`matplotlib.projections`¶

Non-separable transforms that map from data space to screen space.

Projections are defined as Axes subclasses. They include the following elements:

A transformation from data coordinates into display coordinates.
An inverse of that transformation. This is used, for example, to convert mouse positions from screen space back into data space.
Transformations for the gridlines, ticks and ticklabels. Custom projections will often need to place these elements in special locations, and Matplotlib has a facility to help with doing so.
Setting up default values (overriding cla), since the defaults for a rectilinear axes may not be appropriate.
Defining the shape of the axes, for example, an elliptical axes, that will be used to draw the background of the plot and for clipping any data elements.
Defining custom locators and formatters for the projection. For example, in a geographic projection, it may be more convenient to display the grid in degrees, even if the data is in radians.
Set up interactive panning and zooming. This is left as an "advanced" feature left to the reader, but there is an example of this for polar plots in matplotlib.projections.polar.
Any additional methods for additional convenience or features.

Once the projection axes is defined, it can be used in one of two ways:

By defining the class attribute name, the projection axes can be registered with matplotlib.projections.register_projection and subsequently simply invoked by name:
```
fig.add_subplot(projection="my_proj_name")
```
For more complex, parameterisable projections, a generic "projection" object may be defined which includes the method _as_mpl_axes. _as_mpl_axes should take no arguments and return the projection's axes subclass and a dictionary of additional arguments to pass to the subclass' __init__ method. Subsequently a parameterised projection can be initialised with:
```
fig.add_subplot(projection=MyProjection(param1=param1_value))
```
where MyProjection is an object which implements a _as_mpl_axes method.

A full-fledged and heavily annotated example is in Custom projection. The polar plot functionality in matplotlib.projections.polar may also be of interest.

class matplotlib.projections.ProjectionRegistry[source]¶

Bases: object

A mapping of registered projection names to projection classes.

get_projection_class(name)[source]¶: Get a projection class from its name.

get_projection_names()[source]¶: Return the names of all projections currently registered.

register(*projections)[source]¶: Register a new set of projections.

matplotlib.projections.get_projection_class(projection=None)[source]¶

Get a projection class from its name.

If projection is None, a standard rectilinear projection is returned.

matplotlib.projections.get_projection_names()¶: Return the names of all projections currently registered.

matplotlib.projections.register_projection(cls)[source]¶

`matplotlib.projections.polar`¶

class matplotlib.projections.polar.InvertedPolarTransform(axis=None, use_rmin=True, _apply_theta_transforms=True)[source]¶

Bases: matplotlib.transforms.Transform

The inverse of the polar transform, mapping Cartesian coordinate space x and y back to theta and r.

Parameters:	shorthand_namestr A string representing the "name" of the transform. The name carries no significance other than to improve the readability of `str(transform)` when DEBUG=True.

has_inverse = True¶: True if this transform has a corresponding inverse transform.

input_dims = 2¶: The number of input dimensions of this transform. Must be overridden (with integers) in the subclass.

inverted()[source]¶

Return the corresponding inverse transformation.

It holds x == self.inverted().transform(self.transform(x)).

The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

output_dims = 2¶: The number of output dimensions of this transform. Must be overridden (with integers) in the subclass.

transform_non_affine(xy)[source]¶

Apply only the non-affine part of this transformation.

transform(values) is always equivalent to transform_affine(transform_non_affine(values)).

In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.

Parameters:	valuesarray The input values as NumPy array of length `input_dims` or shape (N x `input_dims`).
Returns:	array The output values as NumPy array of length `input_dims` or shape (N x `output_dims`), depending on the input.

class matplotlib.projections.polar.PolarAffine(scale_transform, limits)[source]¶

Bases: matplotlib.transforms.Affine2DBase

The affine part of the polar projection. Scales the output so that maximum radius rests on the edge of the axes circle.

limits is the view limit of the data. The only part of its bounds that is used is the y limits (for the radius limits). The theta range is handled by the non-affine transform.

get_matrix()[source]¶: Get the matrix for the affine part of this transform.

class matplotlib.projections.polar.PolarAxes(*args, theta_offset=0, theta_direction=1, rlabel_position=22.5, **kwargs)[source]¶

Bases: matplotlib.axes._axes.Axes

A polar graph projection, where the input dimensions are theta, r.

Theta starts pointing east and goes anti-clockwise.

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_aspectfloat, optional

Set a fixed aspect for the axes box, i.e. the ratio of height to width. 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`	scalar or None
`anchor`	2-tuple of floats or {'C', 'SW', 'S', 'SE', ...}
`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
`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 float or callable
`position`	[left, bottom, width, height] or `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

Returns:

Axes: The new Axes object.

class InvertedPolarTransform(axis=None, use_rmin=True, _apply_theta_transforms=True)¶

Bases: matplotlib.transforms.Transform

The inverse of the polar transform, mapping Cartesian coordinate space x and y back to theta and r.

Parameters:	shorthand_namestr A string representing the "name" of the transform. The name carries no significance other than to improve the readability of `str(transform)` when DEBUG=True.

has_inverse = True¶: True if this transform has a corresponding inverse transform.

input_dims = 2¶: The number of input dimensions of this transform. Must be overridden (with integers) in the subclass.

inverted()¶

Return the corresponding inverse transformation.

It holds x == self.inverted().transform(self.transform(x)).

