tests/testthat/test-psut.R
In MatthewHeun/IEATools: Tools for Working with International Energy Agency Data
test_that("extract_S_units_from_tidy() works as expected", {
S_units <- load_tidy_iea_df() %>%
extract_S_units_from_tidy()
for (i in nrow(S_units)) {
su <- S_units$S_units[[i]]
expect_true(all(su[ , "TJ"] == 1))
}
})
test_that("extract_S_units_from_tidy() works with Matrix objects", {
S_units <- load_tidy_iea_df() %>%
extract_S_units_from_tidy(matrix_class = "Matrix")
for (i in nrow(S_units)) {
su <- S_units$S_units[[i]]
expect_true(matsbyname::is.Matrix(su))
expect_true(all(su[ , "TJ"] == 1))
}
})
test_that("add_psut_matnames() works as expected for R_includes_all_exogenous_flows = FALSE", {
With_matnames <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames(R_includes_all_exogenous_flows = FALSE)
# Ensure that none of the matnames are NA
expect_false(any(is.na(With_matnames$matnames)))
# Specific checks
# Resources
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Resources")) %>% magrittr::extract2("matnames") %>% magrittr::equals("R") %>% all())
# Imports
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Imports")) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
# Exports
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Exports")) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
# International marine bunkers
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International marine bunkers") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International marine bunkers") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
# International aviation bunkers
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International aviation bunkers") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International aviation bunkers") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
# Stock changes
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Stock changes") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Stock changes") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
# Transformation processes
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow.aggregation.point, "Transformation processes") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("U_feed") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow.aggregation.point, "Transformation processes") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
# EIOU
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow.aggregation.point, "Energy industry own use") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("U_EIOU") %>% all())
# Consumption
expect_true(With_matnames %>% dplyr::filter(startsWith(Ledger.side, "Consumption")) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
# Transfers
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Transfers") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("U_feed") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Transfers") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
With_matnames <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B
) %>%
add_psut_matnames()
expect_equal(With_matnames %>% dplyr::filter(matnames == "B") %>% nrow(), 2)
With_matnames_2 <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B)
expect_true(all(With_matnames == With_matnames_2))
})
test_that("add_psut_matnames() works as expected for R_includes_all_exogenous_flows = TRUE", {
With_matnames <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames()
# Ensure that none of the matnames are NA
expect_false(any(is.na(With_matnames$matnames)))
# Specific checks
# Resources
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Resources")) %>% magrittr::extract2("matnames") %>% magrittr::equals("R") %>% all())
# Imports
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Imports")) %>% magrittr::extract2("matnames") %>% magrittr::equals("R") %>% all())
# Exports
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Exports")) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
# International marine bunkers
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International marine bunkers") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International marine bunkers") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("R") %>% all())
# International aviation bunkers
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International aviation bunkers") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International aviation bunkers") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("R") %>% all())
# Stock changes
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Stock changes") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Stock changes") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("R") %>% all())
# Transformation processes
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow.aggregation.point, "Transformation processes") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("U_feed") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow.aggregation.point, "Transformation processes") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
# EIOU
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow.aggregation.point, "Energy industry own use") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("U_EIOU") %>% all())
# Consumption
expect_true(With_matnames %>% dplyr::filter(startsWith(Ledger.side, "Consumption")) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
# Transfers
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Transfers") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("U_feed") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Transfers") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
})
test_that("add_row_col_meta() works as expected", {
With_meta <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B
) %>%
add_row_col_meta()
# Ensure that every row is filled in the new columns.
expect_false(any(is.na(With_meta$rownames)))
expect_false(any(is.na(With_meta$colnames)))
expect_false(any(is.na(With_meta$rowtypes)))
expect_false(any(is.na(With_meta$coltypes)))
# Ensure that row and column types are correct
expect_true(With_meta %>% dplyr::filter(matnames == "R" | matnames == "V") %>% magrittr::extract2("rowtypes") %>% magrittr::equals("Industry") %>% all())
expect_true(With_meta %>% dplyr::filter(matnames == "R" | matnames == "V") %>% magrittr::extract2("coltypes") %>% magrittr::equals("Product") %>% all())
expect_true(With_meta %>% dplyr::filter(startsWith(matnames, "U") | matnames == "Y") %>% magrittr::extract2("rowtypes") %>% magrittr::equals("Product") %>% all())
expect_true(With_meta %>% dplyr::filter(startsWith(matnames, "U") | matnames == "Y") %>% magrittr::extract2("coltypes") %>% magrittr::equals("Industry") %>% all())
expect_true(With_meta %>% dplyr::filter(startsWith(matnames, "B")) %>% magrittr::extract2("rowtypes") %>% magrittr::equals("Product") %>% all())
expect_true(With_meta %>% dplyr::filter(startsWith(matnames, "B")) %>% magrittr::extract2("coltypes") %>% magrittr::equals("Industry") %>% all())
# Ensure that row and column identifiers are correct
# Rows of R and V are the Flow names
magrittr::equals(With_meta %>% dplyr::filter(matnames == "R" | matnames == "V") %>% magrittr::extract2("rownames"),
With_meta %>% dplyr::filter(matnames == "R" | matnames == "V") %>% magrittr::extract2("Flow")) %>%
all() %>%
expect_true()
# Columns of R and V are the Product names
magrittr::equals(With_meta %>% dplyr::filter(matnames == "R" | matnames == "V") %>% magrittr::extract2("colnames"),
With_meta %>% dplyr::filter(matnames == "R" | matnames == "V") %>% magrittr::extract2("Product")) %>%
all() %>%
expect_true()
# Rows of U and Y are the Product names
magrittr::equals(With_meta %>% dplyr::filter(matnames == "U" | matnames == "Y") %>% magrittr::extract2("rownames"),
With_meta %>% dplyr::filter(matnames == "U" | matnames == "Y") %>% magrittr::extract2("Product")) %>%
all() %>%
expect_true()
# Rows of B are the Product names
magrittr::equals(With_meta %>% dplyr::filter(matnames == "B") %>% magrittr::extract2("rownames"),
With_meta %>% dplyr::filter(matnames == "B") %>% magrittr::extract2("Product")) %>%
all() %>%
expect_true()
# Columns of U and Y are the Flow names
magrittr::equals(With_meta %>% dplyr::filter(matnames == "U" | matnames == "Y") %>% magrittr::extract2("colnames"),
With_meta %>% dplyr::filter(matnames == "U" | matnames == "Y") %>% magrittr::extract2("Flow")) %>%
all() %>%
expect_true()
magrittr::equals(With_meta %>% dplyr::filter(matnames == "B") %>% magrittr::extract2("colnames"),
With_meta %>% dplyr::filter(matnames == "B") %>% magrittr::extract2("Flow")) %>%
all() %>%
expect_true()
