class PolarAxes(Axes):
"""
A polar graph projection, where the input dimensions are *theta*, *r*.
Theta starts pointing east and goes anti-clockwise.
"""
name = 'polar'
def __init__(self, *args, **kwargs):
"""
Create a new Polar Axes for a polar plot.
The following optional kwargs are supported:
- *resolution*: The number of points of interpolation between
each pair of data points. Set to 1 to disable
interpolation.
"""
self.resolution = kwargs.pop('resolution', 1)
self._default_theta_offset = kwargs.pop('theta_offset', 0)
self._default_theta_direction = kwargs.pop('theta_direction', 1)
self._default_rlabel_position = kwargs.pop('rlabel_position', 22.5)
if self.resolution not in (None, 1):
warnings.warn(
"""The resolution kwarg to Polar plots is now ignored.
If you need to interpolate data points, consider running
cbook.simple_linear_interpolation on the data before passing to matplotlib.""")
Axes.__init__(self, *args, **kwargs)
self.set_aspect('equal', adjustable='box', anchor='C')
self.cla()
__init__.__doc__ = Axes.__init__.__doc__
def cla(self):
Axes.cla(self)
self.title.set_y(1.05)
self.xaxis.set_major_formatter(self.ThetaFormatter())
self.xaxis.isDefault_majfmt = True
angles = np.arange(0.0, 360.0, 45.0)
self.set_thetagrids(angles)
self.yaxis.set_major_locator(self.RadialLocator(self.yaxis.get_major_locator()))
self.grid(rcParams['polaraxes.grid'])
self.xaxis.set_ticks_position('none')
self.yaxis.set_ticks_position('none')
self.yaxis.set_tick_params(label1On=True)
# Why do we need to turn on yaxis tick labels, but
# xaxis tick labels are already on?
self.set_theta_offset(self._default_theta_offset)
self.set_theta_direction(self._default_theta_direction)
def _init_axis(self):
"move this out of __init__ because non-separable axes don't use it"
self.xaxis = maxis.XAxis(self)
self.yaxis = maxis.YAxis(self)
# Calling polar_axes.xaxis.cla() or polar_axes.xaxis.cla()
# results in weird artifacts. Therefore we disable this for
# now.
# self.spines['polar'].register_axis(self.yaxis)
self._update_transScale()
def _set_lim_and_transforms(self):
self.transAxes = BboxTransformTo(self.bbox)
# Transforms the x and y axis separately by a scale factor
# It is assumed that this part will have non-linear components
self.transScale = TransformWrapper(IdentityTransform())
# A (possibly non-linear) projection on the (already scaled)
# data. This one is aware of rmin
self.transProjection = self.PolarTransform(self)
# This one is not aware of rmin
self.transPureProjection = self.PolarTransform(self, use_rmin=False)
# An affine transformation on the data, generally to limit the
# range of the axes
self.transProjectionAffine = self.PolarAffine(self.transScale, self.viewLim)
# The complete data transformation stack -- from data all the
# way to display coordinates
self.transData = self.transScale + self.transProjection + \
(self.transProjectionAffine + self.transAxes)
# This is the transform for theta-axis ticks. It is
# equivalent to transData, except it always puts r == 1.0 at
# the edge of the axis circle.
self._xaxis_transform = (
self.transPureProjection +
self.PolarAffine(IdentityTransform(), Bbox.unit()) +
self.transAxes)
# The theta labels are moved from radius == 0.0 to radius == 1.1
self._theta_label1_position = Affine2D().translate(0.0, 1.1)
self._xaxis_text1_transform = (
self._theta_label1_position +
self._xaxis_transform)
self._theta_label2_position = Affine2D().translate(0.0, 1.0 / 1.1)
self._xaxis_text2_transform = (
self._theta_label2_position +
self._xaxis_transform)
# This is the transform for r-axis ticks. It scales the theta
# axis so the gridlines from 0.0 to 1.0, now go from 0.0 to
# 2pi.
self._yaxis_transform = (
Affine2D().scale(np.pi * 2.0, 1.0) +
self.transData)
# The r-axis labels are put at an angle and padded in the r-direction
self._r_label_position = ScaledTranslation(
self._default_rlabel_position, 0.0, Affine2D())
self._yaxis_text_transform = (
self._r_label_position +
Affine2D().scale(1.0 / 360.0, 1.0) +
self._yaxis_transform
)
def get_xaxis_transform(self,which='grid'):
if which not in ['tick1','tick2','grid']:
msg = "'which' must be one of [ 'tick1' | 'tick2' | 'grid' ]"
raise ValueError(msg)
return self._xaxis_transform
def get_xaxis_text1_transform(self, pad):
return self._xaxis_text1_transform, 'center', 'center'
def get_xaxis_text2_transform(self, pad):
return self._xaxis_text2_transform, 'center', 'center'
def get_yaxis_transform(self,which='grid'):
if which not in ['tick1','tick2','grid']:
msg = "'which' must be on of [ 'tick1' | 'tick2' | 'grid' ]"
raise ValueError(msg)
return self._yaxis_transform
def get_yaxis_text1_transform(self, pad):
angle = self.get_rlabel_position()
if angle < 90.:
return self._yaxis_text_transform, 'bottom', 'left'
elif angle < 180.:
return self._yaxis_text_transform, 'bottom', 'right'
elif angle < 270.:
return self._yaxis_text_transform, 'top', 'right'
else:
return self._yaxis_text_transform, 'top', 'left'
def get_yaxis_text2_transform(self, pad):
angle = self.get_rlabel_position()
if angle < 90.:
return self._yaxis_text_transform, 'top', 'right'
elif angle < 180.:
return self._yaxis_text_transform, 'top', 'left'
elif angle < 270.:
return self._yaxis_text_transform, 'bottom', 'left'
else:
return self._yaxis_text_transform, 'bottom', 'right'
def _gen_axes_patch(self):
return Circle((0.5, 0.5), 0.5)
def _gen_axes_spines(self):
return {'polar':mspines.Spine.circular_spine(self,
(0.5, 0.5), 0.5)}
def set_rmax(self, rmax):
self.viewLim.y1 = rmax
def get_rmax(self):
return self.viewLim.ymax
def set_rmin(self, rmin):
self.viewLim.y0 = rmin
def get_rmin(self):
return self.viewLim.ymin
def set_theta_offset(self, offset):
"""
Set the offset for the location of 0 in radians.
"""
self._theta_offset = offset
def get_theta_offset(self):
"""
Get the offset for the location of 0 in radians.
"""
return self._theta_offset
def set_theta_zero_location(self, loc):
"""
Sets the location of theta's zero. (Calls set_theta_offset
with the correct value in radians under the hood.)
May be one of "N", "NW", "W", "SW", "S", "SE", "E", or "NE".
"""
mapping = {
'N': np.pi * 0.5,
'NW': np.pi * 0.75,
'W': np.pi,
'SW': np.pi * 1.25,
'S': np.pi * 1.5,
'SE': np.pi * 1.75,
'E': 0,
'NE': np.pi * 0.25 }
return self.set_theta_offset(mapping[loc])
def set_theta_direction(self, direction):
"""
Set the direction in which theta increases.
clockwise, -1:
Theta increases in the clockwise direction
counterclockwise, anticlockwise, 1:
Theta increases in the counterclockwise direction
"""
if direction in ('clockwise',):
self._direction = -1
elif direction in ('counterclockwise', 'anticlockwise'):
self._direction = 1
elif direction in (1, -1):
self._direction = direction
else:
raise ValueError("direction must be 1, -1, clockwise or counterclockwise")
def get_theta_direction(self):
"""
Get the direction in which theta increases.
-1:
Theta increases in the clockwise direction
1:
Theta increases in the counterclockwise direction
"""
return self._direction
def set_rlim(self, *args, **kwargs):
if 'rmin' in kwargs:
kwargs['ymin'] = kwargs.pop('rmin')
if 'rmax' in kwargs:
kwargs['ymax'] = kwargs.pop('rmax')
return self.set_ylim(*args, **kwargs)
def get_rlabel_position(self):
"""
Returns
-------
float
The theta position of the radius labels in degrees.
