foxes.output.FlowPlots2D.gen_states_fig_yz(var, x_direction=270.0, ylabel='y [m]', zlabel='z [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, animated=False, rotor_color=None, precalc=False, **kwargs)[source]

Generates 2D farm flow figure in a vertical yz-plane.

Parameters

var: str

The variable name

x_direction: float, optional

The direction of the x axis, 0 = north

ylabel: str, optional

The y 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

vmin: float, optional

The minimal variable value

vmax: float, optional

The maximal variable value

quiver_n: int, optional

Place a vector at ech `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

animated: bool

Switch for usage for an animation

rotor_color: str, optional

Indicate the rotor orientation by a colored line

precalc: bool or tuple

Flag for pre-calculation run, adding an additional generator call before the actual plot generations, yields data, states, gdata. The same tuple can be given for avoiding its calculation and picking up from there.

kwargs: dict, optional

Additional parameters for SliceData.get_states_data_yz

Yields

fig: matplotlib.Figure

The figure object

si: int, optional

The state index

im: tuple, optional

The image objects, matplotlib.collections.QuadMesh or matplotlib.QuadContourSet