tests/testthat/testWholeWorkflows.R
In Boodogs/zoon-clone: Reproducible, Accessible & Shareable Species Distribution Modelling
context('Whole workflows')
expected_names <- c('occurrence.output', 'covariate.output', 'process.output',
'model.output', 'report', 'call', 'call.list', 'session.info', 'module.versions')
test_that('simple, package data workflow works.', {
skip_on_cran()
work1 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
expect_true(exists('work1'))
expect_equal(names(work1), expected_names)
expect_equal(dim(work1$occurrence.output[[1]]), c(188,5))
expect_is(work1$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(work1$covariate.output[[1]]), c(9,9,1))
expect_equal(names(work1$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(work1$process.output[[1]][[1]]), c(258, 6))
expect_is((work1$model.output[[1]])$model, c('zoonModel'))
expect_is((work1$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is((work1$model.output[[1]])$data, c('data.frame'))
expect_is(work1$report[[1]], 'RasterLayer')
expect_is(work1$session.info, 'sessionInfo')
expect_is(work1$module.versions, 'list')
expect_named(work1$module.versions, c("occurrence","covariate","process","model","output"))
})
test_that('Check basic quoted workflow.', {
skip_on_cran()
work1 <- workflow(occurrence = 'UKAnophelesPlumbeus',
covariate = 'UKAir',
process = 'Background',
model = 'LogisticRegression',
output = 'PrintMap')
expect_true(exists('work1'))
expect_equal(names(work1), expected_names)
expect_equal(dim(work1$occurrence.output[[1]]), c(188,5))
expect_is(work1$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(work1$covariate.output[[1]]), c(9,9,1))
expect_equal(names(work1$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(work1$process.output[[1]][[1]]), c(269, 6))
expect_is((work1$model.output[[1]])$model, c('zoonModel'))
expect_is((work1$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is((work1$model.output[[1]])$data, c('data.frame'))
expect_is(work1$report[[1]], 'RasterLayer')
expect_is(work1$session.info, 'sessionInfo')
expect_is(work1$module.versions, 'list')
expect_named(work1$module.versions, c("occurrence","covariate","process","model","output"))
})
test_that('modules downloading data work', {
skip_on_cran()
work2 <- workflow(occurrence = SpOcc(species = 'Anopheles plumbeus',
extent = c(-10, 10, 45, 65)),
covariate = UKAir,
process = Background(n = 70),
model = RandomForest,
output = PrintMap)
expect_true(exists('work2'))
expect_equal(names(work2), expected_names)
expect_is(work2$occurrence.output[[1]], 'data.frame')
expect_equal(names(work2$occurrence.output[[1]]), c('longitude', 'latitude', 'value', 'type', 'fold'))
expect_true(all(work2$occurrence.output[[1]][,'longitude'] < 20))
expect_true(all(work2$occurrence.output[[1]][,'longitude'] > -20))
expect_true(all(work2$occurrence.output[[1]][,'latitude'] < 65))
expect_true(all(work2$occurrence.output[[1]][,'latitude'] > 45))
expect_true(all(work2$occurrence.output[[1]][,'type']=='presence'))
expect_is(work2$covariate.output[[1]], 'RasterLayer')
expect_is((work2$model.output[[1]])$model, 'zoonModel')
expect_is((work2$model.output[[1]])$model$model, 'randomForest')
expect_is(work2$report[[1]], 'RasterLayer')
expect_is(work2$session.info, 'sessionInfo')
expect_is(work2$module.versions, 'list')
expect_named(work2$module.versions, c("occurrence","covariate","process","model","output"))
})
test_that('Workflows with lists of modules work.', {
skip_on_cran()
# Would like to remove some of the slow online database modules from here.
# In fact I don't think the would pass cran.
workOccurList <- workflow(occurrence = list(UKAnophelesPlumbeus,
SpOcc(species = 'Anopheles plumbeus',
extent = c(-10, 10, 45, 65))),
covariate = UKAir,
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
workCovarList <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = list(UKAir, UKAir),
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
# There's only 1 appropriate process module at the moment!
workProcessList <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = list(Background(n = 70), Background(n = 70)),
model = LogisticRegression,
output = PrintMap)
workModelList <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = Background(n = 70),
model = list(LogisticRegression, RandomForest),
output = PrintMap)
workOutputList <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = Background(n = 70),
model = LogisticRegression,
output = list(PrintMap, PrintMap))
# Note session info is not tested [-8] as it varies from system
# to system - most notably Travis
expect_equivalent(sapply(workOccurList, length)[-8], c(2, 1, 2, 2, 2, 1, 5, 5))
expect_equivalent(sapply(workCovarList, length)[-8], c(1, 2, 2, 2, 2, 1, 5, 5))
expect_equivalent(sapply(workProcessList, length)[-8], c(1, 1, 2, 2, 2, 1, 5, 5))
expect_equivalent(sapply(workModelList, length)[-8], c(1, 1, 1, 2, 2, 1, 5, 5))
expect_equivalent(sapply(workOutputList, length)[-8], c(1, 1, 1, 1, 2, 1, 5, 5))
occurClasses <- unlist(lapply(workOccurList[!names(workOccurList) %in% 'session.info'], function(x) sapply(x, class)))
covarClasses <- unlist(lapply(workCovarList[!names(workCovarList) %in% 'session.info'], function(x) sapply(x, class)))
processClasses <- unlist(lapply(workProcessList[!names(workProcessList) %in% 'session.info'], function(x) sapply(x, class)))
modelClasses <- unlist(lapply(workModelList[!names(workModelList) %in% 'session.info'], function(x) sapply(x, class)))
outputClasses <- unlist(lapply(workOutputList[!names(workOutputList) %in% 'session.info'], function(x) sapply(x, class)))
expect_equivalent(occurClasses, c('data.frame','data.frame','RasterLayer','list',
'list','list','list','RasterLayer','RasterLayer', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
expect_equivalent(covarClasses, c('data.frame','RasterLayer','RasterLayer','list',
'list','list','list','RasterLayer','RasterLayer', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
expect_equivalent(processClasses, c('data.frame','RasterLayer','list',
'list','list','list','RasterLayer','RasterLayer', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
expect_equivalent(modelClasses, c('data.frame','RasterLayer','list',
'list','list','RasterLayer','RasterLayer', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
expect_equivalent(outputClasses, c('data.frame','RasterLayer','list',
'list','RasterLayer','RasterLayer', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
})
test_that('only one set of multiple lists allowed.', {
skip_on_cran()
fnc1 <- function(){
x <- workflow(occurrence = list(UKAnophelesPlumbeus,
UKAnophelesPlumbeus),
covariate = list(UKAir, UKAir),
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
}
fnc2 <- function(){
x <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = list(UKAir, UKAir),
process = list(Background(n = 70),Background(n = 70)),
model = LogisticRegression,
output = PrintMap)
}
fnc3 <- function(){
x <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = Background(n = 70),
model = list(LogisticRegression,LogisticRegression),
output = list(PrintMap, PrintMap))
}
expect_error(fnc1())
expect_error(fnc2())
expect_error(fnc3())
})
test_that('simple, crossvalidation workflow works.', {
skip_on_cran()
workCross <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = BackgroundAndCrossvalid,
model = LogisticRegression,
output = PrintMap)
expect_true(exists('workCross'))
expect_equal(names(workCross), expected_names)
expect_equal(dim(workCross$occurrence.output[[1]]), c(188, 5))
expect_is(workCross$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(workCross$covariate.output[[1]]), c(9,9,1))
expect_equal(names(workCross$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(workCross$process.output[[1]]$df), c(269, 6))
expect_is((workCross$model.output[[1]])$model, c('zoonModel'))
