## Copyright 2013, 2014, 2015, 2016 Ramon Diaz-Uriarte
## This program is free software: you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation, either version 3 of the License, or
## (at your option) any later version.
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
## You should have received a copy of the GNU General Public License
## along with this program. If not, see <http://www.gnu.org/licenses/>.
## Functions that allow passing a matrix or data frame of mappings
## genotype -> fitness so this is taken as input in fitnessEffects.
## and some related functions
to_Magellan <- function(x, file,
max_num_genotypes = 2000) {
## Go directly if you have, as entry, an object from
## rfitness!! to_Fitness_Matrix can be very slow.
## But often, when we use allFitnessEffects, we
## obtain the fitness landscape as genotype_fitness_matrix
## FIXME: we could use that fact here.
## or maybe in to_Fitness_Matrix
if(is.null(file)) {
file <- tempfile()
cat("\n Using file ", file, "\n")
}
if(inherits(x, "genotype_fitness_matrix")) {
write(rep(2, ncol(x) - 1), file = file, ncolumns = ncol(x) - 1)
write.table(x, file = file, append = TRUE,
row.names = FALSE, col.names = FALSE, sep = " ")
} else {
gfm <- to_Fitness_Matrix(x, max_num_genotypes = max_num_genotypes)$gfm
write(rep(2, ncol(gfm) - 1), file = file, ncolumns = ncol(gfm) - 1)
write.table(gfm, file = file, append = TRUE,
row.names = FALSE, col.names = FALSE, sep = " ")
}
}
## ## genotype_fitness_matrix -> fitness landscape as data frame
## fmatrix_to_afe <- function(x) {
## stopifnot(inherits(x, "genotype_fitness_matrix"))
## y <- x[, -ncol(x)]
## nn <- apply(y, 1,
## function(u) paste(sort(colnames(y)[as.logical(u)]),
## collapse = ", "))
## nn[nn == ""] <- "WT"
## return(data.frame(Genotype = nn, Fitness = x[, ncol(x)],
## stringsAsFactors = FALSE))
## }
to_Fitness_Matrix <- function(x, max_num_genotypes) {
## A general converter. Ready to be used by plotFitnessLandscape and
## Magellan exporter.
## FIXME: really, some of this is inefficient. Very. Fix it.
if( (inherits(x, "genotype_fitness_matrix")) ||
( (is.matrix(x) || is.data.frame(x)) && (ncol(x) > 2) ) ) {
## Why this? We go back and forth twice. We need both things. We
## could construct the afe below by appropriately pasting the
## columns names
## if( (is.null(colnames(x))) || any(grepl("^$", colnames(x))))
## stop("Matrix x must have column names")
## This could use fmatrix_to_afe, above!!!
## Major change as of flfast: no longer using from_genotype_fitness
afe <- evalAllGenotypes(allFitnessEffects(
genotFitness = x
##, epistasis = from_genotype_fitness(x)
),
order = FALSE, addwt = TRUE, max = max_num_genotypes)
## Might not be needed with the proper gfm object (so gmf <- x)
## but is needed if arbitrary matrices.
gfm <- allGenotypes_to_matrix(afe)
} else if(inherits(x, "fitnessEffects")) {
if(!is.null(x$orderEffects) )
stop("We cannot yet deal with order effects")
afe <- evalAllGenotypes(x,
order = FALSE,
addwt = TRUE, max = max_num_genotypes)
gfm <- allGenotypes_to_matrix(afe)
} else if( (inherits(x, "evalAllGenotypes")) ||
(inherits(x, "evalAllGenotypesMut"))) {
if(any(grepl(">", x[, 1], fixed = TRUE)))
stop("We cannot deal with order effects yet.")
