from __future__ import absolute_import, print_function

import logging
logger = logging.getLogger(__name__)

from six import string_types

from ..core.properties import Any, Auto, Either, Enum, Int, Seq, Instance, String
from ..core.enums import HorizontalLocation, VerticalLocation
from ..models import ColumnDataSource, Plot, Title, Tool, GraphRenderer
from ..models import glyphs, markers
from ..models.tools import Drag, Inspection, Scroll, Tap
from ..util.options import Options
from ..util.string import format_docstring
from ..transform import linear_cmap
from .helpers import (
    _get_range, _get_scale, _process_axis_and_grid, _process_tools_arg,
    _glyph_function, _process_active_tools, _stack, _graph)

DEFAULT_TOOLS = "pan,wheel_zoom,box_zoom,save,reset,help"

# This class itself is intentionally undocumented (it is used to generate
# documentation elsewhere)
class FigureOptions(Options):

    tools = Either(String, Seq(Either(String, Instance(Tool))), default=DEFAULT_TOOLS, help="""
    Tools the plot should start with.
    """)

    x_range = Any(help="""
    Customize the x-range of the plot.
    """)

    y_range = Any(help="""
    Customize the x-range of the plot.
    """)

    x_minor_ticks = Either(Auto, Int, default="auto", help="""
    Number of minor ticks between adjacent x-axis major ticks.
    """)

    y_minor_ticks = Either(Auto, Int, default="auto", help="""
    Number of minor ticks between adjacent y-axis major ticks.
    """)

    x_axis_location = Enum(VerticalLocation, default="below", help="""
    Where the x-axis should be located.
    """)

    y_axis_location = Enum(HorizontalLocation, default="left", help="""
    Where the y-axis should be located.
    """)

    x_axis_label = String(default="", help="""
    A label for the x-axis.
    """)

    y_axis_label = String(default="", help="""
    A label for the y-axis.
    """)

    active_drag = Either(Auto, String, Instance(Drag), default="auto", help="""
    Which drag tool should initially be active.
    """)

    active_inspect = Either(Auto, String, Instance(Inspection), Seq(Instance(Inspection)), default="auto", help="""
    Which drag tool should initially be active.
    """)

    active_scroll = Either(Auto, String, Instance(Scroll), default="auto", help="""
    Which scroll tool should initially be active.
    """)

    active_tap = Either(Auto, String, Instance(Tap), default="auto", help="""
    Which tap tool should initially be active.
    """)

    x_axis_type = Either(Auto, Enum("linear", "log", "datetime", "mercator"), default="auto", help="""
    The type of the x-axis.
    """)

    y_axis_type = Either(Auto, Enum("linear", "log", "datetime", "mercator"), default="auto", help="""
    The type of the y-axis.
    """)

class Figure(Plot):
    ''' A subclass of :class:`~bokeh.models.plots.Plot` that simplifies plot
    creation with default axes, grids, tools, etc.

    Figure objects have many glyph methods that can be used to draw
    vectorized graphical glyphs:

    .. hlist::
        :columns: 3

{glyph_methods}

    There are also two specialized methods for stacking bars:

    * :func:`~bokeh.plotting.figure.Figure.hbar_stack`
    * :func:`~bokeh.plotting.figure.Figure.vbar_stack`

    And one specialized method for making simple hexbin plots:

    * :func:`~bokeh.plotting.figure.Figure.hexbin`

    In addition to all the Bokeh model property attributes documented below,
    the ``Figure`` initializer also accepts the following options, which can
    help simplify configuration:

    .. bokeh-options:: FigureOptions
        :module: bokeh.plotting.figure

    '''

    __subtype__ = "Figure"
    __view_model__ = "Plot"

    def __init__(self, *arg, **kw):

        if 'plot_width' in kw and 'width' in kw:
            raise ValueError("Figure called with both 'plot_width' and 'width' supplied, supply only one")
        if 'plot_height' in kw and 'height' in kw:
            raise ValueError("Figure called with both 'plot_height' and 'height' supplied, supply only one")
        if 'height' in kw:
            kw['plot_height'] = kw.pop('height')
        if 'width' in kw:
            kw['plot_width'] = kw.pop('width')

        opts = FigureOptions(kw)

        title = kw.get("title", None)
        if isinstance(title, string_types):
            kw['title'] = Title(text=title)

        super(Figure, self).__init__(*arg, **kw)

        self.x_range = _get_range(opts.x_range)
        self.y_range = _get_range(opts.y_range)

        self.x_scale = _get_scale(self.x_range, opts.x_axis_type)
        self.y_scale = _get_scale(self.y_range, opts.y_axis_type)

