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* cast multiple 'value.var' columns * multiple 'fun.aggregate' as well * accept undefined variables in formula * accept optional column prefixes
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@@ -17,122 +17,210 @@ dcast <- function(data, formula, fun.aggregate = NULL, ..., margins = NULL, | |
| subset = subset, fill = fill, value.var = value.var) | ||
| } | ||
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| check_formula <- function(formula, varnames, valnames) { | ||
| if (is.character(formula)) formula = as.formula(formula) | ||
| if (class(formula) != "formula" || length(formula) != 3L) | ||
| stop("Invalid formula. Cast formula should be of the form LHS ~ RHS, for e.g., a + b ~ c.") | ||
| vars = all.vars(formula) | ||
| vars = vars[!vars %chin% c(".", "...")] | ||
| allvars = c(vars, valnames) | ||
| ans = deparse_formula(as.list(formula)[-1L], varnames, allvars) | ||
| } | ||
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| deparse_formula <- function(expr, varnames, allvars) { | ||
| lvars = lapply(expr, function(this) { | ||
| if (is.call(this)) { | ||
| if (this[[1L]] == quote(`+`)) | ||
| unlist(deparse_formula(as.list(this)[-1L], varnames, allvars)) | ||
| else this | ||
| } else if (is.name(this)) { | ||
| if (this == quote(`...`)) { | ||
| subvars = setdiff(varnames, allvars) | ||
| lapply(subvars, as.name) | ||
| } else this | ||
| } | ||
| }) | ||
| lvars = lapply(lvars, function(x) if (length(x) && !is.list(x)) list(x) else x) | ||
| } | ||
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| value_vars <- function(value.var, varnames) { | ||
| if (is.character(value.var)) | ||
| value.var = list(value.var) | ||
| value.var = lapply(value.var, unique) | ||
| valnames = unique(unlist(value.var)) | ||
| iswrong = which(!valnames %in% varnames) | ||
| if (length(iswrong)) | ||
| stop("value.var values [", paste(value.var[iswrong], collapse=", "), "] are not found in 'data'.") | ||
| value.var | ||
| } | ||
|
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||
| aggregate_funs <- function(funs, vals, ...) { | ||
| if (is.call(funs) && funs[[1L]] == "eval") | ||
| funs = eval(funs[[2L]], parent.frame(2L), parent.frame(2L)) | ||
| if (is.call(funs) && as.character(funs[[1L]]) %in% c("c", "list")) | ||
| funs = lapply(as.list(funs)[-1L], function(x) { | ||
| if (is.call(x)) as.list(x)[-1L] else x | ||
| }) | ||
| else funs = list(funs) | ||
| if (length(funs) != length(vals)) { | ||
| if (length(vals) == 1L) | ||
| vals = replicate(length(funs), vals) | ||
| else stop("When 'fun.aggregate' and 'value.var' are both lists, 'value.var' must be either of length =1 or =length(fun.aggregate).") | ||
| } | ||
| dots = list(...) | ||
| construct_funs <- function(fun, val) { | ||
| if (is.name(fun)) fun = list(fun) | ||
| ans = vector("list", length(fun)*length(val)) | ||
| nms = vector("character", length(ans)) | ||
| k = 1L | ||
| for (i in fun) { | ||
| for (j in val) { | ||
| expr = list(i, as.name(j)) | ||
| if (length(dots)) | ||
| expr = c(expr, dots) | ||
| ans[[k]] = as.call(expr) | ||
| nms[k] = paste(all.names(i, max.names=1L, functions=TRUE), j, sep="_") | ||
| k = k+1L; | ||
| } | ||
| } | ||
| setattr(ans, 'names', nms) | ||
| } | ||
| ans = lapply(seq_along(funs), function(i) construct_funs(funs[[i]], vals[[i]])) | ||
| as.call(c(quote(list), unlist(ans))) | ||
| } | ||
|
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||
