Nothing
tests/testthat/testProbeSmoothing.r
In growthPheno: Functional Analysis of Phenotypic Growth Data to Smooth and Extract Traits
cat("#### Test probeSmoothing with Judith Atieno 0278\n")
test_that("chickpea_growthPheno", {
skip_if_not_installed("growthPheno")
skip_on_cran()
library(growthPheno)
library(ggplot2)
data(dat1)
#'## Values of df for which to obtain plots
df <- c(4,7)
#'## Obtain plots
testthat::expect_warning(t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
facet.x = "Treatment.1", facet.y = "Smarthouse",
which.plots=c("bothseparately"),
ggplotFuncs=list(scale_x_continuous(breaks=
seq(30, 50, by=2)))))
testthat::expect_equal(nrow(t), 8480)
testthat::expect_equal(ncol(t), 15)
testthat::expect_warning(
t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
trait.types=c("AGR"),
facet.x = "Treatment.1", facet.y = "Smarthouse"))
testthat::expect_equal(nrow(t), 8480)
testthat::expect_equal(ncol(t), 12)
testthat::expect_warning(
t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
trait.types=c("response"),
facet.x = "Treatment.1", facet.y = "Smarthouse",
which.plots="dfcompare", get.rates=FALSE))
testthat::expect_equal(nrow(t), 8480)
testthat::expect_true(all(c("Snapshot.ID.Tag", "Days", "TimeAfterPlanting", "ShootArea1000",
"Treatment.1", "Smarthouse", "ShootArea1000",
"ShootArea1000.smooth.Direct.4", "ShootArea1000.smooth.Direct.7")
%in% names(t)))
#include relative.boxplots
testthat::expect_warning(
t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
trait.types=c("response"),
facet.x = "Treatment.1", facet.y = "Smarthouse",
which.plots="dfcompare", deviations.plots = "relat",
get.rates=FALSE))
testthat::expect_equal(nrow(t), 8480)
testthat::expect_true(all(c("Snapshot.ID.Tag", "Days", "TimeAfterPlanting", "ShootArea1000",
"Treatment.1", "Smarthouse", "ShootArea1000",
"ShootArea1000.smooth.Direct.4", "ShootArea1000.smooth.Direct.7")
%in% names(t)))
#'## Include deviations boxplots
testthat::expect_error(t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
x.title = "DAP",
trait.types=c("response"), get.rates=FALSE,
which.plots="dfcompare",
deviations.boxplots = "absolute"))
#deviations.boxplots deprecated
testthat::expect_warning(
t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
x.title = "DAP",
trait.types=c("response"), get.rates=FALSE,
facet.x = "Treatment.1", facet.y = "Smarthouse",
which.plots="dfcompare",
deviations.plots = "absolute"))
testthat::expect_equal(nrow(t), 8480)
testthat::expect_true(all(c("Snapshot.ID.Tag", "Days", "TimeAfterPlanting", "ShootArea1000",
"Treatment.1", "Smarthouse", "ShootArea1000",
"ShootArea1000.smooth.Direct.4", "ShootArea1000.smooth.Direct.7")
%in% names(t)))
testthat::expect_warning(t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
x.title = "DAP",
trait.types=c("response", "AGR"),
facet.x = "Treatment.1", facet.y = "Smarthouse",
which.plots="methodscompare",
deviations.plots = c("absolute", "relative")))
testthat::expect_equal(nrow(t), 8480)
testthat::expect_true(all(c("Snapshot.ID.Tag", "Days", "TimeAfterPlanting", "ShootArea1000",
"Treatment.1", "Smarthouse", "ShootArea1000",
"Days.diffs", "ShootArea1000.AGR",
"ShootArea1000.smooth.Direct.4", "ShootArea1000.smooth.AGR.Direct.4",
"ShootArea1000.smooth.Direct.7",
"ShootArea1000.smooth.AGR.Direct.7")
%in% names(t)))
testthat::expect_lt(max(abs(t["ShootArea1000"] - t["ShootArea1000.smooth.Direct.4"]),
na.rm = TRUE) - 5.563407, 1e-07)
testthat::expect_lt(max(abs(t["ShootArea1000"] - t["ShootArea1000.smooth.Direct.4"])/
t["ShootArea1000.smooth.Direct.4"]) - 370.7951, 1e-04)
})
cat("#### Test probeSmoothing with small example\n")