        _process_axis_and_grid(self, opts.x_axis_type, opts.x_axis_location, opts.x_minor_ticks, opts.x_axis_label, self.x_range, 0)
        _process_axis_and_grid(self, opts.y_axis_type, opts.y_axis_location, opts.y_minor_ticks, opts.y_axis_label, self.y_range, 1)

        tool_objs, tool_map = _process_tools_arg(self, opts.tools)
        self.add_tools(*tool_objs)
        _process_active_tools(self.toolbar, tool_map, opts.active_drag, opts.active_inspect, opts.active_scroll, opts.active_tap)

    annular_wedge = _glyph_function(glyphs.AnnularWedge)

    annulus = _glyph_function(glyphs.Annulus, """
Examples:

        .. bokeh-plot::
            :source-position: above

            from bokeh.plotting import figure, output_file, show

            plot = figure(plot_width=300, plot_height=300)
            plot.annulus(x=[1, 2, 3], y=[1, 2, 3], color="#7FC97F",
                         inner_radius=0.2, outer_radius=0.5)

            show(plot)

    """)

    arc = _glyph_function(glyphs.Arc)

    asterisk = _glyph_function(markers.Asterisk, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.asterisk(x=[1,2,3], y=[1,2,3], size=20, color="#F0027F")

        show(plot)

""")

    bezier = _glyph_function(glyphs.Bezier)

    circle = _glyph_function(markers.Circle, """
.. note::
    Only one of ``size`` or ``radius`` should be provided. Note that ``radius``
    defaults to data units.

Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.circle(x=[1, 2, 3], y=[1, 2, 3], size=20)

        show(plot)

""")

    circle_cross = _glyph_function(markers.CircleCross, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.circle_cross(x=[1,2,3], y=[4,5,6], size=20,
                          color="#FB8072", fill_alpha=0.2, line_width=2)

        show(plot)

""")

    circle_x = _glyph_function(markers.CircleX, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.circle_x(x=[1, 2, 3], y=[1, 2, 3], size=20,
                     color="#DD1C77", fill_alpha=0.2)

        show(plot)

""")

    cross = _glyph_function(markers.Cross, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.cross(x=[1, 2, 3], y=[1, 2, 3], size=20,
                   color="#E6550D", line_width=2)

        show(plot)

""")

    diamond = _glyph_function(markers.Diamond, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.diamond(x=[1, 2, 3], y=[1, 2, 3], size=20,
                    color="#1C9099", line_width=2)

        show(plot)

""")

    diamond_cross = _glyph_function(markers.DiamondCross, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.diamond_cross(x=[1, 2, 3], y=[1, 2, 3], size=20,
                           color="#386CB0", fill_color=None, line_width=2)

        show(plot)

""")

    hbar = _glyph_function(glyphs.HBar, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.hbar(y=[1, 2, 3], height=0.5, left=0, right=[1,2,3], color="#CAB2D6")

        show(plot)
""")

    ellipse = _glyph_function(glyphs.Ellipse, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.ellipse(x=[1, 2, 3], y=[1, 2, 3], width=30, height=20,
                     color="#386CB0", fill_color=None, line_width=2)

        show(plot)

""")

    hex = _glyph_function(markers.Hex, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.hex(x=[1, 2, 3], y=[1, 2, 3], size=[10,20,30], color="#74ADD1")

        show(plot)

""")

    hex_tile = _glyph_function(glyphs.HexTile, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300, match_aspect=True)
        plot.hex_tile(r=[0, 0, 1], q=[1, 2, 2], fill_color="#74ADD1")

        show(plot)

""")

    image = _glyph_function(glyphs.Image, """
.. note::
    If both ``palette`` and ``color_mapper`` are passed, a ``ValueError``
    exception will be raised. If neither is passed, then the ``Greys9``
    palette will be used as a default.