The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

output_dims = 2¶: The number of output dimensions of this transform. Must be overridden (with integers) in the subclass.

transform_non_affine(xy)¶

Apply only the non-affine part of this transformation.

transform(values) is always equivalent to transform_affine(transform_non_affine(values)).

In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.

Parameters:	valuesarray The input values as NumPy array of length `input_dims` or shape (N x `input_dims`).
Returns:	array The output values as NumPy array of length `input_dims` or shape (N x `output_dims`), depending on the input.

class PolarAffine(scale_transform, limits)¶

Bases: matplotlib.transforms.Affine2DBase

The affine part of the polar projection. Scales the output so that maximum radius rests on the edge of the axes circle.

limits is the view limit of the data. The only part of its bounds that is used is the y limits (for the radius limits). The theta range is handled by the non-affine transform.

get_matrix()¶: Get the matrix for the affine part of this transform.

class PolarTransform(axis=None, use_rmin=True, _apply_theta_transforms=True)¶

Bases: matplotlib.transforms.Transform

The base polar transform. This handles projection theta and r into Cartesian coordinate space x and y, but does not perform the ultimate affine transformation into the correct position.

Parameters:	shorthand_namestr A string representing the "name" of the transform. The name carries no significance other than to improve the readability of `str(transform)` when DEBUG=True.

has_inverse = True¶: True if this transform has a corresponding inverse transform.

input_dims = 2¶: The number of input dimensions of this transform. Must be overridden (with integers) in the subclass.

inverted()¶

Return the corresponding inverse transformation.

It holds x == self.inverted().transform(self.transform(x)).

The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

output_dims = 2¶: The number of output dimensions of this transform. Must be overridden (with integers) in the subclass.

transform_non_affine(tr)¶

Apply only the non-affine part of this transformation.

transform(values) is always equivalent to transform_affine(transform_non_affine(values)).

In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.

Parameters:	valuesarray The input values as NumPy array of length `input_dims` or shape (N x `input_dims`).
Returns:	array The output values as NumPy array of length `input_dims` or shape (N x `output_dims`), depending on the input.

transform_path_non_affine(path)¶

Apply the non-affine part of this transform to Path path, returning a new Path.

transform_path(path) is equivalent to transform_path_affine(transform_path_non_affine(values)).

class RadialLocator(base, axes=None)¶

Bases: matplotlib.ticker.Locator

Used to locate radius ticks.

Ensures that all ticks are strictly positive. For all other tasks, it delegates to the base Locator (which may be different depending on the scale of the r-axis).

nonsingular(vmin, vmax)¶

Adjust a range as needed to avoid singularities.

This method gets called during autoscaling, with (v0, v1) set to the data limits on the axes if the axes contains any data, or (-inf, +inf) if not.

If v0 == v1 (possibly up to some floating point slop), this method returns an expanded interval around this value.
If (v0, v1) == (-inf, +inf), this method returns appropriate default view limits.
Otherwise, (v0, v1) is returned without modification.

pan(numsteps)¶

[Deprecated]

Notes

Deprecated since version 3.3:

refresh()¶

[Deprecated]

Notes

Deprecated since version 3.3:

view_limits(vmin, vmax)¶

Select a scale for the range from vmin to vmax.

Subclasses should override this method to change locator behaviour.

zoom(direction)¶

[Deprecated]

Notes

Deprecated since version 3.3:

class ThetaFormatter¶

Bases: matplotlib.ticker.Formatter

Used to format the theta tick labels. Converts the native unit of radians into degrees and adds a degree symbol.

class ThetaLocator(base)¶

Bases: matplotlib.ticker.Locator

Used to locate theta ticks.

This will work the same as the base locator except in the case that the view spans the entire circle. In such cases, the previously used default locations of every 45 degrees are returned.

pan(numsteps)¶

[Deprecated]

Notes

Deprecated since version 3.3:

refresh()¶

[Deprecated] Refresh internal information based on current limits.

Notes

Deprecated since version 3.3.

set_axis(axis)¶

view_limits(vmin, vmax)¶

Select a scale for the range from vmin to vmax.

Subclasses should override this method to change locator behaviour.

zoom(direction)¶

[Deprecated]

Notes

Deprecated since version 3.3:

can_pan()[source]¶

Return whether this axes supports the pan/zoom button functionality.

For polar axes, this is slightly misleading. Both panning and zooming are performed by the same button. Panning is performed in azimuth while zooming is done along the radial.

can_zoom()[source]¶

Return whether this axes supports the zoom box button functionality.

Polar axes do not support zoom boxes.

cla()[source]¶: Clear the axes.

drag_pan(button, key, x, y)[source]¶

Called when the mouse moves during a pan operation.

Parameters:	button`MouseButton` The pressed mouse button. keystr or None The pressed key, if any. x, yfloat The mouse coordinates in display coords.

Notes

This is intended to be overridden by new projection types.

draw(renderer, *args, **kwargs)[source]¶

Draw the Artist (and its children) using the given renderer.

This has no effect if the artist is not visible (Artist.get_visible returns False).

Parameters:	renderer`RendererBase` subclass.

Notes

This method is overridden in the Artist subclasses.

end_pan()[source]¶

Called when a pan operation completes (when the mouse button is up.)