x <- x[, c(1, 2)]
if(x[1, "Genotype"] != "WT") {
## Yes, because we expect this present below
x <- rbind(data.frame(Genotype = "WT",
Fitness = 1,
stringsAsFactors = FALSE),
x)
}
afe <- x
## in case we pass an evalAllgenotypesfitandmut
gfm <- allGenotypes_to_matrix(afe)
} else if(is.data.frame(x)) {
## Assume a two-column data frame of genotypes as character
## vectors and fitness
if(colnames(x)[2] != "Fitness")
stop("We cannot guess what you are passing here")
afe <- evalAllGenotypes(allFitnessEffects(genotFitness = x),
order = FALSE, addwt = TRUE,
max = max_num_genotypes)
gfm <- allGenotypes_to_matrix(afe)
} else {
stop("We cannot guess what you are passing here")
}
return(list(gfm = gfm, afe = afe))
}
## Based on from_genotype_fitness
## but if we are passed a fitness landscapes as produced by
## rfitness, do nothing. Well, it actually does something.
##Modified
to_genotFitness_std <- function(x,
frequencyDependentFitness = FALSE,
frequencyType = frequencyType,
simplify = TRUE,
min_filter_fitness = 1e-9,
sort_gene_names = TRUE) {
## Would break with output from allFitnessEffects and
## output from allGenotypeAndMut
## For the very special and weird case of
## a matrix but only a single gene so with a 0 and 1
## No, this is a silly and meaningless case.
## if( ( ncol(x) == 2 ) && (nrow(x) == 1) && (x[1, 1] == 1) ) {
## } else blabla:
## if((ncol(x) > 2) && !(inherits(x, "matrix"))
## stop(paste0("Genotype fitness input either two-column data frame",
## " or a numeric matrix with > 2 columns."))
## if( (ncol(x) > 2) && (nrow(x) == 1) )
## stop(paste0("It looks like you have a matrix for a single genotype",
## " of a single gene. For this degenerate cases use",
## " a data frame specification."))
if(! (inherits(x, "matrix") || inherits(x, "data.frame")) )
stop("Input must inherit from matrix or data.frame.")
if(ncol(x) > 2) {
if (!frequencyDependentFitness){
if(inherits(x, "matrix")) {
if(!is.numeric(x))
stop("A genotype fitness matrix/data.frame must be numeric.")
} else if(inherits(x, "data.frame")) {
if(!all(unlist(lapply(x, is.numeric))))
stop("A genotype fitness matrix/data.frame must be numeric.")
}
}else{
if(!inherits(x, "data.frame"))
stop("Input must inherit from data.frame.")
if(ncol(x) == 0){
stop("You have an empty data.frame")
}
if(!all(unlist(lapply(x[,-ncol(x)], is.numeric)))){
stop("All columns except last one must be numeric.")
}
if(is.factor(x[, ncol(x)])) {
warning("Last column of genotype fitness is a factor. ",
"Converting to character.")
x[, ncol(x)] <- as.character(x[, ncol(x)])
}
if(!all(unlist(lapply(x[, ncol(x)], is.character)))){
stop("All elements in last column must be character.")
}
}
## We are expecting here a matrix of 0/1 where columns are genes
## except for the last column, that is Fitness
## Of course, can ONLY work with epistastis, NOT order
## return(genot_fitness_to_epistasis(x))
if(any(duplicated(colnames(x))))
stop("duplicated column names")
cnfl <- which(colnames(x)[-ncol(x)] == "")
if(length(cnfl)) {
freeletter <- setdiff(LETTERS, colnames(x))[1]
if(length(freeletter) == 0) stop("Renaiming failed")
warning("One column named ''. Renaming to ", freeletter)
colnames(x)[cnfl] <- freeletter
}
if(!is.null(colnames(x)) && sort_gene_names) {
ncx <- ncol(x)
cnx <- colnames(x)[-ncx]
ocnx <- gtools::mixedorder(cnx)
if(!(identical(cnx[ocnx], cnx))) {
message("Sorting gene column names alphabetically")
x <- cbind(x[, ocnx, drop = FALSE], Fitness = x[, (ncx)])
}
}
if(is.null(colnames(x))) {
ncx <- (ncol(x) - 1)
message("No column names: assigning gene names from LETTERS")
if(ncx > length(LETTERS))
stop("More genes than LETTERS; please give gene names",
" as you see fit.")
colnames(x) <- c(LETTERS[1:ncx], "Fitness")
}
if(!all(as.matrix(x[, -ncol(x)]) %in% c(0, 1) ))
stop("First ncol - 1 entries not in {0, 1}.")
