foxes.output.FlowPlots2D.get_mean_fig_xy(var, xlabel='x [m]', ylabel='y [m]', levels=None, figsize=None, title=None, vlabel=None, fig=None, ax=None, add_bar=True, cmap=None, vmin=None, vmax=None, quiver_n=None, quiver_pars={}, ret_state=False, ret_im=False, ret_data=False, animated=False, **kwargs)[source]

Generates 2D farm flow figure in a horizontal xy-plane.

Parameters

var: str

The variable name

xlabel: str, optional

The x axis label

ylabel: str, optional

The y 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

vmin: float, optional

The minimal variable value

vmax: float, optional

The maximal variable value

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

kwargs: dict, optional

Additional parameters for SliceData.get_mean_data_xy

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)