Notes

This is intended to be overridden by new projection types.

format_coord(theta, r)[source]¶: Return a format string formatting the x, y coordinates.

get_data_ratio()[source]¶: Return the aspect ratio of the data itself. For a polar plot, this should always be 1.0

get_rlabel_position()[source]¶

Returns:	float The theta position of the radius labels in degrees.

get_rmax()[source]¶

Returns:	float Outer radial limit.

get_rmin()[source]¶

Returns:	float The inner radial limit.

get_rorigin()[source]¶

Returns:	float

get_rsign()[source]¶

get_theta_direction()[source]¶

Get the direction in which theta increases.

-1:: Theta increases in the clockwise direction
1:: Theta increases in the counterclockwise direction

get_theta_offset()[source]¶: Get the offset for the location of 0 in radians.

get_thetamax()[source]¶: Return the maximum theta limit in degrees.

get_thetamin()[source]¶: Get the minimum theta limit in degrees.

get_xaxis_text1_transform(pad)[source]¶

Returns:

transformTransform: The transform used for drawing x-axis labels, which will add pad_points of padding (in points) between the axes and the label. The x-direction is in data coordinates and the y-direction is in axis coordinates
valign{'center', 'top', 'bottom', 'baseline', 'center_baseline'}: The text vertical alignment.
halign{'center', 'left', 'right'}: The text horizontal alignment.

Notes

This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements in different locations.

get_xaxis_text2_transform(pad)[source]¶

Returns:

transformTransform: The transform used for drawing secondary x-axis labels, which will add pad_points of padding (in points) between the axes and the label. The x-direction is in data coordinates and the y-direction is in axis coordinates
valign{'center', 'top', 'bottom', 'baseline', 'center_baseline'}: The text vertical alignment.
halign{'center', 'left', 'right'}: The text horizontal alignment.

Notes

This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements in different locations.

get_xaxis_transform(which='grid')[source]¶: Get the transformation used for drawing x-axis labels, ticks and gridlines. The x-direction is in data coordinates and the y-direction is in axis coordinates.

Note

This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements in different locations.

get_yaxis_text1_transform(pad)[source]¶

Returns:

transformTransform: The transform used for drawing y-axis labels, which will add pad_points of padding (in points) between the axes and the label. The x-direction is in axis coordinates and the y-direction is in data coordinates
valign{'center', 'top', 'bottom', 'baseline', 'center_baseline'}: The text vertical alignment.
halign{'center', 'left', 'right'}: The text horizontal alignment.

Notes

This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements in different locations.

get_yaxis_text2_transform(pad)[source]¶

Returns:

transformTransform: The transform used for drawing secondart y-axis labels, which will add pad_points of padding (in points) between the axes and the label. The x-direction is in axis coordinates and the y-direction is in data coordinates
valign{'center', 'top', 'bottom', 'baseline', 'center_baseline'}: The text vertical alignment.
halign{'center', 'left', 'right'}: The text horizontal alignment.

Notes

This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements in different locations.

get_yaxis_transform(which='grid')[source]¶: Get the transformation used for drawing y-axis labels, ticks and gridlines. The x-direction is in axis coordinates and the y-direction is in data coordinates.

Note

This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements in different locations.

name = 'polar'¶

set_rgrids(radii, labels=None, angle=None, fmt=None, **kwargs)[source]¶

Set the radial gridlines on a polar plot.

Parameters:	radiituple with floats The radii for the radial gridlines labelstuple with strings or None The labels to use at each radial gridline. The `matplotlib.ticker.ScalarFormatter` will be used if None. anglefloat The angular position of the radius labels in degrees. fmtstr or None Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'.
Returns:	lineslist of `lines.Line2D` The radial gridlines. labelslist of `text.Text` The tick labels.
Other Parameters:	*kwargs kwargs* are optional `Text` properties for the labels.

See also

PolarAxes.set_thetagrids
Axis.get_gridlines
Axis.get_ticklabels

set_rlabel_position(value)[source]¶

Update the theta position of the radius labels.

Parameters:	valuenumber The angular position of the radius labels in degrees.

set_rlim(bottom=None, top=None, emit=True, auto=False, **kwargs)[source]¶: See set_ylim.

set_rmax(rmax)[source]¶

Set the outer radial limit.

Parameters:	rmaxfloat

set_rmin(rmin)[source]¶

Set the inner radial limit.

Parameters:	rminfloat

set_rorigin(rorigin)[source]¶

Update the radial origin.

Parameters:	roriginfloat

set_rscale(*args, **kwargs)[source]¶

set_rticks(*args, **kwargs)[source]¶

set_theta_direction(direction)[source]¶

Set the direction in which theta increases.

clockwise, -1:: Theta increases in the clockwise direction
counterclockwise, anticlockwise, 1:: Theta increases in the counterclockwise direction

set_theta_offset(offset)[source]¶: Set the offset for the location of 0 in radians.

set_theta_zero_location(loc, offset=0.0)[source]¶

Set the location of theta's zero.

This simply calls set_theta_offset with the correct value in radians.

Parameters:	locstr May be one of "N", "NW", "W", "SW", "S", "SE", "E", or "NE". offsetfloat, default: 0 An offset in degrees to apply from the specified loc. Note: this offset is always applied counter-clockwise regardless of the direction setting.

set_thetagrids(angles, labels=None, fmt=None, **kwargs)[source]¶

Set the theta gridlines in a polar plot.

