target_sda outputs unexpected NAs

[jdhoffa]

There are two big issues exposed in the reprex below.

• target_sda should only output values in the range of years presented in the co2_scenario input.
• target_sda should not output a value for target_NA (which seems to be a scenario defined as NA?)

---

Brief description of the problem

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)
library(r2dii.analysis)

# ald with only sectors that we have CO2 scenarios for
ald <- head(ald_demo, 100) %>% 
  filter(sector %in% c("cement", "steel"))

matched<- prioritize(match_name(loanbook_demo, ald))

co2_scenario <- co2_intensity_scenario_demo

out <- target_sda(matched, ald, co2_scenario) 

out_targets <- out %>% 
  filter(!(emission_factor_metric %in% c("projected", "corporate_economy")))

# all targets before 2020 are NA
out_targets %>% 
  filter(year < 2020)
#> # A tibble: 14 x 4
#>    sector  year emission_factor_metric emission_factor_value
#>    <chr>  <dbl> <chr>                                  <dbl>
#>  1 cement  2013 target_NA                                 NA
#>  2 cement  2013 target_demo                               NA
#>  3 cement  2014 target_NA                                 NA
#>  4 cement  2014 target_demo                               NA
#>  5 cement  2015 target_NA                                 NA
#>  6 cement  2015 target_demo                               NA
#>  7 cement  2016 target_NA                                 NA
#>  8 cement  2016 target_demo                               NA
#>  9 cement  2017 target_NA                                 NA
#> 10 cement  2017 target_demo                               NA
#> 11 cement  2018 target_NA                                 NA
#> 12 cement  2018 target_demo                               NA
#> 13 cement  2019 target_NA                                 NA
#> 14 cement  2019 target_demo                               NA

# some targets after 2020 are NA
out_targets %>% 
  filter(year >= 2020)
#> # A tibble: 93 x 4
#>    sector  year emission_factor_metric emission_factor_value
#>    <chr>  <dbl> <chr>                                  <dbl>
#>  1 cement  2020 target_NA                             NA    
#>  2 cement  2020 target_demo                            0.723
#>  3 cement  2021 target_NA                             NA    
#>  4 cement  2021 target_demo                            0.660
#>  5 cement  2022 target_NA                             NA    
#>  6 cement  2022 target_demo                            0.597
#>  7 cement  2023 target_NA                             NA    
#>  8 cement  2023 target_demo                            0.534
#>  9 cement  2024 target_NA                             NA    
#> 10 cement  2024 target_demo                            0.471
#> # … with 83 more rows

^{Created on 2021-06-08 by the reprex package (v2.0.0)}