tests/testthat/test-cleans.R
In earamendia/ECCTools: ECCTools Assists With Energy Conversion Chain Analysis
###########################################################
context("Cleaning up PSUT")
###########################################################
# Testing convert_to_net_trade function:
test_that("convert_to_net_trade works", {
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format.csv", package = "ECCTools")
# Loading AB_data
AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe")
# Adding a couple of rows for having both imports and exports
dummy_net_trade <- tibble::tribble(
~Country, ~Method, ~Energy.type, ~Last.stage, ~Year, ~Ledger.side, ~Flow.aggregation.point, ~Flow, ~Product, ~Unit, ~E.dot,
"A", "PCM", "E", "Final", 2018, "Supply", "Total primary energy supply", "Imports", "Coking coal", "ktoe", 840,
"A", "PCM", "E", "Final", 2018, "Supply", "Total primary energy supply", "Imports", "Natural gas", "ktoe", 1100,
"A", "PCM", "E", "Final", 2018, "Supply", "Total primary energy supply", "Imports", "Crude oil", "ktoe", 4000,
"B", "PCM", "E", "Final", 2018, "Supply", "Total primary energy supply", "Imports", "Coke oven coke", "ktoe", 600,
"A", "PCM", "E", "Final", 2018, "Supply", "Total primary energy supply", "Exports", "Coke oven coke", "ktoe", -1400,
)
AB_net_trade_testing <- AB_data %>%
dplyr::bind_rows(dummy_net_trade) %>%
IEATools::specify_all()
# First test, that shouldn't change the data frame at all
test_unchanged_df <- convert_to_net_trade(AB_data %>%
IEATools::specify_all())
checking_row_equality <- dplyr::left_join(AB_data %>%
IEATools::specify_all(),
test_unchanged_df,
by = c("Country", "Method", "Energy.type", "Last.stage", "Year", "Ledger.side", "Flow.aggregation.point", "Flow", "Product", "Unit")) %>%
dplyr::mutate(
diff = E.dot.x - E.dot.y
) %>%
dplyr::summarise(max_diff = max(abs(diff))) %>%
dplyr::pull()
expect_equal(checking_row_equality, 0)
# Second test, that should change the data frame where there are both imports and exports
test_changed_df <- convert_to_net_trade(AB_net_trade_testing)
checking_row_equality <- dplyr::left_join(AB_data %>%
IEATools::specify_all(),
test_changed_df,
by = c("Country", "Method", "Energy.type", "Last.stage", "Year", "Ledger.side", "Flow.aggregation.point", "Flow", "Product", "Unit")) %>%
dplyr::mutate(
diff = E.dot.x - E.dot.y
) %>%
dplyr::filter(! (stringr::str_detect(Flow, "Imports") | stringr::str_detect(Flow, "Exports"))) %>%
dplyr::summarise(max_diff = max(abs(diff))) %>%
dplyr::pull()
expect_equal(checking_row_equality, 0)
check_trade <- test_changed_df %>%
dplyr::filter(stringr::str_detect(Flow, "Imports") | stringr::str_detect(Flow, "Exports"))
expect_equal(check_trade[[1, "E.dot"]], -800)
expect_equal(check_trade[[1, "Flow"]], "Exports [of Coke oven coke]")
expect_equal(check_trade[[2, "E.dot"]], -1160)
expect_equal(check_trade[[2, "Flow"]], "Exports [of Coking coal]")
expect_equal(check_trade[[3, "E.dot"]], 500)
expect_equal(check_trade[[3, "Flow"]], "Imports [of Crude oil]")
expect_equal(check_trade[[4, "E.dot"]], -1400)
expect_equal(check_trade[[4, "Flow"]], "Exports [of Natural gas]")
expect_equal(check_trade[[5, "E.dot"]], 200)
expect_equal(check_trade[[5, "Flow"]], "Imports [of Coke oven coke]")
expect_equal(check_trade[[8, "E.dot"]], 2500)
expect_equal(check_trade[[8, "Flow"]], "Imports [of Natural gas]")
})
# Testing stat_diffs_to_balancing:
test_that("stat_diffs_to_balancing works",{
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "ECCTools")
AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe")
AB_data_specified <- AB_data %>%
IEATools::specify_all()
AB_data_stat_diffs_to_balancing <- AB_data_specified %>%
IEATools::add_psut_matnames() %>%
stat_diffs_to_balancing()
expect_equal(AB_data_stat_diffs_to_balancing[1,] %>%
dplyr::select(E.dot) %>%
dplyr::pull(),
500)
stat_diffs_flows <- AB_data_stat_diffs_to_balancing %>%
dplyr::filter(Flow == "Statistical differences")
