first commit

.venv/Lib/site-packages/plotly/matplotlylib/__init__.py

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+"""
+matplotlylib
+============
+
+This module converts matplotlib figure objects into JSON structures which can
+be understood and visualized by Plotly.
+
+Most of the functionality should be accessed through the parent directory's
+'tools' module or 'plotly' package.
+
+"""
+from __future__ import absolute_import
+
+from plotly.matplotlylib.renderer import PlotlyRenderer
+from plotly.matplotlylib.mplexporter import Exporter

.venv/Lib/site-packages/plotly/matplotlylib/mplexporter/__init__.py

@@ -0,0 +1,2 @@
+from .renderers import Renderer
+from .exporter import Exporter

.venv/Lib/site-packages/plotly/matplotlylib/mplexporter/_py3k_compat.py

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+"""
+Simple fixes for Python 2/3 compatibility
+"""
+import sys
+
+PY3K = sys.version_info[0] >= 3
+
+
+if PY3K:
+    import builtins
+    import functools
+
+    reduce = functools.reduce
+    zip = builtins.zip
+    xrange = builtins.range
+    map = builtins.map
+else:
+    import __builtin__
+    import itertools
+
+    builtins = __builtin__
+    reduce = __builtin__.reduce
+    zip = itertools.izip
+    xrange = __builtin__.xrange
+    map = itertools.imap

.venv/Lib/site-packages/plotly/matplotlylib/mplexporter/exporter.py

@@ -0,0 +1,310 @@
+"""
+Matplotlib Exporter
+===================
+This submodule contains tools for crawling a matplotlib figure and exporting
+relevant pieces to a renderer.
+"""
+import warnings
+import io
+from . import utils
+
+import matplotlib
+from matplotlib import transforms, collections
+from matplotlib.backends.backend_agg import FigureCanvasAgg
+
+
+class Exporter(object):
+    """Matplotlib Exporter
+
+    Parameters
+    ----------
+    renderer : Renderer object
+        The renderer object called by the exporter to create a figure
+        visualization.  See mplexporter.Renderer for information on the
+        methods which should be defined within the renderer.
+    close_mpl : bool
+        If True (default), close the matplotlib figure as it is rendered. This
+        is useful for when the exporter is used within the notebook, or with
+        an interactive matplotlib backend.
+    """
+
+    def __init__(self, renderer, close_mpl=True):
+        self.close_mpl = close_mpl
+        self.renderer = renderer
+
+    def run(self, fig):
+        """
+        Run the exporter on the given figure
+
+        Parmeters
+        ---------
+        fig : matplotlib.Figure instance
+            The figure to export
+        """
+        # Calling savefig executes the draw() command, putting elements
+        # in the correct place.
+        if fig.canvas is None:
+            canvas = FigureCanvasAgg(fig)
+        fig.savefig(io.BytesIO(), format="png", dpi=fig.dpi)
+        if self.close_mpl:
+            import matplotlib.pyplot as plt
+
+            plt.close(fig)
+        self.crawl_fig(fig)
+
+    @staticmethod
+    def process_transform(
+        transform, ax=None, data=None, return_trans=False, force_trans=None
+    ):
+        """Process the transform and convert data to figure or data coordinates
+
+        Parameters
+        ----------
+        transform : matplotlib Transform object
+            The transform applied to the data
+        ax : matplotlib Axes object (optional)
+            The axes the data is associated with
+        data : ndarray (optional)
+            The array of data to be transformed.
+        return_trans : bool (optional)
+            If true, return the final transform of the data
+        force_trans : matplotlib.transform instance (optional)
+            If supplied, first force the data to this transform
+
+        Returns
+        -------
+        code : string
+            Code is either "data", "axes", "figure", or "display", indicating
+            the type of coordinates output.
+        transform : matplotlib transform
+            the transform used to map input data to output data.
+            Returned only if return_trans is True
+        new_data : ndarray
+            Data transformed to match the given coordinate code.
+            Returned only if data is specified
+        """
+        if isinstance(transform, transforms.BlendedGenericTransform):
+            warnings.warn(
+                "Blended transforms not yet supported. "
+                "Zoom behavior may not work as expected."
+            )
+
+        if force_trans is not None:
+            if data is not None:
+                data = (transform - force_trans).transform(data)
+            transform = force_trans
+
+        code = "display"
+        if ax is not None:
+            for (c, trans) in [
+                ("data", ax.transData),
+                ("axes", ax.transAxes),
+                ("figure", ax.figure.transFigure),
+                ("display", transforms.IdentityTransform()),
+            ]:
+                if transform.contains_branch(trans):
+                    code, transform = (c, transform - trans)
+                    break
+
+        if data is not None:
+            if return_trans:
+                return code, transform.transform(data), transform
+            else:
+                return code, transform.transform(data)
+        else:
+            if return_trans:
+                return code, transform
+            else:
+                return code
+
+    def crawl_fig(self, fig):
+        """Crawl the figure and process all axes"""
+        with self.renderer.draw_figure(fig=fig, props=utils.get_figure_properties(fig)):
+            for ax in fig.axes:
+                self.crawl_ax(ax)
+
+    def crawl_ax(self, ax):
+        """Crawl the axes and process all elements within"""
+        with self.renderer.draw_axes(ax=ax, props=utils.get_axes_properties(ax)):
+            for line in ax.lines:
+                self.draw_line(ax, line)
+            for text in ax.texts:
+                self.draw_text(ax, text)
+            for (text, ttp) in zip(
+                [ax.xaxis.label, ax.yaxis.label, ax.title],
+                ["xlabel", "ylabel", "title"],
+            ):
+                if hasattr(text, "get_text") and text.get_text():
+                    self.draw_text(ax, text, force_trans=ax.transAxes, text_type=ttp)
+            for artist in ax.artists:
+                # TODO: process other artists
+                if isinstance(artist, matplotlib.text.Text):
+                    self.draw_text(ax, artist)
+            for patch in ax.patches:
+                self.draw_patch(ax, patch)
+            for collection in ax.collections:
+                self.draw_collection(ax, collection)
+            for image in ax.images:
+                self.draw_image(ax, image)
+
+            legend = ax.get_legend()
+            if legend is not None:
+                props = utils.get_legend_properties(ax, legend)
+                with self.renderer.draw_legend(legend=legend, props=props):
+                    if props["visible"]:
+                        self.crawl_legend(ax, legend)
+
+    def crawl_legend(self, ax, legend):
+        """
+        Recursively look through objects in legend children
+        """
+        legendElements = list(
+            utils.iter_all_children(legend._legend_box, skipContainers=True)
+        )
+        legendElements.append(legend.legendPatch)
+        for child in legendElements:
+            # force a large zorder so it appears on top
+            child.set_zorder(1e6 + child.get_zorder())
+
+            # reorder border box to make sure marks are visible
+            if isinstance(child, matplotlib.patches.FancyBboxPatch):
+                child.set_zorder(child.get_zorder() - 1)
+
+            try:
+                # What kind of object...
+                if isinstance(child, matplotlib.patches.Patch):
+                    self.draw_patch(ax, child, force_trans=ax.transAxes)
+                elif isinstance(child, matplotlib.text.Text):
+                    if child.get_text() != "None":
+                        self.draw_text(ax, child, force_trans=ax.transAxes)
+                elif isinstance(child, matplotlib.lines.Line2D):
+                    self.draw_line(ax, child, force_trans=ax.transAxes)
+                elif isinstance(child, matplotlib.collections.Collection):
+                    self.draw_collection(ax, child, force_pathtrans=ax.transAxes)
+                else:
+                    warnings.warn("Legend element %s not impemented" % child)
+            except NotImplementedError:
+                warnings.warn("Legend element %s not impemented" % child)
+
+    def draw_line(self, ax, line, force_trans=None):
+        """Process a matplotlib line and call renderer.draw_line"""
+        coordinates, data = self.process_transform(
+            line.get_transform(), ax, line.get_xydata(), force_trans=force_trans
+        )
+        linestyle = utils.get_line_style(line)
+        if linestyle["dasharray"] is None and linestyle["drawstyle"] == "default":
+            linestyle = None
+        markerstyle = utils.get_marker_style(line)
+        if (
+            markerstyle["marker"] in ["None", "none", None]
+            or markerstyle["markerpath"][0].size == 0
+        ):
+            markerstyle = None
+        label = line.get_label()
+        if markerstyle or linestyle:
+            self.renderer.draw_marked_line(
+                data=data,
+                coordinates=coordinates,
+                linestyle=linestyle,
+                markerstyle=markerstyle,
+                label=label,
+                mplobj=line,
+            )
+
+    def draw_text(self, ax, text, force_trans=None, text_type=None):
+        """Process a matplotlib text object and call renderer.draw_text"""
+        content = text.get_text()
+        if content:
+            transform = text.get_transform()
+            position = text.get_position()
+            coords, position = self.process_transform(
+                transform, ax, position, force_trans=force_trans
+            )
+            style = utils.get_text_style(text)
+            self.renderer.draw_text(
+                text=content,
+                position=position,
+                coordinates=coords,
+                text_type=text_type,
+                style=style,
+                mplobj=text,
+            )
+
+    def draw_patch(self, ax, patch, force_trans=None):
+        """Process a matplotlib patch object and call renderer.draw_path"""
+        vertices, pathcodes = utils.SVG_path(patch.get_path())
+        transform = patch.get_transform()
+        coordinates, vertices = self.process_transform(
+            transform, ax, vertices, force_trans=force_trans
+        )
+        linestyle = utils.get_path_style(patch, fill=patch.get_fill())
+        self.renderer.draw_path(
+            data=vertices,
+            coordinates=coordinates,
+            pathcodes=pathcodes,
+            style=linestyle,
+            mplobj=patch,
+        )
+
+    def draw_collection(
+        self, ax, collection, force_pathtrans=None, force_offsettrans=None
+    ):
+        """Process a matplotlib collection and call renderer.draw_collection"""
+        (transform, transOffset, offsets, paths) = collection._prepare_points()
+
+        offset_coords, offsets = self.process_transform(
+            transOffset, ax, offsets, force_trans=force_offsettrans
+        )
+        path_coords = self.process_transform(transform, ax, force_trans=force_pathtrans)
+
+        processed_paths = [utils.SVG_path(path) for path in paths]
+        processed_paths = [
+            (
+                self.process_transform(
+                    transform, ax, path[0], force_trans=force_pathtrans
+                )[1],
+                path[1],
+            )
+            for path in processed_paths
+        ]
+
+        path_transforms = collection.get_transforms()
+        try:
+            # matplotlib 1.3: path_transforms are transform objects.
+            # Convert them to numpy arrays.
+            path_transforms = [t.get_matrix() for t in path_transforms]
+        except AttributeError:
+            # matplotlib 1.4: path transforms are already numpy arrays.
+            pass
+
+        styles = {
+            "linewidth": collection.get_linewidths(),
+            "facecolor": collection.get_facecolors(),
+            "edgecolor": collection.get_edgecolors(),
+            "alpha": collection._alpha,
+            "zorder": collection.get_zorder(),
+        }
+
+        offset_dict = {"data": "before", "screen": "after"}
+        offset_order = offset_dict[collection.get_offset_position()]
+
+        self.renderer.draw_path_collection(
+            paths=processed_paths,
+            path_coordinates=path_coords,
+            path_transforms=path_transforms,
+            offsets=offsets,
+            offset_coordinates=offset_coords,
+            offset_order=offset_order,
+            styles=styles,
+            mplobj=collection,
+        )
+
+    def draw_image(self, ax, image):
+        """Process a matplotlib image object and call renderer.draw_image"""
+        self.renderer.draw_image(
+            imdata=utils.image_to_base64(image),
+            extent=image.get_extent(),
+            coordinates="data",
+            style={"alpha": image.get_alpha(), "zorder": image.get_zorder()},
+            mplobj=image,
+        )

.venv/Lib/site-packages/plotly/matplotlylib/mplexporter/renderers/__init__.py

@@ -0,0 +1,12 @@
+"""
+Matplotlib Renderers
+====================
+This submodule contains renderer objects which define renderer behavior used
+within the Exporter class.  The base renderer class is :class:`Renderer`, an
+abstract base class
+"""
+
+from .base import Renderer
+from .vega_renderer import VegaRenderer, fig_to_vega
+from .vincent_renderer import VincentRenderer, fig_to_vincent
+from .fake_renderer import FakeRenderer, FullFakeRenderer

