Nothing
tests/testthat/test-mztia.R
In disprofas: Non-Parametric Dissolution Profile Analysis
context("Dissolution Profile Tolerance Intervals")
# The tests use the values published in the SAS/QC(R) 13.1: User's Guide,
# Chapter 5 (The Capability Procedure), details on pp 421-424. The data set is
# described on page 199: The fluid weights of 100 drink cans are measured in
# ounces. The filling process is assumed to be in statistical control. The
# measurements are saved in a SAS data set named Cans. The tolerance intervals
# calculated by the capability procedure are presented on page 416 in
# Figure 5.25. The data are put into a data frame so that the can be used for
# analysis by the mztia function.
test_that("mztia_succeeds_CAPABILITY", {
m_alpha_P <- matrix(c(rep(c(0.01, 0.05, 0.1), each = 3),
1 - rep(c(0.1, 0.05, 0.01), times = 3)),
ncol = 2, byrow = FALSE)
ll <-
apply(m_alpha_P, MARGIN = 1, FUN = function(x)
mztia(data = dip5, shape = "long", tcol = 1, grouping = "type",
reference = "reference", response = "weight", alpha = x[1],
P = x[2], cap = FALSE, bounds = c(0, 100), QS = c(5, 15))
[["Data"]][102, "weight"])
ul <-
apply(m_alpha_P, MARGIN = 1, FUN = function(x)
mztia(data = dip5, shape = "long", tcol = 1, grouping = "type",
reference = "reference", response = "weight", alpha = x[1],
P = x[2], cap = FALSE, bounds = c(0, 100), QS = c(5, 15))
[["Data"]][103, "weight"])
# <-><-><-><->
expect_equal(signif(ll, 4), c(11.92, 11.90, 11.86, 11.92, 11.90, 11.87,
11.92, 11.91, 11.88))
expect_equal(signif(ul, 4), c(12.10, 12.12, 12.15, 12.10, 12.11, 12.15,
12.09, 12.11, 12.14))
# Results presented in SAS/QC(R) 13.1: User's Guide, Chapter 5 (The
# CAPABILITY procedure), sub-chapter INTERVALS statement: CAPABILITY
# procedure
# Figure 5.25 Statistical Intervals for Weight (pp. 415-417)
# Approximate Tolerance Interval Containing At Least Proportion p of the
# Population (p. 416)
# Confidence P Tolerance Limits
# 99.00% 0.900 11.92 12.10
# 99.00% 0.950 11.90 12.12
# 99.00% 0.990 11.86 12.15
# 95.00% 0.900 11.92 12.10
# 95.00% 0.950 11.90 12.11
# 95.00% 0.990 11.87 12.15
# 90.00% 0.900 11.92 12.09
# 90.00% 0.950 11.91 12.11
# 90.00% 0.990 11.88 12.14
})
test_that("mztia_succeeds_with_df_shape_long", {
tmp <-
mztia(data = dip5, shape = "long", tcol = 1, grouping = "type",
reference = "reference", response = "weight", alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15))[["Data"]]
# <-><-><-><->
expect_equal(signif(tmp[101, "weight"], 9), 12.0093000)
expect_equal(signif(tmp[102, "weight"], 9), 11.8715203)
expect_equal(signif(tmp[103, "weight"], 9), 12.1470797)
expect_equal(signif(tmp[104, "weight"], 9), 6.871520286)
expect_equal(signif(tmp[105, "weight"], 9), 17.1470797)
expect_equal(signif(tmp[106, "weight"], 9), -3.1284797)
expect_equal(signif(tmp[107, "weight"], 9), 27.1470797)
})
test_that("mztia_succeeds_with_df_shape_wide", {
tmp1 <- mztia(data = dip1, shape = "wide", tcol = 3:10, grouping = "type",
reference = "R", response = NULL, alpha = 0.05, P = 0.99,
cap = FALSE, bounds = c(0, 100), QS = c(5, 15))[["Data"]]
tmp2 <- mztia(data = dip1, shape = "wide", tcol = 3:10, grouping = "type",
reference = "R", response = NULL, alpha = 0.05, P = 0.99,
cap = TRUE, bounds = c(0, 100), QS = c(5, 15))[["Data"]]
# <-><-><-><->
expect_equal(
signif(tmp1[tmp1$type1 == "Mean" & tmp1$type2 == "Mean", "response"], 9),
c(46.7716667, 60.1333333, 67.2750000, 71.9866667, 78.0700000,
84.8166667, 89.0933333, 91.4383333))
expect_equal(
signif(tmp1[tmp1$type1 == "TL" & tmp1$type2 == "LTL", "response"], 9),
c(27.2264050, 46.1548274, 56.9041726, 65.4435423, 69.5425900, 77.2027513,
76.2458801, 80.2932086))
expect_equal(
signif(tmp1[tmp1$type1 == "TL" & tmp1$type2 == "UTL", "response"], 9),
c(66.3169283, 74.1118393, 77.6458274, 78.5297910, 86.5974100, 92.4305820,
101.940787, 102.583458))
expect_equal(
signif(tmp1[tmp1$type1 == "TL.S1" & tmp1$type2 == "LTL", "response"], 9),
c(22.2264050, 41.1548274, 51.9041726, 60.4435423, 64.5425900, 72.2027513,
