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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.
|
matplotlib.projections_api#matplotlib.projections.geo.HammerAxes.InvertedHammerTransform.transform_non_affine
|
name='hammer'
|
matplotlib.projections_api#matplotlib.projections.geo.HammerAxes.name
|
set(*, adjustable=<UNSET>, agg_filter=<UNSET>, alpha=<UNSET>, anchor=<UNSET>, animated=<UNSET>, aspect=<UNSET>, autoscale_on=<UNSET>, autoscalex_on=<UNSET>, autoscaley_on=<UNSET>, axes_locator=<UNSET>, axisbelow=<UNSET>, box_aspect=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, facecolor=<UNSET>, frame_on=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, label=<UNSET>, latitude_grid=<UNSET>, longitude_grid=<UNSET>, longitude_grid_ends=<UNSET>, navigate=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, position=<UNSET>, prop_cycle=<UNSET>, rasterization_zorder=<UNSET>, rasterized=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, title=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, xbound=<UNSET>, xlabel=<UNSET>, xlim=<UNSET>, xmargin=<UNSET>, xscale=<UNSET>, xticklabels=<UNSET>, xticks=<UNSET>, ybound=<UNSET>, ylabel=<UNSET>, ylim=<UNSET>, ymargin=<UNSET>, yscale=<UNSET>, yticklabels=<UNSET>, yticks=<UNSET>, zorder=<UNSET>)[source]
Set multiple properties at once. Supported properties are
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 (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
latitude_grid unknown
longitude_grid unknown
longitude_grid_ends unknown
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 unknown
xmargin float greater than -0.5
xscale unknown
xticklabels unknown
xticks unknown
ybound unknown
ylabel str
ylim unknown
ymargin float greater than -0.5
yscale unknown
yticklabels unknown
yticks unknown
zorder float
|
matplotlib.projections_api#matplotlib.projections.geo.HammerAxes.set
|
classmatplotlib.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 built in the Figure fig.
rect[left, bottom, width, height]
The Axes is built 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 (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 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. classInvertedLambertTransform(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.
classLambertTransform(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'
set(*, adjustable=<UNSET>, agg_filter=<UNSET>, alpha=<UNSET>, anchor=<UNSET>, animated=<UNSET>, aspect=<UNSET>, autoscale_on=<UNSET>, autoscalex_on=<UNSET>, autoscaley_on=<UNSET>, axes_locator=<UNSET>, axisbelow=<UNSET>, box_aspect=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, facecolor=<UNSET>, frame_on=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, label=<UNSET>, latitude_grid=<UNSET>, longitude_grid=<UNSET>, longitude_grid_ends=<UNSET>, navigate=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, position=<UNSET>, prop_cycle=<UNSET>, rasterization_zorder=<UNSET>, rasterized=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, title=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, xbound=<UNSET>, xlabel=<UNSET>, xlim=<UNSET>, xmargin=<UNSET>, xscale=<UNSET>, xticklabels=<UNSET>, xticks=<UNSET>, ybound=<UNSET>, ylabel=<UNSET>, ylim=<UNSET>, ymargin=<UNSET>, yscale=<UNSET>, yticklabels=<UNSET>, yticks=<UNSET>, zorder=<UNSET>)[source]
Set multiple properties at once. Supported properties are
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 (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
latitude_grid unknown
longitude_grid unknown
longitude_grid_ends unknown
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 unknown
xmargin float greater than -0.5
xscale unknown
xticklabels unknown
xticks unknown
ybound unknown
ylabel str
ylim unknown
ymargin float greater than -0.5
yscale unknown
yticklabels unknown
yticks unknown
zorder float
|
matplotlib.projections_api#matplotlib.projections.geo.LambertAxes
|
cla()[source]
Clear the Axes.
|
matplotlib.projections_api#matplotlib.projections.geo.LambertAxes.cla
|
classInvertedLambertTransform(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.
|
matplotlib.projections_api#matplotlib.projections.geo.LambertAxes.InvertedLambertTransform
|
has_inverse=True
True if this transform has a corresponding inverse transform.
|
matplotlib.projections_api#matplotlib.projections.geo.LambertAxes.InvertedLambertTransform.has_inverse
|
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.
|
matplotlib.projections_api#matplotlib.projections.geo.LambertAxes.InvertedLambertTransform.inverted
|
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.
|
matplotlib.projections_api#matplotlib.projections.geo.LambertAxes.InvertedLambertTransform.transform_non_affine
|
classLambertTransform(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.
