test: update test for active learning

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)