "6794625711", "6797129669", "6837224216",
    "6854383242", "6857913476", "6925257824", "7144493576", "7147844586",
    "7169244672", "7178674687", "7187117681", "7187736442", "7216842755",
    "7252122311", "7339449691", "7343564276", "7346518431", "7355617391",
    "7374272948", "7392281626", "7412215611", "7461148296", "7484147636",
    "7543583393", "7548411526", "7564339788", "7612777571", "7661642962",
    "7672123632", "7749234674", "7757827346", "7761869155", "7766334486",
    "7823329598", "7855482687", "7897613819", "8115878241", "8127612456",
    "8128716858", "8139183856", "8179123236", "8242218232", "8332431283",
    "8335286557", "8337492592", "8343873562", "8344892814", "8373914124",
    "8374266567", "8388362595", "8456443771", "8544655428", "8559495749",
    "8591483111", "8617486352", "8629654414", "8645313658", "8651368991",
    "8659678167", "8678262638", "8683372219", "8697337625", "8729958711",
    "8756924831", "8795648123", "8796781476", "8797222874", "8799919987",
    "8847852527", "8873734735", "8912526689", "8937326245", "9127712591",
    "9141998723", "9166619467", "9171479678", "9196511659", "9198121218",
    "9216584399", "9268842155", "9274995215", "9337725435", "9366621519",
    "9371315544", "9379333826", "9415313425", "9449592831", "9456767414",
    "9485757253", "9524245545", "9531919588", "9532597996", "9578689565",
    "9641775822", "9665316194", "9765377468", "9782765779", "9797246358",
    "9818758559", "9869754839", "9914965219", "9945643398", "9965382796",
    "9999291226"), class = "factor")), .Names = c("Q1_Gender",
"structure.c..2713356459....4697558946....3572816992....7169244672..."
), row.names = c(NA, 312L), class = "data.frame")

test_that("Many categories",
{
    expect_error(SankeyDiagram(datText), NA)
})

dat.longnames <- structure(list(`D3 - Gender` = structure(c(2L, 1L, 2L, 2L, 2L,
1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L,
1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L,
1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L,
2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L,
1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L,
1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L,
1L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L,
2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L,
1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L,
1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L,
1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L,
1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L,
2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L,
1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L,
1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L,
1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L,
1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L,
2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L,
1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L,
1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L,
2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L,
2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L,
1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L,
2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,
