separate_metric_from_name() splits up some scenario names wrong

[jacobvjk]

When running target_market_share on a scenario that has a name which includes a dash, separate_metric_from_name() will wrongly split everything after the dash and drop that part of the name.

While the calculation does not necessarily fail, this generates a warning and produces inconsistent scenario names between input and output (see reprex below).

Note that this can be problematic, if one were to use geco_2021 scenarios for 1.5c-unif and 1.5c-diff. The scenarios names in the result would be indistinguishable.

---

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(r2dii.data)
library(r2dii.match)


scenario_test <- tibble::tribble(
  ~scenario_source,   ~scenario, ~sector,     ~technology,  ~region, ~year,              ~tmsr,                  ~smsp,
       "test_2021", "1.5c-scen", "power",       "coalcap", "global", 2021L,                  1,                      0,
       "test_2021", "1.5c-scen", "power",        "gascap", "global", 2021L,                  1,                      0,
       "test_2021", "1.5c-scen", "power",      "hydrocap", "global", 2021L,                  1,                      0,
       "test_2021", "1.5c-scen", "power",    "nuclearcap", "global", 2021L,                  1,                      0,
       "test_2021", "1.5c-scen", "power",        "oilcap", "global", 2021L,                  1,                      0,
       "test_2021", "1.5c-scen", "power", "renewablescap", "global", 2021L,                  1,                      0,
       "test_2021", "1.5c-scen", "power",       "coalcap", "global", 2022L,  0.980550658847261,   -0.00533815150443876,
       "test_2021", "1.5c-scen", "power",        "gascap", "global", 2022L,   1.03354175921615,      0.007450150681128,
       "test_2021", "1.5c-scen", "power",      "hydrocap", "global", 2022L,   1.00999497266883,     0.0019055064844559,
       "test_2021", "1.5c-scen", "power",    "nuclearcap", "global", 2022L,    1.0211760246908,    0.00102774473801909,
       "test_2021", "1.5c-scen", "power",        "oilcap", "global", 2022L,  0.996148327056334,  -0.000188168602196809,
       "test_2021", "1.5c-scen", "power", "renewablescap", "global", 2022L,   1.16216522079607,     0.0349281658652597,
       "test_2021", "1.5c-scen", "power",       "coalcap", "global", 2023L,  0.961101317694522,    -0.0106763030088775,
       "test_2021", "1.5c-scen", "power",        "gascap", "global", 2023L,    1.0670835184323,      0.014900301362256,
       "test_2021", "1.5c-scen", "power",      "hydrocap", "global", 2023L,   1.01998994533766,    0.00381101296891184,
       "test_2021", "1.5c-scen", "power",    "nuclearcap", "global", 2023L,    1.0423520493816,    0.00205548947603818,
       "test_2021", "1.5c-scen", "power",        "oilcap", "global", 2023L,  0.992296654112668,  -0.000376337204393625,
       "test_2021", "1.5c-scen", "power", "renewablescap", "global", 2023L,   1.32433044159215,     0.0698563317305194,
       "test_2021", "1.5c-scen", "power",       "coalcap", "global", 2024L,  0.941651976541783,    -0.0160144545133162,
       "test_2021", "1.5c-scen", "power",        "gascap", "global", 2024L,   1.10062527764846,      0.022350452043384,
       "test_2021", "1.5c-scen", "power",      "hydrocap", "global", 2024L,   1.02998491800648,    0.00571651945336774,
       "test_2021", "1.5c-scen", "power",    "nuclearcap", "global", 2024L,    1.0635280740724,    0.00308323421405727,
       "test_2021", "1.5c-scen", "power",        "oilcap", "global", 2024L,  0.988444981169002,  -0.000564505806590434,
       "test_2021", "1.5c-scen", "power", "renewablescap", "global", 2024L,   1.48649566238822,      0.104784497595779,
       "test_2021", "1.5c-scen", "power",       "coalcap", "global", 2025L,  0.922202635389044,     -0.021352606017755,
       "test_2021", "1.5c-scen", "power",        "gascap", "global", 2025L,   1.13416703686461,      0.029800602724512,
       "test_2021", "1.5c-scen", "power",      "hydrocap", "global", 2025L,   1.03997989067531,    0.00762202593782364,
       "test_2021", "1.5c-scen", "power",    "nuclearcap", "global", 2025L,    1.0847040987632,    0.00411097895207636,
       "test_2021", "1.5c-scen", "power",        "oilcap", "global", 2025L,  0.984593308225336,  -0.000752674408787243,
       "test_2021", "1.5c-scen", "power", "renewablescap", "global", 2025L,   1.64866088318429,      0.139712663461039,
       "test_2021", "1.5c-scen", "power",       "coalcap", "global", 2026L,   0.88869003909333,    -0.0305506202295842,
       "test_2021", "1.5c-scen", "power",        "gascap", "global", 2026L,   1.15655075755489,     0.0347723780828709,
       "test_2021", "1.5c-scen", "power",      "hydrocap", "global", 2026L,   1.05502014053871,     0.0104893968243815,
       "test_2021", "1.5c-scen", "power",    "nuclearcap", "global", 2026L,   1.22288798195939,     0.0108175143338382,
       "test_2021", "1.5c-scen", "power",        "oilcap", "global", 2026L,    1.0149329550691,   0.000729530602187077,
       "test_2021", "1.5c-scen", "power", "renewablescap", "global", 2026L,   2.02141641037022,      0.219999094897005
  )


region_isos_test <- r2dii.data::region_isos %>% 
  dplyr::filter(source == "geco_2021", region == "global") %>% 
  dplyr::mutate(source = "test_2021")

matched <- match_name(r2dii.data::loanbook_demo, r2dii.data::abcd_demo) %>%
  prioritize()

tms <- r2dii.analysis::target_market_share(
  data = matched,
  abcd = r2dii.data::abcd_demo,
  scenario = scenario_test,
  region_isos = region_isos_test
)
#> Warning: Expected 2 pieces. Additional pieces discarded in 72 rows [3, 4, 7, 8,
#> 11, 12, 15, 16, 19, 20, 23, 24, 27, 28, 31, 32, 35, 36, 39, 40, ...].

unique(scenario_test$scenario)
#> [1] "1.5c-scen"

unique(tms$metric)
#> [1] "projected"         "target_1.5c"       "corporate_economy"
Created on 2022-12-12 with [reprex v2.0.2](https://reprex.tidyverse.org/)