display_gradients

mrinufft.trajectories.display.display_gradients(trajectory: ndarray[tuple[int, ...], dtype[_ScalarType_co]], shot_ids: tuple[int, ...] = (0,), figsize: float = 5, fill_area: bool = True, show_norm: bool = True, uni_signal: str | None = 'gray', uni_gradient: str | None = None, subfigure: Figure | Axes | None = None, show_constraints: bool = False, acq: Acquisition | None = None, constraints_order: int | str | None = None) → tuple[Axes]

Display gradients based on trajectory of any dimension.

Parameters:

• trajectory (NDArray) – Trajectory to display.

• shot_ids (list of int) – Indices of the shots to display. The default is (0,).

• figsize (float, optional) – Size of the figure.

• fill_area (bool, optional) – Fills the area under the curve for improved visibility and representation of the integral, aka trajectory. The default is True.

• show_norm (bool, optional) – Show an additional illustration of the signal as the modulated distance to the center. The default is True.

• uni_signal (str or None, optional) – Define whether the signal should be represented by a unique color given as argument or just by the default color cycle when None. The default is “gray”.

• uni_signal – Define whether the gradients should be represented by a unique color given as argument or just by the default color cycle when None. The default is None.

• subfigure (plt.Figure or plt.SubFigure, optional) – The figure where the trajectory should be displayed. The default is None.

• show_constraints (bool, optional) – Display the points where the gradients and slew rates are above the gmax and smax limits, respectively. The default is False.

• acq (Acquisition, optional) – Acquisition configuration to use. If None, the default acquisition is used.

• constraint_order (int, str, optional) – Norm order defining how the constraints are checked, typically 2 or np.inf, following the numpy.linalg.norm conventions on parameter ord. The default is None.

Returns:

axes – Axes of the figure.

Return type:

plt.Axes