tests/testthat/test-modules-print.R
In kaz-yos/tableone: Create 'Table 1' to Describe Baseline Characteristics with or without Propensity Score Weights
################################################################################
### Define behaviors of formatters for printing
##
## Created on: 2020-07-22
## Author: Kazuki Yoshida
################################################################################
library(testthat)
set.seed(384452428)
###
### Describe formatters that are common to all variables
################################################################################
describe("ModuleFormatNumericVector", {
it("creates a character vector from numeric", {
eg_num <- rnorm(n = 1000, sd = 10000)
expect_true(is.character(ModuleFormatNumericVector(x = eg_num,
digits = 1)))
})
it("aligns numbers vertically with appropriate digits", {
eg_num <- c(1480.61787738437,
4110.08315419201,
0,
-2072.69756465216,
-679.687900350949,
-4313.08599182373,
-8542.3392630109,
-7823.95523336236,
-21234.6667893914,
-274.448648953072,
-186.40513038433,
NA,
NaN,
Inf)
## Decimal alignment example. Copied and edited below.
c(" 1480.61787738437",
" 4110.08315419201",
" 0",
" -2072.69756465216",
" -679.687900350949",
" -4313.08599182373",
" -8542.3392630109",
" -7823.95523336236",
"-21234.6667893914",
" -274.448648953072",
" -186.40513038433",
" NA",
" NaN",
" Inf")
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 0),
c(" 1481",
" 4110",
" 0",
" -2073",
" -680",
" -4313",
" -8542",
" -7824",
"-21235",
" -274",
" -186",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 1),
c(" 1480.6",
" 4110.1",
" 0.0",
" -2072.7",
" -679.7",
" -4313.1",
" -8542.3",
" -7824.0",
"-21234.7",
" -274.4",
" -186.4",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 2),
c(" 1480.62",
" 4110.08",
" 0.00",
" -2072.70",
" -679.69",
" -4313.09",
" -8542.34",
" -7823.96",
"-21234.67",
" -274.45",
" -186.41",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 3),
c(" 1480.618",
" 4110.083",
" 0.000",
" -2072.698",
" -679.688",
" -4313.086",
" -8542.339",
" -7823.955",
"-21234.667",
" -274.449",
" -186.405",
" NA",
" NaN",
" Inf"))
})
it("uses decimal.mark and big.mark when specified", {
eg_num <- c(1480.61787738437,
4110.08315419201,
0,
-2072.69756465216,
-679.687900350949,
-4313.08599182373,
-8542.3392630109,
-7823.95523336236,
-21234.6667893914,
-274.448648953072,
-186.40513038433,
NA,
NaN,
Inf)
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 0,
formatOptions = list(decimal.mark = "_",
big.mark = ",")),
c(" 1,481",
" 4,110",
" 0",
" -2,073",
" -680",
" -4,313",
" -8,542",
" -7,824",
"-21,235",
" -274",
" -186",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 1,
formatOptions = list(decimal.mark = "_",
big.mark = ",")),
c(" 1,480_6",
" 4,110_1",
" 0_0",
" -2,072_7",
" -679_7",
" -4,313_1",
" -8,542_3",
" -7,824_0",
"-21,234_7",
" -274_4",
" -186_4",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 2,
formatOptions = list(decimal.mark = "_",
big.mark = ",")),
c(" 1,480_62",
" 4,110_08",
" 0_00",
" -2,072_70",
" -679_69",
" -4,313_09",
" -8,542_34",
" -7,823_96",
"-21,234_67",
" -274_45",
" -186_41",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 3,
formatOptions = list(decimal.mark = "_",
big.mark = ",")),
c(" 1,480_618",
" 4,110_083",
" 0_000",
" -2,072_698",
" -679_688",
" -4,313_086",
" -8,542_339",
" -7,823_955",
"-21,234_667",
" -274_449",
" -186_405",
" NA",
" NaN",
" Inf"))
})
})
describe("ModuleFormatPercents (for missing percentage)", {
it("creates a character vector from numeric", {
eg_perc <- c(0, runif(n = 1000, min = 0, max = 1), 1) * 100
expect_true(is.character(ModuleFormatPercents(percents = eg_perc,
digits = 1)))
})
it("aligns numbers vertically with appropriate digits", {
eg_perc <- as.double(c(0, 1.1111, 100, NA, NaN, Inf))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 0),
c(" 0",
" 1",
"100",
" NA",
"NaN",
"Inf"))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 1),
c(" 0.0",
" 1.1",
"100.0",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 2),
c(" 0.00",
" 1.11",
