From: Chun-Heng Huang <applerman@hotmail.com>
Date: Mon, 11 Mar 2013 04:20:04 +0000 (+0800)
Subject: Matlab interface parameter checking
X-Git-Tag: v194~14
X-Git-Url: https://granicus.if.org/sourcecode?a=commitdiff_plain;h=3a30c797bd2e570dfcb736475264f25d0bf79e99;p=liblinear

Matlab interface parameter checking
Check 'nlhs' argument.
Allow various output size for predict.
---

diff --git a/matlab/README b/matlab/README
index 3c8b0eb..3259bdf 100644
--- a/matlab/README
+++ b/matlab/README
@@ -95,6 +95,7 @@ matlab> model = train(training_label_vector, training_instance_matrix [,'libline
             if 'col' is set, each column of training_instance_matrix is a data instance. Otherwise each row is a data instance.
 
 matlab> [predicted_label, accuracy, decision_values/prob_estimates] = predict(testing_label_vector, testing_instance_matrix, model [, 'liblinear_options', 'col']);
+matlab> [predicted_label] = predict(testing_label_vector, testing_instance_matrix, model [, 'liblinear_options', 'col']);
 
         -testing_label_vector:
             An m by 1 vector of prediction labels. If labels of test
diff --git a/matlab/predict.c b/matlab/predict.c
index b1d56d5..2fd992e 100644
--- a/matlab/predict.c
+++ b/matlab/predict.c
@@ -49,14 +49,14 @@ void read_sparse_instance(const mxArray *prhs, int index, struct feature_node *x
 	x[j].index = -1;
 }
 
-static void fake_answer(mxArray *plhs[])
+static void fake_answer(int nlhs, mxArray *plhs[])
 {
-	plhs[0] = mxCreateDoubleMatrix(0, 0, mxREAL);
-	plhs[1] = mxCreateDoubleMatrix(0, 0, mxREAL);
-	plhs[2] = mxCreateDoubleMatrix(0, 0, mxREAL);
+	int i;
+	for(i=0;i<nlhs;i++)
+		plhs[i] = mxCreateDoubleMatrix(0, 0, mxREAL);
 }
 
-void do_predict(mxArray *plhs[], const mxArray *prhs[], struct model *model_, const int predict_probability_flag)
+void do_predict(int nlhs, mxArray *plhs[], const mxArray *prhs[], struct model *model_, const int predict_probability_flag)
 {
 	int label_vector_row_num, label_vector_col_num;
 	int feature_number, testing_instance_number;
@@ -65,6 +65,7 @@ void do_predict(mxArray *plhs[], const mxArray *prhs[], struct model *model_, co
 	double *ptr_prob_estimates, *ptr_dec_values, *ptr;
 	struct feature_node *x;
 	mxArray *pplhs[1]; // instance sparse matrix in row format
+	mxArray *tplhs[3]; // temporary storage for plhs[]
 
 	int correct = 0;
 	int total = 0;
@@ -95,13 +96,13 @@ void do_predict(mxArray *plhs[], const mxArray *prhs[], struct model *model_, co
 	if(label_vector_row_num!=testing_instance_number)
 	{
 		mexPrintf("Length of label vector does not match # of instances.\n");
-		fake_answer(plhs);
+		fake_answer(nlhs, plhs);
 		return;
 	}
 	if(label_vector_col_num!=1)
 	{
 		mexPrintf("label (1st argument) should be a vector (# of column is 1).\n");
-		fake_answer(plhs);
+		fake_answer(nlhs, plhs);
 		return;
 	}
 
@@ -117,7 +118,7 @@ void do_predict(mxArray *plhs[], const mxArray *prhs[], struct model *model_, co
 		if(mexCallMATLAB(1, pplhs, 1, pprhs, "transpose"))
 		{
 			mexPrintf("Error: cannot transpose testing instance matrix\n");
-			fake_answer(plhs);
+			fake_answer(nlhs, plhs);
 			return;
 		}
 	}
@@ -125,15 +126,15 @@ void do_predict(mxArray *plhs[], const mxArray *prhs[], struct model *model_, co
 
 	prob_estimates = Malloc(double, nr_class);
 
