tidy3d.Coords

class Coords

Bases: Tidy3dBaseModel

Holds data about a set of x,y,z positions on a grid.

Parameters:

• x (Attribute: x) –

  Type	ArrayLike[dtype=float, ndim=1]
  Default
  Description	1-dimensional array of x coordinates.

• y (Attribute: y) –

  Type	ArrayLike[dtype=float, ndim=1]
  Default
  Description	1-dimensional array of y coordinates.

• z (Attribute: z) –

  Type	ArrayLike[dtype=float, ndim=1]
  Default
  Description	1-dimensional array of z coordinates.

Example

>>> x = np.linspace(-1, 1, 10)
>>> y = np.linspace(-1, 1, 11)
>>> z = np.linspace(-1, 1, 12)
>>> coords = Coords(x=x, y=y, z=z)

Attributes

to_dict	Return a dict of the three Coord1D objects as numpy arrays.
to_list	Return a list of the three Coord1D objects as numpy arrays.

Methods

spatial_interp(array, interp_method[, ...])

Similar to xarrray.DataArray.interp with 2 enhancements:

x

y

z

property to_dict

Return a dict of the three Coord1D objects as numpy arrays.

property to_list

Return a list of the three Coord1D objects as numpy arrays.

spatial_interp(array, interp_method, fill_value='extrapolate')

Similar to xarrray.DataArray.interp with 2 enhancements:

1) Check if the coordinate of the supplied data are in monotonically increasing order. If they are, apply the faster assume_sorted=True.

2. For axes of single entry, instead of error, apply isel() along the axis.

Parameters:

• array (Union[SpatialDataArray, ScalarFieldDataArray]) – Supplied scalar dataset

• interp_method (InterpMethod) – Interpolation method.

• fill_value (Union[Literal['extrapolate'], float] = "extrapolate") – Value used to fill in for points outside the data range. If set to ‘extrapolate’, values will be extrapolated into those regions using the “nearest” method.

Returns:

The interpolated spatial dataset.

Return type:

Union[SpatialDataArray, ScalarFieldDataArray]

Note

This method is called from a Coords instance with the array to be interpolated as an argument, not the other way around.

__hash__()

Hash method.