.venv/Lib/site-packages/plotly/matplotlylib/mplexporter/renderers/base.py

@@ -0,0 +1,429 @@
+import warnings
+import itertools
+from contextlib import contextmanager
+from distutils.version import LooseVersion
+
+import numpy as np
+import matplotlib as mpl
+from matplotlib import transforms
+
+from .. import utils
+from .. import _py3k_compat as py3k
+
+
+class Renderer(object):
+    @staticmethod
+    def ax_zoomable(ax):
+        return bool(ax and ax.get_navigate())
+
+    @staticmethod
+    def ax_has_xgrid(ax):
+        return bool(ax and ax.xaxis._gridOnMajor and ax.yaxis.get_gridlines())
+
+    @staticmethod
+    def ax_has_ygrid(ax):
+        return bool(ax and ax.yaxis._gridOnMajor and ax.yaxis.get_gridlines())
+
+    @property
+    def current_ax_zoomable(self):
+        return self.ax_zoomable(self._current_ax)
+
+    @property
+    def current_ax_has_xgrid(self):
+        return self.ax_has_xgrid(self._current_ax)
+
+    @property
+    def current_ax_has_ygrid(self):
+        return self.ax_has_ygrid(self._current_ax)
+
+    @contextmanager
+    def draw_figure(self, fig, props):
+        if hasattr(self, "_current_fig") and self._current_fig is not None:
+            warnings.warn("figure embedded in figure: something is wrong")
+        self._current_fig = fig
+        self._fig_props = props
+        self.open_figure(fig=fig, props=props)
+        yield
+        self.close_figure(fig=fig)
+        self._current_fig = None
+        self._fig_props = {}
+
+    @contextmanager
+    def draw_axes(self, ax, props):
+        if hasattr(self, "_current_ax") and self._current_ax is not None:
+            warnings.warn("axes embedded in axes: something is wrong")
+        self._current_ax = ax
+        self._ax_props = props
+        self.open_axes(ax=ax, props=props)
+        yield
+        self.close_axes(ax=ax)
+        self._current_ax = None
+        self._ax_props = {}
+
+    @contextmanager
+    def draw_legend(self, legend, props):
+        self._current_legend = legend
+        self._legend_props = props
+        self.open_legend(legend=legend, props=props)
+        yield
+        self.close_legend(legend=legend)
+        self._current_legend = None
+        self._legend_props = {}
+
+    # Following are the functions which should be overloaded in subclasses
+
+    def open_figure(self, fig, props):
+        """
+        Begin commands for a particular figure.
+
+        Parameters
+        ----------
+        fig : matplotlib.Figure
+            The Figure which will contain the ensuing axes and elements
+        props : dictionary
+            The dictionary of figure properties
+        """
+        pass
+
+    def close_figure(self, fig):
+        """
+        Finish commands for a particular figure.
+
+        Parameters
+        ----------
+        fig : matplotlib.Figure
+            The figure which is finished being drawn.
+        """
+        pass
+
+    def open_axes(self, ax, props):
+        """
+        Begin commands for a particular axes.
+
+        Parameters
+        ----------
+        ax : matplotlib.Axes
+            The Axes which will contain the ensuing axes and elements
+        props : dictionary
+            The dictionary of axes properties
+        """
+        pass
+
+    def close_axes(self, ax):
+        """
+        Finish commands for a particular axes.
+
+        Parameters
+        ----------
+        ax : matplotlib.Axes
+            The Axes which is finished being drawn.
+        """
+        pass
+
+    def open_legend(self, legend, props):
+        """
+        Beging commands for a particular legend.
+
+        Parameters
+        ----------
+        legend : matplotlib.legend.Legend
+                The Legend that will contain the ensuing elements
+        props : dictionary
+                The dictionary of legend properties
+        """
+        pass
+
+    def close_legend(self, legend):
+        """
+        Finish commands for a particular legend.
+
+        Parameters
+        ----------
+        legend : matplotlib.legend.Legend
+                The Legend which is finished being drawn
+        """
+        pass
+
+    def draw_marked_line(
+        self, data, coordinates, linestyle, markerstyle, label, mplobj=None
+    ):
+        """Draw a line that also has markers.
+
+        If this isn't reimplemented by a renderer object, by default, it will
+        make a call to BOTH draw_line and draw_markers when both markerstyle
+        and linestyle are not None in the same Line2D object.
+
+        """
+        if linestyle is not None:
+            self.draw_line(data, coordinates, linestyle, label, mplobj)
+        if markerstyle is not None:
+            self.draw_markers(data, coordinates, markerstyle, label, mplobj)
+
+    def draw_line(self, data, coordinates, style, label, mplobj=None):
+        """
+        Draw a line. By default, draw the line via the draw_path() command.
+        Some renderers might wish to override this and provide more
+        fine-grained behavior.
+
+        In matplotlib, lines are generally created via the plt.plot() command,
+        though this command also can create marker collections.
+
+        Parameters
+        ----------
+        data : array_like
+            A shape (N, 2) array of datapoints.
+        coordinates : string
+            A string code, which should be either 'data' for data coordinates,
+            or 'figure' for figure (pixel) coordinates.
+        style : dictionary
+            a dictionary specifying the appearance of the line.
+        mplobj : matplotlib object
+            the matplotlib plot element which generated this line
+        """
+        pathcodes = ["M"] + (data.shape[0] - 1) * ["L"]
+        pathstyle = dict(facecolor="none", **style)
+        pathstyle["edgecolor"] = pathstyle.pop("color")
+        pathstyle["edgewidth"] = pathstyle.pop("linewidth")
+        self.draw_path(
+            data=data,
+            coordinates=coordinates,
+            pathcodes=pathcodes,
+            style=pathstyle,
+            mplobj=mplobj,
+        )
+
+    @staticmethod
+    def _iter_path_collection(paths, path_transforms, offsets, styles):
+        """Build an iterator over the elements of the path collection"""
+        N = max(len(paths), len(offsets))
+
+        # Before mpl 1.4.0, path_transform can be a false-y value, not a valid
+        # transformation matrix.
+        if LooseVersion(mpl.__version__) < LooseVersion("1.4.0"):
+            if path_transforms is None:
+                path_transforms = [np.eye(3)]
+
+        edgecolor = styles["edgecolor"]
+        if np.size(edgecolor) == 0:
+            edgecolor = ["none"]
+        facecolor = styles["facecolor"]
+        if np.size(facecolor) == 0:
+            facecolor = ["none"]
+
+        elements = [
+            paths,
+            path_transforms,
+            offsets,
+            edgecolor,
+            styles["linewidth"],
+            facecolor,
+        ]
+
+        it = itertools
+        return it.islice(py3k.zip(*py3k.map(it.cycle, elements)), N)
+
+    def draw_path_collection(
+        self,
+        paths,
+        path_coordinates,
+        path_transforms,
+        offsets,
+        offset_coordinates,
+        offset_order,
+        styles,
+        mplobj=None,
+    ):
+        """
+        Draw a collection of paths. The paths, offsets, and styles are all
+        iterables, and the number of paths is max(len(paths), len(offsets)).
+
+        By default, this is implemented via multiple calls to the draw_path()
+        function. For efficiency, Renderers may choose to customize this
+        implementation.
+
+        Examples of path collections created by matplotlib are scatter plots,
+        histograms, contour plots, and many others.
+
+        Parameters
+        ----------
+        paths : list
+            list of tuples, where each tuple has two elements:
+            (data, pathcodes).  See draw_path() for a description of these.
+        path_coordinates: string
+            the coordinates code for the paths, which should be either
+            'data' for data coordinates, or 'figure' for figure (pixel)
+            coordinates.
+        path_transforms: array_like
+            an array of shape (*, 3, 3), giving a series of 2D Affine
+            transforms for the paths. These encode translations, rotations,
+            and scalings in the standard way.
+        offsets: array_like
+            An array of offsets of shape (N, 2)
+        offset_coordinates : string
+            the coordinates code for the offsets, which should be either
+            'data' for data coordinates, or 'figure' for figure (pixel)
+            coordinates.
+        offset_order : string
+            either "before" or "after". This specifies whether the offset
+            is applied before the path transform, or after.  The matplotlib
+            backend equivalent is "before"->"data", "after"->"screen".
+        styles: dictionary
+            A dictionary in which each value is a list of length N, containing
+            the style(s) for the paths.
+        mplobj : matplotlib object
+            the matplotlib plot element which generated this collection
+        """
+        if offset_order == "before":
+            raise NotImplementedError("offset before transform")
+
+        for tup in self._iter_path_collection(paths, path_transforms, offsets, styles):
+            (path, path_transform, offset, ec, lw, fc) = tup
+            vertices, pathcodes = path
+            path_transform = transforms.Affine2D(path_transform)
+            vertices = path_transform.transform(vertices)
+            # This is a hack:
+            if path_coordinates == "figure":
+                path_coordinates = "points"
+            style = {
+                "edgecolor": utils.export_color(ec),
+                "facecolor": utils.export_color(fc),
+                "edgewidth": lw,
+                "dasharray": "10,0",
+                "alpha": styles["alpha"],
+                "zorder": styles["zorder"],
+            }
+            self.draw_path(
+                data=vertices,
+                coordinates=path_coordinates,
+                pathcodes=pathcodes,
+                style=style,
+                offset=offset,
+                offset_coordinates=offset_coordinates,
+                mplobj=mplobj,
+            )
+
+    def draw_markers(self, data, coordinates, style, label, mplobj=None):
+        """
+        Draw a set of markers. By default, this is done by repeatedly
+        calling draw_path(), but renderers should generally overload
+        this method to provide a more efficient implementation.
+
+        In matplotlib, markers are created using the plt.plot() command.
+
+        Parameters
+        ----------
+        data : array_like
+            A shape (N, 2) array of datapoints.
+        coordinates : string
+            A string code, which should be either 'data' for data coordinates,
+            or 'figure' for figure (pixel) coordinates.
+        style : dictionary
+            a dictionary specifying the appearance of the markers.
+        mplobj : matplotlib object
+            the matplotlib plot element which generated this marker collection
+        """
+        vertices, pathcodes = style["markerpath"]
+        pathstyle = dict(
+            (key, style[key])
+            for key in ["alpha", "edgecolor", "facecolor", "zorder", "edgewidth"]
+        )
+        pathstyle["dasharray"] = "10,0"
+        for vertex in data:
+            self.draw_path(
+                data=vertices,
+                coordinates="points",
+                pathcodes=pathcodes,
+                style=pathstyle,
+                offset=vertex,
+                offset_coordinates=coordinates,
+                mplobj=mplobj,
+            )
+
+    def draw_text(
+        self, text, position, coordinates, style, text_type=None, mplobj=None
+    ):
+        """
+        Draw text on the image.
+
+        Parameters
+        ----------
+        text : string
+            The text to draw
+        position : tuple
+            The (x, y) position of the text
+        coordinates : string
+            A string code, which should be either 'data' for data coordinates,
+            or 'figure' for figure (pixel) coordinates.
+        style : dictionary
+            a dictionary specifying the appearance of the text.
+        text_type : string or None
+            if specified, a type of text such as "xlabel", "ylabel", "title"
+        mplobj : matplotlib object
+            the matplotlib plot element which generated this text
+        """
+        raise NotImplementedError()
+
+    def draw_path(
+        self,
+        data,
+        coordinates,
+        pathcodes,
+        style,
+        offset=None,
+        offset_coordinates="data",
+        mplobj=None,
+    ):
+        """
+        Draw a path.
+
+        In matplotlib, paths are created by filled regions, histograms,
+        contour plots, patches, etc.
+
+        Parameters
+        ----------
+        data : array_like
+            A shape (N, 2) array of datapoints.
+        coordinates : string
+            A string code, which should be either 'data' for data coordinates,
+            'figure' for figure (pixel) coordinates, or "points" for raw
+            point coordinates (useful in conjunction with offsets, below).
+        pathcodes : list
+            A list of single-character SVG pathcodes associated with the data.
+            Path codes are one of ['M', 'm', 'L', 'l', 'Q', 'q', 'T', 't',
+                                   'S', 's', 'C', 'c', 'Z', 'z']
+            See the SVG specification for details.  Note that some path codes
+            consume more than one datapoint (while 'Z' consumes none), so
+            in general, the length of the pathcodes list will not be the same
+            as that of the data array.
+        style : dictionary
+            a dictionary specifying the appearance of the line.
+        offset : list (optional)
+            the (x, y) offset of the path. If not given, no offset will
+            be used.
+        offset_coordinates : string (optional)
+            A string code, which should be either 'data' for data coordinates,
+            or 'figure' for figure (pixel) coordinates.
+        mplobj : matplotlib object
+            the matplotlib plot element which generated this path
+        """
+        raise NotImplementedError()
+
+    def draw_image(self, imdata, extent, coordinates, style, mplobj=None):
+        """
+        Draw an image.
+
+        Parameters
+        ----------
+        imdata : string
+            base64 encoded png representation of the image
+        extent : list
+            the axes extent of the image: [xmin, xmax, ymin, ymax]
+        coordinates: string
+            A string code, which should be either 'data' for data coordinates,
+            or 'figure' for figure (pixel) coordinates.
+        style : dictionary
+            a dictionary specifying the appearance of the image
+        mplobj : matplotlib object
+            the matplotlib plot object which generated this image
+        """
+        raise NotImplementedError()

.venv/Lib/site-packages/plotly/matplotlylib/mplexporter/renderers/fake_renderer.py

