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style all scopes (v2) #2

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53f7b1e
clear cases
lorenzwalthert Apr 18, 2021
65803e4
more unambiguous formatting
lorenzwalthert Apr 18, 2021
86adbd1
can't do alignment as it was before
lorenzwalthert Apr 18, 2021
0d5a223
fix alignment
lorenzwalthert Apr 18, 2021
087e17f
right align for detection
lorenzwalthert Apr 18, 2021
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7 changes: 4 additions & 3 deletions R/BenchmarkResult.R
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Original file line number Diff line number Diff line change
Expand Up @@ -268,7 +268,7 @@ BenchmarkResult = R6Class("BenchmarkResult",
tab = insert_named(tab, scores)

cns = c("uhash", "nr", "resample_result", "task_id", "learner_id", "resampling_id", "iters",
"warnings", "errors", "params", ids(measures))
"warnings", "errors", "params", ids(measures))
cns = intersect(cns, names(tab))
tab[, cns, with = FALSE]
},
Expand Down Expand Up @@ -300,10 +300,11 @@ BenchmarkResult = R6Class("BenchmarkResult",
learner_phashes = NULL

filter_if_not_null = function(column, hashes) {
if (is.null(hashes))
if (is.null(hashes)) {
fact
else
} else {
fact[unique(hashes), on = column, nomatch = NULL]
}
}


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11 changes: 8 additions & 3 deletions R/Learner.R
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Expand Up @@ -244,8 +244,9 @@ Learner = R6Class("Learner",
}

pdata = learner_predict(self, task, row_ids)
if (is.null(pdata))
if (is.null(pdata)) {
return(NULL)
}

as_prediction(check_prediction_data(pdata))
},
Expand All @@ -269,8 +270,9 @@ Learner = R6Class("Learner",
newdata = as.data.table(assert_data_frame(newdata, min.rows = 1L))

if (is.null(task)) {
if (is.null(self$state$train_task))
if (is.null(self$state$train_task)) {
stopf("No task stored, and no task provided")
}
task = self$state$train_task$clone()
} else {
task = assert_task(as_task(task, clone = TRUE))
Expand Down Expand Up @@ -414,7 +416,10 @@ Learner = R6Class("Learner",
switch(name,
.param_set = value$clone(deep = TRUE),
fallback = if (is.null(value)) NULL else value$clone(deep = TRUE),
state = { value$log = copy(value$log); value },
state = {
value$log = copy(value$log)
value
},
value
)
}
Expand Down
3 changes: 2 additions & 1 deletion R/MeasureDebug.R
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Expand Up @@ -51,8 +51,9 @@ MeasureDebug = R6Class("MeasureDebug",
private = list(
.score = function(prediction, ...) {
na_ratio = self$param_set$get_values()$na_ratio
if (na_ratio > runif(1L))
if (na_ratio > runif(1L)) {
return(NA_integer_)
}
length(prediction$row_ids)
}
)
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2 changes: 1 addition & 1 deletion R/PredictionDataClassif.R
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Expand Up @@ -90,7 +90,7 @@ c.PredictionDataClassif = function(..., keep_duplicates = TRUE) {
if (!keep_duplicates) {
keep = !duplicated(tab, by = "row_ids", fromLast = TRUE)
tab = tab[keep]
prob = prob[keep,, drop = FALSE]
prob = prob[keep, , drop = FALSE]
}

result = as.list(tab)
Expand Down
11 changes: 7 additions & 4 deletions R/ResampleResult.R
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Original file line number Diff line number Diff line change
Expand Up @@ -149,7 +149,7 @@ ResampleResult = R6Class("ResampleResult",
set(tab, j = "learner_id", value = ids(tab[["learner"]]))
set(tab, j = "resampling_id", value = ids(tab[["resampling"]]))
setcolorder(tab, c("task", "task_id", "learner", "learner_id", "resampling", "resampling_id",
"iteration", "prediction"))
"iteration", "prediction"))
}

if (conditions) {
Expand Down Expand Up @@ -224,8 +224,9 @@ ResampleResult = R6Class("ResampleResult",
task = function(rhs) {
assert_ro_binding(rhs)
tab = self$data$tasks(self$view)
if (nrow(tab) == 0L)
if (nrow(tab) == 0L) {
return(NULL)
}
tab$task[[1L]]
},

Expand All @@ -235,8 +236,9 @@ ResampleResult = R6Class("ResampleResult",
learner = function(rhs) {
assert_ro_binding(rhs)
tab = self$data$learners(self$view, states = FALSE)
if (nrow(tab) == 0L)
if (nrow(tab) == 0L) {
return(NULL)
}
tab$learner[[1L]]
},

Expand All @@ -245,8 +247,9 @@ ResampleResult = R6Class("ResampleResult",
resampling = function(rhs) {
assert_ro_binding(rhs)
tab = self$data$resamplings(self$view)
if (nrow(tab) == 0L)
if (nrow(tab) == 0L) {
return(NULL)
}
tab$resampling[[1L]]
},

Expand Down
14 changes: 8 additions & 6 deletions R/ResultData.R
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Expand Up @@ -295,18 +295,20 @@ ResultData = R6Class("ResultData",
#' Returns `NULL` if the [ResultData] is empty.
task_type = function() {
tab = self$data$tasks
if (nrow(tab))
if (nrow(tab)) {
tab$task[[1L]]$task_type
else
} else {
NULL
}
}
),

private = list(
get_view_index = function(view) {
if (is.null(view))
if (is.null(view)) {
return(TRUE)
self$data$fact[list(view), on = "uhash", nomatch = NULL, which = TRUE]
}
self$data$fact[list(view), on = "uhash", nomatch = NULL, which = TRUE]
},

deep_clone = function(name, value) {
Expand Down Expand Up @@ -382,8 +384,8 @@ reassemble_learners = function(learners, states = NULL, param_vals = NULL) {
learners = lapply(learners, function(l) l$clone(deep = TRUE))

if (!is.null(states)) {
Map(function(l, s) {
l$state = s
Map(function(l, s) {
l$state = s
}, l = learners, s = states)
}

Expand Down
4 changes: 2 additions & 2 deletions R/Task.R
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Expand Up @@ -351,8 +351,8 @@ Task = R6Class("Task",

ci = self$col_info[list(keep_cols), on = "id"]
data = do.call(data.table, Map(auto_convert,
value = as.list(data)[ci$id],
id = ci$id, type = ci$type, levels = ci$levels))
value = as.list(data)[ci$id],
id = ci$id, type = ci$type, levels = ci$levels))

data = as_data_backend(data, primary_key = pk)
} else {
Expand Down
2 changes: 1 addition & 1 deletion R/TaskClassif_penguins.R
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Expand Up @@ -35,7 +35,7 @@ load_task_penguins = function() {
penguins = as.data.table(palmerpenguins::penguins)
setnames(penguins,
old = c("bill_length_mm", "bill_depth_mm", "flipper_length_mm", "body_mass_g"),
new = c("bill_length", "bill_depth", "flipper_length", "body_mass")
new = c("bill_length", "bill_depth", "flipper_length", "body_mass")
)

b = as_data_backend(penguins)
Expand Down
6 changes: 3 additions & 3 deletions R/TaskGeneratorMoons.R
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Expand Up @@ -57,9 +57,9 @@ TaskGeneratorMoons = R6Class("TaskGeneratorMoons",
x = c(runif(n1, 0, pi), runif(n2, pi, 2 * pi))

data.table(
y = factor(rep(c("A", "B"), c(n1, n2)), levels = c("A", "B")),
x1 = 5 * cos(x) + rnorm(n, mean = mu, sd = sigma),
x2 = 10 * sin(x) + rnorm(n, mean = mu, sd = sigma)
y = factor(rep(c("A", "B"), c(n1, n2)), levels = c("A", "B")),
x1 = 5 * cos(x) + rnorm(n, mean = mu, sd = sigma),
x2 = 10 * sin(x) + rnorm(n, mean = mu, sd = sigma)
Comment on lines +60 to +62
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@lorenzwalthert This indentation looks off - is this causes because l61/62 start with numbers?

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indention or spacing after the first =? It was aligned before and styler does not allow complicated left alignment, so I made it right-aligned. We can also unalign if you want.

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Ah now I see - cos and sin were aligned before but complicated left alignment is not possible.

