DOC: fix multi example

Documentation/Cookbook/Scripts/otbGenerateWrappersRstDoc.py

@@ -29,8 +29,6 @@ from otbApplication import ParameterType_Bool, ParameterType_Int, ParameterType_
 from otb_warnings import application_documentation_warnings
 
 linesep = os.linesep
-pixeltypes = {' uchar' : 1, ' int8' : 0, ' uint8' : 1, ' int16' : 2, ' uint16': 3, ' int32' : 4, ' uint32' : 5, ' float' : 6, ' double': 7}
-
 
 def EncloseString(s):
     if not s.startswith("\"") :
@@ -54,6 +52,7 @@ def ExpandPath(filename,path,exp):
         return os.path.join(path,filename)
 
 def GetPixelType(value):
+    pixeltypes = {' uchar' : 1, ' int8' : 0, ' uint8' : 1, ' int16' : 2, ' uint16': 3, ' int32' : 4, ' uint32' : 5, ' float' : 6, ' double': 7}
     # look for type
     foundcode = -1
     foundname = ""
@@ -64,38 +63,16 @@ def GetPixelType(value):
             break
     return foundcode,foundname
 
-def render_choice(app, key):
-    "Render a choice parameter to rst"
-
-    # First render all the choice values
-    choice_keys = app.GetChoiceKeys(key)
-    choice_names = app.GetChoiceNames(key)
-
-    choice_entries = ""
-    for (choice_key, choice_name) in zip(choice_keys, choice_names):
-        # For the description, replace newlines by |br| because we are in a bullet list item
-        choice_description = app.GetParameterDescription(key + "." + choice_key).replace("\n", " |br| ")
-        choice_entries += template_parameter_choice_entry.format(
-            name=choice_name,
-            #key=choice_key, # if we want to show the key in choice parameter values
-            description=choice_description
-        )
-
-    # Then render the full choice parameter
-    return template_parameter_choice.format(
-        name=app.GetParameterName(key),
-        key=key,
-        value="[" + "|".join(choice_keys) + "]",
-        flags=rst_parameter_flags(app, key),
-        description=app.GetParameterDescription(key),
-        choices=choice_entries,
-    )
-
 def GetApplicationExamplePythonSnippet(app,idx,expand = False, inputpath="",outputpath=""):
     appname = "app"
-
     output = ""
 
+    # Render example comment
+    if len(app.GetExampleComment(idx)) > 0:
+        output += app.GetExampleComment(idx) + ":\n\n"
+
+    output += ".. code-block:: python\n\n"
+
     output+= "\timport otbApplication" + linesep + linesep
     output+= "\t" + appname + " = otbApplication.Registry.CreateApplication(\"" + app.GetName() + "\")" + linesep + linesep
     for i in range(0, app.GetExampleNumberOfParameters(idx)):
@@ -172,9 +149,36 @@ def GetApplicationExamplePythonSnippet(app,idx,expand = False, inputpath="",outp
             output += "\t" + appname + ".SetParameterStringList("+EncloseString(param)+ ", " + str(values) + ")"
         output+=linesep
     output += linesep
-    output+= "\t" + appname + ".ExecuteAndWriteOutput()"+ linesep
+    output+= "\t" + appname + ".ExecuteAndWriteOutput()" + linesep + linesep
     return output
 
+def render_choice(app, key):
+    "Render a choice parameter to rst"
+
+    # First render all the choice values
+    choice_keys = app.GetChoiceKeys(key)
+    choice_names = app.GetChoiceNames(key)
+
+    choice_entries = ""
+    for (choice_key, choice_name) in zip(choice_keys, choice_names):
+        # For the description, replace newlines by |br| because we are in a bullet list item
+        choice_description = app.GetParameterDescription(key + "." + choice_key).replace("\n", " |br| ")
+        choice_entries += template_parameter_choice_entry.format(
+            name=choice_name,
+            #key=choice_key, # if we want to show the key in choice parameter values
+            description=choice_description
+        )
+
+    # Then render the full choice parameter
+    return template_parameter_choice.format(
+        name=app.GetParameterName(key),
+        key=key,
+        value="[" + "|".join(choice_keys) + "]",
+        flags=rst_parameter_flags(app, key),
+        description=app.GetParameterDescription(key),
+        choices=choice_entries,
+    )
+
 def rst_section(text, delimiter, ref=None):
     "Make a rst section title"
 
@@ -235,22 +239,22 @@ def detect_abuse(app):
 
     fake_groups = {}
     keys = app.GetParametersKeys()
+    choice_keys = [k for k in keys if app.GetParameterType(k) == ParameterType_Choice]
 
     # For each choice parameter
-    for key in keys:
-        if app.GetParameterType(key) == ParameterType_Choice:
+    for key in choice_keys:
 