Parameters:	anglestuple with floats, degrees The angles of the theta gridlines. labelstuple with strings or None The labels to use at each theta gridline. The `projections.polar.ThetaFormatter` will be used if None. fmtstr or None Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'. Note that the angle that is used is in radians.
Returns:	lineslist of `lines.Line2D` The theta gridlines. labelslist of `text.Text` The tick labels.
Other Parameters:	*kwargs kwargs* are optional `Text` properties for the labels.

See also

PolarAxes.set_rgrids
Axis.get_gridlines
Axis.get_ticklabels

set_thetalim(*args, **kwargs)[source]¶

Set the minimum and maximum theta values.

Can take the following signatures:

set_thetalim(minval, maxval): Set the limits in radians.
set_thetalim(thetamin=minval, thetamax=maxval): Set the limits in degrees.

where minval and maxval are the minimum and maximum limits. Values are wrapped in to the range \([0, 2\pi]\) (in radians), so for example it is possible to do set_thetalim(-np.pi / 2, np.pi / 2) to have an axes symmetric around 0. A ValueError is raised if the absolute angle difference is larger than a full circle.

set_thetamax(thetamax)[source]¶: Set the maximum theta limit in degrees.

set_thetamin(thetamin)[source]¶: Set the minimum theta limit in degrees.

set_ylim(bottom=None, top=None, emit=True, auto=False, *, ymin=None, ymax=None)[source]¶

Set the data limits for the radial axis.

Parameters:

bottomfloat, optional: The bottom limit (default: None, which leaves the bottom limit unchanged). The bottom and top ylims may be passed as the tuple (bottom, top) as the first positional argument (or as the bottom keyword argument).
topfloat, optional: The top limit (default: None, which leaves the top limit unchanged).
emitbool, default: True: Whether to notify observers of limit change.
autobool or None, default: False: Whether to turn on autoscaling of the y-axis. True turns on, False turns off, None leaves unchanged.
ymin, ymaxfloat, optional: These arguments are deprecated and will be removed in a future version. They are equivalent to bottom and top respectively, and it is an error to pass both ymin and bottom or ymax and top.

Returns:

bottom, top(float, float): The new y-axis limits in data coordinates.

set_yscale(*args, **kwargs)[source]¶

Set the y-axis scale.

Parameters:	value{"linear", "log", "symlog", "logit", ...} or `ScaleBase` The axis scale type to apply. **kwargs Different keyword arguments are accepted, depending on the scale. See the respective class keyword arguments: `matplotlib.scale.LinearScale` `matplotlib.scale.LogScale` `matplotlib.scale.SymmetricalLogScale` `matplotlib.scale.LogitScale` `matplotlib.scale.FuncScale`

Notes

By default, Matplotlib supports the above mentioned scales. Additionally, custom scales may be registered using matplotlib.scale.register_scale. These scales can then also be used here.

start_pan(x, y, button)[source]¶

Called when a pan operation has started.

Parameters:	x, yfloat The mouse coordinates in display coords. button`MouseButton` The pressed mouse button.

Notes

This is intended to be overridden by new projection types.

class matplotlib.projections.polar.PolarTransform(axis=None, use_rmin=True, _apply_theta_transforms=True)[source]¶

Bases: matplotlib.transforms.Transform

The base polar transform. This handles projection theta and r into Cartesian coordinate space x and y, but does not perform the ultimate affine transformation into the correct position.

Parameters:	shorthand_namestr A string representing the "name" of the transform. The name carries no significance other than to improve the readability of `str(transform)` when DEBUG=True.

has_inverse = True¶: True if this transform has a corresponding inverse transform.

input_dims = 2¶: The number of input dimensions of this transform. Must be overridden (with integers) in the subclass.

inverted()[source]¶

Return the corresponding inverse transformation.

It holds x == self.inverted().transform(self.transform(x)).

The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

output_dims = 2¶: The number of output dimensions of this transform. Must be overridden (with integers) in the subclass.

transform_non_affine(tr)[source]¶

Apply only the non-affine part of this transformation.

transform(values) is always equivalent to transform_affine(transform_non_affine(values)).

In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.

Parameters:	valuesarray The input values as NumPy array of length `input_dims` or shape (N x `input_dims`).
Returns:	array The output values as NumPy array of length `input_dims` or shape (N x `output_dims`), depending on the input.

transform_path_non_affine(path)[source]¶

Apply the non-affine part of this transform to Path path, returning a new Path.

transform_path(path) is equivalent to transform_path_affine(transform_path_non_affine(values)).

class matplotlib.projections.polar.RadialAxis(*args, **kwargs)[source]¶

Bases: matplotlib.axis.YAxis

A radial Axis.

This overrides certain properties of a YAxis to provide special-casing for a radial axis.

Parameters:	axes`matplotlib.axes.Axes` The `Axes` to which the created Axis belongs. pickradiusfloat The acceptance radius for containment tests. See also `Axis.contains`.

axis_name = 'radius'¶: Read-only name identifying the axis.

cla()[source]¶

[Deprecated]

Notes

Deprecated since version 3.4:

clear()[source]¶

Clear the axis.

This resets axis properties to their default values:

the label
the scale
locators, formatters and ticks
major and minor grid
units
registered callbacks

class matplotlib.projections.polar.RadialLocator(base, axes=None)[source]¶

Bases: matplotlib.ticker.Locator

Used to locate radius ticks.

