diff --git a/neuroglancer_utils/create_datasets/create_full_cube.py b/neuroglancer_utils/create_datasets/create_full_cube.py
new file mode 100644
index 0000000..12d6918
--- /dev/null
+++ b/neuroglancer_utils/create_datasets/create_full_cube.py
@@ -0,0 +1,14 @@
+from cloudvolume import CloudVolume
+import numpy as np
+
+def create_volume(output_path="file://datasets/cube"):
+    rawdata = np.full(shape=(100, 100, 100), fill_value=255.0).astype(np.float32)
+    CloudVolume.from_numpy(
+        rawdata,
+        vol_path=output_path,
+        resolution=(40, 40, 40),
+        chunk_size=(100, 100, 100),
+        layer_type="image",
+        progress=True,
+        compress=False
+    )
\ No newline at end of file
diff --git a/neuroglancer_utils/create_datasets/create_sphere.py b/neuroglancer_utils/create_datasets/create_sphere.py
index 0169e51..626d33d 100644
--- a/neuroglancer_utils/create_datasets/create_sphere.py
+++ b/neuroglancer_utils/create_datasets/create_sphere.py
@@ -20,25 +20,18 @@ def create_sphere_in_cube(size, radius):
     sphere[0 : size // 10, :, :] = 0.5
     sphere[9 * size // 10 :, :, :] = 0.5
 
-    return (sphere.astype(np.float32) * 255.0)
+    return sphere.astype(np.float32) * 255.0
 
 
 def create_volume(output_path="file://datasets/sphere"):
-    info = CloudVolume.create_new_info(
-        num_channels=1,
+    rawdata = create_sphere_in_cube(100, 0.9)
+    #rawdata = np.full(shape=(100, 100, 100), fill_value=255.0).astype(np.float32)
+    CloudVolume.from_numpy(
+        rawdata,
+        vol_path=output_path,
+        resolution=(40, 40, 40),
+        chunk_size=(100, 100, 100),
         layer_type="image",
-        data_type="float32",  # Channel images might be 'uint8'
-        # raw, png, jpeg, compressed_segmentation, fpzip, kempressed, zfpc, compresso, crackle
-        encoding="raw",
-        resolution=[40, 40, 40],  # Voxel scaling, units are in nanometers
-        voxel_offset=[0, 0, 0],  # x,y,z offset in voxels from the origin
-        # Pick a convenient size for your underlying chunk representation
-        # Powers of two are recommended, doesn't need to cover image exactly
-        chunk_size=[100, 100, 100],  # units are voxels
-        volume_size=[100, 100, 100],  # e.g. a cubic millimeter dataset
+        progress=True,
+        compress=False
     )
-    vol = CloudVolume(output_path, info=info)
-    vol.commit_info()
-    rawdata = create_sphere_in_cube(100, 0.9)
-    print(rawdata[30:40])
-    vol[:, :, :] = rawdata[:, :, :]