tests/testthat/test_adp.R

In oce: Analysis of Oceanographic Data

# vim:textwidth=128:expandtab:shiftwidth=4:softtabstop=4
library(oce)
data(adp)

test_that("array values in data slot of 'adp' dataset are well-formed", {
    dataNames <- names(adp[["data"]])
    dimExpected <- c(25L, 84L, 4L)
    for (name in c("a", "g", "q", "v")) {
        expect_true(name %in% dataNames)
        expect_true(identical(dimExpected, dim(adp[[name]])))
        if (name %in% c("a", "g", "q")) {
            expect_true(is.raw(adp[[name]]))
        }
    }
})

test_that("as.adp() inserts data properly", {
    data(adp)
    t <- adp[["time"]]
    d <- adp[["distance"]]
    v <- adp[["v"]]
    a <- as.adp(time = t, distance = d, v = v)
    expect_equal(a[["time"]], adp[["time"]])
    expect_equal(a[["distance"]], adp[["distance"]])
    expect_equal(a[["v"]], adp[["v"]])
})

test_that("adpEnsembleAverage() produces correctly-dimensioned results", {
    n <- 5
    adpAvg <- adpEnsembleAverage(adp, n = n)
    expect_equal(length(adp[["time"]]), n * length(adpAvg[["time"]]))
    expect_equal(dim(adp[["v"]]), c(n, 1, 1) * dim(adpAvg[["v"]]))
    for (name in names(adp@data)) {
        if (is.vector(adp[[name]]) && "distance" != name) {
            expect_equal(adpAvg[[name]][1], mean(adp[[name]][1:n]))
        }
    }
    expect_equal(adpAvg[["v"]][1, 1, 1], mean(adp[["v"]][1:n, 1, 1]))
    expect_equal(adpAvg[["v"]][1, 2, 1], mean(adp[["v"]][1:n, 2, 1]))
    expect_equal(adpAvg[["v"]][1, 1, 2], mean(adp[["v"]][1:n, 1, 2]))
    # Test leftover bins: case 1, with a leftover
    adpAvg <- adpEnsembleAverage(adp, n = 4, leftover = TRUE)
    nexpected <- 7 # have 6*4 full bins, plus 1 leftover bin
    expect_equal(length(adpAvg[["time"]]), nexpected)
    expect_equal(tail(adp[["time"]], 1), tail(adpAvg[["time"]], 1))
    expect_equal(dim(adpAvg[["v"]])[1], nexpected)
    expect_equal(dim(adpAvg[["v"]]), dim(adpAvg[["q"]]))
    expect_equal(dim(adpAvg[["v"]]), dim(adpAvg[["a"]]))
    expect_equal(dim(adpAvg[["v"]]), dim(adpAvg[["g"]]))
    # Test leftover bins: case 2, with no leftover
    adpAvg <- adpEnsembleAverage(adp, n = 4)
    nexpected <- 6 # because 6*4 < 25
    expect_equal(length(adpAvg[["time"]]), nexpected)
    expect_equal(dim(adpAvg[["v"]])[1], nexpected)
    expect_equal(dim(adpAvg[["v"]]), dim(adpAvg[["q"]]))
    expect_equal(dim(adpAvg[["v"]]), dim(adpAvg[["a"]]))
    expect_equal(dim(adpAvg[["v"]]), dim(adpAvg[["g"]]))
})

f <- "~/Dropbox/data/archive/sleiwex/2008/moorings/m09/adp/rdi_2615/raw/adp_rdi_2615.000"
if (file.exists(f)) {
    skip_on_cran()
    test_that("details of a local RDI", {
        # args for read.adp.rdi() are file, from, to, by and tz
        expect_silent(d <- read.oce(f, 1, 3, 1, "UTC"))
        expect_equal(d[["time"]], as.POSIXct(c(
            "2008-06-25 10:00:00",
            "2008-06-25 10:00:10",
            "2008-06-25 10:00:20"
        ), tz = "UTC"))

