From c1132606169875be6d07b54b30e8ae9446341bc2 Mon Sep 17 00:00:00 2001
From: Peter Carbonetto
Date: Sun, 4 Jun 2017 12:06:36 -0500
Subject: Removed FORCE_FLOAT from prdt.h/prdt.cpp.

---
 src/logistic.h | 93 +++++++++++++++++++++++++++++-----------------------------
 1 file changed, 47 insertions(+), 46 deletions(-)

(limited to 'src/logistic.h')

diff --git a/src/logistic.h b/src/logistic.h
index a68ee09..e951935 100644
--- a/src/logistic.h
+++ b/src/logistic.h
@@ -1,52 +1,54 @@
 #ifndef LOGISTIC_H_   /* Include guard */
 #define LOGISTIC_H_
 
-/* Mixed interface */
-void logistic_mixed_pred(gsl_vector *beta  // Vector of parameters length = 1 + Sum_k(C_k - 1) + Kc
-			 ,gsl_matrix_int *X  //Matrix Nobs x K 
-			 ,gsl_vector_int *nlev // Vector with number categories
-			 ,gsl_matrix *Xc   // continuous covariates  Matrix Nobs x Kc 
-			 ,gsl_vector *yhat //Vector of prob. predicted by the logistic
-			 );
+// Mixed interface.
+void logistic_mixed_pred(gsl_vector *beta,     // Vector of parameters
+					       // length = 1+Sum_k(C_k-1)+Kc.
+			 gsl_matrix_int *X,    // Matrix Nobs x K.
+			 gsl_vector_int *nlev, // Vector with num. categories.
+			 gsl_matrix *Xc,       // Continuous covariates matrix
+					       // Nobs x Kc
+			 gsl_vector *yhat);    // Vector of prob. predicted by
+					       // the logistic.
  
-int logistic_mixed_fit(gsl_vector *beta  // Vector of parameters length = 1 + Sum_k(C_k - 1) + Kc
-		       ,gsl_matrix_int *X  //Matrix Nobs x K 
-		       ,gsl_vector_int *nlev // Vector with number categories
-		       ,gsl_matrix *Xc   // continuous covariates  Matrix Nobs x Kc 
-		       ,gsl_vector *y //Vector of prob. to predict
-		       ,double lambdaL1 // Regularization L1 0.0 if not used
-		       ,double lambdaL2); // Regularization L2 0.0 if not used
+int logistic_mixed_fit(gsl_vector *beta,     // Vector of parameters
+					     // length = 1+Sum_k(C_k-1)+Kc
+		       gsl_matrix_int *X,    // Matrix Nobs x K.
+		       gsl_vector_int *nlev, // Vector with number categories.
+		       gsl_matrix *Xc,       // Continuous covariates
+					     // matrix Nobs x Kc
+		       gsl_vector *y,        // Vector of prob. to predict.
+		       double lambdaL1,      // Reg. L1 0.0 if not used.
+		       double lambdaL2);     // Reg. L2 0.0 if not used.
 
-double fLogit_mixed(gsl_vector *beta
-		    ,gsl_matrix_int *X
-		    ,gsl_vector_int *nlev
-		    ,gsl_matrix *Xc   // continuous covariates  Matrix Nobs x Kc 
-		    ,gsl_vector *y
-		    ,double lambdaL1
-		    ,double lambdaL2);
+double fLogit_mixed(gsl_vector *beta,
+		    gsl_matrix_int *X,
+		    gsl_vector_int *nlev,
+		    gsl_matrix *Xc, // continuous covariates matrix Nobs x Kc 
+		    gsl_vector *y,
+		    double lambdaL1,
+		    double lambdaL2);
 
 
-/* Categorical only interface */
-void logistic_cat_pred(gsl_vector *beta  // Vector of parameters length = 1 + Sum_k(C_k - 1) + Kc
-		       ,gsl_matrix_int *X  //Matrix Nobs x K 
-		       ,gsl_vector_int *nlev // Vector with number categories
-		       ,gsl_vector *yhat //Vector of prob. predicted by the logistic
-		       );
+// Categorical-only interface.
+void logistic_cat_pred(gsl_vector *beta,  // Vector of parameters length = 1 + Sum_k(C_k - 1) + Kc
+		       gsl_matrix_int *X,  //Matrix Nobs x K 
+		       gsl_vector_int *nlev, // Vector with number categories
+		       gsl_vector *yhat); //Vector of prob. predicted by the logistic
  
-int logistic_cat_fit(gsl_vector *beta  // Vector of parameters length = 1 + Sum_k(C_k - 1) + Kc
-		     ,gsl_matrix_int *X  //Matrix Nobs x K 
-		     ,gsl_vector_int *nlev // Vector with number categories
-		     ,gsl_vector *y //Vector of prob. to predict
-		     ,double lambdaL1 // Regularization L1 0.0 if not used
-		     ,double lambdaL2); // Regularization L2 0.0 if not used
-
-double fLogit_cat(gsl_vector *beta
-		  ,gsl_matrix_int *X
-		  ,gsl_vector_int *nlev
-		  ,gsl_vector *y
-		  ,double lambdaL1
-		  ,double lambdaL2);
+int logistic_cat_fit(gsl_vector *beta,  // Vector of parameters length = 1 + Sum_k(C_k - 1) + Kc
+		     gsl_matrix_int *X,  //Matrix Nobs x K 
+		     gsl_vector_int *nlev, // Vector with number categories
+		     gsl_vector *y, //Vector of prob. to predict
+		     double lambdaL1, // Regularization L1 0.0 if not used
+		     double lambdaL2); // Regularization L2 0.0 if not used
 
+double fLogit_cat(gsl_vector *beta,
+		  gsl_matrix_int *X,
+		  gsl_vector_int *nlev,
+		  gsl_vector *y,
+		  double lambdaL1,
+		  double lambdaL2);
 
 /* Continuous only interface */
 void logistic_cont_pred(gsl_vector *beta  // Vector of parameters length = 1 + Sum_k(C_k - 1) + Kc
@@ -60,11 +62,10 @@ int logistic_cont_fit(gsl_vector *beta  // Vector of parameters length = 1 + Sum
 		      ,double lambdaL1 // Regularization L1 0.0 if not used
 		      ,double lambdaL2); // Regularization L2 0.0 if not used
 
-double fLogit_cont(gsl_vector *beta
-		   ,gsl_matrix *Xc   // continuous covariates  Matrix Nobs x Kc 
-		   ,gsl_vector *y
-		   ,double lambdaL1
-		   ,double lambdaL2);
-
+double fLogit_cont(gsl_vector *beta,
+		   gsl_matrix *Xc, // Continuous covariates matrix Nobs x Kc .
+		   gsl_vector *y,
+		   double lambdaL1,
+		   double lambdaL2);
 
 #endif // LOGISTIC_H_
-- 
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