"100.00",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 3),
c(" 0.000",
" 1.111",
"100.000",
" NA",
" NaN",
" Inf"))
})
it("uses decimal.mark when specified", {
eg_perc <- as.double(c(0, 1.1111, 100, NA, NaN, Inf))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 1),
c(" 0.0",
" 1.1",
"100.0",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 1,
formatOptions = list(decimal.mark = "-")),
c(" 0-0",
" 1-1",
"100-0",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 1,
formatOptions = list(decimal.mark = "D")),
c(" 0D0",
" 1D1",
"100D0",
" NA",
" NaN",
" Inf"))
})
})
describe("ModuleFormatPValues", {
example_p_values <- c(0, runif(n = 1000, min = 0, max = 1), 1)
it("creates a character vector", {
expect_true(is.character(ModuleFormatPValues(pValues = example_p_values,
pDigits = 2)))
})
it("creates <0.01 etc given 0", {
eg_p <- as.double(0)
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 1),
"<0.1")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 2),
"<0.01")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 3),
"<0.001")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 4),
"<0.0001")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 5),
"<0.00001")
})
it("returns character version for what pDigits permits, otherwise gives <0.01 etc", {
eg_p <- as.double(0.0011)
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 1),
"<0.1")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 2),
"<0.01")
## Leading space when there is no <
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 3),
" 0.001")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 4),
" 0.0011")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 5),
" 0.00110")
})
it("alignes output vertically", {
## Note that for rounding off a 5, the IEC 60559 standard (see also
## ‘IEEE 754’) is expected to be used, ‘_go to the even digit_’.
## Therefore ‘round(0.5)’ is ‘0’ and ‘round(-1.5)’ is ‘-2’. However,
## this is dependent on OS services and on representation error
## (since e.g. ‘0.15’ is not represented exactly, the rounding rule
## applies to the represented number and not to the printed number,
## and so ‘round(0.15, 1)’ could be either ‘0.1’ or ‘0.2’).
eg_p <- as.double(c(0, 0.1111111, 0.15, 0.94, 0.9999, 1, NA, NaN))
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 1),
c("<0.1",
" 0.1",
" 0.1", # round(0.15, 1) => 0.1 in R 4.0.2 on macOS 10.15.5.
" 0.9",
" 1.0",
" 1.0",
" NA",
" NaN"))
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 2),
c("<0.01",
" 0.11",
" 0.15",
" 0.94",
" 1.00",
" 1.00",
" NA",
" NaN"))
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 3),
c("<0.001",
" 0.111",
" 0.150",
" 0.940",
" 1.000",
" 1.000",
" NA",
" NaN"))
})
it("uses decimal.mark when specified", {
eg_p <- as.double(c(0, 0.1111111, 0.15, 0.94, 0.9999, 1, NA, NaN))
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 2),
c("<0.01",
" 0.11",
" 0.15",
" 0.94",
" 1.00",
" 1.00",
" NA",
" NaN"))
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 2,
formatOption = list(decimal.mark = "-")),
c("<0-01",
" 0-11",
" 0-15",
" 0-94",
" 1-00",
" 1-00",
" NA",
" NaN"))
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 2,
formatOption = list(decimal.mark = "D")),
c("<0D01",
" 0D11",
" 0D15",
" 0D94",
" 1D00",
" 1D00",
" NA",
" NaN"))
})
})
###
### Describe formatters for continuous variables
################################################################################
describe("ModuleConvertNormal", {
## Taken from pbc$alk.phos in survival
eg_min <- 289.000
eg_p25 <- 871.500
eg_median <- 1259.000
eg_mean <- 1982.656
eg_p75 <- 1980.000
eg_max <- 13862.400
eg_sd <- 2140.389
## The function receives a single row matrix of summary statistics
## from ModuleContFormatStrata.
eg_mat <- matrix(c(eg_mean, eg_sd),
ncol = 2,
byrow = TRUE,
dimnames = list(NULL,
c("mean", "sd")))
it("returns a data frame with two columns", {
expect_true(is.data.frame(ModuleConvertNormal(eg_mat,
digits = 1)))
expect_equal(ncol(ModuleConvertNormal(eg_mat,
digits = 1)),
2)
})
it("returns a column of numeric mean and a formatted column of character (SD)", {
