tests/testthat/test-final_to_useful.R
In MatthewHeun/IEATools: Tools for Working with International Energy Agency Data
test_that("form_C_mats() works with 0-row input", {
allocation_table <- load_fu_allocation_data()
allocation_table <- allocation_table[0, ]
res <- form_C_mats(allocation_table)
expect_equal(nrow(res), 0)
expect_setequal(names(res), c(IEATools::iea_cols$country, IEATools::iea_cols$method, IEATools::iea_cols$energy_type, IEATools::iea_cols$last_stage, IEATools::iea_cols$year,
IEATools::template_cols$C_eiou, IEATools::template_cols$C_Y))
})
test_that("form_C_mats() works as expected", {
allocation_table <- load_fu_allocation_data()
C_df <- form_C_mats(allocation_table)
# Check type of year column
expect_true(is.numeric(C_df$Year))
# Check that the Unit column is missing. It has no meaning for allocations.
expect_true(is.null(C_df[[IEATools::iea_cols$unit]]))
# Check some values.
C_EIOU_GHA_1971 <- C_df %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2(IEATools::template_cols$C_eiou) %>%
magrittr::extract2(1)
r1 <- "Electricity -> Main activity producer electricity plants"
r2 <- "Refinery gas -> Oil refineries"
c1 <- "Electric lights -> Light"
c2 <- "Electric motors -> MD"
c3 <- "Industrial furnaces -> HTH.600.C"
expect_equal(C_EIOU_GHA_1971[[r1, c1]], 0.5)
expect_equal(C_EIOU_GHA_1971[[r1, c2]], 0.5)
expect_equal(C_EIOU_GHA_1971[[r1, c3]], 0)
expect_equal(C_EIOU_GHA_1971[[r2, c1]], 0)
expect_equal(C_EIOU_GHA_1971[[r2, c2]], 0)
expect_equal(C_EIOU_GHA_1971[[r2, c3]], 1)
C_Y_ZAF_2000 <- C_df %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2(IEATools::template_cols$C_Y) %>%
magrittr::extract2(1)
r1 <- "Blast furnace gas -> Iron and steel"
c1 <- "Airplanes -> MD"
r_kerosene <- "Kerosene type jet fuel excl. biofuels -> Domestic aviation"
c_stoves <- "Industrial furnaces -> HTH.600.C"
expect_equal(C_Y_ZAF_2000[[r1, c_stoves]], 1)
expect_equal(C_Y_ZAF_2000[[r_kerosene, c1]], 1)
# Set a wrong value and expect a warning.
allocation_table_wrong <- allocation_table
allocation_table_wrong[[3, "1971"]] <- 0.9 # Was 1.0. This change should trigger an error on this row.
expect_warning(diagnostic_df <- form_C_mats(allocation_table_wrong), "Not all rows in the C matrices sum to 1.")
# Check that the diagnostic data frame is correct
expect_equal(diagnostic_df[[1, IEATools::mat_meta_cols$rownames]], "Refinery gas -> Oil refineries")
expect_equal(diagnostic_df[[1, ".should_be_1_vector"]], 0.9)
# Check the row and column types
for (i in 1:nrow(C_df)) {
expect_equal(matsbyname::rowtype(C_df$C_EIOU[[i]]), "Product -> Industry")
expect_equal(matsbyname::coltype(C_df$C_EIOU[[i]]), "Industry -> Product")
expect_equal(matsbyname::rowtype(C_df$C_Y[[i]]), "Product -> Industry")
expect_equal(matsbyname::coltype(C_df$C_Y[[i]]), "Industry -> Product")
}
})
test_that("form_C_mats() works with Matrix objects", {
allocation_table <- load_fu_allocation_data()
C_df <- form_C_mats(allocation_table, matrix_class = "Matrix")
# Check that we made Matrix objects.
expect_true(all(sapply(C_df$C_EIOU, matsbyname::is.Matrix)))
expect_true(all(sapply(C_df$C_Y, matsbyname::is.Matrix)))
# Check type of year column
expect_true(is.numeric(C_df$Year))
# Check that the Unit column is missing. It has no meaning for allocations.
expect_true(is.null(C_df[[IEATools::iea_cols$unit]]))
# Check some values.
C_EIOU_GHA_1971 <- C_df %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2(IEATools::template_cols$C_eiou) %>%
magrittr::extract2(1)
r1 <- "Electricity -> Main activity producer electricity plants"
r2 <- "Refinery gas -> Oil refineries"
c1 <- "Electric lights -> Light"
c2 <- "Electric motors -> MD"
c3 <- "Industrial furnaces -> HTH.600.C"
expect_equal(C_EIOU_GHA_1971[r1, c1], 0.5)
expect_equal(C_EIOU_GHA_1971[r1, c2], 0.5)
expect_equal(C_EIOU_GHA_1971[r1, c3], 0)
expect_equal(C_EIOU_GHA_1971[r2, c1], 0)
expect_equal(C_EIOU_GHA_1971[r2, c2], 0)
expect_equal(C_EIOU_GHA_1971[r2, c3], 1)
C_Y_ZAF_2000 <- C_df %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2(IEATools::template_cols$C_Y) %>%
magrittr::extract2(1)
r1 <- "Blast furnace gas -> Iron and steel"
c1 <- "Airplanes -> MD"
r_kerosene <- "Kerosene type jet fuel excl. biofuels -> Domestic aviation"
c_stoves <- "Industrial furnaces -> HTH.600.C"
expect_equal(C_Y_ZAF_2000[r1, c_stoves], 1)
expect_equal(C_Y_ZAF_2000[r_kerosene, c1], 1)
# Set a wrong value and expect a warning.
allocation_table_wrong <- allocation_table
allocation_table_wrong[[3, "1971"]] <- 0.9 # Was 1.0. This change should trigger an error on this row.
expect_warning(diagnostic_df <- form_C_mats(allocation_table_wrong, matrix_class = "Matrix"), "Not all rows in the C matrices sum to 1.")
# Check that the diagnostic data frame is correct
expect_equal(diagnostic_df[[1, IEATools::mat_meta_cols$rownames]], "Refinery gas -> Oil refineries")
expect_equal(diagnostic_df[[1, ".should_be_1_vector"]], 0.9)
# Check the row and column types
for (i in 1:nrow(C_df)) {
expect_equal(matsbyname::rowtype(C_df$C_EIOU[[i]]), "Product -> Industry")
expect_equal(matsbyname::coltype(C_df$C_EIOU[[i]]), "Industry -> Product")
expect_equal(matsbyname::rowtype(C_df$C_Y[[i]]), "Product -> Industry")
expect_equal(matsbyname::coltype(C_df$C_Y[[i]]), "Industry -> Product")
}
})
test_that("form_eta_fu_phi_u_vecs() works as expected", {
efficiency_table <- load_eta_fu_data()
eta_fu_phi_u_df <- form_eta_fu_phi_u_vecs(efficiency_table)
# Check type of year column
expect_true(is.numeric(eta_fu_phi_u_df$Year))
# Check that the Unit column is missing. It has no meaning for allocations.
expect_true(is.null(eta_fu_phi_u_df[[IEATools::iea_cols$unit]]))
# Check some values
eta_GHA_1971 <- eta_fu_phi_u_df$eta.fu[[1]]
expect_equal(eta_GHA_1971[["Irons -> MTH.200.C", 1]], 0.85)
expect_equal(eta_GHA_1971[["Trucks -> MD", 1]], 0.30)
expect_equal(eta_GHA_1971[["Fans -> MD", 1]], 0.10)
expect_equal(eta_GHA_1971[["Boat engines -> MD", 1]], 0.30)
phi_ZAR_2000 <- eta_fu_phi_u_df$phi.u[[4]]
expect_equal(phi_ZAR_2000[["MD", 1]], 1)
expect_equal(phi_ZAR_2000[["LTH.20.C", 1]], 0.0167700821734027)
expect_equal(phi_ZAR_2000[["HTH.600.C", 1]], 0.65853519)
expect_equal(phi_ZAR_2000[["Light", 1]], 0.1830161054172770)
# Check row and column types
for (i in 1:nrow(eta_fu_phi_u_df)) {
expect_equal(matsbyname::rowtype(eta_fu_phi_u_df$eta.fu[[i]]), "Industry -> Product")
expect_equal(matsbyname::coltype(eta_fu_phi_u_df$eta.fu[[i]]), "eta.fu")
}
for (i in 1:nrow(eta_fu_phi_u_df)) {
expect_equal(matsbyname::rowtype(eta_fu_phi_u_df$phi.u[[i]]), "Product")
expect_equal(matsbyname::coltype(eta_fu_phi_u_df$phi.u[[i]]), "phi")
}
})
test_that("form_eta_fu_phi_u_vecs() errors when phi values are different", {
efficiency_table <- load_eta_fu_data()
