replacing plyr occurences

[suhaani-agarwal]

trying out if tests are passing with a new branch with some changes in PR#188

[suhaani-agarwal]

All the files ( mentioned in issue #165 ) with replaced plyr occurences are working now and tests are passing. @tdhock Please review and let me know if these changes are okay or anything needs change.

[tdhock]

thanks! please remove plyr from DESCRIPTION

[suhaani-agarwal]

thanks! please remove plyr from DESCRIPTION

plyr isnt present in Suggests. in DESCRIPTION it is present as an import

If i remove this, it will cause error in CRAN checks because it is also being imported in NAMESPACE . something like this. :
Namespace dependency missing from DESCRIPTION Imports/Depends entries: ‘plyr’

[tdhock]

please remove from NAMESPACE too

[suhaani-agarwal]

NAMESPACE contains plyr imports - "as.quoted" and "defaults" which are being used in almost all test files. Removing these is causing many errors.

Should all these occurrences of as.quoted and defaults be replaced?

[tdhock]

yes please

[suhaani-agarwal]

I have replaced the plyr imported functions as.quoted() and defaults() that were imported in NAMESPACE and were being used in many files in /R folder. I replaced them with functions with same functionality in utilities.r and the compiler tests are working with those functions (which were earlier failing).

The plyr occurences have been replaced in /tests folder and as.quoted() and defaults() have also been replaced in /R folder

But the CRAN tests are still giving the same error : Error: Namespace dependency missing from DESCRIPTION Imports/Depends entries: ‘plyr’

Maybe it is because of the presence of plyr being used in other files in the /R folder ?

What shall be done about these?