2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L,
2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L,
2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L,
1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L,
1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L,
1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L,
1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L,
2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L,
2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L,
1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L,
1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L,
1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L,
1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L,
2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L), levels = c("Male",
"Female"), class = "factor", questiontype = "PickOne", dataset = "Cola Tracking - January to December 2017.sav", values = c(Male = 1,
Female = 2), sourcevalues = c(Male = 1, Female = 2), codeframe = list(
    Male = 1, Female = 2, NET = c(1, 2)), name = "d3", label = "D3 - Gender", question = "D3 - Gender"),
    `D4 - Living arrangements` = structure(c(3L, 3L, 3L, 2L,
    5L, 3L, 5L, 2L, 5L, 5L, 5L, 3L, 1L, 5L, 3L, 5L, 2L, 1L, 5L,
    3L, 3L, 5L, 5L, 2L, 5L, 3L, 5L, 5L, 5L, 5L, 3L, 5L, 5L, 1L,
    5L, 5L, 5L, 1L, 2L, 6L, 6L, 3L, 6L, 5L, 6L, 4L, 2L, 5L, 3L,
    5L, 3L, 6L, 1L, 3L, 5L, 3L, 1L, 2L, 5L, 3L, 3L, 6L, 3L, 5L,
    2L, 6L, 3L, 5L, 1L, 2L, 2L, 3L, 4L, 6L, 3L, 5L, 5L, 3L, 6L,
    3L, 3L, 3L, 5L, 2L, 3L, 3L, 5L, 2L, 3L, 4L, 1L, 6L, 3L, 5L,
    5L, 4L, 5L, 4L, 3L, 1L, 3L, 2L, 5L, 3L, 5L, 3L, 5L, 2L, 4L,
    3L, 4L, 5L, 5L, 5L, 3L, 2L, 2L, 3L, 5L, 1L, 3L, 1L, 3L, 3L,
    3L, 6L, 3L, 5L, 5L, 5L, 2L, 5L, 3L, 6L, 3L, 3L, 3L, 3L, 1L,
    2L, 5L, 5L, 3L, 3L, 3L, 6L, 5L, 5L, 1L, 2L, 2L, 5L, 6L, 5L,
    1L, 3L, 5L, 3L, 3L, 3L, 3L, 5L, 3L, 6L, 3L, 3L, 5L, 5L, 5L,
    5L, 5L, 3L, 3L, 5L, 3L, 4L, 3L, 6L, 3L, 3L, 5L, 5L, 5L, 1L,
    3L, 3L, 4L, 2L, 3L, 5L, 2L, 3L, 5L, 3L, 5L, 3L, 3L, 3L, 5L,
    4L, 3L, 3L, 5L, 3L, 3L, 5L, 2L, 3L, 3L, 5L, 3L, 1L, 3L, 5L,
    3L, 5L, 2L, 1L, 5L, 3L, 5L, 2L, 3L, 5L, 5L, 5L, 3L, 5L, 5L,
    1L, 5L, 5L, 5L, 1L, 3L, 2L, 3L, 6L, 5L, 5L, 5L, 3L, 3L, 5L,
    5L, 2L, 5L, 2L, 3L, 5L, 3L, 3L, 6L, 3L, 3L, 1L, 2L, 3L, 1L,
    6L, 5L, 6L, 5L, 5L, 1L, 1L, 5L, 2L, 3L, 2L, 5L, 3L, 3L, 3L,
    3L, 5L, 3L, 4L, 6L, 3L, 5L, 5L, 5L, 3L, 3L, 5L, 2L, 3L, 3L,
    1L, 2L, 3L, 4L, 5L, 6L, 5L, 5L, 3L, 4L, 3L, 6L, 3L, 1L, 1L,
    5L, 6L, 2L, 5L, 5L, 3L, 3L, 5L, 3L, 4L, 4L, 1L, 5L, 5L, 5L,
    3L, 5L, 2L, 2L, 3L, 1L, 5L, 1L, 1L, 3L, 3L, 6L, 5L, 3L, 5L,
    5L, 5L, 2L, 5L, 3L, 5L, 6L, 1L, 2L, 5L, 4L, 5L, 3L, 3L, 5L,
    3L, 6L, 5L, 5L, 1L, 2L, 5L, 6L, 5L, 5L, 5L, 2L, 5L, 3L, 3L,
    5L, 5L, 3L, 5L, 5L, 5L, 3L, 3L, 4L, 5L, 5L, 3L, 3L, 3L, 3L,
    5L, 5L, 1L, 4L, 2L, 3L, 5L, 5L, 2L, 3L, 5L, 5L, 3L, 5L, 3L,
    3L, 3L, 5L, 6L, 2L, 4L, 3L, 3L, 5L, 2L, 2L, 5L, 3L, 5L, 2L,
    5L, 5L, 5L, 5L, 3L, 1L, 3L, 3L, 3L, 5L, 5L, 2L, 3L, 5L, 5L,
    3L, 5L, 5L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 1L, 2L, 5L, 5L, 5L,
    6L, 3L, 6L, 5L, 5L, 6L, 2L, 5L, 2L, 3L, 5L, 3L, 5L, 6L, 3L,
    5L, 5L, 3L, 3L, 5L, 5L, 6L, 5L, 5L, 1L, 1L, 5L, 2L, 5L, 4L,
    6L, 3L, 5L, 6L, 3L, 5L, 5L, 3L, 5L, 1L, 3L, 5L, 2L, 3L, 3L,
    3L, 5L, 5L, 1L, 2L, 4L, 5L, 1L, 6L, 3L, 5L, 4L, 6L, 3L, 1L,
    5L, 3L, 3L, 6L, 3L, 5L, 5L, 3L, 5L, 5L, 2L, 4L, 4L, 1L, 3L,
    4L, 2L, 5L, 2L, 1L, 6L, 5L, 5L, 5L, 1L, 3L, 3L, 3L, 3L, 6L,
    5L, 3L, 6L, 5L, 5L, 5L, 3L, 3L, 3L, 3L, 3L, 1L, 3L, 5L, 5L,
    5L, 3L, 3L, 3L, 6L, 5L, 5L, 5L, 1L, 2L, 2L, 5L, 5L, 1L, 3L,
    5L, 5L, 2L, 3L, 5L, 7L, 5L, 6L, 2L, 5L, 5L, 5L, 3L, 3L, 5L,
    3L, 3L, 4L, 5L, 3L, 2L, 5L, 5L, 5L, 1L, 3L, 2L, 5L, 5L, 2L,
    3L, 5L, 3L, 3L, 2L, 3L, 3L, 5L, 3L, 6L, 4L, 5L, 3L, 2L, 5L,
    3L, 5L, 5L, 3L, 2L, 5L, 5L, 3L, 3L, 3L, 3L, 5L, 5L, 3L, 3L,
    5L, 5L, 2L, 5L, 5L, 5L, 5L, 5L, 3L, 3L, 5L, 5L, 1L, 5L, 1L,
    6L, 5L, 5L, 3L, 4L, 5L, 5L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 3L,
    2L, 5L, 1L, 6L, 3L, 5L, 2L, 3L, 1L, 5L, 2L, 2L, 3L, 3L, 6L,
    5L, 5L, 3L, 4L, 6L, 3L, 5L, 3L, 5L, 3L, 5L, 1L, 3L, 5L, 2L,
    5L, 1L, 2L, 5L, 2L, 3L, 4L, 5L, 1L, 6L, 3L, 4L, 5L, 3L, 3L,
    6L, 3L, 1L, 5L, 3L, 3L, 5L, 3L, 3L, 5L, 2L, 4L, 4L, 4L, 5L,
    3L, 5L, 5L, 3L, 4L, 2L, 3L, 1L, 1L, 5L, 3L, 3L, 3L, 3L, 3L,
    3L, 6L, 5L, 3L, 6L, 5L, 5L, 5L, 2L, 5L, 3L, 5L, 6L, 3L, 3L,
    3L, 3L, 1L, 2L, 5L, 4L, 5L, 3L, 3L, 5L, 5L, 5L, 5L, 6L, 5L,
    5L, 3L, 5L, 3L, 7L, 3L, 2L, 3L, 5L, 3L, 5L, 5L, 3L, 5L, 5L,
    3L, 3L, 4L, 5L, 3L, 6L, 5L, 5L, 3L, 3L, 5L, 5L, 4L, 2L, 3L,
    2L, 3L, 5L, 5L, 3L, 5L, 4L, 3L, 2L, 3L, 3L, 5L, 3L, 5L, 2L,
    4L), levels = c("Living with your parents/guardian", "Living alone",
    "Living with partner only", "Living with children only",
    "Living with partner and children", "Sharing accommodation",
    "Other (Please type into the box.)"), class = "factor", questiontype = "PickOne", dataset = "Cola Tracking - January to December 2017.sav", values = c(`Living with your parents/guardian` = 1,
    `Living alone` = 2, `Living with partner only` = 3, `Living with children only` = 4,
    `Living with partner and children` = 5, `Sharing accommodation` = 6,
    `Other (Please type into the box.)` = 7), sourcevalues = c(`Living with your parents/guardian` = 1,
    `Living alone` = 2, `Living with partner only` = 3, `Living with children only` = 4,
    `Living with partner and children` = 5, `Sharing accommodation` = 6,
    `Other (Please type into the box.)` = 7), codeframe = list(
        `Living with your parents/guardian` = 1, `Living alone` = 2,
        `Living with partner only` = 3, `Living with children only` = 4,
        `Living with partner and children` = 5, `Sharing accommodation` = 6,
        `Other (Please type into the box.)` = 7, NET = c(1, 2,
        3, 4, 5, 6, 7)), name = "d4", label = "D4 - Living arrangements", question = "D4 - Living arrangements")), row.names = c(NA,
800L), class = "data.frame")

test_that("Label truncation keeps nodes", {
    sdat100 <- SankeyDiagram(dat.longnames, label.max.length = 100,
                         output.data.only = TRUE, link.color = "Target")
    sdat10 <- SankeyDiagram(dat.longnames, label.max.length = 10,
                        output.data.only = TRUE, link.color = "Target")
    expect_equal(nrow(sdat100), nrow(sdat10))
    expect_equal(sdat100$nodes$group, sdat10$nodes$group)
})