tests/testthat/test_others.R
In earamendia/EROITools: EROITools
test_that("calc_fec_from_ff_as_elec_by_group",{
# 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_fec_from_ff_as_elec_by_group()
# Testing
res_dta %>%
dplyr::filter(! matnames %in% c("Y", "U_EIOU")) %>%
nrow() %>%
expect_equal(0)
# Country A, Iron and steel:
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2920)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(530.9091, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(530.9091, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2389.091, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
# Country A, Coal mines
res_dta %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(20)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3.636364, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3.636364, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(16.36364, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
# Country B, Iron and steel
res_dta %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(300)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(264.7059, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(264.7059, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(35.29412, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Oil products") %>%
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()
res_gma <- tidy_AB_data_gma_prepared %>%
calc_fec_from_ff_as_elec_by_group()
# Testing
# Country A, Iron and steel:
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2920)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(530.9091, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(530.9091, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2389.091, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
# Country A, Coal mines
res_gma %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(20)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3.636364, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3.636364, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(16.36364, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
# Country B, Iron and steel
res_gma %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(300)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(264.7059, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(264.7059, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(35.29412, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
})
test_that("calc_share_elec_supply_by_ff_group",{
# 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_elec_supply_by_ff_group()
# Testing
res_dta %>%
dplyr::filter(Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Product.Group == "All fossil fuels") %>%
dplyr::ungroup() %>% dplyr::select(Share) %>% dplyr::pull() %>%
expect_equal(c(1,1))
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1176471, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "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_share_elec_supply_by_ff_group()
# Testing
res_gma %>%
dplyr::filter(Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_gma %>%
dplyr::filter(Product.Group == "All fossil fuels") %>%
dplyr::ungroup() %>% dplyr::select(Share) %>% dplyr::pull() %>%
expect_equal(c(1,1))
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1176471, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
})
test_that("calc_fec_from_ff_as_heat_by_group",{
# 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_fec_from_ff_as_heat_by_group()
# Testing; first country A iron and steel
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(40)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(7.272727, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(7.272727, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(32.72727, tolerance = 1e-5)
# Second country A, oil refineries
res_dta %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(80)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(14.54545, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(14.54545, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(65.45455, tolerance = 1e-4)
# Third country B, oil refineries
res_dta %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(60)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(52.94118, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(52.94118, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(7.058824, 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_fec_from_ff_as_heat_by_group()
# Testing; first country A iron and steel
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(40)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(7.272727, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(7.272727, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(32.72727, tolerance = 1e-5)
# Second country A, oil refineries
res_gma %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(80)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(14.54545, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(14.54545, tolerance = 1e4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(65.45455, tolerance = 1e-4)
# Third country B, oil refineries
res_gma %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(60)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(52.94118, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(52.94118, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(7.058824, tolerance = 1e-5)
})
test_that("calc_share_heat_supply_by_ff_group",{
# 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_heat_supply_by_ff_group()
# Country A
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1454545, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1454545, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6545455, tolerance = 1e-5)
# Country B
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.5294118, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.5294118, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.07058824, 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_share_heat_supply_by_ff_group()
# Country A
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1454545, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1454545, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6545455, tolerance = 1e-4)
# Country B
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.5294118, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.5294118, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.07058824, tolerance = 1e-5)
})
test_that("calc_fec_from_ff_by_group",{
# 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_fec_from_ff_by_group()
# Note that heat coming out of oil refineries is defined as Heat [from Other processes]!!! so not coming from FF. Hence the values.
# Country A:
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(9100)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3731.81818, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(1318.181818, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(1318.181818+4050, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4050)
# Country B:
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(5250)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(750+152.9412, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2147.059, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2200+2147.059, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2200)
# 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_fec_from_ff_by_group()
# Note that heat coming out of oil refineries is defined as Heat [from Other processes]!!! so not coming from FF. Hence the values.