Ensures that all ticks are strictly positive. For all other tasks, it delegates to the base Locator (which may be different depending on the scale of the r-axis).

nonsingular(vmin, vmax)[source]¶

Adjust a range as needed to avoid singularities.

This method gets called during autoscaling, with (v0, v1) set to the data limits on the axes if the axes contains any data, or (-inf, +inf) if not.

If v0 == v1 (possibly up to some floating point slop), this method returns an expanded interval around this value.
If (v0, v1) == (-inf, +inf), this method returns appropriate default view limits.
Otherwise, (v0, v1) is returned without modification.

pan(numsteps)[source]¶

[Deprecated]

Notes

Deprecated since version 3.3:

refresh()[source]¶

[Deprecated]

Notes

Deprecated since version 3.3:

view_limits(vmin, vmax)[source]¶

Select a scale for the range from vmin to vmax.

Subclasses should override this method to change locator behaviour.

zoom(direction)[source]¶

[Deprecated]

Notes

Deprecated since version 3.3:

class matplotlib.projections.polar.RadialTick(*args, **kwargs)[source]¶

Bases: matplotlib.axis.YTick

A radial-axis tick.

This subclass of YTick provides radial ticks with some small modification to their re-positioning such that ticks are rotated based on axes limits. This results in ticks that are correctly perpendicular to the spine. Labels are also rotated to be perpendicular to the spine, when 'auto' rotation is enabled.

bbox is the Bound2D bounding box in display coords of the Axes loc is the tick location in data coords size is the tick size in points

update_position(loc)[source]¶: Set the location of tick in data coords with scalar loc.

class matplotlib.projections.polar.ThetaAxis(*args, **kwargs)[source]¶

Bases: matplotlib.axis.XAxis

A theta Axis.

This overrides certain properties of an XAxis to provide special-casing for an angular axis.

Parameters:	axes`matplotlib.axes.Axes` The `Axes` to which the created Axis belongs. pickradiusfloat The acceptance radius for containment tests. See also `Axis.contains`.

axis_name = 'theta'¶: Read-only name identifying the axis.

cla()[source]¶

[Deprecated]

Notes

Deprecated since version 3.4:

clear()[source]¶

Clear the axis.

This resets axis properties to their default values:

the label
the scale
locators, formatters and ticks
major and minor grid
units
registered callbacks

class matplotlib.projections.polar.ThetaFormatter[source]¶

Bases: matplotlib.ticker.Formatter

Used to format the theta tick labels. Converts the native unit of radians into degrees and adds a degree symbol.

class matplotlib.projections.polar.ThetaLocator(base)[source]¶

Bases: matplotlib.ticker.Locator

Used to locate theta ticks.

This will work the same as the base locator except in the case that the view spans the entire circle. In such cases, the previously used default locations of every 45 degrees are returned.

pan(numsteps)[source]¶

[Deprecated]

Notes

Deprecated since version 3.3:

refresh()[source]¶

[Deprecated] Refresh internal information based on current limits.

Notes

Deprecated since version 3.3.

set_axis(axis)[source]¶

view_limits(vmin, vmax)[source]¶

Select a scale for the range from vmin to vmax.

Subclasses should override this method to change locator behaviour.

zoom(direction)[source]¶

[Deprecated]

Notes

Deprecated since version 3.3:

class matplotlib.projections.polar.ThetaTick(axes, *args, **kwargs)[source]¶

Bases: matplotlib.axis.XTick

A theta-axis tick.

This subclass of XTick provides angular ticks with some small modification to their re-positioning such that ticks are rotated based on tick location. This results in ticks that are correctly perpendicular to the arc spine.

When 'auto' rotation is enabled, labels are also rotated to be parallel to the spine. The label padding is also applied here since it's not possible to use a generic axes transform to produce tick-specific padding.

bbox is the Bound2D bounding box in display coords of the Axes loc is the tick location in data coords size is the tick size in points

update_position(loc)[source]¶: Set the location of tick in data coords with scalar loc.

`matplotlib.projections.geo`¶

class matplotlib.projections.geo.AitoffAxes(*args, **kwargs)[source]¶

Bases: matplotlib.projections.geo.GeoAxes

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_aspectfloat, optional

Set a fixed aspect for the axes box, i.e. the ratio of height to width. 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`	scalar or None
`anchor`	2-tuple of floats or {'C', 'SW', 'S', 'SE', ...}
`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
`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 float or callable
`position`	[left, bottom, width, height] or `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

Returns:

Axes: The new Axes object.

class AitoffTransform(resolution)[source]¶

Bases: matplotlib.projections.geo._GeoTransform

The base Aitoff transform.

Create a new geographical transform.

Resolution is the number of steps to interpolate between each input line segment to approximate its path in curved space.

has_inverse = True¶: True if this transform has a corresponding inverse transform.

inverted()[source]¶

Return the corresponding inverse transformation.

It holds x == self.inverted().transform(self.transform(x)).

The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

transform_non_affine(ll)[source]¶

Apply only the non-affine part of this transformation.

transform(values) is always equivalent to transform_affine(transform_non_affine(values)).

In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.

Parameters:	valuesarray The input values as NumPy array of length `input_dims` or shape (N x `input_dims`).
Returns:	array The output values as NumPy array of length `input_dims` or shape (N x `output_dims`), depending on the input.

class InvertedAitoffTransform(resolution)[source]¶

Bases: matplotlib.projections.geo._GeoTransform

Create a new geographical transform.