expect_is((workCross$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is(workCross$report[[1]], 'RasterLayer')
expect_is(workCross$session.info, 'sessionInfo')
expect_is(workCross$module.versions, 'list')
expect_named(workCross$module.versions, c("occurrence","covariate","process","model","output"))
})
test_that('chains work.', {
skip_on_cran()
chain1 <- workflow(occurrence = Chain(UKAnophelesPlumbeus,UKAnophelesPlumbeus),
covariate = UKAir,
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
chain2 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = Chain(UKAir,UKAir),
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
chain3 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = Chain(UKAir,UKAir),
process = Background(n = 70),
model = LogisticRegression,
output = Chain(PrintMap, PrintMap))
chain4 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = Background(n = 70),
model = LogisticRegression,
output = Chain(PrintMap, PrintMap))
chain5 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = Chain(Background(n = 70), NoProcess),
model = LogisticRegression,
output = PrintMap)
expect_true(exists('chain1'))
expect_equal(dim(chain1$occurrence.output[[1]]), c(376, 5))
expect_is(chain1$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(chain1$covariate.output[[1]]), c(9,9,1))
expect_equal(names(chain1$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(chain1$process.output[[1]]$df), c(446, 6))
expect_is((chain1$model.output[[1]])$model, c('zoonModel'))
expect_is((chain1$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is(chain1$report[[1]], 'RasterLayer')
expect_is(chain1$session.info, 'sessionInfo')
expect_is(chain1$module.versions, 'list')
expect_named(chain1$module.versions, c("occurrence","covariate","process","model","output"))
expect_true(exists('chain2'))
expect_equal(dim(chain2$occurrence.output[[1]]), c(188, 5))
expect_is(chain2$covariate.output[[1]], 'RasterStack')
expect_equal(dim(chain2$covariate.output[[1]]), c(9,9,2))
expect_equal(names(chain2$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer.1', 'layer.2'))
expect_equal(dim(chain2$process.output[[1]]$df), c(258, 7))
expect_is((chain2$model.output[[1]])$model, c('zoonModel'))
expect_is((chain2$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is(chain2$report[[1]], 'RasterLayer')
expect_is(chain2$session.info, 'sessionInfo')
expect_is(chain2$module.versions, 'list')
expect_named(chain2$module.versions, c("occurrence","covariate","process","model","output"))
expect_true(exists('chain3'))
expect_equal(dim(chain3$occurrence.output[[1]]), c(188, 5))
expect_is(chain3$covariate.output[[1]], 'RasterStack')
expect_equal(dim(chain3$covariate.output[[1]]), c(9,9,2))
expect_equal(names(chain3$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer.1', 'layer.2'))
expect_equal(dim(chain3$process.output[[1]]$df), c(258, 7))
expect_is((chain3$model.output[[1]])$model, c('zoonModel'))
expect_is((chain3$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is(chain3$report[[1]], 'list')
expect_is(chain3$session.info, 'sessionInfo')
expect_is(chain3$module.versions, 'list')
expect_named(chain3$module.versions, c("occurrence","covariate","process","model","output"))
expect_true(exists('chain4'))
expect_equal(dim(chain4$occurrence.output[[1]]), c(188, 5))
expect_is(chain4$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(chain4$covariate.output[[1]]), c(9,9,1))
expect_equal(names(chain4$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(chain4$process.output[[1]]$df), c(258, 6))
expect_is((chain4$model.output[[1]])$model, c('zoonModel'))
expect_is((chain4$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is(chain4$report[[1]], 'list')
expect_is(chain4$session.info, 'sessionInfo')
expect_is(chain4$module.versions, 'list')
expect_named(chain4$module.versions, c("occurrence","covariate","process","model","output"))
expect_true(exists('chain5'))
expect_equal(dim(chain5$occurrence.output[[1]]), c(188, 5))
expect_is(chain5$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(chain5$covariate.output[[1]]), c(9,9,1))
expect_equal(names(chain5$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(chain5$process.output[[1]]$df), c(258, 6))
expect_is((chain5$model.output[[1]])$model, c('zoonModel'))
expect_is((chain5$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is(chain5$report[[1]], 'RasterLayer')
expect_is(chain5$session.info, 'sessionInfo')
