tensors! suppress tests for hallucinated features

src/keyframed/curve.py

@@ -32,7 +32,7 @@ def ensure_sorteddict_of_keyframes(
         sorteddict = curve
     elif isinstance(curve, dict):
         sorteddict = SortedDict(curve)
-    elif isinstance(curve, Number):
+    elif isinstance(curve, (Number, np.ndarray, torch.Tensor)):
         sorteddict = SortedDict({0:Keyframe(t=0,value=curve, interpolation_method=default_interpolation, interpolator_arguments=default_interpolator_args)})
     elif (isinstance(curve, list) or isinstance(curve, tuple)):
         d_ = {}
@@ -81,7 +81,7 @@ def ensure_sorteddict_of_keyframes(
             implied_interpolation = kf.interpolation_method
             implied_interpolator_args = kf.interpolator_arguments
             d_[k] = kf
-        elif isinstance(v, Number):
+        elif isinstance(v, (Number, np.ndarray, torch.Tensor)):
             d_[k] = Keyframe(t=k,value=v, interpolation_method=implied_interpolation, interpolator_arguments=implied_interpolator_args)
         else:
             raise NotImplementedError

tests/test_numpy_vector.py

@@ -1,4 +1,5 @@
 import numpy as np
+from keyframed import Curve
 
 def test_vector_interpolation_linear():
     # Test linear interpolation with vectors
@@ -10,19 +11,19 @@ def test_vector_interpolation_linear():
     assert np.allclose(curve[2.5], np.array([2.5, 2.5, 2.5]))
     assert np.allclose(curve[7.5], np.array([7.5, 7.5, 7.5]))
 
-def test_vector_interpolation_custom():
-    # Test custom interpolation function for vectors
-    def custom_interp(t, t0, value0, t1, value1):
-        # Example: simple linear interpolation
-        return value0 + (value1 - value0) * (t - t0) / (t1 - t0)
+# def test_vector_interpolation_custom():
+#     # Test custom interpolation function for vectors
+#     def custom_interp(t, t0, value0, t1, value1):
+#         # Example: simple linear interpolation
+#         return value0 + (value1 - value0) * (t - t0) / (t1 - t0)
 
-    start_vec = np.array([1, 2, 3])
-    end_vec = np.array([4, 5, 6])
-    curve = Curve({0: start_vec, 10: end_vec})
-    curve.set_interpolation(custom_interp)
+#     start_vec = np.array([1, 2, 3])
+#     end_vec = np.array([4, 5, 6])
+#     curve = Curve({0: start_vec, 10: end_vec})
+#     curve.set_interpolation(custom_interp)
 
-    assert np.allclose(curve[5], np.array([2.5, 3.5, 4.5]))
-    assert np.allclose(curve[2], np.array([1.3, 2.3, 3.3]))
+#     assert np.allclose(curve[5], np.array([2.5, 3.5, 4.5]))
+#     assert np.allclose(curve[2], np.array([1.3, 2.3, 3.3]))
 
 def test_vector_keyframe_insertion():
     # Test inserting vector keyframes
@@ -33,18 +34,18 @@ def test_vector_keyframe_insertion():
     assert np.allclose(curve[0], np.array([1, 2, 3]))
     assert np.allclose(curve[5], np.array([4, 5, 6]))
 
-def test_vector_interpolation_bounds():
-    # Test vector interpolation at curve bounds
-    curve = Curve({0: np.array([0, 0]), 10: np.array([10, 10])}, default_interpolation='linear')
+# def test_vector_interpolation_bounds():
+#     # Test vector interpolation at curve bounds
+#     curve = Curve({0: np.array([0, 0]), 10: np.array([10, 10])}, default_interpolation='linear')
 
-    assert np.allclose(curve[-5], np.array([0, 0]))  # Test extrapolation if your curve supports it
-    assert np.allclose(curve[15], np.array([10, 10]))
+#     assert np.allclose(curve[-5], np.array([0, 0]))  # Test extrapolation if your curve supports it
+#     assert np.allclose(curve[15], np.array([10, 10]))
 
-def test_vector_mixed_interpolation():
-    # Test curves with mixed scalar and vector interpolation
-    curve = Curve({0: 0, 5: np.array([5, 10, 15]), 10: 10}, default_interpolation='linear')
+# def test_vector_mixed_interpolation():
+#     # Test curves with mixed scalar and vector interpolation
+#     curve = Curve({0: 0, 5: np.array([5, 10, 15]), 10: 10}, default_interpolation='linear')
 
-    assert curve[2.5] == 2.5  # Scalar interpolation
-    assert np.allclose(curve[7.5], np.array([7.5, 12.5, 17.5]))  # Vector interpolation
+#     assert curve[2.5] == 2.5  # Scalar interpolation
+#     assert np.allclose(curve[7.5], np.array([7.5, 12.5, 17.5]))  # Vector interpolation
 
 # Add more tests for edge cases, different vector lengths, and other interpolation methods as needed

tests/test_torch_vector.py

@@ -5,35 +5,35 @@
 
 # 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])
+    start_tensor = torch.tensor([0, 0, 0], dtype=torch.float32)
+    end_tensor = torch.tensor([10, 10, 10], dtype=torch.float32)
     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]))
+    assert torch.allclose(curve[5], torch.tensor([5, 5, 5], dtype=torch.float32))
+    assert torch.allclose(curve[2.5], torch.tensor([2.5, 2.5, 2.5], dtype=torch.float32))
+    assert torch.allclose(curve[7.5], torch.tensor([7.5, 7.5, 7.5], dtype=torch.float32))
 
 # 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')
+# 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)
+#     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)
+# 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)
+#     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]))
+#     assert torch.allclose(curve[0.5], torch.tensor([1.5, 1.5, 1.5]))
 
 # Test tensor keyframe insertion
 def test_tensor_keyframe_insertion():
@@ -45,10 +45,10 @@ def test_tensor_keyframe_insertion():
     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')
+# 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]))
+#     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