added code to expose c_api_pred_contrib in the R package (#1259)

* added code to expose c_api_pred_contrib in the R package

* removed Rprintf

* reverted to previous version of install.libs.R

.gitignore

@@ -380,3 +380,4 @@ lightgbm.model
 
 # duplicate version file
 python-package/lightgbm/VERSION.txt
+.Rproj.user

R-package/R/lgb.Booster.R

@@ -615,6 +615,7 @@ Booster <- R6Class(
 #'        sum of predictions from boosting iterations' results. E.g., setting \code{rawscore=TRUE} for
 #'        logistic regression would result in predictions for log-odds instead of probabilities.
 #' @param predleaf whether predict leaf index instead.
+#' @param predcontrib return per-feature contributions for each record.
 #' @param header only used for prediction for text file. True if text file has header
 #' @param reshape whether to reshape the vector of predictions to a matrix form when there are several
 #'        prediction outputs per case.
@@ -655,6 +656,7 @@ predict.lgb.Booster <- function(object, data,
                         num_iteration = NULL,
                         rawscore = FALSE,
                         predleaf = FALSE,
+                        predcontrib = FALSE,
                         header = FALSE,
                         reshape = FALSE, ...) {
   
@@ -668,6 +670,7 @@ predict.lgb.Booster <- function(object, data,
                  num_iteration,
                  rawscore,
                  predleaf,
+                 predcontrib,
                  header,
                  reshape, ...)
 }

R-package/R/lgb.Predictor.R

@@ -63,6 +63,7 @@ Predictor <- R6Class(
                        num_iteration = NULL,
                        rawscore = FALSE,
                        predleaf = FALSE,
+                       predcontrib = FALSE,
                        header = FALSE,
                        reshape = FALSE) {
       
@@ -86,6 +87,7 @@ Predictor <- R6Class(
           as.integer(header),
           as.integer(rawscore),
           as.integer(predleaf),
+          as.integer(predcontrib),
           as.integer(num_iteration),
           private$params,
           lgb.c_str(tmp_filename))
@@ -99,6 +101,7 @@ Predictor <- R6Class(
         
         # Not a file, we need to predict from R object
         num_row <- nrow(data)
+        
         npred <- 0L
         
         # Check number of predictions to do
@@ -108,6 +111,7 @@ Predictor <- R6Class(
                           as.integer(num_row),
                           as.integer(rawscore),
                           as.integer(predleaf),
+                          as.integer(predcontrib),
                           as.integer(num_iteration))
         
         # Pre-allocate empty vector
@@ -123,6 +127,7 @@ Predictor <- R6Class(
                             as.integer(ncol(data)),
                             as.integer(rawscore),
                             as.integer(predleaf),
+                            as.integer(predcontrib),
                             as.integer(num_iteration),
                             private$params)
           
@@ -142,6 +147,7 @@ Predictor <- R6Class(
                             nrow(data),
                             as.integer(rawscore),
                             as.integer(predleaf),
+                            as.integer(predcontrib),
                             as.integer(num_iteration),
                             private$params)
           
@@ -165,7 +171,7 @@ Predictor <- R6Class(
       
       # Data reshaping
       
-      if (predleaf) {
+      if (predleaf | predcontrib) {
         
         # Predict leaves only, reshaping is mandatory
         preds <- matrix(preds, ncol = npred_per_case, byrow = TRUE)

include/LightGBM/lightgbm_R.h

@@ -388,6 +388,7 @@ LIGHTGBM_C_EXPORT LGBM_SE LGBM_BoosterPredictForFile_R(LGBM_SE handle,
   LGBM_SE data_has_header,
   LGBM_SE is_rawscore,
   LGBM_SE is_leafidx,
+  LGBM_SE is_predcontrib,
   LGBM_SE num_iteration,
   LGBM_SE parameter,
   LGBM_SE result_filename,
@@ -407,6 +408,7 @@ LIGHTGBM_C_EXPORT LGBM_SE LGBM_BoosterCalcNumPredict_R(LGBM_SE handle,
   LGBM_SE num_row,
   LGBM_SE is_rawscore,
   LGBM_SE is_leafidx,
+  LGBM_SE is_predcontrib,
   LGBM_SE num_iteration,
   LGBM_SE out_len,
   LGBM_SE call_state);
@@ -438,6 +440,7 @@ LIGHTGBM_C_EXPORT LGBM_SE LGBM_BoosterPredictForCSC_R(LGBM_SE handle,
   LGBM_SE num_row,
   LGBM_SE is_rawscore,
   LGBM_SE is_leafidx,
+  LGBM_SE is_predcontrib,
   LGBM_SE num_iteration,
   LGBM_SE parameter,
   LGBM_SE out_result,
@@ -464,6 +467,7 @@ LIGHTGBM_C_EXPORT LGBM_SE LGBM_BoosterPredictForMat_R(LGBM_SE handle,
   LGBM_SE ncol,
   LGBM_SE is_rawscore,
   LGBM_SE is_leafidx,
+  LGBM_SE is_predcontrib,
   LGBM_SE num_iteration,
   LGBM_SE parameter,
   LGBM_SE out_result,

src/lightgbm_R.cpp

@@ -479,7 +479,7 @@ LGBM_SE LGBM_BoosterGetPredict_R(LGBM_SE handle,
   R_API_END();
 }
 