# Country A:
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(9100)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3731.81818, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(1318.181818, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(1318.181818+4050, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4050)
# Country B:
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(5250)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(750+152.9412, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2147.059, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2200+2147.059, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2200)
})
test_that("calc_fec_from_ff_as_fuel_by_group",{
# 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_fec_from_ff_as_fuel_by_group()
# Country A:
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(5700)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(950)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(700)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4750)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4050)
# Country B:
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3950)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(750)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(1000)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3200)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2200)
# Quick test for including non-energy uses
res_dta_non_energy_uses <- tidy_AB_dta %>%
calc_fec_from_ff_as_fuel_by_group(include_non_energy_uses = TRUE)
# Country A:
res_dta_non_energy_uses %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(5700)
res_dta_non_energy_uses %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(950)
res_dta_non_energy_uses %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(700)
res_dta_non_energy_uses %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4750)
res_dta_non_energy_uses %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4050)
# 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_fec_from_ff_as_fuel_by_group()
# Country A:
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(5700)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(950)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(700)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4750)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4050)
# Country B:
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3950)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(750)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(1000)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3200)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2200)
})
test_that("calc_share_elec_supply_by_ff_group works with losses",{
# 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") %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Supply",
Flow.aggregation.point = "TFC compare",
Flow = "Losses",
Product = "Electricity",
Unit = "ktoe",
E.dot = -50
) %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Supply",
Flow.aggregation.point = "Transformation processes",
Flow = "A balancing industry",
Product = "Electricity",
Unit = "ktoe",
E.dot = 50
) %>%
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() %>%
ECCTools::specify_losses_as_industry()
# 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_elec_supply_by_ff_group()
# Testing
res_dta %>%
dplyr::filter(Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Product.Group == "All fossil fuels") %>%
dplyr::ungroup() %>% dplyr::select(Share) %>% dplyr::pull() %>%
expect_equal(c(0.9846154,1), tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8055944, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.179021, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.179021, tolerance = 1e-5)
# Useless because no change in country B's ECC
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.1176471, tolerance = 1e-5)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.8823529, tolerance = 1e-5)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.8823529, tolerance = 1e-5)
# Only A because this is the country that changes
# This time we add losses without increasing supply
tidy_A_data_bis <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe") %>%
dplyr::filter(Country == "A") %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Supply",
Flow.aggregation.point = "TFC compare",
Flow = "Losses",
Product = "Electricity",
Unit = "ktoe",
E.dot = -50
) %>%
# reducing consumption as 50 goes to losses
dplyr::mutate(
E.dot = dplyr::case_when(
(Flow == "Iron and steel" & Product == "Electricity") ~ 2870,
TRUE ~ E.dot
)
) %>%
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() %>%
ECCTools::specify_losses_as_industry()
# Calcs
tidy_A_dta_bis <- tidy_A_data_bis %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE)
res_dta_bis <- tidy_A_dta_bis %>%
calc_share_elec_supply_by_ff_group()
# Testing:
res_dta_bis %>%
dplyr::filter(Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta_bis %>%
dplyr::filter(Product.Group == "All fossil fuels") %>%
dplyr::ungroup() %>% dplyr::select(Share) %>% dplyr::pull() %>%
expect_equal(1)
res_dta_bis %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_dta_bis %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_dta_bis %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
# SECOND, WE TEST THE GMA APPROACH
# THE LOSSES APPROACH IS NOT YET IMPLEMENTED AT THE COUNTRY LEVEL!!!
# 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_share_elec_supply_by_ff_group()
# Testing
# res_gma %>%
# dplyr::filter(Product.Group == "Oil products") %>%
# nrow() %>%
# expect_equal(0)
# res_gma %>%
# dplyr::filter(Product.Group == "All fossil fuels") %>%
# dplyr::ungroup() %>% dplyr::select(Share) %>% dplyr::pull() %>%
# expect_equal(c(1,1))
# res_gma %>%
# dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.8181818, tolerance = 1e-5)
# res_gma %>%
# dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.1818182, tolerance = 1e-5)
# res_gma %>%
# dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.1818182, tolerance = 1e-5)
# res_gma %>%
# dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.1176471, tolerance = 1e-5)
# res_gma %>%
# dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.8823529, tolerance = 1e-5)
# res_gma %>%
# dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.8823529, tolerance = 1e-5)
})
test_that("calc_share_heat_supply_by_ff_group works with losses modelling",{
# 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") %>%
dplyr::filter(Country == "A") %>%
# Adding losses of Heat
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Supply",
Flow.aggregation.point = "TFC compare",
Flow = "Losses",
Product = "Heat",
Unit = "ktoe",
E.dot = -10
) %>%
dplyr::mutate(
E.dot = dplyr::case_when(
(Flow == "Iron and steel" & Product == "Heat") ~ 40,
TRUE ~ E.dot
)
) %>%
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() %>%
ECCTools::specify_losses_as_industry()
# 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_heat_supply_by_ff_group()
# Country A
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1454545, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1454545, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6545455, tolerance = 1e-5)
# Country B
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.6)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
# nrow() %>%
# expect_equal(0)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.5294118, tolerance = 1e-5)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.5294118, tolerance = 1e-5)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.07058824, tolerance = 1e-5)
