tests/testthat/test_shares.R
In earamendia/EROITools: EROITools
test_that("calc_share_primary_ff_supply_by_product_by_group works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "EROITools")
# Loading data
tidy_AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df() %>%
IEATools::specify_all() %>%
ECCTools::specify_elect_heat_renewables() %>%
ECCTools::specify_elect_heat_fossil_fuels() %>%
ECCTools::specify_elect_heat_nuclear() %>%
ECCTools::specify_other_elec_heat_production() %>%
ECCTools::specify_elect_heat_markets() %>%
IEATools::add_psut_matnames(R_includes_all_exogenous_flows = FALSE) %>%
ECCTools::stat_diffs_to_balancing() %>%
ECCTools::stock_changes_to_balancing()
# FIRST, WE TEST THE DTA APPROACH
# Calculating total use of each product
tidy_AB_dta <- tidy_AB_data %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE)
res_dta <- tidy_AB_dta %>%
calc_share_primary_ff_supply_by_product_by_group()
# Testing
res_dta %>%
dplyr::filter(Country == "A", Product == "Coking coal", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_dta %>%
dplyr::filter(Country == "A", Product == "Crude oil", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6746032, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Natural gas", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3253968, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Coking coal", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2840909, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Crude oil", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4829545, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Natural gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2329545, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B") %>%
nrow() %>%
expect_equal(0)
# SECOND, WE TEST THE GMA APPROACH
tidy_AB_data_gma <- tidy_AB_data %>%
ECCTools::transform_to_gma()
tidy_AB_data_gma_prepared <- tidy_AB_data_gma %>%
prepare_gma_for_shares()
# dplyr::mutate(
# Country = stringr::str_extract(Flow, "\\{.*\\}") %>%
# stringr::str_remove("\\{") %>%
# stringr::str_remove("\\}"),
# Flow = stringr::str_remove(Flow, "\\{.*\\}_"),
# product_without_origin = stringr::str_remove(Product, "\\{.*\\}_"),
# )
res_gma <- tidy_AB_data_gma_prepared %>%
calc_share_primary_ff_supply_by_product_by_group()
# Testing
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Coking coal", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Crude oil", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6746032, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Natural gas", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3253968, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Coking coal", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2840909, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Crude oil", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4829545, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Natural gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2329545, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B") %>%
nrow() %>%
expect_equal(0)
})
test_that("calc_share_ff_use_by_product_by_group works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "EROITools")
#"inst/extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv"
# Loading data
tidy_AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe") %>%
IEATools::specify_all() %>%
ECCTools::specify_elect_heat_renewables() %>%
ECCTools::specify_elect_heat_fossil_fuels() %>%
ECCTools::specify_elect_heat_nuclear() %>%
ECCTools::specify_other_elec_heat_production() %>%
ECCTools::specify_elect_heat_markets() %>%
IEATools::add_psut_matnames(R_includes_all_exogenous_flows = FALSE) %>%
ECCTools::stat_diffs_to_balancing() %>%
ECCTools::stock_changes_to_balancing()
# FIRST, WE TEST THE DTA APPROACH
# Calculating total use of each product
tidy_AB_dta <- tidy_AB_data %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE)
res_dta <- tidy_AB_dta %>%
calc_share_ff_use_by_product_by_group()
# General tests:
res_dta %>%
dplyr::filter(Non_Energy_Uses == "Included") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Energy.stage != "Final (fuel)") %>%
nrow() %>%
expect_equal(0)
# Country A tests
# Coal products
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products", Product == "Blast furnace gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.7894737, tolerance = 1e-6)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products", Product == "Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2105263, tolerance = 1e-6)
# Oil products
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products", Product == "Kerosene type jet fuel excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.432098, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products", Product == "Motor gasoline excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.567901, tolerance = 1e-6)
# Natural gas
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas", Product == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(1, tolerance = 1e-6)
# Oil and gas products
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products", Product == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.147368, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products", Product == "Kerosene type jet fuel excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.368421, tolerance = 1e-6)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products", Product == "Motor gasoline excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4842105, tolerance = 1e-6)
# All fossil fuels
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.122807, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Kerosene type jet fuel excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3070175, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Motor gasoline excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4035088, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Blast furnace gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1315789, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.0350877, tolerance = 1e-4)
# Country B
# Coal products
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products", Product == "Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1333333, tolerance = 1e-6)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products", Product == "Blast furnace gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8666667, tolerance = 1e-6)
