diff --git a/.vscode/settings.json b/.vscode/settings.json
index d35c5419942948e9f9dccac24c74e65b78fc296f..de288e1eab6a537caed290ce0fc5e70be7ae9dba 100644
--- a/.vscode/settings.json
+++ b/.vscode/settings.json
@@ -1,12 +1,3 @@
 {
-    "python.formatting.provider": "black",
-    "python.testing.unittestArgs": [
-        "-v",
-        "-s",
-        "./tests",
-        "-p",
-        "test*.py"
-    ],
-    "python.testing.pytestEnabled": false,
-    "python.testing.unittestEnabled": true
+    "python.formatting.provider": "black"
 }
\ No newline at end of file
diff --git a/PyNutil/processing/counting_and_load.py b/PyNutil/processing/counting_and_load.py
index f7498e2640ab255965e8052b2017e2f463f49197..a22601713b1cb33644658767becccb430e046a48 100644
--- a/PyNutil/processing/counting_and_load.py
+++ b/PyNutil/processing/counting_and_load.py
@@ -209,10 +209,7 @@ def warp_image(image, triangulation, rescaleXY):
     newY[newY >= reg_h] = reg_h - 1
     newX[newX < 0] = 0
     newY[newY < 0] = 0
-    new_image = np.zeros_like(image)
-    mask = (newX <= reg_w) & (newY <= reg_h) & (newX > 0) & (newY > 0)
-    new_image[mask] = image[mask]
-    new_image[~mask] = 0
+    new_image = image[newY, newX]
     return new_image
 
 
@@ -227,8 +224,14 @@ def flat_to_dataframe(
     if (image_vector is not None) and (volume is not None):
         image = generate_target_slice(image_vector, volume)
         image = np.float64(image)
+        random_number = np.random.randint(0,1000)
+        outim = ((image==0) * 255).astype(np.uint8)
+        cv2.imwrite(f"{random_number}_linear.jpg",  outim)
         if triangulation is not None:
             image = warp_image(image, triangulation, rescaleXY)
+            outim = ((image==0) * 255).astype(np.uint8)
+
+            cv2.imwrite(f"{random_number}_warped.jpg", outim)
     elif file.endswith(".flat"):
         image = read_flat_file(file)
     elif file.endswith(".seg"):
diff --git a/workflows/127_linear.jpg b/workflows/127_linear.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..a71a4a447750e4a9c20bbc4ba46082fab4b49263
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diff --git a/workflows/127_warped.jpg b/workflows/127_warped.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..d17c913968813f085986ba905824e5ca417d6584
Binary files /dev/null and b/workflows/127_warped.jpg differ
diff --git a/workflows/131_linear.jpg b/workflows/131_linear.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..ef7546274d1b8fdeab1e49661cb1ff8dca6f59b4
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diff --git a/workflows/519_linear.jpg b/workflows/519_linear.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..9525247bb716978cbebf104e6b0422fbed9f3dfa
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diff --git a/workflows/519_warped.jpg b/workflows/519_warped.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..fa1e72db8526ecbbe500b8062a8f8670a9a6bb3d
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diff --git a/workflows/741_linear.jpg b/workflows/741_linear.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..689f856749704bee52219aebb3be78f06eca06df
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diff --git a/workflows/741_warped.jpg b/workflows/741_warped.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..d6123c809124dac3e768401e09e8674f441cba1f
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diff --git a/workflows/886_linear.jpg b/workflows/886_linear.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..5acba6e9f5825c2a1b54cc1226445b68ea699d5f
Binary files /dev/null and b/workflows/886_linear.jpg differ
diff --git a/workflows/886_warped.jpg b/workflows/886_warped.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..f08b0f532031a120dc7ba5e35d073bc69e15283c
Binary files /dev/null and b/workflows/886_warped.jpg differ
diff --git a/workflows/basic_example_custom_atlas.py b/workflows/basic_example_custom_atlas.py
index 78bdf9705413828b56a2d8a2e77f5ef18f351169..c42727d376028067f8140cbbb8c8e6e199ee4031 100644
--- a/workflows/basic_example_custom_atlas.py
+++ b/workflows/basic_example_custom_atlas.py
@@ -13,14 +13,15 @@ from PyNutil import PyNutil
 ###The label_path is the path to the corresponding atlas .csv
 ###The object_cutoff is a cut-off for min object size
 ### get_coordinates, if use_flat=True, place flat files in folder titled "flat_files" at same level as "segmentations" folder 
+#This does not use BrainGlobe API.
 
 pnt = PyNutil(
-    segmentation_folder="../tests/test_data/linear_allen_mouse/",
-    alignment_json="../tests/test_data/linear_allen_mouse/alignment_linear.json",
+    segmentation_folder="../tests/test_data/nonlinear_allen_mouse/",
+    alignment_json="../tests/test_data/nonlinear_allen_mouse/alignment.json",
     colour=[0, 0, 0],
     atlas_path="../tests/test_data/allen_mouse_2017_atlas/annotation_25_reoriented_2017.nrrd",
     label_path="../tests/test_data/allen_mouse_2017_atlas//allen2017_colours.csv",
 )
 pnt.get_coordinates(object_cutoff=0, use_flat=False)
 pnt.quantify_coordinates()
-pnt.save_analysis("../test_result/test_linear_allen_mouse")
+pnt.save_analysis("../test_result/test_nonlinear_allen_mouse_noflat_24_02_25")