Load.slices

pyPLUTO.Load.slices(self, var: ndarray[tuple[Any, ...], dtype[_ScalarT]], check: bool = True, diag: bool | None = None, x1: int | list | None = None, x2: int | list | None = None, x3: int | list | None = None, **kwargs: Any) → ndarray

Function that slices the variable in the 3 directions. Also, it can slice the diagonal of the variable.

Parameters:

- axis1: int | None, default None

Axis to be used as the first axis of the 2-D sub-arrays from which the diagonals should be taken. Defaults to first axis (0).

- axis2: int | None, default None

Axis to be used as the second axis of the 2-D sub-arrays from which the diagonals should be taken. Defaults to second axis (1).

- diag: bool | None, default None

If not None (or ‘min’), slice the main diagonal of the variable. If ‘min’, slice the opposite diagonal.

- offset: int | None, default None

Offset of the diagonal from the main diagonal. Can be positive or negative. Defaults to main diagonal (0).

- var: np.ndarray

The variable to slice.

- x1: int | list | None, default None

The slice in the 1st direction.

- x2: int | list | None, default None

The slice in the 2nd direction.

- x3: int | list | None, default None

The slice in the 3rd direction.

—-

Returns:

• newvar: NDArray

  The sliced variable.

Examples

• Example #1: Slice the variable in the 3 directions

  >>> slices(var, x1=0, x2=0, x3=0)
  

• Example #2: Slice the variable in the diagonal

  >>> slices(var, diag=True)
  

• Example #3: Slice the variable in the opposite diagonal

  >>> slices(var, diag="min")
  

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