# Change a value to be different. Change a MD phi value from 1 to 0.99.
expect_equal(efficiency_table[32, "1971"], 1.0)
efficiency_table[32, "1971"] <- 0.9999
expect_equal(efficiency_table[32, "1971"], 0.9999)
expect_error(form_eta_fu_phi_u_vecs(efficiency_table), "Found useful products with different phi values in form_eta_fu_phi_u_vecs")
})
test_that("form_eta_fu_phi_u_vecs() works when the incoming data frame has no rows", {
efficiency_table <- load_eta_fu_data()
efficiency_table <- efficiency_table[0, ]
eta_fu_phi_u_df <- form_eta_fu_phi_u_vecs(efficiency_table)
expect_true(IEATools::template_cols$eta_fu %in% names(eta_fu_phi_u_df))
expect_true(IEATools::template_cols$phi_u %in% names(eta_fu_phi_u_df))
})
test_that("extend_to_useful_helper() works as intended", {
# These tests come from the "Pushing Y to Useful" tab in file "Matrix f->u example calcs.xlsx"
# Set up some matrices and data frames
Y_f <- matrix(c(100, 50,
200, 25), byrow = TRUE, nrow = 2, ncol = 2,
dimnames = list(c("Elect", "Petrol"), c("Residential", "Construction"))) %>%
matsbyname::setrowtype(IEATools::row_col_types$product) %>%
matsbyname::setcoltype(IEATools::row_col_types$industry)
Allocation_Table <- tibble::tribble(~Destination, ~Ef.product, ~Machine, ~Eu.product, ~C,
"Residential", "Elect", "Lights", "Light", 0.5,
"Residential", "Elect", "Water heaters", "MTH", 0.5,
"Construction", "Elect", "Elect motors", "MD", 0.25,
"Construction", "Elect", "Lights", "Light", 0.25,
"Construction", "Elect", "Heaters", "MTH", 0.5,
"Residential", "Petrol", "Engines", "MD", 0.25,
"Residential", "Petrol", "Burner", "MTH", 0.75,
"Construction", "Petrol", "Autos", "MD", 0.6,
"Construction", "Petrol", "Furnace", "LTH", 0.4)
Efficiency_Table <- tibble::tribble(~Machine, ~Eu.product, ~eta.fu,
"Lights", "Light", 0.45,
"Water heaters", "MTH", 0.9,
"Elect motors", "MD", 0.95,
"Heaters", "MTH", 0.9,
"Engines", "MD", 0.25,
"Burner", "MTH", 0.98,
"Autos", "MD", 0.15,
"Furnace", "LTH", 0.97)
# Calculate some matrices
C_Y <- Allocation_Table %>%
dplyr::mutate(
rownames = RCLabels::paste_pref_suff(pref = Ef.product, suff = Destination, notation = RCLabels::arrow_notation),
colnames = RCLabels::paste_pref_suff(pref = Machine, suff = Eu.product, notation = RCLabels::arrow_notation),
rowtypes = RCLabels::paste_pref_suff(pref = row_col_types$product, suff = row_col_types$industry, notation = RCLabels::arrow_notation),
coltypes = RCLabels::paste_pref_suff(pref = row_col_types$industry, suff = row_col_types$product, notation = RCLabels::arrow_notation),
matnames = "C_Y",
Destination = NULL,
Ef.product = NULL,
Machine = NULL,
Eu.product = NULL
) %>%
dplyr::rename(
matvals = C
) %>%
dplyr::group_by(matnames) %>%
matsindf::collapse_to_matrices(matrix_class = "Matrix") %>%
magrittr::extract2("matvals") %>%
magrittr::extract2(1)
eta.fu_rownames <- Efficiency_Table %>%
dplyr::mutate(
rownames = RCLabels::paste_pref_suff(pref = Machine, suff = Eu.product, notation = RCLabels::arrow_notation)
) %>%
magrittr::extract2("rownames")
eta_fu <- Efficiency_Table %>%
magrittr::extract2("eta.fu") %>%
matrix(ncol = 1, dimnames = list(eta.fu_rownames, "eta.fu")) %>%
matsbyname::setrowtype(RCLabels::paste_pref_suff(pref = row_col_types$industry,
suff = row_col_types$product,
notation = RCLabels::arrow_notation))
# Calculate actual results
res <- IEATools:::extend_to_useful_helper(dest_mat = Y_f, C_mat = C_Y, eta_fu_vec = eta_fu)
# Calculate expected results
## Step 1
Y_f_vec <- matsbyname::vectorize_byname(Y_f, notation = RCLabels::arrow_notation)
Y_f_vec_hat <- matsbyname::hatize_byname(Y_f_vec, keep = "rownames")
Y_f_vec_hat_C_Y <- matsbyname::matrixproduct_byname(Y_f_vec_hat, C_Y)
eta_fu_hat <- matsbyname::hatize_byname(eta_fu, keep = "rownames") %>%
arrow_to_from_byname(margin = 2)
expect_equal(eta_fu_hat[["Engines -> MD", "MD [from Engines]"]],
Efficiency_Table %>% dplyr::filter(Machine == "Engines") %>%
magrittr::extract2("eta.fu"))
## Step 2
add_to_U_feed_expected <- Y_f_vec_hat_C_Y %>%
matsbyname::aggregate_to_pref_suff_byname(keep = "pref", margin = 1, notation = RCLabels::arrow_notation) %>%
matsbyname::clean_byname(margin = 1) %>%
matsbyname::setcoltype(row_col_types$industry)
expect_equal(res$add_to_U, add_to_U_feed_expected)
## Step 3
add_to_V_expected <- Y_f_vec_hat_C_Y %>%
matsbyname::colsums_byname() %>%
matsbyname::hatize_byname(keep = "colnames") %>%
matsbyname::matrixproduct_byname(eta_fu_hat) %>%
matsbyname::setrowtype(row_col_types$industry) %>%
matsbyname::setcoltype(row_col_types$product)
expect_equal(res$add_to_V, add_to_V_expected)
## Step 4
add_to_Y_expected <- matsbyname::matrixproduct_byname(Y_f_vec_hat_C_Y, eta_fu_hat) %>%
matsbyname::transpose_byname() %>%
matsbyname::aggregate_to_pref_suff_byname(keep = "suff", margin = 2, notation = RCLabels::arrow_notation) %>%
matsbyname::clean_byname() %>%
matsbyname::setrowtype(row_col_types$product) %>%
matsbyname::setcoltype(row_col_types$industry)
expect_equal(res$add_to_dest, add_to_Y_expected)
## Now check the details fu matrix
details_fu_mat_expected <- matsbyname::matrixproduct_byname(Y_f_vec_hat_C_Y, eta_fu_hat) |>
matsbyname::clean_byname() |>
# Set row and column types to match other destination matrices.
matsbyname::setrowtype(RCLabels::paste_pref_suff(pref = row_col_types$product,
suff = row_col_types$industry,
notation = RCLabels::arrow_notation)) |>
matsbyname::setcoltype(RCLabels::paste_pref_suff(pref = row_col_types$product,
suff = row_col_types$industry,
notation = RCLabels::from_notation))
expect_equal(res$details_fu, details_fu_mat_expected)
})
test_that("extend_to_useful() works as expected", {
C_data <- load_fu_allocation_data() %>%
form_C_mats()
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs()
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df(apply_fixes = FALSE) %>%
specify_all() %>%
prep_psut() %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
with_useful <- psut_mats %>%
extend_to_useful()
with_useful <- stack_final_useful_df(with_useful, psut_mats)
# Check some of the values
# Allocation of ZAF EIOU electricity for lighting and mechanical drive in 2000
EIOU_Electricity_Coal_mines <- psut_mats %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("U_EIOU") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electricity", "Coal mines")
alloc_EIOU_ZA_2000 <- C_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("C_EIOU") %>%
magrittr::extract2(1)
C_lights <- alloc_EIOU_ZA_2000 %>%
magrittr::extract("Electricity -> Coal mines", "Electric lights -> Light")
C_motors <- alloc_EIOU_ZA_2000 %>%
magrittr::extract("Electricity -> Coal mines", "Electric motors -> MD")
expected_elect_into_lights_in_mines <- EIOU_Electricity_Coal_mines * C_lights
expected_elect_into_motors_in_mines <- EIOU_Electricity_Coal_mines * C_motors
eta_lights <- eta_fu_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric lights -> Light", 1)
eta_motors <- eta_fu_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric motors -> MD", 1)
expected_light_into_mines <- expected_elect_into_lights_in_mines * eta_lights
expected_md_into_mines <- expected_elect_into_motors_in_mines * eta_motors
actual_light_into_mines <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("U_EIOU") %>%
magrittr::extract2(1) %>%
magrittr::extract("Light [from Electric lights]", "Coal mines")
actual_md_into_mines <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("U_EIOU") %>%
magrittr::extract2(1) %>%
magrittr::extract("MD [from Electric motors]", "Coal mines")
expect_equal(actual_light_into_mines, expected_light_into_mines)
expect_equal(actual_md_into_mines, expected_md_into_mines)
# ZAF allocation of Other bituminous coal to MTH.200.C
OBC_to_Chem <- psut_mats %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Other bituminous coal", "Chemical and petrochemical")
alloc_Y_ZA_2000 <- C_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("C_Y") %>%
magrittr::extract2(1)
C_heaters <- alloc_Y_ZA_2000 %>%
magrittr::extract("Other bituminous coal -> Chemical and petrochemical", "Electric heaters -> MTH.200.C")
expected_OBC_into_heaters_in_chem <- OBC_to_Chem * C_heaters
eta_heaters <- eta_fu_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric heaters -> MTH.200.C", 1)
expected_200C_into_chem <- expected_OBC_into_heaters_in_chem * eta_heaters
actual_200C_into_chem <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("MTH.200.C [from Electric heaters]", "Chemical and petrochemical")
expect_equal(actual_200C_into_chem, expected_200C_into_chem)
# Light is a little more complicated, because some electricity is also used for Light in Chem
# First work on OBC
Elect_to_Chem <- psut_mats %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electricity", "Chemical and petrochemical")
C_OBC_light <- alloc_Y_ZA_2000 %>%
magrittr::extract("Other bituminous coal -> Chemical and petrochemical", "Electric lights -> Light")
C_Elect_light <- alloc_Y_ZA_2000 %>%
magrittr::extract("Electricity -> Chemical and petrochemical", "Electric lights -> Light")
expected_OBC_into_lights_in_chem <- OBC_to_Chem * C_OBC_light
expected_Elect_into_lights_in_chem <- Elect_to_Chem * C_Elect_light
expected_OBC_light_into_chem <- expected_OBC_into_lights_in_chem * eta_lights
expected_Elect_light_into_chem <- expected_Elect_into_lights_in_chem * eta_lights
expected_light_into_chem <- expected_OBC_light_into_chem + expected_Elect_light_into_chem
actual_light_into_chem <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Light [from Electric lights]", "Chemical and petrochemical")
expect_equal(actual_light_into_chem, expected_light_into_chem)
# Allocation of GHA final demand electricity for lighting and mechanical drive Non-ferrous metals in 1971
Elect_to_NFM <- psut_mats %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electricity", "Non-ferrous metals")
alloc_Y_GH_1971 <- C_data %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("C_Y") %>%
magrittr::extract2(1)
C_motors <- alloc_Y_GH_1971 %>%
magrittr::extract("Electricity -> Non-ferrous metals", "Electric motors -> MD")
C_lights <- alloc_Y_GH_1971 %>%
magrittr::extract("Electricity -> Non-ferrous metals", "Electric lights -> Light")
expected_elect_into_motors_in_NFM <- Elect_to_NFM * C_motors
expected_elect_into_lights_in_NFM <- Elect_to_NFM * C_lights
eta_motors <- eta_fu_data %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric motors -> MD", 1)
eta_lights <- eta_fu_data %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric lights -> Light", 1)
expected_md_into_NFM <- expected_elect_into_motors_in_NFM * eta_motors
expected_light_into_NFM <- expected_elect_into_lights_in_NFM * eta_lights
actual_md_into_NFM <- with_useful %>%
dplyr::filter(Country == "GHA", Last.stage == "Useful", Year == 1971) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("MD [from Electric motors]", "Non-ferrous metals")
actual_light_into_NFM <- with_useful %>%
dplyr::filter(Country == "GHA", Last.stage == "Useful", Year == 1971) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Light [from Electric lights]", "Non-ferrous metals")
expect_equal(actual_md_into_NFM, expected_md_into_NFM)
expect_equal(actual_light_into_NFM, expected_light_into_NFM)