# Natural gas
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas", Product == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(1, tolerance = 1e-6)
# Oil and gas products
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products", Product == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3125, tolerance = 1e-6)
# SECOND, WE TEST THE GMA APPROACH
tidy_AB_data_gma <- tidy_AB_data %>%
ECCTools::transform_to_gma()
tidy_AB_data_gma_prepared <- tidy_AB_data_gma %>%
prepare_gma_for_shares()
# dplyr::mutate(
# Country = stringr::str_extract(Flow, "\\{.*\\}") %>%
# stringr::str_remove("\\{") %>%
# stringr::str_remove("\\}"),
# Flow = stringr::str_remove(Flow, "\\{.*\\}_"),
# product_without_origin = stringr::str_remove(Product, "\\{.*\\}_"),
# )
res_gma <- tidy_AB_data_gma_prepared %>%
calc_share_ff_use_by_product_by_group()
# Country A tests
# Coal products
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Coal products", Product == "{A}_Blast furnace gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.7894737, tolerance = 1e-6)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Coal products", Product == "{A}_Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.08421052, tolerance = 1e-6)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Coal products", Product == "{B}_Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1263158, tolerance = 1e-6)
# Oil products
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Oil products", Product == "{A}_Kerosene type jet fuel excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.432098, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Oil products", Product == "{A}_Motor gasoline excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.567901, tolerance = 1e-6)
# Natural gas
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas", Product == "{A}_Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(1, tolerance = 1e-6)
# Oil and gas products
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products", Product == "{A}_Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.147368, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products", Product == "{A}_Kerosene type jet fuel excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.368421, tolerance = 1e-6)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products", Product == "{A}_Motor gasoline excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4842105, tolerance = 1e-6)
# All fossil fuels
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.122807, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Kerosene type jet fuel excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3070175, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Motor gasoline excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4035088, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Blast furnace gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1315789, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.01403508, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{B}_Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.02105262, tolerance = 1e-4)
# Country B
# Coal products
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Coal products", Product == "{B}_Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1333333, tolerance = 1e-6)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Coal products", Product == "{B}_Blast furnace gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8666667, tolerance = 1e-6)
# Natural gas
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas", Product == "{A}_Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(1, tolerance = 1e-6)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas", Product == "{B}_Natural gas") %>%
nrow() %>%
expect_equal(0)
# Oil and gas products
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products", Product == "{A}_Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3125, tolerance = 1e-6)
# THIRD, QUICK TEST WITH NON-ENERGY USES
tidy_AB_data_non_energy <- tidy_AB_data %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Consumption",
Flow.aggregation.point = "Industry",
Flow = IEATools::non_energy_flows$non_energy_use_industry_transformation_energy,
Product = "Coke oven coke",
Unit = "ktoe",
E.dot = 300,
matnames = "Y"
)
# Calculating energy use by product excluding non-energy uses:
res_dta_excl_non_energy <- tidy_AB_data_non_energy %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE) %>%
calc_share_ff_use_by_product_by_group()
# Checking coke oven coke
res_dta_excl_non_energy %>%
dplyr::filter(Country == "A", Product == "Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2105263, tolerance = 1e-6)
res_dta_excl_non_energy %>%
dplyr::filter(Country == "A", Product == "Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.0350877, tolerance = 1e-6)
# Calculating energy use by product including non-energy uses:
res_dta_incl_non_energy <- tidy_AB_data_non_energy %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE) %>%
calc_share_ff_use_by_product_by_group(include_non_energy_uses = TRUE)
# Checking coke oven coke
res_dta_incl_non_energy %>%
dplyr::filter(Country == "A", Product == "Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4, tolerance = 1e-6)
res_dta_incl_non_energy %>%
dplyr::filter(Country == "A", Product == "Blast furnace gas", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6, tolerance = 1e-6)
res_dta_incl_non_energy %>%
dplyr::filter(Country == "A", Product == "Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.08333333, tolerance = 1e-6)
res_dta_incl_non_energy %>%
dplyr::filter(Country == "A", Product == "Blast furnace gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.125, tolerance = 1e-6)
res_dta_incl_non_energy %>%
dplyr::filter(Country == "A", Product == "Natural gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1166667, tolerance = 1e-6)
# Trying with GMA:
tidy_AB_data_non_energy_gma <- tidy_AB_data_non_energy %>%
ECCTools::transform_to_gma()
tidy_AB_data_non_energy_gma_adapted <- tidy_AB_data_non_energy_gma %>%
prepare_gma_for_shares()
res_gma_inc_non_energy_uses <- tidy_AB_data_non_energy_gma_adapted %>%
calc_share_ff_use_by_product_by_group(include_non_energy_uses = TRUE)
# Checking coke oven coke
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{A}_Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2153846, tolerance = 1e-6)
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{B}_Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1846154, tolerance = 1e-6)