"""
return self._r_label_position.to_values()[4]
def set_rlabel_position(self, value):
"""Updates the theta position of the radius labels.
Parameters
----------
value : number
The angular position of the radius labels in degrees.
"""
self._r_label_position._t = (value, 0.0)
self._r_label_position.invalidate()
def set_yscale(self, *args, **kwargs):
Axes.set_yscale(self, *args, **kwargs)
self.yaxis.set_major_locator(
self.RadialLocator(self.yaxis.get_major_locator()))
def set_rscale(self, *args, **kwargs):
return Axes.set_yscale(self, *args, **kwargs)
def set_rticks(self, *args, **kwargs):
return Axes.set_yticks(self, *args, **kwargs)
@docstring.dedent_interpd
def set_thetagrids(self, angles, labels=None, frac=None, fmt=None,
**kwargs):
"""
Set the angles at which to place the theta grids (these
gridlines are equal along the theta dimension). *angles* is in
degrees.
*labels*, if not None, is a ``len(angles)`` list of strings of
the labels to use at each angle.
If *labels* is None, the labels will be ``fmt %% angle``
*frac* is the fraction of the polar axes radius at which to
place the label (1 is the edge). e.g., 1.05 is outside the axes
and 0.95 is inside the axes.
Return value is a list of tuples (*line*, *label*), where
*line* is :class:`~matplotlib.lines.Line2D` instances and the
*label* is :class:`~matplotlib.text.Text` instances.
kwargs are optional text properties for the labels:
%(Text)s
ACCEPTS: sequence of floats
"""
# Make sure we take into account unitized data
angles = self.convert_yunits(angles)
angles = np.asarray(angles, np.float_)
self.set_xticks(angles * (np.pi / 180.0))
if labels is not None:
self.set_xticklabels(labels)
elif fmt is not None:
self.xaxis.set_major_formatter(FormatStrFormatter(fmt))
if frac is not None:
self._theta_label1_position.clear().translate(0.0, frac)
self._theta_label2_position.clear().translate(0.0, 1.0 / frac)
for t in self.xaxis.get_ticklabels():
t.update(kwargs)
return self.xaxis.get_ticklines(), self.xaxis.get_ticklabels()
@docstring.dedent_interpd
def set_rgrids(self, radii, labels=None, angle=None, fmt=None,
**kwargs):
"""
Set the radial locations and labels of the *r* grids.
The labels will appear at radial distances *radii* at the
given *angle* in degrees.
*labels*, if not None, is a ``len(radii)`` list of strings of the
labels to use at each radius.
If *labels* is None, the built-in formatter will be used.
Return value is a list of tuples (*line*, *label*), where
*line* is :class:`~matplotlib.lines.Line2D` instances and the
*label* is :class:`~matplotlib.text.Text` instances.
kwargs are optional text properties for the labels:
%(Text)s
ACCEPTS: sequence of floats
"""
# Make sure we take into account unitized data
radii = self.convert_xunits(radii)
radii = np.asarray(radii)
rmin = radii.min()
if rmin <= 0:
raise ValueError('radial grids must be strictly positive')
self.set_yticks(radii)
if labels is not None:
self.set_yticklabels(labels)
elif fmt is not None:
self.yaxis.set_major_formatter(FormatStrFormatter(fmt))
if angle is None:
angle = self.get_rlabel_position()
self.set_rlabel_position(angle)
for t in self.yaxis.get_ticklabels():
t.update(kwargs)
return self.yaxis.get_gridlines(), self.yaxis.get_ticklabels()
def set_xscale(self, scale, *args, **kwargs):
if scale != 'linear':
raise NotImplementedError("You can not set the xscale on a polar plot.")
def set_xlim(self, *args, **kargs):
# The xlim is fixed, no matter what you do
self.viewLim.intervalx = (0.0, np.pi * 2.0)
def format_coord(self, theta, r):
"""
Return a format string formatting the coordinate using Unicode
characters.
"""
theta /= math.pi
# \u03b8: lower-case theta
# \u03c0: lower-case pi
# \u00b0: degree symbol
return '\u03b8=%0.3f\u03c0 (%0.3f\u00b0), r=%0.3f' % (theta, theta * 180.0, r)
def get_data_ratio(self):
'''
Return the aspect ratio of the data itself. For a polar plot,
this should always be 1.0
'''
return 1.0
### Interactive panning
def can_zoom(self):
"""
Return *True* if this axes supports the zoom box button functionality.
Polar axes do not support zoom boxes.
"""
return False
def can_pan(self) :
"""
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.
"""
return True
def start_pan(self, x, y, button):
angle = np.deg2rad(self.get_rlabel_position())
mode = ''
if button == 1:
epsilon = np.pi / 45.0
t, r = self.transData.inverted().transform_point((x, y))
if t >= angle - epsilon and t <= angle + epsilon:
mode = 'drag_r_labels'
elif button == 3:
mode = 'zoom'
self._pan_start = cbook.Bunch(
rmax = self.get_rmax(),
trans = self.transData.frozen(),
trans_inverse = self.transData.inverted().frozen(),
r_label_angle = self.get_rlabel_position(),
x = x,
y = y,
mode = mode
)
def end_pan(self):
del self._pan_start
def drag_pan(self, button, key, x, y):
p = self._pan_start
if p.mode == 'drag_r_labels':
startt, startr = p.trans_inverse.transform_point((p.x, p.y))
t, r = p.trans_inverse.transform_point((x, y))
# Deal with theta
dt0 = t - startt
dt1 = startt - t
if abs(dt1) < abs(dt0):
dt = abs(dt1) * sign(dt0) * -1.0
else:
dt = dt0 * -1.0
dt = (dt / np.pi) * 180.0
self.set_rlabel_position(p.r_label_angle - dt)
trans, vert1, horiz1 = self.get_yaxis_text1_transform(0.0)
trans, vert2, horiz2 = self.get_yaxis_text2_transform(0.0)
for t in self.yaxis.majorTicks + self.yaxis.minorTicks:
t.label1.set_va(vert1)
t.label1.set_ha(horiz1)
t.label2.set_va(vert2)
t.label2.set_ha(horiz2)
elif p.mode == 'zoom':
startt, startr = p.trans_inverse.transform_point((p.x, p.y))
t, r = p.trans_inverse.transform_point((x, y))
dr = r - startr
# Deal with r
scale = r / startr
self.set_rmax(p.rmax / scale)
class PolarAxes(Axes):
"""
A polar graph projection, where the input dimensions are *theta*, *r*.
Theta starts pointing east and goes anti-clockwise.
"""
name = 'polar'
class PolarTransform(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
output_dims = 2
is_separable = False
def __init__(self, axis=None):
Transform.__init__(self)
self._axis = axis
def transform(self, tr):
xy = np.empty(tr.shape, np.float_)
if self._axis is not None:
rmin = self._axis.viewLim.ymin
else:
rmin = 0
t = tr[:, 0:1]
r = tr[:, 1:2]
x = xy[:, 0:1]
y = xy[:, 1:2]
if rmin != 0:
r = r - rmin
mask = r < 0
x[:] = np.where(mask, np.nan, r * np.cos(t))
y[:] = np.where(mask, np.nan, r * np.sin(t))
else:
x[:] = r * np.cos(t)
y[:] = r * np.sin(t)
return xy
transform.__doc__ = Transform.transform.__doc__
transform_non_affine = transform
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def transform_path(self, path):
vertices = path.vertices
if len(vertices) == 2 and vertices[0, 0] == vertices[1, 0]:
return Path(self.transform(vertices), path.codes)
ipath = path.interpolated(path._interpolation_steps)
return Path(self.transform(ipath.vertices), ipath.codes)
transform_path.__doc__ = Transform.transform_path.__doc__
transform_path_non_affine = transform_path
transform_path_non_affine.__doc__ = Transform.transform_path_non_affine.__doc__
def inverted(self):
return PolarAxes.InvertedPolarTransform(self._axis)
inverted.__doc__ = Transform.inverted.__doc__
class PolarAffine(Affine2DBase):
"""
The affine part of the polar projection. Scales the output so
that maximum radius rests on the edge of the axes circle.
