cleanup

R/RcppExports.R

@@ -29,7 +29,7 @@ lm_variance_cr2 <- function(X, Xunweighted, XtX_inv, ei, weight_mean, clusters,
     .Call(`_estimatr_lm_variance_cr2`, X, Xunweighted, XtX_inv, ei, weight_mean, clusters, J, ci, which_covs)
 }
 
-naomitwhy <- function(df, isna, recursive_subset) {
-    .Call(`_estimatr_naomitwhy`, df, isna, recursive_subset)
+naomitwhy <- function(df, recursive_subset) {
+    .Call(`_estimatr_naomitwhy`, df, recursive_subset)
 }
 

R/helper_na_omit_detailed.R

@@ -10,7 +10,7 @@
 #' @seealso \code{\link{na.omit}}
 na.omit_detailed.data.frame <- function(object){
 
-  naomitwhy(object, is.na(object), function(x, w) x[w, , drop=FALSE])
+  naomitwhy(object, function(x, w) x[w, , drop=FALSE])
 
 }
 

src/RcppExports.cpp

@@ -107,15 +107,14 @@ BEGIN_RCPP
 END_RCPP
 }
 // naomitwhy
-DataFrame naomitwhy(DataFrame df, LogicalMatrix isna, Function recursive_subset);
-RcppExport SEXP _estimatr_naomitwhy(SEXP dfSEXP, SEXP isnaSEXP, SEXP recursive_subsetSEXP) {
+DataFrame naomitwhy(DataFrame df, Function recursive_subset);
+RcppExport SEXP _estimatr_naomitwhy(SEXP dfSEXP, SEXP recursive_subsetSEXP) {
 BEGIN_RCPP
     Rcpp::RObject rcpp_result_gen;
     Rcpp::RNGScope rcpp_rngScope_gen;
     Rcpp::traits::input_parameter< DataFrame >::type df(dfSEXP);
-    Rcpp::traits::input_parameter< LogicalMatrix >::type isna(isnaSEXP);
     Rcpp::traits::input_parameter< Function >::type recursive_subset(recursive_subsetSEXP);
-    rcpp_result_gen = Rcpp::wrap(naomitwhy(df, isna, recursive_subset));
+    rcpp_result_gen = Rcpp::wrap(naomitwhy(df, recursive_subset));
     return rcpp_result_gen;
 END_RCPP
 }
@@ -128,7 +127,7 @@ static const R_CallMethodDef CallEntries[] = {
     {"_estimatr_lm_solver", (DL_FUNC) &_estimatr_lm_solver, 3},
     {"_estimatr_lm_variance", (DL_FUNC) &_estimatr_lm_variance, 8},
     {"_estimatr_lm_variance_cr2", (DL_FUNC) &_estimatr_lm_variance_cr2, 9},
-    {"_estimatr_naomitwhy", (DL_FUNC) &_estimatr_naomitwhy, 3},
+    {"_estimatr_naomitwhy", (DL_FUNC) &_estimatr_naomitwhy, 2},
     {NULL, NULL, 0}
 };
 

src/naomit.cpp

@@ -15,75 +15,54 @@ SEXP generic_logical_subset( SEXP xin , LogicalVector w){
 }
 
 // [[Rcpp::export]]
-DataFrame naomitwhy(DataFrame df, LogicalMatrix isna, Function recursive_subset) {
+DataFrame naomitwhy(DataFrame df, Function recursive_subset) {
   int m = df.nrow();
   int n = df.ncol();
-  int N = isna.ncol();
 
+  Function isna("is.na");
 
   CharacterVector df_names = df.names();
 
-  IntegerVector na_to_col_map(n);
-  if(N == n){
-    std::fill(na_to_col_map.begin(), na_to_col_map.end(), 1);
-  }
-  else {
-    Function dim("dim");
-
-    for(int i = 0; i < n; i++){
-      SEXP dfi = df[i];
-      if(Rf_isVectorAtomic(dfi) && LENGTH(dfi) == m){
-        na_to_col_map[i] = 1;
-      } else {
-        SEXP nc = dim(dfi);
-        na_to_col_map[i] = Rf_isNull(nc) ? 1 : INTEGER(nc)[1];
-      }
-    }
-  }
-
   LogicalVector omit = LogicalVector(m);
 