# SECOND, WE TEST THE GMA APPROACH
# NOTE THAT LOSSES MODELLING IS NOT IMPLEMENTED YET FOR COUNTRY LEVEL!!
# 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_share_heat_supply_by_ff_group()
# Country A
# res_dta %>%
# dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.8)
# res_dta %>%
# dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
# nrow() %>%
# expect_equal(0)
# res_dta %>%
# dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.1454545, tolerance = 1e-4)
# res_dta %>%
# dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.1454545, tolerance = 1e-4)
# res_dta %>%
# dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.6545455, tolerance = 1e-4)
# Country B
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.6)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
# nrow() %>%
# expect_equal(0)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.5294118, tolerance = 1e-5)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.5294118, tolerance = 1e-5)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.07058824, tolerance = 1e-5)
})
earamendia/EROITools documentation built on May 19, 2023, 10:30 a.m.
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test_that("calc_fec_from_ff_as_elec_by_group",{
# 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_fec_from_ff_as_elec_by_group()
# Testing
res_dta %>%
dplyr::filter(! matnames %in% c("Y", "U_EIOU")) %>%
nrow() %>%
expect_equal(0)
# Country A, Iron and steel:
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2920)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(530.9091, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(530.9091, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2389.091, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
# Country A, Coal mines
res_dta %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(20)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3.636364, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3.636364, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(16.36364, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
# Country B, Iron and steel
res_dta %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(300)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(264.7059, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(264.7059, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(35.29412, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Oil products") %>%
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()
res_gma <- tidy_AB_data_gma_prepared %>%
calc_fec_from_ff_as_elec_by_group()
# Testing
# Country A, Iron and steel:
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2920)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(530.9091, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(530.9091, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2389.091, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
# Country A, Coal mines
res_gma %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(20)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3.636364, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3.636364, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(16.36364, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Coal mines", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
# Country B, Iron and steel
res_gma %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(300)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(264.7059, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(264.7059, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(35.29412, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Iron and steel", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
})
test_that("calc_share_elec_supply_by_ff_group",{
# 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_elec_supply_by_ff_group()
# Testing
res_dta %>%
dplyr::filter(Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Product.Group == "All fossil fuels") %>%
dplyr::ungroup() %>% dplyr::select(Share) %>% dplyr::pull() %>%
expect_equal(c(1,1))
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1176471, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "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_share_elec_supply_by_ff_group()
# Testing
res_gma %>%
dplyr::filter(Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_gma %>%
dplyr::filter(Product.Group == "All fossil fuels") %>%
dplyr::ungroup() %>% dplyr::select(Share) %>% dplyr::pull() %>%
expect_equal(c(1,1))
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1176471, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8823529, tolerance = 1e-5)
})
test_that("calc_fec_from_ff_as_heat_by_group",{
# 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_fec_from_ff_as_heat_by_group()
# Testing; first country A iron and steel
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(40)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(7.272727, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(7.272727, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(32.72727, tolerance = 1e-5)
# Second country A, oil refineries
res_dta %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(80)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(14.54545, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(14.54545, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(65.45455, tolerance = 1e-4)
# Third country B, oil refineries
res_dta %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(60)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(52.94118, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(52.94118, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(7.058824, 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_fec_from_ff_as_heat_by_group()
# Testing; first country A iron and steel
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(40)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(7.272727, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(7.272727, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Iron and steel", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(32.72727, tolerance = 1e-5)
# Second country A, oil refineries
res_gma %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(80)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(14.54545, tolerance = 1e-4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(14.54545, tolerance = 1e4)
res_gma %>%
dplyr::filter(Country == "A", Flow == "Oil refineries", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(65.45455, tolerance = 1e-4)
# Third country B, oil refineries
res_gma %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(60)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(52.94118, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(52.94118, tolerance = 1e-5)
res_gma %>%
dplyr::filter(Country == "B", Flow == "Oil refineries", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(7.058824, tolerance = 1e-5)
})
test_that("calc_share_heat_supply_by_ff_group",{
# 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_heat_supply_by_ff_group()
# Country A
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1454545, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1454545, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6545455, tolerance = 1e-5)
# Country B
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.5294118, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.5294118, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.07058824, 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_share_heat_supply_by_ff_group()
# Country A
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1454545, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1454545, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6545455, tolerance = 1e-4)
# Country B
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.5294118, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.5294118, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.07058824, tolerance = 1e-5)
})
test_that("calc_fec_from_ff_by_group",{
# 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_fec_from_ff_by_group()
# Note that heat coming out of oil refineries is defined as Heat [from Other processes]!!! so not coming from FF. Hence the values.