# Check that a warning is emitted when the energy balance check fails.
# The default 2019 psut_mats (before fixing energy balance) has a slight energy balance mismatch.
# This test sets the tolerance especially tight to force an energy balance failure.
(with_useful_warn <- psut_mats %>%
extend_to_useful(tol = 1e-10)) |>
# We receive 4 warnings, one for each row of the table.
expect_warning("Energy is not balanced") |>
expect_warning("Energy is not balanced") |>
expect_warning("Energy is not balanced") |>
expect_warning("Energy is not balanced")
# Verify that we have correct r_EIOU matrices for the useful stage.
r_EIOU_check <- with_useful %>%
dplyr::mutate(
r_EIOU_check = matsbyname::quotient_byname(U_EIOU, U) %>%
matsbyname::replaceNaN_byname(val = 0),
should_be_zero = matsbyname::difference_byname(r_EIOU_check, r_EIOU),
is_zero = matsbyname::iszero_byname(should_be_zero)
)
expect_true(all(unlist(r_EIOU_check$is_zero)))
# Check that we have details matrices
# None of the rows where last stage is final should have a matrix.
with_useful |>
dplyr::filter(Last.stage == "Final") |>
magrittr::extract2("Y_fu_details") |>
sapply(FUN = is.null) |>
all() |>
expect_true()
with_useful |>
dplyr::filter(Last.stage == "Final") |>
magrittr::extract2("U_EIOU_fu_details") |>
sapply(FUN = is.null) |>
all() |>
expect_true()
# But where Last.stage is useful, we will have matrices
# Test a couple values to make sure everything is working.
Y_fu_details_example <- with_useful |>
dplyr::filter(Last.stage == "Useful") |>
magrittr::extract2("Y_fu_details") |>
magrittr::extract2(1) |>
matsbyname::select_cols_byname(retain_pattern = "Light [from Electric lights]", fixed = TRUE) |>
matsbyname::select_rows_byname(retain_pattern = "Electricity -> Non-ferrous metals") |>
magrittr::extract(1, 1) |>
expect_equal(994.392210)
U_EIOU_fu_details_example <- with_useful |>
dplyr::filter(Last.stage == "Useful") |>
magrittr::extract2("U_EIOU_fu_details") |>
magrittr::extract2(4) |>
matsbyname::select_cols_byname(retain_pattern = "MD [from Electric motors]", fixed = TRUE) |>
matsbyname::select_rows_byname(retain_pattern = "Electricity -> Oil refineries") |>
magrittr::extract(1, 1) |>
expect_equal(32250.355200)
})
test_that("extend_to_useful() works with Matrix objects", {
C_data <- load_fu_allocation_data() %>%
form_C_mats(matrix_class = "Matrix")
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs(matrix_class = "Matrix")
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df(apply_fixes = FALSE) %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
with_useful <- psut_mats %>%
extend_to_useful()
with_useful <- stack_final_useful_df(with_useful, psut_mats)
# Check some of the values
# Allocation of ZAF EIOU electricity for lighting and mechanical drive in 2000
EIOU_Electricity_Coal_mines <- psut_mats %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("U_EIOU") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electricity", "Coal mines")
alloc_EIOU_ZA_2000 <- C_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("C_EIOU") %>%
magrittr::extract2(1)
C_lights <- alloc_EIOU_ZA_2000 %>%
magrittr::extract("Electricity -> Coal mines", "Electric lights -> Light")
C_motors <- alloc_EIOU_ZA_2000 %>%
magrittr::extract("Electricity -> Coal mines", "Electric motors -> MD")
expected_elect_into_lights_in_mines <- EIOU_Electricity_Coal_mines * C_lights
expected_elect_into_motors_in_mines <- EIOU_Electricity_Coal_mines * C_motors
eta_lights <- eta_fu_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric lights -> Light", 1)
eta_motors <- eta_fu_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric motors -> MD", 1)
expected_light_into_mines <- expected_elect_into_lights_in_mines * eta_lights
expected_md_into_mines <- expected_elect_into_motors_in_mines * eta_motors
actual_light_into_mines <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("U_EIOU") %>%
magrittr::extract2(1) %>%
magrittr::extract("Light [from Electric lights]", "Coal mines")
actual_md_into_mines <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("U_EIOU") %>%
magrittr::extract2(1) %>%
magrittr::extract("MD [from Electric motors]", "Coal mines")
expect_equal(actual_light_into_mines, expected_light_into_mines)
expect_equal(actual_md_into_mines, expected_md_into_mines)
# ZAF allocation of Other bituminous coal to MTH.200.C
OBC_to_Chem <- psut_mats %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Other bituminous coal", "Chemical and petrochemical")
alloc_Y_ZA_2000 <- C_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("C_Y") %>%
magrittr::extract2(1)
C_heaters <- alloc_Y_ZA_2000 %>%
magrittr::extract("Other bituminous coal -> Chemical and petrochemical", "Electric heaters -> MTH.200.C")
expected_OBC_into_heaters_in_chem <- OBC_to_Chem * C_heaters
eta_heaters <- eta_fu_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric heaters -> MTH.200.C", 1)
expected_200C_into_chem <- expected_OBC_into_heaters_in_chem * eta_heaters
actual_200C_into_chem <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("MTH.200.C [from Electric heaters]", "Chemical and petrochemical")
expect_equal(actual_200C_into_chem, expected_200C_into_chem)
# Light is a little more complicated, because some electricity is also used for Light in Chem
# First work on OBC
Elect_to_Chem <- psut_mats %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electricity", "Chemical and petrochemical")
C_OBC_light <- alloc_Y_ZA_2000 %>%
magrittr::extract("Other bituminous coal -> Chemical and petrochemical", "Electric lights -> Light")
C_Elect_light <- alloc_Y_ZA_2000 %>%
magrittr::extract("Electricity -> Chemical and petrochemical", "Electric lights -> Light")
expected_OBC_into_lights_in_chem <- OBC_to_Chem * C_OBC_light
expected_Elect_into_lights_in_chem <- Elect_to_Chem * C_Elect_light
expected_OBC_light_into_chem <- expected_OBC_into_lights_in_chem * eta_lights
expected_Elect_light_into_chem <- expected_Elect_into_lights_in_chem * eta_lights
expected_light_into_chem <- expected_OBC_light_into_chem + expected_Elect_light_into_chem
actual_light_into_chem <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Light [from Electric lights]", "Chemical and petrochemical")
expect_equal(actual_light_into_chem, expected_light_into_chem)
# Allocation of GHA final demand electricity for lighting and mechanical drive Non-ferrous metals in 1971
Elect_to_NFM <- psut_mats %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electricity", "Non-ferrous metals")
alloc_Y_GH_1971 <- C_data %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("C_Y") %>%
magrittr::extract2(1)
C_motors <- alloc_Y_GH_1971 %>%
magrittr::extract("Electricity -> Non-ferrous metals", "Electric motors -> MD")
C_lights <- alloc_Y_GH_1971 %>%
magrittr::extract("Electricity -> Non-ferrous metals", "Electric lights -> Light")
expected_elect_into_motors_in_NFM <- Elect_to_NFM * C_motors
expected_elect_into_lights_in_NFM <- Elect_to_NFM * C_lights
eta_motors <- eta_fu_data %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric motors -> MD", 1)
eta_lights <- eta_fu_data %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric lights -> Light", 1)
expected_md_into_NFM <- expected_elect_into_motors_in_NFM * eta_motors
expected_light_into_NFM <- expected_elect_into_lights_in_NFM * eta_lights
actual_md_into_NFM <- with_useful %>%
dplyr::filter(Country == "GHA", Last.stage == "Useful", Year == 1971) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("MD [from Electric motors]", "Non-ferrous metals")
actual_light_into_NFM <- with_useful %>%
dplyr::filter(Country == "GHA", Last.stage == "Useful", Year == 1971) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Light [from Electric lights]", "Non-ferrous metals")
expect_equal(actual_md_into_NFM, expected_md_into_NFM)
expect_equal(actual_light_into_NFM, expected_light_into_NFM)
# Check that a warning is emitted when the energy balance check fails.
# The default 2019 psut_mats (before fixing energy balance) has a slight energy balance mismatch.
# This test sets the tolerance especially tight to force an energy balance failure.
(with_useful_warn <- psut_mats %>%
extend_to_useful(tol = 1e-10)) |>
# Four warnings, one for each row of the psut_mats data frame.
expect_warning("Energy is not balanced") |>
expect_warning("Energy is not balanced") |>
expect_warning("Energy is not balanced") |>
expect_warning("Energy is not balanced")
# Verify that we have correct r_EIOU matrices for the useful stage.
r_EIOU_check <- with_useful %>%
dplyr::mutate(
r_EIOU_check = matsbyname::quotient_byname(U_EIOU, U) %>%
matsbyname::replaceNaN_byname(val = 0),
should_be_zero = matsbyname::difference_byname(r_EIOU_check, r_EIOU),
is_zero = matsbyname::iszero_byname(should_be_zero)
)
expect_true(all(unlist(r_EIOU_check$is_zero)))
# Check that we have details matrices
# None of the rows where last stage is final should have a matrix.
with_useful |>
dplyr::filter(Last.stage == "Final") |>
magrittr::extract2("Y_fu_details") |>
sapply(FUN = is.null) |>
all() |>
expect_true()
with_useful |>
dplyr::filter(Last.stage == "Final") |>
magrittr::extract2("U_EIOU_fu_details") |>
sapply(FUN = is.null) |>
all() |>
expect_true()