71.2458801, 75.2932086))
expect_equal(
signif(tmp1[tmp1$type1 == "TL.S1" & tmp1$type2 == "UTL", "response"], 9),
c(71.3169283, 79.1118393, 82.6458274, 83.5297910, 91.5974100, 97.4305820,
106.940787, 107.583458))
expect_equal(
signif(tmp1[tmp1$type1 == "TL.S2" & tmp1$type2 == "LTL", "response"], 9),
c(12.2264050, 31.1548274, 41.9041726, 50.4435423, 54.5425900, 62.2027513,
61.2458801, 65.2932086))
expect_equal(
signif(tmp1[tmp1$type1 == "TL.S2" & tmp1$type2 == "UTL", "response"], 9),
c(81.3169283, 89.1118393, 92.6458274, 93.5297910, 101.5974100, 107.430582,
116.940787, 117.583458))
expect_equal(
signif(tmp2[tmp2$type1 == "TL" & tmp2$type2 == "UTL", "response"], 9),
c(66.3169283, 74.1118393, 77.6458274, 78.5297910, 86.5974100, 92.4305820,
100.000000, 100.000000))
expect_equal(
signif(tmp2[tmp2$type1 == "TL.S1" & tmp2$type2 == "UTL", "response"], 9),
c(71.3169283, 79.1118393, 82.6458274, 83.5297910, 91.5974100, 97.4305820,
105.000000, 105.000000))
expect_equal(
signif(tmp2[tmp2$type1 == "TL.S2" & tmp2$type2 == "UTL", "response"], 9),
c(81.3169283, 89.1118393, 92.6458274, 93.5297910, 101.5974100, 107.430582,
115.000000, 115.000000))
})
test_that("mztia_fails", {
tmp0 <- dip1
tmp0$t.5 <- as.factor(tmp0$t.5)
tmp1 <- dip1
tmp1$type <- as.character(tmp1$type)
# <-><-><->
expect_error(
mztia(data = as.matrix(dip1[, 3:10]), shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"data must be provided as data frame")
expect_error(
mztia(data = dip1, shape = 1, tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"shape must be a string")
expect_error(
mztia(data = dip1, shape = "weit", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"specify shape")
expect_error(
mztia(data = dip1, shape = "wide", tcol = "tico",
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"tcol must be an integer")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10 + 0.1,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"tcol must be an integer")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 7:11,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"Some columns specified by tcol were not found")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 7,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"Did you provide a data frame")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 2:6,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"Some names of columns specified by tcol")
expect_error(
mztia(data = tmp0, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"Some columns specified by tcol are not numeric")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = 5, reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"grouping must be a string")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "lot", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"grouping variable was not found")
expect_error(
mztia(data = tmp1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"grouping variable's column in data")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = 1, response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"reference must be a string")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "REF", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"The reference variable was not found")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "type", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"The reference variable was not found")
expect_error(
mztia(data = dip5, shape = "long", tcol = 3, grouping = "type",
reference = "reference", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"data frame provided via data is in long format"
)
expect_error(
mztia(data = dip5, shape = "long", tcol = 3, grouping = "type",
reference = "reference", response = 5, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"response must be a string of length 1"
)
expect_error(
mztia(data = dip5, shape = "long", tcol = 3, grouping = "type",
reference = "reference", response = c("type", "batch"), alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"response must be a string of length 1"