| dcast.data.table <- function(data, formula, fun.aggregate = NULL, ..., margins = NULL, | ||
| subset = NULL, fill = NULL, drop = TRUE, value.var = guess(data), verbose = getOption("datatable.verbose")) { | ||
| if (!is.data.table(data)) stop("'data' must be a data.table.") | ||
| if (anyDuplicated(names(data))) stop('data.table to cast must have unique column names') | ||
| drop = as.logical(drop[1]) | ||
| if (is.na(drop)) stop("'drop' must be logical TRUE/FALSE") | ||
| lvals = value_vars(value.var, names(data)) | ||
| valnames = unique(unlist(lvals)) | ||
| lvars = check_formula(formula, names(data), valnames) | ||
| lvars = lapply(lvars, function(x) if (!length(x)) quote(`.`) else x) | ||
| # tired of lapply and the way it handles environments! | ||
| allcols = c(unlist(lvars), lapply(valnames, as.name)) | ||
| dat = vector("list", length(allcols)) | ||
| for (i in seq_along(allcols)) { | ||
| x = allcols[[i]] | ||
| dat[[i]] = if (identical(x, quote(`.`))) rep(".", nrow(data)) | ||
| else eval(x, data, parent.frame()) | ||
| if (is.function(dat[[i]])) | ||
| stop("Column [", deparse(x), "] not found or of unknown type.") | ||
| } | ||
| setattr(lvars, 'names', c("lhs", "rhs")) | ||
| # Have to take care of duplicate names, and provide names for expression columns properly. | ||
| varnames = make.unique(sapply(unlist(lvars), all.vars, max.names=1L), sep="_") | ||
| dupidx = which(valnames %in% varnames) | ||
| if (length(dupidx)) { | ||
| dups = valnames[dupidx] | ||
| valnames = tail(make.unique(c(varnames, valnames)), -length(varnames)) | ||
| lvals = lapply(lvals, function(x) { x[x %in% dups] = valnames[dupidx]; x }) | ||
| } | ||
| lhsnames = head(varnames, length(lvars$lhs)) | ||
| rhsnames = tail(varnames, -length(lvars$lhs)) | ||
| setattr(dat, 'names', c(varnames, valnames)) | ||
| setDT(dat) | ||
| if (any(sapply(as.list(dat)[varnames], is.list))) { | ||
| stop("Columns specified in formula can not be of type list") | ||
| } | ||
| m <- as.list(match.call()[-1L]) | ||
| subset <- m[["subset"]][[2L]] | ||
| if (!is.null(subset)) { | ||
| if (is.name(subset)) subset = as.call(list(quote(`(`), subset)) | ||
| idx = which(eval(subset, data, parent.frame())) # any advantage thro' secondary keys? | ||
| dat = .Call(CsubsetDT, dat, idx, seq_along(dat)) | ||
| } | ||
| if (!nrow(dat) || !ncol(dat)) stop("Can not cast an empty data.table") | ||
| fun.call = m[["fun.aggregate"]] | ||
| fill.default = NULL | ||
| if (is.null(fun.call)) { | ||
| oo = forderv(dat, by=varnames, retGrp=TRUE) | ||
| if (attr(oo, 'maxgrpn') > 1L) { | ||
| message("Aggregate function missing, defaulting to 'length'") | ||
| fun.call = quote(length) | ||
| } | ||
| } | ||
| if (!is.null(fun.call)) { | ||
| fun.call = aggregate_funs(fun.call, lvals, ...) | ||
| errmsg = "Aggregating function(s) should take vector inputs and return a single value (length=1). However, function(s) returns length!=1. This value will have to be used to fill any missing combinations, and therefore must be length=1. Either override by setting the 'fill' argument explicitly or modify your function to handle this case appropriately." | ||
| if (is.null(fill)) { | ||
| tryCatch(fill.default <- dat[0][, eval(fun.call)], warning = function(x) stop(errmsg, call.=FALSE)) | ||
| if (nrow(fill.default) != 1L) stop(errmsg, call.=FALSE) | ||
| } | ||
| if (!any(valnames %chin% varnames)) { | ||
| dat = dat[, eval(fun.call), by=c(varnames)] | ||
| } else { | ||
| dat = dat[, { .SD; eval(fun.call) }, by=c(varnames), .SDcols = valnames] | ||
| } | ||