@@ -0,0 +1,88 @@
+from .base import Renderer
+
+
+class FakeRenderer(Renderer):
+    """
+    Fake Renderer
+
+    This is a fake renderer which simply outputs a text tree representing the
+    elements found in the plot(s).  This is used in the unit tests for the
+    package.
+
+    Below are the methods your renderer must implement. You are free to do
+    anything you wish within the renderer (i.e. build an XML or JSON
+    representation, call an external API, etc.)  Here the renderer just
+    builds a simple string representation for testing purposes.
+    """
+
+    def __init__(self):
+        self.output = ""
+
+    def open_figure(self, fig, props):
+        self.output += "opening figure\n"
+
+    def close_figure(self, fig):
+        self.output += "closing figure\n"
+
+    def open_axes(self, ax, props):
+        self.output += "  opening axes\n"
+
+    def close_axes(self, ax):
+        self.output += "  closing axes\n"
+
+    def open_legend(self, legend, props):
+        self.output += "    opening legend\n"
+
+    def close_legend(self, legend):
+        self.output += "    closing legend\n"
+
+    def draw_text(
+        self, text, position, coordinates, style, text_type=None, mplobj=None
+    ):
+        self.output += "    draw text '{0}' {1}\n".format(text, text_type)
+
+    def draw_path(
+        self,
+        data,
+        coordinates,
+        pathcodes,
+        style,
+        offset=None,
+        offset_coordinates="data",
+        mplobj=None,
+    ):
+        self.output += "    draw path with {0} vertices\n".format(data.shape[0])
+
+    def draw_image(self, imdata, extent, coordinates, style, mplobj=None):
+        self.output += "    draw image of size {0}\n".format(len(imdata))
+
+
+class FullFakeRenderer(FakeRenderer):
+    """
+    Renderer with the full complement of methods.
+
+    When the following are left undefined, they will be implemented via
+    other methods in the class.  They can be defined explicitly for
+    more efficient or specialized use within the renderer implementation.
+    """
+
+    def draw_line(self, data, coordinates, style, label, mplobj=None):
+        self.output += "    draw line with {0} points\n".format(data.shape[0])
+
+    def draw_markers(self, data, coordinates, style, label, mplobj=None):
+        self.output += "    draw {0} markers\n".format(data.shape[0])
+
+    def draw_path_collection(
+        self,
+        paths,
+        path_coordinates,
+        path_transforms,
+        offsets,
+        offset_coordinates,
+        offset_order,
+        styles,
+        mplobj=None,
+    ):
+        self.output += "    draw path collection " "with {0} offsets\n".format(
+            offsets.shape[0]
+        )

.venv/Lib/site-packages/plotly/matplotlylib/mplexporter/renderers/vega_renderer.py

@@ -0,0 +1,145 @@
+import warnings
+import json
+import random
+from .base import Renderer
+from ..exporter import Exporter
+
+
+class VegaRenderer(Renderer):
+    def open_figure(self, fig, props):
+        self.props = props
+        self.figwidth = int(props["figwidth"] * props["dpi"])
+        self.figheight = int(props["figheight"] * props["dpi"])
+        self.data = []
+        self.scales = []
+        self.axes = []
+        self.marks = []
+
+    def open_axes(self, ax, props):
+        if len(self.axes) > 0:
+            warnings.warn("multiple axes not yet supported")
+        self.axes = [
+            dict(type="x", scale="x", ticks=10),
+            dict(type="y", scale="y", ticks=10),
+        ]
+        self.scales = [
+            dict(name="x", domain=props["xlim"], type="linear", range="width",),
+            dict(name="y", domain=props["ylim"], type="linear", range="height",),
+        ]
+
+    def draw_line(self, data, coordinates, style, label, mplobj=None):
+        if coordinates != "data":
+            warnings.warn("Only data coordinates supported. Skipping this")
+        dataname = "table{0:03d}".format(len(self.data) + 1)
+
+        # TODO: respect the other style settings
+        self.data.append(
+            {"name": dataname, "values": [dict(x=d[0], y=d[1]) for d in data]}
+        )
+        self.marks.append(
+            {
+                "type": "line",
+                "from": {"data": dataname},
+                "properties": {
+                    "enter": {
+                        "interpolate": {"value": "monotone"},
+                        "x": {"scale": "x", "field": "data.x"},
+                        "y": {"scale": "y", "field": "data.y"},
+                        "stroke": {"value": style["color"]},
+                        "strokeOpacity": {"value": style["alpha"]},
+                        "strokeWidth": {"value": style["linewidth"]},
+                    }
+                },
+            }
+        )
+
+    def draw_markers(self, data, coordinates, style, label, mplobj=None):
+        if coordinates != "data":
+            warnings.warn("Only data coordinates supported. Skipping this")
+        dataname = "table{0:03d}".format(len(self.data) + 1)
+
+        # TODO: respect the other style settings
+        self.data.append(
+            {"name": dataname, "values": [dict(x=d[0], y=d[1]) for d in data]}
+        )
+        self.marks.append(
+            {
+                "type": "symbol",
+                "from": {"data": dataname},
+                "properties": {
+                    "enter": {
+                        "interpolate": {"value": "monotone"},
+                        "x": {"scale": "x", "field": "data.x"},
+                        "y": {"scale": "y", "field": "data.y"},
+                        "fill": {"value": style["facecolor"]},
+                        "fillOpacity": {"value": style["alpha"]},
+                        "stroke": {"value": style["edgecolor"]},
+                        "strokeOpacity": {"value": style["alpha"]},
+                        "strokeWidth": {"value": style["edgewidth"]},
+                    }
+                },
+            }
+        )
+
+    def draw_text(
+        self, text, position, coordinates, style, text_type=None, mplobj=None
+    ):
+        if text_type == "xlabel":
+            self.axes[0]["title"] = text
+        elif text_type == "ylabel":
+            self.axes[1]["title"] = text
+
+
+class VegaHTML(object):
+    def __init__(self, renderer):
+        self.specification = dict(
+            width=renderer.figwidth,
+            height=renderer.figheight,
+            data=renderer.data,
+            scales=renderer.scales,
+            axes=renderer.axes,
+            marks=renderer.marks,
+        )
+
+    def html(self):
+        """Build the HTML representation for IPython."""
+        id = random.randint(0, 2 ** 16)
+        html = '<div id="vis%d"></div>' % id
+        html += "<script>\n"
+        html += VEGA_TEMPLATE % (json.dumps(self.specification), id)
+        html += "</script>\n"
+        return html
+
+    def _repr_html_(self):
+        return self.html()
+
+
+def fig_to_vega(fig, notebook=False):
+    """Convert a matplotlib figure to vega dictionary
+
+    if notebook=True, then return an object which will display in a notebook
+    otherwise, return an HTML string.
+    """
+    renderer = VegaRenderer()
+    Exporter(renderer).run(fig)
+    vega_html = VegaHTML(renderer)
+    if notebook:
+        return vega_html
+    else:
+        return vega_html.html()
+
+
+VEGA_TEMPLATE = """
+( function() {
+  var _do_plot = function() {
+    if ( (typeof vg == 'undefined') && (typeof IPython != 'undefined')) {
+      $([IPython.events]).on("vega_loaded.vincent", _do_plot);
+      return;
+    }
+    vg.parse.spec(%s, function(chart) {
+      chart({el: "#vis%d"}).update();
+    });
+  };
+  _do_plot();
+})();
+"""

.venv/Lib/site-packages/plotly/matplotlylib/mplexporter/renderers/vincent_renderer.py

@@ -0,0 +1,54 @@
+import warnings
+from .base import Renderer
+from ..exporter import Exporter
+
+
+class VincentRenderer(Renderer):
+    def open_figure(self, fig, props):
+        self.chart = None
+        self.figwidth = int(props["figwidth"] * props["dpi"])
+        self.figheight = int(props["figheight"] * props["dpi"])
+
+    def draw_line(self, data, coordinates, style, label, mplobj=None):
+        import vincent  # only import if VincentRenderer is used
+
+        if coordinates != "data":
+            warnings.warn("Only data coordinates supported. Skipping this")
+        linedata = {"x": data[:, 0], "y": data[:, 1]}
+        line = vincent.Line(
+            linedata, iter_idx="x", width=self.figwidth, height=self.figheight
+        )
+
+        # TODO: respect the other style settings
+        line.scales["color"].range = [style["color"]]
+
+        if self.chart is None:
+            self.chart = line
+        else:
+            warnings.warn("Multiple plot elements not yet supported")
+
+    def draw_markers(self, data, coordinates, style, label, mplobj=None):
+        import vincent  # only import if VincentRenderer is used
+
+        if coordinates != "data":
+            warnings.warn("Only data coordinates supported. Skipping this")
+        markerdata = {"x": data[:, 0], "y": data[:, 1]}
+        markers = vincent.Scatter(
+            markerdata, iter_idx="x", width=self.figwidth, height=self.figheight
+        )
+
+        # TODO: respect the other style settings
+        markers.scales["color"].range = [style["facecolor"]]
+
+        if self.chart is None:
+            self.chart = markers
+        else:
+            warnings.warn("Multiple plot elements not yet supported")
+
+
+def fig_to_vincent(fig):
+    """Convert a matplotlib figure to a vincent object"""
+    renderer = VincentRenderer()
+    exporter = Exporter(renderer)
+    exporter.run(fig)
+    return renderer.chart

.venv/Lib/site-packages/plotly/matplotlylib/mplexporter/tools.py

@@ -0,0 +1,55 @@
+"""
+Tools for matplotlib plot exporting
+"""
+
+
+def ipynb_vega_init():
+    """Initialize the IPython notebook display elements
+
+    This function borrows heavily from the excellent vincent package:
+    http://github.com/wrobstory/vincent
+    """
+    try:
+        from IPython.core.display import display, HTML
+    except ImportError:
+        print("IPython Notebook could not be loaded.")
+
+    require_js = """
+    if (window['d3'] === undefined) {{
+        require.config({{ paths: {{d3: "http://d3js.org/d3.v3.min"}} }});
+        require(["d3"], function(d3) {{
+          window.d3 = d3;
+          {0}
+        }});
+    }};
+    if (window['topojson'] === undefined) {{
+        require.config(
+            {{ paths: {{topojson: "http://d3js.org/topojson.v1.min"}} }}
+            );
+        require(["topojson"], function(topojson) {{
+          window.topojson = topojson;
+        }});
+    }};
+    """
+    d3_geo_projection_js_url = "http://d3js.org/d3.geo.projection.v0.min.js"
+    d3_layout_cloud_js_url = "http://wrobstory.github.io/d3-cloud/" "d3.layout.cloud.js"
+    topojson_js_url = "http://d3js.org/topojson.v1.min.js"
+    vega_js_url = "http://trifacta.github.com/vega/vega.js"
+
+    dep_libs = """$.getScript("%s", function() {
+        $.getScript("%s", function() {
+            $.getScript("%s", function() {
+                $.getScript("%s", function() {
+                        $([IPython.events]).trigger("vega_loaded.vincent");
+                })
+            })
+        })
+    });""" % (
+        d3_geo_projection_js_url,
+        d3_layout_cloud_js_url,
+        topojson_js_url,
+        vega_js_url,
+    )
+    load_js = require_js.format(dep_libs)
+    html = "<script>" + load_js + "</script>"
+    display(HTML(html))

.venv/Lib/site-packages/plotly/matplotlylib/mplexporter/utils.py

@@ -0,0 +1,382 @@
+"""
+Utility Routines for Working with Matplotlib Objects
+====================================================
+"""
+import itertools
+import io
+import base64
+
+import numpy as np
+
+import warnings
+
+import matplotlib
+from matplotlib.colors import colorConverter
+from matplotlib.path import Path
+from matplotlib.markers import MarkerStyle
+from matplotlib.transforms import Affine2D
+from matplotlib import ticker
+
+
+def export_color(color):
+    """Convert matplotlib color code to hex color or RGBA color"""
+    if color is None or colorConverter.to_rgba(color)[3] == 0:
+        return "none"
+    elif colorConverter.to_rgba(color)[3] == 1:
+        rgb = colorConverter.to_rgb(color)
+        return "#{0:02X}{1:02X}{2:02X}".format(*(int(255 * c) for c in rgb))
+    else:
+        c = colorConverter.to_rgba(color)
+        return (
+            "rgba("
+            + ", ".join(str(int(np.round(val * 255))) for val in c[:3])
+            + ", "
+            + str(c[3])
+            + ")"
+        )
+
+
+def _many_to_one(input_dict):
+    """Convert a many-to-one mapping to a one-to-one mapping"""
+    return dict((key, val) for keys, val in input_dict.items() for key in keys)
+
+
+LINESTYLES = _many_to_one(
+    {
+        ("solid", "-", (None, None)): "none",
+        ("dashed", "--"): "6,6",
+        ("dotted", ":"): "2,2",
+        ("dashdot", "-."): "4,4,2,4",
+        ("", " ", "None", "none"): None,
+    }
+)
+
+
+def get_dasharray(obj):
+    """Get an SVG dash array for the given matplotlib linestyle
+
+    Parameters
+    ----------
+    obj : matplotlib object
+        The matplotlib line or path object, which must have a get_linestyle()
+        method which returns a valid matplotlib line code
+
+    Returns
+    -------
+    dasharray : string
+        The HTML/SVG dasharray code associated with the object.
+    """
+    if obj.__dict__.get("_dashSeq", None) is not None:
+        return ",".join(map(str, obj._dashSeq))
+    else:
+        ls = obj.get_linestyle()
+        dasharray = LINESTYLES.get(ls, "not found")
+        if dasharray == "not found":
+            warnings.warn(
+                "line style '{0}' not understood: "
+                "defaulting to solid line.".format(ls)
+            )
+            dasharray = LINESTYLES["solid"]
+        return dasharray
+
+
+PATH_DICT = {
+    Path.LINETO: "L",
+    Path.MOVETO: "M",
+    Path.CURVE3: "S",
+    Path.CURVE4: "C",
+    Path.CLOSEPOLY: "Z",
+}
+
+
+def SVG_path(path, transform=None, simplify=False):
+    """Construct the vertices and SVG codes for the path
+
+    Parameters
+    ----------
+    path : matplotlib.Path object
+
+    transform : matplotlib transform (optional)
+        if specified, the path will be transformed before computing the output.
+
+    Returns
+    -------
+    vertices : array
+        The shape (M, 2) array of vertices of the Path. Note that some Path
+        codes require multiple vertices, so the length of these vertices may
+        be longer than the list of path codes.
+    path_codes : list
+        A length N list of single-character path codes, N <= M. Each code is
+        a single character, in ['L','M','S','C','Z']. See the standard SVG
+        path specification for a description of these.
+    """
+    if transform is not None:
+        path = path.transformed(transform)
+
+    vc_tuples = [
+        (vertices if path_code != Path.CLOSEPOLY else [], PATH_DICT[path_code])
+        for (vertices, path_code) in path.iter_segments(simplify=simplify)
+    ]
+
+    if not vc_tuples:
+        # empty path is a special case
+        return np.zeros((0, 2)), []
+    else:
+        vertices, codes = zip(*vc_tuples)
+        vertices = np.array(list(itertools.chain(*vertices))).reshape(-1, 2)
+        return vertices, list(codes)
+
+
+def get_path_style(path, fill=True):
+    """Get the style dictionary for matplotlib path objects"""
+    style = {}
+    style["alpha"] = path.get_alpha()
+    if style["alpha"] is None:
+        style["alpha"] = 1
+    style["edgecolor"] = export_color(path.get_edgecolor())
+    if fill:
+        style["facecolor"] = export_color(path.get_facecolor())
+    else:
+        style["facecolor"] = "none"
+    style["edgewidth"] = path.get_linewidth()
+    style["dasharray"] = get_dasharray(path)
+    style["zorder"] = path.get_zorder()
+    return style
+
+
+def get_line_style(line):
+    """Get the style dictionary for matplotlib line objects"""
+    style = {}
+    style["alpha"] = line.get_alpha()
+    if style["alpha"] is None:
+        style["alpha"] = 1
+    style["color"] = export_color(line.get_color())
+    style["linewidth"] = line.get_linewidth()
+    style["dasharray"] = get_dasharray(line)
+    style["zorder"] = line.get_zorder()
+    style["drawstyle"] = line.get_drawstyle()
+    return style
+
+
+def get_marker_style(line):
+    """Get the style dictionary for matplotlib marker objects"""
+    style = {}
+    style["alpha"] = line.get_alpha()
+    if style["alpha"] is None:
+        style["alpha"] = 1
+
+    style["facecolor"] = export_color(line.get_markerfacecolor())
+    style["edgecolor"] = export_color(line.get_markeredgecolor())
+    style["edgewidth"] = line.get_markeredgewidth()
+
+    style["marker"] = line.get_marker()
+    markerstyle = MarkerStyle(line.get_marker())
+    markersize = line.get_markersize()
+    markertransform = markerstyle.get_transform() + Affine2D().scale(
+        markersize, -markersize
+    )
+    style["markerpath"] = SVG_path(markerstyle.get_path(), markertransform)
+    style["markersize"] = markersize
+    style["zorder"] = line.get_zorder()
+    return style
+
+
+def get_text_style(text):
+    """Return the text style dict for a text instance"""
+    style = {}
+    style["alpha"] = text.get_alpha()
+    if style["alpha"] is None:
+        style["alpha"] = 1
+    style["fontsize"] = text.get_size()
+    style["color"] = export_color(text.get_color())
+    style["halign"] = text.get_horizontalalignment()  # left, center, right
+    style["valign"] = text.get_verticalalignment()  # baseline, center, top
+    style["malign"] = text._multialignment  # text alignment when '\n' in text
+    style["rotation"] = text.get_rotation()
+    style["zorder"] = text.get_zorder()
+    return style
+
+
+def get_axis_properties(axis):
+    """Return the property dictionary for a matplotlib.Axis instance"""
+    props = {}
+    label1On = axis._major_tick_kw.get("label1On", True)
+
+    if isinstance(axis, matplotlib.axis.XAxis):
+        if label1On:
+            props["position"] = "bottom"
+        else:
+            props["position"] = "top"
+    elif isinstance(axis, matplotlib.axis.YAxis):
+        if label1On:
+            props["position"] = "left"
+        else:
+            props["position"] = "right"
+    else:
+        raise ValueError("{0} should be an Axis instance".format(axis))
+
+    # Use tick values if appropriate
+    locator = axis.get_major_locator()
+    props["nticks"] = len(locator())
+    if isinstance(locator, ticker.FixedLocator):
+        props["tickvalues"] = list(locator())
+    else:
+        props["tickvalues"] = None
+
+    # Find tick formats
+    formatter = axis.get_major_formatter()
+    if isinstance(formatter, ticker.NullFormatter):
+        props["tickformat"] = ""
+    elif isinstance(formatter, ticker.FixedFormatter):
+        props["tickformat"] = list(formatter.seq)
+    elif isinstance(formatter, ticker.FuncFormatter):
+        props["tickformat"] = list(formatter.func.args[0].values())
+    elif not any(label.get_visible() for label in axis.get_ticklabels()):
+        props["tickformat"] = ""
+    else:
+        props["tickformat"] = None
+
+    # Get axis scale
+    props["scale"] = axis.get_scale()
+
+    # Get major tick label size (assumes that's all we really care about!)
+    labels = axis.get_ticklabels()
+    if labels:
+        props["fontsize"] = labels[0].get_fontsize()
+    else:
+        props["fontsize"] = None
+
+    # Get associated grid
+    props["grid"] = get_grid_style(axis)
+
+    # get axis visibility
+    props["visible"] = axis.get_visible()
+
+    return props
+
+
+def get_grid_style(axis):
+    gridlines = axis.get_gridlines()
+    if axis._major_tick_kw["gridOn"] and len(gridlines) > 0:
+        color = export_color(gridlines[0].get_color())
+        alpha = gridlines[0].get_alpha()
+        dasharray = get_dasharray(gridlines[0])
+        return dict(gridOn=True, color=color, dasharray=dasharray, alpha=alpha)
+    else:
+        return {"gridOn": False}
+
+
+def get_figure_properties(fig):
+    return {
+        "figwidth": fig.get_figwidth(),
+        "figheight": fig.get_figheight(),
+        "dpi": fig.dpi,
+    }
+
+
+def get_axes_properties(ax):
+    props = {
+        "axesbg": export_color(ax.patch.get_facecolor()),
+        "axesbgalpha": ax.patch.get_alpha(),
+        "bounds": ax.get_position().bounds,
+        "dynamic": ax.get_navigate(),
+        "axison": ax.axison,
+        "frame_on": ax.get_frame_on(),
+        "patch_visible": ax.patch.get_visible(),
+        "axes": [get_axis_properties(ax.xaxis), get_axis_properties(ax.yaxis)],
+    }
+
+    for axname in ["x", "y"]:
+        axis = getattr(ax, axname + "axis")
+        domain = getattr(ax, "get_{0}lim".format(axname))()
+        lim = domain
+        if isinstance(axis.converter, matplotlib.dates.DateConverter):
+            scale = "date"
+            try:
+                import pandas as pd
+                from pandas.tseries.converter import PeriodConverter
+            except ImportError:
+                pd = None
+
+            if pd is not None and isinstance(axis.converter, PeriodConverter):
+                _dates = [pd.Period(ordinal=int(d), freq=axis.freq) for d in domain]
+                domain = [
+                    (d.year, d.month - 1, d.day, d.hour, d.minute, d.second, 0)
+                    for d in _dates
+                ]
+            else:
+                domain = [
+                    (
+                        d.year,
+                        d.month - 1,
+                        d.day,
+                        d.hour,
+                        d.minute,
+                        d.second,
+                        d.microsecond * 1e-3,
+                    )
+                    for d in matplotlib.dates.num2date(domain)
+                ]
+        else:
+            scale = axis.get_scale()
+
+        if scale not in ["date", "linear", "log"]:
+            raise ValueError("Unknown axis scale: " "{0}".format(axis.get_scale()))
+
+        props[axname + "scale"] = scale
+        props[axname + "lim"] = lim
+        props[axname + "domain"] = domain
+
+    return props
+
+
+def iter_all_children(obj, skipContainers=False):
+    """
+    Returns an iterator over all childen and nested children using
+    obj's get_children() method
+
+    if skipContainers is true, only childless objects are returned.
+    """
+    if hasattr(obj, "get_children") and len(obj.get_children()) > 0:
+        for child in obj.get_children():
+            if not skipContainers:
+                yield child
+            # could use `yield from` in python 3...
+            for grandchild in iter_all_children(child, skipContainers):
+                yield grandchild
+    else:
+        yield obj
+
+
+def get_legend_properties(ax, legend):
+    handles, labels = ax.get_legend_handles_labels()
+    visible = legend.get_visible()
+    return {"handles": handles, "labels": labels, "visible": visible}
+
+
+def image_to_base64(image):
+    """
+    Convert a matplotlib image to a base64 png representation
+
+    Parameters
+    ----------
+    image : matplotlib image object
+        The image to be converted.
+
+    Returns
+    -------
+    image_base64 : string
+        The UTF8-encoded base64 string representation of the png image.
+    """
+    ax = image.axes
+    binary_buffer = io.BytesIO()
+
+    # image is saved in axes coordinates: we need to temporarily
+    # set the correct limits to get the correct image
+    lim = ax.axis()
+    ax.axis(image.get_extent())
+    image.write_png(binary_buffer)
+    ax.axis(lim)
+
+    binary_buffer.seek(0)
+    return base64.b64encode(binary_buffer.read()).decode("utf-8")