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{A}_Blast furnace gas", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6, tolerance = 1e-6)
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{A}_Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.04487179, tolerance = 1e-6)
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{B}_Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.03846154, tolerance = 1e-6)
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{A}_Blast furnace gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.125, tolerance = 1e-6)
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{A}_Natural gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1166667, tolerance = 1e-6)
})
test_that("calc_shares_elec_by_ff_group works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "EROITools")
# Loading data
tidy_AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe") %>%
IEATools::specify_all() %>%
ECCTools::specify_elect_heat_renewables() %>%
ECCTools::specify_elect_heat_fossil_fuels() %>%
ECCTools::specify_elect_heat_nuclear() %>%
ECCTools::specify_other_elec_heat_production() %>%
ECCTools::specify_elect_heat_markets() %>%
IEATools::add_psut_matnames(R_includes_all_exogenous_flows = FALSE) %>%
ECCTools::stat_diffs_to_balancing() %>%
ECCTools::stock_changes_to_balancing()
# FIRST, WE TEST THE DTA APPROACH
# Calculating total use of each product
tidy_AB_dta <- tidy_AB_data %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE)
res_dta <- tidy_AB_dta %>%
calc_shares_elec_by_ff_group()
# Testing
res_dta %>%
dplyr::filter(Product.Group == "Coal products", Product == "Electricity [from Coal products]") %>%
dplyr::select(Share) %>%
dplyr::pull() %>%
expect_equal(c(1, 1))
res_dta %>%
dplyr::filter(Product.Group == "Oil products", Product == "Electricity [from Oil products]") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Product.Group == "Natural gas", Product == "Electricity [from Natural gas]") %>%
dplyr::select(Share) %>%
dplyr::pull() %>%
expect_equal(c(1, 1))
res_dta %>%
dplyr::filter(Product.Group == "Oil and gas products", Product == "Electricity [from Natural gas]") %>%
dplyr::select(Share) %>%
dplyr::pull() %>%
expect_equal(c(1, 1))
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Electricity [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Electricity [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "Electricity [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1176471, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "Electricity [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
# SECOND, WE TEST THE GMA APPROACH
tidy_AB_data_gma <- tidy_AB_data %>%
ECCTools::transform_to_gma()
tidy_AB_data_gma_prepared <- tidy_AB_data_gma %>%
prepare_gma_for_shares()
res_gma <- tidy_AB_data_gma_prepared %>%
calc_shares_elec_by_ff_group()
# Testing
res_gma %>%
dplyr::filter(Product.Group == "Coal products", Product == "{A}_Electricity [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Product.Group == "Oil products", Product == "{A}_Electricity [from Oil products]") %>%
nrow() %>%
expect_equal(0)
res_gma %>%
dplyr::filter(Product.Group == "Natural gas", Product == "{A}_Electricity [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Product.Group == "Oil and gas products", Product == "{B}_Electricity [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Electricity [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Electricity [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "{B}_Electricity [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1176471, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "{B}_Electricity [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
})
test_that("calc_shares_heat_by_ff_group works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "EROITools")
# Loading data
tidy_AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df() %>%
IEATools::specify_all() %>%
ECCTools::specify_elect_heat_renewables() %>%
ECCTools::specify_elect_heat_fossil_fuels() %>%
ECCTools::specify_elect_heat_nuclear() %>%
ECCTools::specify_other_elec_heat_production() %>%
ECCTools::specify_elect_heat_markets() %>%
IEATools::add_psut_matnames(R_includes_all_exogenous_flows = FALSE) %>%
ECCTools::stat_diffs_to_balancing() %>%
ECCTools::stock_changes_to_balancing()
# FIRST, WE TEST THE DTA APPROACH
# Calculating total use of each product
tidy_AB_dta <- tidy_AB_data %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE)
res_dta <- tidy_AB_dta %>%
calc_shares_heat_by_ff_group()
# Testing
res_dta %>%
dplyr::filter(Product.Group == "Coal products", Product == "Heat [from Coal products]") %>%
dplyr::select(Share) %>%
dplyr::pull() %>%
expect_equal(c(1, 1))
res_dta %>%
dplyr::filter(Product.Group == "Oil products", Product == "Heat [from Oil products]") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Product.Group == "Natural gas", Product == "Heat [from Natural gas]") %>%
dplyr::select(Share) %>%
dplyr::pull() %>%
expect_equal(c(1, 1))
res_dta %>%
dplyr::filter(Product.Group == "Oil and gas products", Product == "Heat [from Natural gas]") %>%
dplyr::select(Share) %>%
dplyr::pull() %>%
expect_equal(c(1, 1))
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Heat [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Heat [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "Heat [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1176471, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "Heat [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
# SECOND, WE TEST THE GMA APPROACH
tidy_AB_data_gma <- tidy_AB_data %>%
ECCTools::transform_to_gma()
tidy_AB_data_gma_prepared <- tidy_AB_data_gma %>%
prepare_gma_for_shares()
res_gma <- tidy_AB_data_gma_prepared %>%
calc_shares_heat_by_ff_group()
# Testing
res_gma %>%
dplyr::filter(Product.Group == "Coal products", Product == "{A}_Heat [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Product.Group == "Oil products", Product == "{A}_Heat [from Oil products]") %>%
nrow() %>%
expect_equal(0)
res_gma %>%
dplyr::filter(Product.Group == "Natural gas", Product == "{A}_Heat [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Product.Group == "Oil and gas products", Product == "{B}_Heat [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Heat [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Heat [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "{B}_Heat [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1176471, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "{B}_Heat [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
})