expect_equal(stat_diffs_flows[1,] %>%
dplyr::select(matnames) %>%
dplyr::pull(),
"B")
expect_equal(stat_diffs_flows[1,] %>%
dplyr::select(E.dot) %>%
dplyr::pull(),
10)
expect_equal(stat_diffs_flows[2,] %>%
dplyr::select(matnames) %>%
dplyr::pull(),
"B")
expect_equal(stat_diffs_flows[2,] %>%
dplyr::select(E.dot) %>%
dplyr::pull(),
-10)
})
# Testing stock_changes_to_balancing:
test_that("stock_changes_to_balancing works",{
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "ECCTools")
AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe")
AB_data_specified <- AB_data %>%
IEATools::specify_all()
AB_data_stock_changes_to_balancing <- AB_data_specified %>%
IEATools::add_psut_matnames() %>%
stock_changes_to_balancing()
expect_equal(AB_data_stock_changes_to_balancing[1,] %>%
dplyr::select(E.dot) %>%
dplyr::pull(),
500)
stock_changes_flows <- AB_data_stock_changes_to_balancing %>%
dplyr::filter(
stringr::str_detect(.data[["Flow"]], "Stock changes")
)
expect_equal(stock_changes_flows[1,] %>%
dplyr::select(matnames) %>%
dplyr::pull(),
"B")
expect_equal(stock_changes_flows[1,] %>%
dplyr::select(E.dot) %>%
dplyr::pull(),
-20)
expect_equal(stock_changes_flows[2,] %>%
dplyr::select(matnames) %>%
dplyr::pull(),
"B")
expect_equal(stock_changes_flows[2,] %>%
dplyr::select(E.dot) %>%
dplyr::pull(),
10)
expect_equal(stock_changes_flows[3,] %>%
dplyr::select(matnames) %>%
dplyr::pull(),
"B")
expect_equal(stock_changes_flows[4,] %>%
dplyr::select(matnames) %>%
dplyr::pull(),
"B")
})
test_that("Checking the sum_R_V argument of the calc_io_mats works well", {
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "ECCTools")
AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe")
AB_data_specified <- AB_data %>%
IEATools::specify_all() %>%
tibble::add_row(
Country = c("A", "A", "A"),
Method = c("PCM", "PCM", "PCM"),
Energy.type = c("E", "E", "E"),
Last.stage = c("Final", "Final", "Final"),
Year = c(2018, 2018, 2018),
Ledger.side = c("Consumption", "Consumption", "Consumption"),
Flow.aggregation.point = c("Transport", "Transport", "Transport"),
Flow = c("Road", "Road", "Road"),
Product = c("Anthracite", "Hard coal (if no detail)", "Brown coal (if no detail)"),
Unit = c("ktoe", "ktoe", "ktoe"),
E.dot = c(-50, -40, -10)
)
AB_data_stock_changes_to_balancing <- AB_data_specified %>%
IEATools::add_psut_matnames() %>%
stock_changes_to_balancing()
# Here we add a test: the calc_io_mats() function from Recca must work fine when using the sum_R_V method
AB_data_specified_io_Y_U_method <- AB_data_specified %>%
IEATools::prep_psut() %>%
Recca::calc_io_mats()
AB_data_specified_io_R_V_method <- AB_data_specified %>%
IEATools::prep_psut() %>%
Recca::calc_io_mats(method_q_calculation = "sum_R_V_cols")
AB_data_stock_changes_to_balancing_io_Y_U_method <- AB_data_stock_changes_to_balancing %>%
IEATools::prep_psut() %>%
Recca::calc_io_mats()
AB_data_stock_changes_to_balancing_io_R_V_method <- AB_data_stock_changes_to_balancing %>%
IEATools::prep_psut() %>%
Recca::calc_io_mats(method_q_calculation = "sum_R_V_cols")
# Without Balancing, sum_Y_U method
expect_equal(AB_data_specified_io_Y_U_method$q[[1]][["Anthracite", 1]], 50)
expect_equal(AB_data_specified_io_Y_U_method$q[[1]][["Hard coal (if no detail)", 1]], 40)
expect_equal(AB_data_specified_io_Y_U_method$q[[1]][["Brown coal (if no detail)", 1]], 30)
expect_equal(AB_data_specified_io_Y_U_method$q[[1]][["Coking coal", 1]], 5020)
# Without Balancing, sum_R_V method
expect_equal(AB_data_specified_io_R_V_method$q[[1]][["Anthracite", 1]], 20)
expect_equal(AB_data_specified_io_R_V_method$q[[1]][["Hard coal (if no detail)", 1]], 20)
expect_error(AB_data_specified_io_R_V_method$q[[1]][["Brown coal (if no detail)", 1]])
expect_equal(AB_data_specified_io_R_V_method$q[[1]][["Coking coal", 1]], 5000)
# With Balancing, sum_Y_U method
expect_equal(AB_data_stock_changes_to_balancing_io_Y_U_method$q[[1]][["Anthracite", 1]], 50)
expect_equal(AB_data_stock_changes_to_balancing_io_Y_U_method$q[[1]][["Hard coal (if no detail)", 1]], 40)
expect_equal(AB_data_stock_changes_to_balancing_io_Y_U_method$q[[1]][["Brown coal (if no detail)", 1]], 20)
expect_equal(AB_data_stock_changes_to_balancing_io_Y_U_method$q[[1]][["Coking coal", 1]], 5000)
# With Balancing, sum_R_V method
expect_error(AB_data_stock_changes_to_balancing_io_R_V_method$q[[1]][["Anthracite", 1]])
expect_equal(AB_data_stock_changes_to_balancing_io_R_V_method$q[[1]][["Hard coal (if no detail)", 1]], 10)
expect_error(AB_data_stock_changes_to_balancing_io_R_V_method$q[[1]][["Brown coal (if no detail)", 1]])
expect_equal(AB_data_stock_changes_to_balancing_io_R_V_method$q[[1]][["Coking coal", 1]], 5000)
})
test_that("Convert fuel gasoline works", {
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format.csv", package = "ECCTools")
# Loading AB_data
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, Product = "Gasoline type jet fuel", Ledger.side = "Consumption", Flow.aggregation.point = "Industry", Flow = "Iron and steel", Unit = "ktoe", E.dot = 20
) %>%
tibble::add_row(
Country = "A", Method = "PCM", Energy.type = "E", Last.stage = "Final", Year = 2018, Product = "Gasoline type jet fuel", Ledger.side = "Supply", Flow.aggregation.point = "Total primary energy supply", Flow = "Exports", Unit = "ktoe", E.dot = 50
) %>%
tibble::add_row(
Country = "A", Method = "PCM", Energy.type = "E", Last.stage = "Final", Year = 2018, Product = "Gasoline type jet fuel", Ledger.side = "Supply", Flow.aggregation.point = "Total primary energy supply", Flow = "Imports", Unit = "ktoe", E.dot = 100
) %>%
IEATools::specify_all()
AB_data %>%
dplyr::filter(Product == "Gasoline type jet fuel") %>%
nrow() %>%
expect_equal(3)
test_gathering <- AB_data %>%
convert_fuel_gasoline_into_motor_gasoline()
test_gathering %>%
dplyr::filter(Product == "Motor gasoline excl. biofuels", Flow == "Iron and steel", Country == "A") %>%
magrittr::extract2("E.dot") %>%
expect_equal(520)
test_gathering %>%
dplyr::filter(Product == "Motor gasoline excl. biofuels", Flow == "Imports [of Motor gasoline excl. biofuels]", Country == "A") %>%
magrittr::extract2("E.dot") %>%
expect_equal(100)
test_gathering %>%
dplyr::filter(Product == "Motor gasoline excl. biofuels", Flow == "Exports [of Motor gasoline excl. biofuels]", Country == "A") %>%
magrittr::extract2("E.dot") %>%
expect_equal(50)
test_gathering %>%
dplyr::filter(Product == "Gasoline type jet fuel") %>%
nrow() %>%
expect_equal(0)
})
# ###########################################################
# context("IEA energy balance")
# ###########################################################
#
# test_that("calc_tidy_iea_df_balance works correctly for 2018 data", {
# Ebal_2018 <- IEATools::load_tidy_iea_df(IEATools::sample_iea_data_path(2018)) %>%
# IEATools::calc_tidy_iea_df_balances()
# expect_false(all(Ebal_2018$balance_OK))
# expect_true(Ebal_2018 %>% dplyr::filter(Country == "GHA", Year == 1971, Product == "Aviation gasoline") %>% magrittr::extract2("balance_OK"))
# expect_false(Ebal_2018 %>% dplyr::filter(Country == "GHA", Year == 1971, Product == "Electricity") %>% magrittr::extract2("balance_OK"))
# expect_true(Ebal_2018 %>% dplyr::filter(Country == "ZAF", Year == 1971, Product == "Hydro") %>% magrittr::extract2("balance_OK"))
# expect_false(Ebal_2018 %>% dplyr::filter(Country == "ZAF", Year == 2000, Product == "Other bituminous coal") %>% magrittr::extract2("balance_OK"))
# })
#
#
# test_that("calc_tidy_iea_df_balance works correctly for 2019 data", {
# Ebal_2019 <- IEATools::load_tidy_iea_df(IEATools::sample_iea_data_path(2019)) %>%
# IEATools::calc_tidy_iea_df_balances()
# expect_false(all(Ebal_2019$balance_OK))
# expect_true(Ebal_2019 %>% dplyr::filter(Country == "GHA", Year == 1971, Product == "Aviation gasoline") %>% magrittr::extract2("balance_OK"))
# expect_false(Ebal_2019 %>% dplyr::filter(Country == "GHA", Year == 1971, Product == "Electricity") %>% magrittr::extract2("balance_OK"))
