import numpy as np
from n3fit.model_gen import generate_pdf_model
[docs]def test_replica_split():
"""Check that multi replica pdf and concatenated single output pdfs agree"""
num_replicas = 3
replica_axis = 1
fake_fl = [
{"fl": i, "largex": [0.5, 1.5], "smallx": [1.5, 2.5]}
for i in ["u", "ubar", "d", "dbar", "c", "g", "s", "sbar"]
]
pdf_model = generate_pdf_model(
nodes=[8],
activations=["linear"],
seed=34,
flav_info=fake_fl,
fitbasis="FLAVOUR",
num_replicas=num_replicas,
)
rng = np.random.default_rng(seed=34)
eps = 1e-9
pdf_input = np.maximum(rng.random((1, 5, 1)), eps)
int_input = np.maximum(rng.random((1, 2_000, 1)), eps)
fake_input = {
'pdf_input': np.sort(pdf_input, axis=1),
'integrator_input': np.sort(int_input, axis=1),
}
output_full = pdf_model(fake_input)
pdf_models = pdf_model.split_replicas()
output_split = [pdf(fake_input) for pdf in pdf_models]
output_split_stacked = np.stack(output_split, axis=replica_axis)
np.testing.assert_allclose(output_full, output_split_stacked, rtol=1e-5)