# ADD SOME TEST WITH NON-ENERGY USES?????
test_that("calc_shares_ff_by_group_inc_elec_heat works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "EROITools")
# Loading data
tidy_AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df() %>%
IEATools::specify_all() %>%
ECCTools::specify_elect_heat_renewables() %>%
ECCTools::specify_elect_heat_fossil_fuels() %>%
ECCTools::specify_elect_heat_nuclear() %>%
ECCTools::specify_other_elec_heat_production() %>%
ECCTools::specify_elect_heat_markets() %>%
IEATools::add_psut_matnames(R_includes_all_exogenous_flows = FALSE) %>%
ECCTools::stat_diffs_to_balancing() %>%
ECCTools::stock_changes_to_balancing()
# FIRST, WE TEST THE DTA APPROACH
# Calculating total use of each product
tidy_AB_dta <- tidy_AB_data %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE)
res_dta <- tidy_AB_dta %>%
calc_shares_ff_by_group_inc_elec_heat()
# Testing
# Checking coal products shares
res_dta %>%
dplyr::filter(Country == "A", Product == "Blast furnace gas", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.200974, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.053593, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Electricity [from Coal products]", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.7015834, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Heat [from Coal products]", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.04384896, tolerance = 1e-5)
# Checking oil products shares
res_dta %>%
dplyr::filter(Country == "A", Product == "Kerosene type jet fuel excl. biofuels", Product.Group == "Oil products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.432098, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Motor gasoline excl. biofuels", Product.Group == "Oil products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.56790, tolerance = 1e-5)
# Checking natural gas shares
res_dta %>%
dplyr::filter(Country == "A", Product == "Natural gas", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.5310345, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Electricity [from Natural gas]", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4413793, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Heat [from Natural gas]", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.02758621, tolerance = 1e-5)
# Checking Oil and gas products shares
res_dta %>%
dplyr::filter(Country == "A", Product == "Natural gas", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.130398, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Kerosene type jet fuel excl. biofuels", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3259949, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Motor gasoline excl. biofuels", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4284505, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Heat [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.006773914, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Electricity [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1083827, tolerance = 1e-5)
# Checking All fossil fuels group shares
res_dta %>%
dplyr::filter(Country == "A", Product == "Natural gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.07692308, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Kerosene type jet fuel excl. biofuels", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1923077, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Motor gasoline excl. biofuels", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2527473, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Heat [from Natural gas]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.003996, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Electricity [from Natural gas]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.06393605, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Blast furnace gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.08241758, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.02197802, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Electricity [from Coal products]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2877123, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Heat [from Coal products]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.01798201, tolerance = 1e-5)
# Couple of country B tests as well:
res_dta %>%
dplyr::filter(Country == "B", Product == "Natural gas", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2300406, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product == "Heat [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.0608931, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product == "Electricity [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.202977, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product == "Kerosene type jet fuel excl. biofuels", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2300406, tolerance = 1e-5)
# SECOND, WE TEST THE GMA APPROACH
tidy_AB_data_gma <- tidy_AB_data %>%
ECCTools::transform_to_gma()
tidy_AB_data_gma_prepared <- tidy_AB_data_gma %>%
prepare_gma_for_shares()
res_gma <- tidy_AB_data_gma_prepared %>%
calc_shares_ff_by_group_inc_elec_heat()
# Testing
# Coal products
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Blast furnace gas", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.200974, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.0214372, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{B}_Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.0321558, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Electricity [from Coal products]", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.7015834, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Heat [from Coal products]", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.04384896, tolerance = 1e-5)
# Checking oil products shares
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Kerosene type jet fuel excl. biofuels", Product.Group == "Oil products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.432098, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Motor gasoline excl. biofuels", Product.Group == "Oil products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.56790, tolerance = 1e-5)
# Checking natural gas shares
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Natural gas", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.5310345, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Electricity [from Natural gas]", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4413793, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Heat [from Natural gas]", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.02758621, tolerance = 1e-5)
# Checking Oil and gas products shares
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Natural gas", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.130398, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Kerosene type jet fuel excl. biofuels", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3259949, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Motor gasoline excl. biofuels", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4284505, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Heat [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.006773914, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Electricity [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1083827, tolerance = 1e-5)
# Checking All fossil fuels group shares
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Natural gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.07692308, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Kerosene type jet fuel excl. biofuels", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1923077, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Motor gasoline excl. biofuels", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2527473, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Heat [from Natural gas]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.003996, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Electricity [from Natural gas]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.06393605, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Blast furnace gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.08241758, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.008791208, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{B}_Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.01318681, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Electricity [from Coal products]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2877123, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Heat [from Coal products]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.01798201, tolerance = 1e-5)
# Couple of country B tests as well:
res_gma %>%
dplyr::filter(Country == "B", Product == "{B}_Natural gas", Product.Group == "Oil and gas products") %>%
nrow() %>% expect_equal(0)
res_gma %>%
dplyr::filter(Country == "B", Product == "{A}_Natural gas", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2300406, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product == "{B}_Heat [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.0608931, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product == "{B}_Electricity [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.202977, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product == "{B}_Kerosene type jet fuel excl. biofuels", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2300406, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product == "{A}_Kerosene type jet fuel excl. biofuels", Product.Group == "Oil and gas products") %>%
nrow() %>% expect_equal(0)
})
test_that("prepare_gma_for_shares function works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "EROITools")
# Loading data
tidy_AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df() %>%
IEATools::specify_all() %>%
ECCTools::specify_elect_heat_renewables() %>%
ECCTools::specify_elect_heat_fossil_fuels() %>%
ECCTools::specify_elect_heat_nuclear() %>%
ECCTools::specify_other_elec_heat_production() %>%
ECCTools::specify_elect_heat_markets() %>%
IEATools::add_psut_matnames(R_includes_all_exogenous_flows = FALSE) %>%
ECCTools::stat_diffs_to_balancing() %>%
ECCTools::stock_changes_to_balancing()
# Converting to gma:
tidy_AB_data_gma <- tidy_AB_data %>%
ECCTools::transform_to_gma()
# Plain code version of df:
tidy_AB_data_gma_prepared <- tidy_AB_data_gma %>%
dplyr::mutate(
Country = stringr::str_extract(Flow, "\\{.*\\}") %>%
stringr::str_remove("\\{") %>%
stringr::str_remove("\\}"),
Flow = stringr::str_remove(Flow, "\\{.*\\}_"),
product_without_origin = stringr::str_remove(Product, "\\{.*\\}_"),
)
# Function version of df:
tidy_AB_data_gma_prepared_bis <- prepare_gma_for_shares(tidy_AB_data_gma)
# Comparing and expecting the same df:
expect_true(all(tidy_AB_data_gma_prepared == tidy_AB_data_gma_prepared_bis))
})
earamendia/EROITools documentation built on May 19, 2023, 10:30 a.m.