)
expect_error(
mztia(data = dip5, shape = "long", tcol = 3, grouping = "type",
reference = "reference", response = "assay", alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"response variable was not found"
)
expect_error(
mztia(data = dip5, shape = "long", tcol = 3, grouping = "type",
reference = "reference", response = "type", alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"column specified by response is not numeric"
)
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = -1,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"specify alpha")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 9,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"specify alpha")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = -1, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"specify P")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 9, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"specify P")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = 0, bounds = c(0, 100), QS = c(5, 15)),
"cap must be a logical")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c("l", "u"), QS = c(5, 15)),
"bounds must be a numeric vector")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(5, 50, 90), QS = c(5, 15)),
"bounds must be a numeric vector")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(100, 0), QS = c(5, 15)),
"specify bounds in the form")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c("l", "u")),
"QS must be a numeric vector")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15, 30)),
"QS must be a numeric vector")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(-5, 15)),
"specify QS in the range")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 105)),
"specify QS in the range")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(15, 5)),
"Q S1 must be smaller Q S2")
})
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context("Dissolution Profile Tolerance Intervals")
# The tests use the values published in the SAS/QC(R) 13.1: User's Guide,
# Chapter 5 (The Capability Procedure), details on pp 421-424. The data set is
# described on page 199: The fluid weights of 100 drink cans are measured in
# ounces. The filling process is assumed to be in statistical control. The
# measurements are saved in a SAS data set named Cans. The tolerance intervals
# calculated by the capability procedure are presented on page 416 in
# Figure 5.25. The data are put into a data frame so that the can be used for
# analysis by the mztia function.
test_that("mztia_succeeds_CAPABILITY", {
m_alpha_P <- matrix(c(rep(c(0.01, 0.05, 0.1), each = 3),
1 - rep(c(0.1, 0.05, 0.01), times = 3)),
ncol = 2, byrow = FALSE)
ll <-
apply(m_alpha_P, MARGIN = 1, FUN = function(x)
mztia(data = dip5, shape = "long", tcol = 1, grouping = "type",
reference = "reference", response = "weight", alpha = x[1],
P = x[2], cap = FALSE, bounds = c(0, 100), QS = c(5, 15))
[["Data"]][102, "weight"])
ul <-
apply(m_alpha_P, MARGIN = 1, FUN = function(x)
mztia(data = dip5, shape = "long", tcol = 1, grouping = "type",
reference = "reference", response = "weight", alpha = x[1],
P = x[2], cap = FALSE, bounds = c(0, 100), QS = c(5, 15))
[["Data"]][103, "weight"])
# <-><-><-><->
expect_equal(signif(ll, 4), c(11.92, 11.90, 11.86, 11.92, 11.90, 11.87,
11.92, 11.91, 11.88))
expect_equal(signif(ul, 4), c(12.10, 12.12, 12.15, 12.10, 12.11, 12.15,
12.09, 12.11, 12.14))
# Results presented in SAS/QC(R) 13.1: User's Guide, Chapter 5 (The
# CAPABILITY procedure), sub-chapter INTERVALS statement: CAPABILITY
# procedure
# Figure 5.25 Statistical Intervals for Weight (pp. 415-417)
# Approximate Tolerance Interval Containing At Least Proportion p of the
# Population (p. 416)
# Confidence P Tolerance Limits
# 99.00% 0.900 11.92 12.10
# 99.00% 0.950 11.90 12.12
# 99.00% 0.990 11.86 12.15
# 95.00% 0.900 11.92 12.10
# 95.00% 0.950 11.90 12.11
# 95.00% 0.990 11.87 12.15
# 90.00% 0.900 11.92 12.09
# 90.00% 0.950 11.91 12.11
# 90.00% 0.990 11.88 12.14
})
