diff --git a/src/mpol/images.py b/src/mpol/images.py
index b0f9b2dc..5090fd6a 100644
--- a/src/mpol/images.py
+++ b/src/mpol/images.py
@@ -315,40 +315,4 @@ def to_FITS(self, fname="cube.fits", overwrite=False, header_kwargs=None):
         hdul = fits.HDUList([hdu])
         hdul.writeto(fname, overwrite=overwrite)
 
-        hdul.close()
-
-
-def np_to_imagecube(image, coords, nchan=1, wrap=False):
-    """Convenience function for converting a numpy image into an MPoL ImageCube 
-    tensor (see mpol.images.ImageCube)
-
-    Parameters
-    ----------
-    image : array
-        An image in numpy format
-    coords : `mpol.coordinates.GridCoords` object
-        Instance of the `mpol.coordinates.GridCoords` class
-    nchan : int, default=1
-        Number of channels in the image. Default assumes a single 2D image
-    wrap : bool, default=False 
-        Whether to wrap the numpy image so that index 0 is in the image center
-        (FFT algorithms typically place index 0 in the image corner)
-
-    Returns
-    -------
-    icube : `mpol.images.ImageCube` object
-        The image cube tensor
-    """
-    if wrap: 
-        # move the 0 index to the image center 
-        image = utils.center_np_image(image)
-
-    # broadcast image to (nchan, npix, npix)
-    img_packed_cube = np.broadcast_to(image, 
-                                      (nchan, coords.npix, coords.npix)).copy()
-
-    # convert to pytorch tensor
-    img_packed_tensor = torch.from_numpy(img_packed_cube)
-
-    # insert into ImageCube layer
-    return ImageCube(coords=coords, nchan=nchan, cube=img_packed_tensor)
+        hdul.close()
\ No newline at end of file