Merge pull request #38 from jonathan-taylor/master

change to C library -- allowing for row major ordering, adjusted wrapper

Author: jonathan-taylor

C-software

@@ -45,4 +45,3 @@ importFrom("stats", "coef", "df", "lm", "pf")
 importFrom("stats", "glm", "residuals", "vcov")
 importFrom("stats", "rbinom", "rexp")
 importFrom("Rcpp", "sourceCpp")
-

selectiveInference/NAMESPACE

@@ -45,12 +45,13 @@ randomizedLASSO = function(X,
     soln = rep(0, p)
     Xsoln = rep(0, n)
     linear_func = (- t(X) %*% y - perturb_) / n
+
     gradient = 1. * linear_func
     ever_active = rep(0, p)
     nactive = as.integer(0)
 
     result = solve_QP_wide(X,                  # design matrix
-    	                   lam / n,                # vector of Lagrange multipliers
+    	                   lam / n,            # vector of Lagrange multipliers
 		           ridge_term / n,     # ridge_term 
                            max_iter, 
                            soln, 
@@ -66,7 +67,6 @@ randomizedLASSO = function(X,
 		           objective_stop,     # objective_stop
 			   kkt_stop,           # kkt_stop
 			   param_stop)         # param_stop
-
 
     sign_soln = sign(result$soln)
 

selectiveInference/R/funs.randomized.R

@@ -101,6 +101,7 @@ Rcpp::List solve_QP_wide(Rcpp::NumericMatrix X,
 			 int param_stop
 			 ) {
 
+  int column_major = 1; // R has matrices in column major order
   int ncase = X.nrow(); // number of cases
   int nfeature = X.ncol(); // number of features
 
@@ -139,6 +140,7 @@ Rcpp::List solve_QP_wide(Rcpp::NumericMatrix X,
 			(int *) nactive.begin(),
 			ncase,
 			nfeature,
+			column_major,
 			(double *) bound.begin(),
 			ridge_term,
 			(double *) theta.begin(),
@@ -162,6 +164,7 @@ Rcpp::List solve_QP_wide(Rcpp::NumericMatrix X,
 				 (int *) need_update.begin(),
 				 nfeature,
 				 ncase,
+				 column_major,
 				 (double *) bound.begin(),
 				 ridge_term,
 				 kkt_tol);
@@ -176,7 +179,8 @@ Rcpp::List solve_QP_wide(Rcpp::NumericMatrix X,
 		       (double *) linear_func.begin(),
 		       (int *) need_update.begin(),
 		       nfeature,
-		       ncase);
+		       ncase,
+		       column_major);
 
   return(Rcpp::List::create(Rcpp::Named("soln") = theta,
 			    Rcpp::Named("gradient") = gradient,

selectiveInference/src/Rcpp-debias.cpp

@@ -1,8 +1,8 @@
 library(selectiveInference)
 ### Test
-
 n = 80; p = 50
 
+
 X = matrix(rnorm(n * p), n, p)
 Y = rnorm(n)
 lam = 2
@@ -14,4 +14,5 @@ soln2 = coef(G, s=lam/n, exact=TRUE, x=X, y=Y)[-1]
 print(soln1)
 print(soln2)
 plot(soln1, soln2)
-print(summary(lm(soln1 ~ soln2)))
+print(summary(lm(soln1 ~ soln2)))
+