|
matplotlib.projections_api#matplotlib.projections.geo.LambertAxes.LambertTransform
|
has_inverse=True
True if this transform has a corresponding inverse transform.
|
matplotlib.projections_api#matplotlib.projections.geo.LambertAxes.LambertTransform.has_inverse
|
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.
|
matplotlib.projections_api#matplotlib.projections.geo.LambertAxes.LambertTransform.inverted
|
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.
|
matplotlib.projections_api#matplotlib.projections.geo.LambertAxes.LambertTransform.transform_non_affine
|
name='lambert'
|
matplotlib.projections_api#matplotlib.projections.geo.LambertAxes.name
|
set(*, adjustable=<UNSET>, agg_filter=<UNSET>, alpha=<UNSET>, anchor=<UNSET>, animated=<UNSET>, aspect=<UNSET>, autoscale_on=<UNSET>, autoscalex_on=<UNSET>, autoscaley_on=<UNSET>, axes_locator=<UNSET>, axisbelow=<UNSET>, box_aspect=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, facecolor=<UNSET>, frame_on=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, label=<UNSET>, latitude_grid=<UNSET>, longitude_grid=<UNSET>, longitude_grid_ends=<UNSET>, navigate=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, position=<UNSET>, prop_cycle=<UNSET>, rasterization_zorder=<UNSET>, rasterized=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, title=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, xbound=<UNSET>, xlabel=<UNSET>, xlim=<UNSET>, xmargin=<UNSET>, xscale=<UNSET>, xticklabels=<UNSET>, xticks=<UNSET>, ybound=<UNSET>, ylabel=<UNSET>, ylim=<UNSET>, ymargin=<UNSET>, yscale=<UNSET>, yticklabels=<UNSET>, yticks=<UNSET>, zorder=<UNSET>)[source]
Set multiple properties at once. Supported properties are
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 (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
latitude_grid unknown
longitude_grid unknown
longitude_grid_ends unknown
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 unknown
xmargin float greater than -0.5
xscale unknown
xticklabels unknown
xticks unknown
ybound unknown
ylabel str
ylim unknown
ymargin float greater than -0.5
yscale unknown
yticklabels unknown
yticks unknown
zorder float
|
matplotlib.projections_api#matplotlib.projections.geo.LambertAxes.set
|
classmatplotlib.projections.geo.MollweideAxes(*args, **kwargs)[source]
Bases: matplotlib.projections.geo.GeoAxes Build an Axes in a figure. Parameters
figFigure
The Axes is built in the Figure fig.
rect[left, bottom, width, height]
The Axes is built 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 (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 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. classInvertedMollweideTransform(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.
classMollweideTransform(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'
set(*, adjustable=<UNSET>, agg_filter=<UNSET>, alpha=<UNSET>, anchor=<UNSET>, animated=<UNSET>, aspect=<UNSET>, autoscale_on=<UNSET>, autoscalex_on=<UNSET>, autoscaley_on=<UNSET>, axes_locator=<UNSET>, axisbelow=<UNSET>, box_aspect=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, facecolor=<UNSET>, frame_on=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, label=<UNSET>, latitude_grid=<UNSET>, longitude_grid=<UNSET>, longitude_grid_ends=<UNSET>, navigate=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, position=<UNSET>, prop_cycle=<UNSET>, rasterization_zorder=<UNSET>, rasterized=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, title=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, xbound=<UNSET>, xlabel=<UNSET>, xlim=<UNSET>, xmargin=<UNSET>, xscale=<UNSET>, xticklabels=<UNSET>, xticks=<UNSET>, ybound=<UNSET>, ylabel=<UNSET>, ylim=<UNSET>, ymargin=<UNSET>, yscale=<UNSET>, yticklabels=<UNSET>, yticks=<UNSET>, zorder=<UNSET>)[source]
Set multiple properties at once. Supported properties are
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 (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
latitude_grid unknown
longitude_grid unknown
longitude_grid_ends unknown
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 unknown
xmargin float greater than -0.5
xscale unknown
xticklabels unknown
xticks unknown
ybound unknown
ylabel str
ylim unknown
ymargin float greater than -0.5
yscale unknown
yticklabels unknown
yticks unknown
zorder float
|
matplotlib.projections_api#matplotlib.projections.geo.MollweideAxes
|
classInvertedMollweideTransform(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.
|
matplotlib.projections_api#matplotlib.projections.geo.MollweideAxes.InvertedMollweideTransform
|
has_inverse=True
True if this transform has a corresponding inverse transform.
|
matplotlib.projections_api#matplotlib.projections.geo.MollweideAxes.InvertedMollweideTransform.has_inverse
|
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.