.venv/Lib/site-packages/plotly/matplotlylib/mpltools.py

@@ -0,0 +1,611 @@
+"""
+Tools
+
+A module for converting from mpl language to plotly language.
+
+"""
+import math
+import datetime
+
+import warnings
+import matplotlib.dates
+
+
+def check_bar_match(old_bar, new_bar):
+    """Check if two bars belong in the same collection (bar chart).
+
+    Positional arguments:
+    old_bar -- a previously sorted bar dictionary.
+    new_bar -- a new bar dictionary that needs to be sorted.
+
+    """
+    tests = []
+    tests += (new_bar["orientation"] == old_bar["orientation"],)
+    tests += (new_bar["facecolor"] == old_bar["facecolor"],)
+    if new_bar["orientation"] == "v":
+        new_width = new_bar["x1"] - new_bar["x0"]
+        old_width = old_bar["x1"] - old_bar["x0"]
+        tests += (new_width - old_width < 0.000001,)
+        tests += (new_bar["y0"] == old_bar["y0"],)
+    elif new_bar["orientation"] == "h":
+        new_height = new_bar["y1"] - new_bar["y0"]
+        old_height = old_bar["y1"] - old_bar["y0"]
+        tests += (new_height - old_height < 0.000001,)
+        tests += (new_bar["x0"] == old_bar["x0"],)
+    if all(tests):
+        return True
+    else:
+        return False
+
+
+def check_corners(inner_obj, outer_obj):
+    inner_corners = inner_obj.get_window_extent().corners()
+    outer_corners = outer_obj.get_window_extent().corners()
+    if inner_corners[0][0] < outer_corners[0][0]:
+        return False
+    elif inner_corners[0][1] < outer_corners[0][1]:
+        return False
+    elif inner_corners[3][0] > outer_corners[3][0]:
+        return False
+    elif inner_corners[3][1] > outer_corners[3][1]:
+        return False
+    else:
+        return True
+
+
+def convert_dash(mpl_dash):
+    """Convert mpl line symbol to plotly line symbol and return symbol."""
+    if mpl_dash in DASH_MAP:
+        return DASH_MAP[mpl_dash]
+    else:
+        dash_array = mpl_dash.split(",")
+
+        if len(dash_array) < 2:
+            return "solid"
+
+        # Catch the exception where the off length is zero, in case
+        # matplotlib 'solid' changes from '10,0' to 'N,0'
+        if math.isclose(float(dash_array[1]), 0.0):
+            return "solid"
+
+        # If we can't find the dash pattern in the map, convert it
+        # into custom values in px, e.g. '7,5' -> '7px,5px'
+        dashpx = ",".join([x + "px" for x in dash_array])
+
+        # TODO: rewrite the convert_dash code
+        # only strings 'solid', 'dashed', etc allowed
+        if dashpx == "7.4px,3.2px":
+            dashpx = "dashed"
+        elif dashpx == "12.8px,3.2px,2.0px,3.2px":
+            dashpx = "dashdot"
+        elif dashpx == "2.0px,3.3px":
+            dashpx = "dotted"
+        return dashpx
+
+
+def convert_path(path):
+    verts = path[0]  # may use this later
+    code = tuple(path[1])
+    if code in PATH_MAP:
+        return PATH_MAP[code]
+    else:
+        return None
+
+
+def convert_symbol(mpl_symbol):
+    """Convert mpl marker symbol to plotly symbol and return symbol."""
+    if isinstance(mpl_symbol, list):
+        symbol = list()
+        for s in mpl_symbol:
+            symbol += [convert_symbol(s)]
+        return symbol
+    elif mpl_symbol in SYMBOL_MAP:
+        return SYMBOL_MAP[mpl_symbol]
+    else:
+        return "circle"  # default
+
+
+def hex_to_rgb(value):
+    """
+    Change a hex color to an rgb tuple
+
+    :param (str|unicode) value: The hex string we want to convert.
+    :return: (int, int, int) The red, green, blue int-tuple.
+
+    Example:
+
+        '#FFFFFF' --> (255, 255, 255)
+
+    """
+    value = value.lstrip("#")
+    lv = len(value)
+    return tuple(int(value[i : i + lv // 3], 16) for i in range(0, lv, lv // 3))
+
+
+def merge_color_and_opacity(color, opacity):
+    """
+    Merge hex color with an alpha (opacity) to get an rgba tuple.
+
+    :param (str|unicode) color: A hex color string.
+    :param (float|int) opacity: A value [0, 1] for the 'a' in 'rgba'.
+    :return: (int, int, int, float) The rgba color and alpha tuple.
+
+    """
+    if color is None:  # None can be used as a placeholder, just bail.
+        return None
+
+    rgb_tup = hex_to_rgb(color)
+    if opacity is None:
+        return "rgb {}".format(rgb_tup)
+
+    rgba_tup = rgb_tup + (opacity,)
+    return "rgba {}".format(rgba_tup)
+
+
+def convert_va(mpl_va):
+    """Convert mpl vertical alignment word to equivalent HTML word.
+
+    Text alignment specifiers from mpl differ very slightly from those used
+    in HTML. See the VA_MAP for more details.
+
+    Positional arguments:
+    mpl_va -- vertical mpl text alignment spec.
+
+    """
+    if mpl_va in VA_MAP:
+        return VA_MAP[mpl_va]
+    else:
+        return None  # let plotly figure it out!
+
+
+def convert_x_domain(mpl_plot_bounds, mpl_max_x_bounds):
+    """Map x dimension of current plot to plotly's domain space.
+
+    The bbox used to locate an axes object in mpl differs from the
+    method used to locate axes in plotly. The mpl version locates each
+    axes in the figure so that axes in a single-plot figure might have
+    the bounds, [0.125, 0.125, 0.775, 0.775] (x0, y0, width, height),
+    in mpl's figure coordinates. However, the axes all share one space in
+    plotly such that the domain will always be [0, 0, 1, 1]
+    (x0, y0, x1, y1). To convert between the two, the mpl figure bounds
+    need to be mapped to a [0, 1] domain for x and y. The margins set
+    upon opening a new figure will appropriately match the mpl margins.
+
+    Optionally, setting margins=0 and simply copying the domains from
+    mpl to plotly would place axes appropriately. However,
+    this would throw off axis and title labeling.
+
+    Positional arguments:
+    mpl_plot_bounds -- the (x0, y0, width, height) params for current ax **
+    mpl_max_x_bounds -- overall (x0, x1) bounds for all axes **
+
+    ** these are all specified in mpl figure coordinates
+
+    """
+    mpl_x_dom = [mpl_plot_bounds[0], mpl_plot_bounds[0] + mpl_plot_bounds[2]]
+    plotting_width = mpl_max_x_bounds[1] - mpl_max_x_bounds[0]
+    x0 = (mpl_x_dom[0] - mpl_max_x_bounds[0]) / plotting_width
+    x1 = (mpl_x_dom[1] - mpl_max_x_bounds[0]) / plotting_width
+    return [x0, x1]
+
+
+def convert_y_domain(mpl_plot_bounds, mpl_max_y_bounds):
+    """Map y dimension of current plot to plotly's domain space.
+
+    The bbox used to locate an axes object in mpl differs from the
+    method used to locate axes in plotly. The mpl version locates each
+    axes in the figure so that axes in a single-plot figure might have
+    the bounds, [0.125, 0.125, 0.775, 0.775] (x0, y0, width, height),
+    in mpl's figure coordinates. However, the axes all share one space in
+    plotly such that the domain will always be [0, 0, 1, 1]
+    (x0, y0, x1, y1). To convert between the two, the mpl figure bounds
+    need to be mapped to a [0, 1] domain for x and y. The margins set
+    upon opening a new figure will appropriately match the mpl margins.
+
+    Optionally, setting margins=0 and simply copying the domains from
+    mpl to plotly would place axes appropriately. However,
+    this would throw off axis and title labeling.
+
+    Positional arguments:
+    mpl_plot_bounds -- the (x0, y0, width, height) params for current ax **
+    mpl_max_y_bounds -- overall (y0, y1) bounds for all axes **
+
+    ** these are all specified in mpl figure coordinates
+
+    """
+    mpl_y_dom = [mpl_plot_bounds[1], mpl_plot_bounds[1] + mpl_plot_bounds[3]]
+    plotting_height = mpl_max_y_bounds[1] - mpl_max_y_bounds[0]
+    y0 = (mpl_y_dom[0] - mpl_max_y_bounds[0]) / plotting_height
+    y1 = (mpl_y_dom[1] - mpl_max_y_bounds[0]) / plotting_height
+    return [y0, y1]
+
+
+def display_to_paper(x, y, layout):
+    """Convert mpl display coordinates to plotly paper coordinates.
+
+    Plotly references object positions with an (x, y) coordinate pair in either
+    'data' or 'paper' coordinates which reference actual data in a plot or
+    the entire plotly axes space where the bottom-left of the bottom-left
+    plot has the location (x, y) = (0, 0) and the top-right of the top-right
+    plot has the location (x, y) = (1, 1). Display coordinates in mpl reference
+    objects with an (x, y) pair in pixel coordinates, where the bottom-left
+    corner is at the location (x, y) = (0, 0) and the top-right corner is at
+    the location (x, y) = (figwidth*dpi, figheight*dpi). Here, figwidth and
+    figheight are in inches and dpi are the dots per inch resolution.
+
+    """
+    num_x = x - layout["margin"]["l"]
+    den_x = layout["width"] - (layout["margin"]["l"] + layout["margin"]["r"])
+    num_y = y - layout["margin"]["b"]
+    den_y = layout["height"] - (layout["margin"]["b"] + layout["margin"]["t"])
+    return num_x / den_x, num_y / den_y
+
+
+def get_axes_bounds(fig):
+    """Return the entire axes space for figure.
+
+    An axes object in mpl is specified by its relation to the figure where
+    (0,0) corresponds to the bottom-left part of the figure and (1,1)
+    corresponds to the top-right. Margins exist in matplotlib because axes
+    objects normally don't go to the edges of the figure.
+
+    In plotly, the axes area (where all subplots go) is always specified with
+    the domain [0,1] for both x and y. This function finds the smallest box,
+    specified by two points, that all of the mpl axes objects fit into. This
+    box is then used to map mpl axes domains to plotly axes domains.
+
+    """
+    x_min, x_max, y_min, y_max = [], [], [], []
+    for axes_obj in fig.get_axes():
+        bounds = axes_obj.get_position().bounds
+        x_min.append(bounds[0])
+        x_max.append(bounds[0] + bounds[2])
+        y_min.append(bounds[1])
+        y_max.append(bounds[1] + bounds[3])
+    x_min, y_min, x_max, y_max = min(x_min), min(y_min), max(x_max), max(y_max)
+    return (x_min, x_max), (y_min, y_max)
+
+
+def get_axis_mirror(main_spine, mirror_spine):
+    if main_spine and mirror_spine:
+        return "ticks"
+    elif main_spine and not mirror_spine:
+        return False
+    elif not main_spine and mirror_spine:
+        return False  # can't handle this case yet!
+    else:
+        return False  # nuttin'!
+
+
+def get_bar_gap(bar_starts, bar_ends, tol=1e-10):
+    if len(bar_starts) == len(bar_ends) and len(bar_starts) > 1:
+        sides1 = bar_starts[1:]
+        sides2 = bar_ends[:-1]
+        gaps = [s2 - s1 for s2, s1 in zip(sides1, sides2)]
+        gap0 = gaps[0]
+        uniform = all([abs(gap0 - gap) < tol for gap in gaps])
+        if uniform:
+            return gap0
+
+
+def convert_rgba_array(color_list):
