removed plotSimple

Author: sridhs21

XPointMLTest.py

@@ -59,25 +59,16 @@ def expand_xpoints_mask(binary_mask, kernel_size=9):
 
     return expanded_mask
 
-def plotSimple(arr, outfile):
-    plt.imshow(arr, interpolation="nearest", origin="upper")
-    plt.colorbar()
-    plt.savefig(outfile)
-    plt.clf()
-
 def rotate(frameData,deg):
     if deg not in [90, 180, 270]:
         print(f"invalid rotation specified... exiting")
         sys.exit()
+        
     psi = v2.functional.rotate(frameData["psi"], deg, v2.InterpolationMode.BILINEAR)
     all = v2.functional.rotate(frameData["all"], deg, v2.InterpolationMode.BILINEAR)
-
-    plotSimple(all[0], f"{frameData['fnum']}_rotation{deg}_all0.png")
-    plotSimple(all[1], f"{frameData['fnum']}_rotation{deg}_all1.png")
-    plotSimple(all[2], f"{frameData['fnum']}_rotation{deg}_all2.png")
-    plotSimple(all[3], f"{frameData['fnum']}_rotation{deg}_all3.png")
-    
+    # For mask, use nearest neighbor interpolation to preserve binary values
     mask = v2.functional.rotate(frameData["mask"], deg, v2.InterpolationMode.NEAREST)
+    
     return {
         "fnum": frameData["fnum"],
         "rotation": deg,
@@ -100,12 +91,6 @@ def reflect(frameData,axis):
     all = torch.flip(frameData["all"], dims=(axis+1,))
     mask = torch.flip(frameData["mask"], dims=(axis+1,))
 
-    plotSimple(all[0], f"{frameData['fnum']}_reflectionAxis{axis}_all0.png")
-    plotSimple(all[1], f"{frameData['fnum']}_reflectionAxis{axis}_all1.png")
-    plotSimple(all[2], f"{frameData['fnum']}_reflectionAxis{axis}_all2.png")
-    plotSimple(all[3], f"{frameData['fnum']}_reflectionAxis{axis}_all3.png")
-    
-    
     return {
         "fnum": frameData["fnum"],
         "rotation": 0,
@@ -278,10 +263,6 @@ def load(self, fnum):
         by_torch = torch.from_numpy(fields["By"]).float().unsqueeze(0)
         jz_torch = torch.from_numpy(fields["Jz"]).float().unsqueeze(0)
         all_torch = torch.cat((psi_torch,bx_torch,by_torch,jz_torch)) # [4, Nx, Ny]
-        plotSimple(all_torch[0], f"{fnum}_all0.png")
-        plotSimple(all_torch[1], f"{fnum}_all1.png")
-        plotSimple(all_torch[2], f"{fnum}_all2.png")
-        plotSimple(all_torch[3], f"{fnum}_all3.png")
         mask_torch = torch.from_numpy(binaryMap).float().unsqueeze(0)  # [1, Nx, Ny]
 
         if self.verbosity > 0: