enstools.plot.grid

enstools.plot.grid(plot_function, variable, lon=None, lat=None, figure=None, axes=None, shape=None, cmaps=None, **kwargs)

Create a multi-panel plot by mapping the first dimension of the input array to a plot function specified in the second argument.

Parameters:

plot_functionCallable

the plot function to use. supported are all function in enstools.plot

variablexarray.DataArray or np.ndarray

the data to plot. Should be an 3d-Array, the first dimension is used to create the grid.

lonxarray.DataArray or np.ndarray or str

longitude coordinate or name of longitude coordinate. The name may only be used for xarray variables.

latxarray.DataArray or np.ndarray or str

latitude coordinate or name of longitude coordinate. The name may only be used for xarray variables.

figurematplotlib.figure.Figure

If provided, this figure instance will be used (and returned), otherwise a new figure will be created.

axesarray of matplotlib.axes.Axes

if provided, this has to be an array of matplotlib.axes.Axes instances with the desired shape of the plot.

shapetuple

The shape of the multi-panel plot (nrows, ncols). Not providing shape or axes is an error!

cmapslist

A list of cmap names. The number of entries has to be the number of panel plots to create.

**kwargs:

Keyword arguments, they are forwarded top the actual plt function that creates the individual panels

Returns:

tuple:

fig, ax, where ax is an array for Axes objects

Examples

>>> fig, ax = grid(contour, data["TOT_PREC"][27, :, :, :], data["rlon"], data["rlat"], shape=(4, 5), cmaps=cmaps, rotated_pole=data["rotated_pole"], colorbar=False)    

Example of displaying the result of K-Mean clustering for the COSMO-DE Ensemble. Each cluster has a different colormap.