# If columns are already there, add_row_col_meta() shouldn't do anything.
With_meta <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B
) %>%
tibble::add_column(
rownames = "a very odd name",
colnames = "a WEIRD name",
rowtypes = "a damn weird row type",
coltypes = "a bloody strange col type"
)
With_meta_2 <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B
) %>%
tibble::add_column(
rownames = "a very odd name",
colnames = "a WEIRD name",
rowtypes = "a damn weird row type",
coltypes = "a bloody strange col type"
) %>%
add_row_col_meta() %>%
magrittr::equals(With_meta) %>%
all() %>%
expect_true()
# Now, expect error if only one of the 4 expected columns is present.
With_meta <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
dplyr::mutate(
"{IEATools::mat_meta_cols$rownames}" := "a very odd rowname"
) %>%
add_row_col_meta() %>%
expect_error(regexp = "'rownames' is")
# Verify that any added column triggers the error.
# This time do "colnames"
load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
dplyr::mutate(
"{IEATools::mat_meta_cols$colnames}" := "a bad colname"
) %>%
add_row_col_meta() %>%
testthat::expect_error(regexp = "'colnames' is ")
# rowtypes
load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
dplyr::mutate(
"{IEATools::mat_meta_cols$rowtypes}" := "a bad rowtype"
) %>%
add_row_col_meta() %>%
testthat::expect_error(regexp = "'rowtypes' is ")
# coltypes
load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
dplyr::mutate(
"{IEATools::mat_meta_cols$coltypes}" := "a bad coltype"
) %>%
add_row_col_meta() %>%
testthat::expect_error(regexp = "'coltypes' is ")
})
test_that("collapse_to_psut() works expected", {
With_mats <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B
) %>%
add_row_col_meta() %>%
collapse_to_tidy_psut()
expect_equal(nrow(With_mats), 21)
# Ensure that all values in the matrices (excluding B) are positive.
With_mats %>%
dplyr::filter(matnames != "B") %>%
dplyr::mutate(
gezero = matsbyname::compare_byname(matvals, ">=", 0) %>% matsbyname::all_byname()
) %>%
magrittr::extract2("gezero") %>%
as.logical() %>%
all() %>%
expect_true()
})
test_that("collapse_to_psut() works with Matrix objects", {
With_mats <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B
) %>%
add_row_col_meta() %>%
collapse_to_tidy_psut(matrix_class = "Matrix")
expect_equal(nrow(With_mats), 21)
# Ensure that all values in the matrices (excluding B) are positive.
With_mats %>%
dplyr::filter(matnames != "B") %>%
dplyr::mutate(
gezero = matsbyname::compare_byname(matvals, ">=", 0) %>% matsbyname::all_byname()
) %>%
magrittr::extract2("gezero") %>%
as.logical() %>%
all() %>%
expect_true()
for (i in 1:nrow(With_mats)) {
expect_true(matsbyname::is.Matrix(With_mats$matvals[[i]]))
}
})
test_that("prep_psut() works as expected", {
Simple <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut() %>%
tidyr::pivot_longer(cols = c("R", "U", "U_EIOU", "U_feed", "r_EIOU", "V", "Y", "S_units"),
names_to = "matnames", values_to = "matvals") %>%
dplyr::rename(matval_simple = matvals)
expect_equal(names(Simple),
c("Country", "Method", "Energy.type", "Last.stage", "Year", "matnames", "matval_simple"))
S_units <- load_tidy_iea_df() %>%
specify_all() %>%
extract_S_units_from_tidy()
Complicated <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
add_row_col_meta() %>%
collapse_to_tidy_psut() %>%
tidyr::spread(key = matnames, value = matvals) %>%
dplyr::mutate(
U = matsbyname::sum_byname(U_feed, U_EIOU),
r_EIOU = matsbyname::quotient_byname(U_EIOU, U) %>%
matsbyname::replaceNaN_byname(0)
) %>%
dplyr::full_join(S_units, by = c("Country", "Method", "Energy.type", "Last.stage", "Year")) %>%
tidyr::gather(key = matnames, value = matvals, R, U, U_EIOU, U_feed, r_EIOU, V, Y, S_units) %>%
dplyr::rename(matval_complicated = matvals)
# Simple and Complicated ought to be the same.
dplyr::full_join(Simple, Complicated, by = c("Country", "Method", "Energy.type", "Last.stage", "Year", "matnames")) %>%
dplyr::mutate(
same = matsbyname::equal_byname(matval_simple, matval_complicated)
) %>%
magrittr::extract2("same") %>%
as.logical() %>%
all() %>%
expect_true()
# Verify that S_units has the correct row and column types.
# On 21 July 2020, it did not!
S_units[[IEATools::psut_cols$s_units]][[1]] %>%
matsbyname::rowtype() %>%
expect_equal(IEATools::row_col_types$product)
S_units[[IEATools::psut_cols$s_units]][[1]] %>%
matsbyname::coltype() %>%
expect_equal(IEATools::row_col_types$unit)
})
test_that("prep_psut() works with Matrix objects", {
Simple <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
tidyr::pivot_longer(cols = c("R", "U", "U_EIOU", "U_feed", "r_EIOU", "V", "Y", "S_units"),
names_to = "matnames", values_to = "matvals") %>%
dplyr::rename(matval_simple = matvals)
for (i in 1:nrow(Simple)) {
expect_true(matsbyname::is.Matrix(Simple$matval_simple[[i]]))
}
expect_equal(names(Simple),
c("Country", "Method", "Energy.type", "Last.stage", "Year", "matnames", "matval_simple"))
S_units <- load_tidy_iea_df() %>%
specify_all() %>%
extract_S_units_from_tidy(matrix_class = "Matrix")
Complicated <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
add_row_col_meta() %>%
collapse_to_tidy_psut(matrix_class = "Matrix") %>%
tidyr::spread(key = matnames, value = matvals) %>%
dplyr::mutate(
U = matsbyname::sum_byname(U_feed, U_EIOU),
r_EIOU = matsbyname::quotient_byname(U_EIOU, U) %>%
matsbyname::replaceNaN_byname(0)
) %>%
dplyr::full_join(S_units, by = c("Country", "Method", "Energy.type", "Last.stage", "Year")) %>%
tidyr::gather(key = matnames, value = matvals, R, U, U_EIOU, U_feed, r_EIOU, V, Y, S_units) %>%
dplyr::rename(matval_complicated = matvals)
# Simple and Complicated ought to be the same.
dplyr::full_join(Simple, Complicated, by = c("Country", "Method", "Energy.type", "Last.stage", "Year", "matnames")) %>%
dplyr::mutate(
same = matsbyname::equal_byname(matval_simple, matval_complicated)
) %>%
magrittr::extract2("same") %>%
as.logical() %>%
all() %>%
expect_true()