-	plhs[0] = mxCreateDoubleMatrix(testing_instance_number, 1, mxREAL);
+	tplhs[0] = mxCreateDoubleMatrix(testing_instance_number, 1, mxREAL);
 	if(predict_probability_flag)
-		plhs[2] = mxCreateDoubleMatrix(testing_instance_number, nr_class, mxREAL);
+		tplhs[2] = mxCreateDoubleMatrix(testing_instance_number, nr_class, mxREAL);
 	else
-		plhs[2] = mxCreateDoubleMatrix(testing_instance_number, nr_w, mxREAL);
+		tplhs[2] = mxCreateDoubleMatrix(testing_instance_number, nr_w, mxREAL);
 
-	ptr_predict_label = mxGetPr(plhs[0]);
-	ptr_prob_estimates = mxGetPr(plhs[2]);
-	ptr_dec_values = mxGetPr(plhs[2]);
+	ptr_predict_label = mxGetPr(tplhs[0]);
+	ptr_prob_estimates = mxGetPr(tplhs[2]);
+	ptr_dec_values = mxGetPr(tplhs[2]);
 	x = Malloc(struct feature_node, feature_number+2);
 	for(instance_index=0;instance_index<testing_instance_number;instance_index++)
 	{
@@ -189,8 +190,8 @@ void do_predict(mxArray *plhs[], const mxArray *prhs[], struct model *model_, co
 		info("Accuracy = %g%% (%d/%d)\n", (double) correct/total*100,correct,total);
 
 	// return accuracy, mean squared error, squared correlation coefficient
-	plhs[1] = mxCreateDoubleMatrix(3, 1, mxREAL);
-	ptr = mxGetPr(plhs[1]);
+	tplhs[1] = mxCreateDoubleMatrix(3, 1, mxREAL);
+	ptr = mxGetPr(tplhs[1]);
 	ptr[0] = (double)correct/total*100;
 	ptr[1] = error/total;
 	ptr[2] = ((total*sumpt-sump*sumt)*(total*sumpt-sump*sumt))/
@@ -199,12 +200,20 @@ void do_predict(mxArray *plhs[], const mxArray *prhs[], struct model *model_, co
 	free(x);
 	if(prob_estimates != NULL)
 		free(prob_estimates);
+
+	switch(nlhs){
+		case 3:	plhs[2] = tplhs[2];
+				plhs[1] = tplhs[1];
+		case 1:
+		case 0:	plhs[0] = tplhs[0];
+	}
 }
 
 void exit_with_help()
 {
 	mexPrintf(
 			"Usage: [predicted_label, accuracy, decision_values/prob_estimates] = predict(testing_label_vector, testing_instance_matrix, model, 'liblinear_options','col')\n"
+			"       [predicted_label] = predict(testing_label_vector, testing_instance_matrix, model, 'liblinear_options','col')\n"
 			"liblinear_options:\n"
 			"-b probability_estimates: whether to output probability estimates, 0 or 1 (default 0); currently for logistic regression only\n"
 			"-q quiet mode (no outputs)\n"
@@ -225,10 +234,10 @@ void mexFunction( int nlhs, mxArray *plhs[],
 	info = &mexPrintf;
 	col_format_flag = 0;
 
-	if(nrhs > 5 || nrhs < 3)
+	if(nlhs == 2 || nlhs > 3 || nrhs > 5 || nrhs < 3)
 	{
 		exit_with_help();
-		fake_answer(plhs);
+		fake_answer(nlhs, plhs);
 		return;
 	}
 	if(nrhs == 5)
@@ -242,7 +251,7 @@ void mexFunction( int nlhs, mxArray *plhs[],
 
 	if(!mxIsDouble(prhs[0]) || !mxIsDouble(prhs[1])) {
 		mexPrintf("Error: label vector and instance matrix must be double\n");
-		fake_answer(plhs);
+		fake_answer(nlhs, plhs);
 		return;
 	}
 
@@ -269,7 +278,7 @@ void mexFunction( int nlhs, mxArray *plhs[],
 				if(i>=argc && argv[i-1][1] != 'q')
 				{
 					exit_with_help();
-					fake_answer(plhs);
+					fake_answer(nlhs, plhs);
 					return;
 				}
 				switch(argv[i-1][1])
@@ -284,7 +293,7 @@ void mexFunction( int nlhs, mxArray *plhs[],
 					default:
 						mexPrintf("unknown option\n");
 						exit_with_help();
-						fake_answer(plhs);
+						fake_answer(nlhs, plhs);
 						return;
 				}
 			}
@@ -296,7 +305,7 @@ void mexFunction( int nlhs, mxArray *plhs[],
 		{
 			mexPrintf("Error: can't read model: %s\n", error_msg);
 			free_and_destroy_model(&model_);
-			fake_answer(plhs);
+			fake_answer(nlhs, plhs);
 			return;
 		}
 
