Python matplotlib.transforms.BboxTransformFrom() Examples

The following are 18 code examples of matplotlib.transforms.BboxTransformFrom(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module matplotlib.transforms , or try the search function .
Example #1
Source File: _base.py    From python3_ios with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
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)
Example #2
Source File: _base.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
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)
Example #3
Source File: legend.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
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)
        )
Example #4
Source File: _base.py    From CogAlg with MIT License 5 votes vote down vote up 
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)
Example #5
Source File: legend.py    From CogAlg with MIT License 5 votes vote down vote up 
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)
        )
Example #6
Source File: _base.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
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)
Example #7
Source File: legend.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
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)
        )
Example #8
Source File: _base.py    From ImageFusion with MIT License 5 votes vote down vote up 
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)
Example #9
Source File: legend.py    From ImageFusion with MIT License 5 votes vote down vote up 
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))
Example #10
Source File: legend.py    From Computable with MIT License 5 votes vote down vote up 
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))
Example #11
Source File: legend.py    From python3_ios with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
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)
        )
Example #12
Source File: _base.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up 
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)
Example #13
Source File: legend.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up 
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)
        )
Example #14
Source File: _base.py    From neural-network-animation with MIT License 5 votes vote down vote up 
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)
Example #15
Source File: legend.py    From neural-network-animation with MIT License 5 votes vote down vote up 
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))
Example #16
Source File: legend.py    From matplotlib-4-abaqus with MIT License 5 votes vote down vote up 
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))
Example #17
Source File: _base.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up 
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)
Example #18
Source File: legend.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up 
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)
        )