Scrape primary industry names from R, V, and Y matrices

Primary industry names are needed for aggregation. This function interrogates the row names of R and V and the column names Y matrices for names that start with p_industries. The assumption is that many of these row and column names may have compound names of the form "Resources [of Oil and gas extraction]". So this function looks for leading strings. If "Resources" is in p_industries, "Resources [of Oil and gas extraction]" will be among the returned strings.

Usage

find_p_industry_names(
  .sutdata = NULL,
  p_industry_prefixes = Recca::industry_cols$p_industry_prefixes,
  R = Recca::psut_cols$R,
  V = Recca::psut_cols$V,
  Y = Recca::psut_cols$Y,
  p_industries_complete = Recca::industry_cols$p_industries_complete
)

Arguments

.sutdata: An optional data frame containing columns of PSUT matrices
p_industry_prefixes: The name of a column in .sutdata containing vectors of prefixes that identify primary industry names, or a vector of prefixes that identify primary industry names. Default is Recca::industry_cols$p_industry_prefixes. Hint: IEATools::tpes_flows contains a good list of primary industry prefixes.
R: The name of the R matrix column in .sutdata or an R matrix.
V: The name of the V matrix column in .sutdata or a V matrix.
Y: The name of the Y matrix column in .sutdata or a Y matrix.
p_industries_complete: The name of the output column containing complete names of primary industries. Default is Recca::industry_cols$p_industries_complete.

Value

If .sutdata is a data frame, a data frame with additional column p_industries_complete. If .sutdata is a list of named matrices (R, V, and Y), A vector or vectors of full names of primary industries in the R, V, and Y matrices, a list of primary industries.

Details

Note all of R, V, and Y need to be specified.

Examples

Rrows <- c("Resources [of Oil and gas extraction]", "Resources [of Coal mines]")
R <- matrix(c(1, 0,
              0, 2), nrow = 2, byrow = TRUE,
            dimnames = list(Rrows, c("Crude oil", "Brown coal")))
Vrows <- c("Imports [of Crude oil]", "Stock changes [of Bituminous coal]")
V <- matrix(c(3, 0,
              0, 4), nrow = 2, byrow = TRUE,
            dimnames = list(Vrows, c("Crude oil", "Bituminous coal")))
Ycols <- c("Exports [of Electricity]", "International marine bunkers [of Gas/diesel oil]")
Y <- matrix(c(5, 0,
              0, 6), nrow = 2, byrow = TRUE,
            dimnames = list(c("Electricity", "Gas/diesel oil"), Ycols))
p_industry_prefixes <- c("Resources", "Imports", "Exports",
                         "Stock changes", "International marine bunkers")
# This function works with individual matrices, so long as they are
# first wrapped in `list()`.
find_p_industry_names(p_industry_prefixes = list(p_industry_prefixes),
                      R = list(R), V = list(V), Y = list(Y))
#> $p_industries_complete
#> [1] "Resources [of Oil and gas extraction]"           
#> [2] "Resources [of Coal mines]"                       
#> [3] "Imports [of Crude oil]"                          
#> [4] "Stock changes [of Bituminous coal]"              
#> [5] "Exports [of Electricity]"                        
#> [6] "International marine bunkers [of Gas/diesel oil]"
#> 
# Also works in the context of a data frame.
# Use a `tibble`, because it handles matrices better
res <- tibble::tibble(R = list(R,R), V = list(V,V), Y = list(Y,Y),
                     p_industries = list(p_industry_prefixes, "Resources")) %>%
 find_p_industry_names(p_industry_prefixes = "p_industries")
res$p_industries_complete[[1]]
#> [1] "Resources [of Oil and gas extraction]"           
#> [2] "Resources [of Coal mines]"                       
#> [3] "Imports [of Crude oil]"                          
#> [4] "Stock changes [of Bituminous coal]"              
#> [5] "Exports [of Electricity]"                        
#> [6] "International marine bunkers [of Gas/diesel oil]"
res$p_industries_complete[[2]]
#> [1] "Resources [of Oil and gas extraction]"
#> [2] "Resources [of Coal mines]"