test_that("mztia_succeeds_with_df_shape_long", {
tmp <-
mztia(data = dip5, shape = "long", tcol = 1, grouping = "type",
reference = "reference", response = "weight", alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15))[["Data"]]
# <-><-><-><->
expect_equal(signif(tmp[101, "weight"], 9), 12.0093000)
expect_equal(signif(tmp[102, "weight"], 9), 11.8715203)
expect_equal(signif(tmp[103, "weight"], 9), 12.1470797)
expect_equal(signif(tmp[104, "weight"], 9), 6.871520286)
expect_equal(signif(tmp[105, "weight"], 9), 17.1470797)
expect_equal(signif(tmp[106, "weight"], 9), -3.1284797)
expect_equal(signif(tmp[107, "weight"], 9), 27.1470797)
})
test_that("mztia_succeeds_with_df_shape_wide", {
tmp1 <- mztia(data = dip1, shape = "wide", tcol = 3:10, grouping = "type",
reference = "R", response = NULL, alpha = 0.05, P = 0.99,
cap = FALSE, bounds = c(0, 100), QS = c(5, 15))[["Data"]]
tmp2 <- mztia(data = dip1, shape = "wide", tcol = 3:10, grouping = "type",
reference = "R", response = NULL, alpha = 0.05, P = 0.99,
cap = TRUE, bounds = c(0, 100), QS = c(5, 15))[["Data"]]
# <-><-><-><->
expect_equal(
signif(tmp1[tmp1$type1 == "Mean" & tmp1$type2 == "Mean", "response"], 9),
c(46.7716667, 60.1333333, 67.2750000, 71.9866667, 78.0700000,
84.8166667, 89.0933333, 91.4383333))
expect_equal(
signif(tmp1[tmp1$type1 == "TL" & tmp1$type2 == "LTL", "response"], 9),
c(27.2264050, 46.1548274, 56.9041726, 65.4435423, 69.5425900, 77.2027513,
76.2458801, 80.2932086))
expect_equal(
signif(tmp1[tmp1$type1 == "TL" & tmp1$type2 == "UTL", "response"], 9),
c(66.3169283, 74.1118393, 77.6458274, 78.5297910, 86.5974100, 92.4305820,
101.940787, 102.583458))
expect_equal(
signif(tmp1[tmp1$type1 == "TL.S1" & tmp1$type2 == "LTL", "response"], 9),
c(22.2264050, 41.1548274, 51.9041726, 60.4435423, 64.5425900, 72.2027513,
71.2458801, 75.2932086))
expect_equal(
signif(tmp1[tmp1$type1 == "TL.S1" & tmp1$type2 == "UTL", "response"], 9),
c(71.3169283, 79.1118393, 82.6458274, 83.5297910, 91.5974100, 97.4305820,
106.940787, 107.583458))
expect_equal(
signif(tmp1[tmp1$type1 == "TL.S2" & tmp1$type2 == "LTL", "response"], 9),
c(12.2264050, 31.1548274, 41.9041726, 50.4435423, 54.5425900, 62.2027513,
61.2458801, 65.2932086))
expect_equal(
signif(tmp1[tmp1$type1 == "TL.S2" & tmp1$type2 == "UTL", "response"], 9),
c(81.3169283, 89.1118393, 92.6458274, 93.5297910, 101.5974100, 107.430582,
116.940787, 117.583458))
expect_equal(
signif(tmp2[tmp2$type1 == "TL" & tmp2$type2 == "UTL", "response"], 9),
c(66.3169283, 74.1118393, 77.6458274, 78.5297910, 86.5974100, 92.4305820,
100.000000, 100.000000))
expect_equal(
signif(tmp2[tmp2$type1 == "TL.S1" & tmp2$type2 == "UTL", "response"], 9),
c(71.3169283, 79.1118393, 82.6458274, 83.5297910, 91.5974100, 97.4305820,
105.000000, 105.000000))
expect_equal(
signif(tmp2[tmp2$type1 == "TL.S2" & tmp2$type2 == "UTL", "response"], 9),
c(81.3169283, 89.1118393, 92.6458274, 93.5297910, 101.5974100, 107.430582,
115.000000, 115.000000))
})
test_that("mztia_fails", {
tmp0 <- dip1
tmp0$t.5 <- as.factor(tmp0$t.5)
tmp1 <- dip1
tmp1$type <- as.character(tmp1$type)
# <-><-><->
expect_error(
mztia(data = as.matrix(dip1[, 3:10]), shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"data must be provided as data frame")
expect_error(
mztia(data = dip1, shape = 1, tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"shape must be a string")
expect_error(
mztia(data = dip1, shape = "weit", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"specify shape")
expect_error(
mztia(data = dip1, shape = "wide", tcol = "tico",
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"tcol must be an integer")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10 + 0.1,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"tcol must be an integer")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 7:11,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"Some columns specified by tcol were not found")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 7,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"Did you provide a data frame")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 2:6,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"Some names of columns specified by tcol")
