R/confrontation.R

Defines functions simplify_list int_values nas fails failed_confrontations passes is_null has_value has_warning has_error execute namecheck get_stat confront_work check_that .show_confrontation confrontation_nmiss confrontation_nerrs confrontation_nwarn

Documented in check_that

#' @include validator.R
#' @include indicator.R
NULL

# CONFRONTATION OBJECT --------------------------------------------------------


#' Superclass storing results of confronting data with rules
#'
#' @section Details:
#' This class is aimed at developers of this package or packages depending on 
#' it. It is the parent of classes \code{\link{indication}} and 
#' \code{\link{validation}} which are user-facing.
#' 
#' Using \code{\link{confront}}, a set of rules can be executed in the context
#' of one or more (nested) environments holding data. The results of such evaluations
#' are stored in a \code{confrontation} object along with metadata. 
#' 
#' We strongly advise against accessing the data fields or methods internal to
#' this object directly, as we may change or remove them without notice. Use
#' the exported methods listed below in stead.
#' 
#' @family confrontation-methods
#' 
#' @aliases confrontation
#' @keywords internal
setRefClass("confrontation"
  ,fields = list(
      ._call  = "call"       # (user's) call that generated the object
    , ._value = "list"       # results of confrontation 
    , ._calls = "list"       # calls executed during confrontation
    , ._warn  = "list"       # list of 'warning' objects
    , ._error = "list"       # list of 'error' objects
    , ._keys  = "list"       # list with at least 'keyset': an object containing the identifying variables in dat.
    , ._event = "character"  # Metadata identifying the confrontation event.
  )
  , methods=list(
    show = function() .show_confrontation(.self)
  )
)


confrontation_nwarn <- function(x) sum(vapply(x$._warn, function(w)!is.null(w), FUN.VALUE = logical(1)))
confrontation_nerrs <- function(x) sum(vapply(x$._error, function(w)!is.null(w), FUN.VALUE = logical(1)))
confrontation_nmiss <- function(x) sum(vapply(x$._value, anyNA, FUN.VALUE=logical(1)))

.show_confrontation <- function(.self){
  cat(sprintf("Object of class '%s'\n",class(.self)))
  cat(sprintf("Call:\n    ")); print(.self$._call); cat('\n')
  cat(sprintf('Rules confronted: %d\n', length(.self$._calls)))
  cat(sprintf('   With missings: %d\n', confrontation_nmiss(.self) ))
  cat(sprintf('   Threw warning: %d\n', confrontation_nwarn(.self) ))
  cat(sprintf('   Threw errors : %d\n', confrontation_nerrs(.self) ))
}


# S4 GENERICS -----------------------------------------------------------------

#' Confront data with a (set of) expressionset(s)
#'
#' An expressionset is a general class storing rich expressions (basically
#' expressions and some meta data) which we call 'rules'. Examples of
#' expressionset implementations are \code{\link{validator}} objects, storing
#' validation rules and \code{\link{indicator}} objects, storing data quality
#' indicators. The \code{confront} function evaluates the expressions one by one
#' on a dataset while recording some process meta data. All results are stored in
#' a (subclass of a) \code{confrontation} object.  
#'
#'
#' @param dat An R object carrying data
#' @param x An R object carrying \code{\link{rule}}s.
#' @param ref Optionally, an R object carrying reference data. See examples for usage.
#' @param ... Options used at execution time (especially \code{'raise'}). 
#'    See \code{\link{voptions}}.
#' 
#' @section Reference data:
#' 
#' Reference data is typically a \code{list} with a items such as
#' a code list, or a data frame of which rows match the rows of the
#' data under scrutiny.
#' 
#' 
#' @seealso \code{\link{voptions}} 
#' 
#' @family confrontation-methods
#' @family validation-methods
#' @family indication-methods
#'
#' @example ../examples/confront.R
#' @export 
setGeneric("confront",
  def = function(dat, x, ref, ...) standardGeneric("confront")
)