| } | ||
| order_ <- function(x) { | ||
| o = forderv(x, retGrp=TRUE, sort=TRUE) | ||
| idx = attr(o, 'starts') | ||
| if (!length(o)) o = seq_along(x) | ||
| o[idx] # subsetVector retains attributes, using R's subset for now | ||
| } | ||
| cj_uniq <- function(DT) { | ||
| do.call("CJ", lapply(DT, function(x) | ||
| if (is.factor(x)) { | ||
| xint = seq_along(levels(x)) | ||
| setattr(xint, 'levels', levels(x)) | ||
| setattr(xint, 'class', class(x)) | ||
| } else .Call(CsubsetVector, x, order_(x)) | ||
| ))} | ||
| valnames = setdiff(names(dat), varnames) | ||
| # 'dat' != 'data'? then setkey to speed things up (slightly), else ad-hoc (for now). Still very fast! | ||
| if (!is.null(fun.call) || !is.null(subset)) | ||
| setkeyv(dat, varnames) | ||
| if (length(rhsnames)) { | ||
| lhs = shallow(dat, lhsnames); rhs = shallow(dat, rhsnames); val = shallow(dat, valnames) | ||
| # handle drop=TRUE/FALSE - Update: Logic moved to R, AND faster than previous version. Take that... old me :-). | ||
| if (drop) { | ||
| map = setDT(lapply(list(lhsnames, rhsnames), function(cols) frankv(dat, cols=cols, ties.method="dense"))) | ||
| maporder = lapply(map, order_) | ||
| mapunique = lapply(seq_along(map), function(i) .Call(CsubsetVector, map[[i]], maporder[[i]])) | ||
| lhs = .Call(CsubsetDT, lhs, maporder[[1L]], seq_along(lhs)) | ||
| rhs = .Call(CsubsetDT, rhs, maporder[[2L]], seq_along(rhs)) | ||
| } else { | ||
| lhs_ = cj_uniq(lhs); rhs_ = cj_uniq(rhs) | ||
| map = vector("list", 2L) | ||
| .Call(Csetlistelt, map, 1L, lhs_[lhs, which=TRUE]) | ||
| .Call(Csetlistelt, map, 2L, rhs_[rhs, which=TRUE]) | ||
| setDT(map) | ||
| mapunique = vector("list", 2L) | ||
| .Call(Csetlistelt, mapunique, 1L, seq_len(nrow(lhs_))) | ||
| .Call(Csetlistelt, mapunique, 2L, seq_len(nrow(rhs_))) | ||
| lhs = lhs_; rhs = rhs_ | ||
| } | ||
| maplen = sapply(mapunique, length) | ||
| idx = do.call("CJ", mapunique)[map, I := .I][["I"]] # TO DO: move this to C and avoid materialising the Cross Join. | ||
| ans = .Call("Cfcast", lhs, val, maplen[[1L]], maplen[[2L]], idx, fill, fill.default, is.null(fun.call)) | ||
| allcols = do.call("paste", c(rhs, sep="_")) | ||
| if (length(valnames) > 1L) | ||
| allcols = do.call("paste", c(setcolorder(CJ(valnames, allcols, sorted=FALSE), 2:1), sep="_")) | ||
| setattr(ans, 'names', c(lhsnames, allcols)) | ||
| setDT(ans); setattr(ans, 'sorted', lhsnames) | ||
| } else { | ||
| # formula is of the form x + y ~ . (rare case) | ||
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MichaelChirico
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|
||
| if (drop) { | ||
| if (is.null(subset) && is.null(fun.call)) { | ||
| dat = copy(dat) # can't be avoided | ||
| setkeyv(dat, lhsnames) | ||
| } | ||
| ans = dat | ||
| } else { | ||
| lhs = shallow(dat, lhsnames) | ||
| val = shallow(dat, valnames) | ||
| lhs_ = cj_uniq(lhs) | ||
| idx = lhs_[lhs, I := .I][["I"]] | ||
| lhs_[, I := NULL] | ||
| ans = .Call("Cfcast", lhs_, val, nrow(lhs_), 1L, idx, fill, fill.default, is.null(fun.call)) | ||
| setDT(ans); setattr(ans, 'sorted', lhsnames) | ||
| setnames(ans, c(lhsnames, valnames)) | ||
| } | ||
| if (length(valnames) == 1L) | ||
| setnames(ans, valnames, value.var) | ||
| } | ||
| return (ans) | ||
| } | ||
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@arunsrinivasan could you elaborate on what this branch is for? It's not covered in tests and this comment seems to be spurious:
runs just fine without touching that branch (regardless of
drop)