tests/testthat/test-energy_to_exergy.R

In MatthewHeun/Recca: R Energy Conversion Chain Analysis

test_that("extend_to_exergy() works as expected", {
  # Create a vector of phi values.
  # Each final and useful energy carrier needs a phi value.
  # Use the UKEnergy2000mats data frame for the tests.
  # Get the list of final energy carriers from the matrices in UKEnergy2000mats.

  sutmats <- UKEnergy2000mats %>%
    # Put in wide-by-matrix format.
    tidyr::spread(key = matrix.name, value = matrix) %>%
    # Eliminate services ECCs.
    dplyr::filter(Last.stage %in% c("Final", "Useful")) %>%
    dplyr::mutate(
      phi = RCLabels::make_list(Recca::phi_vec, n = nrow(.), lenx = 1)
    )
  res <- extend_to_exergy(sutmats)
  expect_true(Recca::energy_types$x %in% res[[Recca::energy_types$energy_type]] %>% unique())

  # Check a couple values

  # R matrix
  energy_val <- res[[Recca::psut_cols$R]][[1]]["Resources [of Crude]", "Crude"]
  exergy_val <- res[[Recca::psut_cols$R]][[3]]["Resources [of Crude]", "Crude"]
  phi <- Recca::phi_vec["Crude", ]
  expect_equal(energy_val*phi, exergy_val)

  energy_val <- res[[Recca::psut_cols$R]][[1]]["Resources [of NG]", "NG"]
  exergy_val <- res[[Recca::psut_cols$R]][[3]]["Resources [of NG]", "NG"]
  phi <- Recca::phi_vec["NG", ]

  expect_true((res[[Recca::psut_cols$R]] %>% matsbyname::rowtype() == "Industry") %>% all())
  expect_true((res[[Recca::psut_cols$R]] %>% matsbyname::coltype() == "Product") %>% all())

  # U matrix
  energy_val <- res[[Recca::psut_cols$U]][[1]]["Diesel [from Dist.]", "NG dist."]
  exergy_val <- res[[Recca::psut_cols$U]][[3]]["Diesel [from Dist.]", "NG dist."]
  phi <- Recca::phi_vec["Diesel [from Dist.]", ]
  expect_equal(energy_val*phi, exergy_val)

  energy_val <- res[[Recca::psut_cols$U_feed]][[2]]["Elect [from Grid]", "Light fixtures"]
  exergy_val <- res[[Recca::psut_cols$U_feed]][[4]]["Elect [from Grid]", "Light fixtures"]
  phi <- Recca::phi_vec["Elect [from Grid]", ]
  expect_equal(energy_val*phi, exergy_val)

  energy_val <- res[[Recca::psut_cols$U_eiou]][[2]]["Diesel [from Dist.]", "Gas wells & proc."]
  exergy_val <- res[[Recca::psut_cols$U_eiou]][[4]]["Diesel [from Dist.]", "Gas wells & proc."]
  phi <- Recca::phi_vec["Diesel [from Dist.]", ]
  expect_equal(energy_val*phi, exergy_val)

  expect_true((res[[Recca::psut_cols$U]] %>% matsbyname::rowtype() == "Product") %>% all())
  expect_true((res[[Recca::psut_cols$U]] %>% matsbyname::coltype() == "Industry") %>% all())

  # V matrix
  energy_val <- res[[Recca::psut_cols$V]][[1]]["Power plants", "Elect"]
  exergy_val <- res[[Recca::psut_cols$V]][[3]]["Power plants", "Elect"]
  phi <- Recca::phi_vec["Elect", ]
  expect_equal(energy_val*phi, exergy_val)

  energy_val <- res[[Recca::psut_cols$V]][[2]]["Furnaces", "LTH"]
  exergy_val <- res[[Recca::psut_cols$V]][[4]]["Furnaces", "LTH"]
  phi <- Recca::phi_vec["LTH", ]
  expect_equal(energy_val*phi, exergy_val)

  expect_true((res[[Recca::psut_cols$V]] %>% matsbyname::rowtype() == "Industry") %>% all())
  expect_true((res[[Recca::psut_cols$V]] %>% matsbyname::coltype() == "Product") %>% all())

