Format

jaxpm/painting.py

@@ -222,8 +222,7 @@ def cic_read_dx_impl(grid_mesh, disp, halo_size):
     pmid = pmid.reshape([-1, 3])
     disp = disp.reshape([-1, 3])
 
-    return gather(pmid, disp,
+    return gather(pmid, disp, grid_mesh).reshape(original_shape)
-                  grid_mesh).reshape(original_shape)
 
 
 @partial(jax.jit, static_argnums=(2, 3))

jaxpm/painting_utils.py

@@ -25,12 +25,15 @@ def _chunk_split(ptcl_num, chunk_size, *arrays):
     return remainder, chunks
 
 
-def enmesh(base_indices, displacements, cell_size, base_shape, offset, new_cell_size, new_shape):
+def enmesh(base_indices, displacements, cell_size, base_shape, offset,
+           new_cell_size, new_shape):
     """Multilinear enmeshing."""
     base_indices = jnp.asarray(base_indices)
     displacements = jnp.asarray(displacements)
     with jax.experimental.enable_x64():
-        cell_size = jnp.float64(cell_size) if new_cell_size is not None else jnp.array(cell_size, dtype=displacements.dtype)
+        cell_size = jnp.float64(
+            cell_size) if new_cell_size is not None else jnp.array(
+                cell_size, dtype=displacements.dtype)
         if base_shape is not None:
             base_shape = jnp.array(base_shape, dtype=base_indices.dtype)
         offset = jnp.float64(offset)
@@ -40,12 +43,14 @@ def enmesh(base_indices, displacements, cell_size, base_shape, offset, new_cell_
             new_shape = jnp.array(new_shape, dtype=base_indices.dtype)
 
     spatial_dim = base_indices.shape[1]
-    neighbor_offsets = (jnp.arange(2**spatial_dim, dtype=base_indices.dtype)[:, jnp.newaxis] >>
+    neighbor_offsets = (
+        jnp.arange(2**spatial_dim, dtype=base_indices.dtype)[:, jnp.newaxis] >>
         jnp.arange(spatial_dim, dtype=base_indices.dtype)) & 1
 
     if new_cell_size is not None:
         particle_positions = base_indices * cell_size + displacements - offset
-        particle_positions = particle_positions[:, jnp.newaxis]  # insert neighbor axis
+        particle_positions = particle_positions[:, jnp.
+                                                newaxis]  # insert neighbor axis
         new_indices = particle_positions + neighbor_offsets * new_cell_size  # multilinear
 
         if base_shape is not None:
@@ -56,7 +61,9 @@ def enmesh(base_indices, displacements, cell_size, base_shape, offset, new_cell_
         new_displacements = particle_positions - new_indices * new_cell_size
 
         if base_shape is not None:
-            new_displacements -= jnp.rint(new_displacements / grid_length) * grid_length  # also abs(new_displacements) < new_cell_size is expected
+            new_displacements -= jnp.rint(
+                new_displacements / grid_length
+            ) * grid_length  # also abs(new_displacements) < new_cell_size is expected
 
         new_indices = new_indices.astype(base_indices.dtype)
         new_displacements = new_displacements.astype(displacements.dtype)

jaxpm/pm.py

@@ -1,9 +1,7 @@
-
 import jax.numpy as jnp
 import jax_cosmo as jc
 
-from jaxpm.distributed import (fft3d, ifft3d,
+from jaxpm.distributed import fft3d, ifft3d, normal_field
-                               normal_field)
 from jaxpm.growth import (dGf2a, dGfa, growth_factor, growth_factor_second,
                           growth_rate, growth_rate_second)
 from jaxpm.kernels import (PGD_kernel, fftk, gradient_kernel,
@@ -27,7 +25,8 @@ def pm_forces(positions,
         mesh_shape = delta.shape
 
     if paint_absolute_pos:
-        paint_fn = lambda pos: cic_paint(jnp.zeros(shape=mesh_shape , device=sharding),
+        paint_fn = lambda pos: cic_paint(jnp.zeros(shape=mesh_shape,
+                                                   device=sharding),
                                          pos,
                                          halo_size=halo_size,
                                          sharding=sharding)
@@ -72,7 +71,8 @@ def lpt(cosmo,
     """
     paint_absolute_pos = particles is not None
     if particles is None:
-        particles = jnp.zeros_like(initial_conditions , shape=(*initial_conditions.shape , 3))
+        particles = jnp.zeros_like(initial_conditions,
+                                   shape=(*initial_conditions.shape, 3))
 
     a = jnp.atleast_1d(a)
     E = jnp.sqrt(jc.background.Esqr(cosmo, a))
@@ -172,7 +172,8 @@ def make_ode_fn(mesh_shape,
     return nbody_ode
 
 
-def make_diffrax_ode(cosmo, mesh_shape,
+def make_diffrax_ode(cosmo,
+                     mesh_shape,
                      paint_absolute_pos=True,
                      halo_size=0,
                      sharding=None):
@@ -199,6 +200,7 @@ def make_diffrax_ode(cosmo, mesh_shape,
 
     return nbody_ode
 
+
 def pgd_correction(pos, mesh_shape, params):
     """
     improve the short-range interactions of PM-Nbody simulations with potential gradient descent method,

jaxpm/utils.py

@@ -5,7 +5,6 @@ import numpy as np
 from jax.scipy.stats import norm
 from scipy.special import legendre
 