#' Get or set event information metadata from a 'confrontation' object.
#' 
#' The purpose of event information is to store information that allows for
#' identification of the confronting event.
#' 
#' 
#' @param x an object of class \code{confrontation}
#' 
#' @return  A a character vector with elements
#'   \code{"agent"}, which defaults to the R version and platform returned by
#'   \code{R.version}, a timestamp (\code{"time"})  in ISO 8601 format and a
#'   \code{"actor"} which is the user name returned by \code{Sys.info()}. The
#'   last element is called \code{"trigger"} (default \code{NA_character_}), which
#'   can be used to administrate the event that triggered the confrontation.
#'
#' @references 
#' Mark van der Loo and Olav ten Bosch (2017) 
#' \href{https://goo.gl/hEGdbo}{Design of a generic machine-readable validation report structure}, 
#' version 1.0.0. 
#' 
#' @examples
#' data(retailers)
#' rules <- validator(turnover >= 0, staff >=0)
#' cf <- confront(retailers, rules)
#' event(cf)
#' 
#' # adapt event information
#' u <- event(cf)
#' u["trigger"] <- "spontaneous validation"
#' event(cf) <- u
#' event(cf)
#' 
#' @family confrontation-methods
#' @family validation-methods
#' @family indication-methods
#' 
#' @export
setGeneric("event", def = function(x) standardGeneric("event"))

#' @rdname event
setGeneric("event<-", def=function(x, value) standardGeneric("event<-"))

## syntactic sugar function

#' Simple data validation interface
#'
#' @section Details:
#' Creates an object of class \code{\link{validator}} and \code{\link{confront}}s it with the data.
#' This function is easy to use in combination with the \pkg{magrittr} pipe operator.
#' 
#' @param dat an R object carrying data
#' @param ... a comma-separated set of validating expressions.
#' 
#' @return An object of class \code{\link{validation}}
#' @example ../examples/check_that.R   
#' @family validation-methods
#' @export
check_that <- function(dat,...){
  cf <- confront(dat,validator(...))
  cf$._call <- sys.call()
  cf
}


#' Get key set stored with a confrontation
#'
#' @inheritParams event
#'
#' @return If a confrontation is created with the \code{key=} option
#' set, this function returns the key set, otherwise \code{NULL}
#'
#' @export
setGeneric("keyset", def=function(x) standardGeneric("keyset"))

#' @rdname keyset
#' @family confrontation-methods
#' @export 
setMethod("keyset", "confrontation", function(x){
  x$._keys$keyset
})


#' Get values from object
#' 
#' 
#' @param x an R object
#' @param ... Arguments to pass to or from other methods
#'
#' @export
setGeneric('values',def=function(x,...) standardGeneric('values'))

#' Get messages from  a confrontation object
#' @param x An object of class \code{\link{confrontation}}
#' @param ... Arguments to be passed to other methods.
#' 
#' 
#' @example ../examples/exceptions.R
#' @family confrontation-methods
#' @export 
setGeneric("errors",def = function(x,...) standardGeneric("errors"))