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test_that("calc_share_primary_ff_supply_by_product_by_group works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "EROITools")
# Loading data
tidy_AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df() %>%
IEATools::specify_all() %>%
ECCTools::specify_elect_heat_renewables() %>%
ECCTools::specify_elect_heat_fossil_fuels() %>%
ECCTools::specify_elect_heat_nuclear() %>%
ECCTools::specify_other_elec_heat_production() %>%
ECCTools::specify_elect_heat_markets() %>%
IEATools::add_psut_matnames(R_includes_all_exogenous_flows = FALSE) %>%
ECCTools::stat_diffs_to_balancing() %>%
ECCTools::stock_changes_to_balancing()
# FIRST, WE TEST THE DTA APPROACH
# Calculating total use of each product
tidy_AB_dta <- tidy_AB_data %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE)
res_dta <- tidy_AB_dta %>%
calc_share_primary_ff_supply_by_product_by_group()
# Testing
res_dta %>%
dplyr::filter(Country == "A", Product == "Coking coal", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_dta %>%
dplyr::filter(Country == "A", Product == "Crude oil", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6746032, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Natural gas", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3253968, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Coking coal", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2840909, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Crude oil", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4829545, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Natural gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2329545, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B") %>%
nrow() %>%
expect_equal(0)
# SECOND, WE TEST THE GMA APPROACH
tidy_AB_data_gma <- tidy_AB_data %>%
ECCTools::transform_to_gma()
tidy_AB_data_gma_prepared <- tidy_AB_data_gma %>%
prepare_gma_for_shares()
# dplyr::mutate(
# Country = stringr::str_extract(Flow, "\\{.*\\}") %>%
# stringr::str_remove("\\{") %>%
# stringr::str_remove("\\}"),
# Flow = stringr::str_remove(Flow, "\\{.*\\}_"),
# product_without_origin = stringr::str_remove(Product, "\\{.*\\}_"),
# )
res_gma <- tidy_AB_data_gma_prepared %>%
calc_share_primary_ff_supply_by_product_by_group()
# Testing
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Coking coal", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Crude oil", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6746032, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Natural gas", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3253968, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Coking coal", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2840909, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Crude oil", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4829545, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Natural gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2329545, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B") %>%
nrow() %>%
expect_equal(0)
})
test_that("calc_share_ff_use_by_product_by_group works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "EROITools")
#"inst/extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv"
# Loading data
tidy_AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe") %>%
IEATools::specify_all() %>%
ECCTools::specify_elect_heat_renewables() %>%
ECCTools::specify_elect_heat_fossil_fuels() %>%
ECCTools::specify_elect_heat_nuclear() %>%
ECCTools::specify_other_elec_heat_production() %>%
ECCTools::specify_elect_heat_markets() %>%
IEATools::add_psut_matnames(R_includes_all_exogenous_flows = FALSE) %>%
ECCTools::stat_diffs_to_balancing() %>%
ECCTools::stock_changes_to_balancing()
# FIRST, WE TEST THE DTA APPROACH
# Calculating total use of each product
tidy_AB_dta <- tidy_AB_data %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE)
res_dta <- tidy_AB_dta %>%
calc_share_ff_use_by_product_by_group()
# General tests:
res_dta %>%
dplyr::filter(Non_Energy_Uses == "Included") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Energy.stage != "Final (fuel)") %>%
nrow() %>%
expect_equal(0)
# Country A tests
# Coal products
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products", Product == "Blast furnace gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.7894737, tolerance = 1e-6)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products", Product == "Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2105263, tolerance = 1e-6)
# Oil products
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products", Product == "Kerosene type jet fuel excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.432098, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products", Product == "Motor gasoline excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.567901, tolerance = 1e-6)
# Natural gas
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas", Product == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(1, tolerance = 1e-6)
# Oil and gas products
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products", Product == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.147368, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products", Product == "Kerosene type jet fuel excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.368421, tolerance = 1e-6)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products", Product == "Motor gasoline excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4842105, tolerance = 1e-6)
# All fossil fuels
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.122807, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Kerosene type jet fuel excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3070175, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Motor gasoline excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4035088, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Blast furnace gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1315789, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.0350877, tolerance = 1e-4)
# Country B
# Coal products
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products", Product == "Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1333333, tolerance = 1e-6)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products", Product == "Blast furnace gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8666667, tolerance = 1e-6)
# Natural gas
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas", Product == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(1, tolerance = 1e-6)