expect_is(chain5$module.versions, 'list')
expect_named(chain5$module.versions, c("occurrence","covariate","process","model","output"))
})
test_that('workflow with mix of syntax works.', {
skip_on_cran()
workSyn <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = 'UKAir',
process = BackgroundAndCrossvalid(k=2),
model = list(LogisticRegression, RandomForest),
output = Chain('PrintMap', 'PrintMap'))
expect_true(exists('workSyn'))
expect_equal(names(workSyn), expected_names)
expect_equal(dim(workSyn$occurrence.output[[1]]), c(188,5))
expect_is(workSyn$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(workSyn$covariate.output[[1]]), c(9,9,1))
expect_equal(names(workSyn$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(workSyn$process.output[[1]][[1]]), c(269, 6))
expect_is((workSyn$model.output[[1]])$model, c('zoonModel'))
expect_is((workSyn$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is((workSyn$model.output[[1]])$data, c('data.frame'))
expect_is(workSyn$report[[1]], 'RasterLayer')
expect_is(workSyn$session.info, 'sessionInfo')
expect_is(workSyn$module.versions, 'list')
expect_named(workSyn$module.versions, c("occurrence","covariate","process","model","output"))
})
# test_that('workflow with user defined cross validation', {
#
# skip_on_cran()
#
# extent = c(-10, 10, 55, 65)
#
# reorderExtent <- extent[c(1, 3, 2, 4)]
#
# # Get the data
# raw <- occ2df(occ(query = 'Anopheles plumbeus',
# geometry = reorderExtent,
# from = 'gbif',
# limit = 10000))
# raw$value <- 1
#
# write.csv(raw, file = file.path(tempdir(), 'test.csv'), row.names = FALSE)
#
# work2 <- workflow(occurrence = Chain(SpOcc(species = 'Anopheles plumbeus',
# extent = c(-10, 10, 45, 55)),
# LocalOccurrenceData(file.path(tempdir(), 'test.csv'),
# 'presence',
# columns = c(long = 'longitude',
# lat = 'latitude',
# value = 'value'),
# externalValidation = TRUE)),
# covariate = UKAir,
# process = NoProcess,
# model = RandomForest,
# output = PerformanceMeasures)
#
# str(work2$model.output)
#
# expect_true(exists('workSyn'))
# expect_equal(names(workSyn), expected_names)
# expect_equal(dim(workSyn$occurrence.output[[1]]), c(188,5))
# expect_is(workSyn$covariate.output[[1]], 'RasterLayer')
# expect_equal(dim(workSyn$covariate.output[[1]]), c(9,9,1))
# expect_equal(names(workSyn$process.output[[1]]$df),
# c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
# expect_equal(dim(workSyn$process.output[[1]][[1]]), c(269, 6))
# expect_is((workSyn$model.output[[1]])$model, c('zoonModel'))
# expect_is((workSyn$model.output[[1]])$model$model, c('glm', 'lm'))
# expect_is((workSyn$model.output[[1]])$data, c('data.frame'))
# expect_is(workSyn$report[[1]], 'list')
#
# })
## add external validation dataset (fold == 0)
test_that('Output understands which previous model was listed.', {
skip_on_cran()
# See issue 263 for discussion
# https://github.com/zoonproject/zoon/issues/263
# Create a local raster *with a differently named layer*
# The listed covariate tests above erroneously passed because we
# listed UKAir twice, so they had identical layer names.
UKAirRas2 <<- UKAirRas
names(UKAirRas2) <- 'NewName'
work1 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = list(LocalRaster(UKAirRas2), UKAir),
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
work2 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = list(LocalRaster(UKAirRas2), UKAir),
process = Background(n = 70),
model = LogisticRegression,
output = Chain(PrintMap, PrintMap))
rm(list = c('UKAirRas2'))
expect_equivalent(sapply(work1, length)[-8], c(1, 2, 2, 2, 2, 1, 5, 5))
covarClasses1 <- unlist(lapply(work1[!names(work1) %in% 'session.info'], function(x) sapply(x, class)))
expect_equivalent(covarClasses1, c('data.frame','RasterLayer','RasterLayer','list',
'list','list','list','RasterLayer','RasterLayer', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
expect_equivalent(sapply(work2, length)[-8], c(1, 2, 2, 2, 2, 1, 5, 5))
covarClasses2 <- unlist(lapply(work2[!names(work2) %in% 'session.info'], function(x) sapply(x, class)))
expect_equivalent(covarClasses2, c('data.frame','RasterLayer','RasterLayer','list',
'list','list','list','list','list', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
})
test_that('Running modules with parameters', {
skip_on_cran()
# I dont think we do this elsewhere
})
Boodogs/zoon-clone documentation built on May 6, 2019, 7:59 a.m.