# Verify that S_units has the correct row and column types.
# On 21 July 2020, it did not!
S_units[[IEATools::psut_cols$s_units]][[1]] %>%
matsbyname::rowtype() %>%
expect_equal(IEATools::row_col_types$product)
S_units[[IEATools::psut_cols$s_units]][[1]] %>%
matsbyname::coltype() %>%
expect_equal(IEATools::row_col_types$unit)
})
test_that("prep_psut() works as expected with empty .tidy_iea_df", {
iea_data <- load_tidy_iea_df() %>%
specify_all()
empty_iea_data <- iea_data[0, ]
zero_psut <- prep_psut(empty_iea_data)
cn <- colnames(zero_psut)
for (col_name in c(IEATools::iea_cols$country,
IEATools::iea_cols$method,
IEATools::iea_cols$energy_type,
IEATools::iea_cols$last_stage,
IEATools::iea_cols$year,
"R", "U", "U_EIOU", "U_feed", "V", "Y", "S_units")) {
expect_true(col_name %in% cn)
}
expect_equal(nrow(zero_psut), 0)
})
test_that("prep_psut() correctly makes columns of U and r_EIOU matrices", {
psut <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut()
psut_with_test_cols <- psut %>%
dplyr::mutate(
U_test = matsbyname::sum_byname(U_feed, U_EIOU),
r_EIOU_test = matsbyname::quotient_byname(U_EIOU, U),
r_EIOU_test = matsbyname::replaceNaN_byname(r_EIOU, val = 0)
)
expect_equal(psut_with_test_cols[["U_test"]], psut_with_test_cols[["U"]])
expect_equal(psut_with_test_cols[["r_EIOU_test"]], psut_with_test_cols[["r_EIOU"]])
})
test_that("prep_psut() correctly makes columns of U and r_EIOU matrices with Matrix objects", {
psut <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix")
psut_with_test_cols <- psut %>%
dplyr::mutate(
U_test = matsbyname::sum_byname(U_feed, U_EIOU),
r_EIOU_test = matsbyname::quotient_byname(U_EIOU, U),
r_EIOU_test = matsbyname::replaceNaN_byname(r_EIOU, val = 0)
)
# Verify that we made Matrix objects everywhere
for (j in 6:ncol(psut_with_test_cols)) {
for (i in 1:nrow(psut_with_test_cols)) {
expect_true(matsbyname::is.Matrix(psut_with_test_cols[[i, j]][[1]]))
}
}
expect_equal(psut_with_test_cols[["U_test"]], psut_with_test_cols[["U"]])
expect_equal(psut_with_test_cols[["r_EIOU_test"]], psut_with_test_cols[["r_EIOU"]])
})
test_that("replace_null_RUV() works correctly with missing R and U", {
# Set up so that the psut data frame has missing for
# R, U, U_feed, and U_EIOU in 1971 for GHA.
psut <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut() %>%
tidyr::pivot_longer(cols = c("R", "U", "U_EIOU", "U_feed", "r_EIOU", "V", "Y", "S_units"), names_to = "matnames", values_to = "matvals") %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "R")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U_feed")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U_EIOU")) %>%
tidyr::pivot_wider(names_from = "matnames", values_from = "matvals")
# Check that replace_null_RUV() works as expected.
res <- psut %>%
replace_null_RUV()
expected_R <- psut$Y[[1]] %>%
matsbyname::transpose_byname() %>%
matsbyname::colsums_byname() %>%
matsbyname::hadamardproduct_byname(0) %>%
matsbyname::setrownames_byname(IEATools::tpes_flows$resources)
expected_U <- psut$V[[1]] %>%
matsbyname::transpose_byname() %>%
matsbyname::hadamardproduct_byname(0)
# Verify that the NULL R matrix has been replaced with the correct 0 matrix.
expect_equal(res$R[[1]], expected_R)
# Verify that U_feed and U_EIOU are no longer NULL and is rather that transposed V matrix full of zeroes.
expect_equal(res$U[[1]], expected_U)
expect_equal(res$U_feed[[1]], expected_U)
expect_equal(res$U_EIOU[[1]], expected_U)
# We haven't removed the r_EIOU matrices. So those should be same as before
expect_equal(res$r_EIOU[[1]], psut$r_EIOU[[1]])
# Test that everything works correctly with a list.
mats_list <- list(U = NULL, r_EIOU = NULL, V = psut$V[[1]],
Y = psut$Y[[1]], S_units = psut$S_units[[1]],
R = NULL, U_EIOU = NULL, U_feed = NULL)
res_list <- replace_null_RUV(mats_list)
expect_equal(res_list$R, expected_R)
expect_equal(res_list$U, expected_U)
expect_equal(res_list$U_feed, expected_U)
expect_equal(res_list$U_EIOU, expected_U)
expect_equal(res_list$r_EIOU, expected_U)
# Test that everything works correctly with individual matrices passed in the ... argument
res_indiv <- replace_null_RUV(U = mats_list$U, r_eiou = mats_list$r_EIOU, V = mats_list$V,
Y = mats_list$Y,
R = mats_list$R, U_eiou = mats_list$U_EIOU, U_feed = mats_list$U_feed)
expect_equal(res_indiv$R, expected_R)
expect_equal(res_indiv$U_feed, expected_U)
expect_equal(res_indiv$U_EIOU, expected_U)
expect_equal(res_indiv$U, expected_U)
expect_equal(res_indiv$r_EIOU, expected_U)
})
test_that("replace_null_RUV() works correctly with missing R and U and Matrix objects", {
# Set up so that the psut data frame has missing for
# R, U, U_feed, and U_EIOU in 1971 for GHA.
psut <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
tidyr::pivot_longer(cols = c("R", "U", "U_EIOU", "U_feed", "r_EIOU", "V", "Y", "S_units"), names_to = "matnames", values_to = "matvals") %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "R")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U_feed")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U_EIOU")) %>%
tidyr::pivot_wider(names_from = "matnames", values_from = "matvals")
# Check that replace_null_RUV() works as expected.
res <- psut %>%
replace_null_RUV()
expected_R <- psut$Y[[1]] %>%
matsbyname::transpose_byname() %>%
matsbyname::colsums_byname() %>%
matsbyname::hadamardproduct_byname(0) %>%
matsbyname::setrownames_byname(IEATools::tpes_flows$resources)
expected_U <- psut$V[[1]] %>%
matsbyname::transpose_byname() %>%
matsbyname::hadamardproduct_byname(0)
# Verify that the NULL R matrix has been replaced with the correct 0 matrix.
expect_equal(res$R[[1]], expected_R)
# Verify that U_feed and U_EIOU are no longer NULL and is rather that transposed V matrix full of zeroes.
expect_equal(res$U[[1]], expected_U)
expect_equal(res$U_feed[[1]], expected_U)
expect_equal(res$U_EIOU[[1]], expected_U)
# We haven't removed the r_EIOU matrices. So those should be same as before
expect_equal(res$r_EIOU[[1]], psut$r_EIOU[[1]])
