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Merge pull request #367 from jemus42/fix-collate-order
Fix Collate: order by splitting zzz.R
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,115 @@ | ||
| # These elements need to be at the top of the Collate: order! | ||
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| mlr3proba_learners = new.env() | ||
| mlr3proba_tasks = new.env() | ||
| mlr3proba_measures = new.env() | ||
| mlr3proba_task_gens = new.env() | ||
| mlr3proba_pipeops = new.env() | ||
| mlr3proba_graphs = new.env() | ||
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| register_learner = function(name, constructor) { | ||
| assert_class(constructor, "R6ClassGenerator") | ||
| if (name %in% names(mlr3proba_learners)) stopf("learner %s registered twice", name) | ||
| mlr3proba_learners[[name]] = constructor | ||
| } | ||
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| register_task = function(name, constructor) { | ||
| if (name %in% names(mlr3proba_tasks)) stopf("task %s registered twice", name) | ||
| mlr3proba_tasks[[name]] = constructor | ||
| } | ||
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| register_measure = function(name, constructor) { | ||
| if (name %in% names(mlr3proba_measures)) stopf("measure %s registered twice", name) | ||
| mlr3proba_measures[[name]] = constructor | ||
| } | ||
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| register_task_generator = function(name, constructor) { | ||
| if (name %in% names(mlr3proba_task_gens)) stopf("task generator %s registered twice", name) | ||
| mlr3proba_task_gens[[name]] = constructor | ||
| } | ||
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| register_pipeop = function(name, constructor) { | ||
| if (name %in% names(mlr3proba_pipeops)) stopf("pipeop %s registered twice", name) | ||
| mlr3proba_pipeops[[name]] = constructor | ||
| } | ||
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| register_graph = function(name, constructor) { | ||
| if (name %in% names(mlr3proba_graphs)) stopf("graph %s registered twice", name) | ||
| mlr3proba_graphs[[name]] = constructor | ||
| } | ||
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| register_reflections = function() { | ||
| x = utils::getFromNamespace("mlr_reflections", ns = "mlr3") | ||
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| # task | ||
| x$task_types = x$task_types[!c("surv", "dens")] | ||
| x$task_types = setkeyv(rbind(x$task_types, rowwise_table( | ||
| ~type, ~package, ~task, ~learner, ~prediction, ~prediction_data, ~measure, | ||
| "surv", "mlr3proba", "TaskSurv", "LearnerSurv", "PredictionSurv", "PredictionDataSurv", "MeasureSurv", | ||
| "dens", "mlr3proba", "TaskDens", "LearnerDens", "PredictionDens", "PredictionDataDens", "MeasureDens" | ||
| )), "type") | ||
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| x$task_col_roles$surv = x$task_col_roles$regr | ||
| x$task_col_roles$dens = c("feature", "target", "label", "order", "group", "weight", "stratum") | ||
| x$task_properties$surv = x$task_properties$regr | ||
| x$task_properties$dens = x$task_properties$regr | ||
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| # learner | ||
| x$learner_properties$surv = x$learner_properties$regr | ||
| x$learner_properties$dens = x$learner_properties$regr | ||
| x$learner_predict_types$surv = list( | ||
| crank = c("crank", "lp", "distr", "response"), | ||
| distr = c("crank", "lp", "distr", "response"), | ||
| lp = c("crank", "lp", "distr", "response"), | ||
| response = c("crank", "lp", "distr", "response") | ||
| ) | ||
| x$learner_predict_types$dens = list( | ||
| pdf = c("pdf", "cdf", "distr"), | ||
| cdf = c("pdf", "cdf", "distr"), | ||
| distr = c("pdf", "cdf", "distr") | ||
| ) | ||
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| # measure | ||
| x$measure_properties$surv = x$measure_properties$regr | ||
| x$measure_properties$dens = x$measure_properties$regr | ||
| x$default_measures$surv = "surv.cindex" | ||
| x$default_measures$dens = "dens.logloss" | ||
| } | ||
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| register_mlr3 = function() { | ||
| # reflections | ||
| register_reflections() | ||
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| # tasks | ||
| mlr_tasks = utils::getFromNamespace("mlr_tasks", ns = "mlr3") | ||
| iwalk(as.list(mlr3proba_tasks), function(obj, name) mlr_tasks$add(name, obj)) # nolint | ||
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| # task generators | ||
| mlr_task_gens = utils::getFromNamespace("mlr_task_generators", ns = "mlr3") | ||
| iwalk(as.list(mlr3proba_task_gens), function(obj, name) mlr_task_gens$add(name, obj)) # nolint | ||
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| # learners | ||
| mlr_learners = utils::getFromNamespace("mlr_learners", ns = "mlr3") | ||
| iwalk(as.list(mlr3proba_learners), function(obj, name) mlr_learners$add(name, obj)) # nolint | ||
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| # measures | ||
| mlr_measures = utils::getFromNamespace("mlr_measures", ns = "mlr3") | ||
| iwalk(as.list(mlr3proba_measures), function(obj, name) mlr_measures$add(name, obj)) # nolint | ||
| } | ||
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| register_mlr3pipelines = function() { | ||
| mlr3pipelines::add_class_hierarchy_cache(c("PredictionSurv", "Prediction")) | ||
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| # pipeops | ||
| mlr_pipeops = utils::getFromNamespace("mlr_pipeops", ns = "mlr3pipelines") | ||
| iwalk(as.list(mlr3proba_pipeops), function(obj, name) mlr_pipeops$add(name, obj)) # nolint | ||
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| # Breslow needs another argument so we do it manually | ||
| mlr_pipeops$add("breslowcompose", PipeOpBreslow, list(R6Class("Learner", | ||
| public = list(id = "breslowcompose", task_type = "surv", predict_types = "lp", | ||
| packages = c("mlr3", "mlr3proba"), param_set = ps()))$new())) | ||
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| # graphs | ||
| mlr_graphs = utils::getFromNamespace("mlr_graphs", ns = "mlr3pipelines") | ||
| iwalk(as.list(mlr3proba_graphs), function(obj, name) mlr_graphs$add(name, obj)) # nolint | ||
| } |
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