{"action":"created","comment":{"url":"https://api.github.com/repos/mlr-org/mlr/pulls/comments/204065489","pull_request_review_id":139081745,"id":204065489,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDIwNDA2NTQ4OQ==","diff_hunk":"@@ -0,0 +1,164 @@\n+#' @title gstat regression learner.\n+#'\n+#' @description\n+#' mlr learner for regression tasks using [gstat::gstat].\n+#'\n+#' This learner does not use the krige interface from gstat. This is because we want to make it the most general as possible.\n+#' Therefore the learner makes use the combination of gstat::gstat and gstat::predict to compute spatial predidction.\n+#' You can read more this StackOverflow thread : https://stackoverflow.com/questions/13920342/how-to-make-ordinary-kriging-by-using-gstat-predict.\n+#'\n+#' The learner handles gstat variogram autofitting functionnality presented in this post https://www.r-spatial.org/r/2016/02/14/gstat-variogram-fitting.html.\n+#' To use manual fitting, you must provide a list to the argument model that holds the following elements :\n+#' psill, model, range and nugget.\n+#' To use auto fitting, simply provide a list containting the types of models to be tested.\n+#' Manual fitting example : lrn.man = makeLearner(cl = 'regr.gstat', id = 'manual', psill = 1, model = 'Sph', range = 900, nugget = 1, locations = ~x+y).\\n\n+# 'Automatic fitting example : lrn.auto = makeLearner(cl = 'regr.gstat', id = 'auto', psill = c('Sph','Exp','Gau', 'Mat'), locations = ~x+y)\"\n+#'\n+#' @references Edzer J Pebesma\n+#' Multivariable geostatistics in S: the gstat package\n+#' Computers & Geosciences Volume 30, Issue 7, 2004, 683-691.\n+#'\n+#'\n+#' @name regr.gstat\n+#' @rdname regr.gstat\n+NULL\n+\n+#' @export\n+makeRLearner.regr.gstat = function() {\n+  makeRLearnerRegr(\n+    cl = \"regr.gstat\",\n+    package = \"gstat\",\n+    par.set = makeParamSet(\n+      # gstat::gstat params\n+      makeFunctionLearnerParam(id = \"g\"),\n+      makeUntypedLearnerParam(id = \"id\"), # FIXME what should be the type ?\n+      makeUntypedLearnerParam(id = \"locations\", default = ~x+y), # FIXME what should be the type ?\n+      makeUntypedLearnerParam(id = \"beta.gstat\"),\n+      makeIntegerLearnerParam(id = \"nmax\", default = 0),\n+      makeIntegerLearnerParam(id = \"nmin\", default = 0),\n+      makeIntegerLearnerParam(id = \"omax\", default = 0),\n+      makeNumericLearnerParam(id = \"maxdist\", allow.inf = TRUE, default = Inf),\n+      makeLogicalLearnerParam(id = \"dummy\", default = FALSE),\n+      makeUntypedLearnerParam(id = \"set\"),\n+      makeFunctionLearnerParam(id = \"x\"),\n+      makeLogicalLearnerParam(id = \"fill.all\", default = FALSE),\n+      makeLogicalLearnerParam(id = \"fill.cross\", default = TRUE),\n+      makeDiscreteLearnerParam(id = \"variance\", values = c(\"identity\", \"mu\", \"mu(1-mu)\"), default = \"identity\"),\n+      makeUntypedLearnerParam(id = \"merge\"),\n+      makeIntegerLearnerParam(id = \"degree\", default = 0),\n+      makeLogicalLearnerParam(id = \"vdist\", default = FALSE),\n+      # gstat::variogram params\n+      makeNumericLearnerParam(id = \"cutoff\"), # FIXME default value\n+      makeNumericLearnerParam(id = \"width\"),\n+      makeNumericLearnerParam(id = \"alpha\", default = 0),\n+      makeNumericLearnerParam(id = \"beta.variogram\", default = 0),\n+      makeNumericLearnerParam(id = \"tol.hor\"),\n+      makeNumericLearnerParam(id = \"tol.ver\"),\n+      makeLogicalLearnerParam(id = \"cressie\", default = FALSE),\n+      makeNumericLearnerParam(id = \"dX\", default = 0),\n+      makeNumericLearnerParam(id = \"boundaries\", default = 0),\n+      makeLogicalLearnerParam(id = \"cloud\", default = FALSE),\n+      makeUntypedLearnerParam(id = \"trend.beta\", default = NULL),\n+      makeIntegerLearnerParam(id = \"debug.level\", default = 1),\n+      makeLogicalLearnerParam(id = \"cross\", default = TRUE),\n+      makeLogicalLearnerParam(id = \"map\", default = FALSE),\n+      makeLogicalLearnerParam(id = \"projected\", default = TRUE),\n+      makeNumericLearnerParam(id = \"lambda\", default = 1.0),\n+      makeLogicalLearnerParam(id = \"verbose\", default = FALSE),\n+      makeLogicalLearnerParam(id = \"covariogram\", default = FALSE),\n+      makeLogicalLearnerParam(id = \"PR\", default = FALSE),\n+      makeIntegerLearnerParam(id = \"pseudo\", default = -1),\n+      # gstat::fit.variogram params\n+      makeLogicalLearnerParam(id = \"fit.sills\", default = TRUE),\n+      makeLogicalLearnerParam(id = \"fit.ranges\", default = TRUE),\n+      makeIntegerLearnerParam(id = \"fit.method\", default = 7),\n+      makeLogicalLearnerParam(id = \"warn.if.neg\", default = FALSE),\n+      makeLogicalLearnerParam(id = \"fit.kappa\", default = FALSE),\n+      # gstat::vgm params\n+      makeUntypedLearnerParam(id = \"psill\", default = NA),\n+      makeUntypedLearnerParam(id = \"model\"), # FIXME what should be the type ?\n+      makeUntypedLearnerParam(id = \"range\", default = NA),\n+      makeNumericLearnerParam(id = \"kappa\", default = 0.5),\n+      makeUntypedLearnerParam(id = \"nugget\"),\n+      makeUntypedLearnerParam(id = \"add.to\"),\n+      makeUntypedLearnerParam(id = \"covtable\"),\n+      makeNumericLearnerParam(id = \"Err\", default = 0)","path":"R/RLearner_regr_gstat.R","position":85,"original_position":85,"commit_id":"51a7c7bf830c91a16416196e3238f4f71e1e9f5a","original_commit_id":"51a7c7bf830c91a16416196e3238f4f71e1e9f5a","user":{"login":"larskotthoff","id":579233,"node_id":"MDQ6VXNlcjU3OTIzMw==","avatar_url":"https://avatars2.githubusercontent.com/u/579233?v=4","gravatar_id":"","url":"https://api.github.com/users/larskotthoff","html_url":"https://github.com/larskotthoff","followers_url":"https://api.github.com/users/larskotthoff/followers","following_url":"https://api.github.com/users/larskotthoff/following{/other_user}","gists_url":"https://api.github.com/users/larskotthoff/gists{/gist_id}","starred_url":"https://api.github.com/users/larskotthoff/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/larskotthoff/subscriptions","organizations_url":"https://api.github.com/users/larskotthoff/orgs","repos_url":"https://api.github.com/users/larskotthoff/repos","events_url":"https://api.github.com/users/larskotthoff/events{/privacy}","received_events_url":"https://api.github.com/users/larskotthoff/received_events","type":"User","site_admin":false},"body":"Can you provide ranges for the parameters where possible please? Do e.g. all the numeric parameters from -inf to inf?","created_at":"2018-07-20T14:36:25Z","updated_at":"2018-07-20T14:44:02Z","html_url":"https://github.com/mlr-org/mlr/pull/2394#discussion_r204065489","pull_request_url":"https://api.github.com/repos/mlr-org/mlr/pulls/2394","author_association":"CONTRIBUTOR","_links":{"self":{"href":"https://api.github.com/repos/mlr-org/mlr/pulls/comments/204065489"},"html":{"href":"https://github.com/mlr-org/mlr/pull/2394#discussion_r204065489"},"pull_request":{"href":"https://api.github.com/repos/mlr-org/mlr/pulls/2394"}}},"pull_request":{"url":"https://api.github.com/repos/mlr-org/mlr/pulls/2394","id":202859829,"node_id":"MDExOlB1bGxSZXF1ZXN0MjAyODU5ODI5","html_url":"https://github.com/mlr-org/mlr/pull/2394","diff_url":"https://github.com/mlr-org/mlr/pull/2394.diff","patch_url":"https://github.com/mlr-org/mlr/pull/2394.patch","issue_url":"https://api.github.com/repos/mlr-org/mlr/issues/2394","number":2394,"state":"open","locked":false,"title":"integration of regr.gstat learner","user":{"login":"pokyah","id":15193683,"node_id":"MDQ6VXNlcjE1MTkzNjgz","avatar_url":"https://avatars0.githubusercontent.com/u/15193683?v=4","gravatar_id":"","url":"https://api.github.com/users/pokyah","html_url":"https://github.com/pokyah","followers_url":"https://api.github.com/users/pokyah/followers","following_url":"https://api.github.com/users/pokyah/following{/other_user}","gists_url":"https://api.github.com/users/pokyah/gists{/gist_id}","starred_url":"https://api.github.com/users/pokyah/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/pokyah/subscriptions","organizations_url":"https://api.github.com/users/pokyah/orgs","repos_url":"https://api.github.com/users/pokyah/repos","events_url":"https://api.github.com/users/pokyah/events{/privacy}","received_events_url":"https://api.github.com/users/pokyah/received_events","type":"User","site_admin":false},"body":"Hi mlr's Team,\r\n\r\nI'm pleased to submit my first and major contribution to your package for review.