## Column names must be generic (col1, col2).
## Both mean (SD) and median [IQR] are stacked up together.
expect_equal(ModuleConvertNormal(eg_mat,
digits = 0),
data.frame(col1 = eg_mean,
col2 = " (2140)"))
expect_equal(ModuleConvertNormal(eg_mat,
digits = 1),
data.frame(col1 = eg_mean,
col2 = " (2140.4)"))
expect_equal(ModuleConvertNormal(eg_mat,
digits = 2),
data.frame(col1 = eg_mean,
col2 = " (2140.39)"))
expect_equal(ModuleConvertNormal(eg_mat,
digits = 3),
data.frame(col1 = eg_mean,
col2 = " (2140.389)"))
})
it("respects formatOptions", {
expect_equal(ModuleConvertNormal(eg_mat,
digits = 0,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_mean,
col2 = " (2,140)"))
expect_equal(ModuleConvertNormal(eg_mat,
digits = 1,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_mean,
col2 = " (2,140D4)"))
expect_equal(ModuleConvertNormal(eg_mat,
digits = 2,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_mean,
col2 = " (2,140D39)"))
expect_equal(ModuleConvertNormal(eg_mat,
digits = 3,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_mean,
col2 = " (2,140D389)"))
})
})
describe("ModuleConvertNonNormal", {
## Taken from pbc$alk.phos in survival
eg_min <- 289.000
eg_p25 <- 871.500
eg_median <- 1259.000
eg_mean <- 1982.656
eg_p75 <- 1980.000
eg_max <- 13862.400
eg_sd <- 2140.389
## The function receives a single row matrix of summary statistics
## from ModuleContFormatStrata.
eg_mat <- matrix(c(eg_median, eg_p25, eg_p75, eg_min, eg_max),
ncol = 5,
byrow = TRUE,
dimnames = list(NULL,
c("median", "p25", "p75", "min", "max")))
it("returns a data frame with two columns", {
expect_true(is.data.frame(ModuleConvertNonNormal(eg_mat,
digits = 1)))
expect_equal(ncol(ModuleConvertNonNormal(eg_mat,
digits = 1)),
2)
})
it("returns a column of numeric mean and a formatted column of character (SD)", {
## Column names must be generic (col1, col2).
## Both mean (SD) and median [IQR] are stacked up together.
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 0),
data.frame(col1 = eg_median,
col2 = " [872, 1980]"))
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 1),
data.frame(col1 = eg_median,
col2 = " [871.5, 1980.0]"))
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 2),
data.frame(col1 = eg_median,
col2 = " [871.50, 1980.00]"))
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 3),
data.frame(col1 = eg_median,
col2 = " [871.500, 1980.000]"))
})
it("respects formatOptions", {
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 0,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_median,
col2 = " [872, 1,980]"))
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 1,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_median,
col2 = " [871D5, 1,980D0]"))
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 2,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_median,
col2 = " [871D50, 1,980D00]"))
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 3,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_median,
col2 = " [871D500, 1,980D000]"))
})
})
###
### Describe formatters for categorical variables
################################################################################
describe("ModuleCatFormatVariables", {
## It receives a list of data frames named lstVars.
## Example below:
## lstVars
## $status
## n miss p.miss level freq percent cum.percent
## 1 418 0 0 0 232 55.502392 55.50239
## 2 418 0 0 1 25 5.980861 61.48325
## 3 418 0 0 2 161 38.516746 100.00000
##
## $trt
## n miss p.miss level freq percent cum.percent
## 1 418 106 25.35885 1 158 50.64103 50.64103
## 2 418 106 25.35885 2 154 49.35897 100.00000
})
kaz-yos/tableone documentation built on April 20, 2022, 12:16 p.m.