# But where Last.stage is useful, we will have matrices
# Test a couple values to make sure everything is working.
Y_fu_details_example <- with_useful |>
dplyr::filter(Last.stage == "Useful") |>
magrittr::extract2("Y_fu_details") |>
magrittr::extract2(1) |>
matsbyname::select_cols_byname(retain_pattern = "Light [from Electric lights]", fixed = TRUE) |>
matsbyname::select_rows_byname(retain_pattern = "Electricity -> Non-ferrous metals") |>
magrittr::extract(1, 1) |>
expect_equal(994.392210)
U_EIOU_fu_details_example <- with_useful |>
dplyr::filter(Last.stage == "Useful") |>
magrittr::extract2("U_EIOU_fu_details") |>
magrittr::extract2(4) |>
matsbyname::select_cols_byname(retain_pattern = "MD [from Electric motors]", fixed = TRUE) |>
matsbyname::select_rows_byname(retain_pattern = "Electricity -> Oil refineries") |>
magrittr::extract(1, 1) |>
expect_equal(32250.355200)
})
test_that("extend_to_useful() works with individual matrices", {
C_data <- load_fu_allocation_data() %>%
form_C_mats()
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs()
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut() %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
useful_mats <- extend_to_useful(R = psut_mats$R[[1]],
U_feed = psut_mats$U_feed[[1]],
U_eiou = psut_mats$U_EIOU[[1]],
U = psut_mats$U[[1]],
r_eiou = psut_mats$r_eiou[[1]],
V = psut_mats$V[[1]],
Y = psut_mats$Y[[1]],
C_eiou = psut_mats$C_EIOU[[1]],
C_Y = psut_mats$C_Y[[1]],
eta_fu = psut_mats$eta.fu[[1]],
phi_u = psut_mats$phi.u[[1]])
# Ensure that expected matrices are included.
# There should be no more matrices than these.
expect_setequal(names(useful_mats),
c("U_feed_Useful", "U_EIOU_Useful", "U_Useful",
"r_EIOU_Useful", "V_Useful", "Y_Useful",
"Y_fu_details", "U_EIOU_fu_details"))
# Try with an adjusted value of C_EIOU.
# This will cause energy imbalance.
C_EIOU_adjusted <- psut_mats$C_EIOU[[1]]
C_EIOU_adjusted[1, 1] <- 1.1 * C_EIOU_adjusted[1, 1]
extend_to_useful(R = psut_mats$R[[1]],
U_feed = psut_mats$U_feed[[1]],
U_eiou = psut_mats$U_EIOU[[1]],
U = psut_mats$U[[1]],
r_eiou = psut_mats$r_eiou[[1]],
V = psut_mats$V[[1]],
Y = psut_mats$Y[[1]],
C_eiou = C_EIOU_adjusted,
C_Y = psut_mats$C_Y[[1]],
eta_fu = psut_mats$eta.fu[[1]],
phi_u = psut_mats$phi.u[[1]]) %>%
expect_warning(regexp = "Energy is not balanced")
# Try with C_eiou missing, thereby ignoring any EIOU.
# Do the same calculation as above, but don't include
# the C_eiou argument.
# This approach should run through the calculations OK, but
# cause an energy imbalance error when checked.
without_C_EIOU <- extend_to_useful(R = psut_mats$R[[1]],
U_feed = psut_mats$U_feed[[1]],
U_eiou = psut_mats$U_EIOU[[1]],
U = psut_mats$U[[1]],
r_eiou = psut_mats$r_eiou[[1]],
V = psut_mats$V[[1]],
Y = psut_mats$Y[[1]],
C_Y = psut_mats$C_Y[[1]],
eta_fu = psut_mats$eta.fu[[1]],
phi_u = psut_mats$phi.u[[1]]) |>
expect_warning(regexp = "Energy is not balanced")
})
test_that("extend_to_useful() works with individual Matrix objects", {
C_data <- load_fu_allocation_data() %>%
form_C_mats(matrix_class = "Matrix")
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs(matrix_class = "Matrix")
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
useful_mats <- extend_to_useful(R = psut_mats$R[[1]],
U_feed = psut_mats$U_feed[[1]],
U_eiou = psut_mats$U_EIOU[[1]],
U = psut_mats$U[[1]],
r_eiou = psut_mats$r_eiou[[1]],
V = psut_mats$V[[1]],
Y = psut_mats$Y[[1]],
C_eiou = psut_mats$C_EIOU[[1]],
C_Y = psut_mats$C_Y[[1]],
eta_fu = psut_mats$eta.fu[[1]],
phi_u = psut_mats$phi.u[[1]])
# Ensure that expected matrices are included.
# There should be no more matrices than these.
expect_equal(names(useful_mats),
c("U_feed_Useful", "U_EIOU_Useful", "U_Useful",
"r_EIOU_Useful", "V_Useful", "Y_Useful",
"Y_fu_details", "U_EIOU_fu_details"))
# Try with C_eiou missing, thereby ignoring any EIOU.
# Do the same calculation as above, but don't include
# the C_eiou argument.
# This approach should run through the calculations OK, but
# cause an energy imbalance error when checked.
extend_to_useful(R = psut_mats$R[[1]],
U_feed = psut_mats$U_feed[[1]],
U_eiou = psut_mats$U_EIOU[[1]],
U = psut_mats$U[[1]],
r_eiou = psut_mats$r_eiou[[1]],
V = psut_mats$V[[1]],
Y = psut_mats$Y[[1]],
C_Y = psut_mats$C_Y[[1]],
eta_fu = psut_mats$eta.fu[[1]],
phi_u = psut_mats$phi.u[[1]]) %>%
expect_warning(regexp = "Energy is not balanced")
})
test_that("extend_to_useful() works with list of matrices", {
C_data <- load_fu_allocation_data() %>%
form_C_mats()
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs()
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut() %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
# Make a list out of the first row of matrices
var_store <- as.list(psut_mats[1, ])
useful_list <- extend_to_useful(var_store)
# When a list is used as the data store, we should get all variables returned.
expect_equal(names(useful_list),
c("Country", "Method", "Energy.type", "Last.stage", "Year",
"Y", "S_units", "R", "U", "U_feed",
"U_EIOU", "r_EIOU", "V", "C_EIOU", "C_Y",
"eta.fu", "phi.u", "U_feed_Useful", "U_EIOU_Useful", "U_Useful",
"r_EIOU_Useful", "V_Useful", "Y_Useful",
"Y_fu_details", "U_EIOU_fu_details"))
})
test_that("extend_to_useful() works with list of Matrix objects", {
C_data <- load_fu_allocation_data() %>%
form_C_mats(matrix_class = "Matrix")
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs(matrix_class = "Matrix")
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
# Make a list out of the first row of matrices
var_store <- as.list(psut_mats[1, ])
useful_list <- extend_to_useful(var_store)
# Ensure all are Matrix objects
for (i in 8:23) {
if (is.list(useful_list[[i]])) {
expect_true(matsbyname::is.Matrix(useful_list[[i]][[1]]))
} else {
expect_true(matsbyname::is.Matrix(useful_list[[i]]))
}
}
# When a list is used as the data store, we should get all variables returned.
expect_equal(names(useful_list),
c("Country", "Method", "Energy.type", "Last.stage", "Year",
"Y", "S_units", "R", "U", "U_feed",
"U_EIOU", "r_EIOU", "V", "C_EIOU", "C_Y",
"eta.fu", "phi.u", "U_feed_Useful", "U_EIOU_Useful", "U_Useful",
"r_EIOU_Useful", "V_Useful", "Y_Useful",
"Y_fu_details", "U_EIOU_fu_details"))
})
test_that("extend_to_useful() works with empty lists", {
C_data <- load_fu_allocation_data() |>
form_C_mats(matrix_class = "Matrix")
eta_fu_data <- load_eta_fu_data() |>
form_eta_fu_phi_u_vecs(matrix_class = "Matrix")
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
# Make a list out of the first row of matrices
var_store <- as.list(psut_mats[0, ])
useful_list <- extend_to_useful(var_store)
expect_setequal(names(useful_list),
c("Country", "Method", "Energy.type", "Last.stage", "Year",
"Y", "S_units", "R", "U", "U_feed",
"U_EIOU", "r_EIOU", "V", "C_EIOU", "C_Y",
"eta.fu", "phi.u", "U_feed_Useful", "U_EIOU_Useful", "U_Useful",
"r_EIOU_Useful", "V_Useful", "Y_Useful"))
expect_true(all(sapply(useful_list, length) == 0))
})
test_that("extend_to_useful() returns works with empty data frames", {
C_data <- load_fu_allocation_data() %>%
form_C_mats(matrix_class = "Matrix")
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs(matrix_class = "Matrix")
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
# Make a no-row data frame.
psut_mats <- psut_mats[0, ]
with_useful <- psut_mats %>%
extend_to_useful()
expect_equal(nrow(with_useful), 0)
expect_setequal(names(with_useful),
c("Country", "Method", "Energy.type", "Last.stage", "Year",
"Y", "S_units", "R", "U", "U_feed",
"U_EIOU", "r_EIOU", "V", "C_EIOU", "C_Y",
"eta.fu", "phi.u", "U_feed_Useful", "U_EIOU_Useful", "U_Useful",
"r_EIOU_Useful", "V_Useful", "Y_Useful"))
})
MatthewHeun/IEATools documentation built on Feb. 6, 2024, 3:29 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
test_that("form_C_mats() works with 0-row input", {
allocation_table <- load_fu_allocation_data()
allocation_table <- allocation_table[0, ]
res <- form_C_mats(allocation_table)
expect_equal(nrow(res), 0)
expect_setequal(names(res), c(IEATools::iea_cols$country, IEATools::iea_cols$method, IEATools::iea_cols$energy_type, IEATools::iea_cols$last_stage, IEATools::iea_cols$year,
IEATools::template_cols$C_eiou, IEATools::template_cols$C_Y))
})
test_that("form_C_mats() works as expected", {
allocation_table <- load_fu_allocation_data()
C_df <- form_C_mats(allocation_table)
# Check type of year column
expect_true(is.numeric(C_df$Year))
# Check that the Unit column is missing. It has no meaning for allocations.
expect_true(is.null(C_df[[IEATools::iea_cols$unit]]))