# Test that everything works correctly with a list.
mats_list <- list(U = NULL, r_EIOU = NULL, V = psut$V[[1]],
Y = psut$Y[[1]], S_units = psut$S_units[[1]],
R = NULL, U_EIOU = NULL, U_feed = NULL)
res_list <- replace_null_RUV(mats_list)
expect_equal(res_list$R, expected_R)
expect_equal(res_list$U, expected_U)
expect_equal(res_list$U_feed, expected_U)
expect_equal(res_list$U_EIOU, expected_U)
expect_equal(res_list$r_EIOU, expected_U)
# Test that everything works correctly with individual matrices passed in the ... argument
res_indiv <- replace_null_RUV(U = mats_list$U, r_eiou = mats_list$r_EIOU, V = mats_list$V,
Y = mats_list$Y,
R = mats_list$R, U_eiou = mats_list$U_EIOU, U_feed = mats_list$U_feed)
expect_equal(res_indiv$R, expected_R)
expect_equal(res_indiv$U_feed, expected_U)
expect_equal(res_indiv$U_EIOU, expected_U)
expect_equal(res_indiv$U, expected_U)
expect_equal(res_indiv$r_EIOU, expected_U)
})
test_that("replace_null_RUV() works correctly with missing U and V", {
# Set up so that the psut data frame has missing for
# U and V in 1971 for GHA.
psut <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut() %>%
tidyr::pivot_longer(cols = dplyr::any_of(c("R", "U_EIOU", "U_feed", "U", "r_EIOU", "V", "Y", "S_units")), names_to = "matnames", values_to = "matvals") %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "V")) %>%
tidyr::pivot_wider(names_from = "matnames", values_from = "matvals")
# Check that replace_null_RUV() works as expected.
res <- psut %>%
replace_null_RUV()
expected_V <- psut$R[[1]] %>%
matsbyname::hadamardproduct_byname(0)
expected_U <- expected_V %>%
matsbyname::transpose_byname()
# Verify that the missing V matrix has been replaced with the correct 0 matrix.
expect_equal(res$V[[1]], expected_V)
# Verify that the missing U matrix has been replaced with the correct 0 matrix.
expect_equal(res$U[[1]], expected_U)
})
test_that("replace_null_RUV() works correctly with missing U and V with Matrix objects", {
# Set up so that the psut data frame has missing for
# U and V in 1971 for GHA.
psut <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
tidyr::pivot_longer(cols = dplyr::any_of(c("R", "U_EIOU", "U_feed", "U", "r_EIOU", "V", "Y", "S_units")), names_to = "matnames", values_to = "matvals") %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "V")) %>%
tidyr::pivot_wider(names_from = "matnames", values_from = "matvals")
# Check that replace_null_RUV() works as expected.
res <- psut %>%
replace_null_RUV()
expected_V <- psut$R[[1]] %>%
matsbyname::hadamardproduct_byname(0)
expected_U <- expected_V %>%
matsbyname::transpose_byname()
# Verify that the missing V matrix has been replaced with the correct 0 matrix.
expect_equal(res$V[[1]], expected_V)
# Verify that the missing U matrix has been replaced with the correct 0 matrix.
expect_equal(res$U[[1]], expected_U)
})
test_that("prep_psut() correctly works with Balancing flows", {
PSUT_flows_with_Balancing <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = c(psut_cols$B, psut_cols$B)
) %>%
prep_psut()
expect_true(
all(c("R", "V", "U_feed", "U_EIOU", "Y", "S_units", "B") %in% colnames(PSUT_flows_with_Balancing))
)
a <- PSUT_flows_with_Balancing %>%
dplyr::select(B) %>%
dplyr::pull() %>%
dplyr::first()
balancing_expected_value <- matrix(nrow = 2, ncol = 2,
c(0, 100, -100, 0)) |>
matsbyname::setcolnames_byname(c("Non-ferrous metals", "Stock changes [of Crude oil]")) |>
matsbyname::setrownames_byname(c("Crude oil", "Electricity")) |>
matsbyname::setcoltype("Industry") |>
matsbyname::setrowtype("Product")
expect_true(matsbyname::equal_byname(a, balancing_expected_value))
# expect_true(
# all(balancing_expected_value == (PSUT_flows_with_Balancing %>%
# dplyr::select(B) %>%
# dplyr::pull() %>%
# dplyr::first())
# ))
})
test_that("prep_psut() correctly works with Balancing flows and Matrix objects", {
PSUT_flows_with_Balancing <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = c(psut_cols$B, psut_cols$B)
) %>%
prep_psut(matrix_class = "Matrix")
expect_true(
all(c("R", "V", "U_feed", "U_EIOU", "Y", "S_units", "B") %in% colnames(PSUT_flows_with_Balancing))
)
a <- PSUT_flows_with_Balancing %>%
dplyr::select(B) %>%
dplyr::pull() %>%
dplyr::first()
balancing_expected_value <- matrix(nrow = 2, ncol = 2,
c(0, 100, -100, 0)) |>
matsbyname::setcolnames_byname(c("Non-ferrous metals", "Stock changes [of Crude oil]")) |>
matsbyname::setrownames_byname(c("Crude oil", "Electricity")) |>
matsbyname::setcoltype("Industry") |>
matsbyname::setrowtype("Product")
expect_true(matsbyname::equal_byname(a, balancing_expected_value))
# expect_true(
# all(balancing_expected_value == (PSUT_flows_with_Balancing %>%
# dplyr::select(B) %>%
# dplyr::pull() %>%
# dplyr::first())
# ))
})
test_that("prep_psut() works when there is no energy industry own use", {
# Set up so that the psut data frame has NULL for
# R, U_feed, and U_EIOU in 1971 for GHA.
psut <- load_tidy_iea_df() %>%
specify_all() %>%
# Eliminate energy industry own use, so we do not get a U_EIOU matrix.
dplyr::filter(.data[[IEATools::iea_cols$flow_aggregation_point]] != IEATools::tfc_compare_flows$energy_industry_own_use) %>%
prep_psut()
# In this case, the U_EIOU matrix should be 0.
for (i in 1:nrow(psut)) {
expect_true(psut$U_EIOU[[i]] %>% matsbyname::iszero_byname())
}
})
test_that("prep_psut() works when there is no energy industry own use with Matrix objects", {
# Set up so that the psut data frame has NULL for
# R, U_feed, and U_EIOU in 1971 for GHA.
psut <- load_tidy_iea_df() %>%
specify_all() %>%
# Eliminate energy industry own use, so we do not get a U_EIOU matrix.
dplyr::filter(.data[[IEATools::iea_cols$flow_aggregation_point]] != IEATools::tfc_compare_flows$energy_industry_own_use) %>%
prep_psut(matrix_class = "Matrix")
# In this case, the U_EIOU matrix should be 0.
for (i in 1:nrow(psut)) {
expect_true(psut$U_EIOU[[i]] %>% matsbyname::iszero_byname())
}
})
MatthewHeun/IEATools documentation built on Feb. 6, 2024, 3:29 p.m.
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test_that("extract_S_units_from_tidy() works as expected", {
S_units <- load_tidy_iea_df() %>%
extract_S_units_from_tidy()
for (i in nrow(S_units)) {
su <- S_units$S_units[[i]]
expect_true(all(su[ , "TJ"] == 1))
}
})
test_that("extract_S_units_from_tidy() works with Matrix objects", {
S_units <- load_tidy_iea_df() %>%
extract_S_units_from_tidy(matrix_class = "Matrix")
for (i in nrow(S_units)) {
su <- S_units$S_units[[i]]
expect_true(matsbyname::is.Matrix(su))
expect_true(all(su[ , "TJ"] == 1))
}
})
test_that("add_psut_matnames() works as expected for R_includes_all_exogenous_flows = FALSE", {
With_matnames <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames(R_includes_all_exogenous_flows = FALSE)
# Ensure that none of the matnames are NA
expect_false(any(is.na(With_matnames$matnames)))
# Specific checks
# Resources
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Resources")) %>% magrittr::extract2("matnames") %>% magrittr::equals("R") %>% all())
# Imports
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Imports")) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
# Exports
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Exports")) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
# International marine bunkers
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International marine bunkers") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International marine bunkers") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
# International aviation bunkers
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International aviation bunkers") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International aviation bunkers") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
# Stock changes
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Stock changes") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Stock changes") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
# Transformation processes
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow.aggregation.point, "Transformation processes") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("U_feed") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow.aggregation.point, "Transformation processes") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
# EIOU
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow.aggregation.point, "Energy industry own use") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("U_EIOU") %>% all())
# Consumption
expect_true(With_matnames %>% dplyr::filter(startsWith(Ledger.side, "Consumption")) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
# Transfers
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Transfers") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("U_feed") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Transfers") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
With_matnames <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B
) %>%
add_psut_matnames()
expect_equal(With_matnames %>% dplyr::filter(matnames == "B") %>% nrow(), 2)
With_matnames_2 <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B)
expect_true(all(With_matnames == With_matnames_2))
})
test_that("add_psut_matnames() works as expected for R_includes_all_exogenous_flows = TRUE", {
With_matnames <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames()
# Ensure that none of the matnames are NA
expect_false(any(is.na(With_matnames$matnames)))
# Specific checks
# Resources
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Resources")) %>% magrittr::extract2("matnames") %>% magrittr::equals("R") %>% all())
# Imports
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Imports")) %>% magrittr::extract2("matnames") %>% magrittr::equals("R") %>% all())
# Exports
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Exports")) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
# International marine bunkers
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International marine bunkers") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International marine bunkers") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("R") %>% all())
# International aviation bunkers
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International aviation bunkers") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "International aviation bunkers") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("R") %>% all())
# Stock changes
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Stock changes") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Stock changes") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("R") %>% all())
# Transformation processes
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow.aggregation.point, "Transformation processes") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("U_feed") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow.aggregation.point, "Transformation processes") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
# EIOU
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow.aggregation.point, "Energy industry own use") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("U_EIOU") %>% all())
# Consumption
expect_true(With_matnames %>% dplyr::filter(startsWith(Ledger.side, "Consumption")) %>% magrittr::extract2("matnames") %>% magrittr::equals("Y") %>% all())
# Transfers
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Transfers") & E.dot < 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("U_feed") %>% all())
expect_true(With_matnames %>% dplyr::filter(startsWith(Flow, "Transfers") & E.dot > 0) %>% magrittr::extract2("matnames") %>% magrittr::equals("V") %>% all())
})
test_that("add_row_col_meta() works as expected", {
With_meta <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B
) %>%
add_row_col_meta()
# Ensure that every row is filled in the new columns.
expect_false(any(is.na(With_meta$rownames)))
expect_false(any(is.na(With_meta$colnames)))
expect_false(any(is.na(With_meta$rowtypes)))
expect_false(any(is.na(With_meta$coltypes)))
# Ensure that row and column types are correct
expect_true(With_meta %>% dplyr::filter(matnames == "R" | matnames == "V") %>% magrittr::extract2("rowtypes") %>% magrittr::equals("Industry") %>% all())
expect_true(With_meta %>% dplyr::filter(matnames == "R" | matnames == "V") %>% magrittr::extract2("coltypes") %>% magrittr::equals("Product") %>% all())
expect_true(With_meta %>% dplyr::filter(startsWith(matnames, "U") | matnames == "Y") %>% magrittr::extract2("rowtypes") %>% magrittr::equals("Product") %>% all())
expect_true(With_meta %>% dplyr::filter(startsWith(matnames, "U") | matnames == "Y") %>% magrittr::extract2("coltypes") %>% magrittr::equals("Industry") %>% all())
expect_true(With_meta %>% dplyr::filter(startsWith(matnames, "B")) %>% magrittr::extract2("rowtypes") %>% magrittr::equals("Product") %>% all())
expect_true(With_meta %>% dplyr::filter(startsWith(matnames, "B")) %>% magrittr::extract2("coltypes") %>% magrittr::equals("Industry") %>% all())
# Ensure that row and column identifiers are correct
# Rows of R and V are the Flow names
magrittr::equals(With_meta %>% dplyr::filter(matnames == "R" | matnames == "V") %>% magrittr::extract2("rownames"),
With_meta %>% dplyr::filter(matnames == "R" | matnames == "V") %>% magrittr::extract2("Flow")) %>%
all() %>%
expect_true()
# Columns of R and V are the Product names
magrittr::equals(With_meta %>% dplyr::filter(matnames == "R" | matnames == "V") %>% magrittr::extract2("colnames"),
With_meta %>% dplyr::filter(matnames == "R" | matnames == "V") %>% magrittr::extract2("Product")) %>%
all() %>%
expect_true()
# Rows of U and Y are the Product names
magrittr::equals(With_meta %>% dplyr::filter(matnames == "U" | matnames == "Y") %>% magrittr::extract2("rownames"),
With_meta %>% dplyr::filter(matnames == "U" | matnames == "Y") %>% magrittr::extract2("Product")) %>%
all() %>%
expect_true()
# Rows of B are the Product names
magrittr::equals(With_meta %>% dplyr::filter(matnames == "B") %>% magrittr::extract2("rownames"),
With_meta %>% dplyr::filter(matnames == "B") %>% magrittr::extract2("Product")) %>%
all() %>%
expect_true()
# Columns of U and Y are the Flow names
magrittr::equals(With_meta %>% dplyr::filter(matnames == "U" | matnames == "Y") %>% magrittr::extract2("colnames"),
With_meta %>% dplyr::filter(matnames == "U" | matnames == "Y") %>% magrittr::extract2("Flow")) %>%
all() %>%
expect_true()
magrittr::equals(With_meta %>% dplyr::filter(matnames == "B") %>% magrittr::extract2("colnames"),
With_meta %>% dplyr::filter(matnames == "B") %>% magrittr::extract2("Flow")) %>%
all() %>%
expect_true()
# If columns are already there, add_row_col_meta() shouldn't do anything.
With_meta <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B
) %>%
tibble::add_column(
rownames = "a very odd name",
colnames = "a WEIRD name",
rowtypes = "a damn weird row type",
coltypes = "a bloody strange col type"
)
With_meta_2 <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B
) %>%
tibble::add_column(
rownames = "a very odd name",
colnames = "a WEIRD name",
rowtypes = "a damn weird row type",
coltypes = "a bloody strange col type"
) %>%
add_row_col_meta() %>%
magrittr::equals(With_meta) %>%
all() %>%
expect_true()