Resolution is the number of steps to interpolate between each input line segment to approximate its path in curved space.

has_inverse = True¶: True if this transform has a corresponding inverse transform.

inverted()[source]¶

Return the corresponding inverse transformation.

It holds x == self.inverted().transform(self.transform(x)).

The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

transform_non_affine(xy)[source]¶

Apply only the non-affine part of this transformation.

transform(values) is always equivalent to transform_affine(transform_non_affine(values)).

In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.

Parameters:	valuesarray The input values as NumPy array of length `input_dims` or shape (N x `input_dims`).
Returns:	array The output values as NumPy array of length `input_dims` or shape (N x `output_dims`), depending on the input.

name = 'aitoff'¶

class matplotlib.projections.geo.GeoAxes(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

An abstract base class for geographic projections.

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_aspectfloat, optional

Set a fixed aspect for the axes box, i.e. the ratio of height to width. 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`	scalar or None
`anchor`	2-tuple of floats or {'C', 'SW', 'S', 'SE', ...}
`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
`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 float or callable
`position`	[left, bottom, width, height] or `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

Returns:

Axes: The new Axes object.

RESOLUTION = 75¶

class ThetaFormatter(round_to=1.0)[source]¶

Bases: matplotlib.ticker.Formatter

Used to format the theta tick labels. Converts the native unit of radians into degrees and adds a degree symbol.

can_pan()[source]¶

Return whether this axes supports the pan/zoom button functionality.

This axes object does not support interactive pan/zoom.

can_zoom()[source]¶

Return whether this axes supports the zoom box button functionality.

This axes object does not support interactive zoom box.

cla()[source]¶: Clear the axes.

drag_pan(button, key, x, y)[source]¶

Called when the mouse moves during a pan operation.

Parameters:	button`MouseButton` The pressed mouse button. keystr or None The pressed key, if any. x, yfloat The mouse coordinates in display coords.

Notes

This is intended to be overridden by new projection types.

end_pan()[source]¶

Called when a pan operation completes (when the mouse button is up.)

Notes

This is intended to be overridden by new projection types.

format_coord(lon, lat)[source]¶: Return a format string formatting the coordinate.

get_data_ratio()[source]¶: Return the aspect ratio of the data itself.

get_xaxis_text1_transform(pad)[source]¶

Returns:

transformTransform: The transform used for drawing x-axis labels, which will add pad_points of padding (in points) between the axes and the label. The x-direction is in data coordinates and the y-direction is in axis coordinates
valign{'center', 'top', 'bottom', 'baseline', 'center_baseline'}: The text vertical alignment.
halign{'center', 'left', 'right'}: The text horizontal alignment.

Notes

This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements in different locations.

get_xaxis_text2_transform(pad)[source]¶

Returns:

transformTransform: The transform used for drawing secondary x-axis labels, which will add pad_points of padding (in points) between the axes and the label. The x-direction is in data coordinates and the y-direction is in axis coordinates
valign{'center', 'top', 'bottom', 'baseline', 'center_baseline'}: The text vertical alignment.
halign{'center', 'left', 'right'}: The text horizontal alignment.

Notes

This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements in different locations.

get_xaxis_transform(which='grid')[source]¶: Get the transformation used for drawing x-axis labels, ticks and gridlines. The x-direction is in data coordinates and the y-direction is in axis coordinates.

Note

This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements in different locations.

get_yaxis_text1_transform(pad)[source]¶

Returns:

transformTransform: The transform used for drawing y-axis labels, which will add pad_points of padding (in points) between the axes and the label. The x-direction is in axis coordinates and the y-direction is in data coordinates
valign{'center', 'top', 'bottom', 'baseline', 'center_baseline'}: The text vertical alignment.
halign{'center', 'left', 'right'}: The text horizontal alignment.

Notes

This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements in different locations.

get_yaxis_text2_transform(pad)[source]¶

Returns:

transformTransform: The transform used for drawing secondart y-axis labels, which will add pad_points of padding (in points) between the axes and the label. The x-direction is in axis coordinates and the y-direction is in data coordinates
valign{'center', 'top', 'bottom', 'baseline', 'center_baseline'}: The text vertical alignment.
halign{'center', 'left', 'right'}: The text horizontal alignment.

Notes

This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements in different locations.

get_yaxis_transform(which='grid')[source]¶: Get the transformation used for drawing y-axis labels, ticks and gridlines. The x-direction is in axis coordinates and the y-direction is in data coordinates.

Note

This transformation is primarily used by the Axis class, and is meant to be overridden by new kinds of projections that may need to place axis elements in different locations.

set_latitude_grid(degrees)[source]¶: Set the number of degrees between each latitude grid.

set_longitude_grid(degrees)[source]¶: Set the number of degrees between each longitude grid.

set_longitude_grid_ends(degrees)[source]¶: Set the latitude(s) at which to stop drawing the longitude grids.

set_xlim(*args, **kwargs)[source]¶

Set the x-axis view limits.

Parameters:

leftfloat, optional

The left xlim in data coordinates. Passing None leaves the limit unchanged.