"""
def __init__(self, scale_transform, limits):
"""
*limits* is the view limit of the data. The only part of
its bounds that is used is ymax (for the radius maximum).
The theta range is always fixed to (0, 2pi).
"""
Affine2DBase.__init__(self)
self._scale_transform = scale_transform
self._limits = limits
self.set_children(scale_transform, limits)
self._mtx = None
def get_matrix(self):
if self._invalid:
limits_scaled = self._limits.transformed(self._scale_transform)
yscale = limits_scaled.ymax - limits_scaled.ymin
affine = Affine2D() \
.scale(0.5 / yscale) \
.translate(0.5, 0.5)
self._mtx = affine.get_matrix()
self._inverted = None
self._invalid = 0
return self._mtx
get_matrix.__doc__ = Affine2DBase.get_matrix.__doc__
class InvertedPolarTransform(Transform):
"""
The inverse of the polar transform, mapping Cartesian
coordinate space *x* and *y* back to *theta* and *r*.
"""
input_dims = 2
output_dims = 2
is_separable = False
def __init__(self, axis=None):
Transform.__init__(self)
self._axis = axis
def transform(self, xy):
x = xy[:, 0:1]
y = xy[:, 1:]
r = np.sqrt(x * x + y * y)
if self._axis is not None:
r += self._axis.viewLim.ymin
theta = np.arccos(x / r)
theta = np.where(y < 0, 2 * np.pi - theta, theta)
return np.concatenate((theta, r), 1)
transform.__doc__ = Transform.transform.__doc__
def inverted(self):
return PolarAxes.PolarTransform()
inverted.__doc__ = Transform.inverted.__doc__
class ThetaFormatter(Formatter):
"""
Used to format the *theta* tick labels. Converts the native
unit of radians into degrees and adds a degree symbol.
"""
def __call__(self, x, pos=None):
# \u00b0 : degree symbol
if rcParams['text.usetex'] and not rcParams['text.latex.unicode']:
return r"$%0.0f^\circ$" % ((x / np.pi) * 180.0)
else:
# we use unicode, rather than mathtext with \circ, so
# that it will work correctly with any arbitrary font
# (assuming it has a degree sign), whereas $5\circ$
# will only work correctly with one of the supported
# math fonts (Computer Modern and STIX)
return u"%0.0f\u00b0" % ((x / np.pi) * 180.0)
class RadialLocator(Locator):
"""
Used to locate radius ticks.
Ensures that all ticks are strictly positive. For all other
tasks, it delegates to the base
:class:`~matplotlib.ticker.Locator` (which may be different
depending on the scale of the *r*-axis.
"""
def __init__(self, base):
self.base = base
def __call__(self):
ticks = self.base()
return [x for x in ticks if x > 0]
def autoscale(self):
return self.base.autoscale()
def pan(self, numsteps):
return self.base.pan(numsteps)
def zoom(self, direction):
return self.base.zoom(direction)
def refresh(self):
return self.base.refresh()
def view_limits(self, vmin, vmax):
vmin, vmax = self.base.view_limits(vmin, vmax)
return 0, vmax
def __init__(self, *args, **kwargs):
"""
Create a new Polar Axes for a polar plot.
The following optional kwargs are supported:
- *resolution*: The number of points of interpolation between
each pair of data points. Set to 1 to disable
interpolation.
"""
self._rpad = 0.05
self.resolution = kwargs.pop('resolution', None)
if self.resolution not in (None, 1):
warnings.warn(
"""The resolution kwarg to Polar plots is now ignored.
If you need to interpolate data points, consider running
cbook.simple_linear_interpolation on the data before passing to matplotlib.""")
Axes.__init__(self, *args, **kwargs)
self.set_aspect('equal', adjustable='box', anchor='C')
self.cla()
__init__.__doc__ = Axes.__init__.__doc__
def cla(self):
Axes.cla(self)
self.title.set_y(1.05)
self.xaxis.set_major_formatter(self.ThetaFormatter())
self.xaxis.isDefault_majfmt = True
angles = np.arange(0.0, 360.0, 45.0)
self.set_thetagrids(angles)
self.yaxis.set_major_locator(
self.RadialLocator(self.yaxis.get_major_locator()))
self.grid(rcParams['polaraxes.grid'])
self.xaxis.set_ticks_position('none')
self.yaxis.set_ticks_position('none')
self.yaxis.set_tick_params(label1On=True)
# Why do we need to turn on yaxis tick labels, but
# xaxis tick labels are already on?
def _init_axis(self):
"move this out of __init__ because non-separable axes don't use it"
self.xaxis = maxis.XAxis(self)
self.yaxis = maxis.YAxis(self)
# Calling polar_axes.xaxis.cla() or polar_axes.xaxis.cla()
# results in weird artifacts. Therefore we disable this for
# now.
# self.spines['polar'].register_axis(self.yaxis)
self._update_transScale()
def _set_lim_and_transforms(self):
self.transAxes = BboxTransformTo(self.bbox)
# Transforms the x and y axis separately by a scale factor
# It is assumed that this part will have non-linear components
self.transScale = TransformWrapper(IdentityTransform())
# A (possibly non-linear) projection on the (already scaled)
# data. This one is aware of rmin
self.transProjection = self.PolarTransform(self)
# This one is not aware of rmin
self.transPureProjection = self.PolarTransform()
# An affine transformation on the data, generally to limit the
# range of the axes
self.transProjectionAffine = self.PolarAffine(self.transScale,
self.viewLim)
# The complete data transformation stack -- from data all the
# way to display coordinates
self.transData = self.transScale + self.transProjection + \
(self.transProjectionAffine + self.transAxes)
# This is the transform for theta-axis ticks. It is
# equivalent to transData, except it always puts r == 1.0 at
# the edge of the axis circle.
self._xaxis_transform = (self.transPureProjection + self.PolarAffine(
IdentityTransform(), Bbox.unit()) + self.transAxes)
# The theta labels are moved from radius == 0.0 to radius == 1.1
self._theta_label1_position = Affine2D().translate(0.0, 1.1)
self._xaxis_text1_transform = (self._theta_label1_position +
self._xaxis_transform)
self._theta_label2_position = Affine2D().translate(0.0, 1.0 / 1.1)
self._xaxis_text2_transform = (self._theta_label2_position +
self._xaxis_transform)
