V1.1.10

Updating validateInteractiveNormalization to get around edgcase error when running mc.skinPercent(skinCluster, normalize=True) on certain skinClusters.
AKEric · Jun 4, 2024 · a4327b0 · a4327b0
1 parent 7eed643
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Showing 4 changed files with 46 additions and 19 deletions.
diff --git a/skinner/__init__.py b/skinner/__init__.py
@@ -47,9 +47,16 @@
         'weight difference threhold' value.  Changing the default post smooth diff
         value from .01 to .25, to help resolve odd skinning bugs.
     2022-03-31 : v1.1.8 : Bugfixing string formatting error in core -> setWeights.
+    2022-05-18 : v1.1.9 : Updating core.closestPointKdTree to allow numNeighbors=1.
+        Before that it would be auto-set to 2, based on my not understanding how
+        the ndarray return values worked.  Also updating it to support older versions
+        of KDTree that don't have the 'workers' arg.
+    2022-07-18 :  v1.1.10 : Updating validateInteractiveNormalization to get around
+        edgcase error when running mc.skinPercent(skinCluster, normalize=True) on
+        certain skinClusters.
 """
 __author__ = "Eric Pavey"
-__version__ = "1.1.8"
+__version__ = "1.1.10"
 __source__ = "https://github.com/AKEric/skinner"
 __documentation__ = "https://github.com/AKEric/skinner/blob/main/README.md"
 __licence__ = "https://github.com/AKEric/skinner/blob/main/LICENSE.md"
diff --git a/skinner/core.py b/skinner/core.py
@@ -1,6 +1,6 @@
 r"""
 Name : skinner.core.py
-Author : Eric Pavey - [email protected] - https://github.com/AKEric/skinner
+Author : Eric Pavey - [email protected] - www.akeric.com
 Creation Date : 2019-09-28
 Description :
     Import/export skin weights.  It just works, fast.
@@ -87,6 +87,10 @@
        Changing the default post smooth diff value from .01 to .25, to help resolve
        odd skinning bugs.
     2022-03-31 : v1.1.8 : Bugfixing string formatting error in setWeights.
+    2022-05-18 : v1.1.9 : Updating closestPointKdTree to allow numNeighbors=1.
+        Before that it would be auto-set to 2, based on my not understanding how
+        the ndarray return values worked.  Also updating it to support older versions
+        of KDTree that don't have the 'workers' arg.
 
 Examples:
 
@@ -222,11 +226,7 @@ def closestPointKdTree(points:np.ndarray, targets:np.ndarray, numNeighbors:int)
     targets : ndarray[n][3] : All the 3D points being tested against: Their
         order represents the vert index order.  They're what the kdTree is being
         made on;  What originally had weights saved on them.
-    numNeighbors : int : The number of closest neighbors to find/return.  Note
-        that how the KDTree returns its values, if you pass numNeighbors=1 to it,
-        it won't generate the correct type of nested numpy arrays.  Thus, internally,
-        if ther user passes in numNeighbors=1, the code swiches it to numNeighbors=2.
-        Just be aware the return will affected as such.
+    numNeighbors : int : The number of closest neighbors to find/return.
 
     Return : tuple : both are ndarrays of the same length in the vert order of the
         passed in points array.  It is the direct return from KDTree.query()
@@ -244,16 +244,26 @@ def closestPointKdTree(points:np.ndarray, targets:np.ndarray, numNeighbors:int)
         raise ImportError("Unable to import the scipy.spatial module to access the KDTree class")
     if len(targets) < numNeighbors:
         numNeighbors = len(targets)
-    if numNeighbors == 1:
-        # Why? See docstring above.
-        numNeighbors = 2
+
     workers = 1 # The KDTree.query default : Use 1 processor.
     if gMultiThread:
         workers = -1 # use all'dem
     # Build and query a kdTree for our target points, then return the results
     # checking them against our sample points:
     # https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.KDTree.query.html#scipy.spatial.KDTree.query
-    return KDTree(targets).query(points, numNeighbors, workers=workers)
+    try:
+        distances, indexes = KDTree(targets).query(points, numNeighbors, workers=workers)
+    except:
+        # Older versions of KDTree don't support the workers arg.
+        distances, indexes = KDTree(targets).query(points, numNeighbors)
+
+    if numNeighbors == 1:
+        # If we only query one closest distance, numpy will return an array of scalars,
+        # not an array of arrays.  For consistency, we want it to always return
+        # an array of arrays.
+        distances = [[item] for item in distances]
+        indexes = [[item] for item in indexes]
+    return (distances, indexes)
 
 def closestPointBruteForce(points:np.ndarray, targets:np.ndarray, numNeighbors:int) -> tuple:
     r"""
@@ -1971,7 +1981,7 @@ def setWeights(items:list, skinChunks=None, filePath=None, createMissingInfluenc
     # Validation complete
 
     timeStart = time.time()
-    mc.undoInfo(openChunk=True)
+    mc.undoInfo(openChunk=True, chunkName="setWeights")
     try:
         #-------------------------------------------------------------
         # Based on what was proivded to import on, break it down to individual verts:
@@ -2532,7 +2542,7 @@ def setWeights(items:list, skinChunks=None, filePath=None, createMissingInfluenc
                     # To get that, we need to 'unpack' our current weights 'list of sublists':
                     arrayWeights = om2.MDoubleArray([item for item in itertools.chain(*weights)])
 