-
 __all__ = [
     'power_spectrum', 'transfer', 'coherence', 'pktranscoh',
     'cross_correlation_coefficients', 'gaussian_smoothing'

notebooks/05-MultiHost_PM.py

@@ -18,7 +18,7 @@ import numpy as np
 from diffrax import (ConstantStepSize, Dopri5, LeapfrogMidpoint, ODETerm,
                      PIDController, SaveAt, diffeqsolve)
 from jax.experimental.mesh_utils import create_device_mesh
-from jax.experimental.multihost_utils import (process_allgather)
+from jax.experimental.multihost_utils import process_allgather
 from jax.sharding import Mesh, NamedSharding
 from jax.sharding import PartitionSpec as P
 

tests/conftest.py

@@ -1,6 +1,8 @@
 # Parameterized fixture for mesh_shape
 import os
+
 import pytest
+
 os.environ["EQX_ON_ERROR"] = "nan"
 setup_done = False
 on_cluster = False
@@ -10,6 +12,7 @@ def is_on_cluster():
     global on_cluster
     return on_cluster
 
+
 def initialize_distributed():
     global setup_done
     global on_cluster
@@ -26,25 +29,16 @@ def initialize_distributed():
             setup_done = True
             on_cluster = False
             os.environ["JAX_PLATFORM_NAME"] = "cpu"
-      os.environ["XLA_FLAGS"] = "--xla_force_host_platform_device_count=8"
+            os.environ[
+                "XLA_FLAGS"] = "--xla_force_host_platform_device_count=8"
             import jax
 
 
-@pytest.fixture(scope="session", autouse=True)
-def setup_and_teardown_session():
-  # Code to run at the start of the session
-  print("Starting session...")
-  initialize_distributed()
-  # Setup code here
-  # e.g., connecting to a database, initializing some resources, etc.
-
-
-
 @pytest.fixture(
     scope="session",
     params=[
-        ((64, 64, 64) , (512., 512., 512.)),  # BOX
+        ((32, 32, 32), (256., 256., 256.)),  # BOX
-        ((64, 64, 128) , (256. , 256. , 512.)), # RECTANGULAR
+        ((32, 32, 64), (256., 256., 512.)),  # RECTANGULAR
     ])
 def simulation_config(request):
     return request.param
@@ -55,11 +49,11 @@ def lpt_scale_factor(request):
     return request.param
 
 
-
 @pytest.fixture(scope="session")
 def cosmo():
-    from jax_cosmo import Cosmology
     from functools import partial
+
+    from jax_cosmo import Cosmology
     Planck18 = partial(
         Cosmology,
         # Omega_m = 0.3111
@@ -85,9 +79,9 @@ def particle_mesh(simulation_config):
 
 @pytest.fixture(scope="session")
 def fpm_initial_conditions(cosmo, particle_mesh):
-    from jax import numpy as jnp
     import jax_cosmo as jc
     import numpy as np
+    from jax import numpy as jnp
 
     # Generate initial particle positions
     grid = particle_mesh.generate_uniform_particle_grid(shift=0).astype(
@@ -117,7 +111,8 @@ def initial_conditions(fpm_initial_conditions):
 
 @pytest.fixture(scope="session")
 def solver(cosmo, particle_mesh):
-    from fastpm.core import Solver, Cosmology as FastPMCosmology
+    from fastpm.core import Cosmology as FastPMCosmology
+    from fastpm.core import Solver
     ref_cosmo = FastPMCosmology(cosmo)
     return Solver(particle_mesh, ref_cosmo, B=1)
 
@@ -150,8 +145,8 @@ def fpm_lpt2_field(fpm_lpt2, particle_mesh):
 
 @pytest.fixture(scope="session")
 def nbody_from_lpt1(solver, fpm_lpt1, particle_mesh, lpt_scale_factor):
-    from fastpm.core import  leapfrog
     import numpy as np
+    from fastpm.core import leapfrog
 
     if lpt_scale_factor == 0.8:
         pytest.skip("Do not run nbody simulation from scale factor 0.8")
@@ -166,8 +161,8 @@ def nbody_from_lpt1(solver, fpm_lpt1, particle_mesh, lpt_scale_factor):
 
 @pytest.fixture(scope="session")
 def nbody_from_lpt2(solver, fpm_lpt2, particle_mesh, lpt_scale_factor):
-    from fastpm.core import  leapfrog
     import numpy as np
+    from fastpm.core import leapfrog
 
     if lpt_scale_factor == 0.8:
         pytest.skip("Do not run nbody simulation from scale factor 0.8")

tests/helpers.py

@@ -1,10 +1,13 @@
 import jax.numpy as jnp
 
+
 def MSE(x, y):
     return jnp.mean((x - y)**2)
 
+
 def MSE_3D(x, y):
     return ((x - y)**2).mean(axis=0)
 
+
 def MSRE(x, y):
     return jnp.mean(((x - y) / y)**2)