# Check some values.
C_EIOU_GHA_1971 <- C_df %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2(IEATools::template_cols$C_eiou) %>%
magrittr::extract2(1)
r1 <- "Electricity -> Main activity producer electricity plants"
r2 <- "Refinery gas -> Oil refineries"
c1 <- "Electric lights -> Light"
c2 <- "Electric motors -> MD"
c3 <- "Industrial furnaces -> HTH.600.C"
expect_equal(C_EIOU_GHA_1971[[r1, c1]], 0.5)
expect_equal(C_EIOU_GHA_1971[[r1, c2]], 0.5)
expect_equal(C_EIOU_GHA_1971[[r1, c3]], 0)
expect_equal(C_EIOU_GHA_1971[[r2, c1]], 0)
expect_equal(C_EIOU_GHA_1971[[r2, c2]], 0)
expect_equal(C_EIOU_GHA_1971[[r2, c3]], 1)
C_Y_ZAF_2000 <- C_df %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2(IEATools::template_cols$C_Y) %>%
magrittr::extract2(1)
r1 <- "Blast furnace gas -> Iron and steel"
c1 <- "Airplanes -> MD"
r_kerosene <- "Kerosene type jet fuel excl. biofuels -> Domestic aviation"
c_stoves <- "Industrial furnaces -> HTH.600.C"
expect_equal(C_Y_ZAF_2000[[r1, c_stoves]], 1)
expect_equal(C_Y_ZAF_2000[[r_kerosene, c1]], 1)
# Set a wrong value and expect a warning.
allocation_table_wrong <- allocation_table
allocation_table_wrong[[3, "1971"]] <- 0.9 # Was 1.0. This change should trigger an error on this row.
expect_warning(diagnostic_df <- form_C_mats(allocation_table_wrong), "Not all rows in the C matrices sum to 1.")
# Check that the diagnostic data frame is correct
expect_equal(diagnostic_df[[1, IEATools::mat_meta_cols$rownames]], "Refinery gas -> Oil refineries")
expect_equal(diagnostic_df[[1, ".should_be_1_vector"]], 0.9)
# Check the row and column types
for (i in 1:nrow(C_df)) {
expect_equal(matsbyname::rowtype(C_df$C_EIOU[[i]]), "Product -> Industry")
expect_equal(matsbyname::coltype(C_df$C_EIOU[[i]]), "Industry -> Product")
expect_equal(matsbyname::rowtype(C_df$C_Y[[i]]), "Product -> Industry")
expect_equal(matsbyname::coltype(C_df$C_Y[[i]]), "Industry -> Product")
}
})
test_that("form_C_mats() works with Matrix objects", {
allocation_table <- load_fu_allocation_data()
C_df <- form_C_mats(allocation_table, matrix_class = "Matrix")
# Check that we made Matrix objects.
expect_true(all(sapply(C_df$C_EIOU, matsbyname::is.Matrix)))
expect_true(all(sapply(C_df$C_Y, matsbyname::is.Matrix)))
# Check type of year column
expect_true(is.numeric(C_df$Year))
# Check that the Unit column is missing. It has no meaning for allocations.
expect_true(is.null(C_df[[IEATools::iea_cols$unit]]))
# Check some values.
C_EIOU_GHA_1971 <- C_df %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2(IEATools::template_cols$C_eiou) %>%
magrittr::extract2(1)
r1 <- "Electricity -> Main activity producer electricity plants"
r2 <- "Refinery gas -> Oil refineries"
c1 <- "Electric lights -> Light"
c2 <- "Electric motors -> MD"
c3 <- "Industrial furnaces -> HTH.600.C"
expect_equal(C_EIOU_GHA_1971[r1, c1], 0.5)
expect_equal(C_EIOU_GHA_1971[r1, c2], 0.5)
expect_equal(C_EIOU_GHA_1971[r1, c3], 0)
expect_equal(C_EIOU_GHA_1971[r2, c1], 0)
expect_equal(C_EIOU_GHA_1971[r2, c2], 0)
expect_equal(C_EIOU_GHA_1971[r2, c3], 1)
C_Y_ZAF_2000 <- C_df %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2(IEATools::template_cols$C_Y) %>%
magrittr::extract2(1)
r1 <- "Blast furnace gas -> Iron and steel"
c1 <- "Airplanes -> MD"
r_kerosene <- "Kerosene type jet fuel excl. biofuels -> Domestic aviation"
c_stoves <- "Industrial furnaces -> HTH.600.C"
expect_equal(C_Y_ZAF_2000[r1, c_stoves], 1)
expect_equal(C_Y_ZAF_2000[r_kerosene, c1], 1)
# Set a wrong value and expect a warning.
allocation_table_wrong <- allocation_table
allocation_table_wrong[[3, "1971"]] <- 0.9 # Was 1.0. This change should trigger an error on this row.
expect_warning(diagnostic_df <- form_C_mats(allocation_table_wrong, matrix_class = "Matrix"), "Not all rows in the C matrices sum to 1.")
# Check that the diagnostic data frame is correct
expect_equal(diagnostic_df[[1, IEATools::mat_meta_cols$rownames]], "Refinery gas -> Oil refineries")
expect_equal(diagnostic_df[[1, ".should_be_1_vector"]], 0.9)
# Check the row and column types
for (i in 1:nrow(C_df)) {
expect_equal(matsbyname::rowtype(C_df$C_EIOU[[i]]), "Product -> Industry")
expect_equal(matsbyname::coltype(C_df$C_EIOU[[i]]), "Industry -> Product")
expect_equal(matsbyname::rowtype(C_df$C_Y[[i]]), "Product -> Industry")
expect_equal(matsbyname::coltype(C_df$C_Y[[i]]), "Industry -> Product")
}
})
test_that("form_eta_fu_phi_u_vecs() works as expected", {
efficiency_table <- load_eta_fu_data()
eta_fu_phi_u_df <- form_eta_fu_phi_u_vecs(efficiency_table)
# Check type of year column
expect_true(is.numeric(eta_fu_phi_u_df$Year))
# Check that the Unit column is missing. It has no meaning for allocations.
expect_true(is.null(eta_fu_phi_u_df[[IEATools::iea_cols$unit]]))
# Check some values
eta_GHA_1971 <- eta_fu_phi_u_df$eta.fu[[1]]
expect_equal(eta_GHA_1971[["Irons -> MTH.200.C", 1]], 0.85)
expect_equal(eta_GHA_1971[["Trucks -> MD", 1]], 0.30)
expect_equal(eta_GHA_1971[["Fans -> MD", 1]], 0.10)
expect_equal(eta_GHA_1971[["Boat engines -> MD", 1]], 0.30)
phi_ZAR_2000 <- eta_fu_phi_u_df$phi.u[[4]]
expect_equal(phi_ZAR_2000[["MD", 1]], 1)
expect_equal(phi_ZAR_2000[["LTH.20.C", 1]], 0.0167700821734027)
expect_equal(phi_ZAR_2000[["HTH.600.C", 1]], 0.65853519)
expect_equal(phi_ZAR_2000[["Light", 1]], 0.1830161054172770)
# Check row and column types
for (i in 1:nrow(eta_fu_phi_u_df)) {
expect_equal(matsbyname::rowtype(eta_fu_phi_u_df$eta.fu[[i]]), "Industry -> Product")
expect_equal(matsbyname::coltype(eta_fu_phi_u_df$eta.fu[[i]]), "eta.fu")
}
for (i in 1:nrow(eta_fu_phi_u_df)) {
expect_equal(matsbyname::rowtype(eta_fu_phi_u_df$phi.u[[i]]), "Product")
expect_equal(matsbyname::coltype(eta_fu_phi_u_df$phi.u[[i]]), "phi")
}
})
test_that("form_eta_fu_phi_u_vecs() errors when phi values are different", {
efficiency_table <- load_eta_fu_data()