# # This one was OK in the 2018 data, but is off by 1e-4 in the 2019 data.
# expect_false(Ebal_2019 %>% dplyr::filter(Country == "ZAF", Year == 1971, Product == "Hydro") %>% magrittr::extract2("balance_OK"))
# expect_false(Ebal_2019 %>% dplyr::filter(Country == "ZAF", Year == 2000, Product == "Other bituminous coal") %>% magrittr::extract2("balance_OK"))
# })
test_that("add_balancing_vector works", {
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format.csv", package = "ECCTools")
# Loading AB_data
AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe")
AB_tidy_data <- AB_data %>%
IEATools::specify_all()
expect_true(AB_data %>%
IEATools::calc_tidy_iea_df_balances() %>%
IEATools::tidy_iea_df_balanced())
AB_tidy_MR <- AB_data %>%
IEATools::add_psut_matnames() %>%
transform_to_gma()
expect_false(AB_tidy_MR %>%
IEATools::calc_tidy_iea_df_balances() %>%
magrittr::extract2("balance_OK") %>%
all())
AB_tidy_MR_with_balancing <- AB_tidy_MR %>%
add_balancing_vector()
expect_true(AB_tidy_MR_with_balancing %>%
IEATools::calc_tidy_iea_df_balances() %>%
magrittr::extract2("balance_OK") %>%
all())
})
test_that("international_bunkers_to_balancing works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format.csv", package = "ECCTools")
# Loading AB_data
AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe")
AB_tidy_data <- AB_data %>%
IEATools::specify_all()
AB_tidy_data_with_international_bunkers <- AB_tidy_data %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Consumption",
Flow.aggregation.point = "Transport",
Flow = "International aviation bunkers",
Product = "Fuel oil",
Unit = "ktoe",
E.dot = 300
)
res <- AB_tidy_data_with_international_bunkers %>%
IEATools::add_psut_matnames() %>%
international_bunkers_to_balancing()
res %>%
dplyr::filter(stringr::str_detect(Flow, "International")) %>%
magrittr::extract2("matnames") %>%
expect_equal("B")
})
test_that("exports_to_balancing works", {
exports_relocated <- tidy_AB_data %>%
IEATools::add_psut_matnames() %>%
exports_to_balancing()
exports_relocated %>%
IEATools::calc_tidy_iea_df_balances() %>%
IEATools::tidy_iea_df_balanced() %>%
expect_true()
exports_relocated %>%
dplyr::filter(matnames == "B") %>%
dplyr::filter(stringr::str_detect(Flow, "Exports")) %>%
nrow() %>%
expect_equal(4)
n_ini <- exports_relocated %>%
nrow()
n_after <- n_ini - (exports_relocated %>% dplyr::filter(matnames == "B") %>% nrow())
expect_equal(n_after, 98)
})
# ADD TESTS ON SIGN AND LEDGER SIDE
test_that("losses_to_balancing works" ,{
# Number of rows of original tidy_AB_data, we add 1 because we add an additional balancing flow below
n_tidy_AB_data <- nrow(tidy_AB_data) +1
# Add a couple of flows; the losses one and a balancing flow so that we have balance
tidy_AB_data_with_losses <- tidy_AB_data %>%
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 = -100,
) %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Supply",
Flow.aggregation.point = "TFC compare",
Flow = "Some electricity coming from some fancy plant for the sake of the balance",
Product = "Electricity",
Unit = "ktoe",
E.dot = 100,
) %>%
IEATools::add_psut_matnames()
# Check balance
expect_true(tidy_AB_data_with_losses %>% IEATools::calc_tidy_iea_df_balances() %>% IEATools::tidy_iea_df_balanced())
# Relocate losses to balancing
tidy_AB_data_with_losses_relocated <- tidy_AB_data_with_losses %>%
losses_to_balancing()
# Re-check balance
expect_true(tidy_AB_data_with_losses_relocated %>% IEATools::calc_tidy_iea_df_balances() %>% IEATools::tidy_iea_df_balanced())
# Number of Losses flows rows in B matrix, and check value
n_balancing <-tidy_AB_data_with_losses_relocated %>%
dplyr::filter(matnames == "B") %>%
dplyr::filter(Flow == "Losses") %>%
nrow()
expect_equal(n_balancing, 1)
# Check diff values
n_diff <- (tidy_AB_data_with_losses %>%
dplyr::filter(matnames != "B") %>%
nrow()) - n_balancing
expect_equal(n_diff, n_tidy_AB_data)
tidy_AB_data_with_losses_relocated %>%
dplyr::filter(matnames == "B") %>%
magrittr::extract2("E.dot") %>%
expect_equal(100)
tidy_AB_data_with_losses_relocated %>%
dplyr::filter(matnames == "B") %>%
magrittr::extract2("Ledger.side") %>%
expect_equal("balancing")
})
test_that("non_energy_uses_to_balancing works" ,{
n_tidy_AB_data <- tidy_AB_data %>% nrow()
tidy_AB_data_with_neu <- tidy_AB_data %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Supply",
Flow.aggregation.point = "Consumption",
Flow = "Non-energy use in whatever sector",
Product = "Electricity",
Unit = "ktoe",
E.dot = 10,
) %>%
IEATools::add_psut_matnames()
n_balancing <- tidy_AB_data_with_neu %>%
non_energy_uses_to_balancing() %>%
dplyr::filter(matnames == "B") %>%
dplyr::filter(stringr::str_detect(Flow, "Non-energy use")) %>%
nrow()
expect_equal(n_balancing, 1)
n_diff <- (tidy_AB_data_with_neu %>%
dplyr::filter(matnames != "B") %>%
nrow()) - n_balancing
expect_equal(n_diff, n_tidy_AB_data)
})
earamendia/ECCTools documentation built on May 12, 2023, 2:12 a.m.