# Country A:
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(9100)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3731.81818, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(1318.181818, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(1318.181818+4050, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4050)
# Country B:
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(5250)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(750+152.9412, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2147.059, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2200+2147.059, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2200)
# 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_fec_from_ff_by_group()
# Note that heat coming out of oil refineries is defined as Heat [from Other processes]!!! so not coming from FF. Hence the values.
# Country A:
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(9100)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3731.81818, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(1318.181818, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(1318.181818+4050, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4050)
# Country B:
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(5250)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(750+152.9412, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2147.059, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2200+2147.059, tolerance = 1e-4)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2200)
})
test_that("calc_fec_from_ff_as_fuel_by_group",{
# 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_fec_from_ff_as_fuel_by_group()
# Country A:
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(5700)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(950)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(700)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4750)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4050)
# Country B:
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3950)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(750)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(1000)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3200)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2200)
# Quick test for including non-energy uses
res_dta_non_energy_uses <- tidy_AB_dta %>%
calc_fec_from_ff_as_fuel_by_group(include_non_energy_uses = TRUE)
# Country A:
res_dta_non_energy_uses %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(5700)
res_dta_non_energy_uses %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(950)
res_dta_non_energy_uses %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(700)
res_dta_non_energy_uses %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4750)
res_dta_non_energy_uses %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4050)
# 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_fec_from_ff_as_fuel_by_group()
# Country A:
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(5700)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(950)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(700)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4750)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(4050)
# Country B:
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3950)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(750)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
magrittr::extract2("E.dot") %>%
expect_equal(1000)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(3200)
res_dta %>%
dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
magrittr::extract2("E.dot") %>%
expect_equal(2200)
})
test_that("calc_share_elec_supply_by_ff_group works with losses",{
# 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") %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Supply",
Flow.aggregation.point = "TFC compare",
Flow = "Losses",
Product = "Electricity",
Unit = "ktoe",
E.dot = -50
) %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Supply",
Flow.aggregation.point = "Transformation processes",
Flow = "A balancing industry",
Product = "Electricity",
Unit = "ktoe",
E.dot = 50
) %>%
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() %>%
ECCTools::specify_losses_as_industry()
# 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_elec_supply_by_ff_group()
# Testing
res_dta %>%
dplyr::filter(Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Product.Group == "All fossil fuels") %>%
dplyr::ungroup() %>% dplyr::select(Share) %>% dplyr::pull() %>%
expect_equal(c(0.9846154,1), tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8055944, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.179021, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.179021, tolerance = 1e-5)
# Useless because no change in country B's ECC
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.1176471, tolerance = 1e-5)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.8823529, tolerance = 1e-5)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.8823529, tolerance = 1e-5)
# Only A because this is the country that changes
# This time we add losses without increasing supply
tidy_A_data_bis <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe") %>%
dplyr::filter(Country == "A") %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Supply",
Flow.aggregation.point = "TFC compare",
Flow = "Losses",
Product = "Electricity",
Unit = "ktoe",
E.dot = -50
) %>%
# reducing consumption as 50 goes to losses
dplyr::mutate(
E.dot = dplyr::case_when(
(Flow == "Iron and steel" & Product == "Electricity") ~ 2870,
TRUE ~ E.dot
)
) %>%
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() %>%
ECCTools::specify_losses_as_industry()
# Calcs
tidy_A_dta_bis <- tidy_A_data_bis %>%
ECCTools::transform_to_dta(requirement_matrices_list = c("U_feed"),
select_dta_observations = FALSE)
res_dta_bis <- tidy_A_dta_bis %>%
calc_share_elec_supply_by_ff_group()
# Testing:
res_dta_bis %>%
dplyr::filter(Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta_bis %>%
dplyr::filter(Product.Group == "All fossil fuels") %>%
dplyr::ungroup() %>% dplyr::select(Share) %>% dplyr::pull() %>%
expect_equal(1)
res_dta_bis %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8181818, tolerance = 1e-5)
res_dta_bis %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
res_dta_bis %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1818182, tolerance = 1e-5)