        expect_equal(d[["distance"]], c(
            2.23, 2.73, 3.23, 3.73, 4.23, 4.73, 5.23, 5.73, 6.23, 6.73, 7.23, 7.73, 8.23,
            8.73, 9.23, 9.73, 10.23, 10.73, 11.23, 11.73, 12.23, 12.73, 13.23, 13.73, 14.23,
            14.73, 15.23, 15.73, 16.23, 16.73, 17.23, 17.73, 18.23, 18.73, 19.23, 19.73,
            20.23, 20.73, 21.23, 21.73, 22.23, 22.73, 23.23, 23.73, 24.23, 24.73, 25.23,
            25.73, 26.23, 26.73, 27.23, 27.73, 28.23, 28.73, 29.23, 29.73, 30.23, 30.73,
            31.23, 31.73, 32.23, 32.73, 33.23, 33.73, 34.23, 34.73, 35.23, 35.73, 36.23,
            36.73, 37.23, 37.73, 38.23, 38.73, 39.23, 39.73, 40.23, 40.73, 41.23, 41.73,
            42.23, 42.73, 43.23, 43.73
        ))

        v <- array(c(
            0.034, 0.073, 0.107, 0.049, -0.012, 0.11, 0.034, 0.024, 0.104,
            -0.027, -0.015, 0.144, 0.038, 0.076, 0.227, -0.028, -0.02, 0.117,
            0.048, -0.03, 0.187, -0.093, -0.033, 0.2, -0.071, 0.028, 0.166,
            0.029, 0.115, 0.146, 0.081, 0.004, 0.219, 0.025, -0.074, 0.188,
            -0.039, 0.11, 0.113, -0.07, 0.088, 0.249, 0.06, -0.055, 0.15,
            -0.054, 0.019, 0.146, 0.046, -0.08, 0.098, -0.072, 0.013, 0.123,
            -0.004, -0.06, 0.066, -0.058, 0.055, 0.152, -0.022, 0.037, 0.149,
            0.007, -0.053, 0.139, 0.032, -0.007, 0.143, 0.113, -0.046, 0.063,
            0.085, 0.001, 0.18, -0.046, -0.012, 0.097, -0.038, -0.034, 0.113,
            -0.016, 0.061, 0.163, 0.017, 0.013, 0.197, 0, 0.092, 0.229,
            0.015, 0.052, 0.137, -0.048, 0.185, 0.079, -0.029, 0.033, 0.099,
            0.058, -0.039, 0.11, 0.016, 0.108, 0.036, -0.012, 0.084, 0.078,
            0.014, 0.06, 0.044, 0.048, -0.023, 0.036, 0.058, 0.087, 0.078,
            0.03, 0.039, 0.179, -0.074, 0.129, 0.065, 0.056, 0.13, 0.166,
            -0.001, 0.173, 0.145, -0.135, 0.117, 0.057, 0.072, 0.025, 0.176,
            -0.158, 0.096, 0.113, -0.022, 0.021, 0.04, 0.007, 0.015, -0.019,
            -0.063, 0.167, 0.056, -0.104, 0.103, 0.217, 0.008, 0.137, 0.154,
            -0.013, 0.156, 0.242, 0.033, 0.058, 0.083, -0.188, 0.179, 0.208,
            -0.107, 0.087, 0.141, 0.037, 0.192, 0.152, -0.07, 0.185, 0.074,
            -0.022, 0.345, 0.084, -0.078, 0.246, 0.193, -0.039, 0.22, 0.156,
            0.019, 0.277, 0.107, 0.023, 0.296, 0.144, 0.121, 0.281, 0.131,
            0.026, 0.305, 0.215, 0.048, 0.328, 0.225, -0.002, 0.269, 0.052,
            0.079, 0.172, -0.025, 0.054, 0.148, 0.062, 0.1, 0.119, 0.134,
            0.11, 0.277, -0.026, 0.209, 0.264, 0.022, 0.057, 0.168, -0.094,
            0.051, 0.214, -0.06, 0.026, 0.251, 0.083, -0.038, 0.143, -0.162,
            -0.025, 0.176, 0.023, 0.043, 0.233, 0.003, 0.028, 0.25, -0.119,
            -0.058, 0.246, 0.035, 0.038, 0.197, -0.033, -0.053, 0.184, 0.014,
            -0.023, 0.157, -0.038, 0.016, 0.177, -0.051, 0.045, 0.165,
            -0.156, 0.035, 0.126, 0.042, 0.013, 0.045, 0.032, -0.009, 0.132,
            0.047, -0.021, -0.01, 0.052, -0.094, 0.003, 0.073, 0, 0.07,
            0.148, -0.019, 0.139, 0.116, -0.169, -0.052, 0.267, -0.126,
            -0.011, 0.014, -0.136, -0.054, 0.025, -0.168, -0.071, 0.049,
            -0.148, -0.104, 0.156, -0.11, 0.173, 0.105, -0.011, -0.034,