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###########################################################
context("Cleaning up PSUT")
###########################################################
# Testing convert_to_net_trade function:
test_that("convert_to_net_trade works", {
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format.csv", package = "ECCTools")
# Loading AB_data
AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe")
# Adding a couple of rows for having both imports and exports
dummy_net_trade <- tibble::tribble(
~Country, ~Method, ~Energy.type, ~Last.stage, ~Year, ~Ledger.side, ~Flow.aggregation.point, ~Flow, ~Product, ~Unit, ~E.dot,
"A", "PCM", "E", "Final", 2018, "Supply", "Total primary energy supply", "Imports", "Coking coal", "ktoe", 840,
"A", "PCM", "E", "Final", 2018, "Supply", "Total primary energy supply", "Imports", "Natural gas", "ktoe", 1100,
"A", "PCM", "E", "Final", 2018, "Supply", "Total primary energy supply", "Imports", "Crude oil", "ktoe", 4000,
"B", "PCM", "E", "Final", 2018, "Supply", "Total primary energy supply", "Imports", "Coke oven coke", "ktoe", 600,
"A", "PCM", "E", "Final", 2018, "Supply", "Total primary energy supply", "Exports", "Coke oven coke", "ktoe", -1400,
)
AB_net_trade_testing <- AB_data %>%
dplyr::bind_rows(dummy_net_trade) %>%
IEATools::specify_all()
# First test, that shouldn't change the data frame at all
test_unchanged_df <- convert_to_net_trade(AB_data %>%
IEATools::specify_all())
checking_row_equality <- dplyr::left_join(AB_data %>%
IEATools::specify_all(),
test_unchanged_df,
by = c("Country", "Method", "Energy.type", "Last.stage", "Year", "Ledger.side", "Flow.aggregation.point", "Flow", "Product", "Unit")) %>%
dplyr::mutate(
diff = E.dot.x - E.dot.y
) %>%
dplyr::summarise(max_diff = max(abs(diff))) %>%
dplyr::pull()
expect_equal(checking_row_equality, 0)
# Second test, that should change the data frame where there are both imports and exports
test_changed_df <- convert_to_net_trade(AB_net_trade_testing)
checking_row_equality <- dplyr::left_join(AB_data %>%
IEATools::specify_all(),
test_changed_df,
by = c("Country", "Method", "Energy.type", "Last.stage", "Year", "Ledger.side", "Flow.aggregation.point", "Flow", "Product", "Unit")) %>%
dplyr::mutate(
diff = E.dot.x - E.dot.y
) %>%
dplyr::filter(! (stringr::str_detect(Flow, "Imports") | stringr::str_detect(Flow, "Exports"))) %>%
dplyr::summarise(max_diff = max(abs(diff))) %>%
dplyr::pull()
expect_equal(checking_row_equality, 0)
check_trade <- test_changed_df %>%
dplyr::filter(stringr::str_detect(Flow, "Imports") | stringr::str_detect(Flow, "Exports"))
expect_equal(check_trade[[1, "E.dot"]], -800)
expect_equal(check_trade[[1, "Flow"]], "Exports [of Coke oven coke]")
expect_equal(check_trade[[2, "E.dot"]], -1160)
expect_equal(check_trade[[2, "Flow"]], "Exports [of Coking coal]")
expect_equal(check_trade[[3, "E.dot"]], 500)
expect_equal(check_trade[[3, "Flow"]], "Imports [of Crude oil]")
expect_equal(check_trade[[4, "E.dot"]], -1400)
expect_equal(check_trade[[4, "Flow"]], "Exports [of Natural gas]")
expect_equal(check_trade[[5, "E.dot"]], 200)
expect_equal(check_trade[[5, "Flow"]], "Imports [of Coke oven coke]")
expect_equal(check_trade[[8, "E.dot"]], 2500)
expect_equal(check_trade[[8, "Flow"]], "Imports [of Natural gas]")
})
# Testing stat_diffs_to_balancing:
test_that("stat_diffs_to_balancing works",{
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "ECCTools")
AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe")
AB_data_specified <- AB_data %>%
IEATools::specify_all()
AB_data_stat_diffs_to_balancing <- AB_data_specified %>%
IEATools::add_psut_matnames() %>%
stat_diffs_to_balancing()
expect_equal(AB_data_stat_diffs_to_balancing[1,] %>%
dplyr::select(E.dot) %>%
dplyr::pull(),
500)
stat_diffs_flows <- AB_data_stat_diffs_to_balancing %>%
dplyr::filter(Flow == "Statistical differences")
expect_equal(stat_diffs_flows[1,] %>%
dplyr::select(matnames) %>%