# retrieve warnings from a confrontation object
setGeneric("warnings")

# useful ways to aggregate confrontations
setGeneric('aggregate')

# useful ways to sort confrontations
setGeneric('sort')

# S4 METHODS ------------------------------------------------------------------

## The below function is a worker that assumes all relevant data is present in 
## an environment, possibly with a parent containing reference data. Most, if not
## all R-based 'confront' methods will convert to this form and call the worker.
##
## x a validator object
## dat an environment
## key a character indicating a key.
##
confront_work <- function(x, dat, key=NULL, class='confrontation', ...){
  opts         <- x$clone_options(...)
  lin_eq_eps   <- opts('lin.eq.eps')
  lin_ineq_eps <- opts('lin.ineq.eps')
  calls <- x$exprs(expand_assignments=TRUE
            , lin_eq_eps=lin_eq_eps
            , lin_ineq_eps=lin_ineq_eps
            , dat=dat)
  L <- execute(calls,dat,opts)
  new(class,
      ._call    = match.call(definition=confront,call=sys.call(sys.parent(2)))
      , ._calls = calls
      , ._value = lapply(L,"[[",1)
      , ._warn  =  lapply(L,"[[",2)
      , ._error = lapply(L,"[[",3)
      , ._keys  = list(keyset = key)
      , ._event = c(
             agent = sprintf("%s > %s %s.%s > validate %s"
                        , R.version[["platform"]]        
                        , R.version[["language"]], R.version[["major"]], R.version[["minor"]]
                        , utils::packageVersion("validate") )
           , time    = format(Sys.time(),"%Y%m%dT%H%M%S%z")
           , actor   = Sys.info()[["user"]]
           , trigger = NA_character_ )
  )
}


#' @rdname select
#' @aliases [,confrontation-method
#' @family confrontation-methods
#' @export 
setMethod("[","confrontation",function(x,i,j,...,drop=TRUE){

  # this trycatch mechanism protects against an error 
  # occurring when confrontation objects are indexed
  # within lapply. See GH issue #116.
  call <- tryCatch(match.call(call=sys.call(sys.parent()))
            , error = function(e) NULL)
  if (is.null(call)){
    call <- match.call()
  }

  new(class(x)
    , ._call = call
    , ._calls = x$._calls[i]
    , ._value = x$._value[i]
    , ._warn = x$._warn[i]
    , ._error  = x$._error[i]
    , ._keys = x$._keys
  )
})


#' @rdname event
#' @export
setMethod("event", signature = "confrontation", definition = function(x){
  x$._event
})

#' @rdname event
#' @param value \code{[character]} vector of length 4 with event identifiers.
#' @export
setMethod("event<-","confrontation", function(x, value){
  stopifnot(is.character(value))
  stopifnot(all( names(value) == c("agent","time","actor","trigger") ) )
  x$._event <- value
  invisible(x)
})



#' @rdname length
#' @aliases length,confrontation-method
#' @family confrontation-methods
#' @export
setMethod("length","confrontation",function(x) length(x$._value))

# indicators serve a different purpose than validations.


#' Store results of evaluating indicators
#'
#' \bold{This feature is currently experimental and may change in the future}
#'
#' @section Details:
#' An \code{indication} stores a set of results generated by evaluating
#' an \code{\link{indicator}} in the context of data along with some metadata.
#' 
#' 
#' @section Exported S4 methods for \code{indication}:
#' \itemize{
#'  \item{Methods exported for objects of class \code{\link{confrontation}}}
#'  \item{\code{\link{summary,indication-method}}}
#'  \item{\code{\link{values,indication-method}}}
#' }
#' 
#' @keywords internal
#' 
#' @section See also:
#' \itemize{
#' \item{\code{\link{confront}}}
#' \item{\code{\link{validation-class}}}
#' }
#' @aliases indication 
#' @family indication-methods
setRefClass("indication", contains = "confrontation")

#' @rdname confront
setMethod("confront", signature("data.frame","indicator"), function(dat, x, key=NULL,...){
  data_env <- list2env(dat)
  data_env$. <- dat
  confront_work(x, data_env, dat[key], class = "indication",...)
})

#' @rdname confront
setMethod("confront",signature("data.frame","indicator","environment"), function(dat, x, ref, key=NULL, ...){
  data_env <- namecheck(list2env(dat,parent=ref))
  data_env$. <- dat
  confront_work(x,data_env, dat[key], class="indication",...)
})

#' @rdname confront
setMethod("confront",signature("data.frame","indicator","data.frame"),function(dat, x,ref, key=NULL,...){
  env <- new.env()
  env$ref <- ref
  data_env <- namecheck(list2env(dat, parent=env))
  data_env$. <- dat
  confront_work(x, data_env, dat[key], class="indication", ...)
})

