Matplotlib

class matplotlib.projections.ProjectionRegistry [source]

Bases: object

Manages the set of projections available to the system.

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

get_projection_names() [source]: Get a list of the names of all projections currently registered.

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

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.

input_dims = 2

inverted() [source]

Return the corresponding inverse transformation.

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.

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

is_separable = False

output_dims = 2

transform_non_affine(xy) [source]

Performs only the non-affine part of the 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.

Accepts a numpy array of shape (N x input_dims) and returns a numpy array of shape (N x output_dims).

Alternatively, accepts a numpy array of length input_dims and returns a numpy array of length output_dims.

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 Affine transformation array 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:

fig : Figure

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, sharey : Axes, optional

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

frameon : bool, optional

True means that the axes frame is visible.

**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
`anchor`	2-tuple of floats or {'C', 'SW', 'S', 'SE', ...}
`animated`	bool
`aspect`	{'auto', 'equal'} or num
`autoscale_on`	bool
`autoscalex_on`	bool
`autoscaley_on`	bool
`axes_locator`	Callable[[Axes, Renderer], Bbox]
`axisbelow`	bool or 'line'
`clip_box`	`Bbox`
`clip_on`	bool
`clip_path`	[(`Path`, `Transform`) \| `Patch` \| None]
`contains`	callable
`facecolor`	color
`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`
`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`	(lower: float, upper: float)
`xlabel`	str
`xlim`	(left: float, right: float)
`xmargin`	float greater than -0.5
`xscale`	{"linear", "log", "symlog", "logit", ...}
`xticklabels`	List[str]
`xticks`	list
`ybound`	(lower: float, upper: float)
`ylabel`	str
`ylim`	(bottom: float, top: float)
`ymargin`	float greater than -0.5
`yscale`	{"linear", "log", "symlog", "logit", ...}
`yticklabels`	List[str]
`yticks`	list
`zorder`	float

Returns:

axes : 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.

input_dims = 2

inverted()

Return the corresponding inverse transformation.

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.

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

is_separable = False

output_dims = 2

transform_non_affine(xy)

Performs only the non-affine part of the 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.

Accepts a numpy array of shape (N x input_dims) and returns a numpy array of shape (N x output_dims).

Alternatively, accepts a numpy array of length input_dims and returns a numpy array of length output_dims.

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 Affine transformation array 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.

input_dims = 2

inverted()

Return the corresponding inverse transformation.

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.

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

is_separable = False

output_dims = 2

transform_non_affine(tr)

Performs only the non-affine part of the 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.

Accepts a numpy array of shape (N x input_dims) and returns a numpy array of shape (N x output_dims).

Alternatively, accepts a numpy array of length input_dims and returns a numpy array of length output_dims.

transform_path_non_affine(path)

Returns a path, transformed only by the non-affine part of this transform.

path: a Path instance.

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.

autoscale(): autoscale the view limits

pan(numsteps): Pan numticks (can be positive or negative)

refresh(): refresh internal information based on current lim

view_limits(vmin, vmax)

select a scale for the range from vmin to vmax

Normally this method is overridden by subclasses to change locator behaviour.

zoom(direction): Zoom in/out on axis; if direction is >0 zoom in, else zoom out

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.

autoscale(): autoscale the view limits

pan(numsteps): Pan numticks (can be positive or negative)

refresh(): refresh internal information based on current lim

set_axis(axis)

view_limits(vmin, vmax)

select a scale for the range from vmin to vmax

Normally this method is overridden by subclasses to change locator behaviour.

zoom(direction): Zoom in/out on axis; if direction is >0 zoom in, else zoom out

can_pan() [source]

Return True if 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 True if this axes supports the zoom box button functionality.

Polar axes do not support zoom boxes.

cla() [source]: Clear the current axes.

drag_pan(button, key, x, y) [source]

Called when the mouse moves during a pan operation.

button is the mouse button number:

1: LEFT
2: MIDDLE
3: RIGHT

key is a "shift" key

x, y are the mouse coordinates in display coords.

Note

Intended to be overridden by new projection types.

draw(*args, **kwargs) [source]: Draw everything (plot lines, axes, labels)

end_pan() [source]: Called when a pan operation completes (when the mouse button is up.)

Note

Intended to be overridden by new projection types.

format_coord(theta, r) [source]: Return a format string formatting the coordinate using Unicode characters.

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]

get_rmin() [source]

get_rorigin() [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]

get_thetamin() [source]

get_xaxis_text1_transform(pad) [source]

Get the transformation used for drawing x-axis labels, which will add the given amount 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. Returns a 3-tuple of the form:

(transform, valign, halign)

where valign and halign are requested alignments for the text.

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_xaxis_text2_transform(pad) [source]

Get the transformation used for drawing the secondary x-axis labels, which will add the given amount 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. Returns a 3-tuple of the form:

(transform, valign, halign)

where valign and halign are requested alignments for the text.

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_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]

Get the transformation used for drawing y-axis labels, which will add the given amount 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. Returns a 3-tuple of the form:

(transform, valign, halign)

where valign and halign are requested alignments for the text.

