scoring-summary.Rmd

---
output:
  md_document:
    variant: gfm
---
```{r setup, include=FALSE}
if (length(commandArgs(trailingOnly=TRUE)) > 0) {
  args <- commandArgs(trailingOnly=TRUE)
}
validators <- read.csv(args[1])
```
# Scoring results `r args[2]`
```{r, echo=FALSE}
library(knitr)
df <- data.frame(type = c("Performance-based stake", "veMNDE directed stake", "mSOL directed stake", "", "**Total stake**"),
                 stake = c(
                   sum(validators$target_stake_algo),
                   sum(validators$target_stake_vemnde),
                   sum(validators$target_stake_msol),
                   "",
                   sum(validators$target_stake)
                 ),
                 validators = c(
                   sum(validators$target_stake_algo > 0),
                   sum(validators$target_stake_vemnde > 0),
                   sum(validators$target_stake_msol > 0),
                   "",
                   sum(validators$target_stake > 0)
                 ),
                 perf = c(
                   round(sum(validators$avg_adjusted_credits * validators$target_stake_algo) / sum(validators$target_stake_algo)),
                   round(sum(validators$avg_adjusted_credits * validators$target_stake_vemnde) / sum(validators$target_stake_vemnde)),
                   round(sum(validators$avg_adjusted_credits * validators$target_stake_msol) / sum(validators$target_stake_msol)),
                   "",
                   round(sum(validators$avg_adjusted_credits * validators$target_stake) / sum(validators$target_stake))
                 )
)
kable(df, col.names = c("Stake type", "Stake (SOL)", "Validators", "Stake-weighted performance"))
```