} else {
if(!inherits(x, "data.frame"))
stop("genotFitness: if two-column must be data frame")
if(ncol(x) == 0){
stop("You have an empty data.frame")
}
## Make sure no factors
if(is.factor(x[, 1])) {
warning("First column of genotype fitness is a factor. ",
"Converting to character.")
x[, 1] <- as.character(x[, 1])
}
## Make sure no numbers
if(any(is.numeric(x[, 1])))
stop(paste0("genotFitness: first column of data frame is numeric.",
" Ambiguous and suggests possible error. If sure,",
" enter that column as character"))
omarker <- any(grepl(">", x[, 1], fixed = TRUE))
emarker <- any(grepl(",", x[, 1], fixed = TRUE))
nogoodepi <- any(grepl(":", x[, 1], fixed = TRUE))
## if(omarker && emarker) stop("Specify only epistasis or order, not both.")
if(nogoodepi && emarker) stop("Specify the genotypes separated by a ',', not ':'.")
if(nogoodepi && !emarker) stop("Specify the genotypes separated by a ',', not ':'.")
## if(nogoodepi && omarker) stop("If you want order, use '>' and if epistasis ','.")
## if(!omarker && !emarker) stop("You specified neither epistasis nor order")
if(omarker) {
## do something. To be completed
stop("This code not yet ready")
## You can pass to allFitnessEffects genotype -> fitness mappings that
## involve epistasis and order. But they must have different
## genes. Otherwise, it is not manageable.
}
if( emarker || ( (!omarker) && (!emarker) && (!nogoodepi)) ) {
## the second case above corresponds to passing just single letter genotypes
## as there is not a single marker
x <- x[, c(1, 2), drop = FALSE]
if(!all(colnames(x) == c("Genotype", "Fitness"))) {
message("Column names of object not Genotype and Fitness.",
" Renaming them assuming that is what you wanted")
colnames(x) <- c("Genotype", "Fitness")
}
if((!omarker) && (!emarker) && (!nogoodepi)) {
message("All single-gene genotypes as input to to_genotFitness_std")
}
## Yes, we need to do this to scale the fitness and put the "-"
if(frequencyDependentFitness){
anywt <- which(x[, 1] == "WT")
if (length(anywt) > 1){
stop("WT should not appear more than once in fitness specification")
## stop("WT must appear once.")
}
## if(length(anywt) == 0) {
## x <- rbind(data.frame(Genotype = "WT", Fitness = "0"),
## x)
## }
if(is.factor(x[, ncol(x)])) {
warning("Second column of genotype fitness is a factor. ",
"Converting to character.")
x[, ncol(x)] <- as.character(x[, ncol(x)])
}
}
x <- allGenotypes_to_matrix(x, frequencyDependentFitness)
}
}
## And, yes, scale all fitnesses by that of the WT
if (!frequencyDependentFitness){
whichroot <- which(rowSums(x[, -ncol(x), drop = FALSE]) == 0)
if(length(whichroot) == 0) {
warning("No wildtype in the fitness landscape!!! Adding it with fitness 1.")
x <- rbind(c(rep(0, ncol(x) - 1), 1), x)
} else if(x[whichroot, ncol(x)] != 1) {
warning("Fitness of wildtype != 1.",
" Dividing all fitnesses by fitness of wildtype.")
vwt <- x[whichroot, ncol(x)]
x[, ncol(x)] <- x[, ncol(x)]/vwt
}
}
if(any(is.na(x)))
stop("NAs in fitness matrix")
if(!frequencyDependentFitness) {
if(is.data.frame(x))
x <- as.matrix(x)
stopifnot(inherits(x, "matrix"))
if(simplify) {
x <- x[x[, ncol(x)] > min_filter_fitness, , drop = FALSE]
}
class(x) <- c("matrix", "genotype_fitness_matrix")
