-
foxes.output.FlowPlots2D.get_mean_fig_xz(mean_data_xz, xlabel=
'x [m]', zlabel='z [m]', levels=None, figsize=None, title=None, vlabel=None, fig=None, ax=None, add_bar=True, cmap=None, quiver_n=None, quiver_pars={}, ret_state=False, ret_im=False, ret_data=False, animated=False)[source] Generates 2D farm flow figure in a horizontal xz-plane.
Parameters¶
- mean_data_xz: tuple
The pre-calculated data from get_mean_data_xz, (parameters, data, grid_data)
- xlabel: str, optional
The x axis label
- zlabel: str, optional
The z axis label
- levels: int, optional
The number of levels for the contourf plot, or None for pure image
- figsize: tuple, optional
The figsize for plt.Figure
- title: str, optional
The title
- vlabel: str, optional
The variable label
- fig: plt.Figure, optional
The figure object
- ax: plt.Axes, optional
The figure axes
- add_bar: bool
Add a color bar
- cmap: str, optional
The colormap
- quiver_n: int, optional
Place a vector at each `n`th point
- quiver_pars: dict, optional
Parameters for plt.quiver
- ret_state: bool
Flag for state index return
- ret_im: bool
Flag for image return
- ret_data: bool
Flag for returning image data
- animated: bool
Switch for usage for an animation
Returns¶
- fig: matplotlib.Figure
The figure object
- si: int, optional
The state index
- im: tuple, optional
The image objects, matplotlib.collections.QuadMesh or matplotlib.QuadContourSet
- data: numpy.ndarray, optional
The image data, shape: (n_x, n_y)