# Parameterized fixture for mesh_shape import os import pytest os.environ["EQX_ON_ERROR"] = "nan" setup_done = False on_cluster = False def is_on_cluster(): global on_cluster return on_cluster def initialize_distributed(): global setup_done global on_cluster if not setup_done: if "SLURM_JOB_ID" in os.environ: on_cluster = True print("Running on cluster") import jax jax.distributed.initialize() setup_done = True on_cluster = True else: print("Running locally") setup_done = True on_cluster = False os.environ["JAX_PLATFORM_NAME"] = "cpu" os.environ[ "XLA_FLAGS"] = "--xla_force_host_platform_device_count=8" import jax @pytest.fixture( scope="session", params=[ ((32, 32, 32), (256., 256., 256.)), # BOX ((32, 32, 64), (256., 256., 512.)), # RECTANGULAR ]) def simulation_config(request): return request.param @pytest.fixture(scope="session", params=[0.1, 0.5, 0.8]) def lpt_scale_factor(request): return request.param @pytest.fixture(scope="session") def cosmo(): from functools import partial from jax_cosmo import Cosmology Planck18 = partial( Cosmology, # Omega_m = 0.3111 Omega_c=0.2607, Omega_b=0.0490, Omega_k=0.0, h=0.6766, n_s=0.9665, sigma8=0.8102, w0=-1.0, wa=0.0, ) return Planck18() @pytest.fixture(scope="session") def particle_mesh(simulation_config): from pmesh.pm import ParticleMesh mesh_shape, box_shape = simulation_config return ParticleMesh(BoxSize=box_shape, Nmesh=mesh_shape, dtype='f4') @pytest.fixture(scope="session") def fpm_initial_conditions(cosmo, particle_mesh): 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( np.float32) # Interpolate with linear_matter spectrum to get initial density field k = jnp.logspace(-4, 1, 128) pk = jc.power.linear_matter_power(cosmo, k) def pk_fn(x): return jnp.interp(x.reshape([-1]), k, pk).reshape(x.shape) whitec = particle_mesh.generate_whitenoise(42, type='complex', unitary=False) lineark = whitec.apply(lambda k, v: pk_fn(sum(ki**2 for ki in k)**0.5)**0.5 * v * (1 / v.BoxSize).prod()**0.5) init_mesh = lineark.c2r().value # XXX return lineark, grid, init_mesh @pytest.fixture(scope="session") def initial_conditions(fpm_initial_conditions): _, _, init_mesh = fpm_initial_conditions return init_mesh @pytest.fixture(scope="session") def solver(cosmo, particle_mesh): from fastpm.core import Cosmology as FastPMCosmology from fastpm.core import Solver ref_cosmo = FastPMCosmology(cosmo) return Solver(particle_mesh, ref_cosmo, B=1) @pytest.fixture(scope="session") def fpm_lpt1(solver, fpm_initial_conditions, lpt_scale_factor): lineark, grid, _ = fpm_initial_conditions statelpt = solver.lpt(lineark, grid, lpt_scale_factor, order=1) return statelpt @pytest.fixture(scope="session") def fpm_lpt1_field(fpm_lpt1, particle_mesh): return particle_mesh.paint(fpm_lpt1.X).value @pytest.fixture(scope="session") def fpm_lpt2(solver, fpm_initial_conditions, lpt_scale_factor): lineark, grid, _ = fpm_initial_conditions statelpt = solver.lpt(lineark, grid, lpt_scale_factor, order=2) return statelpt @pytest.fixture(scope="session") def fpm_lpt2_field(fpm_lpt2, particle_mesh): return particle_mesh.paint(fpm_lpt2.X).value @pytest.fixture(scope="session") def nbody_from_lpt1(solver, fpm_lpt1, particle_mesh, lpt_scale_factor): 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") stages = np.linspace(lpt_scale_factor, 1.0, 10, endpoint=True) finalstate = solver.nbody(fpm_lpt1, leapfrog(stages)) fpm_mesh = particle_mesh.paint(finalstate.X).value return fpm_mesh @pytest.fixture(scope="session") def nbody_from_lpt2(solver, fpm_lpt2, particle_mesh, lpt_scale_factor): 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") stages = np.linspace(lpt_scale_factor, 1.0, 10, endpoint=True) finalstate = solver.nbody(fpm_lpt2, leapfrog(stages)) fpm_mesh = particle_mesh.paint(finalstate.X).value return fpm_mesh