# Now, expect error if only one of the 4 expected columns is present.
With_meta <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
dplyr::mutate(
"{IEATools::mat_meta_cols$rownames}" := "a very odd rowname"
) %>%
add_row_col_meta() %>%
expect_error(regexp = "'rownames' is")
# Verify that any added column triggers the error.
# This time do "colnames"
load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
dplyr::mutate(
"{IEATools::mat_meta_cols$colnames}" := "a bad colname"
) %>%
add_row_col_meta() %>%
testthat::expect_error(regexp = "'colnames' is ")
# rowtypes
load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
dplyr::mutate(
"{IEATools::mat_meta_cols$rowtypes}" := "a bad rowtype"
) %>%
add_row_col_meta() %>%
testthat::expect_error(regexp = "'rowtypes' is ")
# coltypes
load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
dplyr::mutate(
"{IEATools::mat_meta_cols$coltypes}" := "a bad coltype"
) %>%
add_row_col_meta() %>%
testthat::expect_error(regexp = "'coltypes' is ")
})
test_that("collapse_to_psut() works expected", {
With_mats <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B
) %>%
add_row_col_meta() %>%
collapse_to_tidy_psut()
expect_equal(nrow(With_mats), 21)
# Ensure that all values in the matrices (excluding B) are positive.
With_mats %>%
dplyr::filter(matnames != "B") %>%
dplyr::mutate(
gezero = matsbyname::compare_byname(matvals, ">=", 0) %>% matsbyname::all_byname()
) %>%
magrittr::extract2("gezero") %>%
as.logical() %>%
all() %>%
expect_true()
})
test_that("collapse_to_psut() works with Matrix objects", {
With_mats <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = psut_cols$B
) %>%
add_row_col_meta() %>%
collapse_to_tidy_psut(matrix_class = "Matrix")
expect_equal(nrow(With_mats), 21)
# Ensure that all values in the matrices (excluding B) are positive.
With_mats %>%
dplyr::filter(matnames != "B") %>%
dplyr::mutate(
gezero = matsbyname::compare_byname(matvals, ">=", 0) %>% matsbyname::all_byname()
) %>%
magrittr::extract2("gezero") %>%
as.logical() %>%
all() %>%
expect_true()
for (i in 1:nrow(With_mats)) {
expect_true(matsbyname::is.Matrix(With_mats$matvals[[i]]))
}
})
test_that("prep_psut() works as expected", {
Simple <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut() %>%
tidyr::pivot_longer(cols = c("R", "U", "U_EIOU", "U_feed", "r_EIOU", "V", "Y", "S_units"),
names_to = "matnames", values_to = "matvals") %>%
dplyr::rename(matval_simple = matvals)
expect_equal(names(Simple),
c("Country", "Method", "Energy.type", "Last.stage", "Year", "matnames", "matval_simple"))
S_units <- load_tidy_iea_df() %>%
specify_all() %>%
extract_S_units_from_tidy()
Complicated <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
add_row_col_meta() %>%
collapse_to_tidy_psut() %>%
tidyr::spread(key = matnames, value = matvals) %>%
dplyr::mutate(
U = matsbyname::sum_byname(U_feed, U_EIOU),
r_EIOU = matsbyname::quotient_byname(U_EIOU, U) %>%
matsbyname::replaceNaN_byname(0)
) %>%
dplyr::full_join(S_units, by = c("Country", "Method", "Energy.type", "Last.stage", "Year")) %>%
tidyr::gather(key = matnames, value = matvals, R, U, U_EIOU, U_feed, r_EIOU, V, Y, S_units) %>%
dplyr::rename(matval_complicated = matvals)
# Simple and Complicated ought to be the same.
dplyr::full_join(Simple, Complicated, by = c("Country", "Method", "Energy.type", "Last.stage", "Year", "matnames")) %>%
dplyr::mutate(
same = matsbyname::equal_byname(matval_simple, matval_complicated)
) %>%
magrittr::extract2("same") %>%
as.logical() %>%
all() %>%
expect_true()
# Verify that S_units has the correct row and column types.
# On 21 July 2020, it did not!
S_units[[IEATools::psut_cols$s_units]][[1]] %>%
matsbyname::rowtype() %>%
expect_equal(IEATools::row_col_types$product)
S_units[[IEATools::psut_cols$s_units]][[1]] %>%
matsbyname::coltype() %>%
expect_equal(IEATools::row_col_types$unit)
})
test_that("prep_psut() works with Matrix objects", {
Simple <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
tidyr::pivot_longer(cols = c("R", "U", "U_EIOU", "U_feed", "r_EIOU", "V", "Y", "S_units"),
names_to = "matnames", values_to = "matvals") %>%
dplyr::rename(matval_simple = matvals)
for (i in 1:nrow(Simple)) {
expect_true(matsbyname::is.Matrix(Simple$matval_simple[[i]]))
}
expect_equal(names(Simple),
c("Country", "Method", "Energy.type", "Last.stage", "Year", "matnames", "matval_simple"))
S_units <- load_tidy_iea_df() %>%
specify_all() %>%
extract_S_units_from_tidy(matrix_class = "Matrix")
Complicated <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
add_row_col_meta() %>%
collapse_to_tidy_psut(matrix_class = "Matrix") %>%
tidyr::spread(key = matnames, value = matvals) %>%
dplyr::mutate(
U = matsbyname::sum_byname(U_feed, U_EIOU),
r_EIOU = matsbyname::quotient_byname(U_EIOU, U) %>%
matsbyname::replaceNaN_byname(0)
) %>%
dplyr::full_join(S_units, by = c("Country", "Method", "Energy.type", "Last.stage", "Year")) %>%
tidyr::gather(key = matnames, value = matvals, R, U, U_EIOU, U_feed, r_EIOU, V, Y, S_units) %>%
dplyr::rename(matval_complicated = matvals)
# Simple and Complicated ought to be the same.
dplyr::full_join(Simple, Complicated, by = c("Country", "Method", "Energy.type", "Last.stage", "Year", "matnames")) %>%
dplyr::mutate(
same = matsbyname::equal_byname(matval_simple, matval_complicated)
) %>%
magrittr::extract2("same") %>%
as.logical() %>%
all() %>%
expect_true()