I think right alignment here is somehow non-standard - I think I'd prefer non-matching left alignment after =.

        x1 = 5 * cos(x) + rnorm(n, mean = mu, sd = sigma),
        x2 = 10 * sin(x) + rnorm(n, mean = mu, sd = sigma)

)
},

Expand Down
2 changes: 1 addition & 1 deletion R/TaskSupervised.R
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Expand Up @@ -19,7 +19,7 @@
#' @export
#' @examples
#' TaskSupervised$new("penguins", task_type = "classif", backend = palmerpenguins::penguins,
#' target = "species")
#' target = "species")
TaskSupervised = R6Class("TaskSupervised", inherit = Task,
public = list(

Expand Down
3 changes: 2 additions & 1 deletion R/as_prediction_data.R
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Expand Up @@ -35,8 +35,9 @@ as_prediction_data.list = function(x, task, row_ids = task$row_ids, check = TRUE
assert_names(names(x), subset.of = predict_types)

x$row_ids = row_ids
if (inherits(task, "TaskSupervised"))
if (inherits(task, "TaskSupervised")) {
x$truth = task$truth(row_ids)
}

pdata = new_prediction_data(x, task_type = task$task_type)
if (check) {
Expand Down
3 changes: 2 additions & 1 deletion R/assertions.R
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Expand Up @@ -163,8 +163,9 @@ assert_measure = function(measure, task = NULL, learner = NULL, .var.name = vnam
#' @rdname mlr_assertions
assert_measures = function(measures, task = NULL, learner = NULL, .var.name = vname(measures)) {
lapply(measures, assert_measure, task = task, learner = learner, .var.name = .var.name)
if (anyDuplicated(ids(measures)))
if (anyDuplicated(ids(measures))) {
stopf("Measures need to have unique IDs")
}
invisible(measures)
}

Expand Down
57 changes: 43 additions & 14 deletions R/auto_convert.R
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Expand Up @@ -5,21 +5,35 @@ mlr_reflections$auto_converters = ee = new.env(parent = emptyenv())

## from: logical
ee[["logical___integer"]] =
function(value, type, levels) { as.integer(value) }
function(value, type, levels) {
as.integer(value)
}
ee[["logical___numeric"]] =
function(value, type, levels) { as.double(value) }
function(value, type, levels) {
as.double(value)
}
ee[["logical___character"]] =
function(value, type, levels) { as.character(value) }
function(value, type, levels) {
as.character(value)
}
ee[["logical___factor"]] =
function(value, type, levels) { factor(value, levels = union(levels, value), ordered = FALSE) }
function(value, type, levels) {
factor(value, levels = union(levels, value), ordered = FALSE)
}
ee[["logical___ordered"]] =
function(value, type, levels) { if (all(value %in% c(NA_character_, levels))) factor(value, levels = levels, ordered = TRUE) else NULL }
function(value, type, levels) {
if (all(value %in% c(NA_character_, levels))) factor(value, levels = levels, ordered = TRUE) else NULL
}
ee[["logical___POSIXct"]] =
function(value, type, levels) { if (allMissing(value)) .POSIXct(value, tz = "") else value }
function(value, type, levels) {
if (allMissing(value)) .POSIXct(value, tz = "") else value
}

## from: integer
ee[["integer___logical"]] =
function(value, type, levels) { if (test_integerish(value, lower = 0L, upper = 1L)) as.logical(value) else value }
function(value, type, levels) {
if (test_integerish(value, lower = 0L, upper = 1L)) as.logical(value) else value
}
ee[["integer___numeric"]] =
ee[["logical___numeric"]]
ee[["integer___character"]] =
Expand All @@ -35,7 +49,9 @@ ee[["integer___POSIXct"]] =
ee[["numeric___logical"]] =
ee[["integer___logical"]]
ee[["numeric___integer"]] =
function(value, type, levels) { if (test_integerish(value)) as.integer(value) else value }
function(value, type, levels) {
if (test_integerish(value)) as.integer(value) else value
}
ee[["numeric___character"]] =
ee[["logical___character"]]
ee[["numeric___factor"]] =
Expand All @@ -47,27 +63,40 @@ ee[["numeric___POSIXct"]] =

## from: character
ee[["character___logical"]] =
function(value, type, levels) { if (all(value %in% c(NA_character_, "TRUE", "FALSE", "true", "false", "T", "F"))) as.logical(value) else value }
function(value, type, levels) {
if (all(value %in% c(NA_character_, "TRUE", "FALSE", "true", "false", "T", "F"))) as.logical(value) else value
}
ee[["character___integer"]] =
function(value, type, levels) { if (allMissing(value)) as.integer(value) else value }
function(value, type, levels) {
if (allMissing(value)) as.integer(value) else value
}
ee[["character___numeric"]] =
function(value, type, levels) { if (allMissing(value)) as.double(value) else value }
function(value, type, levels) {
if (allMissing(value)) as.double(value) else value
}
ee[["character___factor"]] =
ee[["logical___factor"]]
ee[["character___ordered"]] =
ee[["logical___ordered"]]
ee[["character___POSIXct"]] =
function(value, type, levels) { x = try(as.POSIXct(value, ""), silent = TRUE); if (inherits(x, "try-error")) value else x }
function(value, type, levels) {
x = try(as.POSIXct(value, ""), silent = TRUE)
if (inherits(x, "try-error")) value else x
}

