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add tests
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180
tests/conftest.py
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180
tests/conftest.py
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# Parameterized fixture for mesh_shape
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import os
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import pytest
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os.environ["EQX_ON_ERROR"] = "nan"
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setup_done = False
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on_cluster = False
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def is_on_cluster():
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global on_cluster
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return on_cluster
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def initialize_distributed():
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global setup_done
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global on_cluster
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if not setup_done:
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if "SLURM_JOB_ID" in os.environ:
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on_cluster = True
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print("Running on cluster")
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import jax
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jax.distributed.initialize()
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setup_done = True
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on_cluster = True
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else:
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print("Running locally")
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setup_done = True
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on_cluster = False
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os.environ["JAX_PLATFORM_NAME"] = "cpu"
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os.environ["XLA_FLAGS"] = "--xla_force_host_platform_device_count=8"
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import jax
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@pytest.fixture(scope="session", autouse=True)
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def setup_and_teardown_session():
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# Code to run at the start of the session
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print("Starting session...")
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initialize_distributed()
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# Setup code here
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# e.g., connecting to a database, initializing some resources, etc.
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@pytest.fixture(
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scope="session",
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params=[
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((64, 64, 64) , (512., 512., 512.)), # BOX
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((64, 64, 128) , (256. , 256. , 512.)), # RECTANGULAR
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])
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def simulation_config(request):
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return request.param
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@pytest.fixture(scope="session", params=[0.1 , 0.5 , 0.8])
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def lpt_scale_factor(request):
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return request.param
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@pytest.fixture(scope="session")
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def cosmo():
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from jax_cosmo import Cosmology
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from functools import partial
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Planck18 = partial(
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Cosmology,
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# Omega_m = 0.3111
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Omega_c=0.2607,
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Omega_b=0.0490,
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Omega_k=0.0,
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h=0.6766,
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n_s=0.9665,
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sigma8=0.8102,
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w0=-1.0,
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wa=0.0,
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)
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return Planck18()
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@pytest.fixture(scope="session")
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def particle_mesh(simulation_config):
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from pmesh.pm import ParticleMesh
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mesh_shape, box_shape = simulation_config
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return ParticleMesh(BoxSize=box_shape, Nmesh=mesh_shape, dtype='f4')
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@pytest.fixture(scope="session")
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def fpm_initial_conditions(cosmo, particle_mesh):
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from jax import numpy as jnp
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import jax_cosmo as jc
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import numpy as np
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# Generate initial particle positions
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grid = particle_mesh.generate_uniform_particle_grid(shift=0).astype(
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np.float32)
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# Interpolate with linear_matter spectrum to get initial density field
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k = jnp.logspace(-4, 1, 128)
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pk = jc.power.linear_matter_power(cosmo, k)
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def pk_fn(x):
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return jnp.interp(x.reshape([-1]), k, pk).reshape(x.shape)
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whitec = particle_mesh.generate_whitenoise(42,
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type='complex',
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unitary=False)
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lineark = whitec.apply(lambda k, v: pk_fn(sum(ki**2 for ki in k)**0.5)**0.5
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* v * (1 / v.BoxSize).prod()**0.5)
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init_mesh = lineark.c2r().value # XXX
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return lineark, grid, init_mesh
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@pytest.fixture(scope="session")
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def initial_conditions(fpm_initial_conditions):
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_, _, init_mesh = fpm_initial_conditions
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return init_mesh
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@pytest.fixture(scope="session")
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def solver(cosmo, particle_mesh):
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from fastpm.core import Solver, Cosmology as FastPMCosmology
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ref_cosmo = FastPMCosmology(cosmo)
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return Solver(particle_mesh, ref_cosmo, B=1)
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@pytest.fixture(scope="session")
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def fpm_lpt1(solver, fpm_initial_conditions, lpt_scale_factor):
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lineark, grid, _ = fpm_initial_conditions
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statelpt = solver.lpt(lineark, grid, lpt_scale_factor, order=1)
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return statelpt
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@pytest.fixture(scope="session")
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def fpm_lpt1_field(fpm_lpt1, particle_mesh):
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return particle_mesh.paint(fpm_lpt1.X).value
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@pytest.fixture(scope="session")
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def fpm_lpt2(solver, fpm_initial_conditions, lpt_scale_factor):
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lineark, grid, _ = fpm_initial_conditions
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statelpt = solver.lpt(lineark, grid, lpt_scale_factor, order=2)
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return statelpt
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@pytest.fixture(scope="session")
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def fpm_lpt2_field(fpm_lpt2, particle_mesh):
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return particle_mesh.paint(fpm_lpt2.X).value
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@pytest.fixture(scope="session")
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def nbody_from_lpt1(solver, fpm_lpt1, particle_mesh, lpt_scale_factor):
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from fastpm.core import leapfrog
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import numpy as np
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if lpt_scale_factor == 0.8:
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pytest.skip("Do not run nbody simulation from scale factor 0.8")
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stages = np.linspace(lpt_scale_factor, 1.0, 10, endpoint=True)
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finalstate = solver.nbody(fpm_lpt1, leapfrog(stages))
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fpm_mesh = particle_mesh.paint(finalstate.X).value
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return fpm_mesh
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@pytest.fixture(scope="session")
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def nbody_from_lpt2(solver, fpm_lpt2, particle_mesh, lpt_scale_factor):
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from fastpm.core import leapfrog
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import numpy as np
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if lpt_scale_factor == 0.8:
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pytest.skip("Do not run nbody simulation from scale factor 0.8")
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stages = np.linspace(lpt_scale_factor, 1.0, 10, endpoint=True)
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finalstate = solver.nbody(fpm_lpt2, leapfrog(stages))
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fpm_mesh = particle_mesh.paint(finalstate.X).value
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return fpm_mesh
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