            0.087, -0.112, -0.055, -0.069, -0.126, 0.047, 0.202, -0.03,
            0.166, 0.208, -0.048, 0.026, -0.02, -0.152, -0.046, 0.173,
            -0.063, -0.068, 0.154, -0.05, -0.058, 0.281, 0.004, -0.08, 0.163,
            0.02, -0.008, 0.102, 0.012, -0.029, 0.216, -0.013, -0.066, 0.187,
            0, 0.082, 0.206, -0.024, 0.061, 0.281, -0.097, 0.024, 0.261,
            -0.028, 0.012, 0.227, -0.076, -0.036, 0.127, -0.2, -0.017, 0.174,
            -0.017, -0.079, 0.291, -0.06, -0.178, 0.206, -0.131, -0.11, 0.21,
            -0.05, -0.063, 0.141, -0.103, -0.22, 0.235, -0.071, -0.217,
            0.262, -0.026, -0.037, 0.234, -0.063, -0.134, 0.243, 0.06,
            -0.097, 0.199, -0.03, -0.136, 0.177, 0.029, -0.134, 0.103, 0.056,
            0.019, 0.185, -0.084, -0.046, 0.096, 0.075, -0.131, 0.155,
            -0.105, -0.169, 0.316, 0.065, -0.159, 0.106, -0.129, -0.049,
            0.158, 0.046, 0.027, 0.272, 0.053, -0.053, 0.155, 0.086, -0.115,
            0.154, 0.002, 0.016, 0.254, 0, 0.011, 0.257, 0.08, -0.049, 0.148,
            0, -0.051, 0.206, -0.05, -0.08, 0.26, -0.007, 0.036, 0.161,
            -0.047, 0.031, 0.246, 0.019, -0.065, 0.115, -0.097, -0.089,
            0.151, -0.042, -0.016, 0.254, 0.017, -0.018, 0.228, 0.022,
            -0.141, 0.291, -0.034, -0.003, 0.27, 0.108, 0.08, 0.235, 0.026,
            -0.061, 0.253, 0.113, -0.128, 0.216, 0, 0.017, 0.172, -0.021,
            -0.029, 0.327, -0.033, -0.048, 0.242, 0.104, 0.038, 0.152, 0.097,
            0.029, 0.273, 0.096, -0.011, 0.279, 0.093, -0.116, 0.09, 0.073,
            -0.014, 0.151, 0.159, 0.051, 0.164, 0.06, -0.027, 0.138, 0.056,
            0.056, 0.189, -0.061, 0.034, 0.199, 0.057, 0.025, 0.084, -0.056,
            -0.056, 0.115, -0.022, 0.085, 0.116, -0.045, 0.023, 0.066, 0.007,
            -0.084, 0.015, 0.005, 0.07, 0.002, 0.081, 0.027, 0.179, 0.045,
            -0.065, 0.048, 0.083, 0.005, 0.01, 0.026, 0.078, -0.053, 0.01,
            -0.087, 0.035, -0.027, 0.026, 0.029, 0.082, 0.03, -0.026, 0.01,
            -0.049, -0.022, 0.008, 0.05, -0.019, 0.105, -0.119, -0.055,
            0.071, 0.005, 0.022, 0.049, -0.04, -0.021, 0.027, 0.095, -0.018,
            -0.017, -0.005, -0.09, 0.155, -0.03, -0.045, 0.014, 0, -0.021,
            0.061, -0.045, -0.169, 0.097, -0.161, -0.121, 0.033, -0.13,
            -0.044, 0.078, -0.04, -0.133, 0.057, -0.003, -0.083, 0.035,
            -0.115, -0.105, -0.02, -0.159, -0.167, -0.147, -0.108, -0.039,
            -0.056, -0.089, -0.15, 0.063, -0.047, -0.113, -0.034, -0.093,
            0.034, -0.018, -0.093, 0.035, 0.024, -0.034, -0.038, 0.078,
            -0.119, -0.009, -0.036, -0.018, -0.057, 0.018, -0.006, 0.001,
            0.061, -0.096, -0.022, -0.07, -0.102, 0.022, 0.054, -0.112, 0.04,
            -0.104, -0.098, 0.052, 0.044, -0.04, 0.03, 0.113, -0.127, 0.01,
            0.06, -0.065, -0.061, 0.025, -0.052, -0.017, 0.083, -0.051, 0,
            0.061, 0.008, 0.041, -0.053, -0.003, -0.119, 0.029, -0.037,
            -0.02, -0.102, 0.042, -0.084, 0.064, -0.076, -0.061, -0.019,
            0.017, -0.062, -0.082, -0.036, -0.07, -0.016, 0.033, -0.101,
