tests/testthat/test-calc_amw_functions.R
In EnergyEconomyDecoupling/MWTools: Functions For Calculation of Muscle Work Within the PSUT Framework
test_that("tidy_fao_live_animals works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
live_animals <- test_data %>%
tidy_fao_live_animals()
expect_true(!is.null(live_animals))
# expect_true(all(unique(live_animals[[MWTools::mw_constants$species]]) == c("Asses", "Buffaloes", "Camels", "Cattle", "Horses", "Mules and hinnies")))
expect_equal(unique(live_animals[[MWTools::mw_constants$country_name]]), c("China", "China, mainland"))
expect_equal(colnames(live_animals),
c(MWTools::mw_constants$country_name,
MWTools::mw_constants$species,
MWTools::mw_cols$year,
MWTools::mw_constants$value))
expect_equal(nrow(live_animals), 1827)
})
test_that("add_concordance_codes works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
live_animals_w.codes <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes()
expect_true(!is.null(live_animals_w.codes))
expect_equal(unique(live_animals_w.codes$Country.code), c("CHN", "CHNM"))
expect_equal(colnames(live_animals_w.codes),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_constants$country_name,
MWTools::mw_constants$species,
MWTools::mw_cols$year,
MWTools::mw_constants$value,
MWTools::conc_cols$country_incl_col))
expect_equal(nrow(live_animals_w.codes), 1827)
})
test_that("trim_fao_data works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
live_animals_trimmed <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data()
expect_true(!is.null(live_animals_trimmed))
expect_equal(unique(live_animals_trimmed$Country.code), "CHNM")
expect_equal(nrow(live_animals_trimmed), 882)
})
test_that("get_working_species works with 'Camelids, other'", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path) |>
dplyr::filter(.data[[MWTools::mw_constants$species]] != MWTools::mw_species$camelids_other)
# "Camelids, other" are present for 2019 only by default, then removed in
# tidy_fao_live_animals() as 1 data point cannot be interpolated or extrapolated,
# add dummy test data
test_data_camelids <- test_data |>
dplyr::filter(.data[[MWTools::mw_constants$species]] != MWTools::mw_species$camelids_other) |>
dplyr::filter(.data[[MWTools::mw_constants$species]] == MWTools::mw_species$camels) |>
dplyr::mutate(
"{MWTools::mw_constants$species}" := dplyr::case_when(
.data[[MWTools::mw_constants$species]] == MWTools::mw_species$camels ~ MWTools::mw_species$camelids_other,
TRUE ~ .data[[MWTools::mw_constants$species]]
)
)
test_data <- rbind(test_data, test_data_camelids)
live_animals_w.species <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species()
expect_true(!is.null(live_animals_w.species))
expect_equal(unique(live_animals_w.species[[MWTools::conc_cols$country_code_col]]), "CHNM")
expect_equal(nrow(live_animals_w.species), 378)
expect_equal(unique(live_animals_w.species[[MWTools::mw_constants$species]]),
c(MWTools::mw_species$asses,
MWTools::mw_species$buffaloes,
MWTools::mw_species$cattle,
MWTools::mw_species$horses,
MWTools::mw_species$mules,
MWTools::mw_species$camelids))
})
test_that("get_working_species works without 'Camelids, other'", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
live_animals_w.species <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
dplyr::filter(.data[[MWTools::mw_constants$species]] != MWTools::mw_species$camelids_other) %>% # "Camelids, other" are absent by default
get_working_species()
expect_true(!is.null(live_animals_w.species))
expect_equal(unique(live_animals_w.species[[MWTools::conc_cols$country_code_col]]), "CHNM")
expect_equal(nrow(live_animals_w.species), 378)
expect_equal(unique(live_animals_w.species[[MWTools::mw_constants$species]]),
c(MWTools::mw_species$asses,
MWTools::mw_species$buffaloes,
MWTools::mw_species$cattle,
MWTools::mw_species$horses,
MWTools::mw_species$mules,
MWTools::mw_species$camelids))
})
test_that("get_working_species works without 'Camelids, other' or 'Camels'.", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
live_animals_w.species <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
