add self-adaptive weighting

tests/test_weighting/test_self_adaptive_weighting.py

@@ -0,0 +1,37 @@
+import pytest
+from pina import Trainer
+from pina.solver import PINN
+from pina.model import FeedForward
+from pina.loss import SelfAdaptiveWeighting
+from pina.problem.zoo import Poisson2DSquareProblem
+
+
+# Initialize problem and model
+problem = Poisson2DSquareProblem()
+problem.discretise_domain(10)
+model = FeedForward(len(problem.input_variables), len(problem.output_variables))
+
+
+@pytest.mark.parametrize("k", [10, 100, 1000])
+def test_constructor(k):
+    SelfAdaptiveWeighting(k=k)
+
+    # Should fail if k is not an integer
+    with pytest.raises(AssertionError):
+        SelfAdaptiveWeighting(k=1.5)
+
+    # Should fail if k is not > 0
+    with pytest.raises(AssertionError):
+        SelfAdaptiveWeighting(k=0)
+
+    # Should fail if k is not > 0
+    with pytest.raises(AssertionError):
+        SelfAdaptiveWeighting(k=-3)
+
+
+@pytest.mark.parametrize("k", [2, 3])
+def test_train_aggregation(k):
+    weighting = SelfAdaptiveWeighting(k=k)
+    solver = PINN(problem=problem, model=model, weighting=weighting)
+    trainer = Trainer(solver=solver, max_epochs=5, accelerator="cpu")
+    trainer.train()