# Verify that S_units has the correct row and column types.
# On 21 July 2020, it did not!
S_units[[IEATools::psut_cols$s_units]][[1]] %>%
matsbyname::rowtype() %>%
expect_equal(IEATools::row_col_types$product)
S_units[[IEATools::psut_cols$s_units]][[1]] %>%
matsbyname::coltype() %>%
expect_equal(IEATools::row_col_types$unit)
})
test_that("prep_psut() works as expected with empty .tidy_iea_df", {
iea_data <- load_tidy_iea_df() %>%
specify_all()
empty_iea_data <- iea_data[0, ]
zero_psut <- prep_psut(empty_iea_data)
cn <- colnames(zero_psut)
for (col_name in c(IEATools::iea_cols$country,
IEATools::iea_cols$method,
IEATools::iea_cols$energy_type,
IEATools::iea_cols$last_stage,
IEATools::iea_cols$year,
"R", "U", "U_EIOU", "U_feed", "V", "Y", "S_units")) {
expect_true(col_name %in% cn)
}
expect_equal(nrow(zero_psut), 0)
})
test_that("prep_psut() correctly makes columns of U and r_EIOU matrices", {
psut <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut()
psut_with_test_cols <- psut %>%
dplyr::mutate(
U_test = matsbyname::sum_byname(U_feed, U_EIOU),
r_EIOU_test = matsbyname::quotient_byname(U_EIOU, U),
r_EIOU_test = matsbyname::replaceNaN_byname(r_EIOU, val = 0)
)
expect_equal(psut_with_test_cols[["U_test"]], psut_with_test_cols[["U"]])
expect_equal(psut_with_test_cols[["r_EIOU_test"]], psut_with_test_cols[["r_EIOU"]])
})
test_that("prep_psut() correctly makes columns of U and r_EIOU matrices with Matrix objects", {
psut <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix")
psut_with_test_cols <- psut %>%
dplyr::mutate(
U_test = matsbyname::sum_byname(U_feed, U_EIOU),
r_EIOU_test = matsbyname::quotient_byname(U_EIOU, U),
r_EIOU_test = matsbyname::replaceNaN_byname(r_EIOU, val = 0)
)
# Verify that we made Matrix objects everywhere
for (j in 6:ncol(psut_with_test_cols)) {
for (i in 1:nrow(psut_with_test_cols)) {
expect_true(matsbyname::is.Matrix(psut_with_test_cols[[i, j]][[1]]))
}
}
expect_equal(psut_with_test_cols[["U_test"]], psut_with_test_cols[["U"]])
expect_equal(psut_with_test_cols[["r_EIOU_test"]], psut_with_test_cols[["r_EIOU"]])
})
test_that("replace_null_RUV() works correctly with missing R and U", {
# Set up so that the psut data frame has missing for
# R, U, U_feed, and U_EIOU in 1971 for GHA.
psut <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut() %>%
tidyr::pivot_longer(cols = c("R", "U", "U_EIOU", "U_feed", "r_EIOU", "V", "Y", "S_units"), names_to = "matnames", values_to = "matvals") %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "R")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U_feed")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U_EIOU")) %>%
tidyr::pivot_wider(names_from = "matnames", values_from = "matvals")
# Check that replace_null_RUV() works as expected.
res <- psut %>%
replace_null_RUV()
expected_R <- psut$Y[[1]] %>%
matsbyname::transpose_byname() %>%
matsbyname::colsums_byname() %>%
matsbyname::hadamardproduct_byname(0) %>%
matsbyname::setrownames_byname(IEATools::tpes_flows$resources)
expected_U <- psut$V[[1]] %>%
matsbyname::transpose_byname() %>%
matsbyname::hadamardproduct_byname(0)
# Verify that the NULL R matrix has been replaced with the correct 0 matrix.
expect_equal(res$R[[1]], expected_R)
# Verify that U_feed and U_EIOU are no longer NULL and is rather that transposed V matrix full of zeroes.
expect_equal(res$U[[1]], expected_U)
expect_equal(res$U_feed[[1]], expected_U)
expect_equal(res$U_EIOU[[1]], expected_U)
# We haven't removed the r_EIOU matrices. So those should be same as before
expect_equal(res$r_EIOU[[1]], psut$r_EIOU[[1]])
# Test that everything works correctly with a list.
mats_list <- list(U = NULL, r_EIOU = NULL, V = psut$V[[1]],
Y = psut$Y[[1]], S_units = psut$S_units[[1]],
R = NULL, U_EIOU = NULL, U_feed = NULL)
res_list <- replace_null_RUV(mats_list)
expect_equal(res_list$R, expected_R)
expect_equal(res_list$U, expected_U)
expect_equal(res_list$U_feed, expected_U)
expect_equal(res_list$U_EIOU, expected_U)
expect_equal(res_list$r_EIOU, expected_U)
# Test that everything works correctly with individual matrices passed in the ... argument
res_indiv <- replace_null_RUV(U = mats_list$U, r_eiou = mats_list$r_EIOU, V = mats_list$V,
Y = mats_list$Y,
R = mats_list$R, U_eiou = mats_list$U_EIOU, U_feed = mats_list$U_feed)
expect_equal(res_indiv$R, expected_R)
expect_equal(res_indiv$U_feed, expected_U)
expect_equal(res_indiv$U_EIOU, expected_U)
expect_equal(res_indiv$U, expected_U)
expect_equal(res_indiv$r_EIOU, expected_U)
})
test_that("replace_null_RUV() works correctly with missing R and U and Matrix objects", {
# Set up so that the psut data frame has missing for
# R, U, U_feed, and U_EIOU in 1971 for GHA.
psut <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
tidyr::pivot_longer(cols = c("R", "U", "U_EIOU", "U_feed", "r_EIOU", "V", "Y", "S_units"), names_to = "matnames", values_to = "matvals") %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "R")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U_feed")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U_EIOU")) %>%
tidyr::pivot_wider(names_from = "matnames", values_from = "matvals")
# Check that replace_null_RUV() works as expected.
res <- psut %>%
replace_null_RUV()
expected_R <- psut$Y[[1]] %>%
matsbyname::transpose_byname() %>%
matsbyname::colsums_byname() %>%
matsbyname::hadamardproduct_byname(0) %>%
matsbyname::setrownames_byname(IEATools::tpes_flows$resources)
expected_U <- psut$V[[1]] %>%
matsbyname::transpose_byname() %>%
matsbyname::hadamardproduct_byname(0)
# Verify that the NULL R matrix has been replaced with the correct 0 matrix.
expect_equal(res$R[[1]], expected_R)
# Verify that U_feed and U_EIOU are no longer NULL and is rather that transposed V matrix full of zeroes.
expect_equal(res$U[[1]], expected_U)
expect_equal(res$U_feed[[1]], expected_U)
expect_equal(res$U_EIOU[[1]], expected_U)
# We haven't removed the r_EIOU matrices. So those should be same as before
expect_equal(res$r_EIOU[[1]], psut$r_EIOU[[1]])
# Test that everything works correctly with a list.
mats_list <- list(U = NULL, r_EIOU = NULL, V = psut$V[[1]],
Y = psut$Y[[1]], S_units = psut$S_units[[1]],
R = NULL, U_EIOU = NULL, U_feed = NULL)
res_list <- replace_null_RUV(mats_list)
expect_equal(res_list$R, expected_R)
expect_equal(res_list$U, expected_U)
expect_equal(res_list$U_feed, expected_U)
expect_equal(res_list$U_EIOU, expected_U)
expect_equal(res_list$r_EIOU, expected_U)
# Test that everything works correctly with individual matrices passed in the ... argument
res_indiv <- replace_null_RUV(U = mats_list$U, r_eiou = mats_list$r_EIOU, V = mats_list$V,
Y = mats_list$Y,
R = mats_list$R, U_eiou = mats_list$U_EIOU, U_feed = mats_list$U_feed)
expect_equal(res_indiv$R, expected_R)
expect_equal(res_indiv$U_feed, expected_U)
expect_equal(res_indiv$U_EIOU, expected_U)
expect_equal(res_indiv$U, expected_U)
expect_equal(res_indiv$r_EIOU, expected_U)
})