# This is the transform for r-axis ticks. It scales the theta
# axis so the gridlines from 0.0 to 1.0, now go from 0.0 to
# 2pi.
self._yaxis_transform = (Affine2D().scale(np.pi * 2.0, 1.0) +
self.transData)
# The r-axis labels are put at an angle and padded in the r-direction
self._r_label1_position = ScaledTranslation(
22.5, self._rpad,
blended_transform_factory(Affine2D(),
BboxTransformToMaxOnly(self.viewLim)))
self._yaxis_text1_transform = (self._r_label1_position +
Affine2D().scale(1.0 / 360.0, 1.0) +
self._yaxis_transform)
self._r_label2_position = ScaledTranslation(
22.5, -self._rpad,
blended_transform_factory(Affine2D(),
BboxTransformToMaxOnly(self.viewLim)))
self._yaxis_text2_transform = (self._r_label2_position +
Affine2D().scale(1.0 / 360.0, 1.0) +
self._yaxis_transform)
def get_xaxis_transform(self, which='grid'):
assert which in ['tick1', 'tick2', 'grid']
return self._xaxis_transform
def get_xaxis_text1_transform(self, pad):
return self._xaxis_text1_transform, 'center', 'center'
def get_xaxis_text2_transform(self, pad):
return self._xaxis_text2_transform, 'center', 'center'
def get_yaxis_transform(self, which='grid'):
assert which in ['tick1', 'tick2', 'grid']
return self._yaxis_transform
def get_yaxis_text1_transform(self, pad):
return self._yaxis_text1_transform, 'center', 'center'
def get_yaxis_text2_transform(self, pad):
return self._yaxis_text2_transform, 'center', 'center'
def _gen_axes_patch(self):
return Circle((0.5, 0.5), 0.5)
def _gen_axes_spines(self):
return {'polar': mspines.Spine.circular_spine(self, (0.5, 0.5), 0.5)}
def set_rmax(self, rmax):
self.viewLim.y1 = rmax
def get_rmax(self):
return self.viewLim.ymax
def set_rmin(self, rmin):
self.viewLim.y0 = rmin
def get_rmin(self):
return self.viewLim.ymin
def set_rlim(self, *args, **kwargs):
if 'rmin' in kwargs:
kwargs['ymin'] = kwargs.pop('rmin')
if 'rmax' in kwargs:
kwargs['ymax'] = kwargs.pop('rmax')
return self.set_ylim(*args, **kwargs)
def set_yscale(self, *args, **kwargs):
Axes.set_yscale(self, *args, **kwargs)
self.yaxis.set_major_locator(
self.RadialLocator(self.yaxis.get_major_locator()))
set_rscale = Axes.set_yscale
set_rticks = Axes.set_yticks
@docstring.dedent_interpd
def set_thetagrids(self,
angles,
labels=None,
frac=None,
fmt=None,
**kwargs):
"""
Set the angles at which to place the theta grids (these
gridlines are equal along the theta dimension). *angles* is in
degrees.
*labels*, if not None, is a ``len(angles)`` list of strings of
the labels to use at each angle.
If *labels* is None, the labels will be ``fmt %% angle``
*frac* is the fraction of the polar axes radius at which to
place the label (1 is the edge). Eg. 1.05 is outside the axes
and 0.95 is inside the axes.
Return value is a list of tuples (*line*, *label*), where
*line* is :class:`~matplotlib.lines.Line2D` instances and the
*label* is :class:`~matplotlib.text.Text` instances.
kwargs are optional text properties for the labels:
%(Text)s
ACCEPTS: sequence of floats
"""
angles = np.asarray(angles, np.float_)
self.set_xticks(angles * (np.pi / 180.0))
if labels is not None:
self.set_xticklabels(labels)
elif fmt is not None:
self.xaxis.set_major_formatter(FormatStrFormatter(fmt))
if frac is not None:
self._theta_label1_position.clear().translate(0.0, frac)
self._theta_label2_position.clear().translate(0.0, 1.0 / frac)
for t in self.xaxis.get_ticklabels():
t.update(kwargs)
return self.xaxis.get_ticklines(), self.xaxis.get_ticklabels()
@docstring.dedent_interpd
def set_rgrids(self,
radii,
labels=None,
angle=None,
rpad=None,
fmt=None,
**kwargs):
"""
Set the radial locations and labels of the *r* grids.
The labels will appear at radial distances *radii* at the
given *angle* in degrees.
*labels*, if not None, is a ``len(radii)`` list of strings of the
labels to use at each radius.
If *labels* is None, the built-in formatter will be used.
*rpad* is a fraction of the max of *radii* which will pad each of
the radial labels in the radial direction.
Return value is a list of tuples (*line*, *label*), where
*line* is :class:`~matplotlib.lines.Line2D` instances and the
*label* is :class:`~matplotlib.text.Text` instances.
kwargs are optional text properties for the labels:
%(Text)s
ACCEPTS: sequence of floats
"""
radii = np.asarray(radii)
rmin = radii.min()
if rmin <= 0:
raise ValueError('radial grids must be strictly positive')
self.set_yticks(radii)
if labels is not None:
self.set_yticklabels(labels)
elif fmt is not None:
self.yaxis.set_major_formatter(FormatStrFormatter(fmt))
if angle is None:
angle = self._r_label1_position.to_values()[4]
if rpad is not None:
self._rpad = rpad
self._r_label1_position._t = (angle, self._rpad)
self._r_label1_position.invalidate()
self._r_label2_position._t = (angle, -self._rpad)
self._r_label2_position.invalidate()
for t in self.yaxis.get_ticklabels():
t.update(kwargs)
return self.yaxis.get_gridlines(), self.yaxis.get_ticklabels()
def set_xscale(self, scale, *args, **kwargs):
if scale != 'linear':
raise NotImplementedError(
"You can not set the xscale on a polar plot.")
def set_xlim(self, *args, **kargs):
# The xlim is fixed, no matter what you do
self.viewLim.intervalx = (0.0, np.pi * 2.0)
def format_coord(self, theta, r):
"""
Return a format string formatting the coordinate using Unicode
characters.
"""
theta /= math.pi
# \u03b8: lower-case theta
# \u03c0: lower-case pi
# \u00b0: degree symbol
return u'\u03b8=%0.3f\u03c0 (%0.3f\u00b0), r=%0.3f' % (theta, theta *
180.0, r)
def get_data_ratio(self):
'''
Return the aspect ratio of the data itself. For a polar plot,
this should always be 1.0
'''
return 1.0
### Interactive panning
def can_zoom(self):
"""
Return True if this axes support the zoom box
"""
return False
def start_pan(self, x, y, button):
angle = self._r_label1_position.to_values()[4] / 180.0 * np.pi
mode = ''
if button == 1:
epsilon = np.pi / 45.0
t, r = self.transData.inverted().transform_point((x, y))
if t >= angle - epsilon and t <= angle + epsilon:
mode = 'drag_r_labels'
elif button == 3:
mode = 'zoom'
self._pan_start = cbook.Bunch(
rmax=self.get_rmax(),
trans=self.transData.frozen(),
trans_inverse=self.transData.inverted().frozen(),
r_label_angle=self._r_label1_position.to_values()[4],
x=x,
y=y,
mode=mode)
def end_pan(self):
del self._pan_start
def drag_pan(self, button, key, x, y):
p = self._pan_start
if p.mode == 'drag_r_labels':
startt, startr = p.trans_inverse.transform_point((p.x, p.y))
t, r = p.trans_inverse.transform_point((x, y))
# Deal with theta
dt0 = t - startt
dt1 = startt - t
if abs(dt1) < abs(dt0):
dt = abs(dt1) * sign(dt0) * -1.0
else:
dt = dt0 * -1.0
dt = (dt / np.pi) * 180.0
rpad = self._rpad
self._r_label1_position._t = (p.r_label_angle - dt, rpad)
self._r_label1_position.invalidate()
self._r_label2_position._t = (p.r_label_angle - dt, -rpad)
self._r_label2_position.invalidate()
elif p.mode == 'zoom':
startt, startr = p.trans_inverse.transform_point((p.x, p.y))
t, r = p.trans_inverse.transform_point((x, y))
dr = r - startr
# Deal with r
scale = r / startr
self.set_rmax(p.rmax / scale)
class PolarAxes(Axes):
"""
A polar graph projection, where the input dimensions are *theta*, *r*.
Theta starts pointing east and goes anti-clockwise.
