-
foxes.output.SliceData.get_mean_data_xy(resolution=
None
, n_img_points=None
, variables=None
, data_format='xarray'
, xmin=None
, ymin=None
, xmax=None
, ymax=None
, z=None
, xspace=500.0
, yspace=500.0
, normalize_x=None
, normalize_y=None
, normalize_z=None
, normalize_v={}
, label_map={}
, vmin={}
, vmax={}
, states_sel=None
, states_isel=None
, weight_turbine=0
, to_file=None
, write_pars={}
, ret_states=False
, ret_grid=False
, verbosity=0
, **kwargs)[source] Creates mean data of 2D farm flow slices in a horizontal xy-plane.
Parameters¶
- resolution: float, optional
The resolution in m
- n_img_points: tuple of int, optional
The number of image points (n, m) in the two directions
- variables: list of str, optional
The variables, or None for all
- data_format: str
The output data format: numpy, pandas, xarray
- xmin: float, optional
The min x coordinate, or None for automatic
- ymin: float, optional
The min y coordinate, or None for automatic
- xmax: float, optional
The max x coordinate, or None for automatic
- ymax: float, optional
The max y coordinate, or None for automatic
- z: float, optional
The z coordinate of the plane
- xspace: float, optional
The extra space in x direction, before and after wind farm
- yspace: float, optional
The extra space in y direction, before and after wind farm
- normalize_x: float, optional
Divide x by this value
- normalize_y: float, optional
Divide y by this value
- normalize_z: float, optional
Divide z by this value
- normalize_v: dict, optional
Divide the variables by these values
- label_map: dict
The mapping from original to new field names
- vmin: dict
Minimal values for variables
- vmax: dict
Maximal values for variables
- states_sel: list, optional
Reduce to selected states
- states_isel: list, optional
Reduce to the selected states indices
- weight_turbine: int, optional
Index of the turbine from which to take the weight
- to_file: str, optional
Write data to this file name
- write_pars: dict
Additional write function parameters
- ret_states: bool
Flag for returning states indices
- ret_grid: bool
Flag for returning grid data
- verbosity: int, optional
The verbosity level, 0 = silent
- kwargs: dict, optional
Parameters forwarded to the algorithm’s calc_points function.
Returns¶
- data: dict or pandas.DataFrame or xarray.Dataset
The gridded data
- states: numpy.ndarray, optional
The states indices
- grid_data: tuple, optional
The grid data (x_pos, y_pos, z_pos, g_pts)