dplyr::pull(),
"B")
expect_equal(stat_diffs_flows[1,] %>%
dplyr::select(E.dot) %>%
dplyr::pull(),
10)
expect_equal(stat_diffs_flows[2,] %>%
dplyr::select(matnames) %>%
dplyr::pull(),
"B")
expect_equal(stat_diffs_flows[2,] %>%
dplyr::select(E.dot) %>%
dplyr::pull(),
-10)
})
# Testing stock_changes_to_balancing:
test_that("stock_changes_to_balancing works",{
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "ECCTools")
AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe")
AB_data_specified <- AB_data %>%
IEATools::specify_all()
AB_data_stock_changes_to_balancing <- AB_data_specified %>%
IEATools::add_psut_matnames() %>%
stock_changes_to_balancing()
expect_equal(AB_data_stock_changes_to_balancing[1,] %>%
dplyr::select(E.dot) %>%
dplyr::pull(),
500)
stock_changes_flows <- AB_data_stock_changes_to_balancing %>%
dplyr::filter(
stringr::str_detect(.data[["Flow"]], "Stock changes")
)
expect_equal(stock_changes_flows[1,] %>%
dplyr::select(matnames) %>%
dplyr::pull(),
"B")
expect_equal(stock_changes_flows[1,] %>%
dplyr::select(E.dot) %>%
dplyr::pull(),
-20)
expect_equal(stock_changes_flows[2,] %>%
dplyr::select(matnames) %>%
dplyr::pull(),
"B")
expect_equal(stock_changes_flows[2,] %>%
dplyr::select(E.dot) %>%
dplyr::pull(),
10)
expect_equal(stock_changes_flows[3,] %>%
dplyr::select(matnames) %>%
dplyr::pull(),
"B")
expect_equal(stock_changes_flows[4,] %>%
dplyr::select(matnames) %>%
dplyr::pull(),
"B")
})
test_that("Checking the sum_R_V argument of the calc_io_mats works well", {
A_B_path <- system.file("extdata/A_B_data_full_2018_format_stat_diffs_stock_changes.csv", package = "ECCTools")
AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe")
AB_data_specified <- AB_data %>%
IEATools::specify_all() %>%
tibble::add_row(
Country = c("A", "A", "A"),
Method = c("PCM", "PCM", "PCM"),
Energy.type = c("E", "E", "E"),
Last.stage = c("Final", "Final", "Final"),
Year = c(2018, 2018, 2018),
Ledger.side = c("Consumption", "Consumption", "Consumption"),
Flow.aggregation.point = c("Transport", "Transport", "Transport"),
Flow = c("Road", "Road", "Road"),
Product = c("Anthracite", "Hard coal (if no detail)", "Brown coal (if no detail)"),
Unit = c("ktoe", "ktoe", "ktoe"),
E.dot = c(-50, -40, -10)
)
AB_data_stock_changes_to_balancing <- AB_data_specified %>%
IEATools::add_psut_matnames() %>%
stock_changes_to_balancing()
# Here we add a test: the calc_io_mats() function from Recca must work fine when using the sum_R_V method
AB_data_specified_io_Y_U_method <- AB_data_specified %>%
IEATools::prep_psut() %>%
Recca::calc_io_mats()
AB_data_specified_io_R_V_method <- AB_data_specified %>%
IEATools::prep_psut() %>%
Recca::calc_io_mats(method_q_calculation = "sum_R_V_cols")
AB_data_stock_changes_to_balancing_io_Y_U_method <- AB_data_stock_changes_to_balancing %>%
IEATools::prep_psut() %>%
Recca::calc_io_mats()
AB_data_stock_changes_to_balancing_io_R_V_method <- AB_data_stock_changes_to_balancing %>%
IEATools::prep_psut() %>%
Recca::calc_io_mats(method_q_calculation = "sum_R_V_cols")
# Without Balancing, sum_Y_U method
expect_equal(AB_data_specified_io_Y_U_method$q[[1]][["Anthracite", 1]], 50)
expect_equal(AB_data_specified_io_Y_U_method$q[[1]][["Hard coal (if no detail)", 1]], 40)
expect_equal(AB_data_specified_io_Y_U_method$q[[1]][["Brown coal (if no detail)", 1]], 30)
expect_equal(AB_data_specified_io_Y_U_method$q[[1]][["Coking coal", 1]], 5020)
# Without Balancing, sum_R_V method
expect_equal(AB_data_specified_io_R_V_method$q[[1]][["Anthracite", 1]], 20)
expect_equal(AB_data_specified_io_R_V_method$q[[1]][["Hard coal (if no detail)", 1]], 20)
expect_error(AB_data_specified_io_R_V_method$q[[1]][["Brown coal (if no detail)", 1]])
expect_equal(AB_data_specified_io_R_V_method$q[[1]][["Coking coal", 1]], 5000)
# With Balancing, sum_Y_U method
expect_equal(AB_data_stock_changes_to_balancing_io_Y_U_method$q[[1]][["Anthracite", 1]], 50)
expect_equal(AB_data_stock_changes_to_balancing_io_Y_U_method$q[[1]][["Hard coal (if no detail)", 1]], 40)