""")

    image_rgba = _glyph_function(glyphs.ImageRGBA, """
.. note::
    The ``image_rgba`` method accepts images as a two-dimensional array of RGBA
    values (encoded as 32-bit integers).

""")

    image_url = _glyph_function(glyphs.ImageURL)

    inverted_triangle = _glyph_function(markers.InvertedTriangle, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.inverted_triangle(x=[1, 2, 3], y=[1, 2, 3], size=20, color="#DE2D26")

        show(plot)

""")

    line = _glyph_function(glyphs.Line, """
Examples:

    .. bokeh-plot::
       :source-position: above

       from bokeh.plotting import figure, output_file, show

       p = figure(title="line", plot_width=300, plot_height=300)
       p.line(x=[1, 2, 3, 4, 5], y=[6, 7, 2, 4, 5])

       show(p)

""")

    multi_line = _glyph_function(glyphs.MultiLine, """
.. note::
    For this glyph, the data is not simply an array of scalars, it is an
    "array of arrays".

Examples:

    .. bokeh-plot::
       :source-position: above

       from bokeh.plotting import figure, output_file, show

       p = figure(plot_width=300, plot_height=300)
       p.multi_line(xs=[[1, 2, 3], [2, 3, 4]], ys=[[6, 7, 2], [4, 5, 7]],
                    color=['red','green'])

       show(p)

""")

    oval = _glyph_function(glyphs.Oval, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.oval(x=[1, 2, 3], y=[1, 2, 3], width=0.2, height=0.4,
                  angle=-0.7, color="#1D91C0")

        show(plot)

""")

    patch = _glyph_function(glyphs.Patch, """
Examples:

    .. bokeh-plot::
       :source-position: above

       from bokeh.plotting import figure, output_file, show

       p = figure(plot_width=300, plot_height=300)
       p.patch(x=[1, 2, 3, 2], y=[6, 7, 2, 2], color="#99d8c9")

       show(p)

""")

    patches = _glyph_function(glyphs.Patches, """
.. note::
    For this glyph, the data is not simply an array of scalars, it is an
    "array of arrays".

Examples:

    .. bokeh-plot::
       :source-position: above

       from bokeh.plotting import figure, output_file, show

       p = figure(plot_width=300, plot_height=300)
       p.patches(xs=[[1,2,3],[4,5,6,5]], ys=[[1,2,1],[4,5,5,4]],
                 color=["#43a2ca", "#a8ddb5"])

       show(p)

""")

    quad = _glyph_function(glyphs.Quad, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.quad(top=[2, 3, 4], bottom=[1, 2, 3], left=[1, 2, 3],
                  right=[1.2, 2.5, 3.7], color="#B3DE69")

        show(plot)

""")

    quadratic = _glyph_function(glyphs.Quadratic)

    ray = _glyph_function(glyphs.Ray, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.ray(x=[1, 2, 3], y=[1, 2, 3], length=45, angle=-0.7, color="#FB8072",
                 line_width=2)

        show(plot)

""")

    rect = _glyph_function(glyphs.Rect, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.rect(x=[1, 2, 3], y=[1, 2, 3], width=10, height=20, color="#CAB2D6",
                  width_units="screen", height_units="screen")

        show(plot)

""")

    step = _glyph_function(glyphs.Step, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.step(x=[1, 2, 3, 4, 5], y=[1, 2, 3, 2, 5], color="#FB8072")

        show(plot)

""")


    segment = _glyph_function(glyphs.Segment, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.segment(x0=[1, 2, 3], y0=[1, 2, 3], x1=[1, 2, 3],
                     y1=[1.2, 2.5, 3.7], color="#F4A582",
                     line_width=3)

        show(plot)

""")

    square = _glyph_function(markers.Square, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.square(x=[1, 2, 3], y=[1, 2, 3], size=[10,20,30], color="#74ADD1")

        show(plot)

""")

    square_cross = _glyph_function(markers.SquareCross, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.square_cross(x=[1, 2, 3], y=[1, 2, 3], size=[10,20,25],
                          color="#7FC97F",fill_color=None, line_width=2)

        show(plot)

""")

    square_x = _glyph_function(markers.SquareX, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.square_x(x=[1, 2, 3], y=[1, 2, 3], size=[10,20,25],
                      color="#FDAE6B",fill_color=None, line_width=2)

        show(plot)

""")

    text = _glyph_function(glyphs.Text, """
.. note::
    The location and angle of the text relative to the ``x``, ``y`` coordinates
    is indicated by the alignment and baseline text properties.