-                    mc.undoInfo(openChunk=True)
+                    mc.undoInfo(openChunk=True, chunkName="setWeights undoHack")
                     try:
                         # Hack the undo queue: Put in dummy values.
                         inf = infDags[0].fullPathName()

diff --git a/skinner/utils.py b/skinner/utils.py
@@ -1,6 +1,6 @@
 r"""
 Name : skinner.utils.py
-Author : Eric Pavey - [email protected] - https://github.com/AKEric/skinner
+Author : Eric Pavey - [email protected] - www.akeric.com
 Creation Date : 2021-10-23
 Description :
     Various utils/tools used in different Skinner modules.
@@ -17,6 +17,9 @@
     2022-03-03 : v1.1.6 : Updating ProgressWindow to print stack trace if exceptions
         are encountered.  Bugfixing getAtBindPose to skip past skinClusters missing
         connected dagPose nodes.
+    2022-07-18 : v1.1.10 : Updating validateInteractiveNormalization to get around
+        edgcase error when running mc.skinPercent(skinCluster, normalize=True) on
+        certain skinClusters.
 """
 import re
 import os
@@ -264,15 +267,22 @@ def validateInteractiveNormalization(skinClusters:list, promptOnNonInteractiveNo
             print("    ", ni)
         if promptOnNonInteractiveNormalization:
             result = mc.confirmDialog(title="Warning",
-                                      message=f"Found {len(nonInteractive)} skinCluster node(s) that don't have their 'normalizeWeights' set to 'interactive'.\n\nSkinner only supports normalized weights:\n\nDo you want skinner to auto convert your skinClusters to 'interactive' normalization?  If not, the tool will exit.",
+                                      message=f"Found {len(nonInteractive)} skinCluster node(s) that don't have their 'normalizeWeights' set to 'interactive'.\n\nSkinner only supports normalized weights:\n\nDo you want skinner to auto convert your skinClusters to 'interactive' normalization?  If not, the tool will exit.\n\nIf you don't understand what this means, it's generally safe to 'Convert'.",
                                       button=("Convert", "Exit"))
             if result == "Exit":
                 raise Exception("User exited tool based on incompatible skinCluster.normalizeWeight values.")
-            mc.undoInfo(openChunk=True)
+            mc.undoInfo(openChunk=True, chunkName="validateInteractiveNormalization")
             try:
                 for skinCluster in nonInteractive:
                     mc.setAttr(f"{skinCluster}.normalizeWeights", 1) # 0 = none, 1 = interactive, 2 = post
-                    mc.skinPercent(skinCluster, normalize=True) # normalize!
+                    try:
+                        # There ahve been times  Maya has errored here, simply saying
+                        # "No objects found.", and nothing else.  But skipping this
+                        # if it fails seems to be ok,
+                        mc.skinPercent(skinCluster, normalize=True) # normalize!
+                    except:
+                        pass
+                    print("    NORM2 END")
                 print("Skinner: updated the above skinCluster nodes to use 'interactive' weight normalization.")
             finally:
                 mc.undoInfo(closeChunk=True)

diff --git a/skinner/window.py b/skinner/window.py
@@ -1,6 +1,6 @@
 r"""
 Name : skinner.window.py
-Author : Eric Pavey - [email protected] - https://github.com/AKEric/skinner
+Author : Eric Pavey - [email protected] - www.akeric.com
 Creation Date : 2019-09-28
 Description : Window / UI code for the skinner tool.  For the back-end API code,
     see skinner.core.py
@@ -1145,7 +1145,7 @@ def importSkin(self, mode="browser"):
         closestNeighborCount = int(self.widget_nearestNeighborNum.text())
         closestNeighborDistMult = float(self.widget_nearestNeighborDistMult.text())
 
-        mc.undoInfo(openChunk=True)
+        mc.undoInfo(openChunk=True, chunkName="importSkin")
 
         result = core.importSkin(items=None, filePaths=paths, verbose=verbose,
                                  printOverview=printOverview, printOverviewMode=printOverviewMode,