Allow applying weights with relative cic paint

jaxpm/painting.py

@@ -16,6 +16,7 @@ def cic_paint_impl(grid_mesh, positions, weight=None):
     mesh: [nx, ny, nz]
     displacement field: [nx, ny, nz, 3]
     """
+
     positions = positions.reshape([-1, 3])
     positions = jnp.expand_dims(positions, 1)
     floor = jnp.floor(positions)
@@ -26,7 +27,11 @@ def cic_paint_impl(grid_mesh, positions, weight=None):
     kernel = 1. - jnp.abs(positions - neighboor_coords)
     kernel = kernel[..., 0] * kernel[..., 1] * kernel[..., 2]
     if weight is not None:
-        kernel = jnp.multiply(jnp.expand_dims(weight, axis=-1), kernel)
+        if jnp.isscalar(weight):
+            kernel = jnp.multiply(jnp.expand_dims(weight, axis=-1), kernel)
+        else:
+            kernel = jnp.multiply(weight.reshape(*positions.shape[:-1]),
+                                  kernel)
 
     neighboor_coords = jnp.mod(
         neighboor_coords.reshape([-1, 8, 3]).astype('int32'),
@@ -144,14 +149,18 @@ def cic_paint_2d(mesh, positions, weight):
     return mesh
 
 
-def cic_paint_dx_impl(displacements, halo_size):
+def cic_paint_dx_impl(displacements, halo_size, weight=1., chunk_size=2**24):
 
     halo_x, _ = halo_size[0]
     halo_y, _ = halo_size[1]
 
     original_shape = displacements.shape
     particle_mesh = jnp.zeros(original_shape[:-1], dtype='float32')
-
+    if not jnp.isscalar(weight):
+        if weight.shape != original_shape[:-1]:
+            raise ValueError("Weight shape must match particle shape")
+        else:
+            weight = weight.flatten()
     # Padding is forced to be zero in a single gpu run
 
     a, b, c = jnp.meshgrid(jnp.arange(particle_mesh.shape[0]),
@@ -161,18 +170,28 @@ def cic_paint_dx_impl(displacements, halo_size):
 
     particle_mesh = jnp.pad(particle_mesh, halo_size)
     pmid = jnp.stack([a + halo_x, b + halo_y, c], axis=-1)
-    pmid = pmid.reshape([-1, 3])
-    return scatter(pmid, displacements.reshape([-1, 3]), particle_mesh)
+    return scatter(pmid.reshape([-1, 3]),
+                   displacements.reshape([-1, 3]),
+                   particle_mesh,
+                   chunk_size=2**24,
+                   val=weight)
 
 
-@partial(jax.jit, static_argnums=(1, 2))
-def cic_paint_dx(displacements, halo_size=0, sharding=None):
+@partial(jax.jit, static_argnums=(1, 2, 4))
+def cic_paint_dx(displacements,
+                 halo_size=0,
+                 sharding=None,
+                 weight=1.0,
+                 chunk_size=2**24):
 
     halo_size, halo_extents = get_halo_size(halo_size, sharding=sharding)
 
     gpu_mesh = sharding.mesh if sharding is not None else None
     spec = sharding.spec if sharding is not None else P()
-    grid_mesh = autoshmap(partial(cic_paint_dx_impl, halo_size=halo_size),
+    grid_mesh = autoshmap(partial(cic_paint_dx_impl,
+                                  halo_size=halo_size,
+                                  weight=weight,
+                                  chunk_size=chunk_size),
                           gpu_mesh=gpu_mesh,
                           in_specs=spec,
                           out_specs=spec)(displacements)

jaxpm/painting_utils.py

@@ -104,8 +104,7 @@ def _scatter_chunk(carry, chunk):
                        spatial_shape)
     # scatter
     ind = tuple(ind[..., i] for i in range(spatial_ndim))
-    mesh = mesh.at[ind].add(val * frac)
-
+    mesh = mesh.at[ind].add(jnp.multiply(jnp.expand_dims(val, axis=-1), frac))
     carry = mesh, offset, cell_size, mesh_shape
     return carry, None
 
@@ -117,11 +116,9 @@ def scatter(pmid,
             val=1.,
             offset=0,
             cell_size=1.):
-
     ptcl_num, spatial_ndim = pmid.shape
     val = jnp.asarray(val)
     mesh = jnp.asarray(mesh)
-
     remainder, chunks = _chunk_split(ptcl_num, chunk_size, pmid, disp, val)
     carry = mesh, offset, cell_size, mesh.shape
     if remainder is not None: