currenttag=$(git describe --tags --abbrev=0 | sed 's/v//') currenttagfull=$(git describe --tags --abbrev=0) defaultbranch=$(git branch | cut -c 3- | grep -E '^master$|^main$') -currentcommit=$(git rev-list --count ${currenttagfull}..${defaultbranch}) -currentversion="${currenttag}.$((currentcommit + 9001 + 1))" -echo "$currentversion"
The + 1 accounts for the fact that this PR’s squash commit is not yet on the default branch. Set both of these files to the resulting version string (and only once per PR, even across multiple commits):
+ 1
DESCRIPTION — the Version: field
DESCRIPTION
Version:
tibble
This will become release v3.1.0, intended for launch end of May.
clinical_breakpoints
as.sir()
future
parallel = TRUE
future::plan()
future::plan(future::multisession)
antibiogram()
wisca()
parallel
future.apply
(group, chunk)
recipes
NA
NA_ab_
NA_mo_
NA_character_
NA_integer_
"1"
as.mic()
"1e-3"
e
as.ab()
ETH
MTH
PHE
PHN
STH
THA
THI1
info = FALSE
reference_data
> breakpoint_R
< breakpoint_R
host = NA
cli
Numeric value (1–22 for WISCA, 1-12 for non-WISCA) indicating how the 'cells' of the antibiogram table should be formatted. See Details > Formatting Type for a list of options.
Numeric value (1-22 for WISCA, 1-12 for non-WISCA) indicating how the 'cells' of the antibiogram table should be formatted. See Details > Formatting Type for a list of options.
A logical to indicate info should be printed - the default is TRUE only in interactive mode.
TRUE
A logical to indicate if parallel computing must be used, defaults to FALSE. Requires the future.apply package. For WISCA, Monte Carlo simulations are distributed across workers; for grouped antibiograms, each group is processed by a separate worker. A non-sequential future::plan() must already be active before setting parallel = TRUE – for example, future::plan(future::multisession). An error is thrown if parallel = TRUE is used without a plan set by the user.
FALSE
When used in R Markdown or Quarto: arguments passed on to knitr::kable() (otherwise, has no use).
knitr::kable()
standardized residuals, - (observed - expected) / sqrt(V), where V is the - residual cell variance (Agresti, 2007, section 2.4.5 - for the case where x is a matrix, n * p * (1 - p) otherwise).
(observed - expected) / sqrt(V)
V
x
n * p * (1 - p)
tol
rank.
min(dim(x))
tol = 0
tol = sqrt(.Machine$double.eps)