Example #1
0
def test_interp1_editable_module(dtype, device, method):
    dtype_device_kwargs = {"dtype": dtype, "device": device}
    x = torch.tensor([0.0, 0.2, 0.3, 0.5, 0.8, 1.0], **dtype_device_kwargs).requires_grad_()
    y = torch.tensor([[1.0, 1.5, 2.1, 1.1, 2.3, 2.5],
                      [0.8, 1.2, 2.2, 0.4, 3.2, 1.2]], **dtype_device_kwargs).requires_grad_()
    xq = torch.linspace(0, 1, 10, **dtype_device_kwargs).requires_grad_()

    cls1 = Interp1D(x, y, method=method)
    cls2 = Interp1D(x, method=method)
    with warnings.catch_warnings():
        warnings.simplefilter("error")
        cls1.assertparams(cls1.__call__, xq)
        cls2.assertparams(cls2.__call__, xq, y)
Example #2
0
 def interp(x, y, xq, extrap):
     return Interp1D(x,
                     y,
                     extrap=extrap,
                     method="cspline",
                     bc_type="natural")(xq)
Example #3
0
 def interp(x, y, xq):
     return Interp1D(x, y, method="cspline", bc_type=bc_type)(xq)
Example #4
0
 def interp(x, y, xq):
     return Interp1D(x, y, method="linear")(xq)
Example #5
0
 def interp(x, y, xq):
     return Interp1D(x,
                     y,
                     method="cspline",
                     bc_type=bc_type,
                     extrap="mirror")(xq)