# Change a value to be different. Change a MD phi value from 1 to 0.99.
expect_equal(efficiency_table[32, "1971"], 1.0)
efficiency_table[32, "1971"] <- 0.9999
expect_equal(efficiency_table[32, "1971"], 0.9999)
expect_error(form_eta_fu_phi_u_vecs(efficiency_table), "Found useful products with different phi values in form_eta_fu_phi_u_vecs")
})
test_that("form_eta_fu_phi_u_vecs() works when the incoming data frame has no rows", {
efficiency_table <- load_eta_fu_data()
efficiency_table <- efficiency_table[0, ]
eta_fu_phi_u_df <- form_eta_fu_phi_u_vecs(efficiency_table)
expect_true(IEATools::template_cols$eta_fu %in% names(eta_fu_phi_u_df))
expect_true(IEATools::template_cols$phi_u %in% names(eta_fu_phi_u_df))
})
test_that("extend_to_useful_helper() works as intended", {
# These tests come from the "Pushing Y to Useful" tab in file "Matrix f->u example calcs.xlsx"
# Set up some matrices and data frames
Y_f <- matrix(c(100, 50,
200, 25), byrow = TRUE, nrow = 2, ncol = 2,
dimnames = list(c("Elect", "Petrol"), c("Residential", "Construction"))) %>%
matsbyname::setrowtype(IEATools::row_col_types$product) %>%
matsbyname::setcoltype(IEATools::row_col_types$industry)
Allocation_Table <- tibble::tribble(~Destination, ~Ef.product, ~Machine, ~Eu.product, ~C,
"Residential", "Elect", "Lights", "Light", 0.5,
"Residential", "Elect", "Water heaters", "MTH", 0.5,
"Construction", "Elect", "Elect motors", "MD", 0.25,
"Construction", "Elect", "Lights", "Light", 0.25,
"Construction", "Elect", "Heaters", "MTH", 0.5,
"Residential", "Petrol", "Engines", "MD", 0.25,
"Residential", "Petrol", "Burner", "MTH", 0.75,
"Construction", "Petrol", "Autos", "MD", 0.6,
"Construction", "Petrol", "Furnace", "LTH", 0.4)
Efficiency_Table <- tibble::tribble(~Machine, ~Eu.product, ~eta.fu,
"Lights", "Light", 0.45,
"Water heaters", "MTH", 0.9,
"Elect motors", "MD", 0.95,
"Heaters", "MTH", 0.9,
"Engines", "MD", 0.25,
"Burner", "MTH", 0.98,
"Autos", "MD", 0.15,
"Furnace", "LTH", 0.97)
# Calculate some matrices
C_Y <- Allocation_Table %>%
dplyr::mutate(
rownames = RCLabels::paste_pref_suff(pref = Ef.product, suff = Destination, notation = RCLabels::arrow_notation),
colnames = RCLabels::paste_pref_suff(pref = Machine, suff = Eu.product, notation = RCLabels::arrow_notation),
rowtypes = RCLabels::paste_pref_suff(pref = row_col_types$product, suff = row_col_types$industry, notation = RCLabels::arrow_notation),
coltypes = RCLabels::paste_pref_suff(pref = row_col_types$industry, suff = row_col_types$product, notation = RCLabels::arrow_notation),
matnames = "C_Y",
Destination = NULL,
Ef.product = NULL,
Machine = NULL,
Eu.product = NULL
) %>%
dplyr::rename(
matvals = C
) %>%
dplyr::group_by(matnames) %>%
matsindf::collapse_to_matrices(matrix_class = "Matrix") %>%
magrittr::extract2("matvals") %>%
magrittr::extract2(1)
eta.fu_rownames <- Efficiency_Table %>%
dplyr::mutate(
rownames = RCLabels::paste_pref_suff(pref = Machine, suff = Eu.product, notation = RCLabels::arrow_notation)
) %>%
magrittr::extract2("rownames")
eta_fu <- Efficiency_Table %>%
magrittr::extract2("eta.fu") %>%
matrix(ncol = 1, dimnames = list(eta.fu_rownames, "eta.fu")) %>%
matsbyname::setrowtype(RCLabels::paste_pref_suff(pref = row_col_types$industry,
suff = row_col_types$product,
notation = RCLabels::arrow_notation))
# Calculate actual results
res <- IEATools:::extend_to_useful_helper(dest_mat = Y_f, C_mat = C_Y, eta_fu_vec = eta_fu)
# Calculate expected results
## Step 1
Y_f_vec <- matsbyname::vectorize_byname(Y_f, notation = RCLabels::arrow_notation)
Y_f_vec_hat <- matsbyname::hatize_byname(Y_f_vec, keep = "rownames")
Y_f_vec_hat_C_Y <- matsbyname::matrixproduct_byname(Y_f_vec_hat, C_Y)
eta_fu_hat <- matsbyname::hatize_byname(eta_fu, keep = "rownames") %>%
arrow_to_from_byname(margin = 2)
expect_equal(eta_fu_hat[["Engines -> MD", "MD [from Engines]"]],
Efficiency_Table %>% dplyr::filter(Machine == "Engines") %>%
magrittr::extract2("eta.fu"))
## Step 2
add_to_U_feed_expected <- Y_f_vec_hat_C_Y %>%
matsbyname::aggregate_to_pref_suff_byname(keep = "pref", margin = 1, notation = RCLabels::arrow_notation) %>%
matsbyname::clean_byname(margin = 1) %>%
matsbyname::setcoltype(row_col_types$industry)
expect_equal(res$add_to_U, add_to_U_feed_expected)
## Step 3
add_to_V_expected <- Y_f_vec_hat_C_Y %>%
matsbyname::colsums_byname() %>%
matsbyname::hatize_byname(keep = "colnames") %>%
matsbyname::matrixproduct_byname(eta_fu_hat) %>%
matsbyname::setrowtype(row_col_types$industry) %>%
matsbyname::setcoltype(row_col_types$product)
expect_equal(res$add_to_V, add_to_V_expected)
## Step 4
add_to_Y_expected <- matsbyname::matrixproduct_byname(Y_f_vec_hat_C_Y, eta_fu_hat) %>%
matsbyname::transpose_byname() %>%
matsbyname::aggregate_to_pref_suff_byname(keep = "suff", margin = 2, notation = RCLabels::arrow_notation) %>%
matsbyname::clean_byname() %>%
matsbyname::setrowtype(row_col_types$product) %>%
matsbyname::setcoltype(row_col_types$industry)
expect_equal(res$add_to_dest, add_to_Y_expected)
## Now check the details fu matrix
details_fu_mat_expected <- matsbyname::matrixproduct_byname(Y_f_vec_hat_C_Y, eta_fu_hat) |>
matsbyname::clean_byname() |>
# Set row and column types to match other destination matrices.
matsbyname::setrowtype(RCLabels::paste_pref_suff(pref = row_col_types$product,
suff = row_col_types$industry,
notation = RCLabels::arrow_notation)) |>
matsbyname::setcoltype(RCLabels::paste_pref_suff(pref = row_col_types$product,
suff = row_col_types$industry,
notation = RCLabels::from_notation))
expect_equal(res$details_fu, details_fu_mat_expected)
})
test_that("extend_to_useful() works as expected", {
C_data <- load_fu_allocation_data() %>%
form_C_mats()
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs()
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df(apply_fixes = FALSE) %>%
specify_all() %>%
prep_psut() %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
with_useful <- psut_mats %>%
extend_to_useful()
with_useful <- stack_final_useful_df(with_useful, psut_mats)
# Check some of the values
# Allocation of ZAF EIOU electricity for lighting and mechanical drive in 2000
EIOU_Electricity_Coal_mines <- psut_mats %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("U_EIOU") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electricity", "Coal mines")
alloc_EIOU_ZA_2000 <- C_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("C_EIOU") %>%
magrittr::extract2(1)
C_lights <- alloc_EIOU_ZA_2000 %>%
magrittr::extract("Electricity -> Coal mines", "Electric lights -> Light")
C_motors <- alloc_EIOU_ZA_2000 %>%
magrittr::extract("Electricity -> Coal mines", "Electric motors -> MD")
expected_elect_into_lights_in_mines <- EIOU_Electricity_Coal_mines * C_lights
expected_elect_into_motors_in_mines <- EIOU_Electricity_Coal_mines * C_motors
eta_lights <- eta_fu_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric lights -> Light", 1)
eta_motors <- eta_fu_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric motors -> MD", 1)
expected_light_into_mines <- expected_elect_into_lights_in_mines * eta_lights
expected_md_into_mines <- expected_elect_into_motors_in_mines * eta_motors
actual_light_into_mines <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("U_EIOU") %>%
magrittr::extract2(1) %>%
magrittr::extract("Light [from Electric lights]", "Coal mines")
actual_md_into_mines <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("U_EIOU") %>%
magrittr::extract2(1) %>%
magrittr::extract("MD [from Electric motors]", "Coal mines")
expect_equal(actual_light_into_mines, expected_light_into_mines)
expect_equal(actual_md_into_mines, expected_md_into_mines)
# ZAF allocation of Other bituminous coal to MTH.200.C
OBC_to_Chem <- psut_mats %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Other bituminous coal", "Chemical and petrochemical")
alloc_Y_ZA_2000 <- C_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("C_Y") %>%
magrittr::extract2(1)
C_heaters <- alloc_Y_ZA_2000 %>%
magrittr::extract("Other bituminous coal -> Chemical and petrochemical", "Electric heaters -> MTH.200.C")
expected_OBC_into_heaters_in_chem <- OBC_to_Chem * C_heaters
eta_heaters <- eta_fu_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric heaters -> MTH.200.C", 1)
expected_200C_into_chem <- expected_OBC_into_heaters_in_chem * eta_heaters
actual_200C_into_chem <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("MTH.200.C [from Electric heaters]", "Chemical and petrochemical")
expect_equal(actual_200C_into_chem, expected_200C_into_chem)
# Light is a little more complicated, because some electricity is also used for Light in Chem
# First work on OBC
Elect_to_Chem <- psut_mats %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electricity", "Chemical and petrochemical")
C_OBC_light <- alloc_Y_ZA_2000 %>%
magrittr::extract("Other bituminous coal -> Chemical and petrochemical", "Electric lights -> Light")
C_Elect_light <- alloc_Y_ZA_2000 %>%
magrittr::extract("Electricity -> Chemical and petrochemical", "Electric lights -> Light")
expected_OBC_into_lights_in_chem <- OBC_to_Chem * C_OBC_light
expected_Elect_into_lights_in_chem <- Elect_to_Chem * C_Elect_light
expected_OBC_light_into_chem <- expected_OBC_into_lights_in_chem * eta_lights
expected_Elect_light_into_chem <- expected_Elect_into_lights_in_chem * eta_lights
expected_light_into_chem <- expected_OBC_light_into_chem + expected_Elect_light_into_chem
actual_light_into_chem <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Light [from Electric lights]", "Chemical and petrochemical")
expect_equal(actual_light_into_chem, expected_light_into_chem)
# Allocation of GHA final demand electricity for lighting and mechanical drive Non-ferrous metals in 1971
Elect_to_NFM <- psut_mats %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electricity", "Non-ferrous metals")
alloc_Y_GH_1971 <- C_data %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("C_Y") %>%
magrittr::extract2(1)
C_motors <- alloc_Y_GH_1971 %>%
magrittr::extract("Electricity -> Non-ferrous metals", "Electric motors -> MD")
C_lights <- alloc_Y_GH_1971 %>%
magrittr::extract("Electricity -> Non-ferrous metals", "Electric lights -> Light")
expected_elect_into_motors_in_NFM <- Elect_to_NFM * C_motors
expected_elect_into_lights_in_NFM <- Elect_to_NFM * C_lights
eta_motors <- eta_fu_data %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric motors -> MD", 1)
eta_lights <- eta_fu_data %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric lights -> Light", 1)
expected_md_into_NFM <- expected_elect_into_motors_in_NFM * eta_motors
expected_light_into_NFM <- expected_elect_into_lights_in_NFM * eta_lights
actual_md_into_NFM <- with_useful %>%
dplyr::filter(Country == "GHA", Last.stage == "Useful", Year == 1971) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("MD [from Electric motors]", "Non-ferrous metals")
actual_light_into_NFM <- with_useful %>%
dplyr::filter(Country == "GHA", Last.stage == "Useful", Year == 1971) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Light [from Electric lights]", "Non-ferrous metals")
expect_equal(actual_md_into_NFM, expected_md_into_NFM)
expect_equal(actual_light_into_NFM, expected_light_into_NFM)