## from: factor
ee[["factor___logical"]] =
ee[["character___logical"]]
ee[["factor___character"]] =
ee[["logical___character"]]
ee[["factor___factor"]] =
function(value, type, levels) { factor(value, levels = union(levels, levels(value)), ordered = FALSE) }
function(value, type, levels) {
factor(value, levels = union(levels, levels(value)), ordered = FALSE)
}
ee[["factor___ordered"]] =
function(value, type, levels) { if (all(levels(value) %in% levels)) factor(value, levels = levels, ordered = TRUE) else NULL }
function(value, type, levels) {
if (all(levels(value) %in% levels)) factor(value, levels = levels, ordered = TRUE) else NULL
}
ee[["factor___POSIXct"]] =
ee[["character___POSIXct"]]

Expand Down
3 changes: 1 addition & 2 deletions R/benchmark_grid.R
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Expand Up @@ -32,9 +32,8 @@
#'
#' # manual instantiation (not suited for a fair comparison of learners!)
#' Map(function(task, resampling) {
#' resampling$instantiate(task)
#' resampling$instantiate(task)
#' }, task = grid$task, resampling = grid$resampling)
#'
#' \dontrun{
#' benchmark(grid)
#' }
Expand Down
20 changes: 10 additions & 10 deletions R/bibentries.R
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Expand Up @@ -14,16 +14,16 @@ bibentries = c(
),

bischl_2012 = bibentry("article",
title = "Resampling Methods for Meta-Model Validation with Recommendations for Evolutionary Computation",
author = "Bernd Bischl and Olaf Mersmann and Heike Trautmann and Claus Weihs",
year = "2012",
month = "jun",
journal = "Evolutionary Computation",
publisher = "MIT Press - Journals",
volume = "20",
number = "2",
pages = "249--275",
doi = "10.1162/evco_a_00069"
title = "Resampling Methods for Meta-Model Validation with Recommendations for Evolutionary Computation",
author = "Bernd Bischl and Olaf Mersmann and Heike Trautmann and Claus Weihs",
year = "2012",
month = "jun",
journal = "Evolutionary Computation",
publisher = "MIT Press - Journals",
volume = "20",
number = "2",
pages = "249--275",
doi = "10.1162/evco_a_00069"
),

breiman_1984 = bibentry("book",
Expand Down
3 changes: 2 additions & 1 deletion R/default_measures.R
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Expand Up @@ -17,8 +17,9 @@
#' default_measures("classif")
#' default_measures("regr")
default_measures = function(task_type) {
if (is.null(task_type))
if (is.null(task_type)) {
return(list())
}
assert_choice(task_type, names(mlr_reflections$default_measures))
keys = mlr_reflections$default_measures[[task_type]]
mlr_measures$mget(keys)
Expand Down
6 changes: 3 additions & 3 deletions R/mlr_reflections.R
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Expand Up @@ -74,9 +74,9 @@ local({
### Task
# task types + constructors
mlr_reflections$task_types = rowwise_table(.key = "type",
~type, ~package, ~task, ~learner, ~prediction, ~measure,
"regr", "mlr3", "TaskRegr", "LearnerRegr", "PredictionRegr", "MeasureRegr",
"classif", "mlr3", "TaskClassif", "LearnerClassif", "PredictionClassif", "MeasureClassif"
~type, ~package, ~task, ~learner, ~prediction, ~measure,
"regr", "mlr3", "TaskRegr", "LearnerRegr", "PredictionRegr", "MeasureRegr",
"classif", "mlr3", "TaskClassif", "LearnerClassif", "PredictionClassif", "MeasureClassif"
Comment on lines -77 to +79
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nice! @lorenzwalthert

)

mlr_reflections$task_feature_types = c(
Expand Down
3 changes: 2 additions & 1 deletion R/mlr_resamplings.R
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Expand Up @@ -39,8 +39,9 @@ as.data.table.DictionaryResampling = function(x, ...) { # nolint
setkeyv(map_dtr(x$keys(), function(key) {
r = tryCatch(x$get(key),
missingDefaultError = function(e) NULL)
if (is.null(r))
if (is.null(r)) {
return(list(key = key))
}

list(key = key, params = list(r$param_set$ids()), iters = r$iters)
}, .fill = TRUE), "key")[]
Expand Down
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