dplyr::filter(.data[[MWTools::mw_constants$species]] != MWTools::mw_species$camelids_other) %>%
dplyr::filter(.data[[MWTools::mw_constants$species]] != MWTools::mw_species$camels) %>%
get_working_species()
expect_true(!is.null(live_animals_w.species))
expect_equal(unique(live_animals_w.species[[MWTools::conc_cols$country_code_col]]), "CHNM")
expect_equal(nrow(live_animals_w.species), 378)
expect_equal(unique(live_animals_w.species[[MWTools::mw_constants$species]]),
c(MWTools::mw_species$asses,
MWTools::mw_species$buffaloes,
MWTools::mw_species$cattle,
MWTools::mw_species$horses,
MWTools::mw_species$mules,
MWTools::mw_species$camelids))
})
test_that("calc_working_animals works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
working_animals <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals()
expect_true(!is.null(working_animals))
expect_equal(nrow(working_animals), 378)
expect_equal(unique(working_animals[[MWTools::conc_cols$species]]),
c(MWTools::mw_species$asses,
MWTools::mw_species$buffaloes,
MWTools::mw_species$cattle,
MWTools::mw_species$horses,
MWTools::mw_species$mules,
MWTools::mw_species$camelids))
expect_equal(colnames(working_animals),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_cols$year,
MWTools::conc_cols$species,
MWTools::amw_analysis_constants$live_animals_col,
MWTools::amw_analysis_constants$prop_working_animals_col,
MWTools::amw_analysis_constants$working_animals_total_col))
})
test_that("calc_sector_split works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
working_animals_s.split <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals() %>%
calc_sector_split()
expect_true(!is.null(working_animals_s.split))
expect_equal(nrow(working_animals_s.split), 378)
expect_equal(colnames(working_animals_s.split),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_cols$year,
MWTools::conc_cols$species,
MWTools::amw_analysis_constants$live_animals_col,
MWTools::amw_analysis_constants$prop_working_animals_col,
MWTools::amw_analysis_constants$working_animals_total_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_ag_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_tr_col,
MWTools::amw_analysis_constants$working_animals_ag_col,
MWTools::amw_analysis_constants$working_animals_tr_col))
})
test_that("calc_yearly_feed works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
working_animals_w.feed <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals() %>%
calc_sector_split() %>%
calc_yearly_feed()
expect_true(!is.null(working_animals_w.feed))
expect_equal(nrow(working_animals_w.feed), 378)
expect_equal(colnames(working_animals_w.feed),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_cols$year,
MWTools::conc_cols$species,
MWTools::amw_analysis_constants$live_animals_col,
MWTools::amw_analysis_constants$prop_working_animals_col,
MWTools::amw_analysis_constants$working_animals_total_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_ag_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_tr_col,
MWTools::amw_analysis_constants$working_animals_ag_col,
MWTools::amw_analysis_constants$working_animals_tr_col,
MWTools::amw_analysis_constants$total_yearly_feed_col))
})
test_that("calc_final_energy works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
working_animals_w.finalenergy <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals() %>%
calc_sector_split() %>%
calc_yearly_feed() %>%
calc_final_energy()
expect_true(!is.null(working_animals_w.finalenergy))
expect_equal(nrow(working_animals_w.finalenergy), 378)
expect_equal(colnames(working_animals_w.finalenergy),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_cols$year,
MWTools::conc_cols$species,
MWTools::amw_analysis_constants$live_animals_col,
MWTools::amw_analysis_constants$prop_working_animals_col,
MWTools::amw_analysis_constants$working_animals_total_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_ag_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_tr_col,
MWTools::amw_analysis_constants$working_animals_ag_col,
MWTools::amw_analysis_constants$working_animals_tr_col,
MWTools::amw_analysis_constants$total_yearly_feed_col,
MWTools::amw_analysis_constants$final_energy_total,