"""
name = 'polar'
class PolarTransform(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
output_dims = 2
is_separable = False
def __init__(self, axis=None, use_rmin=True):
Transform.__init__(self)
self._axis = axis
self._use_rmin = use_rmin
def transform(self, tr):
xy = np.empty(tr.shape, np.float_)
if self._axis is not None:
if self._use_rmin:
rmin = self._axis.viewLim.ymin
else:
rmin = 0
theta_offset = self._axis.get_theta_offset()
theta_direction = self._axis.get_theta_direction()
else:
rmin = 0
theta_offset = 0
theta_direction = 1
t = tr[:, 0:1]
r = tr[:, 1:2]
x = xy[:, 0:1]
y = xy[:, 1:2]
t *= theta_direction
t += theta_offset
if rmin != 0:
r = r - rmin
mask = r < 0
x[:] = np.where(mask, np.nan, r * np.cos(t))
y[:] = np.where(mask, np.nan, r * np.sin(t))
else:
x[:] = r * np.cos(t)
y[:] = r * np.sin(t)
return xy
transform.__doc__ = Transform.transform.__doc__
transform_non_affine = transform
transform_non_affine.__doc__ = Transform.transform_non_affine.__doc__
def transform_path(self, path):
vertices = path.vertices
if len(vertices) == 2 and vertices[0, 0] == vertices[1, 0]:
return Path(self.transform(vertices), path.codes)
ipath = path.interpolated(path._interpolation_steps)
return Path(self.transform(ipath.vertices), ipath.codes)
transform_path.__doc__ = Transform.transform_path.__doc__
transform_path_non_affine = transform_path
transform_path_non_affine.__doc__ = Transform.transform_path_non_affine.__doc__
def inverted(self):
return PolarAxes.InvertedPolarTransform(self._axis, self._use_rmin)
inverted.__doc__ = Transform.inverted.__doc__
class PolarAffine(Affine2DBase):
"""
The affine part of the polar projection. Scales the output so
that maximum radius rests on the edge of the axes circle.
"""
def __init__(self, scale_transform, limits):
"""
*limits* is the view limit of the data. The only part of
its bounds that is used is ymax (for the radius maximum).
The theta range is always fixed to (0, 2pi).
"""
Affine2DBase.__init__(self)
self._scale_transform = scale_transform
self._limits = limits
self.set_children(scale_transform, limits)
self._mtx = None
def get_matrix(self):
if self._invalid:
limits_scaled = self._limits.transformed(self._scale_transform)
yscale = limits_scaled.ymax - limits_scaled.ymin
affine = Affine2D() \
.scale(0.5 / yscale) \
.translate(0.5, 0.5)
self._mtx = affine.get_matrix()
self._inverted = None
self._invalid = 0
return self._mtx
get_matrix.__doc__ = Affine2DBase.get_matrix.__doc__
class InvertedPolarTransform(Transform):
"""
The inverse of the polar transform, mapping Cartesian
coordinate space *x* and *y* back to *theta* and *r*.
"""
input_dims = 2
output_dims = 2
is_separable = False
def __init__(self, axis=None, use_rmin=True):
Transform.__init__(self)
self._axis = axis
self._use_rmin = use_rmin
def transform(self, xy):
if self._axis is not None:
if self._use_rmin:
rmin = self._axis.viewLim.ymin
else:
rmin = 0
theta_offset = self._axis.get_theta_offset()
theta_direction = self._axis.get_theta_direction()
else:
rmin = 0
theta_offset = 0
theta_direction = 1
x = xy[:, 0:1]
y = xy[:, 1:]
r = np.sqrt(x*x + y*y)
theta = np.arccos(x / r)
theta = np.where(y < 0, 2 * np.pi - theta, theta)
theta -= theta_offset
theta *= theta_direction
r += rmin
return np.concatenate((theta, r), 1)
transform.__doc__ = Transform.transform.__doc__
def inverted(self):
return PolarAxes.PolarTransform(self._axis, self._use_rmin)
inverted.__doc__ = Transform.inverted.__doc__
class ThetaFormatter(Formatter):
"""
Used to format the *theta* tick labels. Converts the native
unit of radians into degrees and adds a degree symbol.
"""
def __call__(self, x, pos=None):
# \u00b0 : degree symbol
if rcParams['text.usetex'] and not rcParams['text.latex.unicode']:
return r"$%0.0f^\circ$" % ((x / np.pi) * 180.0)
else:
# we use unicode, rather than mathtext with \circ, so
# that it will work correctly with any arbitrary font
# (assuming it has a degree sign), whereas $5\circ$
# will only work correctly with one of the supported
# math fonts (Computer Modern and STIX)
return u"%0.0f\u00b0" % ((x / np.pi) * 180.0)
class RadialLocator(Locator):
"""
Used to locate radius ticks.
Ensures that all ticks are strictly positive. For all other
tasks, it delegates to the base
:class:`~matplotlib.ticker.Locator` (which may be different
depending on the scale of the *r*-axis.
"""
def __init__(self, base):
self.base = base
def __call__(self):
ticks = self.base()
return [x for x in ticks if x > 0]
def autoscale(self):
return self.base.autoscale()
def pan(self, numsteps):
return self.base.pan(numsteps)
def zoom(self, direction):
return self.base.zoom(direction)
def refresh(self):
return self.base.refresh()
def view_limits(self, vmin, vmax):
vmin, vmax = self.base.view_limits(vmin, vmax)
return 0, vmax
def __init__(self, *args, **kwargs):
"""
Create a new Polar Axes for a polar plot.
The following optional kwargs are supported:
- *resolution*: The number of points of interpolation between
each pair of data points. Set to 1 to disable
interpolation.
"""
self.resolution = kwargs.pop('resolution', None)
if self.resolution not in (None, 1):
warnings.warn(
"""The resolution kwarg to Polar plots is now ignored.
If you need to interpolate data points, consider running
cbook.simple_linear_interpolation on the data before passing to matplotlib.""")
Axes.__init__(self, *args, **kwargs)
self.set_aspect('equal', adjustable='box', anchor='C')
self.cla()
__init__.__doc__ = Axes.__init__.__doc__
def cla(self):
Axes.cla(self)
self.title.set_y(1.05)
self.xaxis.set_major_formatter(self.ThetaFormatter())
self.xaxis.isDefault_majfmt = True
angles = np.arange(0.0, 360.0, 45.0)
self.set_thetagrids(angles)
self.yaxis.set_major_locator(self.RadialLocator(self.yaxis.get_major_locator()))
self.grid(rcParams['polaraxes.grid'])
self.xaxis.set_ticks_position('none')
self.yaxis.set_ticks_position('none')
self.yaxis.set_tick_params(label1On=True)
# Why do we need to turn on yaxis tick labels, but
# xaxis tick labels are already on?
self.set_theta_offset(0)
self.set_theta_direction(1)
def _init_axis(self):
"move this out of __init__ because non-separable axes don't use it"
self.xaxis = maxis.XAxis(self)
self.yaxis = maxis.YAxis(self)
# Calling polar_axes.xaxis.cla() or polar_axes.xaxis.cla()
# results in weird artifacts. Therefore we disable this for
# now.
# self.spines['polar'].register_axis(self.yaxis)
self._update_transScale()
def _set_lim_and_transforms(self):
self.transAxes = BboxTransformTo(self.bbox)
# Transforms the x and y axis separately by a scale factor
# It is assumed that this part will have non-linear components
self.transScale = TransformWrapper(IdentityTransform())
# A (possibly non-linear) projection on the (already scaled)
# data. This one is aware of rmin
self.transProjection = self.PolarTransform(self)
# This one is not aware of rmin
self.transPureProjection = self.PolarTransform(self, use_rmin=False)
# An affine transformation on the data, generally to limit the
# range of the axes
self.transProjectionAffine = self.PolarAffine(self.transScale, self.viewLim)
# The complete data transformation stack -- from data all the
# way to display coordinates
self.transData = self.transScale + self.transProjection + \
(self.transProjectionAffine + self.transAxes)
# This is the transform for theta-axis ticks. It is
# equivalent to transData, except it always puts r == 1.0 at
# the edge of the axis circle.
self._xaxis_transform = (
self.transPureProjection +
self.PolarAffine(IdentityTransform(), Bbox.unit()) +
self.transAxes)
# The theta labels are moved from radius == 0.0 to radius == 1.1
self._theta_label1_position = Affine2D().translate(0.0, 1.1)
self._xaxis_text1_transform = (
self._theta_label1_position +
self._xaxis_transform)
self._theta_label2_position = Affine2D().translate(0.0, 1.0 / 1.1)
self._xaxis_text2_transform = (
self._theta_label2_position +
self._xaxis_transform)