The left and right xlims may also be passed as the tuple (left, right) as the first positional argument (or as the left keyword argument).

rightfloat, optional

The right xlim in data coordinates. Passing None leaves the limit unchanged.

emitbool, default: True

Whether to notify observers of limit change.

autobool or None, default: False

Whether to turn on autoscaling of the x-axis. True turns on, False turns off, None leaves unchanged.

xmin, xmaxfloat, optional

They are equivalent to left and right respectively, and it is an error to pass both xmin and left or xmax and right.

Returns:

left, right(float, float): The new x-axis limits in data coordinates.

See also

get_xlim
set_xbound, get_xbound
invert_xaxis, xaxis_inverted

Notes

The left value may be greater than the right value, in which case the x-axis values will decrease from left to right.

Examples

>>> set_xlim(left, right)
>>> set_xlim((left, right))
>>> left, right = set_xlim(left, right)

One limit may be left unchanged.

>>> set_xlim(right=right_lim)

Limits may be passed in reverse order to flip the direction of the x-axis. For example, suppose x represents the number of years before present. The x-axis limits might be set like the following so 5000 years ago is on the left of the plot and the present is on the right.

>>> set_xlim(5000, 0)

set_xscale(*args, **kwargs)¶

Set the y-axis scale.

Parameters:	value{"linear", "log", "symlog", "logit", ...} or `ScaleBase` The axis scale type to apply. **kwargs Different keyword arguments are accepted, depending on the scale. See the respective class keyword arguments: `matplotlib.scale.LinearScale` `matplotlib.scale.LogScale` `matplotlib.scale.SymmetricalLogScale` `matplotlib.scale.LogitScale` `matplotlib.scale.FuncScale`

Notes

By default, Matplotlib supports the above mentioned scales. Additionally, custom scales may be registered using matplotlib.scale.register_scale. These scales can then also be used here.

set_ylim(*args, **kwargs)¶

Set the x-axis view limits.

Parameters:

leftfloat, optional

The left xlim in data coordinates. Passing None leaves the limit unchanged.

The left and right xlims may also be passed as the tuple (left, right) as the first positional argument (or as the left keyword argument).

rightfloat, optional

The right xlim in data coordinates. Passing None leaves the limit unchanged.

emitbool, default: True

Whether to notify observers of limit change.

autobool or None, default: False

Whether to turn on autoscaling of the x-axis. True turns on, False turns off, None leaves unchanged.

xmin, xmaxfloat, optional

They are equivalent to left and right respectively, and it is an error to pass both xmin and left or xmax and right.

Returns:

left, right(float, float): The new x-axis limits in data coordinates.

See also

get_xlim
set_xbound, get_xbound
invert_xaxis, xaxis_inverted

Notes

The left value may be greater than the right value, in which case the x-axis values will decrease from left to right.

Examples

>>> set_xlim(left, right)
>>> set_xlim((left, right))
>>> left, right = set_xlim(left, right)

One limit may be left unchanged.

>>> set_xlim(right=right_lim)

Limits may be passed in reverse order to flip the direction of the x-axis. For example, suppose x represents the number of years before present. The x-axis limits might be set like the following so 5000 years ago is on the left of the plot and the present is on the right.

>>> set_xlim(5000, 0)

set_yscale(*args, **kwargs)[source]¶

Set the y-axis scale.

Parameters:	value{"linear", "log", "symlog", "logit", ...} or `ScaleBase` The axis scale type to apply. **kwargs Different keyword arguments are accepted, depending on the scale. See the respective class keyword arguments: `matplotlib.scale.LinearScale` `matplotlib.scale.LogScale` `matplotlib.scale.SymmetricalLogScale` `matplotlib.scale.LogitScale` `matplotlib.scale.FuncScale`

Notes

By default, Matplotlib supports the above mentioned scales. Additionally, custom scales may be registered using matplotlib.scale.register_scale. These scales can then also be used here.

start_pan(x, y, button)[source]¶

Called when a pan operation has started.

Parameters:	x, yfloat The mouse coordinates in display coords. button`MouseButton` The pressed mouse button.

Notes

This is intended to be overridden by new projection types.

class matplotlib.projections.geo.HammerAxes(*args, **kwargs)[source]¶

Bases: matplotlib.projections.geo.GeoAxes

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_aspectfloat, optional

Set a fixed aspect for the axes box, i.e. the ratio of height to width. 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`	scalar or None
`anchor`	2-tuple of floats or {'C', 'SW', 'S', 'SE', ...}
`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
`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 float or callable
`position`	[left, bottom, width, height] or `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

Returns:

Axes: The new Axes object.

class HammerTransform(resolution)[source]¶

Bases: matplotlib.projections.geo._GeoTransform

The base Hammer transform.

Create a new geographical transform.

Resolution is the number of steps to interpolate between each input line segment to approximate its path in curved space.

has_inverse = True¶: True if this transform has a corresponding inverse transform.

inverted()[source]¶

Return the corresponding inverse transformation.

It holds x == self.inverted().transform(self.transform(x)).

The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

transform_non_affine(ll)[source]¶

Apply only the non-affine part of this transformation.

transform(values) is always equivalent to transform_affine(transform_non_affine(values)).

In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.

Parameters:	valuesarray The input values as NumPy array of length `input_dims` or shape (N x `input_dims`).
Returns:	array The output values as NumPy array of length `input_dims` or shape (N x `output_dims`), depending on the input.

class InvertedHammerTransform(resolution)[source]¶

Bases: matplotlib.projections.geo._GeoTransform

Create a new geographical transform.

