diff options
author | Johannes Ranke <jranke@uni-bremen.de> | 2018-07-05 18:44:22 +0200 |
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committer | Johannes Ranke <jranke@uni-bremen.de> | 2018-07-05 18:44:22 +0200 |
commit | 9411139beee167c5339e96db448e5dbed19e06bc (patch) | |
tree | 1bba625b3a2288c1ede4eefe1c23d3bcfa0f9fcc /tests/testthat | |
parent | 801e95f1cc7bfcc8480f6f49b9da2331be71d1a9 (diff) |
Maintenance in preparation of improvements
- Switch vignette to html
- Switch tests to testthat
- NEWS.md instead of ChangeLog
- Remove names of y in lists returned by lod and loq
Diffstat (limited to 'tests/testthat')
-rw-r--r-- | tests/testthat/test_din32645.R | 33 | ||||
-rw-r--r-- | tests/testthat/test_inverse.predict.R | 43 | ||||
-rw-r--r-- | tests/testthat/test_lod_loq.R | 28 | ||||
-rw-r--r-- | tests/testthat/test_massart.R | 40 |
4 files changed, 144 insertions, 0 deletions
diff --git a/tests/testthat/test_din32645.R b/tests/testthat/test_din32645.R new file mode 100644 index 0000000..e6d2840 --- /dev/null +++ b/tests/testthat/test_din32645.R @@ -0,0 +1,33 @@ +context("Known results for the dataset provided in DIN 32645") + +require(chemCal) + +m <- lm(y ~ x, data = din32645) +prediction <- inverse.predict(m, 3500, alpha = 0.01) + +test_that("We get correct confidence intervals", { + # Result collected from Procontrol 3.1 (isomehr GmbH) + expect_equal(round(prediction$Confidence, 5), 0.07434) +}) + +test_that("We get a correct critical value", { + crit <- lod(m, alpha = 0.01, beta = 0.5) + # DIN 32645 gives 0.07 for the critical value + # (decision limit, "Nachweisgrenze") + expect_equal(round(crit$x, 2), 0.07) + # According to Dintest test data, we should get 0.0698 + expect_equal(round(crit$x, 4), 0.0698) +}) + +test_that("We get a correct smalles detectable value using the DIN method", { + lod.din <- lod(m, alpha = 0.01, beta = 0.01, method = "din") + # DIN 32645 gives 0.14 for the smallest detectable value ("Erfassungsgrenze") + expect_equal(round(lod.din$x, 2), 0.14) +}) + +test_that("We get a correct limit of quantification", { + loq.din <- loq(m, alpha = 0.01) + # The value cited for Procontrol 3.1 (0.2121) deviates + # at the last digit, so we only test for three digits + expect_equal(round(loq.din$x, 3), 0.212) +}) diff --git a/tests/testthat/test_inverse.predict.R b/tests/testthat/test_inverse.predict.R new file mode 100644 index 0000000..61484dc --- /dev/null +++ b/tests/testthat/test_inverse.predict.R @@ -0,0 +1,43 @@ +context("Inverse predictions") + +library(chemCal) + +test_that("Inverse predictions for unweighted regressions are stable", { + m1 <- lm(y ~ x, data = massart97ex1) + + # Known values from chemcal Version 0.1-37 + p1.1 <- inverse.predict(m1, 15) + expect_equal(signif(p1.1$Prediction, 7), 6.09381) + expect_equal(signif(p1.1$`Standard Error`, 7), 1.767278) + expect_equal(signif(p1.1$Confidence, 7), 4.906751) + + p1.2 <- inverse.predict(m1, 90) + expect_equal(signif(p1.2$Prediction, 7), 43.93983) + expect_equal(signif(p1.2$`Standard Error`, 7), 1.767747) + expect_equal(signif(p1.2$Confidence, 7), 4.908053) + + p1.3 <- inverse.predict(m1, rep(90, 5)) + expect_equal(signif(p1.3$Prediction, 7), 