+    clean_color_list = list()
+    for c in color_list:
+        clean_color_list += [
+            (dict(r=int(c[0] * 255), g=int(c[1] * 255), b=int(c[2] * 255), a=c[3]))
+        ]
+    plotly_colors = list()
+    for rgba in clean_color_list:
+        plotly_colors += ["rgba({r},{g},{b},{a})".format(**rgba)]
+    if len(plotly_colors) == 1:
+        return plotly_colors[0]
+    else:
+        return plotly_colors
+
+
+def convert_path_array(path_array):
+    symbols = list()
+    for path in path_array:
+        symbols += [convert_path(path)]
+    if len(symbols) == 1:
+        return symbols[0]
+    else:
+        return symbols
+
+
+def convert_linewidth_array(width_array):
+    if len(width_array) == 1:
+        return width_array[0]
+    else:
+        return width_array
+
+
+def convert_size_array(size_array):
+    size = [math.sqrt(s) for s in size_array]
+    if len(size) == 1:
+        return size[0]
+    else:
+        return size
+
+
+def get_markerstyle_from_collection(props):
+    markerstyle = dict(
+        alpha=None,
+        facecolor=convert_rgba_array(props["styles"]["facecolor"]),
+        marker=convert_path_array(props["paths"]),
+        edgewidth=convert_linewidth_array(props["styles"]["linewidth"]),
+        # markersize=convert_size_array(props['styles']['size']),  # TODO!
+        markersize=convert_size_array(props["mplobj"].get_sizes()),
+        edgecolor=convert_rgba_array(props["styles"]["edgecolor"]),
+    )
+    return markerstyle
+
+
+def get_rect_xmin(data):
+    """Find minimum x value from four (x,y) vertices."""
+    return min(data[0][0], data[1][0], data[2][0], data[3][0])
+
+
+def get_rect_xmax(data):
+    """Find maximum x value from four (x,y) vertices."""
+    return max(data[0][0], data[1][0], data[2][0], data[3][0])
+
+
+def get_rect_ymin(data):
+    """Find minimum y value from four (x,y) vertices."""
+    return min(data[0][1], data[1][1], data[2][1], data[3][1])
+
+
+def get_rect_ymax(data):
+    """Find maximum y value from four (x,y) vertices."""
+    return max(data[0][1], data[1][1], data[2][1], data[3][1])
+
+
+def get_spine_visible(ax, spine_key):
+    """Return some spine parameters for the spine, `spine_key`."""
+    spine = ax.spines[spine_key]
+    ax_frame_on = ax.get_frame_on()
+    position = spine._position or ("outward", 0.0)
+    if isinstance(position, str):
+        if position == "center":
+            position = ("axes", 0.5)
+        elif position == "zero":
+            position = ("data", 0)
+    position_type, amount = position
+    if position_type == "outward" and amount == 0:
+        spine_frame_like = True
+    else:
+        spine_frame_like = False
+    if not spine.get_visible():
+        return False
+    elif not spine._edgecolor[-1]:  # user's may have set edgecolor alpha==0
+        return False
+    elif not ax_frame_on and spine_frame_like:
+        return False
+    elif ax_frame_on and spine_frame_like:
+        return True
+    elif not ax_frame_on and not spine_frame_like:
+        return True  # we've already checked for that it's visible.
+    else:
+        return False  # oh man, and i thought we exhausted the options...
+
+
+def is_bar(bar_containers, **props):
+    """A test to decide whether a path is a bar from a vertical bar chart."""
+
+    # is this patch in a bar container?
+    for container in bar_containers:
+        if props["mplobj"] in container:
+            return True
+    return False
+
+
+def make_bar(**props):
+    """Make an intermediate bar dictionary.
+
+    This creates a bar dictionary which aids in the comparison of new bars to
+    old bars from other bar chart (patch) collections. This is not the
+    dictionary that needs to get passed to plotly as a data dictionary. That
+    happens in PlotlyRenderer in that class's draw_bar method. In other
+    words, this dictionary describes a SINGLE bar, whereas, plotly will
+    require a set of bars to be passed in a data dictionary.
+
+    """
+    return {
+        "bar": props["mplobj"],
+        "x0": get_rect_xmin(props["data"]),
+        "y0": get_rect_ymin(props["data"]),
+        "x1": get_rect_xmax(props["data"]),
+        "y1": get_rect_ymax(props["data"]),
+        "alpha": props["style"]["alpha"],
+        "edgecolor": props["style"]["edgecolor"],
+        "facecolor": props["style"]["facecolor"],
+        "edgewidth": props["style"]["edgewidth"],
+        "dasharray": props["style"]["dasharray"],
+        "zorder": props["style"]["zorder"],
+    }
+
+
+def prep_ticks(ax, index, ax_type, props):
+    """Prepare axis obj belonging to axes obj.
+
+    positional arguments:
+    ax - the mpl axes instance
+    index - the index of the axis in `props`
+    ax_type - 'x' or 'y' (for now)
+    props - an mplexporter poperties dictionary
+
+    """
+    axis_dict = dict()
+    if ax_type == "x":
+        axis = ax.get_xaxis()
+    elif ax_type == "y":
+        axis = ax.get_yaxis()
+    else:
+        return dict()  # whoops!
+
+    scale = props["axes"][index]["scale"]
+    if scale == "linear":
+        # get tick location information
+        try:
+            tickvalues = props["axes"][index]["tickvalues"]
+            tick0 = tickvalues[0]
+            dticks = [
+                round(tickvalues[i] - tickvalues[i - 1], 12)
+                for i in range(1, len(tickvalues) - 1)
+            ]
+            if all([dticks[i] == dticks[i - 1] for i in range(1, len(dticks) - 1)]):
+                dtick = tickvalues[1] - tickvalues[0]
+            else:
+                warnings.warn(
+                    "'linear' {0}-axis tick spacing not even, "
+                    "ignoring mpl tick formatting.".format(ax_type)
+                )
+                raise TypeError
+        except (IndexError, TypeError):
+            axis_dict["nticks"] = props["axes"][index]["nticks"]
+        else:
+            axis_dict["tick0"] = tick0
+            axis_dict["dtick"] = dtick
+            axis_dict["tickmode"] = None
+    elif scale == "log":
+        try:
+            axis_dict["tick0"] = props["axes"][index]["tickvalues"][0]
+            axis_dict["dtick"] = (
+                props["axes"][index]["tickvalues"][1]
+                - props["axes"][index]["tickvalues"][0]
+            )
+            axis_dict["tickmode"] = None
+        except (IndexError, TypeError):
+            axis_dict = dict(nticks=props["axes"][index]["nticks"])
+        base = axis.get_transform().base
+        if base == 10:
+            if ax_type == "x":
+                axis_dict["range"] = [
+                    math.log10(props["xlim"][0]),
+                    math.log10(props["xlim"][1]),
+                ]
+            elif ax_type == "y":
+                axis_dict["range"] = [
+                    math.log10(props["ylim"][0]),
+                    math.log10(props["ylim"][1]),
+                ]
+        else:
+            axis_dict = dict(range=None, type="linear")
+            warnings.warn(
+                "Converted non-base10 {0}-axis log scale to 'linear'" "".format(ax_type)
+            )
+    else:
+        return dict()
+    # get tick label formatting information
+    formatter = axis.get_major_formatter().__class__.__name__
+    if ax_type == "x" and "DateFormatter" in formatter:
+        axis_dict["type"] = "date"
+        try:
+            axis_dict["tick0"] = mpl_dates_to_datestrings(axis_dict["tick0"], formatter)
+        except KeyError:
+            pass
+        finally:
+            axis_dict.pop("dtick", None)
+            axis_dict.pop("tickmode", None)
+            axis_dict["range"] = mpl_dates_to_datestrings(props["xlim"], formatter)
+
+    if formatter == "LogFormatterMathtext":
+        axis_dict["exponentformat"] = "e"
+    return axis_dict
+
+
+def prep_xy_axis(ax, props, x_bounds, y_bounds):
+    xaxis = dict(
+        type=props["axes"][0]["scale"],
+        range=list(props["xlim"]),
+        showgrid=props["axes"][0]["grid"]["gridOn"],
+        domain=convert_x_domain(props["bounds"], x_bounds),
+        side=props["axes"][0]["position"],
+        tickfont=dict(size=props["axes"][0]["fontsize"]),
+    )
+    xaxis.update(prep_ticks(ax, 0, "x", props))
+    yaxis = dict(
+        type=props["axes"][1]["scale"],
+        range=list(props["ylim"]),
+        showgrid=props["axes"][1]["grid"]["gridOn"],
+        domain=convert_y_domain(props["bounds"], y_bounds),
+        side=props["axes"][1]["position"],
+        tickfont=dict(size=props["axes"][1]["fontsize"]),
+    )
+    yaxis.update(prep_ticks(ax, 1, "y", props))
+    return xaxis, yaxis
+
+
+def mpl_dates_to_datestrings(dates, mpl_formatter):
+    """Convert matplotlib dates to iso-formatted-like time strings.
+
+    Plotly's accepted format: "YYYY-MM-DD HH:MM:SS" (e.g., 2001-01-01 00:00:00)
+
+    Info on mpl dates: http://matplotlib.org/api/dates_api.html
+
+    """
+    _dates = dates
+
+    # this is a pandas datetime formatter, times show up in floating point days
+    # since the epoch (1970-01-01T00:00:00+00:00)
+    if mpl_formatter == "TimeSeries_DateFormatter":
+        try:
+            dates = matplotlib.dates.epoch2num([date * 24 * 60 * 60 for date in dates])
+            dates = matplotlib.dates.num2date(dates)
+        except:
+            return _dates
+
+    # the rest of mpl dates are in floating point days since
+    # (0001-01-01T00:00:00+00:00) + 1. I.e., (0001-01-01T00:00:00+00:00) == 1.0
+    # according to mpl --> try num2date(1)
+    else:
+        try:
+            dates = matplotlib.dates.num2date(dates)
+        except:
+            return _dates
+
+    time_stings = [
+        " ".join(date.isoformat().split("+")[0].split("T")) for date in dates
+    ]
+    return time_stings
+
+
+# dashed is dash in matplotlib
+DASH_MAP = {
+    "10,0": "solid",
+    "6,6": "dash",
+    "2,2": "circle",
+    "4,4,2,4": "dashdot",
+    "none": "solid",
+    "7.4,3.2": "dash",
+}
+
+PATH_MAP = {
+    ("M", "C", "C", "C", "C", "C", "C", "C", "C", "Z"): "o",
+    ("M", "L", "L", "L", "L", "L", "L", "L", "L", "L", "Z"): "*",
+    ("M", "L", "L", "L", "L", "L", "L", "L", "Z"): "8",
+    ("M", "L", "L", "L", "L", "L", "Z"): "h",
+    ("M", "L", "L", "L", "L", "Z"): "p",
+    ("M", "L", "M", "L", "M", "L"): "1",
+    ("M", "L", "L", "L", "Z"): "s",
+    ("M", "L", "M", "L"): "+",
+    ("M", "L", "L", "Z"): "^",
+    ("M", "L"): "|",
+}
+
+SYMBOL_MAP = {
+    "o": "circle",
+    "v": "triangle-down",
+    "^": "triangle-up",
+    "<": "triangle-left",
+    ">": "triangle-right",
+    "s": "square",
+    "+": "cross",
+    "x": "x",
+    "*": "star",
+    "D": "diamond",
+    "d": "diamond",
+}
+
+VA_MAP = {"center": "middle", "baseline": "bottom", "top": "top"}