Resolution is the number of steps to interpolate between each input line segment to approximate its path in curved space.

has_inverse = True¶: True if this transform has a corresponding inverse transform.

inverted()[source]¶

Return the corresponding inverse transformation.

It holds x == self.inverted().transform(self.transform(x)).

The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

transform_non_affine(xy)[source]¶

Apply only the non-affine part of this transformation.

transform(values) is always equivalent to transform_affine(transform_non_affine(values)).

In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.

Parameters:	valuesarray The input values as NumPy array of length `input_dims` or shape (N x `input_dims`).
Returns:	array The output values as NumPy array of length `input_dims` or shape (N x `output_dims`), depending on the input.

name = 'hammer'¶

class matplotlib.projections.geo.LambertAxes(*args, center_longitude=0, center_latitude=0, **kwargs)[source]¶

Bases: matplotlib.projections.geo.GeoAxes

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_aspectfloat, optional

Set a fixed aspect for the axes box, i.e. the ratio of height to width. 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`	scalar or None
`anchor`	2-tuple of floats or {'C', 'SW', 'S', 'SE', ...}
`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
`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 float or callable
`position`	[left, bottom, width, height] or `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

Returns:

Axes: The new Axes object.

class InvertedLambertTransform(center_longitude, center_latitude, resolution)[source]¶

Bases: matplotlib.projections.geo._GeoTransform

Create a new geographical transform.

Resolution is the number of steps to interpolate between each input line segment to approximate its path in curved space.

has_inverse = True¶: True if this transform has a corresponding inverse transform.

inverted()[source]¶

Return the corresponding inverse transformation.

It holds x == self.inverted().transform(self.transform(x)).

The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

transform_non_affine(xy)[source]¶

Apply only the non-affine part of this transformation.

transform(values) is always equivalent to transform_affine(transform_non_affine(values)).

In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.

Parameters:	valuesarray The input values as NumPy array of length `input_dims` or shape (N x `input_dims`).
Returns:	array The output values as NumPy array of length `input_dims` or shape (N x `output_dims`), depending on the input.

class LambertTransform(center_longitude, center_latitude, resolution)[source]¶

Bases: matplotlib.projections.geo._GeoTransform

The base Lambert transform.

Create a new Lambert transform. Resolution is the number of steps to interpolate between each input line segment to approximate its path in curved Lambert space.

has_inverse = True¶: True if this transform has a corresponding inverse transform.

inverted()[source]¶

Return the corresponding inverse transformation.

It holds x == self.inverted().transform(self.transform(x)).

The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

transform_non_affine(ll)[source]¶

Apply only the non-affine part of this transformation.

transform(values) is always equivalent to transform_affine(transform_non_affine(values)).

In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.

Parameters:	valuesarray The input values as NumPy array of length `input_dims` or shape (N x `input_dims`).
Returns:	array The output values as NumPy array of length `input_dims` or shape (N x `output_dims`), depending on the input.

cla()[source]¶: Clear the axes.

name = 'lambert'¶

class matplotlib.projections.geo.MollweideAxes(*args, **kwargs)[source]¶

Bases: matplotlib.projections.geo.GeoAxes

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_aspectfloat, optional

Set a fixed aspect for the axes box, i.e. the ratio of height to width. 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`	scalar or None
`anchor`	2-tuple of floats or {'C', 'SW', 'S', 'SE', ...}
`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
`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 float or callable
`position`	[left, bottom, width, height] or `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

Returns:

Axes: The new Axes object.

class InvertedMollweideTransform(resolution)[source]¶

Bases: matplotlib.projections.geo._GeoTransform

Create a new geographical transform.

Resolution is the number of steps to interpolate between each input line segment to approximate its path in curved space.

has_inverse = True¶: True if this transform has a corresponding inverse transform.

inverted()[source]¶

Return the corresponding inverse transformation.

It holds x == self.inverted().transform(self.transform(x)).

The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

transform_non_affine(xy)[source]¶

Apply only the non-affine part of this transformation.

transform(values) is always equivalent to transform_affine(transform_non_affine(values)).

In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.

Parameters:	valuesarray The input values as NumPy array of length `input_dims` or shape (N x `input_dims`).
Returns:	array The output values as NumPy array of length `input_dims` or shape (N x `output_dims`), depending on the input.

class MollweideTransform(resolution)[source]¶

Bases: matplotlib.projections.geo._GeoTransform

The base Mollweide transform.

Create a new geographical transform.

Resolution is the number of steps to interpolate between each input line segment to approximate its path in curved space.

has_inverse = True¶: True if this transform has a corresponding inverse transform.

inverted()[source]¶

Return the corresponding inverse transformation.

It holds x == self.inverted().transform(self.transform(x)).

The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy.

transform_non_affine(ll)[source]¶

Apply only the non-affine part of this transformation.

transform(values) is always equivalent to transform_affine(transform_non_affine(values)).

In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.

Parameters:	valuesarray The input values as NumPy array of length `input_dims` or shape (N x `input_dims`).
Returns:	array The output values as NumPy array of length `input_dims` or shape (N x `output_dims`), depending on the input.

name = 'mollweide'¶

matplotlib.projections¶

matplotlib.projections.polar¶

matplotlib.projections.geo¶

`matplotlib.projections`¶

`matplotlib.projections.polar`¶

`matplotlib.projections.geo`¶