Returns:
    GlyphRenderer

""")

    triangle = _glyph_function(markers.Triangle, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.triangle(x=[1, 2, 3], y=[1, 2, 3], size=[10,20,25],
                      color="#99D594", line_width=2)

        show(plot)

""")

    vbar = _glyph_function(glyphs.VBar, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.vbar(x=[1, 2, 3], width=0.5, bottom=0, top=[1,2,3], color="#CAB2D6")

        show(plot)

""")

    wedge = _glyph_function(glyphs.Wedge, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.wedge(x=[1, 2, 3], y=[1, 2, 3], radius=15, start_angle=0.6,
                   end_angle=4.1, radius_units="screen", color="#2b8cbe")

        show(plot)

""")

    x = _glyph_function(markers.X, """
Examples:

    .. bokeh-plot::
        :source-position: above

        from bokeh.plotting import figure, output_file, show

        plot = figure(plot_width=300, plot_height=300)
        plot.x(x=[1, 2, 3], y=[1, 2, 3], size=[10, 20, 25], color="#fa9fb5")

        show(plot)

""")

    # -------------------------------------------------------------------------

    def scatter(self, *args, **kwargs):
        """ Creates a scatter plot of the given x and y items.

        Args:
            x (str or seq[float]) : values or field names of center x coordinates
            y (str or seq[float]) : values or field names of center y coordinates
            size (str or list[float]) : values or field names of sizes in screen units
            marker (str, optional): a valid marker_type, defaults to "circle"
            color (color value, optional): shorthand to set both fill and line color
            source (:class:`~bokeh.models.sources.ColumnDataSource`) : a user-supplied data source.
                An attempt will be made to convert the object to :class:`~bokeh.models.sources.ColumnDataSource`
                if needed. If none is supplied, one is created for the user automatically.
            **kwargs: :ref:`userguide_styling_line_properties` and :ref:`userguide_styling_fill_properties`

        Examples:

            >>> p.scatter([1,2,3],[4,5,6], fill_color="red")
            >>> p.scatter("data1", "data2", source=data_source, ...)

        """
        markertype = kwargs.pop("marker", "circle")

        if markertype not in _marker_types:
            raise ValueError("Invalid marker type '%s'. Use markers() to see a list of valid marker types." % markertype)

        # TODO (bev) make better when plotting.scatter is removed
        conversions = {
            "*": "asterisk",
            "+": "cross",
            "o": "circle",
            "ox": "circle_x",
            "o+": "circle_cross"
        }
        if markertype in conversions:
            markertype = conversions[markertype]

        return getattr(self, markertype)(*args, **kwargs)

    def hexbin(self, x, y, size, orientation="pointytop", palette="Viridis256", line_color=None, fill_color=None, aspect_scale=1, **kwargs):
        ''' Perform a simple equal-weight hexagonal binning.

        A :class:`~bokeh.models.glyphs.HexTile` glyph will be added to display
        the binning. The :class:`~bokeh.models.sources.ColumnDataSource` for
        the glyph will have columns ``q``, ``r``, and ``count``, where ``q``
        and ``r`` are `axial coordinates`_ for a tile, and ``count`` is the
        associated bin count.

        It is often useful to set ``match_aspect=True`` on the associated plot,
        so that hexagonal tiles are all regular (i.e. not "stretched") in
        screen space.

        For more sophisicated use-cases, e.g. weighted binning or individually
        scaling hex tiles, use :func:`hex_tile` directly, or consider a higher
        level library such as HoloViews.

        Args:
            x (array[float]) :
                A NumPy array of x-coordinates to bin into haxagonal tiles.

            y (array[float]) :
                A NumPy array of y-coordinates to bin into haxagonal tiles

            size (float) :
                The size of the hexagonal tiling to use. The size is defined as
                distance from the center of a hexagon to a corner.

