Resolves #168 and #169

scripts/spam-ddic

@@ -566,7 +566,7 @@ if mpiRank == boss or not mpi:
 
     VTKglyphDict = {'displacements': PhiField[:, 0:3, -1],
                     'mag(displacements)': magDisp,
-                    'RS': returnStatus}
+                    'returnStatus': returnStatus}
 
     # if regsub add a line to VTK output and also save separate TSV file
     if args.REGSUB:

tools/deformation/deformationField.py

@@ -746,6 +746,11 @@ def mergeRegularGridAndDiscrete(regularGrid=None, discrete=None, labelledImage=N
             Labelled volume used for discrete computation
             Default = None
 
+        binningLabelled : int
+            Are the labelled images and their PhiField at a different bin level than
+            the regular field?
+            Default = 1
+
         alwaysLabel : bool
             If regularGrid point falls inside the label, should we use the
             label displacement automatically?

tools/helpers/optionsParser.py

@@ -1754,7 +1754,7 @@ def deformImageFromFieldParser(parser):
     parser.add_argument('-cgs',
                         action="store_true",
                         dest='CORRECT_GREY_FOR_STRAIN',
-                        help='Only for field mode: Apply a correction to the greyvalues according to strain in tetrahedon? For a dray sample, greyvalues of vacuum should be =0 (Stavropoulou et al. 2020 Frontiers Eq. 12 with mu_w=0). Default = False')
+                        help='Only for field mode: Apply a correction to the greyvalues according to strain in tetrahedon? For a dry sample, greyvalues of vacuum should be =0 (Stavropoulou et al. 2020 Frontiers Eq. 12 with mu_w=0). Default = False')
 
     args = parser.parse_args()
 

tools/label/contacts.py

@@ -146,6 +146,8 @@ def detectAndFixOversegmentation(lab, nVoxThreshold=25):
     same (lowest) label.
     This is recursive, so a label that is merged is re-treated as a larger
     grain, which is checked again.
+    If any labels have merged, the labels will be discontinuous integers,
+    running spam.label.toolkit.makeLabelsSequential is recommended.
 
     Parameters
     ----------
@@ -160,8 +162,6 @@ def detectAndFixOversegmentation(lab, nVoxThreshold=25):
     --------
         lab : 3D numpy array of ints ( of type spam.label.toolkit.labelType)
             An array of labels with 0 as the background.
-            If any labels have merged, the labels will be discontinuous integers,
-            running spam.label.toolkit.makeLabelsSequential is recommended.
     """
     lab = lab.astype(spam.label.labelType)
     bb = spam.label.boundingBoxes(lab)