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context('Whole workflows')
expected_names <- c('occurrence.output', 'covariate.output', 'process.output',
'model.output', 'report', 'call', 'call.list', 'session.info', 'module.versions')
test_that('simple, package data workflow works.', {
skip_on_cran()
work1 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
expect_true(exists('work1'))
expect_equal(names(work1), expected_names)
expect_equal(dim(work1$occurrence.output[[1]]), c(188,5))
expect_is(work1$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(work1$covariate.output[[1]]), c(9,9,1))
expect_equal(names(work1$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(work1$process.output[[1]][[1]]), c(258, 6))
expect_is((work1$model.output[[1]])$model, c('zoonModel'))
expect_is((work1$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is((work1$model.output[[1]])$data, c('data.frame'))
expect_is(work1$report[[1]], 'RasterLayer')
expect_is(work1$session.info, 'sessionInfo')
expect_is(work1$module.versions, 'list')
expect_named(work1$module.versions, c("occurrence","covariate","process","model","output"))
})
test_that('Check basic quoted workflow.', {
skip_on_cran()
work1 <- workflow(occurrence = 'UKAnophelesPlumbeus',
covariate = 'UKAir',
process = 'Background',
model = 'LogisticRegression',
output = 'PrintMap')
expect_true(exists('work1'))
expect_equal(names(work1), expected_names)
expect_equal(dim(work1$occurrence.output[[1]]), c(188,5))
expect_is(work1$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(work1$covariate.output[[1]]), c(9,9,1))
expect_equal(names(work1$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(work1$process.output[[1]][[1]]), c(269, 6))
expect_is((work1$model.output[[1]])$model, c('zoonModel'))
expect_is((work1$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is((work1$model.output[[1]])$data, c('data.frame'))
expect_is(work1$report[[1]], 'RasterLayer')
expect_is(work1$session.info, 'sessionInfo')
expect_is(work1$module.versions, 'list')
expect_named(work1$module.versions, c("occurrence","covariate","process","model","output"))
})
test_that('modules downloading data work', {
skip_on_cran()
work2 <- workflow(occurrence = SpOcc(species = 'Anopheles plumbeus',
extent = c(-10, 10, 45, 65)),
covariate = UKAir,
process = Background(n = 70),
model = RandomForest,
output = PrintMap)
expect_true(exists('work2'))
expect_equal(names(work2), expected_names)
expect_is(work2$occurrence.output[[1]], 'data.frame')
expect_equal(names(work2$occurrence.output[[1]]), c('longitude', 'latitude', 'value', 'type', 'fold'))
expect_true(all(work2$occurrence.output[[1]][,'longitude'] < 20))
expect_true(all(work2$occurrence.output[[1]][,'longitude'] > -20))
expect_true(all(work2$occurrence.output[[1]][,'latitude'] < 65))
expect_true(all(work2$occurrence.output[[1]][,'latitude'] > 45))
expect_true(all(work2$occurrence.output[[1]][,'type']=='presence'))
expect_is(work2$covariate.output[[1]], 'RasterLayer')
expect_is((work2$model.output[[1]])$model, 'zoonModel')
expect_is((work2$model.output[[1]])$model$model, 'randomForest')
expect_is(work2$report[[1]], 'RasterLayer')
expect_is(work2$session.info, 'sessionInfo')
expect_is(work2$module.versions, 'list')
expect_named(work2$module.versions, c("occurrence","covariate","process","model","output"))
})
test_that('Workflows with lists of modules work.', {
skip_on_cran()
# Would like to remove some of the slow online database modules from here.
# In fact I don't think the would pass cran.
workOccurList <- workflow(occurrence = list(UKAnophelesPlumbeus,
SpOcc(species = 'Anopheles plumbeus',
extent = c(-10, 10, 45, 65))),
covariate = UKAir,
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
workCovarList <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = list(UKAir, UKAir),
