Fix missing rejection threshold for prediction

 """ Test SLSOM model on ncRNA.
 """ Test SLSOM model on ncRNA.
 
 
 Usage:
 Usage:
-	predict.py --featurer=<path> --file=<path_fasta> --model=<path> --output=<path> [--keep_features]
+	predict.py --featurer=<path> --file=<path_fasta> --model=<path> --output=<path> [--reject=<value>] [--keep_features]
 	predict.py (-h | --help)
 	predict.py (-h | --help)
 	predict.py --version
 	predict.py --version
 
 
@@ -11,6 +11,7 @@ Options:
 	--file=<path> Path to the fasta file
 	--file=<path> Path to the fasta file
 	--model=<path>	Path to the folder containing the model
 	--model=<path>	Path to the folder containing the model
 	--output=<path>	Path to the output dir
 	--output=<path>	Path to the output dir
+	--reject=<value> Rejection threshold.
 	--keep_features	Keep the features computed in the "output" folder.
 	--keep_features	Keep the features computed in the "output" folder.
 	--version
 	--version
 
 
@@ -27,7 +28,7 @@ from SLSOM.SOM import *
 from SLSOM.util import *
 from SLSOM.util import *
 
 
 def save_pred(som,data,data_names,y,proba,bmu,path):
 def save_pred(som,data,data_names,y,proba,bmu,path):
-	y_label = ["Noncoding" if x==1 else "Coding" for x in y]
+	y_label = ["Noncoding" if x==1 else if x==0 "Coding" else "Rejected" for x in y]
 	res = np.array([
 	res = np.array([
 		[data_names[i],bmu[i],y_label[i]]+[proba[i,j] for j in range(proba.shape[1])]
 		[data_names[i],bmu[i],y_label[i]]+[proba[i,j] for j in range(proba.shape[1])]
 		for i in range(data.shape[0])])
 		for i in range(data.shape[0])])
@@ -66,6 +67,8 @@ def main():
 	print("Model loaded")
 	print("Model loaded")
 	y,proba = ssom.predict(data)
 	y,proba = ssom.predict(data)
 	y = np.array(y)
 	y = np.array(y)
+	if not arguments["--reject"]:
+		y[proba < float(arguments["--reject"])] = -1
 	bmu = np.array(som.get_BMUS(data))
 	bmu = np.array(som.get_BMUS(data))
 
 
 	save_pred(som,data,data_names,y,proba,bmu,output_path)
 	save_pred(som,data,data_names,y,proba,bmu,output_path)