  # Y matrix
  energy_val <- res[[Recca::psut_cols$Y]][[2]]["Light", "Residential"]
  exergy_val <- res[[Recca::psut_cols$Y]][[4]]["Light", "Residential"]
  phi <- Recca::phi_vec["Light", ]
  expect_equal(energy_val*phi, exergy_val)

  energy_val <- res[[Recca::psut_cols$Y]][[2]]["LTH", "Transport"]
  exergy_val <- res[[Recca::psut_cols$Y]][[4]]["LTH", "Transport"]
  phi <- Recca::phi_vec["LTH", ]
  expect_equal(energy_val*phi, exergy_val)

  expect_true((res[[Recca::psut_cols$Y]] %>% matsbyname::rowtype() == "Product") %>% all())
  expect_true((res[[Recca::psut_cols$Y]] %>% matsbyname::coltype() == "Industry") %>% all())

  # Try an erroneous case, when the Energy.type column has something other than E
  sutmats %>%
    dplyr::mutate(
      "{Recca::energy_types$energy_type}" := c("W", "X")
    ) %>%
    extend_to_exergy() %>%
    expect_error("non-energy rows were found:")
})


test_that("extend_to_exergy() works correctly with specified products", {
  # Make an example R matrix
  R <- matrix(c(250.129, 0,
                0, 2087.513), byrow = TRUE, nrow = 2, ncol = 2,
              dimnames = list(c("Resources [of Hydro]",
                                "Resources [of Primary solid biofuels]"),
                              c("Hydro [from Resources]", "Primary solid biofuels [from Resources]"))) %>%
    matsbyname::setrowtype("Industry") %>% matsbyname::setcoltype("Product")

  # Create an example U matrices
  U <- matrix(c(250.129, 0,
                0, 2087.519), byrow = TRUE, nrow = 2, ncol = 2,
              dimnames = list(c("Hydro [from Resources]",
                                "Primary solid biofuels [from Resources]"),
                              c("Manufacture [of Hydro]", "Manufacture [of Primary solid biofuels]"))) %>%
    matsbyname::setrowtype("Product") %>% matsbyname::setcoltype("Industry")

  U_feed <- U
  U_eiou <- matsbyname::hadamardproduct_byname(U_feed, 0.1)
  r_eiou <- matsbyname::quotient_byname(U_eiou, U) %>%
    matsbyname::replaceNaN_byname()

  # Create an example V matrix
  V <- matrix(c(250.129, 0,
                0, 2087.513), byrow = TRUE, nrow = 2, ncol = 2,
              dimnames = list(c("Manufacture [of Hydro]",
                                "Manufacture [of Primary solid biofuels]"),
                              c("Hydro", "Primary solid biofuels"))) %>%
    matsbyname::setrowtype("Industry") %>% matsbyname::setcoltype("Product")

  # Create an example Y matrix
  Y <- matrix(c(250.129, 0,
                0, 2087.513), byrow = TRUE, nrow = 2, ncol = 2,
              dimnames = list(c("Hydro", "Primary solid biofuels"),
                              c("Exports [of Hydro]", "Exports [of Primary solid biofuels]"))) %>%
    matsbyname::setrowtype("Product") %>% matsbyname::setcoltype("Industry")

  # Create an example phi vector
  phi <- matrix(c(42,
                  1,
                  1.11,
                  43), ncol = 1,
                dimnames = list(c("Bogus1",
                                  "Hydro",
                                  "Primary solid biofuels",
                                  "Bogus2"),
                                "phi")) %>%
    matsbyname::setrowtype("Product") %>% matsbyname::setcoltype("phi")