.venv/Lib/site-packages/plotly/matplotlylib/renderer.py

@@ -0,0 +1,865 @@
+"""
+Renderer Module
+
+This module defines the PlotlyRenderer class and a single function,
+fig_to_plotly, which is intended to be the main way that user's will interact
+with the matplotlylib package.
+
+"""
+from __future__ import absolute_import
+
+import warnings
+
+import plotly.graph_objs as go
+from plotly.matplotlylib.mplexporter import Renderer
+from plotly.matplotlylib import mpltools
+
+
+# Warning format
+def warning_on_one_line(msg, category, filename, lineno, file=None, line=None):
+    return "%s:%s: %s:\n\n%s\n\n" % (filename, lineno, category.__name__, msg)
+
+
+warnings.formatwarning = warning_on_one_line
+
+
+class PlotlyRenderer(Renderer):
+    """A renderer class inheriting from base for rendering mpl plots in plotly.
+
+    A renderer class to be used with an exporter for rendering matplotlib
+    plots in Plotly. This module defines the PlotlyRenderer class which handles
+    the creation of the JSON structures that get sent to plotly.
+
+    All class attributes available are defined in __init__().
+
+    Basic Usage:
+
+    # (mpl code) #
+    fig = gcf()
+    renderer = PlotlyRenderer(fig)
+    exporter = Exporter(renderer)
+    exporter.run(fig)  # ... et voila
+
+    """
+
+    def __init__(self):
+        """Initialize PlotlyRenderer obj.
+
+        PlotlyRenderer obj is called on by an Exporter object to draw
+        matplotlib objects like figures, axes, text, etc.
+
+        All class attributes are listed here in the __init__ method.
+
+        """
+        self.plotly_fig = go.Figure()
+        self.mpl_fig = None
+        self.current_mpl_ax = None
+        self.bar_containers = None
+        self.current_bars = []
+        self.axis_ct = 0
+        self.x_is_mpl_date = False
+        self.mpl_x_bounds = (0, 1)
+        self.mpl_y_bounds = (0, 1)
+        self.msg = "Initialized PlotlyRenderer\n"
+
+    def open_figure(self, fig, props):
+        """Creates a new figure by beginning to fill out layout dict.
+
+        The 'autosize' key is set to false so that the figure will mirror
+        sizes set by mpl. The 'hovermode' key controls what shows up when you
+        mouse around a figure in plotly, it's set to show the 'closest' point.
+
+        Positional agurments:
+        fig -- a matplotlib.figure.Figure object.
+        props.keys(): [
+            'figwidth',
+            'figheight',
+            'dpi'
+            ]
+
+        """
+        self.msg += "Opening figure\n"
+        self.mpl_fig = fig
+        self.plotly_fig["layout"] = go.Layout(
+            width=int(props["figwidth"] * props["dpi"]),
+            height=int(props["figheight"] * props["dpi"]),
+            autosize=False,
+            hovermode="closest",
+        )
+        self.mpl_x_bounds, self.mpl_y_bounds = mpltools.get_axes_bounds(fig)
+        margin = go.layout.Margin(
+            l=int(self.mpl_x_bounds[0] * self.plotly_fig["layout"]["width"]),
+            r=int((1 - self.mpl_x_bounds[1]) * self.plotly_fig["layout"]["width"]),
+            t=int((1 - self.mpl_y_bounds[1]) * self.plotly_fig["layout"]["height"]),
+            b=int(self.mpl_y_bounds[0] * self.plotly_fig["layout"]["height"]),
+            pad=0,
+        )
+        self.plotly_fig["layout"]["margin"] = margin
+
+    def close_figure(self, fig):
+        """Closes figure by cleaning up data and layout dictionaries.
+
+        The PlotlyRenderer's job is to create an appropriate set of data and
+        layout dictionaries. When the figure is closed, some cleanup and
+        repair is necessary. This method removes inappropriate dictionary
+        entries, freeing up Plotly to use defaults and best judgements to
+        complete the entries. This method is called by an Exporter object.
+
+        Positional arguments:
+        fig -- a matplotlib.figure.Figure object.
+
+        """
+        self.plotly_fig["layout"]["showlegend"] = False
+        self.msg += "Closing figure\n"
+
+    def open_axes(self, ax, props):
+        """Setup a new axes object (subplot in plotly).
+
+        Plotly stores information about subplots in different 'xaxis' and
+        'yaxis' objects which are numbered. These are just dictionaries
+        included in the layout dictionary. This function takes information
+        from the Exporter, fills in appropriate dictionary entries,
+        and updates the layout dictionary. PlotlyRenderer keeps track of the
+        number of plots by incrementing the axis_ct attribute.
+
+        Setting the proper plot domain in plotly is a bit tricky. Refer to
+        the documentation for mpltools.convert_x_domain and
+        mpltools.convert_y_domain.
+
+        Positional arguments:
+        ax -- an mpl axes object. This will become a subplot in plotly.
+        props.keys() -- [
+            'axesbg',           (background color for axes obj)
+            'axesbgalpha',      (alpha, or opacity for background)
+            'bounds',           ((x0, y0, width, height) for axes)
+            'dynamic',          (zoom/pan-able?)
+            'axes',             (list: [xaxis, yaxis])
+            'xscale',           (log, linear, or date)
+            'yscale',
+            'xlim',             (range limits for x)
+            'ylim',
+            'xdomain'           (xdomain=xlim, unless it's a date)
+            'ydomain'
+            ]
+
+        """
+        self.msg += "  Opening axes\n"
+        self.current_mpl_ax = ax
+        self.bar_containers = [
+            c
+            for c in ax.containers  # empty is OK
+            if c.__class__.__name__ == "BarContainer"
+        ]
+        self.current_bars = []
+        self.axis_ct += 1
+        # set defaults in axes
+        xaxis = go.layout.XAxis(
+            anchor="y{0}".format(self.axis_ct), zeroline=False, ticks="inside"
+        )
+        yaxis = go.layout.YAxis(
+            anchor="x{0}".format(self.axis_ct), zeroline=False, ticks="inside"
+        )
+        # update defaults with things set in mpl
+        mpl_xaxis, mpl_yaxis = mpltools.prep_xy_axis(
+            ax=ax, props=props, x_bounds=self.mpl_x_bounds, y_bounds=self.mpl_y_bounds
+        )
+        xaxis.update(mpl_xaxis)
+        yaxis.update(mpl_yaxis)
+        bottom_spine = mpltools.get_spine_visible(ax, "bottom")
+        top_spine = mpltools.get_spine_visible(ax, "top")
+        left_spine = mpltools.get_spine_visible(ax, "left")
+        right_spine = mpltools.get_spine_visible(ax, "right")
+        xaxis["mirror"] = mpltools.get_axis_mirror(bottom_spine, top_spine)
+        yaxis["mirror"] = mpltools.get_axis_mirror(left_spine, right_spine)
+        xaxis["showline"] = bottom_spine
+        yaxis["showline"] = top_spine
+
+        # put axes in our figure
+        self.plotly_fig["layout"]["xaxis{0}".format(self.axis_ct)] = xaxis
+        self.plotly_fig["layout"]["yaxis{0}".format(self.axis_ct)] = yaxis
+
+        # let all subsequent dates be handled properly if required
+
+        if "type" in dir(xaxis) and xaxis["type"] == "date":
+            self.x_is_mpl_date = True
+
+    def close_axes(self, ax):
+        """Close the axes object and clean up.
+
+        Bars from bar charts are given to PlotlyRenderer one-by-one,
+        thus they need to be taken care of at the close of each axes object.
+        The self.current_bars variable should be empty unless a bar
+        chart has been created.
+
+        Positional arguments:
+        ax -- an mpl axes object, not required at this time.
+
+        """
+        self.draw_bars(self.current_bars)
+        self.msg += "  Closing axes\n"
+        self.x_is_mpl_date = False
+
+    def draw_bars(self, bars):
+
+        # sort bars according to bar containers
+        mpl_traces = []
+        for container in self.bar_containers:
+            mpl_traces.append(
+                [
+                    bar_props
+                    for bar_props in self.current_bars
+                    if bar_props["mplobj"] in container
+                ]
+            )
+        for trace in mpl_traces:
+            self.draw_bar(trace)
+
+    def draw_bar(self, coll):
+        """Draw a collection of similar patches as a bar chart.
+
+        After bars are sorted, an appropriate data dictionary must be created
+        to tell plotly about this data. Just like draw_line or draw_markers,
+        draw_bar translates patch/path information into something plotly
+        understands.
+
+        Positional arguments:
+        patch_coll -- a collection of patches to be drawn as a bar chart.
+
+        """
+        tol = 1e-10
+        trace = [mpltools.make_bar(**bar_props) for bar_props in coll]
+        widths = [bar_props["x1"] - bar_props["x0"] for bar_props in trace]
+        heights = [bar_props["y1"] - bar_props["y0"] for bar_props in trace]
+        vertical = abs(sum(widths[0] - widths[iii] for iii in range(len(widths)))) < tol
+        horizontal = (
+            abs(sum(heights[0] - heights[iii] for iii in range(len(heights)))) < tol
+        )
+        if vertical and horizontal:
+            # Check for monotonic x. Can't both be true!
+            x_zeros = [bar_props["x0"] for bar_props in trace]
+            if all(
+                (x_zeros[iii + 1] > x_zeros[iii] for iii in range(len(x_zeros[:-1])))
+            ):
+                orientation = "v"
+            else:
+                orientation = "h"
+        elif vertical:
+            orientation = "v"
+        else:
+            orientation = "h"
+        if orientation == "v":
+            self.msg += "    Attempting to draw a vertical bar chart\n"
+            old_heights = [bar_props["y1"] for bar_props in trace]
+            for bar in trace:
+                bar["y0"], bar["y1"] = 0, bar["y1"] - bar["y0"]
+            new_heights = [bar_props["y1"] for bar_props in trace]
+            # check if we're stacked or not...
+            for old, new in zip(old_heights, new_heights):
+                if abs(old - new) > tol:
+                    self.plotly_fig["layout"]["barmode"] = "stack"
+                    self.plotly_fig["layout"]["hovermode"] = "x"
+            x = [bar["x0"] + (bar["x1"] - bar["x0"]) / 2 for bar in trace]
+            y = [bar["y1"] for bar in trace]
+            bar_gap = mpltools.get_bar_gap(
+                [bar["x0"] for bar in trace], [bar["x1"] for bar in trace]
+            )
+            if self.x_is_mpl_date:
+                x = [bar["x0"] for bar in trace]
+                formatter = (
+                    self.current_mpl_ax.get_xaxis()
+                    .get_major_formatter()
+                    .__class__.__name__
+                )
+                x = mpltools.mpl_dates_to_datestrings(x, formatter)
+        else:
+            self.msg += "    Attempting to draw a horizontal bar chart\n"
+            old_rights = [bar_props["x1"] for bar_props in trace]
+            for bar in trace:
+                bar["x0"], bar["x1"] = 0, bar["x1"] - bar["x0"]
+            new_rights = [bar_props["x1"] for bar_props in trace]
+            # check if we're stacked or not...
+            for old, new in zip(old_rights, new_rights):
+                if abs(old - new) > tol:
+                    self.plotly_fig["layout"]["barmode"] = "stack"
+                    self.plotly_fig["layout"]["hovermode"] = "y"
+            x = [bar["x1"] for bar in trace]
+            y = [bar["y0"] + (bar["y1"] - bar["y0"]) / 2 for bar in trace]
+            bar_gap = mpltools.get_bar_gap(
+                [bar["y0"] for bar in trace], [bar["y1"] for bar in trace]
+            )
+        bar = go.Bar(
+            orientation=orientation,
+            x=x,
+            y=y,
+            xaxis="x{0}".format(self.axis_ct),
+            yaxis="y{0}".format(self.axis_ct),
+            opacity=trace[0]["alpha"],  # TODO: get all alphas if array?
+            marker=go.bar.Marker(
+                color=trace[0]["facecolor"],  # TODO: get all
+                line=dict(width=trace[0]["edgewidth"]),
+            ),
+        )  # TODO ditto
+        if len(bar["x"]) > 1:
+            self.msg += "    Heck yeah, I drew that bar chart\n"
+            self.plotly_fig.add_trace(bar),
+            if bar_gap is not None:
+                self.plotly_fig["layout"]["bargap"] = bar_gap
+        else:
+            self.msg += "    Bar chart not drawn\n"
+            warnings.warn(
+                "found box chart data with length <= 1, "
+                "assuming data redundancy, not plotting."
+            )
+
+    def draw_legend_shapes(self, mode, shape, **props):
+        """Create a shape that matches lines or markers in legends.
+
+        Main issue is that path for circles do not render, so we have to use 'circle'
+        instead of 'path'.
+        """
+        for single_mode in mode.split("+"):
+            x = props["data"][0][0]
+            y = props["data"][0][1]
+            if single_mode == "markers" and props.get("markerstyle"):
+                size = shape.pop("size", 6)
+                symbol = shape.pop("symbol")
+                # aligning to "center"
+                x0 = 0
+                y0 = 0
+                x1 = size
+                y1 = size
+                markerpath = props["markerstyle"].get("markerpath")
+                if markerpath is None and symbol != "circle":
+                    self.msg += (
+                        "not sure how to handle this marker without a valid path\n"
+                    )
+                    return
+                # marker path to SVG path conversion
+                path = " ".join(
+                    [f"{a} {t[0]},{t[1]}" for a, t in zip(markerpath[1], markerpath[0])]
+                )
+
+                if symbol == "circle":
+                    # symbols like . and o in matplotlib, use circle
+                    # plotly also maps many other markers to circle, such as 1,8 and p
+                    path = None
+                    shape_type = "circle"
+                    x0 = -size / 2
+                    y0 = size / 2
+                    x1 = size / 2
+                    y1 = size + size / 2
+                else:
+                    # triangles, star etc
+                    shape_type = "path"
+                legend_shape = go.layout.Shape(
+                    type=shape_type,
+                    xref="paper",
+                    yref="paper",
+                    x0=x0,
+                    y0=y0,
+                    x1=x1,
+                    y1=y1,
+                    xsizemode="pixel",
+                    ysizemode="pixel",
+                    xanchor=x,
+                    yanchor=y,
+                    path=path,
+                    **shape,
+                )
+
+            elif single_mode == "lines":
+                mode = "line"
+                x1 = props["data"][1][0]
+                y1 = props["data"][1][1]
+
+                legend_shape = go.layout.Shape(
+                    type=mode,
+                    xref="paper",
+                    yref="paper",
+                    x0=x,
+                    y0=y + 0.02,
+                    x1=x1,
+                    y1=y1 + 0.02,
+                    **shape,
+                )
+            else:
+                self.msg += "not sure how to handle this element\n"
+                return
+            self.plotly_fig.add_shape(legend_shape)
+            self.msg += "    Heck yeah, I drew that shape\n"
+
+    def draw_marked_line(self, **props):
+        """Create a data dict for a line obj.
+
+        This will draw 'lines', 'markers', or 'lines+markers'. For legend elements,
+        this will use layout.shapes, so they can be positioned with paper refs.
+
+        props.keys() -- [
+        'coordinates',  ('data', 'axes', 'figure', or 'display')
+        'data',         (a list of xy pairs)
+        'mplobj',       (the matplotlib.lines.Line2D obj being rendered)
+        'label',        (the name of the Line2D obj being rendered)
+        'linestyle',    (linestyle dict, can be None, see below)
+        'markerstyle',  (markerstyle dict, can be None, see below)
+        ]
+
+        props['linestyle'].keys() -- [
+        'alpha',        (opacity of Line2D obj)
+        'color',        (color of the line if it exists, not the marker)
+        'linewidth',
+        'dasharray',    (code for linestyle, see DASH_MAP in mpltools.py)
+        'zorder',       (viewing precedence when stacked with other objects)
+        ]
+
+        props['markerstyle'].keys() -- [
+        'alpha',        (opacity of Line2D obj)
+        'marker',       (the mpl marker symbol, see SYMBOL_MAP in mpltools.py)
+        'facecolor',    (color of the marker face)
+        'edgecolor',    (color of the marker edge)
+        'edgewidth',    (width of marker edge)
+        'markerpath',   (an SVG path for drawing the specified marker)
+        'zorder',       (viewing precedence when stacked with other objects)
+        ]
+
+        """
+        self.msg += "    Attempting to draw a line "
+        line, marker, shape = {}, {}, {}
+        if props["linestyle"] and props["markerstyle"]:
+            self.msg += "... with both lines+markers\n"
+            mode = "lines+markers"
+        elif props["linestyle"]:
+            self.msg += "... with just lines\n"
+            mode = "lines"
+        elif props["markerstyle"]:
+            self.msg += "... with just markers\n"
+            mode = "markers"
+        if props["linestyle"]:
+            color = mpltools.merge_color_and_opacity(
+                props["linestyle"]["color"], props["linestyle"]["alpha"]
+            )
+
+            if props["coordinates"] == "data":
+                line = go.scatter.Line(
+                    color=color,
+                    width=props["linestyle"]["linewidth"],
+                    dash=mpltools.convert_dash(props["linestyle"]["dasharray"]),
+                )
+            else:
+                shape = dict(
+                    line=dict(
+                        color=color,
+                        width=props["linestyle"]["linewidth"],