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################################################################################
### Define behaviors of formatters for printing
##
## Created on: 2020-07-22
## Author: Kazuki Yoshida
################################################################################
library(testthat)
set.seed(384452428)
###
### Describe formatters that are common to all variables
################################################################################
describe("ModuleFormatNumericVector", {
it("creates a character vector from numeric", {
eg_num <- rnorm(n = 1000, sd = 10000)
expect_true(is.character(ModuleFormatNumericVector(x = eg_num,
digits = 1)))
})
it("aligns numbers vertically with appropriate digits", {
eg_num <- c(1480.61787738437,
4110.08315419201,
0,
-2072.69756465216,
-679.687900350949,
-4313.08599182373,
-8542.3392630109,
-7823.95523336236,
-21234.6667893914,
-274.448648953072,
-186.40513038433,
NA,
NaN,
Inf)
## Decimal alignment example. Copied and edited below.
c(" 1480.61787738437",
" 4110.08315419201",
" 0",
" -2072.69756465216",
" -679.687900350949",
" -4313.08599182373",
" -8542.3392630109",
" -7823.95523336236",
"-21234.6667893914",
" -274.448648953072",
" -186.40513038433",
" NA",
" NaN",
" Inf")
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 0),
c(" 1481",
" 4110",
" 0",
" -2073",
" -680",
" -4313",
" -8542",
" -7824",
"-21235",
" -274",
" -186",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 1),
c(" 1480.6",
" 4110.1",
" 0.0",
" -2072.7",
" -679.7",
" -4313.1",
" -8542.3",
" -7824.0",
"-21234.7",
" -274.4",
" -186.4",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 2),
c(" 1480.62",
" 4110.08",
" 0.00",
" -2072.70",
" -679.69",
" -4313.09",
" -8542.34",
" -7823.96",
"-21234.67",
" -274.45",
" -186.41",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 3),
c(" 1480.618",
" 4110.083",
" 0.000",
" -2072.698",
" -679.688",
" -4313.086",
" -8542.339",
" -7823.955",
"-21234.667",
" -274.449",
" -186.405",
" NA",
" NaN",
" Inf"))
})
it("uses decimal.mark and big.mark when specified", {
eg_num <- c(1480.61787738437,
4110.08315419201,
0,
-2072.69756465216,
-679.687900350949,
-4313.08599182373,
-8542.3392630109,
-7823.95523336236,
-21234.6667893914,
-274.448648953072,
-186.40513038433,
NA,
NaN,
Inf)
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 0,
formatOptions = list(decimal.mark = "_",
big.mark = ",")),
c(" 1,481",
" 4,110",
" 0",
" -2,073",
" -680",
" -4,313",
" -8,542",
" -7,824",
"-21,235",
" -274",
" -186",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 1,
formatOptions = list(decimal.mark = "_",
big.mark = ",")),
c(" 1,480_6",
" 4,110_1",
" 0_0",
" -2,072_7",
" -679_7",
" -4,313_1",
" -8,542_3",
" -7,824_0",
"-21,234_7",
" -274_4",
" -186_4",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 2,
formatOptions = list(decimal.mark = "_",
big.mark = ",")),
c(" 1,480_62",
" 4,110_08",
" 0_00",
" -2,072_70",
" -679_69",
" -4,313_09",
" -8,542_34",
" -7,823_96",
"-21,234_67",
" -274_45",
" -186_41",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatNumericVector(x = eg_num,
digits = 3,
formatOptions = list(decimal.mark = "_",
big.mark = ",")),
c(" 1,480_618",
" 4,110_083",
" 0_000",
" -2,072_698",
" -679_688",
" -4,313_086",
" -8,542_339",
" -7,823_955",
"-21,234_667",
" -274_449",
" -186_405",
" NA",
" NaN",
" Inf"))
})
})
describe("ModuleFormatPercents (for missing percentage)", {
it("creates a character vector from numeric", {
eg_perc <- c(0, runif(n = 1000, min = 0, max = 1), 1) * 100
expect_true(is.character(ModuleFormatPercents(percents = eg_perc,
digits = 1)))
})
it("aligns numbers vertically with appropriate digits", {
eg_perc <- as.double(c(0, 1.1111, 100, NA, NaN, Inf))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 0),
c(" 0",
" 1",
"100",
" NA",
"NaN",
"Inf"))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 1),
c(" 0.0",
" 1.1",
"100.0",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 2),
c(" 0.00",
" 1.11",
"100.00",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 3),