|
matplotlib.projections_api#matplotlib.projections.geo.MollweideAxes.InvertedMollweideTransform.inverted
|
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.
|
matplotlib.projections_api#matplotlib.projections.geo.MollweideAxes.InvertedMollweideTransform.transform_non_affine
|
classMollweideTransform(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.
|
matplotlib.projections_api#matplotlib.projections.geo.MollweideAxes.MollweideTransform
|
has_inverse=True
True if this transform has a corresponding inverse transform.
|
matplotlib.projections_api#matplotlib.projections.geo.MollweideAxes.MollweideTransform.has_inverse
|
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.
|
matplotlib.projections_api#matplotlib.projections.geo.MollweideAxes.MollweideTransform.inverted
|
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.
|
matplotlib.projections_api#matplotlib.projections.geo.MollweideAxes.MollweideTransform.transform_non_affine
|
name='mollweide'
|
matplotlib.projections_api#matplotlib.projections.geo.MollweideAxes.name
|
set(*, adjustable=<UNSET>, agg_filter=<UNSET>, alpha=<UNSET>, anchor=<UNSET>, animated=<UNSET>, aspect=<UNSET>, autoscale_on=<UNSET>, autoscalex_on=<UNSET>, autoscaley_on=<UNSET>, axes_locator=<UNSET>, axisbelow=<UNSET>, box_aspect=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, facecolor=<UNSET>, frame_on=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, label=<UNSET>, latitude_grid=<UNSET>, longitude_grid=<UNSET>, longitude_grid_ends=<UNSET>, navigate=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, position=<UNSET>, prop_cycle=<UNSET>, rasterization_zorder=<UNSET>, rasterized=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, title=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, xbound=<UNSET>, xlabel=<UNSET>, xlim=<UNSET>, xmargin=<UNSET>, xscale=<UNSET>, xticklabels=<UNSET>, xticks=<UNSET>, ybound=<UNSET>, ylabel=<UNSET>, ylim=<UNSET>, ymargin=<UNSET>, yscale=<UNSET>, yticklabels=<UNSET>, yticks=<UNSET>, zorder=<UNSET>)[source]
Set multiple properties at once. Supported properties are
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 (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
latitude_grid unknown
longitude_grid unknown
longitude_grid_ends unknown
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 unknown
xmargin float greater than -0.5
xscale unknown
xticklabels unknown
xticks unknown
ybound unknown
ylabel str
ylim unknown
ymargin float greater than -0.5
yscale unknown
yticklabels unknown
yticks unknown
zorder float
|
matplotlib.projections_api#matplotlib.projections.geo.MollweideAxes.set
|
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_api#matplotlib.projections.get_projection_class
|
matplotlib.projections.get_projection_names()[source]
Return the names of all projections currently registered.
|
matplotlib.projections_api#matplotlib.projections.get_projection_names
|
classmatplotlib.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.
|
matplotlib.projections_api#matplotlib.projections.polar.InvertedPolarTransform
|
has_inverse=True
True if this transform has a corresponding inverse transform.
|
matplotlib.projections_api#matplotlib.projections.polar.InvertedPolarTransform.has_inverse
|
input_dims=2
The number of input dimensions of this transform. Must be overridden (with integers) in the subclass.
|
matplotlib.projections_api#matplotlib.projections.polar.InvertedPolarTransform.input_dims
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.InvertedPolarTransform.inverted
|
output_dims=2
The number of output dimensions of this transform. Must be overridden (with integers) in the subclass.
|
matplotlib.projections_api#matplotlib.projections.polar.InvertedPolarTransform.output_dims
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.InvertedPolarTransform.transform_non_affine
|
classmatplotlib.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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAffine
|
get_matrix()[source]
Get the matrix for the affine part of this transform.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAffine.get_matrix
|
classmatplotlib.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 built in the Figure fig.
rect[left, bottom, width, height]
The Axes is built 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 (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 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. classInvertedPolarTransform(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.
classPolarAffine(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.
classPolarTransform(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)).
classRadialLocator(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.
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.
classThetaFormatter[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.
classThetaLocator(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. refresh()[source]
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.
