Test sector*() focusing on type, sector and subsector

[maurolepore]

Here is note and reprex to help myself more quickly and accurately understand analysts's comments, and write tests. In short, create test data focusing on the columns type, sector, and subsector in the datasets companies and scenarios.

--

I'm usually confused when I read comments that focus on the columns tilt_sector and tilt_subsector, but then I realize that the role of these columns in the code is indirect.

While companies$tilt_sector and companies$tilt_subsector are crucial conceptually (they relate to sector and subsector), they play no role in the computation. In the computation, the relevant columns are companies$type, companies$sector, and companies$subsector – which yield different results depending on whether or not the values of these columns match or not the values of scenarios$type, scenarios$sector, and scenarios$subsector.

reprex

if (!interactive()) withr::local_options(width = 500)
devtools::load_all()
#> ℹ Loading tiltIndicator

# Matching type, sector, and subsector. 
companies <- tribble(
  ~companies_id, ~clustered, ~activity_uuid_product_uuid, ~tilt_sector, ~tilt_subsector,       ~type,     ~sector,  ~subsector,
            "a",        "b",                 "unmatched",  "unmatched",     "unmatched",       "ipr",     "total",    "energy",
)
scenarios <- tribble(
  ~sector,   ~subsector,  ~year, ~reductions, ~type, ~scenario,
  "total",     "energy",   2050,         1.0, "ipr",       "a",
)

interesting <- c("grouped", "risk", "profile")

sector_profile(companies, scenarios) |> 
  unnest_product() |> 
  relocate(matches(interesting))
#> # A tibble: 1 × 11
#>   grouped_by risk_category profile_ranking companies_id clustered activity_uuid_product_uuid tilt_sector scenario  year type  tilt_subsector
#>   <chr>      <chr>                   <dbl> <chr>        <chr>     <chr>                      <chr>       <chr>    <dbl> <chr> <chr>         
#> 1 ipr_a_2050 high                        1 a            b         unmatched                  unmatched   a         2050 ipr   unmatched

# Unmatched type
companies <- tribble(
  ~companies_id, ~clustered, ~activity_uuid_product_uuid, ~tilt_sector, ~tilt_subsector,       ~type,     ~sector,  ~subsector,
            "a",        "b",                 "unmatched",  "unmatched",     "unmatched", "unmatched",     "total",    "energy",
)
sector_profile(companies, scenarios) |> 
  unnest_product() |> 
  relocate(matches(interesting))
#> # A tibble: 1 × 11
#>   grouped_by risk_category profile_ranking companies_id clustered activity_uuid_product_uuid tilt_sector scenario  year type      tilt_subsector
#>   <chr>      <chr>                   <dbl> <chr>        <chr>     <chr>                      <chr>       <chr>    <dbl> <chr>     <chr>         
#> 1 <NA>       <NA>                       NA a            b         unmatched                  unmatched   <NA>        NA unmatched unmatched

# Unmatched sector
companies <- tribble(
  ~companies_id, ~clustered, ~activity_uuid_product_uuid, ~tilt_sector, ~tilt_subsector,       ~type,     ~sector,  ~subsector,
            "a",        "b",                 "unmatched",  "unmatched",     "unmatched",       "ipr", "unmatched",    "energy",
)
sector_profile(companies, scenarios) |> 
  unnest_product() |> 
  relocate(matches(interesting))
#> # A tibble: 1 × 11
#>   grouped_by risk_category profile_ranking companies_id clustered activity_uuid_product_uuid tilt_sector scenario  year type  tilt_subsector
#>   <chr>      <chr>                   <dbl> <chr>        <chr>     <chr>                      <chr>       <chr>    <dbl> <chr> <chr>         
#> 1 <NA>       <NA>                       NA a            b         unmatched                  unmatched   <NA>        NA ipr   unmatched

# Unmatched subsector
companies <- tribble(
  ~companies_id, ~clustered, ~activity_uuid_product_uuid, ~tilt_sector, ~tilt_subsector,       ~type,     ~sector,  ~subsector,
            "a",        "b",                 "unmatched",  "unmatched",     "unmatched",       "ipr",     "total", "unmatched",
)
sector_profile(companies, scenarios) |> 
  unnest_product() |> 
  relocate(matches(interesting))
#> # A tibble: 1 × 11
#>   grouped_by risk_category profile_ranking companies_id clustered activity_uuid_product_uuid tilt_sector scenario  year type  tilt_subsector
#>   <chr>      <chr>                   <dbl> <chr>        <chr>     <chr>                      <chr>       <chr>    <dbl> <chr> <chr>         
#> 1 <NA>       <NA>                       NA a            b         unmatched                  unmatched   <NA>        NA ipr   unmatched