#' @rdname confront
setMethod("confront",signature("data.frame","indicator","list"),function(dat, x,ref,key=NULL,...){
  env <- list2env(ref)
  data_env <- namecheck(list2env(dat,parent=env))
  data_env$. <- dat
  confront_work(x, data_env, dat[key], class="indication",...)
})





#' @rdname validate-summary
#' @param object An R object
#' @param ... Currently unused
#'
#' @aliases validate-summary summary,indication-method
#' @section Indication:
#' Some basic information per evaluated indicator is reported: the number 
#' of items to which the indicator was applied, the output \code{class}, 
#' some statistics (min, max, mean , number of NA)
#' and wether an exception occurred (warnings or errors). The evaluated 
#' expression is reported as well.
#' 
#' @family indication-methods
#' @export 
setMethod('summary',signature('indication'), function(object,...){
  data.frame(
    name = names(object$._value)
    , items = sapply(object$._value,length)
    , min = get_stat(object,min,na.rm=TRUE)
    , mean  = get_stat(object,mean,na.rm=TRUE)
    , max = get_stat(object,max,na.rm=TRUE)
    , nNA = nas(object)
    , error = has_error(object)
    , warning = has_warning(object)
    , expression = sapply(object$._calls,call2text)
    , row.names=NULL
    , stringsAsFactors=FALSE
  )  
})

# helper function: x is a confrontation object
get_stat <- function(x,what,...){
  out <- rep(NA,length(x$._value))
  i <- !is_null(x)
  out[i] <- tryCatch(
    sapply(x$._value[i],what,...)
    , error = function(e) NA
    , warning = function(e) NA
  )
  out
}



#' Store results of evaluating validating expressions
#'
#' @section Details:
#' A object of class \code{validation} stores a set of results generated by
#' evaluating an \code{\link{validator}} in the context of data along with some
#' metadata.
#' 
#' 
#' @aliases validation  
#' @family validation-methods
setRefClass("validation", contains = "confrontation")


setMethod("show","validation",function(object){
   cat(sprintf("Object of class '%s'\n",class(object)))
   cat(sprintf("Call:\n    ")); print(object$._call); cat('\n')
   cat(sprintf('Rules confronted: %d\n', length(object$._calls)))
   cat(sprintf('   With fails   : %d\n', failed_confrontations(object)))
   cat(sprintf('   With missings: %d\n', confrontation_nmiss(object)))
   cat(sprintf('   Threw warning: %d\n', confrontation_nwarn(object)))
   cat(sprintf('   Threw error  : %d\n', confrontation_nerrs(object)))
})



#' @rdname confront
#' @param key (optional) name of identifying variable in x.
setMethod("confront", signature("data.frame","validator"), function(dat, x, key=NULL, ...){
  data_env <- list2env(dat)
  data_env$. <- dat
  confront_work(x, data_env, dat[key],'validation',...)
})


namecheck <- function(x){
  n1 <- ls(x)
  n2 <- ls(parent.env(x))
  i <- n1 %in% n2
  if (any(i)){
    n <- paste(paste0("'",n1[i],"'"),collapse=", ") 
    w <- sprintf("Possible reference ambiguity: both current data set and reference data have variables named %s.",n)
    warning(w)
  }
  x
}

#' @rdname confront
setMethod("confront",signature("data.frame","validator","environment"), function(dat, x, ref, key=NULL, ...){
  data_env <- namecheck(list2env(dat,parent=ref))
  data_env$. <- dat
  confront_work(x, data_env, dat[key], class="validation",...)
})

#' @rdname confront
setMethod("confront",signature("data.frame","validator","data.frame"),function(dat, x,ref, key=NULL,...){
  env <- new.env()
  env$ref <- ref
  data_env <- namecheck(list2env(dat, parent=env))
  data_env$. <- dat
  confront_work(x, data_env, dat[key], class="validation", ...)
})

