comparison w4mclassfilter_wrapper.R @ 14:87ec0d3c2266 draft

"planemo upload for repository https://github.com/HegemanLab/w4mclassfilter_galaxy_wrapper/tree/master commit a9664e9a04e49d436ebbb643ba1755397ab759dc"

13:c18040b6e8b9

## libraries
##----------

suppressMessages(library(w4mclassfilter))

if(packageVersion("w4mclassfilter") < "0.98.12")
    stop("Please use 'w4mclassfilter' versions of 0.98.12 and above")

## constants
##----------

modNamC <- "w4mclassfilter" ## module name

}
inclusive <- as.logical(argVc["inclusive"])
classnameColumn <- as.character(argVc["classnameColumn"])
samplenameColumn <- as.character(argVc["samplenameColumn"])

order_smpl <- as.character(argVc["order_smpl"])
order_vrbl <- as.character(argVc["order_vrbl"])

variable_range_filter <- as.character(argVc["variable_range_filter"])
variable_range_filter <- strsplit(x = variable_range_filter, split = ",", fixed = TRUE)[[1]]

## -----------------------------
## Transformation and imputation
## -----------------------------
my_transformation_and_imputation <- if (transformation == "log10") {
  function(m) {
    if (!is.matrix(m))
      stop("Cannot transform and impute data - the supplied data is not in matrix form")
    if (nrow(m) == 0)
      stop("Cannot transform and impute data - data matrix has no rows")
    if (ncol(m) == 0)

    })
    return ( my_imputation_function(m) )
  }
} else if (transformation == "log2") {
  function(m) {
    if (!is.matrix(m))
      stop("Cannot transform and impute data - the supplied data is not in matrix form")
    if (nrow(m) == 0)
      stop("Cannot transform and impute data - data matrix has no rows")
    if (ncol(m) == 0)

      m[is.na(m)] <- NA
    })
    return ( my_imputation_function(m) )
  }
} else {
  # use the method from the w4mclassfilter class
  my_imputation_function
}

##------------------------------
## Computation
##------------------------------

, include               = inclusive
, class_column          = classnameColumn
, samplename_column     = samplenameColumn
, order_vrbl            = order_vrbl
, order_smpl            = order_smpl
, variable_range_filter = variable_range_filter
, failure_action        = my_print
, data_imputation       = my_transformation_and_imputation
)

14:87ec0d3c2266

## libraries
##----------

suppressMessages(library(w4mclassfilter))

expected_version <- "0.98.18"
actual_version <- packageVersion("w4mclassfilter")
if(packageVersion("w4mclassfilter") < expected_version) {
    stop(
         sprintf(
             "Unrecoverable error: Version %s of the 'w4mclassfilter' R package was loaded instead of expected version %s",
             actual_version, expected_version
         )
    )
}

## constants
##----------

modNamC <- "w4mclassfilter" ## module name

}
inclusive <- as.logical(argVc["inclusive"])
classnameColumn <- as.character(argVc["classnameColumn"])
samplenameColumn <- as.character(argVc["samplenameColumn"])

order_vrbl <- as.character(argVc["order_vrbl"])
centering <- as.character(argVc["centering"])
order_smpl <-
  if (centering == 'centroid' || centering == 'median') {
    "sampleMetadata"
  } else {
    as.character(argVc["order_smpl"])
  }

variable_range_filter <- as.character(argVc["variable_range_filter"])
variable_range_filter <- strsplit(x = variable_range_filter, split = ",", fixed = TRUE)[[1]]

## -----------------------------
## Transformation and imputation
## -----------------------------
my_transformation_and_imputation <- if (transformation == "log10") {
  function(m) {
    # convert negative intensities to missing values
    m[m < 0] <- NA
    if (!is.matrix(m))
      stop("Cannot transform and impute data - the supplied data is not in matrix form")
    if (nrow(m) == 0)
      stop("Cannot transform and impute data - data matrix has no rows")
    if (ncol(m) == 0)

    })
    return ( my_imputation_function(m) )
  }
} else if (transformation == "log2") {
  function(m) {
    # convert negative intensities to missing values
    m[m < 0] <- NA
    if (!is.matrix(m))
      stop("Cannot transform and impute data - the supplied data is not in matrix form")
    if (nrow(m) == 0)
      stop("Cannot transform and impute data - data matrix has no rows")
    if (ncol(m) == 0)

      m[is.na(m)] <- NA
    })
    return ( my_imputation_function(m) )
  }
} else {
  function(m) {
    # convert negative intensities to missing values
    m[m < 0] <- NA
    if (!is.matrix(m))
      stop("Cannot transform and impute data - the supplied data is not in matrix form")
    if (nrow(m) == 0)
      stop("Cannot transform and impute data - data matrix has no rows")
    if (ncol(m) == 0)
      stop("Cannot transform and impute data - data matrix has no columns")
    suppressWarnings({
      # suppress warnings here since non-positive values will produce NaN's that will be fixed in the next step
      m[is.na(m)] <- NA
    })
    return ( my_imputation_function(m) )
  }
}

##------------------------------
## Computation
##------------------------------

, include               = inclusive
, class_column          = classnameColumn
, samplename_column     = samplenameColumn
, order_vrbl            = order_vrbl
, order_smpl            = order_smpl
, centering             = centering
, variable_range_filter = variable_range_filter
, failure_action        = my_print
, data_imputation       = my_transformation_and_imputation
)