# This is the transform for r-axis ticks. It scales the theta
# axis so the gridlines from 0.0 to 1.0, now go from 0.0 to
# 2pi.
self._yaxis_transform = (
Affine2D().scale(np.pi * 2.0, 1.0) +
self.transData)
# The r-axis labels are put at an angle and padded in the r-direction
self._r_label_position = ScaledTranslation(
22.5, 0.0, Affine2D())
self._yaxis_text_transform = (
self._r_label_position +
Affine2D().scale(1.0 / 360.0, 1.0) +
self._yaxis_transform
)
def get_xaxis_transform(self,which='grid'):
assert which in ['tick1','tick2','grid']
return self._xaxis_transform
def get_xaxis_text1_transform(self, pad):
return self._xaxis_text1_transform, 'center', 'center'
def get_xaxis_text2_transform(self, pad):
return self._xaxis_text2_transform, 'center', 'center'
def get_yaxis_transform(self,which='grid'):
assert which in ['tick1','tick2','grid']
return self._yaxis_transform
def get_yaxis_text1_transform(self, pad):
angle = self._r_label_position.to_values()[4]
if angle < 90.:
return self._yaxis_text_transform, 'bottom', 'left'
elif angle < 180.:
return self._yaxis_text_transform, 'bottom', 'right'
elif angle < 270.:
return self._yaxis_text_transform, 'top', 'right'
else:
return self._yaxis_text_transform, 'top', 'left'
def get_yaxis_text2_transform(self, pad):
angle = self._r_label_position.to_values()[4]
if angle < 90.:
return self._yaxis_text_transform, 'top', 'right'
elif angle < 180.:
return self._yaxis_text_transform, 'top', 'left'
elif angle < 270.:
return self._yaxis_text_transform, 'bottom', 'left'
else:
return self._yaxis_text_transform, 'bottom', 'right'
def _gen_axes_patch(self):
return Circle((0.5, 0.5), 0.5)
def _gen_axes_spines(self):
return {'polar':mspines.Spine.circular_spine(self,
(0.5, 0.5), 0.5)}
def set_rmax(self, rmax):
self.viewLim.y1 = rmax
def get_rmax(self):
return self.viewLim.ymax
def set_rmin(self, rmin):
self.viewLim.y0 = rmin
def get_rmin(self):
return self.viewLim.ymin
def set_theta_offset(self, offset):
"""
Set the offset for the location of 0 in radians.
"""
self._theta_offset = offset
def get_theta_offset(self):
"""
Get the offset for the location of 0 in radians.
"""
return self._theta_offset
def set_theta_zero_location(self, loc):
"""
Sets the location of theta's zero. (Calls set_theta_offset
with the correct value in radians under the hood.)
May be one of "N", "NW", "W", "SW", "S", "SE", "E", or "NE".
"""
mapping = {
'N': np.pi * 0.5,
'NW': np.pi * 0.75,
'W': np.pi,
'SW': np.pi * 1.25,
'S': np.pi * 1.5,
'SE': np.pi * 1.75,
'E': 0,
'NE': np.pi * 0.25 }
return self.set_theta_offset(mapping[loc])
def set_theta_direction(self, direction):
"""
Set the direction in which theta increases.
clockwise, -1:
Theta increases in the clockwise direction
counterclockwise, anticlockwise, 1:
Theta increases in the counterclockwise direction
"""
if direction in ('clockwise',):
self._direction = -1
elif direction in ('counterclockwise', 'anticlockwise'):
self._direction = 1
elif direction in (1, -1):
self._direction = direction
else:
raise ValueError("direction must be 1, -1, clockwise or counterclockwise")
def get_theta_direction(self):
"""
Get the direction in which theta increases.
-1:
Theta increases in the clockwise direction
1:
Theta increases in the counterclockwise direction
"""
return self._direction
def set_rlim(self, *args, **kwargs):
if 'rmin' in kwargs:
kwargs['ymin'] = kwargs.pop('rmin')
if 'rmax' in kwargs:
kwargs['ymax'] = kwargs.pop('rmax')
return self.set_ylim(*args, **kwargs)
def set_yscale(self, *args, **kwargs):
Axes.set_yscale(self, *args, **kwargs)
self.yaxis.set_major_locator(
self.RadialLocator(self.yaxis.get_major_locator()))
set_rscale = Axes.set_yscale
set_rticks = Axes.set_yticks
@docstring.dedent_interpd
def set_thetagrids(self, angles, labels=None, frac=None, fmt=None,
**kwargs):
"""
Set the angles at which to place the theta grids (these
gridlines are equal along the theta dimension). *angles* is in
degrees.
*labels*, if not None, is a ``len(angles)`` list of strings of
the labels to use at each angle.
If *labels* is None, the labels will be ``fmt %% angle``
*frac* is the fraction of the polar axes radius at which to
place the label (1 is the edge). Eg. 1.05 is outside the axes
and 0.95 is inside the axes.
Return value is a list of tuples (*line*, *label*), where
*line* is :class:`~matplotlib.lines.Line2D` instances and the
*label* is :class:`~matplotlib.text.Text` instances.
kwargs are optional text properties for the labels:
%(Text)s
ACCEPTS: sequence of floats
"""
# Make sure we take into account unitized data
angles = self.convert_yunits(angles)
angles = np.asarray(angles, np.float_)
self.set_xticks(angles * (np.pi / 180.0))
if labels is not None:
self.set_xticklabels(labels)
elif fmt is not None:
self.xaxis.set_major_formatter(FormatStrFormatter(fmt))
if frac is not None:
self._theta_label1_position.clear().translate(0.0, frac)
self._theta_label2_position.clear().translate(0.0, 1.0 / frac)
for t in self.xaxis.get_ticklabels():
t.update(kwargs)
return self.xaxis.get_ticklines(), self.xaxis.get_ticklabels()
@docstring.dedent_interpd
def set_rgrids(self, radii, labels=None, angle=None, fmt=None,
**kwargs):
"""
Set the radial locations and labels of the *r* grids.
The labels will appear at radial distances *radii* at the
given *angle* in degrees.
*labels*, if not None, is a ``len(radii)`` list of strings of the
labels to use at each radius.
If *labels* is None, the built-in formatter will be used.
Return value is a list of tuples (*line*, *label*), where
*line* is :class:`~matplotlib.lines.Line2D` instances and the
*label* is :class:`~matplotlib.text.Text` instances.
kwargs are optional text properties for the labels:
%(Text)s
ACCEPTS: sequence of floats
"""
# Make sure we take into account unitized data
radii = self.convert_xunits(radii)
radii = np.asarray(radii)
rmin = radii.min()
if rmin <= 0:
raise ValueError('radial grids must be strictly positive')
self.set_yticks(radii)
if labels is not None:
self.set_yticklabels(labels)
elif fmt is not None:
self.yaxis.set_major_formatter(FormatStrFormatter(fmt))
if angle is None:
angle = self._r_label_position.to_values()[4]
self._r_label_position._t = (angle, 0.0)
self._r_label_position.invalidate()
for t in self.yaxis.get_ticklabels():
t.update(kwargs)
return self.yaxis.get_gridlines(), self.yaxis.get_ticklabels()
def set_xscale(self, scale, *args, **kwargs):
if scale != 'linear':
raise NotImplementedError("You can not set the xscale on a polar plot.")
def set_xlim(self, *args, **kargs):
# The xlim is fixed, no matter what you do
self.viewLim.intervalx = (0.0, np.pi * 2.0)
def format_coord(self, theta, r):
"""
Return a format string formatting the coordinate using Unicode
characters.
"""
theta /= math.pi
# \u03b8: lower-case theta
# \u03c0: lower-case pi
# \u00b0: degree symbol
return u'\u03b8=%0.3f\u03c0 (%0.3f\u00b0), r=%0.3f' % (theta, theta * 180.0, r)
def get_data_ratio(self):
'''
Return the aspect ratio of the data itself. For a polar plot,
this should always be 1.0
'''
return 1.0
### Interactive panning
def can_zoom(self):
"""
Return *True* if this axes supports the zoom box button functionality.
Polar axes do not support zoom boxes.