#' @rdname confront
setMethod("confront",signature("data.frame","validator","list"),function(dat, x,ref,key=NULL,...){
  env <- list2env(ref)  
  data_env <- namecheck(list2env(dat,parent=env))
  data_env$. <- dat
  confront_work(x, data_env, dat[key], class="validation",...)  
})



# match rows; prepare for 'left join'.
# of     : an environment containing data.frames
# against: a reference data.frame to match againsty.
# using  : a key (character)
#match_rows <- function(of, against, using){  
#  key1 <- against[,using]
#  for ( nm in ls(of) ){
#    i <- match(key1, of[[nm]][,using], nomatch = nrow(of) + 1)
#    of[[nm]] <- of[[nm]][i,,drop=FALSE]
#  }
#}


#add_names <- function(L,x,y,key){
#  keys <- y[[key]]
#  nkey <- length(keys)
#  L <- lapply(L,function(v){ 
#    if ( length(v[[1]]) == nkey ) 
#      v[[1]] <- setNames(v[[1]], keys)   
#    v
#  })
#}  

# execute calls. 
# - Assignments are stored in a separate environment and forgotten afterwards.
# - Failed assignments yield a warning.
execute <- function(calls,env,opts){
  lapply(calls, function(g){
      if ( g[[1]] == ":=" ){ 
        var <- as.character(left(g))
        if ( var %in% variables(env) ) 
          warning(sprintf("Locally overwriting variable '%s'",var))
          assign(var, tryCatch( eval(right(g), env), error=warning), envir=env)
      } else { 
        val <- factory(eval,opts)(g, env)
        if ( !is.na(opts('na.value')) ){
          val[[1]] <- ifelse(is.na(val[[1]]), opts('na.value'), val[[1]])
        }
        val
      }
    }
  )[!is.assignment(calls)]
}

# x inherits from 'confrontation'
has_error <- function(x) !sapply(x$._error,is.null)
has_warning <- function(x) !sapply(x$._warn, is.null)
has_value <- function(x) sapply(x$._value, function(a) !is.null(a))
is_null <- function(x) sapply(x$._value, is.null)

passes <- function(x){
  sapply(x$._value, function(a) 
    if ( is.null(a) ) 0 else sum(a,na.rm=TRUE)  
  )
}

# return confrontation that failed
failed_confrontations <- function(x){
  sum(fails(x) > 0)
}

fails <- function(x){
  sapply(x$._value, function(a) 
    if ( is.null(a) ) 0 else sum(!a,na.rm=TRUE) 
  )
}

nas <- function(x){
  sapply(x$._value, function(a)
    if ( is.null(a) ) 0 else sum(is.na(a))
  )
}


#' @rdname validate-summary
#' @section Validation:
#' Some basic information per evaluated validation rule is reported: the number of
#' items to which the rule was applied, the output \code{class}, some statistics
#' (passes, fails, number of NA) and wether an exception occurred (warnings or
#' errors). The evaluated expression is reported as well.
#' @family validation-methods
setMethod('summary',signature('validation'),function(object,...){
  data.frame(
    name = names(object$._value)
    , items = sapply(object$._value,length)
    , passes = passes(object)
    , fails  = fails(object)
    , nNA = nas(object)
    , error = has_error(object)
    , warning = has_warning(object)
    , expression = sapply(object$._calls,  call2text)
    , row.names=NULL
    , stringsAsFactors=FALSE
  )  
})



#' @rdname values
setMethod('values',signature('confrontation'),function(x,...){
  x$._value
})

#' @rdname values
#' @aliases values,validation-method
#' @param simplify Combine results with similar dimension structure into arrays?
#' @param drop if a single vector or array results, drop 'list' attribute?
#' @family confrontation-methods
setMethod('values',signature('validation'),function(x,simplify=TRUE,drop=TRUE,...){
  int_values(x,simplify,drop,...)
})