+                        dash=mpltools.convert_dash(props["linestyle"]["dasharray"]),
+                    )
+                )
+        if props["markerstyle"]:
+            if props["coordinates"] == "data":
+                marker = go.scatter.Marker(
+                    opacity=props["markerstyle"]["alpha"],
+                    color=props["markerstyle"]["facecolor"],
+                    symbol=mpltools.convert_symbol(props["markerstyle"]["marker"]),
+                    size=props["markerstyle"]["markersize"],
+                    line=dict(
+                        color=props["markerstyle"]["edgecolor"],
+                        width=props["markerstyle"]["edgewidth"],
+                    ),
+                )
+            else:
+                shape = dict(
+                    opacity=props["markerstyle"]["alpha"],
+                    fillcolor=props["markerstyle"]["facecolor"],
+                    symbol=mpltools.convert_symbol(props["markerstyle"]["marker"]),
+                    size=props["markerstyle"]["markersize"],
+                    line=dict(
+                        color=props["markerstyle"]["edgecolor"],
+                        width=props["markerstyle"]["edgewidth"],
+                    ),
+                )
+        if props["coordinates"] == "data":
+            marked_line = go.Scatter(
+                mode=mode,
+                name=(
+                    str(props["label"])
+                    if isinstance(props["label"], str)
+                    else props["label"]
+                ),
+                x=[xy_pair[0] for xy_pair in props["data"]],
+                y=[xy_pair[1] for xy_pair in props["data"]],
+                xaxis="x{0}".format(self.axis_ct),
+                yaxis="y{0}".format(self.axis_ct),
+                line=line,
+                marker=marker,
+            )
+            if self.x_is_mpl_date:
+                formatter = (
+                    self.current_mpl_ax.get_xaxis()
+                    .get_major_formatter()
+                    .__class__.__name__
+                )
+                marked_line["x"] = mpltools.mpl_dates_to_datestrings(
+                    marked_line["x"], formatter
+                )
+            self.plotly_fig.add_trace(marked_line),
+            self.msg += "    Heck yeah, I drew that line\n"
+        elif props["coordinates"] == "axes":
+            # dealing with legend graphical elements
+            self.draw_legend_shapes(mode=mode, shape=shape, **props)
+        else:
+            self.msg += "    Line didn't have 'data' coordinates, " "not drawing\n"
+            warnings.warn(
+                "Bummer! Plotly can currently only draw Line2D "
+                "objects from matplotlib that are in 'data' "
+                "coordinates!"
+            )
+
+    def draw_image(self, **props):
+        """Draw image.
+
+        Not implemented yet!
+
+        """
+        self.msg += "    Attempting to draw image\n"
+        self.msg += "    Not drawing image\n"
+        warnings.warn(
+            "Aw. Snap! You're gonna have to hold off on "
+            "the selfies for now. Plotly can't import "
+            "images from matplotlib yet!"
+        )
+
+    def draw_path_collection(self, **props):
+        """Add a path collection to data list as a scatter plot.
+
+        Current implementation defaults such collections as scatter plots.
+        Matplotlib supports collections that have many of the same parameters
+        in common like color, size, path, etc. However, they needn't all be
+        the same. Plotly does not currently support such functionality and
+        therefore, the style for the first object is taken and used to define
+        the remaining paths in the collection.
+
+        props.keys() -- [
+        'paths',                (structure: [vertices, path_code])
+        'path_coordinates',     ('data', 'axes', 'figure', or 'display')
+        'path_transforms',      (mpl transform, including Affine2D matrix)
+        'offsets',              (offset from axes, helpful if in 'data')
+        'offset_coordinates',   ('data', 'axes', 'figure', or 'display')
+        'offset_order',
+        'styles',               (style dict, see below)
+        'mplobj'                (the collection obj being drawn)
+        ]
+
+        props['styles'].keys() -- [
+        'linewidth',            (one or more linewidths)
+        'facecolor',            (one or more facecolors for path)
+        'edgecolor',            (one or more edgecolors for path)
+        'alpha',                (one or more opacites for path)
+        'zorder',               (precedence when stacked)
+        ]
+
+        """
+        self.msg += "    Attempting to draw a path collection\n"
+        if props["offset_coordinates"] == "data":
+            markerstyle = mpltools.get_markerstyle_from_collection(props)
+            scatter_props = {
+                "coordinates": "data",
+                "data": props["offsets"],
+                "label": None,
+                "markerstyle": markerstyle,
+                "linestyle": None,
+            }
+            self.msg += "    Drawing path collection as markers\n"
+            self.draw_marked_line(**scatter_props)
+        else:
+            self.msg += "    Path collection not linked to 'data', " "not drawing\n"
+            warnings.warn(
+                "Dang! That path collection is out of this "
+                "world. I totally don't know what to do with "
+                "it yet! Plotly can only import path "
+                "collections linked to 'data' coordinates"
+            )
+
+    def draw_path(self, **props):
+        """Draw path, currently only attempts to draw bar charts.
+
+        This function attempts to sort a given path into a collection of
+        horizontal or vertical bar charts. Most of the actual code takes
+        place in functions from mpltools.py.
+
+        props.keys() -- [
+        'data',         (a list of verticies for the path)
+        'coordinates',  ('data', 'axes', 'figure', or 'display')
+        'pathcodes',    (code for the path, structure: ['M', 'L', 'Z', etc.])
+        'style',        (style dict, see below)
+        'mplobj'        (the mpl path object)
+        ]
+
+        props['style'].keys() -- [
+        'alpha',        (opacity of path obj)
+        'edgecolor',
+        'facecolor',
+        'edgewidth',
+        'dasharray',    (style for path's enclosing line)
+        'zorder'        (precedence of obj when stacked)
+        ]
+
+        """
+        self.msg += "    Attempting to draw a path\n"
+        is_bar = mpltools.is_bar(self.current_mpl_ax.containers, **props)
+        if is_bar:
+            self.current_bars += [props]
+        else:
+            self.msg += "    This path isn't a bar, not drawing\n"
+            warnings.warn(
+                "I found a path object that I don't think is part "
+                "of a bar chart. Ignoring."
+            )
+
+    def draw_text(self, **props):
+        """Create an annotation dict for a text obj.
+
+        Currently, plotly uses either 'page' or 'data' to reference
+        annotation locations. These refer to 'display' and 'data',
+        respectively for the 'coordinates' key used in the Exporter.
+        Appropriate measures are taken to transform text locations to
+        reference one of these two options.
+
+        props.keys() -- [
+        'text',         (actual content string, not the text obj)
+        'position',     (an x, y pair, not an mpl Bbox)
+        'coordinates',  ('data', 'axes', 'figure', 'display')
+        'text_type',    ('title', 'xlabel', or 'ylabel')
+        'style',        (style dict, see below)
+        'mplobj'        (actual mpl text object)
+        ]
+
+        props['style'].keys() -- [
+        'alpha',        (opacity of text)
+        'fontsize',     (size in points of text)
+        'color',        (hex color)
+        'halign',       (horizontal alignment, 'left', 'center', or 'right')
+        'valign',       (vertical alignment, 'baseline', 'center', or 'top')
+        'rotation',
+        'zorder',       (precedence of text when stacked with other objs)
+        ]
+
+        """
+        self.msg += "    Attempting to draw an mpl text object\n"
+        if not mpltools.check_corners(props["mplobj"], self.mpl_fig):
+            warnings.warn(
+                "Looks like the annotation(s) you are trying \n"
+                "to draw lies/lay outside the given figure size.\n\n"
+                "Therefore, the resulting Plotly figure may not be \n"
+                "large enough to view the full text. To adjust \n"
+                "the size of the figure, use the 'width' and \n"
+                "'height' keys in the Layout object. Alternatively,\n"
+                "use the Margin object to adjust the figure's margins."
+            )
+        align = props["mplobj"]._multialignment
+        if not align:
+            align = props["style"]["halign"]  # mpl default
+        if "annotations" not in self.plotly_fig["layout"]:
+            self.plotly_fig["layout"]["annotations"] = []
+        if props["text_type"] == "xlabel":
+            self.msg += "      Text object is an xlabel\n"
+            self.draw_xlabel(**props)
+        elif props["text_type"] == "ylabel":
+            self.msg += "      Text object is a ylabel\n"
+            self.draw_ylabel(**props)
+        elif props["text_type"] == "title":
+            self.msg += "      Text object is a title\n"
+            self.draw_title(**props)
+        else:  # just a regular text annotation...
+            self.msg += "      Text object is a normal annotation\n"
+            if props["coordinates"] != "data":
+                self.msg += (
+                    "        Text object isn't linked to 'data' " "coordinates\n"
+                )
+                x_px, y_px = (
+                    props["mplobj"].get_transform().transform(props["position"])
+                )
+                x, y = mpltools.display_to_paper(x_px, y_px, self.plotly_fig["layout"])
+                xref = "paper"
+                yref = "paper"
+                xanchor = props["style"]["halign"]  # no difference here!
+                yanchor = mpltools.convert_va(props["style"]["valign"])
+            else:
+                self.msg += "        Text object is linked to 'data' " "coordinates\n"
+                x, y = props["position"]
+                axis_ct = self.axis_ct
+                xaxis = self.plotly_fig["layout"]["xaxis{0}".format(axis_ct)]
+                yaxis = self.plotly_fig["layout"]["yaxis{0}".format(axis_ct)]
+                if (
+                    xaxis["range"][0] < x < xaxis["range"][1]
+                    and yaxis["range"][0] < y < yaxis["range"][1]
+                ):
+                    xref = "x{0}".format(self.axis_ct)
+                    yref = "y{0}".format(self.axis_ct)
+                else:
+                    self.msg += (
+                        "            Text object is outside "
+                        "plotting area, making 'paper' reference.\n"
+                    )
+                    x_px, y_px = (
+                        props["mplobj"].get_transform().transform(props["position"])
+                    )
+                    x, y = mpltools.display_to_paper(
+                        x_px, y_px, self.plotly_fig["layout"]
+                    )
+                    xref = "paper"
+                    yref = "paper"
+                xanchor = props["style"]["halign"]  # no difference here!
+                yanchor = mpltools.convert_va(props["style"]["valign"])
+            annotation = go.layout.Annotation(
+                text=(
+                    str(props["text"])
+                    if isinstance(props["text"], str)
+                    else props["text"]
+                ),
+                opacity=props["style"]["alpha"],
+                x=x,
+                y=y,
+                xref=xref,
+                yref=yref,
+                align=align,
+                xanchor=xanchor,
+                yanchor=yanchor,
+                showarrow=False,  # change this later?
+                font=go.layout.annotation.Font(
+                    color=props["style"]["color"], size=props["style"]["fontsize"]
+                ),
+            )
+            self.plotly_fig["layout"]["annotations"] += (annotation,)
+            self.msg += "    Heck, yeah I drew that annotation\n"
+
+    def draw_title(self, **props):
+        """Add a title to the current subplot in layout dictionary.
+
+        If there exists more than a single plot in the figure, titles revert
+        to 'page'-referenced annotations.
+
+        props.keys() -- [
+        'text',         (actual content string, not the text obj)
+        'position',     (an x, y pair, not an mpl Bbox)
+        'coordinates',  ('data', 'axes', 'figure', 'display')
+        'text_type',    ('title', 'xlabel', or 'ylabel')
+        'style',        (style dict, see below)
+        'mplobj'        (actual mpl text object)
+        ]
+
+        props['style'].keys() -- [
+        'alpha',        (opacity of text)
+        'fontsize',     (size in points of text)
+        'color',        (hex color)
+        'halign',       (horizontal alignment, 'left', 'center', or 'right')
+        'valign',       (vertical alignment, 'baseline', 'center', or 'top')
+        'rotation',
+        'zorder',       (precedence of text when stacked with other objs)
+        ]
+
+        """
+        self.msg += "        Attempting to draw a title\n"
+        if len(self.mpl_fig.axes) > 1:
+            self.msg += (
+                "          More than one subplot, adding title as " "annotation\n"
+            )
+            x_px, y_px = props["mplobj"].get_transform().transform(props["position"])
+            x, y = mpltools.display_to_paper(x_px, y_px, self.plotly_fig["layout"])
+            annotation = go.layout.Annotation(
+                text=props["text"],
+                font=go.layout.annotation.Font(
+                    color=props["style"]["color"], size=props["style"]["fontsize"]
+                ),
+                xref="paper",
+                yref="paper",
+                x=x,
+                y=y,
+                xanchor="center",
+                yanchor="bottom",
+                showarrow=False,  # no arrow for a title!
+            )
+            self.plotly_fig["layout"]["annotations"] += (annotation,)
+        else:
+            self.msg += (
+                "          Only one subplot found, adding as a " "plotly title\n"
+            )
+            self.plotly_fig["layout"]["title"] = props["text"]
+            titlefont = dict(
+                size=props["style"]["fontsize"], color=props["style"]["color"]
+            )
+            self.plotly_fig["layout"]["titlefont"] = titlefont
+
+    def draw_xlabel(self, **props):
+        """Add an xaxis label to the current subplot in layout dictionary.
+
+        props.keys() -- [
+        'text',         (actual content string, not the text obj)
+        'position',     (an x, y pair, not an mpl Bbox)
+        'coordinates',  ('data', 'axes', 'figure', 'display')
+        'text_type',    ('title', 'xlabel', or 'ylabel')
+        'style',        (style dict, see below)
+        'mplobj'        (actual mpl text object)
+        ]
+
+        props['style'].keys() -- [
+        'alpha',        (opacity of text)
+        'fontsize',     (size in points of text)
+        'color',        (hex color)
+        'halign',       (horizontal alignment, 'left', 'center', or 'right')
+        'valign',       (vertical alignment, 'baseline', 'center', or 'top')
+        'rotation',
+        'zorder',       (precedence of text when stacked with other objs)
+        ]
+
+        """
+        self.msg += "        Adding xlabel\n"
+        axis_key = "xaxis{0}".format(self.axis_ct)
+        self.plotly_fig["layout"][axis_key]["title"] = str(props["text"])
+        titlefont = dict(size=props["style"]["fontsize"], color=props["style"]["color"])
+        self.plotly_fig["layout"][axis_key]["titlefont"] = titlefont
+
+    def draw_ylabel(self, **props):
+        """Add a yaxis label to the current subplot in layout dictionary.
+
+        props.keys() -- [
+        'text',         (actual content string, not the text obj)
+        'position',     (an x, y pair, not an mpl Bbox)
+        'coordinates',  ('data', 'axes', 'figure', 'display')
+        'text_type',    ('title', 'xlabel', or 'ylabel')
+        'style',        (style dict, see below)
+        'mplobj'        (actual mpl text object)
+        ]
+
+        props['style'].keys() -- [
+        'alpha',        (opacity of text)
+        'fontsize',     (size in points of text)
+        'color',        (hex color)
+        'halign',       (horizontal alignment, 'left', 'center', or 'right')
+        'valign',       (vertical alignment, 'baseline', 'center', or 'top')
+        'rotation',
+        'zorder',       (precedence of text when stacked with other objs)
+        ]
+
+        """
+        self.msg += "        Adding ylabel\n"
+        axis_key = "yaxis{0}".format(self.axis_ct)
+        self.plotly_fig["layout"][axis_key]["title"] = props["text"]
+        titlefont = dict(size=props["style"]["fontsize"], color=props["style"]["color"])
+        self.plotly_fig["layout"][axis_key]["titlefont"] = titlefont
+
+    def resize(self):
+        """Revert figure layout to allow plotly to resize.
+
+        By default, PlotlyRenderer tries its hardest to precisely mimic an
+        mpl figure. However, plotly is pretty good with aesthetics. By
+        running PlotlyRenderer.resize(), layout parameters are deleted. This
+        lets plotly choose them instead of mpl.
+
+        """
+        self.msg += "Resizing figure, deleting keys from layout\n"
+        for key in ["width", "height", "autosize", "margin"]:
+            try:
+                del self.plotly_fig["layout"][key]
+            except (KeyError, AttributeError):
+                pass
+
+    def strip_style(self):
+        self.msg += "Stripping mpl style is no longer supported\n"