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
# There's only 1 appropriate process module at the moment!
workProcessList <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = list(Background(n = 70), Background(n = 70)),
model = LogisticRegression,
output = PrintMap)
workModelList <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = Background(n = 70),
model = list(LogisticRegression, RandomForest),
output = PrintMap)
workOutputList <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = Background(n = 70),
model = LogisticRegression,
output = list(PrintMap, PrintMap))
# Note session info is not tested [-8] as it varies from system
# to system - most notably Travis
expect_equivalent(sapply(workOccurList, length)[-8], c(2, 1, 2, 2, 2, 1, 5, 5))
expect_equivalent(sapply(workCovarList, length)[-8], c(1, 2, 2, 2, 2, 1, 5, 5))
expect_equivalent(sapply(workProcessList, length)[-8], c(1, 1, 2, 2, 2, 1, 5, 5))
expect_equivalent(sapply(workModelList, length)[-8], c(1, 1, 1, 2, 2, 1, 5, 5))
expect_equivalent(sapply(workOutputList, length)[-8], c(1, 1, 1, 1, 2, 1, 5, 5))
occurClasses <- unlist(lapply(workOccurList[!names(workOccurList) %in% 'session.info'], function(x) sapply(x, class)))
covarClasses <- unlist(lapply(workCovarList[!names(workCovarList) %in% 'session.info'], function(x) sapply(x, class)))
processClasses <- unlist(lapply(workProcessList[!names(workProcessList) %in% 'session.info'], function(x) sapply(x, class)))
modelClasses <- unlist(lapply(workModelList[!names(workModelList) %in% 'session.info'], function(x) sapply(x, class)))
outputClasses <- unlist(lapply(workOutputList[!names(workOutputList) %in% 'session.info'], function(x) sapply(x, class)))
expect_equivalent(occurClasses, c('data.frame','data.frame','RasterLayer','list',
'list','list','list','RasterLayer','RasterLayer', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
expect_equivalent(covarClasses, c('data.frame','RasterLayer','RasterLayer','list',
'list','list','list','RasterLayer','RasterLayer', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
expect_equivalent(processClasses, c('data.frame','RasterLayer','list',
'list','list','list','RasterLayer','RasterLayer', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
expect_equivalent(modelClasses, c('data.frame','RasterLayer','list',
'list','list','RasterLayer','RasterLayer', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
expect_equivalent(outputClasses, c('data.frame','RasterLayer','list',
'list','RasterLayer','RasterLayer', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
})
test_that('only one set of multiple lists allowed.', {
skip_on_cran()
fnc1 <- function(){
x <- workflow(occurrence = list(UKAnophelesPlumbeus,
UKAnophelesPlumbeus),
covariate = list(UKAir, UKAir),
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
}
fnc2 <- function(){
x <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = list(UKAir, UKAir),
process = list(Background(n = 70),Background(n = 70)),
model = LogisticRegression,
output = PrintMap)
}
fnc3 <- function(){
x <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = Background(n = 70),
model = list(LogisticRegression,LogisticRegression),
output = list(PrintMap, PrintMap))
}
expect_error(fnc1())
expect_error(fnc2())
expect_error(fnc3())
})
test_that('simple, crossvalidation workflow works.', {
skip_on_cran()
workCross <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = BackgroundAndCrossvalid,
model = LogisticRegression,
output = PrintMap)
expect_true(exists('workCross'))
expect_equal(names(workCross), expected_names)
expect_equal(dim(workCross$occurrence.output[[1]]), c(188, 5))
expect_is(workCross$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(workCross$covariate.output[[1]]), c(9,9,1))
expect_equal(names(workCross$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(workCross$process.output[[1]]$df), c(269, 6))
expect_is((workCross$model.output[[1]])$model, c('zoonModel'))
expect_is((workCross$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is(workCross$report[[1]], 'RasterLayer')
expect_is(workCross$session.info, 'sessionInfo')
expect_is(workCross$module.versions, 'list')
expect_named(workCross$module.versions, c("occurrence","covariate","process","model","output"))
})
test_that('chains work.', {
skip_on_cran()