#' @rdname values
#' @aliases  values,indication-method
#' @family validation-methods
setMethod('values',signature('indication'),function(x,simplify=TRUE,drop=TRUE,...){
  int_values(x,simplify,drop,...)
})

int_values <- function(x,simplify,drop,...){
  out <- if ( simplify ){
    simplify_list(x$._value[!is_null(x)])
  } else {
    getMethod(values,signature='confrontation')(x,...)
  }
  if (drop && length(out) == 1) out[[1]] else out
}


simplify_list <- function(L){
  len <- sapply(L,num_result)
  lapply(unique(len), function(l){
    m <- sapply(L[len==l], get_result)
    if ( l == 1 )
      m <- matrix(m,nrow=1,dimnames=list(NULL,names(m)))
    m
  })
}


#' @rdname errors
setMethod("errors","confrontation",function(x,...){
  i <- has_error(x)
  x$._error[i]
})


#' @rdname errors
#' @export 
setMethod("warnings","confrontation",function(x,...){
  i <- has_warning(x)
  x$._warn[i]
})

#' Get names from \code{confrontation} object
#'
#' @rdname names
#' @family validation-methods
#' @export
setMethod("names", "confrontation", function(x){
  names(x$._value)
})


#' Plot validation results
#' 
#' Creates a barplot of validation result. For each validation rule, a stacked bar
#' is plotted with percentages of failing, passing, and missing results.
#' 
#' @param x a confrontation object.
#' @param fill \code{[character]} vector of length 3. Colors representing fails, passes, and missings
#' @param col  Edge colors for the bars.
#' @param rulenames \code{[character]} vector of size \code{length(x)}. If not specified, names
#'        are taken from \code{x}.
#' @param labels \code{[character]} vector of length 4. Replace legend annotation.
#' @param title \code{[character]} Change the default title.
#' @param xlab \code{[character]} Change the title
#' @param y not used
#' @param ... not used
#'
#' @details 
#' The plot function tries to be smart about placing labels on the y axis. When 
#' the number of bars becomes too large, no y axis annotation will be shown and the 
#' bars will become space-filling.
#'
#'
#' @export
#' @family validation-methods
#' @example ../examples/plot.R
setMethod("plot","validation", function(x, y
                    , fill=c("#FE2712","#66B032","#dddddd")
                    , col=fill
                    , rulenames = names(x)
                    , labels=c("Fails","Passing","Missing","Total")
                    , title = NULL
                    , xlab = NULL
                    , ...)
{
  stopifnot(length(rulenames) == length(x))
  if(length(errors(x))>=1){
    errs <- paste(names(errors(x)), sep=", ")
    msgf("Rules %s not included in plot since they could not be executed. See ?errors"
        , errs)
  }
  m <- aggregate(x, by="rule")
  rulenames <- rulenames[!( names(x) %in% names(errors(x)) )]
  if (is.null(m)){
    msgf("Noting to plot")
    return(NULL)
  }
  plot_validation(as.matrix(m[, c("nfail","npass","nNA"), drop=FALSE]) 
                 , fill      = fill
                 , col       = col
                 , rulenames = rulenames
                 , labels    = labels
                 , title     = title
                 , xlab      = xlab )
})



