## ----setupknitr, include = FALSE----------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
load(system.file(file.path("extdata", "environmental_impact_vignette.rda"), package = "iotables"))

## ----setup, echo=FALSE, message=FALSE-----------------------------------------
library(iotables)
library(dplyr, quietly = TRUE)
library(tidyr, quietly = TRUE)

## ----getiotable, eval=FALSE---------------------------------------------------
# # For faster building this data has been loaded from "../extdata/environmental_impact_vignette.rda"
# BE <- iotable_get(
#   source = "naio_10_cp1700", geo = "BE",
#   year = 2015,
#   labelling = "short", unit = "MIO_EUR",
#   stk_flow = "TOTAL"
# )

## ----getairpol, eval=FALSE----------------------------------------------------
# # For faster building this data has been loaded from "../extdata/environmental_impact_vignette.rda"
# ghg <- airpol_get(airpol = "GHG", geo = "BE", year = 2020, unit = "THS_T")

## ----ghgindicators------------------------------------------------------------
be_io <- BE %>%
  supplementary_add(ghg)

ghg_indicator <- input_indicator_create(
  data_table = be_io,
  input_row  = "GHG_emission"
)

## ----ghgindicator-------------------------------------------------------------
# Only the top 5 is printed, rename, arrange and top_n are tidyverse functions:
ghg_indicator %>%
  vector_transpose_longer(.keep = TRUE) %>%
  rename(GHG_emission_indicator = .data$value) %>%
  arrange(-.data$GHG_emission_indicator) %>%
  top_n(5)

## ----getco2indicators, eval=FALSE---------------------------------------------
# co2 <- airpol_get(airpol = "CO2", geo = "BE", year = 2020, unit = "THS_T")

## ----co2indicators------------------------------------------------------------
be_io_c <- BE %>%
  supplementary_add(co2)

co2_indicator <- input_indicator_create(
  data_table  = be_io_c,
  input_row   = "CO2_emission"
)

# Only the top 5 is printed:
co2_indicator %>%
  vector_transpose_longer(.keep = TRUE) %>%
  rename(CO2_emission_indicator = .data$value) %>%
  arrange(-.data$CO2_emission_indicator) %>%
  top_n(5)

## ----getmethaneindicators, eval=FALSE-----------------------------------------
# methane <- airpol_get(airpol = "CH4", geo = "BE", year = 2020, unit = "THS_T")

## ----methaneindicators--------------------------------------------------------
be_io_m <- BE %>%
  supplementary_add(methane)

methane_indicator <- input_indicator_create(
  data_table = be_io_m,
  input_row  = "CH4_emission"
)

# Only the top 5 is printed:
methane_indicator %>%
  vector_transpose_longer(.keep = TRUE) %>%
  rename(CH4_emission_indicator = .data$value) %>%
  arrange(-.data$CH4_emission_indicator) %>%
  top_n(5)

## ----ghgmultiplier, message=FALSE---------------------------------------------
I_be <- input_coefficient_matrix_create(
  data_table = BE,
  digits = 4
) %>%
  leontief_inverse_create()

ghg_multipliers <- multiplier_create(
  input_vector = ghg_indicator,
  Im = I_be,
  multiplier_name = "GHG_multiplier",
  digits = 4
)

# Only the top 5 is printed:
ghg_multipliers %>%
  vector_transpose_longer(.keep = TRUE) %>%
  rename(GHG_multiplier = .data$value) %>%
  arrange(-.data$GHG_multiplier) %>%
  top_n(5)

## ----savevignettedata, eval=FALSE---------------------------------------------
# save(methane, co2, ghg, BE, file = file.path("..", "inst", "extdata", "environmental_impact_vignette.rda"))