expect_equal(AB_data_stock_changes_to_balancing_io_Y_U_method$q[[1]][["Brown coal (if no detail)", 1]], 20)
expect_equal(AB_data_stock_changes_to_balancing_io_Y_U_method$q[[1]][["Coking coal", 1]], 5000)
# With Balancing, sum_R_V method
expect_error(AB_data_stock_changes_to_balancing_io_R_V_method$q[[1]][["Anthracite", 1]])
expect_equal(AB_data_stock_changes_to_balancing_io_R_V_method$q[[1]][["Hard coal (if no detail)", 1]], 10)
expect_error(AB_data_stock_changes_to_balancing_io_R_V_method$q[[1]][["Brown coal (if no detail)", 1]])
expect_equal(AB_data_stock_changes_to_balancing_io_R_V_method$q[[1]][["Coking coal", 1]], 5000)
})
test_that("Convert fuel gasoline works", {
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format.csv", package = "ECCTools")
# Loading AB_data
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, Product = "Gasoline type jet fuel", Ledger.side = "Consumption", Flow.aggregation.point = "Industry", Flow = "Iron and steel", Unit = "ktoe", E.dot = 20
) %>%
tibble::add_row(
Country = "A", Method = "PCM", Energy.type = "E", Last.stage = "Final", Year = 2018, Product = "Gasoline type jet fuel", Ledger.side = "Supply", Flow.aggregation.point = "Total primary energy supply", Flow = "Exports", Unit = "ktoe", E.dot = 50
) %>%
tibble::add_row(
Country = "A", Method = "PCM", Energy.type = "E", Last.stage = "Final", Year = 2018, Product = "Gasoline type jet fuel", Ledger.side = "Supply", Flow.aggregation.point = "Total primary energy supply", Flow = "Imports", Unit = "ktoe", E.dot = 100
) %>%
IEATools::specify_all()
AB_data %>%
dplyr::filter(Product == "Gasoline type jet fuel") %>%
nrow() %>%
expect_equal(3)
test_gathering <- AB_data %>%
convert_fuel_gasoline_into_motor_gasoline()
test_gathering %>%
dplyr::filter(Product == "Motor gasoline excl. biofuels", Flow == "Iron and steel", Country == "A") %>%
magrittr::extract2("E.dot") %>%
expect_equal(520)
test_gathering %>%
dplyr::filter(Product == "Motor gasoline excl. biofuels", Flow == "Imports [of Motor gasoline excl. biofuels]", Country == "A") %>%
magrittr::extract2("E.dot") %>%
expect_equal(100)
test_gathering %>%
dplyr::filter(Product == "Motor gasoline excl. biofuels", Flow == "Exports [of Motor gasoline excl. biofuels]", Country == "A") %>%
magrittr::extract2("E.dot") %>%
expect_equal(50)
test_gathering %>%
dplyr::filter(Product == "Gasoline type jet fuel") %>%
nrow() %>%
expect_equal(0)
})
# ###########################################################
# context("IEA energy balance")
# ###########################################################
#
# test_that("calc_tidy_iea_df_balance works correctly for 2018 data", {
# Ebal_2018 <- IEATools::load_tidy_iea_df(IEATools::sample_iea_data_path(2018)) %>%
# IEATools::calc_tidy_iea_df_balances()
# expect_false(all(Ebal_2018$balance_OK))
# expect_true(Ebal_2018 %>% dplyr::filter(Country == "GHA", Year == 1971, Product == "Aviation gasoline") %>% magrittr::extract2("balance_OK"))
# expect_false(Ebal_2018 %>% dplyr::filter(Country == "GHA", Year == 1971, Product == "Electricity") %>% magrittr::extract2("balance_OK"))
# expect_true(Ebal_2018 %>% dplyr::filter(Country == "ZAF", Year == 1971, Product == "Hydro") %>% magrittr::extract2("balance_OK"))
# expect_false(Ebal_2018 %>% dplyr::filter(Country == "ZAF", Year == 2000, Product == "Other bituminous coal") %>% magrittr::extract2("balance_OK"))
# })
#
#
# test_that("calc_tidy_iea_df_balance works correctly for 2019 data", {
# Ebal_2019 <- IEATools::load_tidy_iea_df(IEATools::sample_iea_data_path(2019)) %>%
# IEATools::calc_tidy_iea_df_balances()
# expect_false(all(Ebal_2019$balance_OK))
# expect_true(Ebal_2019 %>% dplyr::filter(Country == "GHA", Year == 1971, Product == "Aviation gasoline") %>% magrittr::extract2("balance_OK"))
# expect_false(Ebal_2019 %>% dplyr::filter(Country == "GHA", Year == 1971, Product == "Electricity") %>% magrittr::extract2("balance_OK"))