MWTools::amw_analysis_constants$final_energy_ag,
MWTools::amw_analysis_constants$final_energy_tr))
})
test_that("calc_primary_energy",{
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
working_animals_w.primaryenergy <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals() %>%
calc_sector_split() %>%
calc_yearly_feed() %>%
calc_final_energy() %>%
calc_primary_energy()
expect_true(!is.null(working_animals_w.primaryenergy))
expect_equal(nrow(working_animals_w.primaryenergy), 378)
expect_equal(colnames(working_animals_w.primaryenergy),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_cols$year,
MWTools::conc_cols$species,
MWTools::amw_analysis_constants$live_animals_col,
MWTools::amw_analysis_constants$prop_working_animals_col,
MWTools::amw_analysis_constants$working_animals_total_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_ag_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_tr_col,
MWTools::amw_analysis_constants$working_animals_ag_col,
MWTools::amw_analysis_constants$working_animals_tr_col,
MWTools::amw_analysis_constants$total_yearly_feed_col,
MWTools::amw_analysis_constants$final_energy_total,
MWTools::amw_analysis_constants$final_energy_ag,
MWTools::amw_analysis_constants$final_energy_tr,
MWTools::amw_analysis_constants$primary_energy_total,
MWTools::amw_analysis_constants$primary_energy_ag,
MWTools::amw_analysis_constants$primary_energy_tr))
})
test_that("calc_useful_energy() works as expected",{
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
working_animals_w.usefulenergy <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals() %>%
calc_sector_split() %>%
calc_yearly_feed() %>%
calc_final_energy() %>%
calc_primary_energy() %>%
calc_useful_energy()
expect_true(!is.null(working_animals_w.usefulenergy))
expect_equal(nrow(working_animals_w.usefulenergy), 378)
expect_equal(colnames(working_animals_w.usefulenergy),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_cols$year,
MWTools::conc_cols$species,
MWTools::amw_analysis_constants$live_animals_col,
MWTools::amw_analysis_constants$prop_working_animals_col,
MWTools::amw_analysis_constants$working_animals_total_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_ag_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_tr_col,
MWTools::amw_analysis_constants$working_animals_ag_col,
MWTools::amw_analysis_constants$working_animals_tr_col,
MWTools::amw_analysis_constants$total_yearly_feed_col,
MWTools::amw_analysis_constants$final_energy_total,
MWTools::amw_analysis_constants$final_energy_ag,
MWTools::amw_analysis_constants$final_energy_tr,
MWTools::amw_analysis_constants$primary_energy_total,
MWTools::amw_analysis_constants$primary_energy_ag,
MWTools::amw_analysis_constants$primary_energy_tr,
MWTools::amw_analysis_constants$power_per_animal,
MWTools::amw_analysis_constants$working_seconds_col,
MWTools::amw_analysis_constants$useful_energy_total,
MWTools::amw_analysis_constants$useful_energy_ag,
MWTools::amw_analysis_constants$useful_energy_tr))
})
test_that("tidy_pfu_data works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
tidy_pfu_data <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals() %>%
calc_sector_split() %>%
calc_yearly_feed() %>%
calc_final_energy() %>%
calc_primary_energy() %>%
calc_useful_energy() %>%
tidy_pfu_data()
expect_true(!is.null(tidy_pfu_data))
expect_equal(nrow(tidy_pfu_data), 2268)
expect_equal(colnames(tidy_pfu_data),
c(MWTools::conc_cols$country_col,
MWTools::fao_cols$year_fao_col,
MWTools::conc_cols$species,
MWTools::mw_constants$stage_col,
MWTools::mw_constants$sector_col,
MWTools::fao_cols$unit_fao_col,
"Edot"))
})
test_that("calc_amw_pfu", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
tidy_pfu_data <- test_data %>%
calc_amw_pfu()
expect_true(!is.null(tidy_pfu_data))
expect_equal(nrow(tidy_pfu_data), 2268)
expect_equal(colnames(tidy_pfu_data),
c(MWTools::conc_cols$country_col,
MWTools::fao_cols$year_fao_col,
MWTools::conc_cols$species,
MWTools::mw_constants$stage_col,
MWTools::mw_constants$sector_col,
MWTools::fao_cols$unit_fao_col,
"Edot"))
})
EnergyEconomyDecoupling/MWTools documentation built on April 14, 2025, 9:27 a.m.