c(" 0.000",
" 1.111",
"100.000",
" NA",
" NaN",
" Inf"))
})
it("uses decimal.mark when specified", {
eg_perc <- as.double(c(0, 1.1111, 100, NA, NaN, Inf))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 1),
c(" 0.0",
" 1.1",
"100.0",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 1,
formatOptions = list(decimal.mark = "-")),
c(" 0-0",
" 1-1",
"100-0",
" NA",
" NaN",
" Inf"))
expect_equal(ModuleFormatPercents(percents = eg_perc,
digits = 1,
formatOptions = list(decimal.mark = "D")),
c(" 0D0",
" 1D1",
"100D0",
" NA",
" NaN",
" Inf"))
})
})
describe("ModuleFormatPValues", {
example_p_values <- c(0, runif(n = 1000, min = 0, max = 1), 1)
it("creates a character vector", {
expect_true(is.character(ModuleFormatPValues(pValues = example_p_values,
pDigits = 2)))
})
it("creates <0.01 etc given 0", {
eg_p <- as.double(0)
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 1),
"<0.1")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 2),
"<0.01")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 3),
"<0.001")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 4),
"<0.0001")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 5),
"<0.00001")
})
it("returns character version for what pDigits permits, otherwise gives <0.01 etc", {
eg_p <- as.double(0.0011)
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 1),
"<0.1")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 2),
"<0.01")
## Leading space when there is no <
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 3),
" 0.001")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 4),
" 0.0011")
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 5),
" 0.00110")
})
it("alignes output vertically", {
## Note that for rounding off a 5, the IEC 60559 standard (see also
## ‘IEEE 754’) is expected to be used, ‘_go to the even digit_’.
## Therefore ‘round(0.5)’ is ‘0’ and ‘round(-1.5)’ is ‘-2’. However,
## this is dependent on OS services and on representation error
## (since e.g. ‘0.15’ is not represented exactly, the rounding rule
## applies to the represented number and not to the printed number,
## and so ‘round(0.15, 1)’ could be either ‘0.1’ or ‘0.2’).
eg_p <- as.double(c(0, 0.1111111, 0.15, 0.94, 0.9999, 1, NA, NaN))
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 1),
c("<0.1",
" 0.1",
" 0.1", # round(0.15, 1) => 0.1 in R 4.0.2 on macOS 10.15.5.
" 0.9",
" 1.0",
" 1.0",
" NA",
" NaN"))
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 2),
c("<0.01",
" 0.11",
" 0.15",
" 0.94",
" 1.00",
" 1.00",
" NA",
" NaN"))
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 3),
c("<0.001",
" 0.111",
" 0.150",
" 0.940",
" 1.000",
" 1.000",
" NA",
" NaN"))
})
it("uses decimal.mark when specified", {
eg_p <- as.double(c(0, 0.1111111, 0.15, 0.94, 0.9999, 1, NA, NaN))
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 2),
c("<0.01",
" 0.11",
" 0.15",
" 0.94",
" 1.00",
" 1.00",
" NA",
" NaN"))
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 2,
formatOption = list(decimal.mark = "-")),
c("<0-01",
" 0-11",
" 0-15",
" 0-94",
" 1-00",
" 1-00",
" NA",
" NaN"))
expect_equal(ModuleFormatPValues(pValues = eg_p,
pDigits = 2,
formatOption = list(decimal.mark = "D")),
c("<0D01",
" 0D11",
" 0D15",
" 0D94",
" 1D00",
" 1D00",
" NA",
" NaN"))
})
})
###
### Describe formatters for continuous variables
################################################################################
describe("ModuleConvertNormal", {
## Taken from pbc$alk.phos in survival
eg_min <- 289.000
eg_p25 <- 871.500
eg_median <- 1259.000
eg_mean <- 1982.656
eg_p75 <- 1980.000
eg_max <- 13862.400
eg_sd <- 2140.389
## The function receives a single row matrix of summary statistics
## from ModuleContFormatStrata.
eg_mat <- matrix(c(eg_mean, eg_sd),
ncol = 2,
byrow = TRUE,
dimnames = list(NULL,
c("mean", "sd")))
it("returns a data frame with two columns", {
expect_true(is.data.frame(ModuleConvertNormal(eg_mat,
digits = 1)))
expect_equal(ncol(ModuleConvertNormal(eg_mat,
digits = 1)),
2)
})
it("returns a column of numeric mean and a formatted column of character (SD)", {
