mpl_toolkits.axes_grid1.mpl_axes.Axes¶

class mpl_toolkits.axes_grid1.mpl_axes.Axes(fig, rect, facecolor=None, frameon=True, sharex=None, sharey=None, label='', xscale=None, yscale=None, box_aspect=None, **kwargs)[source]¶

Bases: matplotlib.axes._axes.Axes

Build an axes in a figure.

Parameters:

figFigure

The axes is build in the Figure fig.

rect[left, bottom, width, height]

The axes is build in the rectangle rect. rect is in Figure coordinates.

sharex, shareyAxes, optional

The x or y axis is shared with the x or y axis in the input Axes.

frameonbool, default: True

Whether the axes frame is visible.

box_aspectNone, or a number, optional

Sets the aspect of the axes box. See set_box_aspect for details.

**kwargs

Other optional keyword arguments:

Property	Description
`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`	float or None
`anchor`	2-tuple of floats or {'C', 'SW', 'S', 'SE', ...}
`animated`	bool
`aspect`	{'auto'} or num
`autoscale_on`	bool
`autoscalex_on`	bool
`autoscaley_on`	bool
`axes_locator`	Callable[[Axes, Renderer], Bbox]
`axisbelow`	bool or 'line'
`box_aspect`	None, or a number
`clip_box`	`Bbox`
`clip_on`	bool
`clip_path`	Patch or (Path, Transform) or None
`contains`	unknown
`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 callable
`position`	[left, bottom, width, height] or `Bbox`
`prop_cycle`	unknown
`rasterization_zorder`	float or None
`rasterized`	bool or None
`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", ...}
`xticklabels`	unknown
`xticks`	unknown
`ybound`	unknown
`ylabel`	str
`ylim`	(bottom: float, top: float)
`ymargin`	float greater than -0.5
`yscale`	{"linear", "log", "symlog", "logit", ...}
`yticklabels`	unknown
`yticks`	unknown
`zorder`	float

Returns:

Axes: The new Axes object.

class AxisDict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object's (key, value) pairs dict(iterable) -> new dictionary initialized as if via: d = {} for k, v in iterable: d[k] = v dict(**kwargs) -> new dictionary initialized with the name=value pairs in the keyword argument list. For example: dict(one=1, two=2)[source]¶

Bases: dict

__call__(self, *v, **kwargs)[source]¶: Call self as a function.

__dict__ = mappingproxy({'__module__': 'mpl_toolkits.axes_grid1.mpl_axes', '__init__': <function Axes.AxisDict.__init__>, '__getitem__': <function Axes.AxisDict.__getitem__>, '__call__': <function Axes.AxisDict.__call__>, '__dict__': <attribute '__dict__' of 'AxisDict' objects>, '__weakref__': <attribute '__weakref__' of 'AxisDict' objects>, '__doc__': None})¶

__getitem__(self, k)[source]¶: x.__getitem__(y) <==> x[y]

__init__(self, axes)[source]¶: Initialize self. See help(type(self)) for accurate signature.

__module__ = 'mpl_toolkits.axes_grid1.mpl_axes'¶

__weakref__¶: list of weak references to the object (if defined)

__module__ = 'mpl_toolkits.axes_grid1.mpl_axes'¶

property axis¶

Convenience method to get or set some axis properties.

Call signatures:

xmin, xmax, ymin, ymax = axis()
xmin, xmax, ymin, ymax = axis([xmin, xmax, ymin, ymax])
xmin, xmax, ymin, ymax = axis(option)
xmin, xmax, ymin, ymax = axis(**kwargs)

Parameters:

xmin, xmax, ymin, ymaxfloat, optional

The axis limits to be set. This can also be achieved using

ax.set(xlim=(xmin, xmax), ylim=(ymin, ymax))

optionbool or str

If a bool, turns axis lines and labels on or off. If a string, possible values are:

Value	Description
'on'	Turn on axis lines and labels. Same as `True`.
'off'	Turn off axis lines and labels. Same as `False`.
'equal'	Set equal scaling (i.e., make circles circular) by changing axis limits. This is the same as `ax.set_aspect('equal', adjustable='datalim')`. Explicit data limits may not be respected in this case.
'scaled'	Set equal scaling (i.e., make circles circular) by changing dimensions of the plot box. This is the same as `ax.set_aspect('equal', adjustable='box', anchor='C')`. Additionally, further autoscaling will be disabled.
'tight'	Set limits just large enough to show all data, then disable further autoscaling.
'auto'	Automatic scaling (fill plot box with data).
'image'	'scaled' with axis limits equal to data limits.
'square'	Square plot; similar to 'scaled', but initially forcing `xmax-xmin == ymax-ymin`.

emitbool, default: True