# Check that a warning is emitted when the energy balance check fails.
# The default 2019 psut_mats (before fixing energy balance) has a slight energy balance mismatch.
# This test sets the tolerance especially tight to force an energy balance failure.
(with_useful_warn <- psut_mats %>%
extend_to_useful(tol = 1e-10)) |>
# We receive 4 warnings, one for each row of the table.
expect_warning("Energy is not balanced") |>
expect_warning("Energy is not balanced") |>
expect_warning("Energy is not balanced") |>
expect_warning("Energy is not balanced")
# Verify that we have correct r_EIOU matrices for the useful stage.
r_EIOU_check <- with_useful %>%
dplyr::mutate(
r_EIOU_check = matsbyname::quotient_byname(U_EIOU, U) %>%
matsbyname::replaceNaN_byname(val = 0),
should_be_zero = matsbyname::difference_byname(r_EIOU_check, r_EIOU),
is_zero = matsbyname::iszero_byname(should_be_zero)
)
expect_true(all(unlist(r_EIOU_check$is_zero)))
# Check that we have details matrices
# None of the rows where last stage is final should have a matrix.
with_useful |>
dplyr::filter(Last.stage == "Final") |>
magrittr::extract2("Y_fu_details") |>
sapply(FUN = is.null) |>
all() |>
expect_true()
with_useful |>
dplyr::filter(Last.stage == "Final") |>
magrittr::extract2("U_EIOU_fu_details") |>
sapply(FUN = is.null) |>
all() |>
expect_true()
# But where Last.stage is useful, we will have matrices
# Test a couple values to make sure everything is working.
Y_fu_details_example <- with_useful |>
dplyr::filter(Last.stage == "Useful") |>
magrittr::extract2("Y_fu_details") |>
magrittr::extract2(1) |>
matsbyname::select_cols_byname(retain_pattern = "Light [from Electric lights]", fixed = TRUE) |>
matsbyname::select_rows_byname(retain_pattern = "Electricity -> Non-ferrous metals") |>
magrittr::extract(1, 1) |>
expect_equal(994.392210)
U_EIOU_fu_details_example <- with_useful |>
dplyr::filter(Last.stage == "Useful") |>
magrittr::extract2("U_EIOU_fu_details") |>
magrittr::extract2(4) |>
matsbyname::select_cols_byname(retain_pattern = "MD [from Electric motors]", fixed = TRUE) |>
matsbyname::select_rows_byname(retain_pattern = "Electricity -> Oil refineries") |>
magrittr::extract(1, 1) |>
expect_equal(32250.355200)
})
test_that("extend_to_useful() works with Matrix objects", {
C_data <- load_fu_allocation_data() %>%
form_C_mats(matrix_class = "Matrix")
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs(matrix_class = "Matrix")
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df(apply_fixes = FALSE) %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
with_useful <- psut_mats %>%
extend_to_useful()
with_useful <- stack_final_useful_df(with_useful, psut_mats)
# Check some of the values
# Allocation of ZAF EIOU electricity for lighting and mechanical drive in 2000
EIOU_Electricity_Coal_mines <- psut_mats %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("U_EIOU") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electricity", "Coal mines")
alloc_EIOU_ZA_2000 <- C_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("C_EIOU") %>%
magrittr::extract2(1)
C_lights <- alloc_EIOU_ZA_2000 %>%
magrittr::extract("Electricity -> Coal mines", "Electric lights -> Light")
C_motors <- alloc_EIOU_ZA_2000 %>%
magrittr::extract("Electricity -> Coal mines", "Electric motors -> MD")
expected_elect_into_lights_in_mines <- EIOU_Electricity_Coal_mines * C_lights
expected_elect_into_motors_in_mines <- EIOU_Electricity_Coal_mines * C_motors
eta_lights <- eta_fu_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric lights -> Light", 1)
eta_motors <- eta_fu_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric motors -> MD", 1)
expected_light_into_mines <- expected_elect_into_lights_in_mines * eta_lights
expected_md_into_mines <- expected_elect_into_motors_in_mines * eta_motors
actual_light_into_mines <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("U_EIOU") %>%
magrittr::extract2(1) %>%
magrittr::extract("Light [from Electric lights]", "Coal mines")
actual_md_into_mines <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("U_EIOU") %>%
magrittr::extract2(1) %>%
magrittr::extract("MD [from Electric motors]", "Coal mines")
expect_equal(actual_light_into_mines, expected_light_into_mines)
expect_equal(actual_md_into_mines, expected_md_into_mines)
# ZAF allocation of Other bituminous coal to MTH.200.C
OBC_to_Chem <- psut_mats %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Other bituminous coal", "Chemical and petrochemical")
alloc_Y_ZA_2000 <- C_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("C_Y") %>%
magrittr::extract2(1)
C_heaters <- alloc_Y_ZA_2000 %>%
magrittr::extract("Other bituminous coal -> Chemical and petrochemical", "Electric heaters -> MTH.200.C")
expected_OBC_into_heaters_in_chem <- OBC_to_Chem * C_heaters
eta_heaters <- eta_fu_data %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric heaters -> MTH.200.C", 1)
expected_200C_into_chem <- expected_OBC_into_heaters_in_chem * eta_heaters
actual_200C_into_chem <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("MTH.200.C [from Electric heaters]", "Chemical and petrochemical")
expect_equal(actual_200C_into_chem, expected_200C_into_chem)
# Light is a little more complicated, because some electricity is also used for Light in Chem
# First work on OBC
Elect_to_Chem <- psut_mats %>%
dplyr::filter(Country == "ZAF", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electricity", "Chemical and petrochemical")
C_OBC_light <- alloc_Y_ZA_2000 %>%
magrittr::extract("Other bituminous coal -> Chemical and petrochemical", "Electric lights -> Light")
C_Elect_light <- alloc_Y_ZA_2000 %>%
magrittr::extract("Electricity -> Chemical and petrochemical", "Electric lights -> Light")
expected_OBC_into_lights_in_chem <- OBC_to_Chem * C_OBC_light
expected_Elect_into_lights_in_chem <- Elect_to_Chem * C_Elect_light
expected_OBC_light_into_chem <- expected_OBC_into_lights_in_chem * eta_lights
expected_Elect_light_into_chem <- expected_Elect_into_lights_in_chem * eta_lights
expected_light_into_chem <- expected_OBC_light_into_chem + expected_Elect_light_into_chem
actual_light_into_chem <- with_useful %>%
dplyr::filter(Country == "ZAF", Last.stage == "Useful", Year == 2000) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Light [from Electric lights]", "Chemical and petrochemical")
expect_equal(actual_light_into_chem, expected_light_into_chem)
# Allocation of GHA final demand electricity for lighting and mechanical drive Non-ferrous metals in 1971
Elect_to_NFM <- psut_mats %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electricity", "Non-ferrous metals")
alloc_Y_GH_1971 <- C_data %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("C_Y") %>%
magrittr::extract2(1)
C_motors <- alloc_Y_GH_1971 %>%
magrittr::extract("Electricity -> Non-ferrous metals", "Electric motors -> MD")
C_lights <- alloc_Y_GH_1971 %>%
magrittr::extract("Electricity -> Non-ferrous metals", "Electric lights -> Light")
expected_elect_into_motors_in_NFM <- Elect_to_NFM * C_motors
expected_elect_into_lights_in_NFM <- Elect_to_NFM * C_lights
eta_motors <- eta_fu_data %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric motors -> MD", 1)
eta_lights <- eta_fu_data %>%
dplyr::filter(Country == "GHA", Year == 1971) %>%
magrittr::extract2("eta.fu") %>%
magrittr::extract2(1) %>%
magrittr::extract("Electric lights -> Light", 1)
expected_md_into_NFM <- expected_elect_into_motors_in_NFM * eta_motors
expected_light_into_NFM <- expected_elect_into_lights_in_NFM * eta_lights
actual_md_into_NFM <- with_useful %>%
dplyr::filter(Country == "GHA", Last.stage == "Useful", Year == 1971) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("MD [from Electric motors]", "Non-ferrous metals")
actual_light_into_NFM <- with_useful %>%
dplyr::filter(Country == "GHA", Last.stage == "Useful", Year == 1971) %>%
magrittr::extract2("Y") %>%
magrittr::extract2(1) %>%
magrittr::extract("Light [from Electric lights]", "Non-ferrous metals")
expect_equal(actual_md_into_NFM, expected_md_into_NFM)
expect_equal(actual_light_into_NFM, expected_light_into_NFM)
# Check that a warning is emitted when the energy balance check fails.
# The default 2019 psut_mats (before fixing energy balance) has a slight energy balance mismatch.
# This test sets the tolerance especially tight to force an energy balance failure.
(with_useful_warn <- psut_mats %>%
extend_to_useful(tol = 1e-10)) |>
# Four warnings, one for each row of the psut_mats data frame.
expect_warning("Energy is not balanced") |>
expect_warning("Energy is not balanced") |>
expect_warning("Energy is not balanced") |>
expect_warning("Energy is not balanced")
# Verify that we have correct r_EIOU matrices for the useful stage.
r_EIOU_check <- with_useful %>%
dplyr::mutate(
r_EIOU_check = matsbyname::quotient_byname(U_EIOU, U) %>%
matsbyname::replaceNaN_byname(val = 0),
should_be_zero = matsbyname::difference_byname(r_EIOU_check, r_EIOU),
is_zero = matsbyname::iszero_byname(should_be_zero)
)
expect_true(all(unlist(r_EIOU_check$is_zero)))
# Check that we have details matrices
# None of the rows where last stage is final should have a matrix.
with_useful |>
dplyr::filter(Last.stage == "Final") |>
magrittr::extract2("Y_fu_details") |>
sapply(FUN = is.null) |>
all() |>
expect_true()
with_useful |>
dplyr::filter(Last.stage == "Final") |>
magrittr::extract2("U_EIOU_fu_details") |>
sapply(FUN = is.null) |>
all() |>
expect_true()