"""
return False
def can_pan(self) :
"""
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.
"""
return True
def start_pan(self, x, y, button):
angle = np.deg2rad(self._r_label_position.to_values()[4])
mode = ''
if button == 1:
epsilon = np.pi / 45.0
t, r = self.transData.inverted().transform_point((x, y))
if t >= angle - epsilon and t <= angle + epsilon:
mode = 'drag_r_labels'
elif button == 3:
mode = 'zoom'
self._pan_start = cbook.Bunch(
rmax = self.get_rmax(),
trans = self.transData.frozen(),
trans_inverse = self.transData.inverted().frozen(),
r_label_angle = self._r_label_position.to_values()[4],
x = x,
y = y,
mode = mode
)
def end_pan(self):
del self._pan_start
def drag_pan(self, button, key, x, y):
p = self._pan_start
if p.mode == 'drag_r_labels':
startt, startr = p.trans_inverse.transform_point((p.x, p.y))
t, r = p.trans_inverse.transform_point((x, y))
# Deal with theta
dt0 = t - startt
dt1 = startt - t
if abs(dt1) < abs(dt0):
dt = abs(dt1) * sign(dt0) * -1.0
else:
dt = dt0 * -1.0
dt = (dt / np.pi) * 180.0
self._r_label_position._t = (p.r_label_angle - dt, 0.0)
self._r_label_position.invalidate()
trans, vert1, horiz1 = self.get_yaxis_text1_transform(0.0)
trans, vert2, horiz2 = self.get_yaxis_text2_transform(0.0)
for t in self.yaxis.majorTicks + self.yaxis.minorTicks:
t.label1.set_va(vert1)
t.label1.set_ha(horiz1)
t.label2.set_va(vert2)
t.label2.set_ha(horiz2)
elif p.mode == 'zoom':
startt, startr = p.trans_inverse.transform_point((p.x, p.y))
t, r = p.trans_inverse.transform_point((x, y))
dr = r - startr
# Deal with r
scale = r / startr
self.set_rmax(p.rmax / scale)
class PolarAxes(Axes):
"""
A polar graph projection, where the input dimensions are *theta*, *r*.
Theta starts pointing east and goes anti-clockwise.
"""
name = 'polar'
def __init__(self, *args, **kwargs):
"""
Create a new Polar Axes for a polar plot.
The following optional kwargs are supported:
- *resolution*: The number of points of interpolation between
each pair of data points. Set to 1 to disable
interpolation.
"""
self.resolution = kwargs.pop('resolution', 1)
self._default_theta_offset = kwargs.pop('theta_offset', 0)
self._default_theta_direction = kwargs.pop('theta_direction', 1)
if self.resolution not in (None, 1):
warnings.warn(
"""The resolution kwarg to Polar plots is now ignored.
If you need to interpolate data points, consider running
cbook.simple_linear_interpolation on the data before passing to matplotlib.""")
Axes.__init__(self, *args, **kwargs)
self.set_aspect('equal', adjustable='box', anchor='C')
self.cla()
__init__.__doc__ = Axes.__init__.__doc__
def cla(self):
Axes.cla(self)
self.title.set_y(1.05)
self.xaxis.set_major_formatter(self.ThetaFormatter())
self.xaxis.isDefault_majfmt = True
angles = np.arange(0.0, 360.0, 45.0)
self.set_thetagrids(angles)
self.yaxis.set_major_locator(self.RadialLocator(self.yaxis.get_major_locator()))
self.grid(rcParams['polaraxes.grid'])
self.xaxis.set_ticks_position('none')
self.yaxis.set_ticks_position('none')
self.yaxis.set_tick_params(label1On=True)
# Why do we need to turn on yaxis tick labels, but
# xaxis tick labels are already on?
self.set_theta_offset(self._default_theta_offset)
self.set_theta_direction(self._default_theta_direction)
def _init_axis(self):
"move this out of __init__ because non-separable axes don't use it"
self.xaxis = maxis.XAxis(self)
self.yaxis = maxis.YAxis(self)
# Calling polar_axes.xaxis.cla() or polar_axes.xaxis.cla()
# results in weird artifacts. Therefore we disable this for
# now.
# self.spines['polar'].register_axis(self.yaxis)
self._update_transScale()
def _set_lim_and_transforms(self):
self.transAxes = BboxTransformTo(self.bbox)
# Transforms the x and y axis separately by a scale factor
# It is assumed that this part will have non-linear components
self.transScale = TransformWrapper(IdentityTransform())
# A (possibly non-linear) projection on the (already scaled)
# data. This one is aware of rmin
self.transProjection = self.PolarTransform(self)
# This one is not aware of rmin
self.transPureProjection = self.PolarTransform(self, use_rmin=False)
# An affine transformation on the data, generally to limit the
# range of the axes
self.transProjectionAffine = self.PolarAffine(self.transScale, self.viewLim)
# The complete data transformation stack -- from data all the
# way to display coordinates
self.transData = self.transScale + self.transProjection + \
(self.transProjectionAffine + self.transAxes)
# This is the transform for theta-axis ticks. It is
# equivalent to transData, except it always puts r == 1.0 at
# the edge of the axis circle.
self._xaxis_transform = (
self.transPureProjection +
self.PolarAffine(IdentityTransform(), Bbox.unit()) +
self.transAxes)
# The theta labels are moved from radius == 0.0 to radius == 1.1
self._theta_label1_position = Affine2D().translate(0.0, 1.1)
self._xaxis_text1_transform = (
self._theta_label1_position +
self._xaxis_transform)
self._theta_label2_position = Affine2D().translate(0.0, 1.0 / 1.1)
self._xaxis_text2_transform = (
self._theta_label2_position +
self._xaxis_transform)
# This is the transform for r-axis ticks. It scales the theta
# axis so the gridlines from 0.0 to 1.0, now go from 0.0 to
# 2pi.
self._yaxis_transform = (
Affine2D().scale(np.pi * 2.0, 1.0) +
self.transData)
# The r-axis labels are put at an angle and padded in the r-direction
self._r_label_position = ScaledTranslation(
22.5, 0.0, Affine2D())
self._yaxis_text_transform = (
self._r_label_position +
Affine2D().scale(1.0 / 360.0, 1.0) +
self._yaxis_transform
)
def get_xaxis_transform(self,which='grid'):
assert which in ['tick1','tick2','grid']
return self._xaxis_transform
def get_xaxis_text1_transform(self, pad):
return self._xaxis_text1_transform, 'center', 'center'
def get_xaxis_text2_transform(self, pad):
return self._xaxis_text2_transform, 'center', 'center'
def get_yaxis_transform(self,which='grid'):
assert which in ['tick1','tick2','grid']
return self._yaxis_transform
def get_yaxis_text1_transform(self, pad):
angle = self._r_label_position.to_values()[4]
if angle < 90.:
return self._yaxis_text_transform, 'bottom', 'left'
elif angle < 180.:
return self._yaxis_text_transform, 'bottom', 'right'
elif angle < 270.:
return self._yaxis_text_transform, 'top', 'right'
else:
return self._yaxis_text_transform, 'top', 'left'
def get_yaxis_text2_transform(self, pad):
angle = self._r_label_position.to_values()[4]
if angle < 90.:
return self._yaxis_text_transform, 'top', 'right'
elif angle < 180.:
return self._yaxis_text_transform, 'top', 'left'
elif angle < 270.:
return self._yaxis_text_transform, 'bottom', 'left'
else:
return self._yaxis_text_transform, 'bottom', 'right'
def _gen_axes_patch(self):
return Circle((0.5, 0.5), 0.5)
def _gen_axes_spines(self):
return {'polar':mspines.Spine.circular_spine(self,
(0.5, 0.5), 0.5)}
def set_rmax(self, rmax):
self.viewLim.y1 = rmax
def get_rmax(self):
return self.viewLim.ymax
def set_rmin(self, rmin):
self.viewLim.y0 = rmin
def get_rmin(self):
return self.viewLim.ymin
def set_theta_offset(self, offset):
"""
Set the offset for the location of 0 in radians.
