diff --git a/datasets/noise_free_test_images/estimate_prnu.py b/datasets/noise_free_test_images/estimate_prnu.py
index 3339fd4..ffff323 100644
--- a/datasets/noise_free_test_images/estimate_prnu.py
+++ b/datasets/noise_free_test_images/estimate_prnu.py
@@ -60,10 +60,13 @@ for splitNXNIndex, splitNXN in enumerate(SPLIT_N_X_N_S):
             m = IMAGE_SIZE_SHAPE[1]
             n = IMAGE_SIZE_SHAPE[0]
 
-            imageWithoutPrnuNpArrayTiles = [imageWithoutPrnuNpArray[x : x + m, y : y + n] for x in range(0, imageWithoutPrnuNpArray.shape[0], m) for y in range(0, imageWithoutPrnuNpArray.shape[1], n)]
+            imageWithoutPrnuNpArrayTiles = [imageWithoutPrnuNpArray[x * m : (x + 1) * m, y * n : (y + 1) * n] for x in range(splitNXN) for y in range(splitNXN)]
+            #print(f'{m=} {n=} {0 * m=} {0 * (m + 1)=}')
+            #print([imageWithoutPrnuNpArrayTile.shape for imageWithoutPrnuNpArrayTile in imageWithoutPrnuNpArrayTiles])
             for imageWithoutPrnuNpArrayTile in imageWithoutPrnuNpArrayTiles:
                 #print(imageWithoutPrnuNpArrayTile.shape, tuple(IMAGE_SIZE_SHAPE[::-1]))
                 #if imageWithoutPrnuNpArrayTile.shape != tuple(IMAGE_SIZE_SHAPE[::-1]):
+                #    exit(1)
                 #    continue
                 imageNoise = randomGaussianImage(scale = 255 * NOISE_FACTOR, size = imageWithoutPrnuNpArrayTile.shape)
                 imageWithPrnuNpArray = imageWithoutPrnuNpArrayTile + prnuNpArray + imageNoise
@@ -80,8 +83,8 @@ for splitNXNIndex, splitNXN in enumerate(SPLIT_N_X_N_S):
                     axis[2].set_title('First image with Gaussian noise\nClipped between 0 and 255')
                     axisImShow(axis[2], np.clip(imageWithoutPrnuNpArray + imageNoise, 0, 255))
 
-                    axis[3].set_title('Actual Gaussian noised PRNU\nClipped between -1 and 1')
-                    axisImShow(axis[3], np.clip(prnuNpArray, -1, 1))
+                    axis[3].set_title('Actual Gaussian noised PRNU')
+                    axisImShow(axis[3], prnuNpArray)
 
                     axes[1][0].set_title('First image with Gaussian noise and PRNU\nClipped between 0 and 255')
                     axisImShow(axes[1][0], np.clip(imageWithoutPrnuNpArray + prnuNpArray + imageNoise, 0, 255))
diff --git a/datasets/raise/fft/verify_dots.py b/datasets/raise/fft/verify_dots.py
index db1f468..563bddb 100644
--- a/datasets/raise/fft/verify_dots.py
+++ b/datasets/raise/fft/verify_dots.py
@@ -11,7 +11,7 @@ from utils import isARawImage, Color, getColorChannel, mergeSingleColorChannelIm
 FOLDERS = {
     'Rafael 23/04/24': '../rafael/230424',
     'RAISE flat-field': '../flat-field/nef',
-    'RAISE not flat-field': '../not_flat-field/nef',
+    'RAISE non-flat-field': '../non-flat-field/nef',
 }
 
 def getImageMergedColorChannels(filePath):
@@ -41,8 +41,8 @@ estimatedPrnus = {folderName: getEstimatedPrnu(folder) for folderName, folder in
 print(f'{corr(estimatedPrnus["Rafael 23/04/24"], estimatedPrnus["Rafael 23/04/24"])=}')
 print(f'{corr(estimatedPrnus["Rafael 23/04/24"], estimatedPrnus["RAISE flat-field"])=}')
 print(f'{corr(estimatedPrnus["RAISE flat-field"], estimatedPrnus["Rafael 23/04/24"])=}')
-print(f'{corr(estimatedPrnus["Rafael 23/04/24"], estimatedPrnus["RAISE not flat-field"])=}')
-print(f'{corr(estimatedPrnus["RAISE flat-field"], estimatedPrnus["RAISE not flat-field"])=}')
+print(f'{corr(estimatedPrnus["Rafael 23/04/24"], estimatedPrnus["RAISE non-flat-field"])=}')
+print(f'{corr(estimatedPrnus["RAISE flat-field"], estimatedPrnus["RAISE non-flat-field"])=}')
 
 plt.imshow(estimatedPrnus['RAISE flat-field'])
 plt.show()
\ No newline at end of file