} else { ## frequency-dependent fitness
## RDU: what is this for? It converts to numbers.
## But it does not work reliably. It does not work when given as "n_"
## We will do this at end. in full_FDF_spec
## conversionTable_o <- conversionTable(ncol(x) - 1, frequencyType)
## x[, ncol(x)] <- sapply(x[, ncol(x)],
## function(x){ findAndReplace(x, conversionTable_o)})
if(frequencyType == "auto"){
ch <- paste(as.character(x[, ncol(x)]), collapse = "")
if( grepl("f_", ch, fixed = TRUE) ){
frequencyType = "rel"
pattern <- stringr::regex("f_(\\d*_*)*")
} else if ( grepl("n_", ch, fixed = TRUE) ){
frequencyType = "abs"
pattern <- stringr::regex("n_(\\d*_*)*")
} else { stop("No pattern found when frequencyType set to 'auto'") }
} else if(frequencyType == "abs"){
pattern <- stringr::regex("n_(\\d*_*)*")
} else {
pattern <- stringr::regex("f_(\\d*_*)*")
}
regularExpressionVector <-
unique(unlist(lapply(x[, ncol(x)],
function(z) {stringr::str_extract_all(string = z,
pattern = pattern)})))
if((!all(regularExpressionVector %in% fVariablesN(ncol(x) - 1, frequencyType))) |
!(length(intersect(regularExpressionVector,
fVariablesN(ncol(x) - 1, frequencyType)) >= 1) )){
stop("There are some errors in fitness column")
}
}
return(x)
}
## Deprecated after flfast
## to_genotFitness_std is faster and has better error checking
## and is very similar and does not use
## the genot_fitness_to_epistasis, which is not reasonable anymore.
## from_genotype_fitness <- function(x) {
## ## Would break with output from allFitnessEffects and
## ## output from allGenotypeAndMut
## ## For the very special and weird case of
## ## a matrix but only a single gene so with a 0 and 1
## ## No, this is a silly and meaningless case.
## ## if( ( ncol(x) == 2 ) && (nrow(x) == 1) && (x[1, 1] == 1) ) {
## ## } else blabla:
## if(! (inherits(x, "matrix") || inherits(x, "data.frame")) )
## stop("Input must inherit from matrix or data.frame.")
## ## if((ncol(x) > 2) && !(inherits(x, "matrix"))
## ## stop(paste0("Genotype fitness input either two-column data frame",
## ## " or a numeric matrix with > 2 columns."))
## ## if( (ncol(x) > 2) && (nrow(x) == 1) )
## ## stop(paste0("It looks like you have a matrix for a single genotype",
## ## " of a single gene. For this degenerate cases use",
## ## " a data frame specification."))
## if(ncol(x) > 2) {
## if(inherits(x, "matrix")) {
## if(!is.numeric(x))
## stop("A genotype fitness matrix/data.frame must be numeric.")
## } else if(inherits(x, "data.frame")) {
## if(!all(unlist(lapply(x, is.numeric))))
## stop("A genotype fitness matrix/data.frame must be numeric.")
## }
## ## We are expecting here a matrix of 0/1 where columns are genes
## ## except for the last column, that is Fitness
## ## Of course, can ONLY work with epistastis, NOT order
## return(genot_fitness_to_epistasis(x))
## } else {
## if(!inherits(x, "data.frame"))
## stop("genotFitness: if two-column must be data frame")
## ## Make sure no factors
## if(is.factor(x[, 1])) x[, 1] <- as.character(x[, 1])
## ## Make sure no numbers
## if(any(is.numeric(x[, 1])))
## stop(paste0("genotFitness: first column of data frame is numeric.",
## " Ambiguous and suggests possible error. If sure,",
## " enter that column as character"))
## omarker <- any(grepl(">", x[, 1], fixed = TRUE))
## emarker <- any(grepl(",", x[, 1], fixed = TRUE))
## nogoodepi <- any(grepl(":", x[, 1], fixed = TRUE))
## ## if(omarker && emarker) stop("Specify only epistasis or order, not both.")
## if(nogoodepi && emarker) stop("Specify the genotypes separated by a ',', not ':'.")
## if(nogoodepi && !emarker) stop("Specify the genotypes separated by a ',', not ':'.")
## ## if(nogoodepi && omarker) stop("If you want order, use '>' and if epistasis ','.")
## ## if(!omarker && !emarker) stop("You specified neither epistasis nor order")
## if(omarker) {
## ## do something. To be completed
## stop("This code not yet ready")
## ## You can pass to allFitnessEffects genotype -> fitness mappings that
## ## involve epistasis and order. But they must have different
## ## genes. Otherwise, it is not manageable.
## }
## if( emarker || ( (!omarker) && (!emarker) && (!nogoodepi)) ) {
## ## the second case above corresponds to passing just single letter genotypes
## ## as there is not a single marker
## x <- x[, c(1, 2), drop = FALSE]
## if(!all(colnames(x) == c("Genotype", "Fitness"))) {
## message("Column names of object not Genotype and Fitness.",
## " Renaming them assuming that is what you wanted")
## colnames(x) <- c("Genotype", "Fitness")
## }
## if((!omarker) && (!emarker) && (!nogoodepi)) {
## message("All single-gene genotypes as input to from_genotype_fitness")
## }
## ## Yes, we need to do this to scale the fitness and put the "-"
## return(genot_fitness_to_epistasis(allGenotypes_to_matrix(x)))
## }
## }
## }
## No longer used for real
genot_fitness_to_epistasis <- function(x) {
## FIXME future:
## - Nope, order cannot be dealt with here. Not a matrix of 0 and 1.
## - modify "fitnessEffects" so we can take a component that is
## - "genot_fitness"; so this would never be exposed to the user
## Why we should not combine this specification with other terms? If
## you use this is because you say "this is the mapping genotype ->
## fitness. Period." so we should not combine other terms (or other
## terms that involve these genes)
nr <- nrow(x)
if(nr < (2^(ncol(x) - 1)))
message("Number of genotypes less than 2^L.",
" Missing genotype will be set to 1")
## This is specific if only epistasis, not order
if(nr > (2^(ncol(x) - 1)))
stop("Number of genotypes > 2^L. Repeated entries?")
f <- x[, ncol(x)]
## Why should I stop?
if(any(f < 0))
message("Negative fitnesses. Watch out if you divide by the wildtype")
x <- x[, -ncol(x), drop = FALSE]
wt <- which(rowSums(x) == 0)
fwt <- 1
if(length(wt) == 1)
fwt <- f[wt]
## No longer being used when we pass fitness landscapse: flfast
if(!isTRUE(all.equal(fwt, 1))) {
message("Fitness of wildtype != 1. ",
"Dividing all fitnesses by fitness of wildtype.")
f <- f/fwt
}
if(is.null(colnames(x)) || any(grepl("^$", colnames(x))) ) {
message("Setting/resetting gene names because one or more are missing.",
" If this is not what you want, pass a matrix",
" with all columns named.")
if(ncol(x) <= 26)
colnames(x) <- LETTERS[1:ncol(x)]
else
colnames(x) <- paste0("G", seq.int(ncol(x)))
}
cn <- colnames(x)
x2 <- matrix("", nrow = nrow(x), ncol = ncol(x))
x2[x == 0] <- "-"
epin <- apply(x2, 1, function(z) paste(paste0(z, cn), collapse = ":"))
if(anyDuplicated(epin))
stop("Non unique names")
s <- f - 1
names(s) <- epin
return(s)
}
allGenotypes_to_matrix <- function(x,
frequencyDependentFitness = FALSE) {
## Makes no sense to allow passing order: the matrix would have
## repeated rows. A > B and B > A both have exactly A and B
## Take output of evalAllGenotypes or identical data frame and return
## a matrix with 0/1 in a column for each gene and a final column of
## Fitness
if (is.factor(x[, 1])) {
warning(
"First column of genotype fitness is a factor. ",
"Converting to character."
)
x[, 1] <- as.character(x[, 1])
}
if (frequencyDependentFitness) {
if (is.factor(x[, ncol(x)])) {
warning(
"Second column of genotype fitness is a factor. ",
"Converting to character."
)
x[, ncol(x)] <- as.character(x[, ncol(x)])
}
}
## A WT can be specified with string "WT"
anywt <- which(x[, 1] == "WT")
if (length(anywt) > 1) stop("More than 1 WT")
if (length(anywt) == 1) {
fwt <- x[anywt, 2]
x <- x[-anywt, ]
## Trivial case of passing just a WT?
} else {
if (!frequencyDependentFitness) {
warning("No WT genotype. Setting its fitness to 1.")