chain1 <- workflow(occurrence = Chain(UKAnophelesPlumbeus,UKAnophelesPlumbeus),
covariate = UKAir,
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
chain2 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = Chain(UKAir,UKAir),
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
chain3 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = Chain(UKAir,UKAir),
process = Background(n = 70),
model = LogisticRegression,
output = Chain(PrintMap, PrintMap))
chain4 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = Background(n = 70),
model = LogisticRegression,
output = Chain(PrintMap, PrintMap))
chain5 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = UKAir,
process = Chain(Background(n = 70), NoProcess),
model = LogisticRegression,
output = PrintMap)
expect_true(exists('chain1'))
expect_equal(dim(chain1$occurrence.output[[1]]), c(376, 5))
expect_is(chain1$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(chain1$covariate.output[[1]]), c(9,9,1))
expect_equal(names(chain1$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(chain1$process.output[[1]]$df), c(446, 6))
expect_is((chain1$model.output[[1]])$model, c('zoonModel'))
expect_is((chain1$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is(chain1$report[[1]], 'RasterLayer')
expect_is(chain1$session.info, 'sessionInfo')
expect_is(chain1$module.versions, 'list')
expect_named(chain1$module.versions, c("occurrence","covariate","process","model","output"))
expect_true(exists('chain2'))
expect_equal(dim(chain2$occurrence.output[[1]]), c(188, 5))
expect_is(chain2$covariate.output[[1]], 'RasterStack')
expect_equal(dim(chain2$covariate.output[[1]]), c(9,9,2))
expect_equal(names(chain2$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer.1', 'layer.2'))
expect_equal(dim(chain2$process.output[[1]]$df), c(258, 7))
expect_is((chain2$model.output[[1]])$model, c('zoonModel'))
expect_is((chain2$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is(chain2$report[[1]], 'RasterLayer')
expect_is(chain2$session.info, 'sessionInfo')
expect_is(chain2$module.versions, 'list')
expect_named(chain2$module.versions, c("occurrence","covariate","process","model","output"))
expect_true(exists('chain3'))
expect_equal(dim(chain3$occurrence.output[[1]]), c(188, 5))
expect_is(chain3$covariate.output[[1]], 'RasterStack')
expect_equal(dim(chain3$covariate.output[[1]]), c(9,9,2))
expect_equal(names(chain3$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer.1', 'layer.2'))
expect_equal(dim(chain3$process.output[[1]]$df), c(258, 7))
expect_is((chain3$model.output[[1]])$model, c('zoonModel'))
expect_is((chain3$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is(chain3$report[[1]], 'list')
expect_is(chain3$session.info, 'sessionInfo')
expect_is(chain3$module.versions, 'list')
expect_named(chain3$module.versions, c("occurrence","covariate","process","model","output"))
expect_true(exists('chain4'))
expect_equal(dim(chain4$occurrence.output[[1]]), c(188, 5))
expect_is(chain4$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(chain4$covariate.output[[1]]), c(9,9,1))
expect_equal(names(chain4$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(chain4$process.output[[1]]$df), c(258, 6))
expect_is((chain4$model.output[[1]])$model, c('zoonModel'))
expect_is((chain4$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is(chain4$report[[1]], 'list')
expect_is(chain4$session.info, 'sessionInfo')
expect_is(chain4$module.versions, 'list')
expect_named(chain4$module.versions, c("occurrence","covariate","process","model","output"))
expect_true(exists('chain5'))
expect_equal(dim(chain5$occurrence.output[[1]]), c(188, 5))
expect_is(chain5$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(chain5$covariate.output[[1]]), c(9,9,1))
expect_equal(names(chain5$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(chain5$process.output[[1]]$df), c(258, 6))
expect_is((chain5$model.output[[1]])$model, c('zoonModel'))
expect_is((chain5$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is(chain5$report[[1]], 'RasterLayer')
expect_is(chain5$session.info, 'sessionInfo')
expect_is(chain5$module.versions, 'list')
expect_named(chain5$module.versions, c("occurrence","covariate","process","model","output"))
})
test_that('workflow with mix of syntax works.', {
skip_on_cran()