test_that("exampleData_growthPheno", {
skip_if_not_installed("growthPheno")
skip_on_cran()
library(growthPheno)
data(exampleData)
vline <- list(ggplot2::geom_vline(xintercept=20, linetype="longdash", size=1),
ggplot2::scale_x_continuous(breaks=seq(12, 36, by=2)))
plotDeviationsBoxes(longi.dat, observed = "PSA", smoothed = "sPSA",
x.factor="DAP", facet.x = ".", facet.y= ".", df =5)
testthat::expect_warning(
tmp <- probeSmoothing(data = longi.dat, response = "PSA",
df = c(4,7), xname="xDAP", times.factor = "DAP",
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 15)
testthat::expect_warning(tmp <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4,7),
which.plots = "methodsc",
facet.y = ".",
get.rates = FALSE,
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 7)
testthat::expect_warning(tmp <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4,7),
which.plots = "dfcompare",
facet.y = ".",
get.rates = FALSE,
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 7)
testthat::expect_warning(tmp <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
which.plots = "dfcompare",
facet.y = ".",
alpha = 0.6, get.rates = FALSE,
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 9)
testthat::expect_warning(
tmp <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
which.plots = "dfcompare", facet.y = ".",
alpha = 0.5, trait.types = "AGR",
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 15)
testthat::expect_warning(tmp <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
facet.y = ".",
deviations.plots = "compare",
propn.types = c(0.025,0.2, 0.25),
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 20)
testthat::expect_warning(tmp <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
facet.x = ".", facet.y = ".",
which.plots = "none",
deviations.plots = "compare",
propn.types = NULL,
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 19)
testthat::expect_warning(
traits <- probeSmoothing(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
facet.x = ".", facet.y = ".",
which.plots = "none",
deviations.plots = "none",
propn.types = NULL))
testthat::expect_silent(med <- plotMedianDeviations(data = traits,
response = "PSA",
response.smoothed = "sPSA",
x="xDAP", xname = "xDAP",
df = c(4,7), x.title = "DAP",
facet.x = ".", facet.y = ".",
trait.types = "response",
propn.types = 0.05,
ggplotFuncsMedDevn = vline))
testthat::expect_equal(length(med), 2)
testthat::expect_true(all(names(med) == c("plots", "med.devn.dat")))
testthat::expect_equal(nrow(med$med.devn.dat), 28)
testthat::expect_equal(ncol(med$med.devn.dat), 6)
testthat::expect_equal(length(med$plots), 1)
testthat::expect_warning(traits <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
facet.x = ".", facet.y = ".",
which.plots = "none",
deviations.plots = c("compare",
"absolute"),
propn.types = NULL))
testthat::expect_equal(nrow(traits), 280)
testthat::expect_equal(ncol(traits), 19)
testthat::expect_warning(traits <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
facet.x = ".", facet.y = ".",
which.plots = "methodsc",
deviations.plots = c("compare",
"absolute"),
propn.types = NULL))
testthat::expect_equal(nrow(traits), 280)
testthat::expect_equal(ncol(traits), 19)
})
cat("#### Test probeSmoothing with tomato example\n")
test_that("tomato_growthPheno", {
skip_if_not_installed("growthPheno")
skip_on_cran()
library(dae)
library(growthPheno)
data(tomato.dat)
tomato.dat <- within(tomato.dat, xDAP <- as.numfac(DAP))
df.vec <- c(4:6,12)
labelMyc <- as_labeller(function(lev) paste(lev, "AMF"))
labelZn <- as_labeller(function(lev) paste("Zn:", lev, "ppm"))
