Calculate (and potentially plot) winrates by ascension

Usage

winrate_ascension(
  runhistory,
  plotit = TRUE,
  relative = FALSE,
  expected = NULL,
  ignoreabandoned = FALSE,
  ci = TRUE,
  samples = 200,
  lower_quant = 0.025,
  upper_quant = 0.975
)

Arguments

runhistory: An STS2RunHistory object, filtered if necessary.
plotit: Whether to plot the data or just return a summary data.frame
relative: Whether to calculate the character-based winrate relative to the total winrate.
expected: If set, the expected winrate to scale values relative to (automatically turns on relative when set).
ignoreabandoned: Remove abandoned runs from data prior to analysis (otherwise abandoned runs count as losses).
ci: Whether to calculate and plot 95% confidence intervals
samples: The number of iterations to use when generating CIs.
lower_quant: The lower quantile of the CIs.
upper_quant: The upper quantile of the CIs.

Value

A data.frame summary of winrates by ascension.

Examples

if (FALSE) { # interactive()
myruns <- load_sts_history()
winrate_ascension(myruns)
}