#' Aggregate validation results
#' 
#' Aggregate results of a validation.
#'  
#' @param x An object of class \code{\link{validation}}
#' @param by Report on violations per rule (default) or per record?
#' @param drop drop list attribute if the result is list of length 1
#' @param ... Arguments to be passed to or from other methods.
#'
#' @return By default, a \code{data.frame} with the following columns.
#' \tabular{ll}{
#'   keys \tab If confront was called with \code{key=}\cr
#'   \code{npass} \tab Number of items passed\cr
#'   \code{nfail} \tab Number of items failing\cr
#'   \code{nNA} \tab Number of items resulting in \code{NA}\cr
#'   \code{rel.pass} \tab Relative number of items passed\cr
#'   \code{rel.fail} \tab Relative number of items failing\cr
#'   \code{rel.NA} \tab Relative number of items resulting in \code{NA}
#' }
#' If \code{by='rule'} the relative numbers are computed with respect to the number 
#' of records for which the rule was evaluated. If \code{by='record'} the relative numbers
#' are computed with respect to the number of rules the record was tested agains. 
#'
#' When \code{by='record'} and not all validation results have the same dimension structure,
#' a list of \code{data.frames} is returned.
#' 
#' @family validation-methods
#' @aliases aggregate,validation-method
#' @example ../examples/aggregate.R
#' @export
setMethod('aggregate',signature('validation'), function(x,by=c('rule','record'), drop=TRUE,...){
  v <- values(x, drop=FALSE)
  by <- match.arg(by)
  aggr <- if ( by == 'rule') colSums else rowSums
  ntot <- if ( by == 'rule') nrow else ncol
  L <- lapply(v, function(y){
    s <- if(is.null(dim(y))) 0 else aggr(y,na.rm=TRUE)
    na <- if(is.null(dim(y))) 0 else aggr(is.na(y))
    N <- if (is.null(dim(y))) 0 else ntot(y)
    nfail = N - s - na
    out <- data.frame( 
      npass = s
      , nfail = nfail 
      , nNA = na
      , rel.pass  = s/N
      , rel.fail  = nfail/N
      , rel.NA = na/N
    )
  
    keys <- x$._keys$keyset
    if (by=="record" && nrow(out)==nrow(keys)) cbind(keys,out) else out
  })
  if ( length(L) == 1 && drop ) L <- L[[1]]
  if ( by == 'rule' && !is.data.frame(L) ){ 
    L <- do.call(rbind,L)
    # values are not errors, and such rules are not included by 'values'
    # we also put rules in the same order as in the 'validator' object.
    ii <- match(names(x)[!names(x) %in% names(errors(x))], rownames(L))
    L <- L[ii,, drop=FALSE]
  }
  L
})




#' Aggregate and sort the results of a validation.
#'   
#' @param x An object of class \code{\link{validation}}
#' @param by Report on violations per rule (default) or per record?
#' @param drop drop list attribute if the result has a single argument.
#' @param decreasing Sort by decreasing number of passes?
#' @param ... Arguments to be passed to or from other methods.
#' @return A \code{data.frame} with the following columns.
#' \tabular{ll}{
#'   keys \tab If confront was called with \code{key=}\cr
#'   \code{npass} \tab Number of items passed\cr
#'   \code{nfail} \tab Number of items failing\cr
#'   \code{nNA} \tab Number of items resulting in \code{NA}\cr
#'   \code{rel.pass} \tab Relative number of items passed\cr
#'   \code{rel.fail} \tab Relative number of items failing\cr
#'   \code{rel.NA} \tab Relative number of items resulting in \code{NA}
#' }
#' If \code{by='rule'} the relative numbers are computed with respect to the number 
#' of records for which the rule was evaluated. If \code{by='record'} the relative numbers
#' are computed with respect to the number of rules the record was tested agains. By default
#' the most failed validations and records with the most fails are on the top. 
#'
#' When \code{by='record'} and not all validation results have the same dimension structure,
#' a list of \code{data.frames} is returned.
#'
#' @family validation-methods
#' @aliases sort,validation-method
#' @example ../examples/aggregate.R
#' @export
setMethod('sort',signature('validation'),function(x, decreasing=FALSE, by=c('rule','record'), drop=TRUE,...){
  v <- values(x, drop=FALSE)
  by <- match.arg(by)
  aggr <- if ( by == 'rule') colSums else rowSums
  ntot <- if ( by == 'rule') nrow else ncol
  L <- lapply(v, function(y){
    s <- aggr(y,na.rm=TRUE)
    i <- order(s,decreasing=decreasing)
    s <- s[i]
    na <- aggr(is.na(y))[i]
    N <- ntot(y)
    nfail = N - s - na
    out <- data.frame( 
       npass = s
       , nfail = nfail 
       , nNA = na
       , rel.pass  = s/N
       , rel.fail  = nfail/N
       , rel.NA = na/N
      )
    if (by=="record"){
      keys <- x$._keys$keyset
      if (nrow(out)==nrow(keys)) cbind(keys[i,,drop=FALSE],out) else out
    } else {
      out
    }
    })
  if ( length(L) == 1 && drop ) L <- L[[1]]
  if ( by== 'rule' && !is.data.frame(L) ) L <- do.call(rbind,L)
  L
})

