test: updates for scipy convergence

pybop/parameters/parameter.py

@@ -539,7 +539,7 @@ def get_bounds_for_plotly(self, apply_transform: bool = False) -> np.ndarray:
         bounds = self.get_bounds(apply_transform=apply_transform)
 
         # Validate that all parameters have bounds
-        if bounds is None:
+        if bounds is None or not np.isfinite(list(bounds.values())).all():
             raise ValueError("All parameters require bounds for plotting.")
 
         return np.asarray(list(bounds.values())).T

tests/unit/test_optimisation.py

@@ -18,7 +18,7 @@ def dataset(self):
         return pybop.Dataset(
             {
                 "Time [s]": np.linspace(0, 360, 10),
-                "Current function [A]": 0.01 * np.ones(10),
+                "Current function [A]": 1e-3 * np.ones(10),
                 "Voltage [V]": np.ones(10),
             }
         )
@@ -134,12 +134,12 @@ def test_no_optimisation_parameters(self, model, dataset):
     )
     @pytest.mark.unit
     def test_optimiser_kwargs(self, cost, optimiser):
-        optim = optimiser(cost=cost, maxiter=3, tol=1e-6)
+        optim = optimiser(cost=cost, maxiter=1, tol=1e-6)
         cost_bounds = cost.parameters.get_bounds()
 
         # Check maximum iterations
         results = optim.run()
-        assert results.n_iterations == 3
+        assert results.n_iterations == 1
 
         if optimiser in [pybop.GradientDescent, pybop.Adam, pybop.NelderMead]:
             # Ignored bounds
@@ -552,11 +552,11 @@ def test_unphysical_result(self, cost):
     @pytest.mark.unit
     def test_optimsation_results(self, cost):
         # Construct OptimisationResult
-        results = pybop.OptimisationResult(x=[0.55], cost=cost, n_iterations=1)
+        results = pybop.OptimisationResult(x=[1e-3], cost=cost, n_iterations=1)
 
         # Asserts
-        assert results.x[0] == 0.55
-        assert results.final_cost == cost([0.55])
+        assert results.x[0] == 1e-3
+        assert results.final_cost == cost([1e-3])
         assert results.n_iterations == 1
 
         # Test non-finite results

tests/unit/test_plots.py

@@ -107,7 +107,10 @@ def test_cost_plots(self, cost):
         # Test without bounds
         for param in cost.parameters:
             param.bounds = None
-        pybop.plot2d(cost, steps=5)
+        with pytest.raises(
+            ValueError, match="All parameters require bounds for plotting."
+        ):
+            pybop.plot2d(cost, steps=5)
 
         # Test with bounds
         pybop.plot2d(cost, bounds=np.array([[0.5, 0.8], [0.4, 0.7]]), steps=5)