# Oil and gas products
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products", Product == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3125, tolerance = 1e-6)
# SECOND, WE TEST THE GMA APPROACH
tidy_AB_data_gma <- tidy_AB_data %>%
ECCTools::transform_to_gma()
tidy_AB_data_gma_prepared <- tidy_AB_data_gma %>%
prepare_gma_for_shares()
# dplyr::mutate(
# Country = stringr::str_extract(Flow, "\\{.*\\}") %>%
# stringr::str_remove("\\{") %>%
# stringr::str_remove("\\}"),
# Flow = stringr::str_remove(Flow, "\\{.*\\}_"),
# product_without_origin = stringr::str_remove(Product, "\\{.*\\}_"),
# )
res_gma <- tidy_AB_data_gma_prepared %>%
calc_share_ff_use_by_product_by_group()
# Country A tests
# Coal products
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Coal products", Product == "{A}_Blast furnace gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.7894737, tolerance = 1e-6)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Coal products", Product == "{A}_Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.08421052, tolerance = 1e-6)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Coal products", Product == "{B}_Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1263158, tolerance = 1e-6)
# Oil products
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Oil products", Product == "{A}_Kerosene type jet fuel excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.432098, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Oil products", Product == "{A}_Motor gasoline excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.567901, tolerance = 1e-6)
# Natural gas
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas", Product == "{A}_Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(1, tolerance = 1e-6)
# Oil and gas products
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products", Product == "{A}_Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.147368, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products", Product == "{A}_Kerosene type jet fuel excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.368421, tolerance = 1e-6)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products", Product == "{A}_Motor gasoline excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4842105, tolerance = 1e-6)
# All fossil fuels
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.122807, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Kerosene type jet fuel excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3070175, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Motor gasoline excl. biofuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4035088, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Blast furnace gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1315789, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.01403508, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{B}_Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.02105262, tolerance = 1e-4)
# Country B
# Coal products
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Coal products", Product == "{B}_Coke oven coke") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1333333, tolerance = 1e-6)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Coal products", Product == "{B}_Blast furnace gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8666667, tolerance = 1e-6)
# Natural gas
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas", Product == "{A}_Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(1, tolerance = 1e-6)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas", Product == "{B}_Natural gas") %>%
nrow() %>%
expect_equal(0)
# Oil and gas products
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products", Product == "{A}_Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3125, tolerance = 1e-6)
# THIRD, QUICK TEST WITH NON-ENERGY USES
tidy_AB_data_non_energy <- tidy_AB_data %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Consumption",
Flow.aggregation.point = "Industry",
Flow = IEATools::non_energy_flows$non_energy_use_industry_transformation_energy,
Product = "Coke oven coke",
Unit = "ktoe",
E.dot = 300,
matnames = "Y"
)
# Calculating energy use by product excluding non-energy uses:
res_dta_excl_non_energy <- tidy_AB_data_non_energy %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE) %>%
calc_share_ff_use_by_product_by_group()
# Checking coke oven coke
res_dta_excl_non_energy %>%
dplyr::filter(Country == "A", Product == "Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2105263, tolerance = 1e-6)
res_dta_excl_non_energy %>%
dplyr::filter(Country == "A", Product == "Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.0350877, tolerance = 1e-6)
# Calculating energy use by product including non-energy uses:
res_dta_incl_non_energy <- tidy_AB_data_non_energy %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE) %>%
calc_share_ff_use_by_product_by_group(include_non_energy_uses = TRUE)
# Checking coke oven coke
res_dta_incl_non_energy %>%
dplyr::filter(Country == "A", Product == "Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4, tolerance = 1e-6)
res_dta_incl_non_energy %>%
dplyr::filter(Country == "A", Product == "Blast furnace gas", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6, tolerance = 1e-6)
res_dta_incl_non_energy %>%
dplyr::filter(Country == "A", Product == "Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.08333333, tolerance = 1e-6)
res_dta_incl_non_energy %>%
dplyr::filter(Country == "A", Product == "Blast furnace gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.125, tolerance = 1e-6)
res_dta_incl_non_energy %>%
dplyr::filter(Country == "A", Product == "Natural gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1166667, tolerance = 1e-6)
# Trying with GMA:
tidy_AB_data_non_energy_gma <- tidy_AB_data_non_energy %>%
ECCTools::transform_to_gma()
tidy_AB_data_non_energy_gma_adapted <- tidy_AB_data_non_energy_gma %>%
prepare_gma_for_shares()
res_gma_inc_non_energy_uses <- tidy_AB_data_non_energy_gma_adapted %>%
calc_share_ff_use_by_product_by_group(include_non_energy_uses = TRUE)
# Checking coke oven coke
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{A}_Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2153846, tolerance = 1e-6)
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{B}_Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1846154, tolerance = 1e-6)
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{A}_Blast furnace gas", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6, tolerance = 1e-6)
