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foxes.output.FlowPlots2D.get_mean_fig_yz(var, x_direction=
270, ylabel='x [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, ret_data=False, animated=False, **kwargs)[source] Generates 2D farm flow figure in a horizontal 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 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_yz
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)