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
buttonMouseButton
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)[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
rendererRendererBase 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 axis 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 axis 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 axis 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 axis 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(*, adjustable=<UNSET>, agg_filter=<UNSET>, alpha=<UNSET>, anchor=<UNSET>, animated=<UNSET>, aspect=<UNSET>, autoscale_on=<UNSET>, autoscalex_on=<UNSET>, autoscaley_on=<UNSET>, axes_locator=<UNSET>, axisbelow=<UNSET>, box_aspect=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, facecolor=<UNSET>, frame_on=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, label=<UNSET>, navigate=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, position=<UNSET>, prop_cycle=<UNSET>, rasterization_zorder=<UNSET>, rasterized=<UNSET>, rgrids=<UNSET>, rlabel_position=<UNSET>, rlim=<UNSET>, rmax=<UNSET>, rmin=<UNSET>, rorigin=<UNSET>, rscale=<UNSET>, rticks=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, theta_direction=<UNSET>, theta_offset=<UNSET>, theta_zero_location=<UNSET>, thetagrids=<UNSET>, thetalim=<UNSET>, thetamax=<UNSET>, thetamin=<UNSET>, title=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, xbound=<UNSET>, xlabel=<UNSET>, xlim=<UNSET>, xmargin=<UNSET>, xscale=<UNSET>, xticklabels=<UNSET>, xticks=<UNSET>, ybound=<UNSET>, ylabel=<UNSET>, ylim=<UNSET>, ymargin=<UNSET>, yscale=<UNSET>, yticklabels=<UNSET>, yticks=<UNSET>, zorder=<UNSET>)[source]
Set multiple properties at once. Supported properties are
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 (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 Bbox
prop_cycle unknown
rasterization_zorder float or None
rasterized bool
rgrids tuple with floats
rlabel_position number
rlim unknown
rmax float
rmin float
rorigin float
rscale unknown
rticks unknown
sketch_params (scale: float, length: float, randomness: float)
snap bool or None
theta_direction unknown
theta_offset unknown
theta_zero_location str
thetagrids tuple with floats, degrees
thetalim unknown
thetamax unknown
thetamin unknown
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 float, optional
ymargin float greater than -0.5
yscale unknown
yticklabels unknown
yticks unknown
zorder float
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.
buttonMouseButton
The pressed mouse button. Notes This is intended to be overridden by new projection types.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.can_pan
|
can_zoom()[source]
Return whether this axes supports the zoom box button functionality. Polar axes do not support zoom boxes.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.can_zoom
|
cla()[source]
Clear the Axes.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.cla
|
drag_pan(button, key, x, y)[source]
Called when the mouse moves during a pan operation. Parameters
buttonMouseButton
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.drag_pan
|
draw(renderer)[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
rendererRendererBase subclass.
Notes This method is overridden in the Artist subclasses.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.draw
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.end_pan
|
format_coord(theta, r)[source]
Return a format string formatting the x, y coordinates.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.format_coord
|
get_data_ratio()[source]
Return the aspect ratio of the data itself. For a polar plot, this should always be 1.0
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_data_ratio
|
get_rlabel_position()[source]
Returns
float
The theta position of the radius labels in degrees.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_rlabel_position
|
get_rmax()[source]
Returns
float
Outer radial limit.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_rmax
|
get_rmin()[source]
Returns
float
The inner radial limit.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_rmin
|
get_rorigin()[source]
Returns
float
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_rorigin
|
get_rsign()[source]
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_rsign
|
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
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_theta_direction
|
get_theta_offset()[source]
Get the offset for the location of 0 in radians.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_theta_offset
|
get_thetamax()[source]
Return the maximum theta limit in degrees.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_thetamax
|
get_thetamin()[source]
Get the minimum theta limit in degrees.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_thetamin
|
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 axis 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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_xaxis_text1_transform
|
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 axis 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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_xaxis_text2_transform
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_xaxis_transform
|
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 axis 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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_yaxis_text1_transform
|
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 axis 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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_yaxis_text2_transform
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.get_yaxis_transform
|
classInvertedPolarTransform(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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.InvertedPolarTransform
|
has_inverse=True
True if this transform has a corresponding inverse transform.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.InvertedPolarTransform.has_inverse
|
input_dims=2
The number of input dimensions of this transform. Must be overridden (with integers) in the subclass.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.InvertedPolarTransform.input_dims
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.InvertedPolarTransform.inverted
|
output_dims=2
The number of output dimensions of this transform. Must be overridden (with integers) in the subclass.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.InvertedPolarTransform.output_dims
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.InvertedPolarTransform.transform_non_affine
|
name='polar'
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.name
|
classPolarAffine(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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.PolarAffine
|
get_matrix()[source]
Get the matrix for the affine part of this transform.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.PolarAffine.get_matrix
|
classPolarTransform(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)).