#'## Gives error that the Length of propn.types is not the same as the number of traits
testthat::expect_warning(testthat::expect_error(
tmp <- probeSmoothing(data = tomato.dat,
response = "PSA", response.smoothed = "sPSA",
times.factor = "DAP", xname = "xDAP",
smoothing.methods = c("dir", "log"),
facet.x = "Zn", facet.y = "AMF",
df = c(4,7), x="xDAP", get.rates = FALSE,
which.plots = "methodsc",
deviations.plots = "compare",
labeller = labeller(Zn = labelZn,
AMF = labelMyc)),
regexp = "Length of propn.types is not the same as the number of trait.types"),
regexp = "get.rates is FALSE and so trait.types changed to response")
testthat::expect_warning(
tom <- probeSmoothing(data = tomato.dat,
response = "PSA",
response.smoothed = "sPSA",
times.factor = "DAP", xname = "xDAP",
smoothing.methods = c("dir", "log"),
facet.x = "Zn", facet.y = "AMF",
df = c(4,7), x="xDAP", get.rates = FALSE,
propn.types = 0.1,
which.plots = "methodsc",
deviations.plots = "compare",
labeller = labeller(Zn = labelZn,
AMF = labelMyc)),
regexp = "get.rates is FALSE and so trait.types changed to response")
testthat::expect_equal(nrow(tom), 1120)
testthat::expect_equal(ncol(tom), 10)
testthat::expect_silent(med <- plotMedianDeviations(data = tom,
response = "PSA",
response.smoothed = "sPSA",
xname = "xDAP",
smoothing.methods = c("dir", "log"),
df = c(4,7), x.title = "DAP",
y.titles = "PSA deviation (kpixels)",
facet.x = "Zn", facet.y = "AMF",
trait.types = "response",
propn.types = 0.1,
labeller = labeller(Zn = labelZn,
AMF = labelMyc)))
testthat::expect_equal(length(med$plots), 1)
testthat::expect_equal(nrow(med$med.devn.dat), 1120)
testthat::expect_equal(ncol(med$med.devn.dat), 8)
#Multiple df, single methods
testthat::expect_warning(tom <- probeSmoothing(data = tomato.dat, response = "PSA",
response.smoothed = "sPSA",
times.factor = "DAP", xname="xDAP", df=5:6,
smoothing.methods = c("logarithmic"),
facet.x = ".", facet.y = ".",
which.plots = "none",
propn.types = c(0.02, 0.2, 0.5),
deviations.plots = "compare.medians"))
testthat::expect_equal(nrow(tom), 1120)
testthat::expect_equal(ncol(tom), 13)
#'Single `df`, multiple methods and trait.types
testthat::expect_warning(tom <- probeSmoothing(data = tomato.dat, response = "PSA",
response.smoothed = "sPSA",
times.factor = "DAP", xname="xDAP", df=5,
smoothing.methods = c("direct","logarithmic"),
facet.x = ".", facet.y = ".",
which.plots = "none",
deviations.plots = "none"))
testthat::expect_equal(nrow(tom), 1120)
testthat::expect_equal(ncol(tom), 13)
testthat::expect_warning(med <- plotMedianDeviations(data = tom, response = "PSA",
response.smoothed = "sPSA",
xname = "xDAP",
smoothing.methods = c("dir", "log"),
df = 5, x.title = "DAP",
facet.x = ".", facet.y = ".",
propn.types = c(0.02, 0.2, 0.5)))
testthat::expect_equal(length(med), 2)
testthat::expect_true(all(names(med) == c("plots", "med.devn.dat")))
testthat::expect_equal(nrow(med$med.devn.dat), 70)
testthat::expect_equal(ncol(med$med.devn.dat), 8)
testthat::expect_equal(length(med$plots), 3)
testthat::expect_true(all(names(med$plots) == c("PSA","PSA.AGR","PSA.RGR")))
testthat::expect_warning(print(med$plots$PSA.AGR))
#'Single `df`, single method
testthat::expect_warning(tom <- probeSmoothing(data = tomato.dat, response = "PSA",
response.smoothed = "sPSA",
times.factor = "DAP", xname="xDAP", df=5,
smoothing.methods = c("direct"),
facet.x = ".", facet.y = ".",
which.plots = "none",
propn.types = c(0.02, 0.2, 0.5),
deviations.plots = "compare.medians"))
testthat::expect_equal(nrow(tom), 1120)
testthat::expect_equal(ncol(tom), 10)
})
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cat("#### Test probeSmoothing with Judith Atieno 0278\n")