grep -rnw './R' -e 'plyr'
./R/plot.r:48:#' ds <- plyr::ddply(df, "gp", plyr::summarise, mean = mean(y), sd = sd(y))
./R/stat-summary.r:104:  summary <- plyr::ddply(data, c("group", "x"), summary, ...)
./R/stat-summary.r:105:  unique <- plyr::ddply(data, c("group", "x"), uniquecols)
./R/stat-summary.r:133:    plyr::rename(
./R/facet-layout.r:29:  panel <- plyr::id(base, drop = TRUE)
./R/facet-layout.r:32:  rows <- if (is.null(names(rows))) 1L else plyr::id(base[names(rows)], drop = TRUE)
./R/facet-layout.r:33:  cols <- if (is.null(names(cols))) 1L else plyr::id(base[names(cols)], drop = TRUE)
./R/facet-layout.r:51:  base <- plyr::unrowname(layout_base(data, vars, drop = drop))
./R/facet-layout.r:53:  id <- plyr::id(base, drop = TRUE)
./R/facet-layout.r:71:  panels <- cbind(layout, plyr::unrowname(base))
./R/facet-layout.r:92:  values <- compact(plyr::llply(data, quoted_df, vars = vars))
./R/facet-layout.r:96:  has_all <- unlist(plyr::llply(values, length)) == length(vars)
./R/facet-layout.r:101:  base <- unique(plyr::ldply(values[has_all]))
./R/facet-layout.r:137:  unique_values <- plyr::llply(df, ulevels)
./R/facet-layout.r:150:  plyr::unrowname(cbind(
./R/facet-layout.r:157:  values <- plyr::eval.quoted(vars, data, emptyenv(), try = TRUE)
./R/stat-summary-bin.R:52:    out <- plyr::ddply(data, "bin", fun)
./R/stat-sum.r:45:    counts <- plyr::count(data, group_by, wt_var = "weight")
./R/stat-sum.r:46:    counts <- plyr::rename(counts, c(freq = "n"), warn_missing = FALSE)
./R/geom-.r:79:    plyr::dlply(data, "PANEL", function(data) {
./R/geom-.r:109:      data <- plyr::quickdf(self$default_aes[missing_aes])
./R/coord-munch.r:63:  plyr::unrowname(data.frame(x = x, y = y, aes_df))
./R/coord-munch.r:115:  lf <- plyr::rename(lf, c(x1 = "t1", x2 = "t2", y1 = "r1", y2 = "r2",
./R/scales-.r:81:  plyr::quickdf(c(mapped, df[setdiff(names(df), names(mapped))]))
./R/scales-.r:90:  plyr::quickdf(c(transformed, df[setdiff(names(df), names(transformed))]))
./R/scales-.r:103:  datacols <- plyr::tryapply(
./R/facet-wrap.r:282:  info <- plyr::ldply(locs, find_pos, layout = layout, size = size)
./R/geom-dotplot.r:216:    data <- plyr::ddply(data, plyvars, function(xx) {
./R/geom-dotplot.r:241:      data <- plyr::ddply(data, "group", transform,
./R/layer.r:193:      include <- data.frame(plyr::eval.quoted(self$subset, data, plot$env))
./R/layer.r:251:    stat_data <- plyr::quickdf(lapply(new, eval, data, baseenv()))
./R/bench.r:19:  plyr::unrowname(data.frame(
./R/facet-labels.r:398:#' msleep$conservation2 <- plyr::revalue(msleep$conservation,
./R/facet-labels.r:508:    row_height <- function(row) max(plyr::laply(row, height_cm))
./R/facet-labels.r:514:    col_width <- function(col) max(plyr::laply(col, width_cm))
./R/geom-path.r:170:    attr <- plyr::ddply(munched, "group", function(df) {
./R/geom-path.r:287:    data <- plyr::ddply(data, "group", stairstep, direction = direction)
./R/geom-path.r:292:    g.data <- plyr::ddply(g.data, "group", function(df) stairstep(df))
./R/position-collide.r:44:    plyr::ddply(data, "xmin", strategy, width = width)
./R/position-collide.r:47:    data <- plyr::ddply(data, "xmin", strategy, width = width)
./R/fortify-map.r:86:#' seats <- plyr::ddply(ia, "subregion", plyr::colwise(mid_range, c("lat", "long")))
./R/stat-bindot.r:39:        data    <- plyr::arrange(data, x)
./R/stat-bindot.r:40:        newdata <- plyr::arrange(newdata, x)
./R/stat-bindot.r:46:        data    <- plyr::arrange(data, y)
./R/stat-bindot.r:47:        newdata <- plyr::arrange(newdata, x)
./R/stat-bindot.r:112:      data <- plyr::ddply(data, "bincenter", plyr::summarise, binwidth = binwidth[1], count = sum(weight))
./R/stat-bindot.r:166:    results <- plyr::ddply(results, "bin", function(df) {
./R/coord-polar.r:286:    plyr::rename(data, c("y" = "theta", "x" = "r"), warn_missing = FALSE)
./R/coord-polar.r:288:    plyr::rename(data, c("y" = "r", "x" = "theta"), warn_missing = FALSE)