# But where Last.stage is useful, we will have matrices
# Test a couple values to make sure everything is working.
Y_fu_details_example <- with_useful |>
dplyr::filter(Last.stage == "Useful") |>
magrittr::extract2("Y_fu_details") |>
magrittr::extract2(1) |>
matsbyname::select_cols_byname(retain_pattern = "Light [from Electric lights]", fixed = TRUE) |>
matsbyname::select_rows_byname(retain_pattern = "Electricity -> Non-ferrous metals") |>
magrittr::extract(1, 1) |>
expect_equal(994.392210)
U_EIOU_fu_details_example <- with_useful |>
dplyr::filter(Last.stage == "Useful") |>
magrittr::extract2("U_EIOU_fu_details") |>
magrittr::extract2(4) |>
matsbyname::select_cols_byname(retain_pattern = "MD [from Electric motors]", fixed = TRUE) |>
matsbyname::select_rows_byname(retain_pattern = "Electricity -> Oil refineries") |>
magrittr::extract(1, 1) |>
expect_equal(32250.355200)
})
test_that("extend_to_useful() works with individual matrices", {
C_data <- load_fu_allocation_data() %>%
form_C_mats()
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs()
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut() %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
useful_mats <- extend_to_useful(R = psut_mats$R[[1]],
U_feed = psut_mats$U_feed[[1]],
U_eiou = psut_mats$U_EIOU[[1]],
U = psut_mats$U[[1]],
r_eiou = psut_mats$r_eiou[[1]],
V = psut_mats$V[[1]],
Y = psut_mats$Y[[1]],
C_eiou = psut_mats$C_EIOU[[1]],
C_Y = psut_mats$C_Y[[1]],
eta_fu = psut_mats$eta.fu[[1]],
phi_u = psut_mats$phi.u[[1]])
# Ensure that expected matrices are included.
# There should be no more matrices than these.
expect_setequal(names(useful_mats),
c("U_feed_Useful", "U_EIOU_Useful", "U_Useful",
"r_EIOU_Useful", "V_Useful", "Y_Useful",
"Y_fu_details", "U_EIOU_fu_details"))
# Try with an adjusted value of C_EIOU.
# This will cause energy imbalance.
C_EIOU_adjusted <- psut_mats$C_EIOU[[1]]
C_EIOU_adjusted[1, 1] <- 1.1 * C_EIOU_adjusted[1, 1]
extend_to_useful(R = psut_mats$R[[1]],
U_feed = psut_mats$U_feed[[1]],
U_eiou = psut_mats$U_EIOU[[1]],
U = psut_mats$U[[1]],
r_eiou = psut_mats$r_eiou[[1]],
V = psut_mats$V[[1]],
Y = psut_mats$Y[[1]],
C_eiou = C_EIOU_adjusted,
C_Y = psut_mats$C_Y[[1]],
eta_fu = psut_mats$eta.fu[[1]],
phi_u = psut_mats$phi.u[[1]]) %>%
expect_warning(regexp = "Energy is not balanced")
# Try with C_eiou missing, thereby ignoring any EIOU.
# Do the same calculation as above, but don't include
# the C_eiou argument.
# This approach should run through the calculations OK, but
# cause an energy imbalance error when checked.
without_C_EIOU <- extend_to_useful(R = psut_mats$R[[1]],
U_feed = psut_mats$U_feed[[1]],
U_eiou = psut_mats$U_EIOU[[1]],
U = psut_mats$U[[1]],
r_eiou = psut_mats$r_eiou[[1]],
V = psut_mats$V[[1]],
Y = psut_mats$Y[[1]],
C_Y = psut_mats$C_Y[[1]],
eta_fu = psut_mats$eta.fu[[1]],
phi_u = psut_mats$phi.u[[1]]) |>
expect_warning(regexp = "Energy is not balanced")
})
test_that("extend_to_useful() works with individual Matrix objects", {
C_data <- load_fu_allocation_data() %>%
form_C_mats(matrix_class = "Matrix")
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs(matrix_class = "Matrix")
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
useful_mats <- extend_to_useful(R = psut_mats$R[[1]],
U_feed = psut_mats$U_feed[[1]],
U_eiou = psut_mats$U_EIOU[[1]],
U = psut_mats$U[[1]],
r_eiou = psut_mats$r_eiou[[1]],
V = psut_mats$V[[1]],
Y = psut_mats$Y[[1]],
C_eiou = psut_mats$C_EIOU[[1]],
C_Y = psut_mats$C_Y[[1]],
eta_fu = psut_mats$eta.fu[[1]],
phi_u = psut_mats$phi.u[[1]])
# Ensure that expected matrices are included.
# There should be no more matrices than these.
expect_equal(names(useful_mats),
c("U_feed_Useful", "U_EIOU_Useful", "U_Useful",
"r_EIOU_Useful", "V_Useful", "Y_Useful",
"Y_fu_details", "U_EIOU_fu_details"))
# Try with C_eiou missing, thereby ignoring any EIOU.
# Do the same calculation as above, but don't include
# the C_eiou argument.
# This approach should run through the calculations OK, but
# cause an energy imbalance error when checked.
extend_to_useful(R = psut_mats$R[[1]],
U_feed = psut_mats$U_feed[[1]],
U_eiou = psut_mats$U_EIOU[[1]],
U = psut_mats$U[[1]],
r_eiou = psut_mats$r_eiou[[1]],
V = psut_mats$V[[1]],
Y = psut_mats$Y[[1]],
C_Y = psut_mats$C_Y[[1]],
eta_fu = psut_mats$eta.fu[[1]],
phi_u = psut_mats$phi.u[[1]]) %>%
expect_warning(regexp = "Energy is not balanced")
})
test_that("extend_to_useful() works with list of matrices", {
C_data <- load_fu_allocation_data() %>%
form_C_mats()
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs()
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut() %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
# Make a list out of the first row of matrices
var_store <- as.list(psut_mats[1, ])
useful_list <- extend_to_useful(var_store)
# When a list is used as the data store, we should get all variables returned.
expect_equal(names(useful_list),
c("Country", "Method", "Energy.type", "Last.stage", "Year",
"Y", "S_units", "R", "U", "U_feed",
"U_EIOU", "r_EIOU", "V", "C_EIOU", "C_Y",
"eta.fu", "phi.u", "U_feed_Useful", "U_EIOU_Useful", "U_Useful",
"r_EIOU_Useful", "V_Useful", "Y_Useful",
"Y_fu_details", "U_EIOU_fu_details"))
})
test_that("extend_to_useful() works with list of Matrix objects", {
C_data <- load_fu_allocation_data() %>%
form_C_mats(matrix_class = "Matrix")
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs(matrix_class = "Matrix")
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
# Make a list out of the first row of matrices
var_store <- as.list(psut_mats[1, ])
useful_list <- extend_to_useful(var_store)
# Ensure all are Matrix objects
for (i in 8:23) {
if (is.list(useful_list[[i]])) {
expect_true(matsbyname::is.Matrix(useful_list[[i]][[1]]))
} else {
expect_true(matsbyname::is.Matrix(useful_list[[i]]))
}
}
# When a list is used as the data store, we should get all variables returned.
expect_equal(names(useful_list),
c("Country", "Method", "Energy.type", "Last.stage", "Year",
"Y", "S_units", "R", "U", "U_feed",
"U_EIOU", "r_EIOU", "V", "C_EIOU", "C_Y",
"eta.fu", "phi.u", "U_feed_Useful", "U_EIOU_Useful", "U_Useful",
"r_EIOU_Useful", "V_Useful", "Y_Useful",
"Y_fu_details", "U_EIOU_fu_details"))
})
test_that("extend_to_useful() works with empty lists", {
C_data <- load_fu_allocation_data() |>
form_C_mats(matrix_class = "Matrix")
eta_fu_data <- load_eta_fu_data() |>
form_eta_fu_phi_u_vecs(matrix_class = "Matrix")
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
# Make a list out of the first row of matrices
var_store <- as.list(psut_mats[0, ])
useful_list <- extend_to_useful(var_store)
expect_setequal(names(useful_list),
c("Country", "Method", "Energy.type", "Last.stage", "Year",
"Y", "S_units", "R", "U", "U_feed",
"U_EIOU", "r_EIOU", "V", "C_EIOU", "C_Y",
"eta.fu", "phi.u", "U_feed_Useful", "U_EIOU_Useful", "U_Useful",
"r_EIOU_Useful", "V_Useful", "Y_Useful"))
expect_true(all(sapply(useful_list, length) == 0))
})
test_that("extend_to_useful() returns works with empty data frames", {
C_data <- load_fu_allocation_data() %>%
form_C_mats(matrix_class = "Matrix")
eta_fu_data <- load_eta_fu_data() %>%
form_eta_fu_phi_u_vecs(matrix_class = "Matrix")
m_cols <- eta_fu_data %>%
IEATools::meta_cols(return_names = TRUE,
years_to_keep = IEATools::iea_cols$year,
not_meta = c(IEATools::template_cols$eta_fu, IEATools::template_cols$phi_u))
psut_mats <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
dplyr::full_join(C_data, by = m_cols) %>%
dplyr::full_join(eta_fu_data, by = m_cols)
# Make a no-row data frame.
psut_mats <- psut_mats[0, ]
with_useful <- psut_mats %>%
extend_to_useful()
expect_equal(nrow(with_useful), 0)
expect_setequal(names(with_useful),
c("Country", "Method", "Energy.type", "Last.stage", "Year",
"Y", "S_units", "R", "U", "U_feed",
"U_EIOU", "r_EIOU", "V", "C_EIOU", "C_Y",
"eta.fu", "phi.u", "U_feed_Useful", "U_EIOU_Useful", "U_Useful",
"r_EIOU_Useful", "V_Useful", "Y_Useful"))
})
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.