aigc

tests/test_torch_matrix.py

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+import torch
+from keyframed import Curve
+
+
+def test_matrix_interpolation():
+    start_matrix = torch.tensor([[0, 0], [0, 0]], dtype=torch.float32)
+    end_matrix = torch.tensor([[1, 1], [1, 1]], dtype=torch.float32)
+    curve = Curve({0: start_matrix, 10: end_matrix}, default_interpolation='linear')
+
+    expected_mid = torch.tensor([[0.5, 0.5], [0.5, 0.5]], dtype=torch.float32)
+    assert torch.allclose(curve[5], expected_mid)

tests/test_torch_vector.py

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+import pytest
+import numpy as np
+import torch
+from keyframed import Curve, Keyframe
+
+# Test linear interpolation with PyTorch tensors
+def test_linear_interpolation_tensor():
+    start_tensor = torch.tensor([0, 0, 0])
+    end_tensor = torch.tensor([10, 10, 10])
+    curve = Curve({0: start_tensor, 10: end_tensor}, default_interpolation='linear')
+
+    assert torch.allclose(curve[5], torch.tensor([5, 5, 5]))
+    assert torch.allclose(curve[2.5], torch.tensor([2.5, 2.5, 2.5]))
+    assert torch.allclose(curve[7.5], torch.tensor([7.5, 7.5, 7.5]))
+
+# Test mixed NumPy array and PyTorch tensor interpolation
+def test_mixed_interpolation():
+    start_array = np.array([1, 2, 3])
+    end_tensor = torch.tensor([4, 5, 6])
+    curve = Curve({0: start_array, 10: end_tensor}, default_interpolation='linear')
+
+    expected_midpoint = torch.tensor([2.5, 3.5, 4.5])
+    assert torch.allclose(curve[5], expected_midpoint)
+
+# Test PyTorch tensor interpolation with custom interpolation method
+def test_custom_tensor_interpolation():
+    def custom_interp(t, t0, value0, t1, value1):
+        value0, value1 = torch.tensor(value0), torch.tensor(value1)
+        return value0 + (value1 - value0) * (t - t0) / (t1 - t0)
+
+    start_tensor = torch.tensor([1, 1, 1])
+    end_tensor = torch.tensor([2, 2, 2])
+    curve = Curve({0: start_tensor, 1: end_tensor})
+    curve.set_interpolation(custom_interp)
+
+    assert torch.allclose(curve[0.5], torch.tensor([1.5, 1.5, 1.5]))
+
+# Test tensor keyframe insertion
+def test_tensor_keyframe_insertion():
+    curve = Curve()
+    curve[0] = torch.tensor([1, 2, 3])
+    curve[5] = torch.tensor([4, 5, 6])
+
+    assert torch.allclose(curve[0], torch.tensor([1, 2, 3]))
+    assert torch.allclose(curve[5], torch.tensor([4, 5, 6]))
+
+# Test tensor interpolation at curve bounds
+def test_tensor_interpolation_bounds():
+    curve = Curve({0: torch.tensor([0, 0]), 10: torch.tensor([10, 10])}, default_interpolation='linear')
+
+    assert torch.allclose(curve[-5], torch.tensor([0, 0]))  # Test extrapolation if your curve supports it
+    assert torch.allclose(curve[15], torch.tensor([10, 10]))
+
+# Add more tests for edge cases and different tensor shapes if necessary