Changeset 5348

Timestamp:

Oct 14, 2022 10:56:05 AM (6 months ago)

Author:

vondreele

Message:

fix to cluster analysis plotting

Location:

trunk

Files:

• GSASIIplot.py (modified) (4 diffs)
• GSASIIseqGUI.py (modified) (1 diff)

trunk/GSASIIplot.py

@@ -11620 +11620 @@
     Ndata = len(CLuDict['Files'])
     neighD = [YM[i][i+1] for i in range(Ndata-1)]
+    Codes = copy.copy(CLuDict['codes'])
+    if Codes is not None:
+        Codes = np.where(Codes<0,5,Codes)
     if CLuDict['CLuZ'] is None and CLuDict['plots'] == 'Dendrogram':
         CLuDict['plots'] = 'All'
@@ -11641 +11644 @@
         Plot.set_ylabel('dist to next',fontsize=12)
     elif CLuDict['plots'] == '2D PCA':
-        if CLuDict['codes'] is not None:
+        if Codes is not None:
             for ixyz,xyz in enumerate(XYZ.T):
-                Plot.scatter(xyz[0],xyz[1],color=Colors[CLuDict['codes'][ixyz]],picker=True)
+                Plot.scatter(xyz[0],xyz[1],color=Colors[Codes[ixyz]],picker=True)
         else:
             for ixyz,xyz in enumerate(XYZ.T):
@@ -11651 +11654 @@
         Plot.set_ylabel('PCA axis-2',fontsize=12)
     elif CLuDict['plots'] == '3D PCA':
-        if CLuDict['codes'] is not None:
+        if Codes is not None:
             for ixyz,xyz in enumerate(XYZ.T):
-                Plot.scatter(xyz[0],xyz[1],xyz[2],color=Colors[CLuDict['codes'][ixyz]],picker=True)
+                Plot.scatter(xyz[0],xyz[1],xyz[2],color=Colors[Codes[ixyz]],picker=True)
         else:
             for ixyz,xyz in enumerate(XYZ.T):
@@ -11674 +11677 @@
         ax1.set_xlabel('Data set',fontsize=12)
         ax1.set_ylabel('Data set',fontsize=12)
-        if CLuDict['codes'] is not None:
+        if Codes is not None:
             for ixyz,xyz in enumerate(XYZ.T):
-                ax2.scatter(xyz[0],xyz[1],color=Colors[CLuDict['codes'][ixyz]],picker=True)
+                ax2.scatter(xyz[0],xyz[1],color=Colors[Codes[ixyz]],picker=True)
         else:
             for ixyz,xyz in enumerate(XYZ.T):

trunk/GSASIIseqGUI.py

@@ -1961 +1961 @@
             elif ClusData['OutMethod'] == 'Local Outlier Factor':
                 ClusData['codes'] = SKN.LocalOutlierFactor().fit_predict(ClusData['DataMatrix'])
-            ClusData['codes'] = np.where(ClusData['codes']>0,1,5)       #red(in) or black(out)
             wx.CallAfter(UpdateClusterAnalysis,G2frame,ClusData,shoNum)