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test_that("tidy_fao_live_animals works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
live_animals <- test_data %>%
tidy_fao_live_animals()
expect_true(!is.null(live_animals))
# expect_true(all(unique(live_animals[[MWTools::mw_constants$species]]) == c("Asses", "Buffaloes", "Camels", "Cattle", "Horses", "Mules and hinnies")))
expect_equal(unique(live_animals[[MWTools::mw_constants$country_name]]), c("China", "China, mainland"))
expect_equal(colnames(live_animals),
c(MWTools::mw_constants$country_name,
MWTools::mw_constants$species,
MWTools::mw_cols$year,
MWTools::mw_constants$value))
expect_equal(nrow(live_animals), 1827)
})
test_that("add_concordance_codes works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
live_animals_w.codes <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes()
expect_true(!is.null(live_animals_w.codes))
expect_equal(unique(live_animals_w.codes$Country.code), c("CHN", "CHNM"))
expect_equal(colnames(live_animals_w.codes),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_constants$country_name,
MWTools::mw_constants$species,
MWTools::mw_cols$year,
MWTools::mw_constants$value,
MWTools::conc_cols$country_incl_col))
expect_equal(nrow(live_animals_w.codes), 1827)
})
test_that("trim_fao_data works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
live_animals_trimmed <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data()
expect_true(!is.null(live_animals_trimmed))
expect_equal(unique(live_animals_trimmed$Country.code), "CHNM")
expect_equal(nrow(live_animals_trimmed), 882)
})
test_that("get_working_species works with 'Camelids, other'", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path) |>
dplyr::filter(.data[[MWTools::mw_constants$species]] != MWTools::mw_species$camelids_other)
# "Camelids, other" are present for 2019 only by default, then removed in
# tidy_fao_live_animals() as 1 data point cannot be interpolated or extrapolated,
# add dummy test data
test_data_camelids <- test_data |>
dplyr::filter(.data[[MWTools::mw_constants$species]] != MWTools::mw_species$camelids_other) |>
dplyr::filter(.data[[MWTools::mw_constants$species]] == MWTools::mw_species$camels) |>
dplyr::mutate(
"{MWTools::mw_constants$species}" := dplyr::case_when(
.data[[MWTools::mw_constants$species]] == MWTools::mw_species$camels ~ MWTools::mw_species$camelids_other,
TRUE ~ .data[[MWTools::mw_constants$species]]
)
)
test_data <- rbind(test_data, test_data_camelids)
live_animals_w.species <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species()
expect_true(!is.null(live_animals_w.species))
expect_equal(unique(live_animals_w.species[[MWTools::conc_cols$country_code_col]]), "CHNM")
expect_equal(nrow(live_animals_w.species), 378)
expect_equal(unique(live_animals_w.species[[MWTools::mw_constants$species]]),
c(MWTools::mw_species$asses,
MWTools::mw_species$buffaloes,
MWTools::mw_species$cattle,
MWTools::mw_species$horses,
MWTools::mw_species$mules,
MWTools::mw_species$camelids))
})
test_that("get_working_species works without 'Camelids, other'", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
live_animals_w.species <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
dplyr::filter(.data[[MWTools::mw_constants$species]] != MWTools::mw_species$camelids_other) %>% # "Camelids, other" are absent by default
get_working_species()
expect_true(!is.null(live_animals_w.species))
expect_equal(unique(live_animals_w.species[[MWTools::conc_cols$country_code_col]]), "CHNM")
expect_equal(nrow(live_animals_w.species), 378)
expect_equal(unique(live_animals_w.species[[MWTools::mw_constants$species]]),
c(MWTools::mw_species$asses,
MWTools::mw_species$buffaloes,
MWTools::mw_species$cattle,
MWTools::mw_species$horses,
MWTools::mw_species$mules,
MWTools::mw_species$camelids))
})
test_that("get_working_species works without 'Camelids, other' or 'Camels'.", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
live_animals_w.species <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
dplyr::filter(.data[[MWTools::mw_constants$species]] != MWTools::mw_species$camelids_other) %>%
