gca(**kwargs)
If there is currently no Axes on this Figure, a new one is created using :None:None:`.Figure.add_subplot`. (To test whether there is currently an Axes on a Figure, check whether figure.axes
is empty. To test whether there is currently a Figure on the pyplot figure stack, check whether :None:None:`.pyplot.get_fignums()` is empty.)
The following kwargs are supported for ensuring the returned Axes adheres to the given projection etc., and for Axes creation if the active Axes does not exist:
Properties:
adjustable: {'box', 'datalim'} 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 anchor: (float, float) or {'C', 'SW', 'S', 'SE', 'E', 'NE', ...} animated: bool aspect: {'auto', 'equal'} or float autoscale_on: bool autoscalex_on: bool autoscaley_on: bool axes_locator: Callable[[Axes, Renderer], Bbox] axisbelow: bool or 'line' box_aspect: float or None clip_box: .Bbox
clip_on: bool clip_path: Patch or (Path, Transform) or None facecolor or fc: color figure: .Figure
frame_on: bool gid: str in_layout: bool label: object navigate: bool navigate_mode: unknown path_effects: .AbstractPathEffect
picker: None or bool or float or callable position: [left, bottom, width, height] or ~matplotlib.transforms.Bbox
prop_cycle: unknown rasterization_zorder: float or None rasterized: bool sketch_params: (scale: float, length: float, randomness: float) snap: bool or None title: str transform: .Transform
url: str visible: bool xbound: unknown xlabel: str xlim: (bottom: float, top: float) xmargin: float greater than -0.5 xscale: {"linear", "log", "symlog", "logit", ...} or .ScaleBase
xticklabels: unknown xticks: unknown ybound: unknown ylabel: str ylim: (bottom: float, top: float) ymargin: float greater than -0.5 yscale: {"linear", "log", "symlog", "logit", ...} or .ScaleBase
yticklabels: unknown yticks: unknown zorder: float
Get the current Axes.
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.signal._czt.CZT
matplotlib.pyplot.plotting
scipy.signal._czt.czt_points
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