-int GetPredictType(LGBM_SE is_rawscore, LGBM_SE is_leafidx) {
+int GetPredictType(LGBM_SE is_rawscore, LGBM_SE is_leafidx, LGBM_SE is_predcontrib) {
   int pred_type = C_API_PREDICT_NORMAL;
   if (R_AS_INT(is_rawscore)) {
     pred_type = C_API_PREDICT_RAW_SCORE;
@@ -487,6 +487,9 @@ int GetPredictType(LGBM_SE is_rawscore, LGBM_SE is_leafidx) {
   if (R_AS_INT(is_leafidx)) {
     pred_type = C_API_PREDICT_LEAF_INDEX;
   }
+  if (R_AS_INT(is_predcontrib)) {
+    pred_type = C_API_PREDICT_CONTRIB;
+  }
   return pred_type;
 }
 
@@ -495,12 +498,13 @@ LGBM_SE LGBM_BoosterPredictForFile_R(LGBM_SE handle,
   LGBM_SE data_has_header,
   LGBM_SE is_rawscore,
   LGBM_SE is_leafidx,
+  LGBM_SE is_predcontrib,
   LGBM_SE num_iteration,
   LGBM_SE parameter,
   LGBM_SE result_filename,
   LGBM_SE call_state) {
   R_API_BEGIN();
-  int pred_type = GetPredictType(is_rawscore, is_leafidx);
+  int pred_type = GetPredictType(is_rawscore, is_leafidx, is_predcontrib);
   CHECK_CALL(LGBM_BoosterPredictForFile(R_GET_PTR(handle), R_CHAR_PTR(data_filename),
     R_AS_INT(data_has_header), pred_type, R_AS_INT(num_iteration), R_CHAR_PTR(parameter),
     R_CHAR_PTR(result_filename)));
@@ -511,11 +515,12 @@ LGBM_SE LGBM_BoosterCalcNumPredict_R(LGBM_SE handle,
   LGBM_SE num_row,
   LGBM_SE is_rawscore,
   LGBM_SE is_leafidx,
+  LGBM_SE is_predcontrib,
   LGBM_SE num_iteration,
   LGBM_SE out_len,
   LGBM_SE call_state) {
   R_API_BEGIN();
-  int pred_type = GetPredictType(is_rawscore, is_leafidx);
+  int pred_type = GetPredictType(is_rawscore, is_leafidx, is_predcontrib);
   int64_t len = 0;
   CHECK_CALL(LGBM_BoosterCalcNumPredict(R_GET_PTR(handle), R_AS_INT(num_row),
     pred_type, R_AS_INT(num_iteration), &len));
@@ -532,13 +537,14 @@ LGBM_SE LGBM_BoosterPredictForCSC_R(LGBM_SE handle,
   LGBM_SE num_row,
   LGBM_SE is_rawscore,
   LGBM_SE is_leafidx,
+  LGBM_SE is_predcontrib,
   LGBM_SE num_iteration,
   LGBM_SE parameter,
   LGBM_SE out_result,
   LGBM_SE call_state) {
 
   R_API_BEGIN();
-  int pred_type = GetPredictType(is_rawscore, is_leafidx);
+  int pred_type = GetPredictType(is_rawscore, is_leafidx, is_predcontrib);
 
   const int* p_indptr = R_INT_PTR(indptr);
   const int* p_indices = R_INT_PTR(indices);
@@ -562,13 +568,14 @@ LGBM_SE LGBM_BoosterPredictForMat_R(LGBM_SE handle,
   LGBM_SE num_col,
   LGBM_SE is_rawscore,
   LGBM_SE is_leafidx,
+  LGBM_SE is_predcontrib,
   LGBM_SE num_iteration,
   LGBM_SE parameter,
   LGBM_SE out_result,
   LGBM_SE call_state) {
 
   R_API_BEGIN();
-  int pred_type = GetPredictType(is_rawscore, is_leafidx);
+  int pred_type = GetPredictType(is_rawscore, is_leafidx, is_predcontrib);
 
   int32_t nrow = R_AS_INT(num_row);
   int32_t ncol = R_AS_INT(num_col);