dplyr::filter(.data[[MWTools::mw_constants$species]] != MWTools::mw_species$camels) %>%
get_working_species()
expect_true(!is.null(live_animals_w.species))
expect_equal(unique(live_animals_w.species[[MWTools::conc_cols$country_code_col]]), "CHNM")
expect_equal(nrow(live_animals_w.species), 378)
expect_equal(unique(live_animals_w.species[[MWTools::mw_constants$species]]),
c(MWTools::mw_species$asses,
MWTools::mw_species$buffaloes,
MWTools::mw_species$cattle,
MWTools::mw_species$horses,
MWTools::mw_species$mules,
MWTools::mw_species$camelids))
})
test_that("calc_working_animals works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
working_animals <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals()
expect_true(!is.null(working_animals))
expect_equal(nrow(working_animals), 378)
expect_equal(unique(working_animals[[MWTools::conc_cols$species]]),
c(MWTools::mw_species$asses,
MWTools::mw_species$buffaloes,
MWTools::mw_species$cattle,
MWTools::mw_species$horses,
MWTools::mw_species$mules,
MWTools::mw_species$camelids))
expect_equal(colnames(working_animals),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_cols$year,
MWTools::conc_cols$species,
MWTools::amw_analysis_constants$live_animals_col,
MWTools::amw_analysis_constants$prop_working_animals_col,
MWTools::amw_analysis_constants$working_animals_total_col))
})
test_that("calc_sector_split works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
working_animals_s.split <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals() %>%
calc_sector_split()
expect_true(!is.null(working_animals_s.split))
expect_equal(nrow(working_animals_s.split), 378)
expect_equal(colnames(working_animals_s.split),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_cols$year,
MWTools::conc_cols$species,
MWTools::amw_analysis_constants$live_animals_col,
MWTools::amw_analysis_constants$prop_working_animals_col,
MWTools::amw_analysis_constants$working_animals_total_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_ag_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_tr_col,
MWTools::amw_analysis_constants$working_animals_ag_col,
MWTools::amw_analysis_constants$working_animals_tr_col))
})
test_that("calc_yearly_feed works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
working_animals_w.feed <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals() %>%
calc_sector_split() %>%
calc_yearly_feed()
expect_true(!is.null(working_animals_w.feed))
expect_equal(nrow(working_animals_w.feed), 378)
expect_equal(colnames(working_animals_w.feed),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_cols$year,
MWTools::conc_cols$species,
MWTools::amw_analysis_constants$live_animals_col,
MWTools::amw_analysis_constants$prop_working_animals_col,
MWTools::amw_analysis_constants$working_animals_total_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_ag_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_tr_col,
MWTools::amw_analysis_constants$working_animals_ag_col,
MWTools::amw_analysis_constants$working_animals_tr_col,
MWTools::amw_analysis_constants$total_yearly_feed_col))
})
test_that("calc_final_energy works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
working_animals_w.finalenergy <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals() %>%
calc_sector_split() %>%
calc_yearly_feed() %>%
calc_final_energy()
expect_true(!is.null(working_animals_w.finalenergy))
expect_equal(nrow(working_animals_w.finalenergy), 378)
expect_equal(colnames(working_animals_w.finalenergy),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_cols$year,
MWTools::conc_cols$species,
MWTools::amw_analysis_constants$live_animals_col,
MWTools::amw_analysis_constants$prop_working_animals_col,
MWTools::amw_analysis_constants$working_animals_total_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_ag_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_tr_col,
MWTools::amw_analysis_constants$working_animals_ag_col,
MWTools::amw_analysis_constants$working_animals_tr_col,
MWTools::amw_analysis_constants$total_yearly_feed_col,
MWTools::amw_analysis_constants$final_energy_total,
MWTools::amw_analysis_constants$final_energy_ag,
MWTools::amw_analysis_constants$final_energy_tr))
})