                In case the apsect scaling is not 1-1, then specifically `size`
                is the distance from the center to the "top" corner with the
                `"pointytop"` orientation, and the distance from the center to
                a "side" corner with the "flattop" orientation.

            orientation ("pointytop" or "flattop", optional) :
                Whether the hexagonal tiles should be oriented with a pointed
                corner on top, or a flat side on top. (default: "pointytop")

            palette (str or seq[color], optional) :
                A palette (or palette name) to use to colormap the bins according
                to count. (default: 'Viridis256')

                If ``fill_color`` is supplied, it overrides this value.

            line_color (color, optional) :
                The outline color for hex tiles, or None (default: None)

            fill_color (color, optional) :
                An optional fill color for hex tiles, or None. If None, then
                the ``palette`` will be used to color map the tiles by
                count. (default: None)

            aspect_scale (float) :
                Match a plot's aspect ratio scaling.

                When working with a plot with ``aspect_scale != 1``, this
                parameter can be set to match the plot, in order to draw
                regular hexagons (insted of "stretched" ones).

                This is roughly equivalent to binning in "screen space", and
                it may be better to use axis-aligned rectangular bins when
                plot aspect scales are not one.

        Any additional keyword arguments are passed to :func:`hex_tile`.

        Returns
            (Glyphrender, DataFrame)
                A tuple with the ``HexTile`` renderer generated to display the
                binning, and a Pandas DataFrame with columns ``q``, ``r``,
                and ``count``, where ``q`` and ``r`` are `axial coordinates`_
                for a tile, and ``count`` is the associated bin count.

        Example:

            .. bokeh-plot::
                :source-position: above

                import numpy as np
                from bokeh.models import HoverTool
                from bokeh.plotting import figure, show

                x = 2 + 2*np.random.standard_normal(500)
                y = 2 + 2*np.random.standard_normal(500)

                p = figure(match_aspect=True, tools="wheel_zoom,reset")
                p.background_fill_color = '#440154'
                p.grid.visible = False

                p.hexbin(x, y, size=0.5, hover_color="pink", hover_alpha=0.8)

                hover = HoverTool(tooltips=[("count", "@c"), ("(q,r)", "(@q, @r)")])
                p.add_tools(hover)

                show(p)

        .. _axial coordinates: https://www.redblobgames.com/grids/hexagons/#coordinates-axial

        '''
        from ..util.hex import hexbin

        bins = hexbin(x, y, size, orientation, aspect_scale=aspect_scale)

        if fill_color is None:
            fill_color = linear_cmap('c', palette, 0, max(bins.counts))

        source = ColumnDataSource(data=dict(q=bins.q, r=bins.r, c=bins.counts))

        r = self.hex_tile(q="q", r="r", size=size, orientation=orientation, aspect_scale=aspect_scale,
                          source=source, line_color=line_color, fill_color=fill_color, **kwargs)

        return (r, bins)

    def hbar_stack(self, stackers, **kw):
        ''' Generate multiple ``HBar`` renderers for levels stacked left to right.

        Args:
            stackers (seq[str]) : a list of data source field names to stack
                successively for ``left`` and ``right`` bar coordinates.

        Any additional keyword arguments are passed to each call to ``hbar``.
        If a keyword value is a list or tuple, then each call will get one
        value from the sequence.

        Returns:
            list[GlyphRenderer]

        Examples:

            Assuming a ``ColumnDataSource`` named ``source`` with columns
            *2106* and *2017*, then the following call to ``hbar_stack`` will
            will create two ``HBar`` renderers that stack:

            .. code-block:: python

                p.hbar_stack(['2016', '2017'], x=10, width=0.9, color=['blue', 'red'], source=source)

            This is equivalent to the following two separate calls:

            .. code-block:: python

                p.hbar(bottom=stack(),       top=stack('2016'),         x=10, width=0.9, color='blue', source=source)
                p.hbar(bottom=stack('2016'), top=stack('2016', '2017'), x=10, width=0.9, color='red', source=source)

        '''
        result = []
        for kw in _stack(stackers, "left", "right", **kw):
            result.append(self.hbar(**kw))
        return result

    def vbar_stack(self, stackers, **kw):
        ''' Generate multiple ``VBar`` renderers for levels stacked bottom
        to top.

        Args:
            stackers (seq[str]) : a list of data source field names to stack
                successively for ``left`` and ``right`` bar coordinates.