\r\n\r\nThis contribution implements a new learner : `regr.gstat` from the [gstat](https://cran.r-project.org/web/packages/gstat/) package developed by @edzer - http://edzer.github.io/\r\n\r\ngstat aims to perform spatial predictions as IDW, various kind of Kriging, trend surfaces, etc.\r\n\r\nThe learner has been unit tested with the default settings and various parameters. \r\n\r\nAn additional `usecase_gstat` vignette has been written. It presents the mlr-gstat functions coding with their raw-gstat counterparts and shows that their outputs are strictly identical.\r\n\r\nI need gstat and mlr in the context of my research, this is why I've decided to start this gstat implementation contribution. This is my first experience with package development. I hope I've done things the good way (as explained in your [wiki](https://github.com/mlr-org/mlr/wiki/Developer-Instructions#mlr-coding-guidelines)) but as I'm not a advanced R user, I guess that many parts of my contribution could be improved.\r\n\r\nI had a discussion with @pat-s about the kind of learner (`regr.` or `spatial.`). Spatial was retained but as the existing kriging learner `reger.km` is already classified as a regression learner, I've finally chosen `regr.gstat`.\r\n\r\nFeel free to contact me for questions, suggestions, etc.\r\n\r\nThanks for your interest.\r\n\r\npokyah\r\n","created_at":"2018-07-20T14:06:44Z","updated_at":"2018-07-20T14:44:02Z","closed_at":null,"merged_at":null,"merge_commit_sha":"30dfd6ef0f2945eeb91eef6ef329b160ce51f131","assignee":null,"assignees":[],"requested_reviewers":[],"requested_teams":[],"labels":[],"milestone":null,"commits_url":"https://api.github.com/repos/mlr-org/mlr/pulls/2394/commits","review_comments_url":"https://api.github.com/repos/mlr-org/mlr/pulls/2394/comments","review_comment_url":"https://api.github.com/repos/mlr-org/mlr/pulls/comments{/number}","comments_url":"https://api.github.com/repos/mlr-org/mlr/issues/2394/comments","statuses_url":"https://api.github.com/repos/mlr-org/mlr/statuses/51a7c7bf830c91a16416196e3238f4f71e1e9f5a","head":{"label":"pokyah:gstat","ref":"gstat","sha":"51a7c7bf830c91a16416196e3238f4f71e1e9f5a","user":{"login":"pokyah","id":15193683,"node_id":"MDQ6VXNlcjE1MTkzNjgz","avatar_url":"https://avatars0.githubusercontent.com/u/15193683?v=4","gravatar_id":"","url":"https://api.github.com/users/pokyah","html_url":"https://github.com/pokyah","followers_url":"https://api.github.com/users/pokyah/followers","following_url":"https://api.github.com/users/pokyah/following{/other_user}","gists_url":"https://api.github.com/users/pokyah/gists{/gist_id}","starred_url":"https://api.github.com/users/pokyah/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/pokyah/subscriptions","organizations_url":"https://api.github.com/users/pokyah/orgs","repos_url":"https://api.github.com/users/pokyah/repos","events_url":"https://api.github.com/users/pokyah/events{/privacy}","received_events_url":"https://api.github.com/users/pokyah/received_events","type":"User","site_admin":false},"repo":{"id":129251823,"node_id":"MDEwOlJlcG9zaXRvcnkxMjkyNTE4MjM=","name":"mlr","full_name":"pokyah/mlr","owner":{"login":"pokyah","id":15193683,"node_id":"MDQ6VXNlcjE1MTkzNjgz","avatar_url":"https://avatars0.githubusercontent.com/u/15193683?v=4","gravatar_id":"","url":"https://api.github.com/users/pokyah","html_url":"https://github.com/pokyah","followers_url":"https://api.github.com/users/pokyah/followers","following_url":"https://api.github.com/users/pokyah/following{/other_user}","gists_url":"https://api.github.com/users/pokyah/gists{/gist_id}","starred_url":"https://api.github.com/users/pokyah/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/pokyah/subscriptions","organizations_url":"https://api.github.com/users/pokyah/orgs","repos_url":"https://api.github.com/users/pokyah/repos","events_url":"https://api.github.com/users/pokyah/events{/privacy}","received_events_url":"https://api.github.com/users/pokyah/received_events","type":"User","site_admin":false},"private":false,"html_url":"https://github.com/pokyah/mlr","description":"mlr: 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