# # This one was OK in the 2018 data, but is off by 1e-4 in the 2019 data.
# expect_false(Ebal_2019 %>% dplyr::filter(Country == "ZAF", Year == 1971, Product == "Hydro") %>% magrittr::extract2("balance_OK"))
# expect_false(Ebal_2019 %>% dplyr::filter(Country == "ZAF", Year == 2000, Product == "Other bituminous coal") %>% magrittr::extract2("balance_OK"))
# })
test_that("add_balancing_vector works", {
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format.csv", package = "ECCTools")
# Loading AB_data
AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe")
AB_tidy_data <- AB_data %>%
IEATools::specify_all()
expect_true(AB_data %>%
IEATools::calc_tidy_iea_df_balances() %>%
IEATools::tidy_iea_df_balanced())
AB_tidy_MR <- AB_data %>%
IEATools::add_psut_matnames() %>%
transform_to_gma()
expect_false(AB_tidy_MR %>%
IEATools::calc_tidy_iea_df_balances() %>%
magrittr::extract2("balance_OK") %>%
all())
AB_tidy_MR_with_balancing <- AB_tidy_MR %>%
add_balancing_vector()
expect_true(AB_tidy_MR_with_balancing %>%
IEATools::calc_tidy_iea_df_balances() %>%
magrittr::extract2("balance_OK") %>%
all())
})
test_that("international_bunkers_to_balancing works",{
# Path to dummy AB data
A_B_path <- system.file("extdata/A_B_data_full_2018_format.csv", package = "ECCTools")
# Loading AB_data
AB_data <- A_B_path %>%
IEATools::load_tidy_iea_df(unit_val = "ktoe")
AB_tidy_data <- AB_data %>%
IEATools::specify_all()
AB_tidy_data_with_international_bunkers <- AB_tidy_data %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Consumption",
Flow.aggregation.point = "Transport",
Flow = "International aviation bunkers",
Product = "Fuel oil",
Unit = "ktoe",
E.dot = 300
)
res <- AB_tidy_data_with_international_bunkers %>%
IEATools::add_psut_matnames() %>%
international_bunkers_to_balancing()
res %>%
dplyr::filter(stringr::str_detect(Flow, "International")) %>%
magrittr::extract2("matnames") %>%
expect_equal("B")
})
test_that("exports_to_balancing works", {
exports_relocated <- tidy_AB_data %>%
IEATools::add_psut_matnames() %>%
exports_to_balancing()
exports_relocated %>%
IEATools::calc_tidy_iea_df_balances() %>%
IEATools::tidy_iea_df_balanced() %>%
expect_true()
exports_relocated %>%
dplyr::filter(matnames == "B") %>%
dplyr::filter(stringr::str_detect(Flow, "Exports")) %>%
nrow() %>%
expect_equal(4)
n_ini <- exports_relocated %>%
nrow()
n_after <- n_ini - (exports_relocated %>% dplyr::filter(matnames == "B") %>% nrow())
expect_equal(n_after, 98)
})
# ADD TESTS ON SIGN AND LEDGER SIDE
test_that("losses_to_balancing works" ,{
# Number of rows of original tidy_AB_data, we add 1 because we add an additional balancing flow below
n_tidy_AB_data <- nrow(tidy_AB_data) +1
# Add a couple of flows; the losses one and a balancing flow so that we have balance
tidy_AB_data_with_losses <- tidy_AB_data %>%
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 = -100,
) %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Supply",
Flow.aggregation.point = "TFC compare",
Flow = "Some electricity coming from some fancy plant for the sake of the balance",
Product = "Electricity",
Unit = "ktoe",
E.dot = 100,
) %>%
IEATools::add_psut_matnames()
# Check balance
expect_true(tidy_AB_data_with_losses %>% IEATools::calc_tidy_iea_df_balances() %>% IEATools::tidy_iea_df_balanced())
# Relocate losses to balancing
tidy_AB_data_with_losses_relocated <- tidy_AB_data_with_losses %>%
losses_to_balancing()
# Re-check balance
expect_true(tidy_AB_data_with_losses_relocated %>% IEATools::calc_tidy_iea_df_balances() %>% IEATools::tidy_iea_df_balanced())
# Number of Losses flows rows in B matrix, and check value
n_balancing <-tidy_AB_data_with_losses_relocated %>%
dplyr::filter(matnames == "B") %>%
dplyr::filter(Flow == "Losses") %>%
nrow()
expect_equal(n_balancing, 1)
# Check diff values
n_diff <- (tidy_AB_data_with_losses %>%
dplyr::filter(matnames != "B") %>%
nrow()) - n_balancing
expect_equal(n_diff, n_tidy_AB_data)
tidy_AB_data_with_losses_relocated %>%
dplyr::filter(matnames == "B") %>%
magrittr::extract2("E.dot") %>%
expect_equal(100)
tidy_AB_data_with_losses_relocated %>%
dplyr::filter(matnames == "B") %>%
magrittr::extract2("Ledger.side") %>%
expect_equal("balancing")
})
test_that("non_energy_uses_to_balancing works" ,{
n_tidy_AB_data <- tidy_AB_data %>% nrow()
tidy_AB_data_with_neu <- tidy_AB_data %>%
tibble::add_row(
Country = "A",
Method = "PCM",
Energy.type = "E",
Last.stage = "Final",
Year = 2018,
Ledger.side = "Supply",
Flow.aggregation.point = "Consumption",
Flow = "Non-energy use in whatever sector",
Product = "Electricity",
Unit = "ktoe",
E.dot = 10,
) %>%
IEATools::add_psut_matnames()
n_balancing <- tidy_AB_data_with_neu %>%
non_energy_uses_to_balancing() %>%
dplyr::filter(matnames == "B") %>%
dplyr::filter(stringr::str_detect(Flow, "Non-energy use")) %>%
nrow()
expect_equal(n_balancing, 1)
n_diff <- (tidy_AB_data_with_neu %>%
dplyr::filter(matnames != "B") %>%
nrow()) - n_balancing
expect_equal(n_diff, n_tidy_AB_data)
})
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