expect_error(
mztia(data = tmp0, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"Some columns specified by tcol are not numeric")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = 5, reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"grouping must be a string")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "lot", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"grouping variable was not found")
expect_error(
mztia(data = tmp1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"grouping variable's column in data")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = 1, response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"reference must be a string")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "REF", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"The reference variable was not found")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "type", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"The reference variable was not found")
expect_error(
mztia(data = dip5, shape = "long", tcol = 3, grouping = "type",
reference = "reference", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"data frame provided via data is in long format"
)
expect_error(
mztia(data = dip5, shape = "long", tcol = 3, grouping = "type",
reference = "reference", response = 5, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"response must be a string of length 1"
)
expect_error(
mztia(data = dip5, shape = "long", tcol = 3, grouping = "type",
reference = "reference", response = c("type", "batch"), alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"response must be a string of length 1"
)
expect_error(
mztia(data = dip5, shape = "long", tcol = 3, grouping = "type",
reference = "reference", response = "assay", alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"response variable was not found"
)
expect_error(
mztia(data = dip5, shape = "long", tcol = 3, grouping = "type",
reference = "reference", response = "type", alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"column specified by response is not numeric"
)
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = -1,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"specify alpha")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 9,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"specify alpha")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = -1, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"specify P")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 9, cap = FALSE, bounds = c(0, 100), QS = c(5, 15)),
"specify P")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = 0, bounds = c(0, 100), QS = c(5, 15)),
"cap must be a logical")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c("l", "u"), QS = c(5, 15)),
"bounds must be a numeric vector")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(5, 50, 90), QS = c(5, 15)),
"bounds must be a numeric vector")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(100, 0), QS = c(5, 15)),
"specify bounds in the form")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c("l", "u")),
"QS must be a numeric vector")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 15, 30)),
"QS must be a numeric vector")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(-5, 15)),
"specify QS in the range")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(5, 105)),
"specify QS in the range")
expect_error(
mztia(data = dip1, shape = "wide", tcol = 3:10,
grouping = "type", reference = "R", response = NULL, alpha = 0.05,
P = 0.99, cap = FALSE, bounds = c(0, 100), QS = c(15, 5)),
"Q S1 must be smaller Q S2")
})
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