test_that("chickpea_growthPheno", {
skip_if_not_installed("growthPheno")
skip_on_cran()
library(growthPheno)
library(ggplot2)
data(dat1)
#'## Values of df for which to obtain plots
df <- c(4,7)
#'## Obtain plots
testthat::expect_warning(t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
facet.x = "Treatment.1", facet.y = "Smarthouse",
which.plots=c("bothseparately"),
ggplotFuncs=list(scale_x_continuous(breaks=
seq(30, 50, by=2)))))
testthat::expect_equal(nrow(t), 8480)
testthat::expect_equal(ncol(t), 15)
testthat::expect_warning(
t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
trait.types=c("AGR"),
facet.x = "Treatment.1", facet.y = "Smarthouse"))
testthat::expect_equal(nrow(t), 8480)
testthat::expect_equal(ncol(t), 12)
testthat::expect_warning(
t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
trait.types=c("response"),
facet.x = "Treatment.1", facet.y = "Smarthouse",
which.plots="dfcompare", get.rates=FALSE))
testthat::expect_equal(nrow(t), 8480)
testthat::expect_true(all(c("Snapshot.ID.Tag", "Days", "TimeAfterPlanting", "ShootArea1000",
"Treatment.1", "Smarthouse", "ShootArea1000",
"ShootArea1000.smooth.Direct.4", "ShootArea1000.smooth.Direct.7")
%in% names(t)))
#include relative.boxplots
testthat::expect_warning(
t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
trait.types=c("response"),
facet.x = "Treatment.1", facet.y = "Smarthouse",
which.plots="dfcompare", deviations.plots = "relat",
get.rates=FALSE))
testthat::expect_equal(nrow(t), 8480)
testthat::expect_true(all(c("Snapshot.ID.Tag", "Days", "TimeAfterPlanting", "ShootArea1000",
"Treatment.1", "Smarthouse", "ShootArea1000",
"ShootArea1000.smooth.Direct.4", "ShootArea1000.smooth.Direct.7")
%in% names(t)))
#'## Include deviations boxplots
testthat::expect_error(t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
x.title = "DAP",
trait.types=c("response"), get.rates=FALSE,
which.plots="dfcompare",
deviations.boxplots = "absolute"))
#deviations.boxplots deprecated
testthat::expect_warning(
t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
x.title = "DAP",
trait.types=c("response"), get.rates=FALSE,
facet.x = "Treatment.1", facet.y = "Smarthouse",
which.plots="dfcompare",
deviations.plots = "absolute"))
testthat::expect_equal(nrow(t), 8480)
testthat::expect_true(all(c("Snapshot.ID.Tag", "Days", "TimeAfterPlanting", "ShootArea1000",
"Treatment.1", "Smarthouse", "ShootArea1000",
"ShootArea1000.smooth.Direct.4", "ShootArea1000.smooth.Direct.7")
%in% names(t)))
testthat::expect_warning(t <- probeSmoothing(dat1, df=df, xname="TimeAfterPlanting",
response="ShootArea1000",
x.title = "DAP",
trait.types=c("response", "AGR"),
facet.x = "Treatment.1", facet.y = "Smarthouse",
which.plots="methodscompare",
deviations.plots = c("absolute", "relative")))
testthat::expect_equal(nrow(t), 8480)
testthat::expect_true(all(c("Snapshot.ID.Tag", "Days", "TimeAfterPlanting", "ShootArea1000",
"Treatment.1", "Smarthouse", "ShootArea1000",
"Days.diffs", "ShootArea1000.AGR",
"ShootArea1000.smooth.Direct.4", "ShootArea1000.smooth.AGR.Direct.4",
"ShootArea1000.smooth.Direct.7",
"ShootArea1000.smooth.AGR.Direct.7")
%in% names(t)))
testthat::expect_lt(max(abs(t["ShootArea1000"] - t["ShootArea1000.smooth.Direct.4"]),
na.rm = TRUE) - 5.563407, 1e-07)
testthat::expect_lt(max(abs(t["ShootArea1000"] - t["ShootArea1000.smooth.Direct.4"])/
t["ShootArea1000.smooth.Direct.4"]) - 370.7951, 1e-04)
})
cat("#### Test probeSmoothing with small example\n")
test_that("exampleData_growthPheno", {
skip_if_not_installed("growthPheno")
skip_on_cran()
library(growthPheno)
data(exampleData)
