本文整理汇总了Python中matplotlib.transforms.BboxTransformFrom方法的典型用法代码示例。如果您正苦于以下问题：Python transforms.BboxTransformFrom方法的具体用法？Python transforms.BboxTransformFrom怎么用？Python transforms.BboxTransformFrom使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类matplotlib.transforms的用法示例。
在下文中一共展示了transforms.BboxTransformFrom方法的5个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _update_loc
# 需要导入模块: from matplotlib import transforms [as 别名]
# 或者: from matplotlib.transforms import BboxTransformFrom [as 别名]
def _update_loc(self, loc_in_canvas):
bbox = self.legend.get_bbox_to_anchor()
# if bbox has zero width or height, the transformation is
# ill-defined. Fall back to the defaul bbox_to_anchor.
if bbox.width == 0 or bbox.height == 0:
self.legend.set_bbox_to_anchor(None)
bbox = self.legend.get_bbox_to_anchor()
_bbox_transform = BboxTransformFrom(bbox)
self.legend._loc = tuple(
_bbox_transform.transform_point(loc_in_canvas)) 示例2: _update_loc
# 需要导入模块: from matplotlib import transforms [as 别名]
# 或者: from matplotlib.transforms import BboxTransformFrom [as 别名]
def _update_loc(self, loc_in_canvas):
bbox = self.legend.get_bbox_to_anchor()
# if bbox has zero width or height, the transformation is
# ill-defined. Fall back to the defaul bbox_to_anchor.
if bbox.width == 0 or bbox.height == 0:
self.legend.set_bbox_to_anchor(None)
bbox = self.legend.get_bbox_to_anchor()
_bbox_transform = BboxTransformFrom(bbox)
self.legend._loc = tuple(
_bbox_transform.transform_point(loc_in_canvas)
) 示例3: _set_lim_and_transforms
# 需要导入模块: from matplotlib import transforms [as 别名]
# 或者: from matplotlib.transforms import BboxTransformFrom [as 别名]
def _set_lim_and_transforms(self):
"""
Set the *_xaxis_transform*, *_yaxis_transform*, *transScale*,
*transData*, *transLimits* and *transAxes* transformations.
.. note::
This method is primarily used by rectilinear projections of the
`~matplotlib.axes.Axes` class, and is meant to be overridden by
new kinds of projection axes that need different transformations
and limits. (See `~matplotlib.projections.polar.PolarAxes` for an
example.)
"""
self.transAxes = mtransforms.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
# (e.g., for a log scale).
self.transScale = mtransforms.TransformWrapper(
mtransforms.IdentityTransform())
# An affine transformation on the data, generally to limit the
# range of the axes
self.transLimits = mtransforms.BboxTransformFrom(
mtransforms.TransformedBbox(self.viewLim, self.transScale))
# The parentheses are important for efficiency here -- they
# group the last two (which are usually affines) separately
# from the first (which, with log-scaling can be non-affine).
self.transData = self.transScale + (self.transLimits + self.transAxes)
self._xaxis_transform = mtransforms.blended_transform_factory(
self.transData, self.transAxes)
self._yaxis_transform = mtransforms.blended_transform_factory(
self.transAxes, self.transData) 示例4: _set_lim_and_transforms
# 需要导入模块: from matplotlib import transforms [as 别名]
# 或者: from matplotlib.transforms import BboxTransformFrom [as 别名]
def _set_lim_and_transforms(self):
"""
set the *dataLim* and *viewLim*
:class:`~matplotlib.transforms.Bbox` attributes and the
*transScale*, *transData*, *transLimits* and *transAxes*
transformations.
.. note::
This method is primarily used by rectilinear projections
of the :class:`~matplotlib.axes.Axes` class, and is meant
to be overridden by new kinds of projection axes that need
different transformations and limits. (See
:class:`~matplotlib.projections.polar.PolarAxes` for an
example.
"""
self.transAxes = mtransforms.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
# (e.g., for a log scale).
self.transScale = mtransforms.TransformWrapper(
mtransforms.IdentityTransform())
# An affine transformation on the data, generally to limit the
# range of the axes
self.transLimits = mtransforms.BboxTransformFrom(
mtransforms.TransformedBbox(self.viewLim, self.transScale))
# The parentheses are important for efficiency here -- they
# group the last two (which are usually affines) separately
# from the first (which, with log-scaling can be non-affine).
self.transData = self.transScale + (self.transLimits + self.transAxes)
self._xaxis_transform = mtransforms.blended_transform_factory(
self.transData, self.transAxes)
self._yaxis_transform = mtransforms.blended_transform_factory(
self.transAxes, self.transData) 示例5: _set_lim_and_transforms
# 需要导入模块: from matplotlib import transforms [as 别名]
# 或者: from matplotlib.transforms import BboxTransformFrom [as 别名]
def _set_lim_and_transforms(self):
"""
set the *_xaxis_transform*, *_yaxis_transform*,
*transScale*, *transData*, *transLimits* and *transAxes*
transformations.
.. note::
This method is primarily used by rectilinear projections
of the :class:`~matplotlib.axes.Axes` class, and is meant
to be overridden by new kinds of projection axes that need
different transformations and limits. (See
:class:`~matplotlib.projections.polar.PolarAxes` for an
example.
"""
self.transAxes = mtransforms.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
# (e.g., for a log scale).
self.transScale = mtransforms.TransformWrapper(
mtransforms.IdentityTransform())
# An affine transformation on the data, generally to limit the
# range of the axes
self.transLimits = mtransforms.BboxTransformFrom(
mtransforms.TransformedBbox(self.viewLim, self.transScale))
# The parentheses are important for efficiency here -- they
# group the last two (which are usually affines) separately
# from the first (which, with log-scaling can be non-affine).
self.transData = self.transScale + (self.transLimits + self.transAxes)
self._xaxis_transform = mtransforms.blended_transform_factory(
self.transData, self.transAxes)
self._yaxis_transform = mtransforms.blended_transform_factory(
self.transAxes, self.transData)