Nothing
# Create temp dir for testthat
tmp <- file.path(tempdir(), "OpenSpecy-testthat")
dir.create(tmp, showWarnings = F)
test_that("Raman batch analysis with test library", {
skip_on_cran()
skip_if_offline(host = "api.osf.io")
batch <- read_extdata("testdata_zipped.zip") |> read_any() |>
expect_silent()
is_OpenSpecy(batch) |> expect_true()
plot(batch) |> expect_silent()
plotly_spec(batch) |> expect_silent()
expect_true(check_OpenSpecy(batch))
get_lib(type = "test", path = tmp) |> expect_no_error()
check_lib(type = "test", path = tmp) |> expect_silent()
lib <- load_lib(type = "test", path = tmp) |> expect_silent()
filter_spec(lib, lib$metadata$SpectrumType == "Raman") |> expect_silent()
batch2 <- conform_spec(batch, lib$wavenumber, res = spec_res(lib$wavenumber)) |>
expect_silent()
expect_true(check_OpenSpecy(batch2))
plotly_spec(batch2) |> expect_silent()
sig_noise(batch2, metric = "run_sig_over_noise") |>
expect_silent()
batch3 <- process_spec(batch2, subtr_baseline = T) |> expect_silent()
plotly_spec(x = batch3, x2 = batch) |> expect_silent()
expect_true(check_OpenSpecy(batch3))
matches <- cor_spec(batch3, library = lib) |> expect_silent()
test_max_cor <- max_cor_named(matches) |> expect_silent()
sig_noise(batch3, metric = "run_sig_over_noise") |>
expect_silent()
})
test_that("Raman batch analysis with complete library", {
skip_on_cran()
skip_if_offline(host = "api.osf.io")
skip_if_not(testthat:::on_ci(), "Not on CI")
batch <- read_extdata(file = "testdata_zipped.zip") |> read_any() |>
expect_silent()
is_OpenSpecy(batch) |> expect_true()
plot(batch) |> expect_silent()
plotly_spec(batch) |> expect_silent()
get_lib(type = "nobaseline", path = tmp) |> expect_no_error()
check_lib(type = "nobaseline", path = tmp) |> expect_silent()
lib <- load_lib(type = "nobaseline", path = tmp) |> expect_silent()
filter_spec(lib, lib$metadata$SpectrumType == "Raman") |> expect_silent()
batch2 <- conform_spec(batch, range = lib$wavenumber,
res = spec_res(lib$wavenumber)) |>
expect_silent()
expect_true(check_OpenSpecy(batch2))
plotly_spec(batch2) |> expect_silent()
test_sn2 <- sig_noise(batch2, metric = "run_sig_over_noise") |>
expect_silent()
batch3 <- process_spec(batch2, subtr_baseline = T) |> expect_silent()
plotly_spec(x = batch3, x2 = batch) |> expect_silent()
expect_true(check_OpenSpecy(batch3))
matches <- cor_spec(batch3, library = lib) |> expect_silent()
test_max_cor <- max_cor_named(matches) |> expect_silent()
test_sn <- sig_noise(batch3, metric = "run_sig_over_noise") |>
expect_silent()
heatmap_spec(batch3, sn = test_sn, cor = test_max_cor, min_sn = 4,
min_cor = 0.7, select = 2, source = "heatplot") |>
expect_silent()
})
test_that("One particle is identified with standard workflow in map", {
skip_on_cran()
map <- read_extdata("CA_tiny_map.zip") |> read_any()
signal_noise <- sig_noise(map, metric = "sig_times_noise", abs = F)
id_map <- def_features(map,signal_noise > 0.01)
unique(id_map$metadata$feature_id) |> length() |> expect_equal(4)
test_collapsed <- collapse_spec(id_map)
test_collapsed$metadata |> nrow() |>
expect_equal(4)
test_collapsed$metadata$feret_max |> round(2) |>
expect_equal(c(NA, 8, 12.31, 4.00))
test_collapsed$metadata$centroid_x |> round(2) |>
expect_equal(c(7.87, 2.00, 7.9, 0.00))
})
# Tidy up
unlink(tmp, recursive = T)
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