#' Coerce a confrontation object to data frame
#'
#' Results of confronting data with validation rules or indicators
#' are created by a \code{\link{confront}}ation. The result is an
#' object (inheriting from) \code{confrontation}. 
#'
#' @inheritParams as.data.frame
#'
#' @return A \code{data.frame} with columns
#' \itemize{
#'   \item{\code{key} Where relevant, and only if \code{key} was specified 
#'    in the call to \code{\link{confront}}}
#'   \item{\code{name} Name of the rule}
#'   \item{\code{value} Value after evaluation}
#'   \item{\code{expression} evaluated expression}
#' }
#'
#' @example ../examples/as.data.frame.R
#'
#' @export
#' @family confrontation-methods
setMethod("as.data.frame","confrontation", function(x,...){
  ew <- has_error(x) | has_warning(x)
  if (any(ew)){
    warning(paste(
      "Encountered warnings and/or erors in confrontation object: " 
      ,"skipped at coercion"))
    x <- x[!ew]
  }
  v <- values(x, simplify=FALSE, drop=FALSE)
  expr <- sapply(x$._calls, call2text)
  nam  <- names(x$._calls)
  
  key_proto <- lapply(x$._keys$keyset, function(x) x[0])
  nrec <- nrow(x$._keys$keyset)

  L <- lapply(seq_along(v), function(i){
    
    df <- data.frame(name=nam[i]
            , value=v[[i]]
            , expression=expr[i]
            , row.names=NULL
            , stringsAsFactors=FALSE)

    if ( nrow(df) == nrow(x$._keys$keyset) ){
      cbind(x$._keys$keyset, df)
    } else if ( length(key_proto) > 0){
      nana <- lapply(key_proto, function(d){
                as(rep(NA, length(v[[i]])) , if (inherits(d, "factor")) "character" else class(d)) 
              })
      cbind(nana, df)
    } else {
      df
    }
  })

  do.call(rbind, L)
})

#getkey <- function(x){
#  k <- names(x)
#  if (is.null(k)) NA_character_ else k
#}

#' Test if all validations resulted in TRUE
#'
#' @param x \code{validation} object (see \code{confront}).
#' @param ... ignored
#' @param na.rm [\code{logical}] If \code{TRUE}, \code{NA} values
#'    are removed before the result is computed.
#' @family validation-methods
#' @export
#'
#' @examples
#' val <- check_that(women, height>60, weight>0)
#' all(val)
setMethod("all","validation",function(x,...,na.rm=FALSE){
  res <- values(x, simplify=FALSE, drop=FALSE)
  if (length(res) == 0) return(TRUE)
  all(sapply(res, all, na.rm=na.rm), na.rm=na.rm)
})

#' Test if any validation resulted in TRUE
#'
#' @param x \code{validation} object (see \code{confront}).
#' @param ... ignored
#' @param na.rm [\code{logical}] If \code{TRUE}, \code{NA} values
#'    are removed before the result is computed.
#'
#' @family validation-methods
#' @export
#'
#' @examples
#' val <- check_that(women, height>60, weight>0)
#' any(val)
setMethod("any","validation",function(x,...,na.rm=FALSE){
  res <- values(x, simplify=FALSE, drop=FALSE)
  if (length(res) == 0) return(FALSE)
  any(sapply(res, any, na.rm=na.rm), na.rm=na.rm)
})

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validate documentation built on March 24, 2022, 5:07 p.m.