test_that("replace_null_RUV() works correctly with missing U and V", {
# Set up so that the psut data frame has missing for
# U and V in 1971 for GHA.
psut <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut() %>%
tidyr::pivot_longer(cols = dplyr::any_of(c("R", "U_EIOU", "U_feed", "U", "r_EIOU", "V", "Y", "S_units")), names_to = "matnames", values_to = "matvals") %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "V")) %>%
tidyr::pivot_wider(names_from = "matnames", values_from = "matvals")
# Check that replace_null_RUV() works as expected.
res <- psut %>%
replace_null_RUV()
expected_V <- psut$R[[1]] %>%
matsbyname::hadamardproduct_byname(0)
expected_U <- expected_V %>%
matsbyname::transpose_byname()
# Verify that the missing V matrix has been replaced with the correct 0 matrix.
expect_equal(res$V[[1]], expected_V)
# Verify that the missing U matrix has been replaced with the correct 0 matrix.
expect_equal(res$U[[1]], expected_U)
})
test_that("replace_null_RUV() works correctly with missing U and V with Matrix objects", {
# Set up so that the psut data frame has missing for
# U and V in 1971 for GHA.
psut <- load_tidy_iea_df() %>%
specify_all() %>%
prep_psut(matrix_class = "Matrix") %>%
tidyr::pivot_longer(cols = dplyr::any_of(c("R", "U_EIOU", "U_feed", "U", "r_EIOU", "V", "Y", "S_units")), names_to = "matnames", values_to = "matvals") %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "U")) %>%
dplyr::filter(!(Country == "GHA" & Year == 1971 & matnames == "V")) %>%
tidyr::pivot_wider(names_from = "matnames", values_from = "matvals")
# Check that replace_null_RUV() works as expected.
res <- psut %>%
replace_null_RUV()
expected_V <- psut$R[[1]] %>%
matsbyname::hadamardproduct_byname(0)
expected_U <- expected_V %>%
matsbyname::transpose_byname()
# Verify that the missing V matrix has been replaced with the correct 0 matrix.
expect_equal(res$V[[1]], expected_V)
# Verify that the missing U matrix has been replaced with the correct 0 matrix.
expect_equal(res$U[[1]], expected_U)
})
test_that("prep_psut() correctly works with Balancing flows", {
PSUT_flows_with_Balancing <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = c(psut_cols$B, psut_cols$B)
) %>%
prep_psut()
expect_true(
all(c("R", "V", "U_feed", "U_EIOU", "Y", "S_units", "B") %in% colnames(PSUT_flows_with_Balancing))
)
a <- PSUT_flows_with_Balancing %>%
dplyr::select(B) %>%
dplyr::pull() %>%
dplyr::first()
balancing_expected_value <- matrix(nrow = 2, ncol = 2,
c(0, 100, -100, 0)) |>
matsbyname::setcolnames_byname(c("Non-ferrous metals", "Stock changes [of Crude oil]")) |>
matsbyname::setrownames_byname(c("Crude oil", "Electricity")) |>
matsbyname::setcoltype("Industry") |>
matsbyname::setrowtype("Product")
expect_true(matsbyname::equal_byname(a, balancing_expected_value))
# expect_true(
# all(balancing_expected_value == (PSUT_flows_with_Balancing %>%
# dplyr::select(B) %>%
# dplyr::pull() %>%
# dplyr::first())
# ))
})
test_that("prep_psut() correctly works with Balancing flows and Matrix objects", {
PSUT_flows_with_Balancing <- load_tidy_iea_df() %>%
specify_all() %>%
add_psut_matnames() %>%
tibble::add_row(
Country = c("GHA", "GHA"),
Method = c("PCM", "PCM"),
Energy.type = c("E", "E"),
Last.stage = c("Final", "Final"),
Year = c(1971, 1971),
Ledger.side = c("Consumption", "Supply"),
Flow.aggregation.point = c("Industry", "Total primary energy supply"),
Flow = c("Non-ferrous metals", "Stock changes [of Crude oil]"),
Product = c("Electricity", "Crude oil"),
Unit = c("ktoe", "ktoe"),
E.dot = c(100, -100),
matnames = c(psut_cols$B, psut_cols$B)
) %>%
prep_psut(matrix_class = "Matrix")
expect_true(
all(c("R", "V", "U_feed", "U_EIOU", "Y", "S_units", "B") %in% colnames(PSUT_flows_with_Balancing))
)
a <- PSUT_flows_with_Balancing %>%
dplyr::select(B) %>%
dplyr::pull() %>%
dplyr::first()
balancing_expected_value <- matrix(nrow = 2, ncol = 2,
c(0, 100, -100, 0)) |>
matsbyname::setcolnames_byname(c("Non-ferrous metals", "Stock changes [of Crude oil]")) |>
matsbyname::setrownames_byname(c("Crude oil", "Electricity")) |>
matsbyname::setcoltype("Industry") |>
matsbyname::setrowtype("Product")
expect_true(matsbyname::equal_byname(a, balancing_expected_value))
# expect_true(
# all(balancing_expected_value == (PSUT_flows_with_Balancing %>%
# dplyr::select(B) %>%
# dplyr::pull() %>%
# dplyr::first())
# ))
})
test_that("prep_psut() works when there is no energy industry own use", {
# Set up so that the psut data frame has NULL for
# R, U_feed, and U_EIOU in 1971 for GHA.
psut <- load_tidy_iea_df() %>%
specify_all() %>%
# Eliminate energy industry own use, so we do not get a U_EIOU matrix.
dplyr::filter(.data[[IEATools::iea_cols$flow_aggregation_point]] != IEATools::tfc_compare_flows$energy_industry_own_use) %>%
prep_psut()
# In this case, the U_EIOU matrix should be 0.
for (i in 1:nrow(psut)) {
expect_true(psut$U_EIOU[[i]] %>% matsbyname::iszero_byname())
}
})
test_that("prep_psut() works when there is no energy industry own use with Matrix objects", {
# Set up so that the psut data frame has NULL for
# R, U_feed, and U_EIOU in 1971 for GHA.
psut <- load_tidy_iea_df() %>%
specify_all() %>%
# Eliminate energy industry own use, so we do not get a U_EIOU matrix.
dplyr::filter(.data[[IEATools::iea_cols$flow_aggregation_point]] != IEATools::tfc_compare_flows$energy_industry_own_use) %>%
prep_psut(matrix_class = "Matrix")
# In this case, the U_EIOU matrix should be 0.
for (i in 1:nrow(psut)) {
expect_true(psut$U_EIOU[[i]] %>% matsbyname::iszero_byname())
}
})
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