fwt <- 1
} else {
fwt <- NA
## message("No WT genotype in FDF: setting it to 0.")
}
}
splitted_genots <- lapply(
x$Genotype,
function(z) nice.vector.eo(z, ",")
)
all_genes <- sort(unique(unlist(splitted_genots)))
m <- matrix(0, nrow = length(splitted_genots), ncol = length(all_genes))
the_match <- lapply(
splitted_genots,
function(z) match(z, all_genes)
)
## A lot simpler with a loop
for (i in 1:nrow(m)) {
m[i, the_match[[i]]] <- 1
}
m <- cbind(m, x[, 2])
colnames(m) <- c(all_genes, "Fitness")
if(!is.na(fwt))
m <- rbind(c(rep(0, length(all_genes)), fwt), m)
if (frequencyDependentFitness) {
m <- as.data.frame(m)
m[, 1:length(all_genes)] <- apply(
m[, 1:length(all_genes)],
2,
as.numeric
)
m[, ncol(m)] <- as.character(m[, ncol(m)])
}
## Ensure sorted
## m <- data.frame(m)
rs <- rowSums(m[, -ncol(m), drop = FALSE])
m <- m[order(rs), , drop = FALSE]
## m <- m[do.call(order, as.list(cbind(rs, m[, -ncol(m)]))), ]
return(m)
}
Magellan_stats <- function(x, max_num_genotypes = 2000,
verbose = FALSE,
use_log = FALSE,
short = TRUE,
replace_missing = FALSE) {
## I always use
## if(!is.null(x) && is.null(file))
## stop("one of object or file name")
## if(is.null(file))
fn <- tempfile()
fnret <- tempfile()
if(verbose)
cat("\n Using input file", fn, " and output file ", fnret, "\n")
if(use_log) {
logarg <- "-l"
} else {
logarg <- NULL
}
if(short) {
shortarg <- "-s"
} else {
shortarg <- NULL
}
if(replace_missing) {
zarg <- "-z"
} else {
zarg <- NULL
}
to_Magellan(x, fn, max_num_genotypes = max_num_genotypes)
## newer versions of Magellan provide some extra values to standard output
call_M <- system2(fl_statistics_binary(),
args = paste(shortarg, logarg, zarg, "-o", fnret, fn),
stdout = NULL)
if(short) {
## tmp <- as.vector(read.table(fnret, skip = 1, header = TRUE)[-1])
tmp <- unlist(read.table(fnret, skip = 1, header = TRUE)[c(-1)])
## ## Make names more explicit, but check we have what we think we have
## ## New versions of Magellan produce different output apparently of variable length
## stopifnot(length(tmp) >= 23) ## 23) ## variable length
## stopifnot(identical(names(tmp)[1:13], ## only some
## c("ngeno", "npeaks", "nsinks", "gamma", "gamma.", "r.s",
## "nchains", "nsteps", "nori", "depth", "magn", "sign",
## "rsign"))) ## , "w.1.", "w.2.", "w.3..", "mode_w", "s.1.",
## ## "s.2.", "s.3..", "mode_s", "pairs_s", "outD_v")))
## if(length(tmp) >= 24) ## the new version
## stopifnot(identical(names(tmp)[c(20, 24)],
## c("steps_m", "mProbOpt_0")))
## ## steps_m: the mean number of steps over the entire landscape to
## ## reach the global optimum
## ## mProbOpt_0: The mean probability to
## ## reach that optimum (again averaged over the entire landscape).
## ## but if there are multiple optima, there are many of these
## names(tmp)[1:13] <- c("n_genotypes", "n_peaks", "n_sinks", "gamma", "gamma_star",
## "r/s","n_chains", "n_steps", "n_origins", "max_depth",
## "epist_magn", "epist_sign", "epist_rsign")## ,
## ## "walsh_coef_1", "walsh_coef_2", "walsh_coef_3", "mode_walsh",
## ## "synerg_coef_1", "synerg_coef_2", "synerg_coef_3", "mode_synerg",
## ## "std_dev_pairs", "var_outdegree")
} else {
message("Output file: ", fnret)
tmp <- readLines(fnret)
}
return(tmp)