# SECOND, WE TEST THE GMA APPROACH
# THE LOSSES APPROACH IS NOT YET IMPLEMENTED AT THE COUNTRY LEVEL!!!
# 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_share_elec_supply_by_ff_group()
# Testing
# res_gma %>%
# dplyr::filter(Product.Group == "Oil products") %>%
# nrow() %>%
# expect_equal(0)
# res_gma %>%
# dplyr::filter(Product.Group == "All fossil fuels") %>%
# dplyr::ungroup() %>% dplyr::select(Share) %>% dplyr::pull() %>%
# expect_equal(c(1,1))
# res_gma %>%
# dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.8181818, tolerance = 1e-5)
# res_gma %>%
# dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.1818182, tolerance = 1e-5)
# res_gma %>%
# dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.1818182, tolerance = 1e-5)
# res_gma %>%
# dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.1176471, tolerance = 1e-5)
# res_gma %>%
# dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.8823529, tolerance = 1e-5)
# res_gma %>%
# dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.8823529, tolerance = 1e-5)
})
test_that("calc_share_heat_supply_by_ff_group works with losses modelling",{
# 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") %>%
dplyr::filter(Country == "A") %>%
# Adding losses of Heat
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Supply",
Flow.aggregation.point = "TFC compare",
Flow = "Losses",
Product = "Heat",
Unit = "ktoe",
E.dot = -10
) %>%
dplyr::mutate(
E.dot = dplyr::case_when(
(Flow == "Iron and steel" & Product == "Heat") ~ 40,
TRUE ~ E.dot
)
) %>%
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() %>%
ECCTools::specify_losses_as_industry()
# 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_heat_supply_by_ff_group()
# Country A
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
magrittr::extract2("Share") %>%
expect_equal(0.8)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
nrow() %>%
expect_equal(0)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1454545, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
magrittr::extract2("Share") %>%
expect_equal(0.1454545, tolerance = 1e-5)
res_dta %>%
dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
magrittr::extract2("Share") %>%
expect_equal(0.6545455, tolerance = 1e-5)
# Country B
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.6)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
# nrow() %>%
# expect_equal(0)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.5294118, tolerance = 1e-5)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.5294118, tolerance = 1e-5)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.07058824, tolerance = 1e-5)
# SECOND, WE TEST THE GMA APPROACH
# NOTE THAT LOSSES MODELLING IS NOT IMPLEMENTED YET FOR COUNTRY LEVEL!!
# 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_share_heat_supply_by_ff_group()
# Country A
# res_dta %>%
# dplyr::filter(Country == "A", Product.Group == "All fossil fuels") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.8)
# res_dta %>%
# dplyr::filter(Country == "A", Product.Group == "Oil products") %>%
# nrow() %>%
# expect_equal(0)
# res_dta %>%
# dplyr::filter(Country == "A", Product.Group == "Oil and gas products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.1454545, tolerance = 1e-4)
# res_dta %>%
# dplyr::filter(Country == "A", Product.Group == "Natural gas") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.1454545, tolerance = 1e-4)
# res_dta %>%
# dplyr::filter(Country == "A", Product.Group == "Coal products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.6545455, tolerance = 1e-4)
# Country B
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "All fossil fuels") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.6)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Oil products") %>%
# nrow() %>%
# expect_equal(0)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Oil and gas products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.5294118, tolerance = 1e-5)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Natural gas") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.5294118, tolerance = 1e-5)
# res_dta %>%
# dplyr::filter(Country == "B", Product.Group == "Coal products") %>%
# magrittr::extract2("Share") %>%
# expect_equal(0.07058824, tolerance = 1e-5)
})
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