## Column names must be generic (col1, col2).
## Both mean (SD) and median [IQR] are stacked up together.
expect_equal(ModuleConvertNormal(eg_mat,
digits = 0),
data.frame(col1 = eg_mean,
col2 = " (2140)"))
expect_equal(ModuleConvertNormal(eg_mat,
digits = 1),
data.frame(col1 = eg_mean,
col2 = " (2140.4)"))
expect_equal(ModuleConvertNormal(eg_mat,
digits = 2),
data.frame(col1 = eg_mean,
col2 = " (2140.39)"))
expect_equal(ModuleConvertNormal(eg_mat,
digits = 3),
data.frame(col1 = eg_mean,
col2 = " (2140.389)"))
})
it("respects formatOptions", {
expect_equal(ModuleConvertNormal(eg_mat,
digits = 0,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_mean,
col2 = " (2,140)"))
expect_equal(ModuleConvertNormal(eg_mat,
digits = 1,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_mean,
col2 = " (2,140D4)"))
expect_equal(ModuleConvertNormal(eg_mat,
digits = 2,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_mean,
col2 = " (2,140D39)"))
expect_equal(ModuleConvertNormal(eg_mat,
digits = 3,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_mean,
col2 = " (2,140D389)"))
})
})
describe("ModuleConvertNonNormal", {
## Taken from pbc$alk.phos in survival
eg_min <- 289.000
eg_p25 <- 871.500
eg_median <- 1259.000
eg_mean <- 1982.656
eg_p75 <- 1980.000
eg_max <- 13862.400
eg_sd <- 2140.389
## The function receives a single row matrix of summary statistics
## from ModuleContFormatStrata.
eg_mat <- matrix(c(eg_median, eg_p25, eg_p75, eg_min, eg_max),
ncol = 5,
byrow = TRUE,
dimnames = list(NULL,
c("median", "p25", "p75", "min", "max")))
it("returns a data frame with two columns", {
expect_true(is.data.frame(ModuleConvertNonNormal(eg_mat,
digits = 1)))
expect_equal(ncol(ModuleConvertNonNormal(eg_mat,
digits = 1)),
2)
})
it("returns a column of numeric mean and a formatted column of character (SD)", {
## Column names must be generic (col1, col2).
## Both mean (SD) and median [IQR] are stacked up together.
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 0),
data.frame(col1 = eg_median,
col2 = " [872, 1980]"))
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 1),
data.frame(col1 = eg_median,
col2 = " [871.5, 1980.0]"))
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 2),
data.frame(col1 = eg_median,
col2 = " [871.50, 1980.00]"))
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 3),
data.frame(col1 = eg_median,
col2 = " [871.500, 1980.000]"))
})
it("respects formatOptions", {
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 0,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_median,
col2 = " [872, 1,980]"))
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 1,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_median,
col2 = " [871D5, 1,980D0]"))
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 2,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_median,
col2 = " [871D50, 1,980D00]"))
expect_equal(ModuleConvertNonNormal(eg_mat,
digits = 3,
formatOptions = list(big.mark = ",", decimal.mark = "D")),
data.frame(col1 = eg_median,
col2 = " [871D500, 1,980D000]"))
})
})
###
### Describe formatters for categorical variables
################################################################################
describe("ModuleCatFormatVariables", {
## It receives a list of data frames named lstVars.
## Example below:
## lstVars
## $status
## n miss p.miss level freq percent cum.percent
## 1 418 0 0 0 232 55.502392 55.50239
## 2 418 0 0 1 25 5.980861 61.48325
## 3 418 0 0 2 161 38.516746 100.00000
##
## $trt
## n miss p.miss level freq percent cum.percent
## 1 418 106 25.35885 1 158 50.64103 50.64103
## 2 418 106 25.35885 2 154 49.35897 100.00000
})
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