vline <- list(ggplot2::geom_vline(xintercept=20, linetype="longdash", size=1),
ggplot2::scale_x_continuous(breaks=seq(12, 36, by=2)))
plotDeviationsBoxes(longi.dat, observed = "PSA", smoothed = "sPSA",
x.factor="DAP", facet.x = ".", facet.y= ".", df =5)
testthat::expect_warning(
tmp <- probeSmoothing(data = longi.dat, response = "PSA",
df = c(4,7), xname="xDAP", times.factor = "DAP",
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 15)
testthat::expect_warning(tmp <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4,7),
which.plots = "methodsc",
facet.y = ".",
get.rates = FALSE,
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 7)
testthat::expect_warning(tmp <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4,7),
which.plots = "dfcompare",
facet.y = ".",
get.rates = FALSE,
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 7)
testthat::expect_warning(tmp <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
which.plots = "dfcompare",
facet.y = ".",
alpha = 0.6, get.rates = FALSE,
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 9)
testthat::expect_warning(
tmp <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
which.plots = "dfcompare", facet.y = ".",
alpha = 0.5, trait.types = "AGR",
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 15)
testthat::expect_warning(tmp <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
facet.y = ".",
deviations.plots = "compare",
propn.types = c(0.025,0.2, 0.25),
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 20)
testthat::expect_warning(tmp <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
facet.x = ".", facet.y = ".",
which.plots = "none",
deviations.plots = "compare",
propn.types = NULL,
ggplotFuncs=vline))
testthat::expect_equal(nrow(tmp), 280)
testthat::expect_equal(ncol(tmp), 19)
testthat::expect_warning(
traits <- probeSmoothing(data = longi.dat,
response = "PSA", response.smoothed = "sPSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
facet.x = ".", facet.y = ".",
which.plots = "none",
deviations.plots = "none",
propn.types = NULL))
testthat::expect_silent(med <- plotMedianDeviations(data = traits,
response = "PSA",
response.smoothed = "sPSA",
x="xDAP", xname = "xDAP",
df = c(4,7), x.title = "DAP",
facet.x = ".", facet.y = ".",
trait.types = "response",
propn.types = 0.05,
ggplotFuncsMedDevn = vline))
testthat::expect_equal(length(med), 2)
testthat::expect_true(all(names(med) == c("plots", "med.devn.dat")))
testthat::expect_equal(nrow(med$med.devn.dat), 28)
testthat::expect_equal(ncol(med$med.devn.dat), 6)
testthat::expect_equal(length(med$plots), 1)
testthat::expect_warning(traits <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
facet.x = ".", facet.y = ".",
which.plots = "none",
deviations.plots = c("compare",
"absolute"),
propn.types = NULL))
testthat::expect_equal(nrow(traits), 280)
testthat::expect_equal(ncol(traits), 19)
testthat::expect_warning(traits <- probeSmoothing(data = longi.dat, response = "PSA",
xname = "xDAP", times.factor = "DAP",
df = c(4:7),
facet.x = ".", facet.y = ".",
which.plots = "methodsc",
deviations.plots = c("compare",
"absolute"),
propn.types = NULL))
testthat::expect_equal(nrow(traits), 280)
testthat::expect_equal(ncol(traits), 19)
})
cat("#### Test probeSmoothing with tomato example\n")
test_that("tomato_growthPheno", {
skip_if_not_installed("growthPheno")
skip_on_cran()
library(dae)
library(growthPheno)
data(tomato.dat)
tomato.dat <- within(tomato.dat, xDAP <- as.numfac(DAP))
df.vec <- c(4:6,12)
labelMyc <- as_labeller(function(lev) paste(lev, "AMF"))
labelZn <- as_labeller(function(lev) paste("Zn:", lev, "ppm"))