"""
self._theta_offset = offset
def get_theta_offset(self):
"""
Get the offset for the location of 0 in radians.
"""
return self._theta_offset
def set_theta_zero_location(self, loc):
"""
Sets the location of theta's zero. (Calls set_theta_offset
with the correct value in radians under the hood.)
May be one of "N", "NW", "W", "SW", "S", "SE", "E", or "NE".
"""
mapping = {
'N': np.pi * 0.5,
'NW': np.pi * 0.75,
'W': np.pi,
'SW': np.pi * 1.25,
'S': np.pi * 1.5,
'SE': np.pi * 1.75,
'E': 0,
'NE': np.pi * 0.25 }
return self.set_theta_offset(mapping[loc])
def set_theta_direction(self, direction):
"""
Set the direction in which theta increases.
clockwise, -1:
Theta increases in the clockwise direction
counterclockwise, anticlockwise, 1:
Theta increases in the counterclockwise direction
"""
if direction in ('clockwise',):
self._direction = -1
elif direction in ('counterclockwise', 'anticlockwise'):
self._direction = 1
elif direction in (1, -1):
self._direction = direction
else:
raise ValueError("direction must be 1, -1, clockwise or counterclockwise")
def get_theta_direction(self):
"""
Get the direction in which theta increases.
-1:
Theta increases in the clockwise direction
1:
Theta increases in the counterclockwise direction
"""
return self._direction
def set_rlim(self, *args, **kwargs):
if 'rmin' in kwargs:
kwargs['ymin'] = kwargs.pop('rmin')
if 'rmax' in kwargs:
kwargs['ymax'] = kwargs.pop('rmax')
return self.set_ylim(*args, **kwargs)
def set_yscale(self, *args, **kwargs):
Axes.set_yscale(self, *args, **kwargs)
self.yaxis.set_major_locator(
self.RadialLocator(self.yaxis.get_major_locator()))
def set_rscale(self, *args, **kwargs):
return Axes.set_yscale(self, *args, **kwargs)
def set_rticks(self, *args, **kwargs):
return Axes.set_yticks(self, *args, **kwargs)
@docstring.dedent_interpd
def set_thetagrids(self, angles, labels=None, frac=None, fmt=None,
**kwargs):
"""
Set the angles at which to place the theta grids (these
gridlines are equal along the theta dimension). *angles* is in
degrees.
*labels*, if not None, is a ``len(angles)`` list of strings of
the labels to use at each angle.
If *labels* is None, the labels will be ``fmt %% angle``
*frac* is the fraction of the polar axes radius at which to
place the label (1 is the edge). Eg. 1.05 is outside the axes
and 0.95 is inside the axes.
Return value is a list of tuples (*line*, *label*), where
*line* is :class:`~matplotlib.lines.Line2D` instances and the
*label* is :class:`~matplotlib.text.Text` instances.
kwargs are optional text properties for the labels:
%(Text)s
ACCEPTS: sequence of floats
"""
# Make sure we take into account unitized data
angles = self.convert_yunits(angles)
angles = np.asarray(angles, np.float_)
self.set_xticks(angles * (np.pi / 180.0))
if labels is not None:
self.set_xticklabels(labels)
elif fmt is not None:
self.xaxis.set_major_formatter(FormatStrFormatter(fmt))
if frac is not None:
self._theta_label1_position.clear().translate(0.0, frac)
self._theta_label2_position.clear().translate(0.0, 1.0 / frac)
for t in self.xaxis.get_ticklabels():
t.update(kwargs)
return self.xaxis.get_ticklines(), self.xaxis.get_ticklabels()
@docstring.dedent_interpd
def set_rgrids(self, radii, labels=None, angle=None, fmt=None,
**kwargs):
"""
Set the radial locations and labels of the *r* grids.
The labels will appear at radial distances *radii* at the
given *angle* in degrees.
*labels*, if not None, is a ``len(radii)`` list of strings of the
labels to use at each radius.
If *labels* is None, the built-in formatter will be used.
Return value is a list of tuples (*line*, *label*), where
*line* is :class:`~matplotlib.lines.Line2D` instances and the
*label* is :class:`~matplotlib.text.Text` instances.
kwargs are optional text properties for the labels:
%(Text)s
ACCEPTS: sequence of floats
"""
# Make sure we take into account unitized data
radii = self.convert_xunits(radii)
radii = np.asarray(radii)
rmin = radii.min()
if rmin <= 0:
raise ValueError('radial grids must be strictly positive')
self.set_yticks(radii)
if labels is not None:
self.set_yticklabels(labels)
elif fmt is not None:
self.yaxis.set_major_formatter(FormatStrFormatter(fmt))
if angle is None:
angle = self._r_label_position.to_values()[4]
self._r_label_position._t = (angle, 0.0)
self._r_label_position.invalidate()
for t in self.yaxis.get_ticklabels():
t.update(kwargs)
return self.yaxis.get_gridlines(), self.yaxis.get_ticklabels()
def set_xscale(self, scale, *args, **kwargs):
if scale != 'linear':
raise NotImplementedError("You can not set the xscale on a polar plot.")
def set_xlim(self, *args, **kargs):
# The xlim is fixed, no matter what you do
self.viewLim.intervalx = (0.0, np.pi * 2.0)
def format_coord(self, theta, r):
"""
Return a format string formatting the coordinate using Unicode
characters.
"""
theta /= math.pi
# \u03b8: lower-case theta
# \u03c0: lower-case pi
# \u00b0: degree symbol
return u'\u03b8=%0.3f\u03c0 (%0.3f\u00b0), r=%0.3f' % (theta, theta * 180.0, r)
def get_data_ratio(self):
'''
Return the aspect ratio of the data itself. For a polar plot,
this should always be 1.0
'''
return 1.0
### Interactive panning
def can_zoom(self):
"""
Return *True* if this axes supports the zoom box button functionality.
Polar axes do not support zoom boxes.
"""
return False
def can_pan(self) :
"""
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.
"""
return True
def start_pan(self, x, y, button):
angle = np.deg2rad(self._r_label_position.to_values()[4])
mode = ''
if button == 1:
epsilon = np.pi / 45.0
t, r = self.transData.inverted().transform_point((x, y))
if t >= angle - epsilon and t <= angle + epsilon:
mode = 'drag_r_labels'
elif button == 3:
mode = 'zoom'
self._pan_start = cbook.Bunch(
rmax = self.get_rmax(),
trans = self.transData.frozen(),
trans_inverse = self.transData.inverted().frozen(),
r_label_angle = self._r_label_position.to_values()[4],
x = x,
y = y,
mode = mode
)
def end_pan(self):
del self._pan_start
def drag_pan(self, button, key, x, y):
p = self._pan_start
if p.mode == 'drag_r_labels':
startt, startr = p.trans_inverse.transform_point((p.x, p.y))
t, r = p.trans_inverse.transform_point((x, y))
# Deal with theta
dt0 = t - startt
dt1 = startt - t
if abs(dt1) < abs(dt0):
dt = abs(dt1) * sign(dt0) * -1.0
else:
dt = dt0 * -1.0
dt = (dt / np.pi) * 180.0
self._r_label_position._t = (p.r_label_angle - dt, 0.0)
self._r_label_position.invalidate()
trans, vert1, horiz1 = self.get_yaxis_text1_transform(0.0)
trans, vert2, horiz2 = self.get_yaxis_text2_transform(0.0)
for t in self.yaxis.majorTicks + self.yaxis.minorTicks:
t.label1.set_va(vert1)
t.label1.set_ha(horiz1)
t.label2.set_va(vert2)
t.label2.set_ha(horiz2)
elif p.mode == 'zoom':
startt, startr = p.trans_inverse.transform_point((p.x, p.y))
t, r = p.trans_inverse.transform_point((x, y))
dr = r - startr
# Deal with r
scale = r / startr
self.set_rmax(p.rmax / scale)