@@ -310,12 +319,12 @@ void mexFunction( int nlhs, mxArray *plhs[],
 		}
 
 		if(mxIsSparse(prhs[1]))
-			do_predict(plhs, prhs, model_, prob_estimate_flag);
+			do_predict(nlhs, plhs, prhs, model_, prob_estimate_flag);
 		else
 		{
 			mexPrintf("Testing_instance_matrix must be sparse; "
 				"use sparse(Testing_instance_matrix) first\n");
-			fake_answer(plhs);
+			fake_answer(nlhs, plhs);
 		}
 
 		// destroy model_
@@ -324,7 +333,7 @@ void mexFunction( int nlhs, mxArray *plhs[],
 	else
 	{
 		mexPrintf("model file should be a struct array\n");
-		fake_answer(plhs);
+		fake_answer(nlhs, plhs);
 	}
 
 	return;
diff --git a/matlab/train.c b/matlab/train.c
index 6351dab..1301ed5 100644
--- a/matlab/train.c
+++ b/matlab/train.c
@@ -243,9 +243,11 @@ int parse_command_line(int nrhs, const mxArray *prhs[], char *model_file_name)
 	return 0;
 }
 
-static void fake_answer(mxArray *plhs[])
+static void fake_answer(int nlhs, mxArray *plhs[])
 {
-	plhs[0] = mxCreateDoubleMatrix(0, 0, mxREAL);
+	int i;
+	for(i=0;i<nlhs;i++)
+		plhs[i] = mxCreateDoubleMatrix(0, 0, mxREAL);
 }
 
 int read_problem_sparse(const mxArray *label_vec, const mxArray *instance_mat)
@@ -342,6 +344,13 @@ void mexFunction( int nlhs, mxArray *plhs[],
 	// (for cross validation)
 	srand(1);
 
+	if(nlhs > 1)
+	{
+		exit_with_help();
+		fake_answer(nlhs, plhs);
+		return;
+	}
+
 	// Transform the input Matrix to libsvm format
 	if(nrhs > 1 && nrhs < 5)
 	{
@@ -349,7 +358,7 @@ void mexFunction( int nlhs, mxArray *plhs[],
 
 		if(!mxIsDouble(prhs[0]) || !mxIsDouble(prhs[1])) {
 			mexPrintf("Error: label vector and instance matrix must be double\n");
-			fake_answer(plhs);
+			fake_answer(nlhs, plhs);
 			return;
 		}
 
@@ -357,7 +366,7 @@ void mexFunction( int nlhs, mxArray *plhs[],
 		{
 			exit_with_help();
 			destroy_param(&param);
-			fake_answer(plhs);
+			fake_answer(nlhs, plhs);
 			return;
 		}
 
@@ -368,7 +377,7 @@ void mexFunction( int nlhs, mxArray *plhs[],
 			mexPrintf("Training_instance_matrix must be sparse; "
 				"use sparse(Training_instance_matrix) first\n");
 			destroy_param(&param);
-			fake_answer(plhs);
+			fake_answer(nlhs, plhs);
 			return;
 		}
 
@@ -383,7 +392,7 @@ void mexFunction( int nlhs, mxArray *plhs[],
 			free(prob.y);
 			free(prob.x);
 			free(x_space);
-			fake_answer(plhs);
+			fake_answer(nlhs, plhs);
 			return;
 		}
 
@@ -412,7 +421,7 @@ void mexFunction( int nlhs, mxArray *plhs[],
 	else
 	{
 		exit_with_help();
-		fake_answer(plhs);
+		fake_answer(nlhs, plhs);
 		return;
 	}
 }
diff --git a/windows/predict.mexw64 b/windows/predict.mexw64
index 1a64777..4a7592c 100755
Binary files a/windows/predict.mexw64 and b/windows/predict.mexw64 differ
diff --git a/windows/train.mexw64 b/windows/train.mexw64
index f08699c..9fc0676 100755
Binary files a/windows/train.mexw64 and b/windows/train.mexw64 differ