            0.002, -0.041, 0.011, 0.026, -0.125, 0.1, -0.012, 0.004, 0,
            -0.043, -0.013, 0.065, 0.007, 0.043, -0.009, -0.022, 0.004,
            0.019, -0.064, 0.138, -0.057, 0.022, 0.003, 0.064, -0.054, 0.009,
            0.077, -0.037, 0.015, 0.106, 0.024, -0.047, 0.069, -0.143,
            -0.016, 0.162, -0.087, -0.085, 0.079, -0.134, -0.073, 0.075,
            -0.077, -0.085, 0.043, -0.108, -0.08, 0.11, -0.095, -0.103,
            0.022, -0.11, -0.002, -0.008, -0.204, -0.062, 0.03, -0.107,
            -0.061, -0.034, 0.084, -0.159, 0.067, 0.031, -0.062, 0.057,
            -0.08, -0.109, 0.095, -0.091, -0.105, 0.023, -0.092, -0.136,
            0.18, -0.115, -0.101, 0.111, 0.038, -0.1, 0.081, 0.016, -0.096,
            0.134, -0.057, -0.041, 0.068, -0.028, -0.111, 0.144, -0.1, 0.056,
            0.15, -0.076, -0.084, 0.095, -0.015, -0.148, -0.004, -0.051,
            0.013, 0.063, -0.018, -0.068, 0.087, -0.009, -0.027, -0.02,
            -0.08, 0.016, -0.034, -0.085, 0.14, 0.086, 0.03, 0.014, -0.034,
            -0.02, -0.064, -0.115, -0.088, 0.019, -0.035, -0.052, 0.098,
            0.059, -0.04, 0.019, -0.062, 0.032, -0.082, -0.048, -0.016,
            0.095, -0.005, -0.041, 0.001, -0.027, -0.117, 0.065, -0.097,
            -0.024, -0.06, 0.013, 0.012, 0.059, -0.069, 0.04, 0.067, -0.06,
            -0.083, 0.019, -0.168, -0.076, -0.005, 0.045, 0.012, 0.044,
            -0.046, 0.034, 0.021, -0.06, 0.088, -0.011, -0.125, 0.001,
            -0.006, -0.088, 0.004, 0.011, -0.081, 0.034, 0.003, 0.078, 0.071,
            0.02, -0.021, -0.083, -0.039, -0.088, 0.042, -0.021, -0.105,
            -0.005, -0.026, -0.067, -0.035, -0.043, -0.001, -0.027, -0.014,
            -0.106, -0.133, 0.047, 0.018, -0.098, -0.054, 0.009, -0.1,
            -0.058, -0.005, -0.074, -0.064, 0.037, 0.001, 0.016, -0.05,
            -0.017, -0.058, 0.002, -0.18, -0.044, -0.051, -0.148, -0.019,
            -0.22, -0.193, -0.055, -0.038, -0.091, -0.037, -0.005, -0.053,
            -0.046, -0.154, -0.104, -0.012, -0.135, -0.14, -0.087, -0.171,
            -0.144, -0.035, 0.047, -0.221, -0.003, -0.068, -0.09, -0.042,
            -0.072, -0.067, 0.041, -0.085, -0.129, -0.008, -0.049, -0.088,
            0.015, 0.013, -0.116, 0.054, 0.042, -0.203, 0.06, -0.083, -0.116,
            -0.03, 0.004, -0.165, 0.09, -0.027, -0.051, 0.051, 0.031, -0.071,
            -0.004, -0.007, -0.167, -0.113, 0.004, -0.102, -0.023, -0.058,
            -0.165, -0.019, 0.051, -0.219, 0.06, 0.049, -0.121, 0.059,
            -0.016, -0.199, 0.024, -0.056, -0.159, 0.065, 0.018, -0.047,
            0.03, 0.029, -0.027, 0.075, -0.069, -0.1, 0.046, -0.048, -0.052,
            0.151, 0.001, -0.055, 0.069, 0.029, -0.041, 0.172, 0.035, -0.099,
            0.19, -0.043, -0.017, 0.101, 0.037, 0.031, 0.163, 0.017, -0.077,
            0.033, -0.08, -0.088, 0.15, -0.012, -0.066, 0.145, -0.058,
            -0.037, 0.058, 0.094, -0.164, 0.006, 0.091, -0.114, -0.015,
            -0.026, -0.032, -0.048, -0.01, -0.162, -0.043, 0.13, -0.089,
            -0.02, 0.063, -0.107, -0.018, 0.018, -0.136, 0.041, 0.1, -0.139,
            -0.002, 0.02, -0.171, -0.042, 0.104
        ), dim = c(3, 84, 4))
        expect_equal(d[["v"]], v)
    })
}