  # Call extend_to_exergy() with the example matrices.
  # Expect no warning.
  res <- extend_to_exergy(R = R, U = U, U_feed = U_feed, U_eiou = U_eiou,
                          V = V, Y = Y, phi = phi,
                          mat_piece = "noun")

  phi_mat <- matrix(c(1, 0,
                      0, 1.11), byrow = TRUE, nrow = 2, ncol = 2)

  expected_R_X <- R %*% phi_mat
  for (i in 1:2) {
    for (j in 1:2) {
      expect_equal(res$R_exergy[[i, j]], expected_R_X[[i, j]])
    }
  }

  expected_U_X <- phi_mat %*% U
  for (i in 1:2) {
    for (j in 1:2) {
      expect_equal(res$U_exergy[[i, j]], expected_U_X[[i, j]])
    }
  }

  expected_U_feed_X <- phi_mat %*% U_feed
  for (i in 1:2) {
    for (j in 1:2) {
      expect_equal(res$U_feed_exergy[[i, j]], expected_U_feed_X[[i, j]])
    }
  }

  expected_U_EIOU_X <- phi_mat %*% U_eiou
  for (i in 1:2) {
    for (j in 1:2) {
      expect_equal(res$U_EIOU_exergy[[i, j]], expected_U_EIOU_X[[i, j]])
    }
  }

  expected_V_X <- V %*% phi_mat
  for (i in 1:2) {
    for (j in 1:2) {
      expect_equal(res$V_exergy[[i, j]], expected_V_X[[i, j]])
    }
  }

  expected_Y_X <- phi_mat %*% Y
  for (i in 1:2) {
    for (j in 1:2) {
      expect_equal(res$Y_exergy[[i, j]], expected_Y_X[[i, j]])
    }
  }

})


test_that("extend_fu_details_to_exergy() works as expected", {
  details_mat <- Matrix::sparseMatrix(i = c(1, 2, 3),
                                      j = c(1, 3, 2),
                                      x = c(10, 20, 100),
                                      dimnames = list(c("Electricity -> Households",
                                                        "Electricity -> Industry",
                                                        "Natural gas -> Households"),
                                                      c("Light [from Electric lamps]",
                                                        "MTH.100.C [from Furnaces]",
                                                        "KE [from Fans]"))) |>
    matsbyname::setrowtype("Product -> Industry") |>
    matsbyname::setcoltype("Product [from Industry]")
  phi_vec <- Matrix::sparseMatrix(i = c(1, 2, 3, 4),
                                  j = c(1, 1, 1, 1),
                                  x = c(1.0, 1-(25+273.15)/(100+273.15), 0.96, 1-(25+273.15)/(1000+273.15)),
                                  dimnames = list(c("KE", "MTH.100.C", "Light", "HTH.1000.C"),
                                                  "phi")) |>
    matsbyname::setrowtype("Product") |>
    matsbyname::setcoltype("phi")
  expected <- details_mat
  expected[1,1] <- 10*0.96 # Light
  expected[2,3] <- 20 # No change for KE
  expected[3,2] <- 100 * (1-(25+273.15)/(100+273.15))
  expected <- expected |>
    matsbyname::setrowtype("Product -> Industry") |>
    matsbyname::setcoltype("Product [from Industry]")
  res <- extend_fu_details_to_exergy(Y_fu_details = details_mat,
                                     U_eiou_fu_details = details_mat,
                                     phi = phi_vec)
  expect_true(matsbyname::equal_byname(res$Y_fu_details_exergy, expected))
  expect_true(matsbyname::equal_byname(res$U_EIOU_fu_details_exergy, expected))

