## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----eval = FALSE-------------------------------------------------------------
# # install.packages("devtools")
# devtools::install_github("IDEMSInternational/carbonr")

## ----message = FALSE, warning = FALSE-----------------------------------------
library(carbonr)

## ----message = FALSE, warning = FALSE, eval=FALSE, include=TRUE---------------
# airport_finder(name = "Vancouver")

## ----message = FALSE, warning = FALSE, echo = FALSE---------------------------
airport_finder(name = "Vancouver") %>%
  knitr::kable()

## ----message = FALSE, warning = FALSE, eval=FALSE, include=TRUE---------------
# airport_finder(name = "Toronto")

## ----message = FALSE, warning = FALSE, echo = FALSE---------------------------
airport_finder(name = "Toronto") %>%
  knitr::kable()

## ----message = FALSE, warning = FALSE-----------------------------------------
airplane_emissions("YVR", "YTZ")

## ----message = FALSE, warning = FALSE, eval=FALSE, include=TRUE---------------
# seaport_finder(country = "Australia", city = "Melbourne")

## ----message = FALSE, warning = FALSE, echo = FALSE---------------------------
seaport_finder(country = "Australia", city = "Melbourne") %>%
  knitr::kable()

## ----message = FALSE, warning = FALSE, eval=FALSE, include=TRUE---------------
# seaport_finder(country = "US", city = "New York")

## ----message = FALSE, warning = FALSE, echo = FALSE---------------------------
seaport_finder(country = "US", city = "New York") %>%
  knitr::kable()

## ----message = FALSE, warning = FALSE-----------------------------------------
ferry_emissions("POR", "BOY", round_trip = TRUE)

## ----message = FALSE, warning = FALSE, eval=FALSE, include=TRUE---------------
# multiple_ind <- tibble::tribble(~ID, ~station,
#                         "From", "Bristol",
#                         "To", "Edinburgh",
#                         "Via", "Birmingham")
# purrr::map(.x = multiple_ind$station, .f = ~rail_finder(.x)) %>%
#   dplyr::bind_rows()

## ----message = FALSE, warning = FALSE, echo=FALSE-----------------------------
multiple_ind <- tibble::tribble(~ID, ~station,
                        "From", "Bristol",
                        "To", "Edinburgh",
                        "Via", "Birmingham")
purrr::map(.x = multiple_ind$station, .f = ~rail_finder(.x)) %>%
  dplyr::bind_rows() %>%
  knitr::kable()

## ----message = FALSE, warning = FALSE-----------------------------------------
rail_emissions(from = "Bristol Temple Meads", to = "Edinburgh", via = "Birmingham New Street")

## ----message = FALSE, warning = FALSE, eval=FALSE, include=TRUE---------------
# multiple_ind <- tibble::tribble(~ID, ~rail_from, ~rail_to, ~air_from, ~air_to, ~air_via,
#                         "Clint", "Bristol Temple Meads", "Paddington", "LHR", "KIS", "NBO",
#                         "Zara", "Bristol Temple Meads", "Paddington", "LHR", "LAX", "ORL")
# multiple_ind %>%
#   dplyr::rowwise() %>%
#   dplyr::mutate(plane_emissions = airplane_emissions(air_from,
#                                               air_to,
#                                               air_via)) %>%
#   dplyr::mutate(train_emissions = rail_emissions(rail_from,
#                                           rail_to)) %>%
#   dplyr::mutate(total_emissions = plane_emissions + train_emissions)

## ----message = FALSE, warning = FALSE, echo = FALSE---------------------------
multiple_ind <- tibble::tribble(~ID, ~rail_from, ~rail_to, ~air_from, ~air_to, ~air_via,
                        "Clint", "Bristol Temple Meads", "Paddington", "LHR", "KIS", "NBO",
                        "Zara", "Bristol Temple Meads", "Paddington", "LHR", "LAX", "ORL")
multiple_ind %>%
  dplyr::rowwise() %>%
  dplyr::mutate(plane_emissions = airplane_emissions(air_from,
                                              air_to,
                                              air_via)) %>%
  dplyr::mutate(train_emissions = rail_emissions(rail_from,
                                          rail_to)) %>%
  dplyr::mutate(total_emissions = plane_emissions + train_emissions) %>%
  knitr::kable()

## ----message = FALSE, warning = FALSE, eval=FALSE, include=TRUE---------------
# df <- data.frame(time = c("10/04/2000", "10/04/2000", "11/04/2000", "11/04/2000", "12/04/2000", "12/04/2000"),
# theatre = rep(c("A", "B"), times = 3),
# desflurane = c(30, 0, 25, 0, 28, 0),
# isoflurane = c(0, 37, 0, 30, 0, 35),
# clinical_waste = c(80, 90, 80, 100, 120, 110),
# electricity_kwh = c(100, 110, 90, 100, 100, 110),
# general_waste = c(65, 55, 70, 50, 60, 30))

## ----message = FALSE, warning = FALSE, echo=FALSE-----------------------------
data.frame(time = c("10/04/2000", "10/04/2000", "11/04/2000", "11/04/2000", "12/04/2000", "12/04/2000"),
theatre = rep(c("A", "B"), times = 3),
desflurane = c(30, 28, 25, 0, 0, 0),
isoflurane = c(0, 0, 0, 30, 37, 35),
clinical_waste = c(80, 90, 80, 100, 120, 110),
electricity_kwh = c(100, 110, 90, 100, 100, 110),
general_waste = c(65, 55, 70, 50, 60, 30)) %>%
  knitr::kable()

## ----message = FALSE, warning = FALSE, eval=FALSE, include=TRUE---------------
# # get emissions and CPI (carbon price index)
# clinical_theatre_data(
#   df,
#   time = time,
#   name = theatre,
#   wet_clinical_waste = clinical_waste,
#   wet_clinical_waste_unit = "kg",
#   electricity_kWh = electricity_kwh,
#   plastic_vars = c(average = "general_waste"),
#   include_cpi = TRUE,
#   jurisdiction = "Australia",
#   year = 2023,
#   value_col = "value_2024",
#   strict = TRUE
# )

## ----message = FALSE, warning = FALSE, echo=FALSE-----------------------------
# get emissions and CPI (carbon price index)
df <- data.frame(time = c("10/04/2000", "10/04/2000", "11/04/2000", "11/04/2000", "12/04/2000", "12/04/2000"),
theatre = rep(c("A", "B"), times = 3),
desflurane = c(30, 0, 25, 0, 28, 0),
isoflurane = c(0, 37, 0, 30, 0, 35),
clinical_waste = c(80, 90, 80, 100, 120, 110),
electricity_kwh = c(100, 110, 90, 100, 100, 110),
general_waste = c(65, 55, 70, 50, 60, 30))
results <- clinical_theatre_data(
  df,
  time = time,
  name = theatre,
  wet_clinical_waste = clinical_waste,
  wet_clinical_waste_unit = "kg",
  electricity_kWh = electricity_kwh,
  plastic_vars = c(average = "general_waste"),
  include_cpi = TRUE,
  jurisdiction = "Australia",
  year = 2023,
  value_col = "value_2024",
  strict = TRUE
)

results[[1]] %>% knitr::kable()

## ----eval = FALSE-------------------------------------------------------------
# shiny_emissions()