}
## Former version, that always tries to give a vector
## and that uses an external executable.
## Magellan_stats and Magellan_draw cannot be tested
## routinely, as they depend on external software
Magellan_stats_former <- function(x, max_num_genotypes = 2000,
verbose = FALSE,
use_log = TRUE,
short = TRUE,
fl_statistics = "fl_statistics",
replace_missing = FALSE) { # nocov start
## I always use
## if(!is.null(x) && is.null(file))
## stop("one of object or file name")
## if(is.null(file))
fn <- tempfile()
fnret <- tempfile()
if(verbose)
cat("\n Using input file", fn, " and output file ", fnret, "\n")
if(use_log) {
logarg <- "-l"
} else {
logarg <- NULL
}
if(short) {
shortarg <- "-s"
} else {
shortarg <- NULL
}
if(replace_missing) {
zarg <- "-z"
} else {
zarg <- NULL
}
to_Magellan(x, fn, max_num_genotypes = max_num_genotypes)
## newer versions of Magellan provide some extra values to standard output
call_M <- system2(fl_statistics,
args = paste(fn, shortarg, logarg, zarg, "-o", fnret),
stdout = NULL)
if(short) {
## tmp <- as.vector(read.table(fnret, skip = 1, header = TRUE)[-1])
tmp <- as.vector(read.table(fnret, skip = 1, header = TRUE)[c(-1)])
## Make names more explicit, but check we have what we think we have
## New versions of Magellan produce different output apparently of variable length
stopifnot(length(tmp) >= 23) ## 23) ## variable length
stopifnot(identical(names(tmp)[1:13], ## only some
c("ngeno", "npeaks", "nsinks", "gamma", "gamma.", "r.s",
"nchains", "nsteps", "nori", "depth", "magn", "sign",
"rsign"))) ## , "w.1.", "w.2.", "w.3..", "mode_w", "s.1.",
## "s.2.", "s.3..", "mode_s", "pairs_s", "outD_v")))
if(length(tmp) >= 24) ## the new version
stopifnot(identical(names(tmp)[c(20, 24)],
c("steps_m", "mProbOpt_0")))
## steps_m: the mean number of steps over the entire landscape to
## reach the global optimum
## mProbOpt_0: The mean probability to
## reach that optimum (again averaged over the entire landscape).
## but if there are multiple optima, there are many of these
names(tmp)[1:13] <- c("n_genotypes", "n_peaks", "n_sinks", "gamma", "gamma_star",
"r/s","n_chains", "n_steps", "n_origins", "max_depth",
"epist_magn", "epist_sign", "epist_rsign")## ,
## "walsh_coef_1", "walsh_coef_2", "walsh_coef_3", "mode_walsh",
## "synerg_coef_1", "synerg_coef_2", "synerg_coef_3", "mode_synerg",
## "std_dev_pairs", "var_outdegree")
} else {
tmp <- readLines(fnret)
}
return(tmp)
} # nocov end
Magellan_draw <- function(x, max_num_genotypes = 2000,
verbose = FALSE,
args = "-f",
fl_draw = "fl_draw",
svg_open = "xdg-open",
file_name = NULL) { # nocov start
## It always works by appending the name so file_name is without the .svg
if(is.null(file_name)) {
fn <- tempfile()
} else {
fn <- file_name
}
fn_out <- paste0(fn, ".svg")
if(verbose)
cat("\n Using input file", fn, " and output file ", fn_out, "\n")
to_Magellan(x, fn, max_num_genotypes = max_num_genotypes)
call_M <- system2(fl_draw, args = paste(fn, args), wait = FALSE)
call_view <- system2(svg_open, args = fn_out, wait = FALSE,
stdout = ifelse(verbose, "", FALSE),
stderr = ifelse(verbose, "", FALSE))
invisible()
} # nocov end
## ## Example of Bozic issues in conversions of fitnes
## m1 <- cbind(c(0, 1), c(1, 0), c(2, 3))
## m2 <- cbind(c(1, 1), c(1, 0), c(2, 3))
## m3 <- data.frame(G = c("A, B", "A"), F = c(1, 2))
## m4 <- data.frame(G = c("A, B", "A", "WT", "B"), F = c(3, 2, 1, 4))
## m5 <- data.frame(G = c("A, B", "A", "WT", "B"), F = c(3, 2, 1, 0))
## m6 <- data.frame(G = c("A, B", "A", "WT", "B"), F = c(3, 2.5, 2, 0))
## And no, it makes no sense to use any of this for mutator: in mutator I
## directly have the multiplication factor of each gene. Which is likely
## what people want anyway. Add it later if needed by using a ratio
## instead of a "-"