test_that("calc_primary_energy",{
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
working_animals_w.primaryenergy <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals() %>%
calc_sector_split() %>%
calc_yearly_feed() %>%
calc_final_energy() %>%
calc_primary_energy()
expect_true(!is.null(working_animals_w.primaryenergy))
expect_equal(nrow(working_animals_w.primaryenergy), 378)
expect_equal(colnames(working_animals_w.primaryenergy),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_cols$year,
MWTools::conc_cols$species,
MWTools::amw_analysis_constants$live_animals_col,
MWTools::amw_analysis_constants$prop_working_animals_col,
MWTools::amw_analysis_constants$working_animals_total_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_ag_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_tr_col,
MWTools::amw_analysis_constants$working_animals_ag_col,
MWTools::amw_analysis_constants$working_animals_tr_col,
MWTools::amw_analysis_constants$total_yearly_feed_col,
MWTools::amw_analysis_constants$final_energy_total,
MWTools::amw_analysis_constants$final_energy_ag,
MWTools::amw_analysis_constants$final_energy_tr,
MWTools::amw_analysis_constants$primary_energy_total,
MWTools::amw_analysis_constants$primary_energy_ag,
MWTools::amw_analysis_constants$primary_energy_tr))
})
test_that("calc_useful_energy() works as expected",{
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
working_animals_w.usefulenergy <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals() %>%
calc_sector_split() %>%
calc_yearly_feed() %>%
calc_final_energy() %>%
calc_primary_energy() %>%
calc_useful_energy()
expect_true(!is.null(working_animals_w.usefulenergy))
expect_equal(nrow(working_animals_w.usefulenergy), 378)
expect_equal(colnames(working_animals_w.usefulenergy),
c(MWTools::conc_cols$country_code_col,
MWTools::conc_cols$amw_region_code_col,
MWTools::mw_cols$year,
MWTools::conc_cols$species,
MWTools::amw_analysis_constants$live_animals_col,
MWTools::amw_analysis_constants$prop_working_animals_col,
MWTools::amw_analysis_constants$working_animals_total_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_ag_col,
MWTools::amw_analysis_constants$prop_wkg_anmls_tr_col,
MWTools::amw_analysis_constants$working_animals_ag_col,
MWTools::amw_analysis_constants$working_animals_tr_col,
MWTools::amw_analysis_constants$total_yearly_feed_col,
MWTools::amw_analysis_constants$final_energy_total,
MWTools::amw_analysis_constants$final_energy_ag,
MWTools::amw_analysis_constants$final_energy_tr,
MWTools::amw_analysis_constants$primary_energy_total,
MWTools::amw_analysis_constants$primary_energy_ag,
MWTools::amw_analysis_constants$primary_energy_tr,
MWTools::amw_analysis_constants$power_per_animal,
MWTools::amw_analysis_constants$working_seconds_col,
MWTools::amw_analysis_constants$useful_energy_total,
MWTools::amw_analysis_constants$useful_energy_ag,
MWTools::amw_analysis_constants$useful_energy_tr))
})
test_that("tidy_pfu_data works", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
tidy_pfu_data <- test_data %>%
tidy_fao_live_animals() %>%
add_concordance_codes() %>%
trim_fao_data() %>%
get_working_species() %>%
calc_working_animals() %>%
calc_sector_split() %>%
calc_yearly_feed() %>%
calc_final_energy() %>%
calc_primary_energy() %>%
calc_useful_energy() %>%
tidy_pfu_data()
expect_true(!is.null(tidy_pfu_data))
expect_equal(nrow(tidy_pfu_data), 2268)
expect_equal(colnames(tidy_pfu_data),
c(MWTools::conc_cols$country_col,
MWTools::fao_cols$year_fao_col,
MWTools::conc_cols$species,
MWTools::mw_constants$stage_col,
MWTools::mw_constants$sector_col,
MWTools::fao_cols$unit_fao_col,
"Edot"))
})
test_that("calc_amw_pfu", {
test_data_path <- amw_test_data_path()
test_data <- read.csv(test_data_path)
tidy_pfu_data <- test_data %>%
calc_amw_pfu()
expect_true(!is.null(tidy_pfu_data))
expect_equal(nrow(tidy_pfu_data), 2268)
expect_equal(colnames(tidy_pfu_data),
c(MWTools::conc_cols$country_col,
MWTools::fao_cols$year_fao_col,
MWTools::conc_cols$species,
MWTools::mw_constants$stage_col,
MWTools::mw_constants$sector_col,
MWTools::fao_cols$unit_fao_col,
"Edot"))
})
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