matplotlib 3.5.1

NotesParametersBackRef
grid(visible=None, which='major', axis='both', **kwargs)

Notes

The axis is drawn as a unit, so the effective zorder for drawing the grid is determined by the zorder of each axis, not by the zorder of the .Line2D objects comprising the grid. Therefore, to set grid zorder, use .set_axisbelow or, for more control, call the ~.Artist.set_zorder method of each axis.

Parameters

visible : bool or None, optional

Whether to show the grid lines. If any kwargs are supplied, it is assumed you want the grid on and visible will be set to True.

If visible is None and there are no kwargs, this toggles the visibility of the lines.

which : {'major', 'minor', 'both'}, optional

The grid lines to apply the changes on.

axis : {'both', 'x', 'y'}, optional

The axis to apply the changes on.

**kwargs : `.Line2D` properties

Define the line properties of the grid, e.g.:

grid(color='r', linestyle='-', linewidth=2)

Valid keyword arguments are:

Properties: agg_filter: a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array alpha: scalar or None animated: bool antialiased or aa: bool clip_box: .Bbox clip_on: bool clip_path: Patch or (Path, Transform) or None color or c: color dash_capstyle: .CapStyle or {'butt', 'projecting', 'round'} dash_joinstyle: .JoinStyle or {'miter', 'round', 'bevel'} dashes: sequence of floats (on/off ink in points) or (None, None) data: (2, N) array or two 1D arrays drawstyle or ds: {'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}, default: 'default' figure: .Figure fillstyle: {'full', 'left', 'right', 'bottom', 'top', 'none'} gid: str in_layout: bool label: object linestyle or ls: {'-', '--', '-.', ':', '', (offset, on-off-seq), ...} linewidth or lw: float marker: marker style string, ~.path.Path or ~.markers.MarkerStyle markeredgecolor or mec: color markeredgewidth or mew: float markerfacecolor or mfc: color markerfacecoloralt or mfcalt: color markersize or ms: float markevery: None or int or (int, int) or slice or list[int] or float or (float, float) or list[bool] path_effects: .AbstractPathEffect picker: float or callable[[Artist, Event], tuple[bool, dict]] pickradius: float rasterized: bool sketch_params: (scale: float, length: float, randomness: float) snap: bool or None solid_capstyle: .CapStyle or {'butt', 'projecting', 'round'} solid_joinstyle: .JoinStyle or {'miter', 'round', 'bevel'} transform: unknown url: str visible: bool xdata: 1D array ydata: 1D array zorder: float

Configure the grid lines.

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy

35 Elements
scipy.signal._waveforms.chirp
scipy.signal._filter_design.sosfreqz
scipy.signal._filter_design.gammatone
scipy.signal._ltisys.dimpulse
scipy.signal._max_len_seq.max_len_seq
scipy.signal._filter_design.freqs
scipy.signal._ltisys.lsim
scipy.linalg._basic.lstsq
scipy.signal._ltisys.dstep
scipy.signal._filter_design.ellip
scipy.interpolate._bspl.evaluate_all_bspl
scipy.signal._filter_design.lp2bs
scipy.signal._filter_design.lp2bp
scipy.signal._fir_filter_design.kaiserord
scipy.signal._ltisys.step2
scipy.signal._filter_design.butter
scipy.signal._signaltools.sosfiltfilt
scipy.signal._signaltools.lfilter
scipy.signal._waveforms.unit_impulse
scipy.signal._filter_design.freqs_zpk
scipy.signal._filter_design.cheby1
scipy.signal._filter_design.bessel
scipy.signal._filter_design.bilinear
scipy.signal._ltisys.lsim2
scipy.signal._ltisys.step
scipy.signal._filter_design.lp2hp
scipy.integrate._odepack_py.odeint
scipy.signal._filter_design.ellipord
scipy.signal._filter_design.lp2lp
scipy.signal._filter_design.cheby2
scipy.signal._filter_design.cheb1ord
scipy.signal._filter_design.buttord
scipy.signal._ltisys.place_poles
scipy.signal._filter_design.bilinear_zpk
scipy.signal._filter_design.cheb2ord

dask

dask.array.random.RandomState.zipf

matplotlib

matplotlib.pyplot.plotting

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


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