From 39498bba8e50fbd4370e5ef1d3fa196e26fee551 Mon Sep 17 00:00:00 2001
From: Hu Zhao <zhao@mbd.rwth-aachen.de>
Date: Fri, 28 Oct 2022 18:15:46 +0200
Subject: [PATCH] test: update test for active learning
---
tests/test_active_learning.py | 16 ++++------------
1 file changed, 4 insertions(+), 12 deletions(-)
diff --git a/tests/test_active_learning.py b/tests/test_active_learning.py
index 06d9fbb..9508a09 100644
--- a/tests/test_active_learning.py
+++ b/tests/test_active_learning.py
@@ -32,11 +32,9 @@ def test_ActiveLearning_init_TypeError(run_sim_obj, prior, likelihood,
ndim = 1
bounds = np.array([[0,1]])
data = np.array([1,2,3])
- n0 = 20
- nt = 100
with pytest.raises(BeartypeCallHintParamViolation):
_ = ActiveLearning(ndim, bounds, data, run_sim_obj, prior, likelihood,
- n0, nt, lhs_sampler, scalar_gasp, optimizer=optimizer)
+ lhs_sampler, scalar_gasp, optimizer=optimizer)
@pytest.mark.parametrize(
@@ -59,11 +57,9 @@ def test_ActiveLearning_init_RuntimeError(run_sim_obj, lhs_sampler,
data = np.array([1,2,3])
prior = uniform.pdf
likelihood = norm.pdf
- n0 = 20
- nt = 100
with pytest.raises(RuntimeError):
_ = ActiveLearning(ndim, bounds, data, run_sim_obj, prior, likelihood,
- n0, nt, lhs_sampler, scalar_gasp)
+ lhs_sampler, scalar_gasp)
@pytest.mark.parametrize(
@@ -82,11 +78,9 @@ def test_ActiveLearning_init_NotImplementedError(scalar_gasp_mean, indicator):
scalar_gasp = ScalarGaSP(1)
prior = uniform.pdf
likelihood = norm.pdf
- n0 = 20
- nt = 100
with pytest.raises(NotImplementedError):
_ = ActiveLearning(ndim, bounds, data, run_sim_obj, prior, likelihood,
- n0, nt, lhs_sampler, scalar_gasp, scalar_gasp_mean=scalar_gasp_mean,
+ lhs_sampler, scalar_gasp, scalar_gasp_mean=scalar_gasp_mean,
indicator=indicator)
def test_ActiveLearning_init_ValueError():
@@ -98,9 +92,7 @@ def test_ActiveLearning_init_ValueError():
scalar_gasp = ScalarGaSP(1)
prior = uniform.pdf
likelihood = norm.pdf
- n0 = 20
- nt = 100
kwgs_optimizer = {"NS":50}
with pytest.raises(ValueError):
_ = ActiveLearning(ndim, bounds, data, run_sim_obj, prior, likelihood,
- n0, nt, lhs_sampler, scalar_gasp, kwgs_optimizer=kwgs_optimizer)
+ lhs_sampler, scalar_gasp, kwgs_optimizer=kwgs_optimizer)
--
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