43.93983) + expect_equal(signif(p1.3$`Standard Error`, 7), 1.141204) + expect_equal(signif(p1.3$Confidence, 7), 3.168489) +}) + +test_that("Inverse predictions for weighted regressions are stable", { + attach(massart97ex3) + yx <- split(y, x) + ybar <- sapply(yx, mean) + s <- round(sapply(yx, sd), digits = 2) + w <- round(1 / (s^2), digits = 3) + weights <- w[factor(x)] + m3 <- lm(y ~ x, w = weights) + + p3.1 <- inverse.predict(m3, 15, ws = 1.67) + expect_equal(signif(p3.1$Prediction, 7), 5.865367) + expect_equal(signif(p3.1$`Standard Error`, 7), 0.8926109) + expect_equal(signif(p3.1$Confidence, 7), 2.478285) + + p3.2 <- inverse.predict(m3, 90, ws = 0.145) + expect_equal(signif(p3.2$Prediction, 7), 44.06025) + expect_equal(signif(p3.2$`Standard Error`, 7), 2.829162) + expect_equal(signif(p3.2$Confidence, 7), 7.855012) +}) diff --git a/tests/testthat/test_lod_loq.R b/tests/testthat/test_lod_loq.R new file mode 100644 index 0000000..6ba0ad0 --- /dev/null +++ b/tests/testthat/test_lod_loq.R @@ -0,0 +1,28 @@ +context("LOD and LOQ") + +library(chemCal) + +test_that("lod is stable across chemCal versions", { + m <- lm(y ~ x, data = din32645) + lod_1 <- lod(m) + expect_equal(signif(lod_1$x, 7), 0.08655484) + expect_equal(signif(lod_1$y, 7), 3317.154) + + # Critical value (decision limit, Nachweisgrenze) + lod_2 <- lod(m, alpha = 0.01, beta = 0.5) + expect_equal(signif(lod_2$x, 7), 0.0698127) + expect_equal(signif(lod_2$y, 7), 3155.393) +}) + +test_that("loq is stable across chemCal versions", { + m2 <- lm(y ~ x, data = massart97ex3) + loq_1 <- loq(m2) + expect_equal(signif(loq_1$x, 7), 13.97764) + expect_equal(signif(loq_1$y, 7), 30.6235) + + loq_2 <- loq(m2, n = 3) + expect_equal(signif(loq_2$x, 7), 9.971963) + expect_equal(signif(loq_2$y, 7), 22.68539) +}) + + diff --git a/tests/testthat/test_massart.R b/tests/testthat/test_massart.R new file mode 100644 index 0000000..791c2e7 --- /dev/null +++ b/tests/testthat/test_massart.R @@ -0,0 +1,40 @@ +context("Known results for the example datasets provided by Massart (1997)") + +require(chemCal) + +test_that("Inverse predictions for example 1 are correct",{ + m1 <- lm(y ~ x, data = massart97ex1) + + # Known values are from the book + p1.1 <- inverse.predict(m1, 15) + expect_equal(round(p1.1$Prediction, 1), 6.1) + expect_equal(round(p1.1$Confidence, 1), 4.9) + + p1.2 <- inverse.predict(m1, 90) + expect_equal(round(p1.2$Prediction, 1), 43.9) + expect_equal(round(p1.2$Confidence, 1), 4.9) + + p1.3 <- inverse.predict(m1, rep(90, 5)) + expect_equal(round(p1.3$Prediction, 1), 43.9) + expect_equal(round(p1.3$Confidence, 1), 3.2) +}) + + +test_that("Inverse predictions for example 3 are correct",{ + attach(massart97ex3) + yx <- split(y, x) + ybar <- sapply(yx, mean) + s <- round(sapply(yx, sd), digits = 2) + w <- round(1 / (s^2), digits = 3) + weights <- w[factor(x)] + m3 <- lm(y ~ x, w = weights) + + # Known values are from the book + p3.1 <- inverse.predict(m3, 15, ws = 1.67) + expect_equal(round(p3.1$Prediction, 1), 5.9) + expect_equal(round(p3.1$Confidence, 1), 2.5) + + p3.2 <- inverse.predict(m3, 90, ws = 0.145) + expect_equal(round(p3.2$Prediction, 1), 44.1) + expect_equal(round(p3.2$Confidence, 1), 7.9) +}) |