From 2e539ed13287f663069a7145ebd0289176752e82 Mon Sep 17 00:00:00 2001
From: Jonathan Guinet <jonathan.guinet@c-s.fr>
Date: Fri, 21 Oct 2011 16:32:24 +0200
Subject: [PATCH] STYLE: fix indent.
---
.../otbTrainSVMImagesClassifier.cxx | 31 +++++++++----------
1 file changed, 14 insertions(+), 17 deletions(-)
diff --git a/Applications/Classification/otbTrainSVMImagesClassifier.cxx b/Applications/Classification/otbTrainSVMImagesClassifier.cxx
index 40a3e57367..1fef88e97c 100644
--- a/Applications/Classification/otbTrainSVMImagesClassifier.cxx
+++ b/Applications/Classification/otbTrainSVMImagesClassifier.cxx
@@ -141,29 +141,28 @@ private:
{
AddParameter(ParameterType_InputImageList, "il", "Input Image List");
- SetParameterDescription("il","a list of input images.");
+ SetParameterDescription("il", "a list of input images.");
AddParameter(ParameterType_InputVectorDataList, "vd", "Vector Data List");
- SetParameterDescription("vd","a list of vector data sample used to train the estimator.");
+ SetParameterDescription("vd", "a list of vector data sample used to train the estimator.");
AddParameter(ParameterType_Filename, "dem", "DEM repository");
MandatoryOff("dem");
- SetParameterDescription("dem","path to SRTM repository");
+ SetParameterDescription("dem", "path to SRTM repository");
AddParameter(ParameterType_Filename, "imstat", "XML image statistics file");
MandatoryOff("imstat");
- SetParameterDescription("imstat","filename of an XML file containing mean and standard deviation of input images.");
+ SetParameterDescription("imstat", "filename of an XML file containing mean and standard deviation of input images.");
AddParameter(ParameterType_Filename, "out", "Output SVM model");
- SetParameterDescription("out","Output SVM model");
+ SetParameterDescription("out", "Output SVM model");
AddParameter(ParameterType_Float, "m", "Margin for SVM learning");
MandatoryOff("m");
- SetParameterDescription("m","Margin for SVM learning");
+ SetParameterDescription("m", "Margin for SVM learning");
AddParameter(ParameterType_Int, "b", "Balance and grow the training set");
SetParameterDescription("b", "Balance and grow the training set");
MandatoryOff("b");
- AddParameter(ParameterType_Choice, "k",
- "SVM Kernel Type");
+ AddParameter(ParameterType_Choice, "k", "SVM Kernel Type");
MandatoryOff("k");
- AddChoice("k.linear", "Linear");
- AddChoice("k.rbf", "Neareast Neighbor");
- AddChoice("k.poly", "Polynomial");
+ AddChoice("k.linear", "Linear");
+ AddChoice("k.rbf", "Neareast Neighbor");
+ AddChoice("k.poly", "Polynomial");
AddChoice("k.sigmoid", "Sigmoid");
SetParameterString("k", "linear");
SetParameterDescription("k", "SVM Kernel Type");
@@ -175,17 +174,15 @@ private:
MandatoryOff("mv");
SetParameterInt("mv", -1);
SetParameterDescription("mv", "Maximum size of the validation sample (default = -1)");
- AddParameter(ParameterType_Float, "vtr",
- "training and validation sample ratio");
+ AddParameter(ParameterType_Float, "vtr", "training and validation sample ratio");
SetParameterDescription("vtr",
- "Ratio between training and validation sample (0.0 = all training, 1.0 = all validation) default = 0.5");
+ "Ratio between training and validation sample (0.0 = all training, 1.0 = all validation) default = 0.5");
MandatoryOff("vtr");
SetParameterFloat("vtr", 0.5);
AddParameter(ParameterType_Empty, "opt", "parameters optimization");
MandatoryOff("opt");
- SetParameterDescription("opt","SVM parameters optimization");
- AddParameter(ParameterType_Filename, "vfn",
- "Name of the discrimination field");
+ SetParameterDescription("opt", "SVM parameters optimization");
+ AddParameter(ParameterType_Filename, "vfn", "Name of the discrimination field");
MandatoryOff("vfn");
SetParameterDescription("vfn", "Name of the field using to discriminate class in the vector data files");
SetParameterString("vfn", "Class");
--
GitLab