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_text2_transform(pad) [source]

Get the transformation used for drawing the secondary y-axis labels, which will add the given amount 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. Returns a 3-tuple of the form:

(transform, valign, halign)

where valign and halign are requested alignments for the text.

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_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:	`radii : tuple with floats` The radii for the radial gridlines `labels : tuple with strings or None` The labels to use at each radial gridline. The `matplotlib.ticker.ScalarFormatter` will be used if None. `angle : float` The angular position of the radius labels in degrees. `fmt : str or None` Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'.
Returns:	`lines, labels : list of lines.Line2D, list of text.Text` lines are the radial gridlines and labels are the tick labels.
Other Parameters:	*kwargs kwargs* are optional `Text` properties for the labels.

set_rlabel_position(value) [source]

Updates the theta position of the radius labels.

Parameters:	`value : number` The angular position of the radius labels in degrees.

set_rlim(*args, **kwargs) [source]

set_rmax(rmax) [source]

set_rmin(rmin) [source]

set_rorigin(rorigin) [source]

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]

Sets the location of theta's zero. (Calls set_theta_offset with the correct value in radians under the hood.)

loc : str: May be one of "N", "NW", "W", "SW", "S", "SE", "E", or "NE".
offset : float, optional: 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:	`angles : tuple with floats, degrees` The angles of the theta gridlines. `labels : tuple with strings or None` The labels to use at each theta gridline. The `projections.polar.ThetaFormatter` will be used if None. `fmt : str or None` Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'. Note that the angle that is used is in radians.
Returns:	`lines, labels : list of lines.Line2D, list of text.Text` lines are the theta gridlines and labels are the tick labels.
Other Parameters:	*kwargs kwargs* are optional `Text` properties for the labels.

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

set_thetamax(thetamax) [source]

set_thetamin(thetamin) [source]

set_xscale(scale, *args, **kwargs) [source]

Set the x-axis scale.

Parameters:	`value : {"linear", "log", "symlog", "logit", ...}` scaling strategy to apply

See also

matplotlib.scale.LinearScale: linear transform
matplotlib.scale.LogTransform: log transform
matplotlib.scale.SymmetricalLogTransform: symlog transform
matplotlib.scale.LogisticTransform: logit transform

Notes

Different kwargs are accepted, depending on the scale. See the scale module for more information.

set_yscale(*args, **kwargs) [source]

Set the y-axis scale.

Parameters:	`value : {"linear", "log", "symlog", "logit", ...}` scaling strategy to apply

See also

matplotlib.scale.LinearScale: linear transform
matplotlib.scale.LogTransform: log transform
matplotlib.scale.SymmetricalLogTransform: symlog transform
matplotlib.scale.LogisticTransform: logit transform

Notes

Different kwargs are accepted, depending on the scale. See the scale module for more information.

start_pan(x, y, button) [source]

Called when a pan operation has started.

x, y are the mouse coordinates in display coords. button is the mouse button number:

1: LEFT
2: MIDDLE
3: RIGHT

Note

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.

input_dims = 2

inverted() [source]

Return the corresponding inverse transformation.

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.

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

is_separable = False

output_dims = 2

transform_non_affine(tr) [source]

Performs only the non-affine part of the 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.

Accepts a numpy array of shape (N x input_dims) and returns a numpy array of shape (N x output_dims).

Alternatively, accepts a numpy array of length input_dims and returns a numpy array of length output_dims.

transform_path_non_affine(path) [source]

Returns a path, transformed only by the non-affine part of this transform.

path: a Path instance.

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.

axis_name = 'radius'

cla() [source]: clear the current axis

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.

autoscale() [source]: autoscale the view limits

pan(numsteps) [source]: Pan numticks (can be positive or negative)

refresh() [source]: refresh internal information based on current lim

view_limits(vmin, vmax) [source]

select a scale for the range from vmin to vmax

Normally this method is overridden by subclasses to change locator behaviour.

zoom(direction) [source]: Zoom in/out on axis; if direction is >0 zoom in, else zoom out

class matplotlib.projections.polar.RadialTick(axes, loc, label, size=None, width=None, color=None, tickdir=None, pad=None, labelsize=None, labelcolor=None, zorder=None, gridOn=None, tick1On=True, tick2On=True, label1On=True, label2On=False, major=True, labelrotation=0, grid_color=None, grid_linestyle=None, grid_linewidth=None, grid_alpha=None, **kw)

[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(axes, pickradius=15) [source]

Bases: matplotlib.axis.XAxis

A theta Axis.

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

Init the axis with the parent Axes instance

axis_name = 'theta'

cla() [source]: clear the current axis

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.

autoscale() [source]: autoscale the view limits

pan(numsteps) [source]: Pan numticks (can be positive or negative)

refresh() [source]: refresh internal information based on current lim

set_axis(axis) [source]

view_limits(vmin, vmax) [source]

select a scale for the range from vmin to vmax

Normally this method is overridden by subclasses to change locator behaviour.

zoom(direction) [source]: Zoom in/out on axis; if direction is >0 zoom in, else zoom out

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.

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

Docs

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projections

matplotlib.projections

matplotlib.projections.polar

Notes

Notes