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.PolarTransform
|
has_inverse=True
True if this transform has a corresponding inverse transform.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.PolarTransform.has_inverse
|
input_dims=2
The number of input dimensions of this transform. Must be overridden (with integers) in the subclass.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.PolarTransform.input_dims
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.PolarTransform.inverted
|
output_dims=2
The number of output dimensions of this transform. Must be overridden (with integers) in the subclass.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.PolarTransform.output_dims
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.PolarTransform.transform_non_affine
|
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)).
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.PolarTransform.transform_path_non_affine
|
classRadialLocator(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.
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.RadialLocator
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.RadialLocator.nonsingular
|
set_axis(axis)[source]
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.RadialLocator.set_axis
|
view_limits(vmin, vmax)[source]
Select a scale for the range from vmin to vmax. Subclasses should override this method to change locator behaviour.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.RadialLocator.view_limits
|
set(*, adjustable=<UNSET>, agg_filter=<UNSET>, alpha=<UNSET>, anchor=<UNSET>, animated=<UNSET>, aspect=<UNSET>, autoscale_on=<UNSET>, autoscalex_on=<UNSET>, autoscaley_on=<UNSET>, axes_locator=<UNSET>, axisbelow=<UNSET>, box_aspect=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, facecolor=<UNSET>, frame_on=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, label=<UNSET>, navigate=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, position=<UNSET>, prop_cycle=<UNSET>, rasterization_zorder=<UNSET>, rasterized=<UNSET>, rgrids=<UNSET>, rlabel_position=<UNSET>, rlim=<UNSET>, rmax=<UNSET>, rmin=<UNSET>, rorigin=<UNSET>, rscale=<UNSET>, rticks=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, theta_direction=<UNSET>, theta_offset=<UNSET>, theta_zero_location=<UNSET>, thetagrids=<UNSET>, thetalim=<UNSET>, thetamax=<UNSET>, thetamin=<UNSET>, title=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, xbound=<UNSET>, xlabel=<UNSET>, xlim=<UNSET>, xmargin=<UNSET>, xscale=<UNSET>, xticklabels=<UNSET>, xticks=<UNSET>, ybound=<UNSET>, ylabel=<UNSET>, ylim=<UNSET>, ymargin=<UNSET>, yscale=<UNSET>, yticklabels=<UNSET>, yticks=<UNSET>, zorder=<UNSET>)[source]
Set multiple properties at once. Supported properties are
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 (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 Bbox
prop_cycle unknown
rasterization_zorder float or None
rasterized bool
rgrids tuple with floats
rlabel_position number
rlim unknown
rmax float
rmin float
rorigin float
rscale unknown
rticks unknown
sketch_params (scale: float, length: float, randomness: float)
snap bool or None
theta_direction unknown
theta_offset unknown
theta_zero_location str
thetagrids tuple with floats, degrees
thetalim unknown
thetamax unknown
thetamin unknown
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 float, optional
ymargin float greater than -0.5
yscale unknown
yticklabels unknown
yticks unknown
zorder float
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set
|
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
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_rgrids
|
set_rlabel_position(value)[source]
Update the theta position of the radius labels. Parameters
valuenumber
The angular position of the radius labels in degrees.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_rlabel_position
|
set_rlim(bottom=None, top=None, emit=True, auto=False, **kwargs)[source]
See set_ylim.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_rlim
|
set_rmax(rmax)[source]
Set the outer radial limit. Parameters
rmaxfloat
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_rmax
|
set_rmin(rmin)[source]
Set the inner radial limit. Parameters
rminfloat
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_rmin
|
set_rorigin(rorigin)[source]
Update the radial origin. Parameters
roriginfloat
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_rorigin
|
set_rscale(*args, **kwargs)[source]
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_rscale
|
set_rticks(*args, **kwargs)[source]
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_rticks
|
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
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_theta_direction
|
set_theta_offset(offset)[source]
Set the offset for the location of 0 in radians.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_theta_offset
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_theta_zero_location
|
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
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matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_thetagrids
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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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_thetalim
|
set_thetamax(thetamax)[source]
Set the maximum theta limit in degrees.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_thetamax
|
set_thetamin(thetamin)[source]
Set the minimum theta limit in degrees.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_thetamin
|
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.
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matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_ylim
|
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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.set_yscale
|
start_pan(x, y, button)[source]
Called when a pan operation has started. Parameters
x, yfloat
The mouse coordinates in display coords.
buttonMouseButton
The pressed mouse button. Notes This is intended to be overridden by new projection types.
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matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.start_pan
|
classThetaFormatter[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.
|
matplotlib.projections_api#matplotlib.projections.polar.PolarAxes.ThetaFormatter
|
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