-            # Consider all its possible values
-            for choice_key in app.GetChoiceKeys(key):
-                fullkey = key + "." + choice_key
+        # Consider all its possible values
+        for choice_key in app.GetChoiceKeys(key):
+            fullkey = key + "." + choice_key
 
-                # See if that value is also used as a group anywhere in the application
-                for k in keys:
-                    if k.startswith(fullkey) and k != fullkey:
+            # See if that value is also used as a group anywhere in the application
+            for k in keys:
+                if k.startswith(fullkey) and k != fullkey:
 
-                        # In that case, mark the first element of that group
-                        if fullkey not in fake_groups.values():
-                            fake_groups[k] = fullkey
+                    # In that case, mark the first element of that group
+                    if fullkey not in fake_groups.values():
+                        fake_groups[k] = fullkey
 
     return fake_groups
 

Documentation/Cookbook/Scripts/otb_warnings.py

@@ -20,8 +20,8 @@ def parameter_warnings(app_warn, app, key):
     #if description == "":
         #warn("missing description")
 
-    #if len(description) > 0 and description[-1] != ".":
-        #warn("description does not end with a period")
+    if len(description) > 0 and description[-1] != ".":
+        warn("description does not end with a period")
 
     if len(description) > 0 and " :" in description:
         warn("description has a space before a colon")

Documentation/Cookbook/rst/templates/application.rst

@@ -32,8 +32,6 @@ From the command-line:
 
 From Python:
 
-.. code-block:: python
-
 {examples_python}
 
 {limitations}

Modules/Applications/AppSegmentation/app/otbSegmentation.cxx

@@ -144,18 +144,24 @@ private:
 
     // Documentation
     SetDocName("Segmentation");
-    SetDocLongDescription("This application allows one to perform various segmentation algorithms on a multispectral image."
-                          "Available segmentation algorithms are two different versions of Mean-Shift segmentation algorithm (one being multi-threaded),"
-                          " simple pixel based connected components according to a user-defined criterion, and watershed from the gradient of the intensity"
-                          " (norm of spectral bands vector). The application has two different modes that affects the nature of its output.\n\nIn raster mode,"
-                          " the output of the application is a classical image of unique labels identifying the segmented regions. The labeled output can be passed to the"
-                          " ColorMapping application to render regions with contrasted colours. Please note that this mode loads the whole input image into memory, and as such"
-                          " can not handle large images. \n\n To segment large data, one can use the vector mode. In this case, the output of the application is a"
-                          " vector file or database. The input image is split into tiles (whose size can be set using the tilesize parameter), and each tile is loaded, segmented"
-                          " with the chosen algorithm, vectorized, and written into the output file or database. This piece-wise behavior ensure that memory will never get overloaded,"
-                          " and that images of any size can be processed. There are few more options in the vector mode. The simplify option allows simplifying the geometry"
-                          " (i.e. remove nodes in polygons) according to a user-defined tolerance. The stitch option tries to stitch together the polygons corresponding"
-                          " to segmented region that may have been split by the tiling scheme. ");
+    SetDocLongDescription(
+        "This application allows one to perform various segmentation algorithms on a multispectral image."
+        " Available segmentation algorithms are two different versions of Mean-Shift segmentation algorithm (one being multi-threaded),"
+        " simple pixel based connected components according to a user-defined criterion, and watershed from the gradient of the intensity"
+        " (norm of spectral bands vector). The application has two different modes that affects the nature of its output.\n\n"
+
+        "In raster mode, the output of the application is a classical image of unique labels identifying the segmented regions. The labeled output can be "
+        "passed to the"
+        " ColorMapping application to render regions with contrasted colours. Please note that this mode loads the whole input image into memory, and as such"
+        " can not handle large images.\n\n"
+
+        "To segment large data, one can use the vector mode. In this case, the output of the application is a"
+        " vector file or database. The input image is split into tiles (whose size can be set using the tilesize parameter), and each tile is loaded, segmented"
+        " with the chosen algorithm, vectorized, and written into the output file or database. This piece-wise behavior ensure that memory will never get"
+        " overloaded, and that images of any size can be processed. There are few more options in the vector mode. The simplify option allows simplifying the "
+        "geometry"
+        " (i.e. remove nodes in polygons) according to a user-defined tolerance. The stitch option tries to stitch together the polygons corresponding"
+        " to segmented region that may have been split by the tiling scheme. ");
 
     SetDocLimitations("In raster mode, the application can not handle large input images. Stitching step of vector mode might become slow with very large input images."
                      " \nMeanShift filter results depends on the number of threads used. \nWatershed and multiscale geodesic morphology segmentation will be performed on the amplitude "