remove back compatibility files for version 0.2

tests/test_equation/test_equation.py

@@ -0,0 +1,49 @@
+from pina.equation import Equation
+from pina.operator import grad, laplacian
+from pina import LabelTensor
+import torch
+import pytest
+
+
+def eq1(input_, output_):
+    u_grad = grad(output_, input_)
+    u1_xx = grad(u_grad, input_, components=["du1dx"], d=["x"])
+    u2_xy = grad(u_grad, input_, components=["du2dx"], d=["y"])
+    return torch.hstack([u1_xx, u2_xy])
+
+
+def eq2(input_, output_):
+    force_term = torch.sin(input_.extract(["x"]) * torch.pi) * torch.sin(
+        input_.extract(["y"]) * torch.pi
+    )
+    delta_u = laplacian(output_.extract(["u1"]), input_)
+    return delta_u - force_term
+
+
+def foo():
+    pass
+
+
+def test_constructor():
+    Equation(eq1)
+    Equation(eq2)
+    with pytest.raises(ValueError):
+        Equation([1, 2, 4])
+    with pytest.raises(ValueError):
+        Equation(foo())
+
+
+def test_residual():
+    eq_1 = Equation(eq1)
+    eq_2 = Equation(eq2)
+
+    pts = LabelTensor(torch.rand(10, 2), labels=["x", "y"])
+    pts.requires_grad = True
+    u = torch.pow(pts, 2)
+    u.labels = ["u1", "u2"]
+
+    eq_1_res = eq_1.residual(pts, u)
+    eq_2_res = eq_2.residual(pts, u)
+
+    assert eq_1_res.shape == torch.Size([10, 2])
+    assert eq_2_res.shape == torch.Size([10, 1])

tests/test_equation/test_system_equation.py

@@ -0,0 +1,101 @@
+from pina.equation import SystemEquation, FixedValue, FixedGradient
+from pina.operator import grad, laplacian
+from pina import LabelTensor
+import torch
+import pytest
+
+
+def eq1(input_, output_):
+    u_grad = grad(output_, input_)
+    u1_xx = grad(u_grad, input_, components=["du1dx"], d=["x"])
+    u2_xy = grad(u_grad, input_, components=["du2dx"], d=["y"])
+    return torch.hstack([u1_xx, u2_xy])
+
+
+def eq2(input_, output_):
+    force_term = torch.sin(input_.extract(["x"]) * torch.pi) * torch.sin(
+        input_.extract(["y"]) * torch.pi
+    )
+    delta_u = laplacian(output_.extract(["u1"]), input_)
+    return delta_u - force_term
+
+
+def foo():
+    pass
+
+
+@pytest.mark.parametrize("reduction", [None, "mean", "sum"])
+def test_constructor(reduction):
+
+    # Constructor with callable functions
+    SystemEquation([eq1, eq2], reduction=reduction)
+
+    # Constructor with Equation instances
+    SystemEquation(
+        [
+            FixedValue(value=0.0, components=["u1"]),
+            FixedGradient(value=0.0, components=["u2"]),
+        ],
+        reduction=reduction,
+    )
+
+    # Constructor with mixed types
+    SystemEquation(
+        [
+            FixedValue(value=0.0, components=["u1"]),
+            eq1,
+        ],
+        reduction=reduction,
+    )
+
+    # Non-standard reduction not implemented
+    with pytest.raises(NotImplementedError):
+        SystemEquation([eq1, eq2], reduction="foo")
+
+    # Invalid input type
+    with pytest.raises(ValueError):
+        SystemEquation(foo)
+
+
+@pytest.mark.parametrize("reduction", [None, "mean", "sum"])
+def test_residual(reduction):
+
+    # Generate random points and output
+    pts = LabelTensor(torch.rand(10, 2), labels=["x", "y"])
+    pts.requires_grad = True
+    u = torch.pow(pts, 2)
+    u.labels = ["u1", "u2"]
+
+    # System with callable functions
+    system_eq = SystemEquation([eq1, eq2], reduction=reduction)
+    res = system_eq.residual(pts, u)
+
+    # Checks on the shape of the residual
+    shape = torch.Size([10, 3]) if reduction is None else torch.Size([10])
+    assert res.shape == shape
+
+    # System with Equation instances
+    system_eq = SystemEquation(
+        [
+            FixedValue(value=0.0, components=["u1"]),
+            FixedGradient(value=0.0, components=["u2"]),
+        ],
+        reduction=reduction,
+    )
+
+    # Checks on the shape of the residual
+    shape = torch.Size([10, 3]) if reduction is None else torch.Size([10])
+    assert res.shape == shape
+
+    # System with mixed types
+    system_eq = SystemEquation(
+        [
+            FixedValue(value=0.0, components=["u1"]),
+            eq1,
+        ],
+        reduction=reduction,
+    )
+
+    # Checks on the shape of the residual
+    shape = torch.Size([10, 3]) if reduction is None else torch.Size([10])
+    assert res.shape == shape