class PolarAffine(mtransforms.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 the y limits (for the radius limits).
The theta range is handled by the non-affine transform.
"""
mtransforms.Affine2DBase.__init__(self)
self._scale_transform = scale_transform
self._limits = limits
self.set_children(scale_transform, limits)
self._mtx = None
__str__ = mtransforms._make_str_method("_scale_transform", "_limits")
def get_matrix(self):
# docstring inherited
if self._invalid:
limits_scaled = self._limits.transformed(self._scale_transform)
yscale = limits_scaled.ymax - limits_scaled.ymin
affine = mtransforms.Affine2D() \
.scale(0.5 / yscale) \
.translate(0.5, 0.5)
self._mtx = affine.get_matrix()
self._inverted = None
self._invalid = 0
return self._mtx
class _WedgeBbox(mtransforms.Bbox):
"""
Transform (theta, r) wedge Bbox into axes bounding box.
Parameters
----------
center : (float, float)
Center of the wedge
viewLim : `~matplotlib.transforms.Bbox`
Bbox determining the boundaries of the wedge
originLim : `~matplotlib.transforms.Bbox`
Bbox determining the origin for the wedge, if different from *viewLim*
"""
def __init__(self, center, viewLim, originLim, **kwargs):
mtransforms.Bbox.__init__(self, [[0, 0], [1, 1]], **kwargs)
self._center = center
self._viewLim = viewLim
self._originLim = originLim
self.set_children(viewLim, originLim)
__str__ = mtransforms._make_str_method("_center", "_viewLim", "_originLim")
def get_points(self):
# docstring inherited
if self._invalid:
points = self._viewLim.get_points().copy()
# Scale angular limits to work with Wedge.
points[:, 0] *= 180 / np.pi
if points[0, 0] > points[1, 0]:
points[:, 0] = points[::-1, 0]
# Scale radial limits based on origin radius.
points[:, 1] -= self._originLim.y0
# Scale radial limits to match axes limits.
rscale = 0.5 / points[1, 1]
points[:, 1] *= rscale
width = min(points[1, 1] - points[0, 1], 0.5)
# Generate bounding box for wedge.
wedge = mpatches.Wedge(self._center,
points[1, 1],
points[0, 0],
points[1, 0],
width=width)
self.update_from_path(wedge.get_path())
# Ensure equal aspect ratio.
w, h = self._points[1] - self._points[0]
deltah = max(w - h, 0) / 2
deltaw = max(h - w, 0) / 2
self._points += np.array([[-deltaw, -deltah], [deltaw, deltah]])
self._invalid = 0
return self._points
class _ThetaShift(mtransforms.ScaledTranslation):
"""
Apply a padding shift based on axes theta limits.
This is used to create padding for radial ticks.
Parameters
----------
axes : `~matplotlib.axes.Axes`
The owning axes; used to determine limits.
pad : float
The padding to apply, in points.
mode : {'min', 'max', 'rlabel'}
Whether to shift away from the start (``'min'``) or the end (``'max'``)
of the axes, or using the rlabel position (``'rlabel'``).
"""
def __init__(self, axes, pad, mode):
mtransforms.ScaledTranslation.__init__(self, pad, pad,
axes.figure.dpi_scale_trans)
self.set_children(axes._realViewLim)
self.axes = axes
self.mode = mode
self.pad = pad
__str__ = mtransforms._make_str_method("axes", "pad", "mode")
def get_matrix(self):
if self._invalid:
if self.mode == 'rlabel':
angle = (
np.deg2rad(self.axes.get_rlabel_position()) *
self.axes.get_theta_direction() +
self.axes.get_theta_offset()
)
else:
if self.mode == 'min':
angle = self.axes._realViewLim.xmin
elif self.mode == 'max':
angle = self.axes._realViewLim.xmax
if self.mode in ('rlabel', 'min'):
padx = np.cos(angle - np.pi / 2)
pady = np.sin(angle - np.pi / 2)
else:
padx = np.cos(angle + np.pi / 2)
pady = np.sin(angle + np.pi / 2)
self._t = (self.pad * padx / 72, self.pad * pady / 72)
return mtransforms.ScaledTranslation.get_matrix(self)
class PolarTransform(mtransforms.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 = output_dims = 2
def __init__(self, axis=None, use_rmin=True,
_apply_theta_transforms=True):
mtransforms.Transform.__init__(self)
self._axis = axis
self._use_rmin = use_rmin
self._apply_theta_transforms = _apply_theta_transforms
__str__ = mtransforms._make_str_method(
"_axis",
use_rmin="_use_rmin",
_apply_theta_transforms="_apply_theta_transforms")
def transform_non_affine(self, tr):
# docstring inherited
t, r = np.transpose(tr)
# PolarAxes does not use the theta transforms here, but apply them for
# backwards-compatibility if not being used by it.
if self._apply_theta_transforms and self._axis is not None:
t *= self._axis.get_theta_direction()
t += self._axis.get_theta_offset()
if self._use_rmin and self._axis is not None:
r = (r - self._axis.get_rorigin()) * self._axis.get_rsign()
r = np.where(r >= 0, r, np.nan)
return np.column_stack([r * np.cos(t), r * np.sin(t)])
def transform_path_non_affine(self, path):
# docstring inherited
vertices = path.vertices
if len(vertices) == 2 and vertices[0, 0] == vertices[1, 0]:
return mpath.Path(self.transform(vertices), path.codes)
ipath = path.interpolated(path._interpolation_steps)
return mpath.Path(self.transform(ipath.vertices), ipath.codes)
def inverted(self):
# docstring inherited
return PolarAxes.InvertedPolarTransform(self._axis, self._use_rmin,
self._apply_theta_transforms)
class InvertedPolarTransform(mtransforms.Transform):
"""
The inverse of the polar transform, mapping Cartesian
coordinate space *x* and *y* back to *theta* and *r*.
"""
input_dims = output_dims = 2
def __init__(self, axis=None, use_rmin=True,
_apply_theta_transforms=True):
mtransforms.Transform.__init__(self)
self._axis = axis
self._use_rmin = use_rmin
self._apply_theta_transforms = _apply_theta_transforms
__str__ = mtransforms._make_str_method(
"_axis",
use_rmin="_use_rmin",
_apply_theta_transforms="_apply_theta_transforms")
def transform_non_affine(self, xy):
# docstring inherited
x, y = xy.T
r = np.hypot(x, y)
theta = (np.arctan2(y, x) + 2 * np.pi) % (2 * np.pi)
# PolarAxes does not use the theta transforms here, but apply them for
# backwards-compatibility if not being used by it.
if self._apply_theta_transforms and self._axis is not None:
theta -= self._axis.get_theta_offset()
theta *= self._axis.get_theta_direction()
theta %= 2 * np.pi
if self._use_rmin and self._axis is not None:
r += self._axis.get_rorigin()
r *= self._axis.get_rsign()
return np.column_stack([theta, r])
def inverted(self):
# docstring inherited
return PolarAxes.PolarTransform(self._axis, self._use_rmin,
self._apply_theta_transforms)