  # Make a data frame and do calculations within.
  df <- tibble::tibble(Country = "USA",
                       Energy.type = "E",
                       Y_fu_details = list(details_mat, details_mat),
                       U_EIOU_fu_details = list(details_mat, details_mat),
                       phi = list(phi_vec, phi_vec))
  res_df <- df |>
    extend_fu_details_to_exergy()
  # Test that the results are as expected.
  res_df |>
    dplyr::filter(Energy.type == "X") |>
    magrittr::extract2("Y_fu_details") |>
    matsbyname::equal_byname(list(expected, expected)) |>
    unlist() |>
    all() |>
    expect_true()
  res_df |>
    dplyr::filter(Energy.type == "X") |>
    magrittr::extract2("U_EIOU_fu_details") |>
    matsbyname::equal_byname(list(expected, expected)) |>
    unlist() |>
    all() |>
    expect_true()
})


test_that("extend_fu_details_to_exergy() works with NULL matrices", {
  extend_fu_details_to_exergy(Y_fu_details = NULL,
                              U_eiou_fu_details = NULL,
                              phi = NULL) |>
    expect_equal(list(Y_fu_details_mat = list(),
                      U_eiou_fu_details_mat = list(),
                      phi_vec = list()))
})


test_that("extend_fu_details_to_exergy() works with a data frame without the details matrices", {
  no_details_df <- tibble::tribble(~R, ~U, ~V, ~Y,
                                   1,  2,  3,  4)
  # A data frame without the details matrices should return NULL.
  expect_null(extend_fu_details_to_exergy(no_details_df))
})


test_that("extend_fu_details_to_exergy() fails when not all Energy.type is 'E'", {
  details_df <- tibble::tribble(~Energy.type, ~R, ~U, ~V, ~Y, ~Y_fu_details, ~U_EIOU_fu_details,
                                "X",          1,  2,  3,  4,    5,             6)
  # A data frame without the details matrices should return NULL.
  extend_fu_details_to_exergy(details_df) |>
    expect_error(regexp = "non-energy rows were found")
})


test_that("extend_fu_details_to_exergy() gives NULL when matrices are NULL", {
  details_mat <- Matrix::sparseMatrix(i = c(1, 2, 3),
                                      j = c(1, 3, 2),
                                      x = c(10, 20, 100),
                                      dimnames = list(c("Electricity -> Households",
                                                        "Electricity -> Industry",
                                                        "Natural gas -> Households"),
                                                      c("Light [from Electric lamps]",
                                                        "MTH.100.C [from Furnaces]",
                                                        "KE [from Fans]"))) |>
    matsbyname::setrowtype("Product -> Industry") |>
    matsbyname::setcoltype("Product [from Industry]")
  phi_vec <- Matrix::sparseMatrix(i = c(1, 2, 3, 4),
                                  j = c(1, 1, 1, 1),
                                  x = c(1.0, 1-(25+273.15)/(100+273.15), 0.96, 1-(25+273.15)/(1000+273.15)),
                                  dimnames = list(c("KE", "MTH.100.C", "Light", "HTH.1000.C"),
                                                  "phi")) |>
    matsbyname::setrowtype("Product") |>
    matsbyname::setcoltype("phi")

  Y_fu_details <- details_mat
  U_EIOU_fu_details <- details_mat
  details_df <- tibble::tribble(~Energy.type, ~phi,    ~R, ~U, ~V, ~Y, ~Y_fu_details, ~U_EIOU_fu_details,
                                "E",          phi_vec, 1,  1,  1,  1,  NULL,          U_EIOU_fu_details,
                                "E",          phi_vec, 2,  2,  2,  2,  Y_fu_details,  NULL)
  # A data frame without the details matrices should return NULL.
  res <- extend_fu_details_to_exergy(details_df)

  res |>
    dplyr::filter(Energy.type == "X", R == 1) |>
    magrittr::extract2("Y_fu_details") |>
    magrittr::extract2(1) |>
    expect_null()
  res |>
    dplyr::filter(Energy.type == "X", R == 2) |>
    magrittr::extract2("U_EIOU_details") |>
    magrittr::extract2(1) |>
    expect_null()
})