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{A}_Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.04487179, tolerance = 1e-6)
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{B}_Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.03846154, tolerance = 1e-6)
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{A}_Blast furnace gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.125, tolerance = 1e-6)
res_gma_inc_non_energy_uses %>%
dplyr::filter(Country == "A", Product == "{A}_Natural gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1166667, tolerance = 1e-6)
})
test_that("calc_shares_elec_by_ff_group works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "EROITools")
# Loading data
tidy_AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe") %>%
IEATools::specify_all() %>%
ECCTools::specify_elect_heat_renewables() %>%
ECCTools::specify_elect_heat_fossil_fuels() %>%
ECCTools::specify_elect_heat_nuclear() %>%
ECCTools::specify_other_elec_heat_production() %>%
ECCTools::specify_elect_heat_markets() %>%
IEATools::add_psut_matnames(R_includes_all_exogenous_flows = FALSE) %>%
ECCTools::stat_diffs_to_balancing() %>%
ECCTools::stock_changes_to_balancing()
# FIRST, WE TEST THE DTA APPROACH
# Calculating total use of each product
tidy_AB_dta <- tidy_AB_data %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE)
res_dta <- tidy_AB_dta %>%
calc_shares_elec_by_ff_group()
# Testing
res_dta %>%
dplyr::filter(Product.Group == "Coal products", Product == "Electricity [from Coal products]") %>%
dplyr::select(Share) %>%
dplyr::pull() %>%
expect_equal(c(1, 1))
res_dta %>%
dplyr::filter(Product.Group == "Oil products", Product == "Electricity [from Oil products]") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Product.Group == "Natural gas", Product == "Electricity [from Natural gas]") %>%
dplyr::select(Share) %>%
dplyr::pull() %>%
expect_equal(c(1, 1))
res_dta %>%
dplyr::filter(Product.Group == "Oil and gas products", Product == "Electricity [from Natural gas]") %>%
dplyr::select(Share) %>%
dplyr::pull() %>%
expect_equal(c(1, 1))
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Electricity [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Electricity [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "Electricity [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1176471, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "Electricity [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
# SECOND, WE TEST THE GMA APPROACH
tidy_AB_data_gma <- tidy_AB_data %>%
ECCTools::transform_to_gma()
tidy_AB_data_gma_prepared <- tidy_AB_data_gma %>%
prepare_gma_for_shares()
res_gma <- tidy_AB_data_gma_prepared %>%
calc_shares_elec_by_ff_group()
# Testing
res_gma %>%
dplyr::filter(Product.Group == "Coal products", Product == "{A}_Electricity [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Product.Group == "Oil products", Product == "{A}_Electricity [from Oil products]") %>%
nrow() %>%
expect_equal(0)
res_gma %>%
dplyr::filter(Product.Group == "Natural gas", Product == "{A}_Electricity [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Product.Group == "Oil and gas products", Product == "{B}_Electricity [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Electricity [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Electricity [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "{B}_Electricity [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1176471, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "{B}_Electricity [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
})
test_that("calc_shares_heat_by_ff_group works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "EROITools")
# Loading data
tidy_AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df() %>%
IEATools::specify_all() %>%
ECCTools::specify_elect_heat_renewables() %>%
ECCTools::specify_elect_heat_fossil_fuels() %>%
ECCTools::specify_elect_heat_nuclear() %>%
ECCTools::specify_other_elec_heat_production() %>%
ECCTools::specify_elect_heat_markets() %>%
IEATools::add_psut_matnames(R_includes_all_exogenous_flows = FALSE) %>%
ECCTools::stat_diffs_to_balancing() %>%
ECCTools::stock_changes_to_balancing()
# FIRST, WE TEST THE DTA APPROACH
# Calculating total use of each product
tidy_AB_dta <- tidy_AB_data %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE)
res_dta <- tidy_AB_dta %>%
calc_shares_heat_by_ff_group()
# Testing
res_dta %>%
dplyr::filter(Product.Group == "Coal products", Product == "Heat [from Coal products]") %>%
dplyr::select(Share) %>%
dplyr::pull() %>%
expect_equal(c(1, 1))
res_dta %>%
dplyr::filter(Product.Group == "Oil products", Product == "Heat [from Oil products]") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Product.Group == "Natural gas", Product == "Heat [from Natural gas]") %>%
dplyr::select(Share) %>%
dplyr::pull() %>%
expect_equal(c(1, 1))
res_dta %>%
dplyr::filter(Product.Group == "Oil and gas products", Product == "Heat [from Natural gas]") %>%
dplyr::select(Share) %>%
dplyr::pull() %>%
expect_equal(c(1, 1))
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Heat [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "Heat [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "Heat [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1176471, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "Heat [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
# SECOND, WE TEST THE GMA APPROACH
tidy_AB_data_gma <- tidy_AB_data %>%
ECCTools::transform_to_gma()
tidy_AB_data_gma_prepared <- tidy_AB_data_gma %>%
prepare_gma_for_shares()
res_gma <- tidy_AB_data_gma_prepared %>%
calc_shares_heat_by_ff_group()
# Testing
res_gma %>%
dplyr::filter(Product.Group == "Coal products", Product == "{A}_Heat [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Product.Group == "Oil products", Product == "{A}_Heat [from Oil products]") %>%
nrow() %>%
expect_equal(0)
res_gma %>%
dplyr::filter(Product.Group == "Natural gas", Product == "{A}_Heat [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Product.Group == "Oil and gas products", Product == "{B}_Heat [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(1)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Heat [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels", Product == "{A}_Heat [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "{B}_Heat [from Coal products]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1176471, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels", Product == "{B}_Heat [from Natural gas]") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
})
