Example #1
0
def staggered_elements(resolution: Shape, bounds: Box,
                       extrapolation: math.Extrapolation):
    cells = GridCell(resolution, bounds)
    grids = []
    for dim in resolution.names:
        lower, upper = extrapolation.valid_outer_faces(dim)
        grids.append(cells.stagger(dim, lower, upper))
    return geom.stack(grids, channel(staggered_direction=resolution.names))
Example #2
0
def batch_stack(*fields, dim: str):
    assert all(isinstance(f, SampledField) for f in fields)
    assert all(isinstance(f, type(fields[0])) for f in fields)
    if any(f.extrapolation != fields[0].extrapolation for f in fields):
        raise NotImplementedError("Concatenating extrapolations not supported")
    if isinstance(fields[0], Grid):
        values = math.batch_stack([f.values for f in fields], dim)
        return fields[0].with_(values=values)
    elif isinstance(fields[0], PointCloud):
        elements = geom.stack(*[f.elements for f in fields], dim=dim)
        values = math.batch_stack([f.values for f in fields], dim=dim)
        colors = math.batch_stack([f.color for f in fields], dim=dim)
        return fields[0].with_(elements=elements, values=values, color=colors)
    raise NotImplementedError(type(fields[0]))
Example #3
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def stack(fields, dim: Shape, dim_bounds: Box = None):
    """
    Stacks the given `SampledField`s along `dim`.

    See Also:
        `concat()`.

    Args:
        fields: List of matching `SampledField` instances.
        dim: Stack dimension as `Shape`. Size is ignored.

    Returns:
        `SampledField` matching stacked fields.
    """
    assert all(
        isinstance(f, SampledField) for f in fields
    ), f"All fields must be SampledFields of the same type but got {fields}"
    assert all(
        isinstance(f, type(fields[0])) for f in fields
    ), f"All fields must be SampledFields of the same type but got {fields}"
    if any(f.extrapolation != fields[0].extrapolation for f in fields):
        raise NotImplementedError("Concatenating extrapolations not supported")
    if isinstance(fields[0], Grid):
        values = math.stack([f.values for f in fields], dim)
        if spatial(dim):
            if dim_bounds is None:
                dim_bounds = Box(**{dim.name: len(fields)})
            return type(fields[0])(values,
                                   extrapolation=fields[0].extrapolation,
                                   bounds=fields[0].bounds * dim_bounds)
        else:
            return fields[0].with_values(values)
    elif isinstance(fields[0], PointCloud):
        elements = geom.stack([f.elements for f in fields], dim=dim)
        values = math.stack([f.values for f in fields], dim=dim)
        colors = math.stack([f.color for f in fields], dim=dim)
        return PointCloud(elements=elements,
                          values=values,
                          color=colors,
                          extrapolation=fields[0].extrapolation,
                          add_overlapping=fields[0]._add_overlapping,
                          bounds=fields[0]._bounds)
    raise NotImplementedError(type(fields[0]))
Example #4
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 def test_stack_type(self):
     bounds1 = Box[0:1, 0:1]
     bounds2 = Box[0:10, 0:10]
     bounds = geom.stack([bounds1, bounds2], batch('batch'))
     self.assertIsInstance(bounds, Box)
Example #5
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 def test_stack_volume(self):
     u = geom.stack([Box[0:1, 0:1], Box[0:2, 0:2]], batch('batch'))
     math.assert_close(u.volume, [1, 4])
Example #6
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 def test_laplace_batched(self):
     bounds = geom.stack([Box[0:1, 0:1], Box[0:10, 0:10]], batch('batch'))
     grid = CenteredGrid(0, extrapolation.ZERO, bounds, x=10, y=10)
     lap = field.laplace(grid)
     self.assertIsInstance(lap, CenteredGrid)
Example #7
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 def test_spatial_gradient_batched(self):
     bounds = geom.stack([Box[0:1, 0:1], Box[0:10, 0:10]], batch('batch'))
     grid = CenteredGrid(0, extrapolation.ZERO, bounds, x=10, y=10)
     grad = field.spatial_gradient(grid)
     self.assertIsInstance(grad, CenteredGrid)