./R/aes.r:93:  plyr::rename(x, .base_to_ggplot, warn_missing = FALSE)
./R/panel.r:69:    panel$x_scales <- plyr::rlply(max(layout$SCALE_X), x_scale$clone())
./R/panel.r:72:    panel$y_scales <- plyr::rlply(max(layout$SCALE_Y), y_scale$clone())
./R/panel.r:146:  scale_index <- plyr::split_indices(scale_id, n)
./R/geom-ribbon.r:94:    positions <- plyr::summarise(data,
./R/z_facets.R:32:  if (plyr::empty(label_df)) {
./R/z_facets.R:46:  labels_df[] <- plyr::llply(labels_df, format, justify = "none")
./R/z_facets.R:132:        layout <- plyr::join(layout, props, by = scale.type)
./R/fortify-spatial.r:17:  coords <- plyr::ldply(model@polygons,fortify)
./R/fortify-spatial.r:26:  plyr::ldply(model@polygons, fortify)
./R/fortify-spatial.r:34:  pieces <- plyr::ldply(seq_along(subpolys), function(i) {
./R/fortify-spatial.r:62:  plyr::ldply(model@lines, fortify)
./R/fortify-spatial.r:70:  pieces <- plyr::ldply(seq_along(lines), function(i) {
./R/z_animint.R:7:#' @import plyr
./R/hexbin.R:10:    plyr::round_any(min(x), binwidth, floor) - 1e-6,
./R/hexbin.R:11:    plyr::round_any(max(x), binwidth, ceiling) + 1e-6
./R/grouping.r:2:# of plyr::id() used by add_group()
./R/grouping.r:19:      data$group <- plyr::id(data[disc], drop = TRUE)
./R/grouping.r:24:    data$group <- plyr::id(data["group"], drop = TRUE)
./R/grouping.r:36:  # are different from NO_GROUP (since they are a result of plyr::id()). NA is
./R/facet-locate.r:35:    data <- plyr::unrowname(data[data_rep, , drop = FALSE])
./R/facet-locate.r:36:    facet_vals <- plyr::unrowname(cbind(
./R/facet-locate.r:49:    keys <- plyr::join.keys(facet_vals, panels, by = vars)
./R/facet-locate.r:74:    data <- plyr::unrowname(data[data_rep, , drop = FALSE])
./R/facet-locate.r:75:    facet_vals <- plyr::unrowname(cbind(
./R/facet-locate.r:80:  keys <- plyr::join.keys(facet_vals, panels, by = names(vars))
./R/geom-hex.r:91:    newdata <- plyr::ddply(g.data, "group", function(df){
./R/geom-segment.r:106:    ends <- plyr::rename(subset(data, select = c(-x, -y)), c("xend" = "x", "yend" = "y"),
./R/position-.r:61:    plyr::ddply(data, "PANEL", function(data) {
./R/stat-.r:86:    plyr::ddply(data, "PANEL", function(data) {
./R/stat-.r:114:    do.call(plyr::rbind.fill, stats)
./R/stat-bin2d.r:117:    origin <- plyr::round_any(range[1], binwidth, floor)
./R/geom-rect.r:40:      polys <- plyr::alply(data, 1, function(row) {
./R/geom-violin.r:106:    plyr::ddply(data, "group", transform,
./R/geom-violin.r:121:      plyr::arrange(transform(data, x = xminv), y),
./R/geom-violin.r:122:      plyr::arrange(transform(data, x = xmaxv), -y)
./R/geom-violin.r:161:    newdata <- plyr::ddply(g.data, "group", function(df){
./R/geom-violin.r:162:                  rbind(plyr::arrange(transform(df, x=xminv), y),
./R/geom-violin.r:163:                        plyr::arrange(transform(df, x=xmaxv), -y))
./R/geom-violin.r:165:    newdata <- plyr::ddply(newdata, "group", function(df) rbind(df, df[1,]))
./R/utilities-matrix.r:18:  do.call("unit.c", do.call("interleave.default", plyr::llply(list(...), as.list)))
./R/utilities-matrix.r:25:  lengths <- unique(setdiff(plyr::laply(vectors, length), 1))
./R/utilities-matrix.r:30:  singletons <- plyr::laply(vectors, length) == 1
./R/utilities-matrix.r:31:  vectors[singletons] <- plyr::llply(vectors[singletons], rep, lengths)
./R/aes-group-order.r:36:## #'   plyr::colwise(rescale01)(economics[, -(1:2)]))
./R/guide-legend.r:254:  guide$geoms <- plyr::llply(layers, function(layer) {
./R/facet-viewports.r:18:  grid <- plyr::ldply(names(grobs), make_grid)
./R/facet-viewports.r:19:  plyr::mlply(grid, assign_vp)
./R/facet-viewports.r:37:  do.call("vpList", plyr::mlply(pos, vp))

[tdhock]

we should classify each of these uses:

• is the feature supported in animint2? if not, remove (for example, geom_violin, stat_sum)
• if so, change plyr:: to data.table code.

however this would not actually change any user-facing functionality, so I believe it is not high priority.