vslice

_HdfData.vslice(

*args,

unit=None,

mesh=None,

order=None,

scales=True,

bounds_error=True,

)

Read data by physical coordinate value with linear interpolation.

Extends read() to accept physical coordinate values as positional arguments. A scalar or Quantity argument for an axis locates the two nearest grid points and linearly interpolates to the target value. Index-space arguments (None, int, slice) are handled identically to read().

Attention

When reading/slicing data, the *args are always supplied in physical (e.g. \((r, \theta, \phi)\)) order. However, unless specified with the order argument, the sliced data array will be returned in storage order.

Parameters:

*argsQuantityLike | int | slice | None

One argument per axis in physical (r, t, p) order. Physical coordinate values trigger interpolation; index-space arguments do not.

unitUnitLike | None, optional

Output unit. Default is None (code units).

meshMeshCodeType | None, optional

Target stagger mesh. Default is None.

orderArrayOrdering | None, optional

Transpose output if it differs from storage order. Default is None.

scalesbool, optional

If True (default), return coordinate slices alongside the data.

bounds_errorbool, optional

If True (default), raise ValueError when a physical value is outside the coordinate range.

Returns:

dataQuantity

Interpolated or sliced data array.

*scalesQuantity

Sliced scales (only returned when scales is True).

Raises:

ValueError

If bounds_error is True and a physical value falls outside the coordinate range.

Examples

>>> # Extract the r = 2.5 solar radii surface
>>> data, r, t, p = reader.vslice(2.5 * u.R_sun)