test_that("Testing texture generation", {
    data_dir <- system.file("extdata/raster/mod13q1", package = "sits")
    # Create a MODIS cube
    cube <- sits_cube(
        source = "BDC",
        collection = "MOD13Q1-6.1",
        data_dir = data_dir,
        progress = FALSE
    )
    feature <- sits_select(cube, bands = "NDVI", dates = "2013-09-14")
    dir_images <- paste0(tempdir(), "/images/")
    if (!dir.exists(dir_images)) {
        suppressWarnings(dir.create(dir_images))
    }
    unlink(list.files(dir_images,
        pattern = "\\.tif$",
        full.names = TRUE
    ))
    # Compute the NDVI variance
    class(feature) <- "data.frame"
    texture <- sits_texture(
        cube = feature,
        NDVIVAR = glcm_variance(NDVI),
        window_size = 5,
        multicores = 1,
        output_dir = dir_images
    )
    expect_true(all(sits_bands(texture) %in% c("NDVI", "NDVIVAR")))

    # Compute the NDVI mean
    texture <- sits_texture(
        cube = feature,
        NDVIMEAN = glcm_mean(NDVI),
        window_size = 5,
        multicores = 1,
        output_dir = dir_images
    )
    expect_true(all(sits_bands(texture) %in% c("NDVI", "NDVIMEAN")))

    # Compute the NDVI contrast
    texture <- sits_texture(
        cube = feature,
        NDVICONTRAST = glcm_contrast(NDVI),
        window_size = 5,
        multicores = 1,
        output_dir = dir_images
    )
    expect_true(all(sits_bands(texture) %in% c("NDVI", "NDVICONTRAST")))

    # Compute the NDVI dissimilarity
    texture <- sits_texture(
        cube = feature,
        NDVIDISSIMILARITY = glcm_dissimilarity(NDVI),
        window_size = 5,
        multicores = 1,
        output_dir = dir_images
    )
    expect_true(all(sits_bands(texture) %in% c("NDVI", "NDVIDISSIMILARITY")))

    # Compute the NDVI homogeneity
    texture <- sits_texture(
        cube = feature,
        NDVIHOMOGEINEITY = glcm_homogeneity(NDVI),
        window_size = 5,
        multicores = 1,
        output_dir = dir_images
    )
    expect_true(all(sits_bands(texture) %in% c("NDVI", "NDVIHOMOGEINEITY")))

    # Compute the NDVI energy
    texture <- sits_texture(
        cube = feature,
        NDVIENERGY = glcm_energy(NDVI),
        window_size = 5,
        multicores = 1,
        output_dir = dir_images
    )
    expect_true(all(sits_bands(texture) %in% c("NDVI", "NDVIENERGY")))

    # Compute the NDVI asm
    texture <- sits_texture(
        cube = feature,
        NDVIASM = glcm_asm(NDVI),
        window_size = 5,
        multicores = 1,
        output_dir = dir_images
    )
    expect_true(all(sits_bands(texture) %in% c("NDVI", "NDVIASM")))

    # Compute the NDVI std
    texture <- sits_texture(
        cube = feature,
        NDVISTD = glcm_std(NDVI),
        window_size = 5,
        multicores = 1,
        output_dir = dir_images
    )
    expect_true(all(sits_bands(texture) %in% c("NDVI", "NDVISTD")))

    # Compute the NDVI correlation
    texture <- sits_texture(
        cube = feature,
        NDVICORRELATION = glcm_correlation(NDVI),
        window_size = 5,
        multicores = 1,
        output_dir = dir_images
    )
    expect_true(all(sits_bands(texture) %in% c("NDVI", "NDVICORRELATION")))

    unlink(dir_images, recursive = TRUE)
})