Plot

class enstools.plot.Backend(value)

Enum class that defining a library for plotting.

BOKEH = 2

PLOTLY = 1

class enstools.plot.Stream(value)

Enum class that defining a type of streamlines.

LINE = 1

VECTOR = 2

enstools.plot.contour(variable, lon=None, lat=None, **kwargs)

Create a plot from an xarray variable that includes coordinates.

Parameters

variablexarray.DataArray

the data to plot.

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.

Other optional keyword arguments:

**kwargs

figure: matplotlib.figure.Figure: If provided, this figure instance will be used (and returned), otherwise a new figure will be created.
axes: matplotlib.axes.Axes: If provided, this axes instance will be used (e.g., of overplotting), otherwise a new axes object will be created.
subplot_args: tuple: Arguments passed on to add_subplot. These arguments are used only if no axes is provided.
subplot_kwargs: dict: Keyword arguments passed on to add_subplot. These arguments are used only if no axes is provided.
filled: [True | False]: If True a filled contour is plotted, which is the default
colorbar: [True | False | “empty”]: If True, a colorbar is created. Default=True. Use empty to reserve space for the colorbar without actually creating it. This is usefull for multipanel plots, where one panel has a colorbar and another not.
levels: np.ndarray: If provided, these levels are used, otherwise the levels are automatically selected.
levels_center_on_zerobool: If true, automatically selected levels are centered around zero.
gridlines: [True | False]: If True, coordinate grid lines are drawn. Default=False
gridline_labes: [True | False]: Whether or not to label the grid lines. The default is not to label them.
coastlines: [True | False | ‘110m’ | ‘50m’ | ‘10m’]: If True, coordinate grid lines are drawn. Default=True
coastlines_kwargs: dict: dictionary with arguments passed on to ax.coastlines()
borders: [True | False | ‘110m’ | ‘50m’ | ‘10m’]: If True, coordinate grid lines are drawn. Default=False
projection: [ cartopy.crs.Projection]: If not None, the Projection object is used to create the plot
rotated_pole: [xarray.DataArray | dict]: Information about the rotated pole. This can either be the CF-standard rotated_pole variable from an input file, or alternatively a dictionary with the keys grid_north_pole_latitude and grid_north_pole_longitude.

All other arguments are forwarded to the matplotlib contour or contourf function.

Returns

tuple: (Figure, Axes) of the new plot is returned. The returned values may be reused in subsequent calls to plot functions.

Examples

>>> fig, ax = enstools.plot.contour(data["TOT_PREC"][0, :, :], coastlines="50m")    

>>> fig, ax1 = enstools.plot.contour(data["PMSL"][0, :] / 100.0, gridlines=True, subplot_args=(121,))   
>>> fig, ax2 = enstools.plot.contour(data["TOT_PREC"][0, :], figure=fig, subplot_args=(122,))           

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)    

images/example_cluster_cosmo_01.png — Example of displaying the result of K-Mean clustering for the COSMO-DE Ensemble. Each cluster has a different colormap.

enstools.plot.interactive_contours(variable, lon=None, lat=None, **kwargs)

Creates a plot of interactive contours.

Parameters

variablexarray

Values of a variable and a range of other parameters describing the variable and 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.

Other optional keyword arguments:

**kwargs

figure: bokeh or plotly figure object: If provided, this figure instance will be used (and returned), otherwise a new figure will be created.
filled: [True | False]: If True a filled contour is plotted, which is the default
selected_backendEnum element, optional, default=Library.BOKEH: Definition of a library for plotting. Element from Library Enum.
aspectfloat, optional, default=None: Aspect ratio between a figure width and a height as a fraction.
sizeint, optional, default=800: Size of a figure width in pixels. Size of a figure height is calculated from an aspectratio.
map_resolution{‘110m’, ‘50m’, ‘10m’}, optional, default=’110m’: Definition of a map resolution.
cmapstr: Name of the color map to use. Default: CMRmap_r
line_widthint: Line width, default is 1.

Returns

figure: Figure object contains interactive contours with a colorbars.

enstools.plot.interactive_streamlines(variable_u, variable_v, lon=None, lat=None, **kwargs)

Creates a plot of interactive streamlines or vectors.

Parameters

variable_u, variable_vxarray.DataArray

u- and v-component of streamline data.

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.

Other optional keyword arguments:

**kwargs

figure: bokeh or plotly figure object: If provided, this figure instance will be used (and returned), otherwise a new figure will be created.
selected_backendEnum element, optional, default=Library.BOKEH: Definition of a library for plotting. Element from Library Enum.
aspectfloat, optional, default=None: Aspect ratio between a figure width and a height as a fraction.
sizeint, optional, default=800: Size of a figure width in pixels. Size of a figure height is calculated from an aspectratio.
map_resolution{‘110m’, ‘50m’, ‘10m’}, optional, default=’110m’: Definition of a map resolution.
line_typeEnum element, optional, default=Stream.LINE: Definition of a line type. Element from Stream Enum.
densityfloat, optional, default=2: Definition of a closeness of streamlines. When density = 1, the domain is divided into a 30x30 grid.
scalefloat, optional, default=0.02: Possibility to scale a size of arrows(for example, to avoid overlap).

Returns

figure: Figure object contains interactive streamlines or vectors.