-  int omit_count = 0, omit_f = m, omit_l = 0;
+  int omit_count = 0;
 
   List why_omit(n);
   why_omit.names() = df_names;
   LogicalVector why_omit_idx(n);
 
 
-  for (int j = 0, ii = 0; j < n; j++) {
+  for (int j = 0; j < n; j++) {
 
     std::vector<int> why_omit_j;
 
-    for (int j_sub = na_to_col_map[j]; j_sub; j_sub--){
-      for (int i = 0; i < m; i++, ii++){
+    LogicalVector v_isna = isna(df[j]);
 
-        if(isna[ii]){
-          if(!omit[i]){
-            why_omit_j.push_back(i + 1);
-          }
+    for(int ii = m; ii < LENGTH(v_isna); ){
+      for(int i = 0; i < m; i++, ii++)
+        v_isna[i] |= v_isna[ii];
+    }
 
-          omit[i] = true;
+    for(int i = 0; i < m; i++){
+      if(v_isna[i]){
+        if(!omit[i]){
+          why_omit_j.push_back(i + 1);
         }
-      }
+        omit[i] = true;
+      };
     }
 
     if(why_omit_j.size() > 0){
-      if(na_to_col_map[j] > 1){
-        std::sort(why_omit_j.begin(), why_omit_j.end());
-      }
       why_omit[j] = wrap(why_omit_j);
       why_omit_idx[j] = true;
-      omit_f = std::min(omit_f, why_omit_j.front());
-      omit_l = std::max(omit_l, why_omit_j.back());
       omit_count += why_omit_j.size();
     }
   }
-  if(omit_count == 0){ return(df); }
 
-  // Rcout << "after\n" << omit_count << "\n";
+  if(omit_count == 0){ return(df); }
 
   IntegerVector omit_idx = IntegerVector(omit_count);
-  for(int i = omit_f-1, ii=0; i < omit_l; i++){
+  for(int i = 0, ii=0; ii < omit_count; i++){
     if(omit[i]) omit_idx[ii++] = i+1;
   }
 
@@ -92,20 +71,18 @@ DataFrame naomitwhy(DataFrame df, LogicalMatrix isna, Function recursive_subset)
 
   omit_idx.attr("why_omit") = why_omit[why_omit_idx];
   omit_idx.attr("class") = CharacterVector::create("omit", "detailed");
-  //omit_idx.attr("tokeep") = !omit;
 
   omit = !omit;
 
   List out(n);
 
   for(int i = 0; i < n; i++){
     SEXP dfi = df(i);
-    if(Rf_isVectorAtomic(dfi) && LENGTH(dfi) == m){
+    if(LENGTH(dfi) == m){
       out[i] = generic_logical_subset(dfi, omit);
     } else {
       out[i] = recursive_subset(dfi, omit);
     }
-
   }
 
   out.names() = df_names;
@@ -120,12 +97,11 @@ DataFrame naomitwhy(DataFrame df, LogicalMatrix isna, Function recursive_subset)
   // require(microbenchmark)
   // df <- expand.grid(x=c(1:100, NA), y=c(1:5, NA), z=c(1:8, NA), q=c(NA,2:5))
   // df2 <- na.omit(df)
-  // microbenchmark(stock=na.omit(df), ours=estimatr:::na.omit_detailed.data.frame(df))
+  // microbenchmark(stock=na.omit(df), ours=estimatr:::na.omit_detailed.data.frame(df), unit="ms")
   // microbenchmark(stock=na.omit(df2), ours=estimatr:::na.omit_detailed.data.frame(df2), unit="ms")
-  //
+
   // df <- rbind(df, df2, df)
   // df2 <- rbind(df2, df2, df2)
-  //
   // microbenchmark(stock=na.omit(df), ours=estimatr:::na.omit_detailed.data.frame(df), unit="ms")
   // microbenchmark(stock=na.omit(df2), ours=estimatr:::na.omit_detailed.data.frame(df2), unit="ms")