def test_lockable_bbox(locked_element):
other_elements = ['x0', 'y0', 'x1', 'y1']
other_elements.remove(locked_element)
orig = mtransforms.Bbox.unit()
locked = mtransforms.LockableBbox(orig, **{locked_element: 2})
# LockableBbox should keep its locked element as specified in __init__.
assert getattr(locked, locked_element) == 2
assert getattr(locked, 'locked_' + locked_element) == 2
for elem in other_elements:
assert getattr(locked, elem) == getattr(orig, elem)
# Changing underlying Bbox should update everything but locked element.
orig.set_points(orig.get_points() + 10)
assert getattr(locked, locked_element) == 2
assert getattr(locked, 'locked_' + locked_element) == 2
for elem in other_elements:
assert getattr(locked, elem) == getattr(orig, elem)
# Unlocking element should revert values back to the underlying Bbox.
setattr(locked, 'locked_' + locked_element, None)
assert getattr(locked, 'locked_' + locked_element) is None
assert np.all(orig.get_points() == locked.get_points())
# Relocking an element should change its value, but not others.
setattr(locked, 'locked_' + locked_element, 3)
assert getattr(locked, locked_element) == 3
assert getattr(locked, 'locked_' + locked_element) == 3
for elem in other_elements:
assert getattr(locked, elem) == getattr(orig, elem)
def _set_lim_and_transforms(self):
# A view limit where the minimum radius can be locked if the user
# specifies an alternate origin.
self._originViewLim = mtransforms.LockableBbox(self.viewLim)
# Handle angular offset and direction.
self._direction = mtransforms.Affine2D() \
.scale(self._default_theta_direction, 1.0)
self._theta_offset = mtransforms.Affine2D() \
.translate(self._default_theta_offset, 0.0)
self.transShift = self._direction + self._theta_offset
# A view limit shifted to the correct location after accounting for
# orientation and offset.
self._realViewLim = mtransforms.TransformedBbox(
self.viewLim, self.transShift)
# Transforms the x and y axis separately by a scale factor
# It is assumed that this part will have non-linear components
self.transScale = mtransforms.TransformWrapper(
mtransforms.IdentityTransform())
# Scale view limit into a bbox around the selected wedge. This may be
# smaller than the usual unit axes rectangle if not plotting the full
# circle.
self.axesLim = _WedgeBbox((0.5, 0.5), self._realViewLim,
self._originViewLim)
# Scale the wedge to fill the axes.
self.transWedge = mtransforms.BboxTransformFrom(self.axesLim)
# Scale the axes to fill the figure.
self.transAxes = mtransforms.BboxTransformTo(self.bbox)
# A (possibly non-linear) projection on the (already scaled)
# data. This one is aware of rmin
self.transProjection = self.PolarTransform(
self, _apply_theta_transforms=False)
# Add dependency on rorigin.
self.transProjection.set_children(self._originViewLim)
# An affine transformation on the data, generally to limit the
# range of the axes
self.transProjectionAffine = self.PolarAffine(self.transScale,
self._originViewLim)
# The complete data transformation stack -- from data all the
# way to display coordinates
self.transData = (
self.transScale + self.transShift + self.transProjection +
(self.transProjectionAffine + self.transWedge + self.transAxes))
# This is the transform for theta-axis ticks. It is
# equivalent to transData, except it always puts r == 0.0 and r == 1.0
# at the edge of the axis circles.
self._xaxis_transform = (mtransforms.blended_transform_factory(
mtransforms.IdentityTransform(),
mtransforms.BboxTransformTo(self.viewLim)) + self.transData)
# The theta labels are flipped along the radius, so that text 1 is on
# the outside by default. This should work the same as before.
flipr_transform = mtransforms.Affine2D() \
.translate(0.0, -0.5) \
.scale(1.0, -1.0) \
.translate(0.0, 0.5)
self._xaxis_text_transform = flipr_transform + 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 thetamin to
# thetamax.
self._yaxis_transform = (mtransforms.blended_transform_factory(
mtransforms.BboxTransformTo(self.viewLim),
mtransforms.IdentityTransform()) + self.transData)
# The r-axis labels are put at an angle and padded in the r-direction
self._r_label_position = mtransforms.Affine2D() \
.translate(self._default_rlabel_position, 0.0)
self._yaxis_text_transform = mtransforms.TransformWrapper(
self._r_label_position + self.transData)