# ADD SOME TEST WITH NON-ENERGY USES?????
test_that("calc_shares_ff_by_group_inc_elec_heat works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "EROITools")
# Loading data
tidy_AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df() %>%
IEATools::specify_all() %>%
ECCTools::specify_elect_heat_renewables() %>%
ECCTools::specify_elect_heat_fossil_fuels() %>%
ECCTools::specify_elect_heat_nuclear() %>%
ECCTools::specify_other_elec_heat_production() %>%
ECCTools::specify_elect_heat_markets() %>%
IEATools::add_psut_matnames(R_includes_all_exogenous_flows = FALSE) %>%
ECCTools::stat_diffs_to_balancing() %>%
ECCTools::stock_changes_to_balancing()
# FIRST, WE TEST THE DTA APPROACH
# Calculating total use of each product
tidy_AB_dta <- tidy_AB_data %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE)
res_dta <- tidy_AB_dta %>%
calc_shares_ff_by_group_inc_elec_heat()
# Testing
# Checking coal products shares
res_dta %>%
dplyr::filter(Country == "A", Product == "Blast furnace gas", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.200974, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.053593, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Electricity [from Coal products]", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.7015834, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Heat [from Coal products]", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.04384896, tolerance = 1e-5)
# Checking oil products shares
res_dta %>%
dplyr::filter(Country == "A", Product == "Kerosene type jet fuel excl. biofuels", Product.Group == "Oil products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.432098, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Motor gasoline excl. biofuels", Product.Group == "Oil products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.56790, tolerance = 1e-5)
# Checking natural gas shares
res_dta %>%
dplyr::filter(Country == "A", Product == "Natural gas", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.5310345, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Electricity [from Natural gas]", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4413793, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Heat [from Natural gas]", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.02758621, tolerance = 1e-5)
# Checking Oil and gas products shares
res_dta %>%
dplyr::filter(Country == "A", Product == "Natural gas", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.130398, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Kerosene type jet fuel excl. biofuels", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3259949, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Motor gasoline excl. biofuels", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4284505, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Heat [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.006773914, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Electricity [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1083827, tolerance = 1e-5)
# Checking All fossil fuels group shares
res_dta %>%
dplyr::filter(Country == "A", Product == "Natural gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.07692308, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Kerosene type jet fuel excl. biofuels", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1923077, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Motor gasoline excl. biofuels", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2527473, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Heat [from Natural gas]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.003996, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Electricity [from Natural gas]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.06393605, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Blast furnace gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.08241758, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.02197802, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Electricity [from Coal products]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2877123, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product == "Heat [from Coal products]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.01798201, tolerance = 1e-5)
# Couple of country B tests as well:
res_dta %>%
dplyr::filter(Country == "B", Product == "Natural gas", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2300406, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product == "Heat [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.0608931, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product == "Electricity [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.202977, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product == "Kerosene type jet fuel excl. biofuels", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2300406, tolerance = 1e-5)
# SECOND, WE TEST THE GMA APPROACH
tidy_AB_data_gma <- tidy_AB_data %>%
ECCTools::transform_to_gma()
tidy_AB_data_gma_prepared <- tidy_AB_data_gma %>%
prepare_gma_for_shares()
res_gma <- tidy_AB_data_gma_prepared %>%
calc_shares_ff_by_group_inc_elec_heat()
# Testing
# Coal products
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Blast furnace gas", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.200974, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.0214372, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{B}_Coke oven coke", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.0321558, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Electricity [from Coal products]", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.7015834, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Heat [from Coal products]", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.04384896, tolerance = 1e-5)
# Checking oil products shares
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Kerosene type jet fuel excl. biofuels", Product.Group == "Oil products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.432098, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Motor gasoline excl. biofuels", Product.Group == "Oil products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.56790, tolerance = 1e-5)
# Checking natural gas shares
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Natural gas", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.5310345, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Electricity [from Natural gas]", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4413793, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Heat [from Natural gas]", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.02758621, tolerance = 1e-5)
# Checking Oil and gas products shares
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Natural gas", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.130398, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Kerosene type jet fuel excl. biofuels", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.3259949, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Motor gasoline excl. biofuels", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.4284505, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Heat [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.006773914, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Electricity [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1083827, tolerance = 1e-5)
# Checking All fossil fuels group shares
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Natural gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.07692308, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Kerosene type jet fuel excl. biofuels", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1923077, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Motor gasoline excl. biofuels", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2527473, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Heat [from Natural gas]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.003996, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Electricity [from Natural gas]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.06393605, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Blast furnace gas", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.08241758, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.008791208, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{B}_Coke oven coke", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.01318681, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Electricity [from Coal products]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2877123, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product == "{A}_Heat [from Coal products]", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.01798201, tolerance = 1e-5)
# Couple of country B tests as well:
res_gma %>%
dplyr::filter(Country == "B", Product == "{B}_Natural gas", Product.Group == "Oil and gas products") %>%
nrow() %>% expect_equal(0)
res_gma %>%
dplyr::filter(Country == "B", Product == "{A}_Natural gas", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2300406, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product == "{B}_Heat [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.0608931, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product == "{B}_Electricity [from Natural gas]", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.202977, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product == "{B}_Kerosene type jet fuel excl. biofuels", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.2300406, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product == "{A}_Kerosene type jet fuel excl. biofuels", Product.Group == "Oil and gas products") %>%
nrow() %>% expect_equal(0)
})
test_that("prepare_gma_for_shares function works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "EROITools")
# Loading data
tidy_AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df() %>%
IEATools::specify_all() %>%
ECCTools::specify_elect_heat_renewables() %>%
ECCTools::specify_elect_heat_fossil_fuels() %>%
ECCTools::specify_elect_heat_nuclear() %>%
ECCTools::specify_other_elec_heat_production() %>%
ECCTools::specify_elect_heat_markets() %>%
IEATools::add_psut_matnames(R_includes_all_exogenous_flows = FALSE) %>%
ECCTools::stat_diffs_to_balancing() %>%
ECCTools::stock_changes_to_balancing()
# Converting to gma:
tidy_AB_data_gma <- tidy_AB_data %>%
ECCTools::transform_to_gma()
# Plain code version of df:
tidy_AB_data_gma_prepared <- tidy_AB_data_gma %>%
dplyr::mutate(
Country = stringr::str_extract(Flow, "\\{.*\\}") %>%
stringr::str_remove("\\{") %>%
stringr::str_remove("\\}"),
Flow = stringr::str_remove(Flow, "\\{.*\\}_"),
product_without_origin = stringr::str_remove(Product, "\\{.*\\}_"),
)
# Function version of df:
tidy_AB_data_gma_prepared_bis <- prepare_gma_for_shares(tidy_AB_data_gma)
# Comparing and expecting the same df:
expect_true(all(tidy_AB_data_gma_prepared == tidy_AB_data_gma_prepared_bis))
})
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