#'## Gives error that the Length of propn.types is not the same as the number of traits
testthat::expect_warning(testthat::expect_error(
tmp <- probeSmoothing(data = tomato.dat,
response = "PSA", response.smoothed = "sPSA",
times.factor = "DAP", xname = "xDAP",
smoothing.methods = c("dir", "log"),
facet.x = "Zn", facet.y = "AMF",
df = c(4,7), x="xDAP", get.rates = FALSE,
which.plots = "methodsc",
deviations.plots = "compare",
labeller = labeller(Zn = labelZn,
AMF = labelMyc)),
regexp = "Length of propn.types is not the same as the number of trait.types"),
regexp = "get.rates is FALSE and so trait.types changed to response")
testthat::expect_warning(
tom <- probeSmoothing(data = tomato.dat,
response = "PSA",
response.smoothed = "sPSA",
times.factor = "DAP", xname = "xDAP",
smoothing.methods = c("dir", "log"),
facet.x = "Zn", facet.y = "AMF",
df = c(4,7), x="xDAP", get.rates = FALSE,
propn.types = 0.1,
which.plots = "methodsc",
deviations.plots = "compare",
labeller = labeller(Zn = labelZn,
AMF = labelMyc)),
regexp = "get.rates is FALSE and so trait.types changed to response")
testthat::expect_equal(nrow(tom), 1120)
testthat::expect_equal(ncol(tom), 10)
testthat::expect_silent(med <- plotMedianDeviations(data = tom,
response = "PSA",
response.smoothed = "sPSA",
xname = "xDAP",
smoothing.methods = c("dir", "log"),
df = c(4,7), x.title = "DAP",
y.titles = "PSA deviation (kpixels)",
facet.x = "Zn", facet.y = "AMF",
trait.types = "response",
propn.types = 0.1,
labeller = labeller(Zn = labelZn,
AMF = labelMyc)))
testthat::expect_equal(length(med$plots), 1)
testthat::expect_equal(nrow(med$med.devn.dat), 1120)
testthat::expect_equal(ncol(med$med.devn.dat), 8)
#Multiple df, single methods
testthat::expect_warning(tom <- probeSmoothing(data = tomato.dat, response = "PSA",
response.smoothed = "sPSA",
times.factor = "DAP", xname="xDAP", df=5:6,
smoothing.methods = c("logarithmic"),
facet.x = ".", facet.y = ".",
which.plots = "none",
propn.types = c(0.02, 0.2, 0.5),
deviations.plots = "compare.medians"))
testthat::expect_equal(nrow(tom), 1120)
testthat::expect_equal(ncol(tom), 13)
#'Single `df`, multiple methods and trait.types
testthat::expect_warning(tom <- probeSmoothing(data = tomato.dat, response = "PSA",
response.smoothed = "sPSA",
times.factor = "DAP", xname="xDAP", df=5,
smoothing.methods = c("direct","logarithmic"),
facet.x = ".", facet.y = ".",
which.plots = "none",
deviations.plots = "none"))
testthat::expect_equal(nrow(tom), 1120)
testthat::expect_equal(ncol(tom), 13)
testthat::expect_warning(med <- plotMedianDeviations(data = tom, response = "PSA",
response.smoothed = "sPSA",
xname = "xDAP",
smoothing.methods = c("dir", "log"),
df = 5, x.title = "DAP",
facet.x = ".", facet.y = ".",
propn.types = c(0.02, 0.2, 0.5)))
testthat::expect_equal(length(med), 2)
testthat::expect_true(all(names(med) == c("plots", "med.devn.dat")))
testthat::expect_equal(nrow(med$med.devn.dat), 70)
testthat::expect_equal(ncol(med$med.devn.dat), 8)
testthat::expect_equal(length(med$plots), 3)
testthat::expect_true(all(names(med$plots) == c("PSA","PSA.AGR","PSA.RGR")))
testthat::expect_warning(print(med$plots$PSA.AGR))
#'Single `df`, single method
testthat::expect_warning(tom <- probeSmoothing(data = tomato.dat, response = "PSA",
response.smoothed = "sPSA",
times.factor = "DAP", xname="xDAP", df=5,
smoothing.methods = c("direct"),
facet.x = ".", facet.y = ".",
which.plots = "none",
propn.types = c(0.02, 0.2, 0.5),
deviations.plots = "compare.medians"))
testthat::expect_equal(nrow(tom), 1120)
testthat::expect_equal(ncol(tom), 10)
})
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