[otb] 02/04: update patch for 5.2

Rashad Kanavath rashad-guest at moszumanska.debian.org
Wed Dec 23 12:19:27 UTC 2015


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rashad-guest pushed a commit to branch master
in repository otb.

commit d981bee77eceddf9d3dcf364fe71f89499d3d111
Author: Rashad Kanavath <rashad.kanavath at c-s.fr>
Date:   Wed Dec 23 13:10:51 2015 +0100

    update patch for 5.2
---
 debian/patches/spelling.patch | 109 +++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 107 insertions(+), 2 deletions(-)

diff --git a/debian/patches/spelling.patch b/debian/patches/spelling.patch
index fecd536..5c827eb 100644
--- a/debian/patches/spelling.patch
+++ b/debian/patches/spelling.patch
@@ -1,6 +1,9 @@
-Author: Andreas Tille <tille at debian.org>, Rashad Kanavath<rashad.kanavath at c-s.fr>
-Last-Update: Tue, 1 Sep 2015 09:25:20 +0200
 Description: Fix some spelling errors to silence lintian enabling  to concentrate on the real problem.
+Author: Andreas Tille <tille at debian.org>,
+Rashad Kanavath<rashad.kanavath at c-s.fr>,
+Bas Couwenberg <sebastic at xs4all.nl>
+Last-Update: 2015-12-17
+
 --- otb.orig/Modules/Applications/AppChangeDetection/app/otbMultivariateAlterationDetector.cxx
 +++ otb/Modules/Applications/AppChangeDetection/app/otbMultivariateAlterationDetector.cxx
 @@ -75,7 +75,7 @@
@@ -3092,3 +3095,105 @@ Description: Fix some spelling errors to silence lintian enabling  to concentrat
  {
    m_StringLayout = new QVBoxLayout();
    m_StringLayout->setSpacing(0);
+--- otb.orig/Modules/Applications/AppClassification/app/otbTrainRegression.cxx
++++ otb/Modules/Applications/AppClassification/app/otbTrainRegression.cxx
+@@ -122,7 +122,7 @@
+ 
+   //Group IO
+   AddParameter(ParameterType_Group, "io", "Input and output data");
+-  SetParameterDescription("io", "This group of parameters allows to set input and output data.");
++  SetParameterDescription("io", "This group of parameters allows setting input and output data.");
+   AddParameter(ParameterType_InputImageList, "io.il", "Input Image List");
+   SetParameterDescription("io.il", "A list of input images. First (n-1) bands should contain the predictor. The last band should contain the output value to predict.");
+   AddParameter(ParameterType_InputFilename, "io.csv", "Input CSV file");
+@@ -144,7 +144,7 @@
+   //Group Sample list
+   AddParameter(ParameterType_Group, "sample", "Training and validation samples parameters");
+   SetParameterDescription("sample",
+-                          "This group of parameters allows to set training and validation sample lists parameters.");
++                          "This group of parameters allows setting training and validation sample lists parameters.");
+ 
+   AddParameter(ParameterType_Int, "sample.mt", "Maximum training predictors");
+   //MandatoryOff("mt");
+@@ -230,7 +230,7 @@
+           }
+         if (words.size() < 2)
+           {
+-          otbAppLogFATAL(<< "Can't parse CSV file : less than 2 columns or unknonw separator (knowns ones are tab, space, comma and semi-colon)");
++          otbAppLogFATAL(<< "Can't parse CSV file : less than 2 columns or unknown separator (knowns ones are tab, space, comma and semi-colon)");
+           }
+         nbCols = words.size();
+         elem.SetSize(nbCols,false);
+--- otb.orig/Modules/Applications/AppClassification/app/otbPredictRegression.cxx
++++ otb/Modules/Applications/AppClassification/app/otbPredictRegression.cxx
+@@ -141,7 +141,7 @@
+     // TODO : use CSV input/output ?
+ 
+     AddParameter(ParameterType_InputImage,  "mask",   "Input Mask");
+-    SetParameterDescription( "mask", "The mask allows to restrict "
++    SetParameterDescription( "mask", "The mask allow restricting "
+       "classification of the input image to the area where mask pixel values "
+       "are greater than 0.");
+     MandatoryOff("mask");
+--- otb.orig/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.cxx
++++ otb/Modules/Applications/AppClassification/app/otbTrainImagesClassifier.cxx
+@@ -115,7 +115,7 @@
+     "Samples are composed of pixel values in each band optionally centered and reduced using an XML statistics file produced by "
+     "the ComputeImagesStatistics application.\n The training vector data must contain polygons with a positive integer field "
+     "representing the class label. The name of this field can be set using the \"Class label field\" parameter. Training and validation "
+-    "sample lists are built such that each class is equally represented in both lists. One parameter allows to control the ratio "
++    "sample lists are built such that each class is equally represented in both lists. One parameter allows controlling the ratio "
