Fixes for normalization issues

src/mrinufft/operators/interfaces/gpunufft.py

@@ -590,12 +590,12 @@ def pipe(
             The oversampling factor the volume shape
         normalize: bool
             Whether to normalize the density compensation.
-            We normalize such that the energy of PSF = 1
         """
         if GPUNUFFT_AVAILABLE is False:
             raise ValueError(
                 "gpuNUFFT is not available, cannot " "estimate the density compensation"
             )
+        original_shape = volume_shape
         volume_shape = (np.array(volume_shape) * osf).astype(int)
         grid_op = MRIGpuNUFFT(
             samples=kspace_loc,
@@ -607,11 +607,10 @@ def pipe(
             max_iter=num_iterations
         )
         if normalize:
-            spike = np.zeros(volume_shape)
-            mid_loc = tuple(v // 2 for v in volume_shape)
-            spike[mid_loc] = 1
-            psf = grid_op.adj_op(grid_op.op(spike))
-            density_comp /= np.linalg.norm(psf)
+            test_op = MRIGpuNUFFT(samples=kspace_loc, shape=original_shape, **kwargs)
+            test_im = np.ones(original_shape, dtype=np.complex64)
+            test_im_recon = test_op.adj_op(density_comp * test_op.op(test_im))
+            density_comp /= np.mean(np.abs(test_im_recon))
         return density_comp.squeeze()
 
     def get_lipschitz_cst(self, max_iter=10, tolerance=1e-5, **kwargs):