        Any additional keyword arguments are passed to each call to ``vbar``.
        If a keyword value is a list or tuple, then each call will get one
        value from the sequence.

        Returns:
            list[GlyphRenderer]

        Examples:

            Assuming a ``ColumnDataSource`` named ``source`` with columns
            *2016* and *2017*, then the following call to ``vbar_stack`` will
            will create two ``VBar`` renderers that stack:

            .. code-block:: python

                p.vbar_stack(['2016', '2017'], x=10, width=0.9, color=['blue', 'red'], source=source)

            This is equivalent to the following two separate calls:

            .. code-block:: python

                p.vbar(bottom=stack(),       top=stack('2016'),         x=10, width=0.9, color='blue', source=source)
                p.vbar(bottom=stack('2016'), top=stack('2016', '2017'), x=10, width=0.9, color='red', source=source)


        '''
        result = []
        for kw in _stack(stackers, "bottom", "top", **kw):
            result.append(self.vbar(**kw))
        return result

    def graph(self, node_source, edge_source, layout_provider, **kwargs):
        ''' Creates a network graph using the given node, edge and layout provider.

        Args:
            node_source (:class:`~bokeh.models.sources.ColumnDataSource`) : a user-supplied data source
                for the graph nodes. An attempt will be made to convert the object to
                :class:`~bokeh.models.sources.ColumnDataSource` if needed. If none is supplied, one is created
                for the user automatically.
            edge_source (:class:`~bokeh.models.sources.ColumnDataSource`) : a user-supplied data source
                for the graph edges. An attempt will be made to convert the object to
                :class:`~bokeh.models.sources.ColumnDataSource` if needed. If none is supplied, one is created
                for the user automatically.
            layout_provider (:class:`~bokeh.models.graphs.LayoutProvider`) : a LayoutProvider instance to
                provide the graph coordinates in Cartesian space.
            **kwargs: :ref:`userguide_styling_line_properties` and :ref:`userguide_styling_fill_properties`
        '''
        kw = _graph(node_source, edge_source, **kwargs)
        graph_renderer = GraphRenderer(layout_provider=layout_provider, **kw)
        self.renderers.append(graph_renderer)
        return graph_renderer

def figure(**kwargs):
    ''' Create a new :class:`~bokeh.plotting.figure.Figure` for plotting.

    Figure objects have many glyph methods that can be used to draw
    vectorized graphical glyphs:

    .. hlist::
        :columns: 3

{glyph_methods}

    There are also two specialized methods for stacking bars:

    * :func:`~bokeh.plotting.figure.Figure.hbar_stack`
    * :func:`~bokeh.plotting.figure.Figure.vbar_stack`

    And one specialized method for making simple hexbin plots:

    * :func:`~bokeh.plotting.figure.Figure.hexbin`

    In addition to the standard :class:`~bokeh.plotting.figure.Figure`
    property values (e.g. ``plot_width`` or ``sizing_mode``) the following
    additional options can be passed as well:

    .. bokeh-options:: FigureOptions
        :module: bokeh.plotting.figure

    Returns:
       Figure

    '''

    return Figure(**kwargs)


_marker_types = [
    "asterisk",
    "circle",
    "circle_cross",
    "circle_x",
    "cross",
    "diamond",
    "diamond_cross",
    "hex",
    "inverted_triangle",
    "square",
    "square_x",
    "square_cross",
    "triangle",
    "x",
    "*",
    "+",
    "o",
    "ox",
    "o+",
]

def markers():
    """ Prints a list of valid marker types for scatter()

    Returns:
        None
    """
    print("Available markers: \n - " + "\n - ".join(_marker_types))

_color_fields = set(["color", "fill_color", "line_color"])
_alpha_fields = set(["alpha", "fill_alpha", "line_alpha"])

_gms = sorted(x for x in dir(Figure) if getattr(getattr(Figure, x), 'glyph_method', False))
_gms = "\n".join("        * :func:`~bokeh.plotting.figure.Figure.%s`" % x for x in _gms)
Figure.__doc__ = format_docstring(Figure.__doc__, glyph_methods=_gms)
figure.__doc__ = format_docstring(figure.__doc__, glyph_methods=_gms)