+     "between the number of samples in training and validation sets. Two parameters allow to manage the size of the training and "
+     "validation sets per class and per image.\n Several classifier parameters can be set depending on the chosen classifier. In the "
+     "validation process, the confusion matrix is organized the following way: rows = reference labels, columns = produced labels. "
+@@ -128,7 +128,7 @@
+ 
+   //Group IO
+   AddParameter(ParameterType_Group, "io", "Input and output data");
+-  SetParameterDescription("io", "This group of parameters allows to set input and output data.");
++  SetParameterDescription("io", "This group of parameters allows setting input and output data.");
+   AddParameter(ParameterType_InputImageList, "io.il", "Input Image List");
+   SetParameterDescription("io.il", "A list of input images.");
+   AddParameter(ParameterType_InputVectorDataList, "io.vd", "Input Vector Data List");
+@@ -149,7 +149,7 @@
+   //Group Sample list
+   AddParameter(ParameterType_Group, "sample", "Training and validation samples parameters");
+   SetParameterDescription("sample",
+-                          "This group of parameters allows to set training and validation sample lists parameters.");
++                          "This group of parameters allows setting training and validation sample lists parameters.");
+ 
+   AddParameter(ParameterType_Int, "sample.mt", "Maximum training sample size per class");
+   //MandatoryOff("mt");
+--- otb.orig/Modules/Applications/AppImageUtils/app/otbManageNoData.cxx
++++ otb/Modules/Applications/AppImageUtils/app/otbManageNoData.cxx
+@@ -61,7 +61,7 @@
+     SetDescription("Manage No-Data");
+     // Documentation
+     SetDocName("No Data management");
+-    SetDocLongDescription("This application has two modes. The first allows to build a mask of no-data pixels from the no-data flags read from the image file. The second allows to update the change the no-data value of an image (pixels value and metadata). This last mode also allows to replace NaN in images with a proper no-data value. To do so, one should activate the NaN is no-data option.");
++    SetDocLongDescription("This application has two modes. The first allows building a mask of no-data pixels from the no-data flags read from the image file. The second allows updating the change the no-data value of an image (pixels value and metadata). This last mode also allows replacing NaN in images with a proper no-data value. To do so, one should activate the NaN is no-data option.");
+     SetDocLimitations("None");
+     SetDocAuthors("OTB-Team");
+     SetDocSeeAlso("BanMath");
+--- otb.orig/Modules/Applications/AppSARCalibration/app/otbSarRadiometricCalibration.cxx
++++ otb/Modules/Applications/AppSARCalibration/app/otbSarRadiometricCalibration.cxx
+@@ -49,7 +49,7 @@
+ 
+     // Documentation
+     SetDocName("SAR Radiometric calibration");
+-    SetDocLongDescription("The objective of SAR calibration is to provide imagery in which the pixel values can be directly related to the radar backscatter of the scene. This application allows to compute Sigma Naught (Radiometric Calibration) for TerraSAR-X, Sentinel1 L1 and Radarsat-2 sensors. Metadata are automatically retrieved from image products.The application supports complex and non-complex images (SLC or detected products).\n");
++    SetDocLongDescription("The objective of SAR calibration is to provide imagery in which the pixel values can be directly related to the radar backscatter of the scene. This application allows one to compute Sigma Naught (Radiometric Calibration) for TerraSAR-X, Sentinel1 L1 and Radarsat-2 sensors. Metadata are automatically retrieved from image products.The application supports complex and non-complex images (SLC or detected products).\n");
+     SetDocLimitations("None");
+     SetDocAuthors("OTB-Team");
+     SetDocSeeAlso(" ");
+--- otb.orig/Modules/Applications/AppSARDecompositions/app/otbSARDecompositions.cxx
++++ otb/Modules/Applications/AppSARDecompositions/app/otbSARDecompositions.cxx
+@@ -111,7 +111,7 @@
+     SetParameterDescription("decomp.haa","H-alpha-A decomposition");
+     
+     AddParameter(ParameterType_Group,"inco","Incoherent decompositions");
+-    SetParameterDescription("inco","This group allows to set parameters related to the incoherent decompositions.");
++    SetParameterDescription("inco","This group allows setting parameters related to the incoherent decompositions.");
+     
+     AddParameter(ParameterType_Int, "inco.kernelsize",   "Kernel size for spatial incoherent averaging.");
+     SetParameterDescription("inco.kernelsize", "Minute (0-59)");

-- 
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