test_that("three RDI reading methods (from, to, by not given)", {
    # https://github.com/dankelley/oce/issues/1557
    adp1 <- read.oce(system.file("extdata", "adp_rdi.000", package = "oce"))
    adp2 <- read.adp(system.file("extdata", "adp_rdi.000", package = "oce"))
    adp3 <- read.adp.rdi(system.file("extdata", "adp_rdi.000", package = "oce"))
    # Do arrays match?
    for (item in c("v", "a", "g", "q")) {
        expect_equal(dim(adp1[[item]]), c(9, 84, 4))
        expect_equal(adp1[[item]], adp2[[item]])
        expect_equal(adp1[[item]], adp3[[item]])
    }
})

test_that("three RDI reading methods (from given)", {
    # https://github.com/dankelley/oce/issues/1557
    adp1 <- read.oce(system.file("extdata", "adp_rdi.000", package = "oce"), from = 2)
    adp2 <- read.adp(system.file("extdata", "adp_rdi.000", package = "oce"), from = 2)
    adp3 <- read.adp.rdi(system.file("extdata", "adp_rdi.000", package = "oce"), from = 2)
    # Do arrays match?
    for (item in c("v", "a", "g", "q")) {
        expect_equal(dim(adp1[[item]]), c(8, 84, 4))
        expect_equal(adp1[[item]], adp2[[item]])
        expect_equal(adp1[[item]], adp3[[item]])
    }
})

test_that("three RDI reading methods (from and by given)", {
    # https://github.com/dankelley/oce/issues/1557
    adp1 <- read.oce(system.file("extdata", "adp_rdi.000", package = "oce"), from = 2, by = 2)
    adp2 <- read.adp(system.file("extdata", "adp_rdi.000", package = "oce"), from = 2, by = 2)
    adp3 <- read.adp.rdi(system.file("extdata", "adp_rdi.000", package = "oce"), from = 2, by = 2)
    # Do arrays match?
    for (item in c("v", "a", "g", "q")) {
        expect_equal(dim(adp1[[item]]), c(4, 84, 4))
        expect_equal(adp1[[item]], adp2[[item]])
        expect_equal(adp1[[item]], adp3[[item]])
    }
})

test_that("three RDI reading methods (from, by and to given)", {
    # https://github.com/dankelley/oce/issues/1557
    adp1 <- read.oce(system.file("extdata", "adp_rdi.000", package = "oce"), from = 2, by = 2, to = 4)
    adp2 <- read.adp(system.file("extdata", "adp_rdi.000", package = "oce"), from = 2, by = 2, to = 4)
    adp3 <- read.adp.rdi(system.file("extdata", "adp_rdi.000", package = "oce"), from = 2, by = 2, to = 4)
    # Do arrays match?
    for (item in c("v", "a", "g", "q")) {
        expect_equal(dim(adp1[[item]]), c(2, 84, 4))
        expect_equal(adp1[[item]], adp2[[item]])
        expect_equal(adp1[[item]], adp3[[item]])
    }
})

test_that("subset by time", {
    tmean <- mean(adp[["time"]])
    n <- sum(adp[["time"]] < tmean)
    earlyTime <- subset(adp, time < tmean)
    expect_equal(length(earlyTime[["orientation"]]), n)
    expect_equal(length(earlyTime[["ensembleNumber"]]), n)
    expect_equal(dim(earlyTime[["v"]])[1], n)
})

test_that("subset by ensembleNumber", {
    en <- adp[["ensembleNumber"]]
    n <- 10
    firstTen <- subset(adp, ensembleNumber < en[n + 1])
    expect_equal(length(firstTen[["orientation"]]), n)
    expect_equal(length(firstTen[["ensembleNumber"]]), n)
    expect_equal(dim(firstTen[["v"]])[1], n)
})

test_that("adpConvertRawToNumeric", {
    expect_equal(class(adp[["a"]][, , 1][, 1][1]), "raw")
    ADP <- adpConvertRawToNumeric(adp)
    expect_equal(class(ADP[["a"]][, , 1][, 1][1]), "numeric")
})