workSyn <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = 'UKAir',
process = BackgroundAndCrossvalid(k=2),
model = list(LogisticRegression, RandomForest),
output = Chain('PrintMap', 'PrintMap'))
expect_true(exists('workSyn'))
expect_equal(names(workSyn), expected_names)
expect_equal(dim(workSyn$occurrence.output[[1]]), c(188,5))
expect_is(workSyn$covariate.output[[1]], 'RasterLayer')
expect_equal(dim(workSyn$covariate.output[[1]]), c(9,9,1))
expect_equal(names(workSyn$process.output[[1]]$df),
c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
expect_equal(dim(workSyn$process.output[[1]][[1]]), c(269, 6))
expect_is((workSyn$model.output[[1]])$model, c('zoonModel'))
expect_is((workSyn$model.output[[1]])$model$model, c('glm', 'lm'))
expect_is((workSyn$model.output[[1]])$data, c('data.frame'))
expect_is(workSyn$report[[1]], 'RasterLayer')
expect_is(workSyn$session.info, 'sessionInfo')
expect_is(workSyn$module.versions, 'list')
expect_named(workSyn$module.versions, c("occurrence","covariate","process","model","output"))
})
# test_that('workflow with user defined cross validation', {
#
# skip_on_cran()
#
# extent = c(-10, 10, 55, 65)
#
# reorderExtent <- extent[c(1, 3, 2, 4)]
#
# # Get the data
# raw <- occ2df(occ(query = 'Anopheles plumbeus',
# geometry = reorderExtent,
# from = 'gbif',
# limit = 10000))
# raw$value <- 1
#
# write.csv(raw, file = file.path(tempdir(), 'test.csv'), row.names = FALSE)
#
# work2 <- workflow(occurrence = Chain(SpOcc(species = 'Anopheles plumbeus',
# extent = c(-10, 10, 45, 55)),
# LocalOccurrenceData(file.path(tempdir(), 'test.csv'),
# 'presence',
# columns = c(long = 'longitude',
# lat = 'latitude',
# value = 'value'),
# externalValidation = TRUE)),
# covariate = UKAir,
# process = NoProcess,
# model = RandomForest,
# output = PerformanceMeasures)
#
# str(work2$model.output)
#
# expect_true(exists('workSyn'))
# expect_equal(names(workSyn), expected_names)
# expect_equal(dim(workSyn$occurrence.output[[1]]), c(188,5))
# expect_is(workSyn$covariate.output[[1]], 'RasterLayer')
# expect_equal(dim(workSyn$covariate.output[[1]]), c(9,9,1))
# expect_equal(names(workSyn$process.output[[1]]$df),
# c('value', 'type', 'fold', 'longitude', 'latitude', 'layer'))
# expect_equal(dim(workSyn$process.output[[1]][[1]]), c(269, 6))
# expect_is((workSyn$model.output[[1]])$model, c('zoonModel'))
# expect_is((workSyn$model.output[[1]])$model$model, c('glm', 'lm'))
# expect_is((workSyn$model.output[[1]])$data, c('data.frame'))
# expect_is(workSyn$report[[1]], 'list')
#
# })
## add external validation dataset (fold == 0)
test_that('Output understands which previous model was listed.', {
skip_on_cran()
# See issue 263 for discussion
# https://github.com/zoonproject/zoon/issues/263
# Create a local raster *with a differently named layer*
# The listed covariate tests above erroneously passed because we
# listed UKAir twice, so they had identical layer names.
UKAirRas2 <<- UKAirRas
names(UKAirRas2) <- 'NewName'
work1 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = list(LocalRaster(UKAirRas2), UKAir),
process = Background(n = 70),
model = LogisticRegression,
output = PrintMap)
work2 <- workflow(occurrence = UKAnophelesPlumbeus,
covariate = list(LocalRaster(UKAirRas2), UKAir),
process = Background(n = 70),
model = LogisticRegression,
output = Chain(PrintMap, PrintMap))
rm(list = c('UKAirRas2'))
expect_equivalent(sapply(work1, length)[-8], c(1, 2, 2, 2, 2, 1, 5, 5))
covarClasses1 <- unlist(lapply(work1[!names(work1) %in% 'session.info'], function(x) sapply(x, class)))
expect_equivalent(covarClasses1, c('data.frame','RasterLayer','RasterLayer','list',
'list','list','list','RasterLayer','RasterLayer', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
expect_equivalent(sapply(work2, length)[-8], c(1, 2, 2, 2, 2, 1, 5, 5))
covarClasses2 <- unlist(lapply(work2[!names(work2) %in% 'session.info'], function(x) sapply(x, class)))
expect_equivalent(covarClasses2, c('data.frame','RasterLayer','RasterLayer','list',
'list','list','list','list','list', 'character',
'list','list','list','list','list',
'matrix','matrix','matrix','matrix','matrix'))
})
test_that('Running modules with parameters', {
skip_on_cran()
# I dont think we do this elsewhere
})
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