#----------------------------------------------------------------------------- # Copyright (c) 2012 - 2019, Anaconda, Inc., and Bokeh Contributors. # All rights reserved. # # The full license is in the file LICENSE.txt, distributed with this software. #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Boilerplate #----------------------------------------------------------------------------- from __future__ import absolute_import, division, print_function, unicode_literals import logging log = logging.getLogger(__name__) #----------------------------------------------------------------------------- # Imports #----------------------------------------------------------------------------- # Standard library imports # External imports from six import string_types # Bokeh imports from ..core.properties import Any, Auto, Either, Enum, Int, List, Seq, Instance, String, Tuple from ..core.enums import HorizontalLocation, MarkerType, VerticalLocation from ..models import ColumnDataSource, Plot, Title, Tool, GraphRenderer from ..models import glyphs as _glyphs from ..models import markers as _markers from ..models.tools import Drag, Inspection, Scroll, Tap from ..util.options import Options from ..transform import linear_cmap from .helpers import ( _get_range, _get_scale, _process_axis_and_grid, _process_tools_arg, _glyph_function, _process_active_tools, _single_stack, _double_stack, _graph, ) #----------------------------------------------------------------------------- # Globals and constants #----------------------------------------------------------------------------- DEFAULT_TOOLS = "pan,wheel_zoom,box_zoom,save,reset,help" __all__ = ( 'Figure', 'figure', 'FigureOptions', 'markers' ) #----------------------------------------------------------------------------- # General API #----------------------------------------------------------------------------- [docs]class Figure(Plot): ''' Create a new Figure for plotting. 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 * :func:`~bokeh.plotting.figure.Figure.annular_wedge` * :func:`~bokeh.plotting.figure.Figure.annulus` * :func:`~bokeh.plotting.figure.Figure.arc` * :func:`~bokeh.plotting.figure.Figure.asterisk` * :func:`~bokeh.plotting.figure.Figure.bezier` * :func:`~bokeh.plotting.figure.Figure.circle` * :func:`~bokeh.plotting.figure.Figure.circle_cross` * :func:`~bokeh.plotting.figure.Figure.circle_x` * :func:`~bokeh.plotting.figure.Figure.cross` * :func:`~bokeh.plotting.figure.Figure.dash` * :func:`~bokeh.plotting.figure.Figure.diamond` * :func:`~bokeh.plotting.figure.Figure.diamond_cross` * :func:`~bokeh.plotting.figure.Figure.ellipse` * :func:`~bokeh.plotting.figure.Figure.harea` * :func:`~bokeh.plotting.figure.Figure.hbar` * :func:`~bokeh.plotting.figure.Figure.hex` * :func:`~bokeh.plotting.figure.Figure.hex_tile` * :func:`~bokeh.plotting.figure.Figure.image` * :func:`~bokeh.plotting.figure.Figure.image_rgba` * :func:`~bokeh.plotting.figure.Figure.image_url` * :func:`~bokeh.plotting.figure.Figure.inverted_triangle` * :func:`~bokeh.plotting.figure.Figure.line` * :func:`~bokeh.plotting.figure.Figure.multi_line` * :func:`~bokeh.plotting.figure.Figure.multi_polygons` * :func:`~bokeh.plotting.figure.Figure.oval` * :func:`~bokeh.plotting.figure.Figure.patch` * :func:`~bokeh.plotting.figure.Figure.patches` * :func:`~bokeh.plotting.figure.Figure.quad` * :func:`~bokeh.plotting.figure.Figure.quadratic` * :func:`~bokeh.plotting.figure.Figure.ray` * :func:`~bokeh.plotting.figure.Figure.rect` * :func:`~bokeh.plotting.figure.Figure.segment` * :func:`~bokeh.plotting.figure.Figure.square` * :func:`~bokeh.plotting.figure.Figure.square_cross` * :func:`~bokeh.plotting.figure.Figure.square_x` * :func:`~bokeh.plotting.figure.Figure.step` * :func:`~bokeh.plotting.figure.Figure.text` * :func:`~bokeh.plotting.figure.Figure.triangle` * :func:`~bokeh.plotting.figure.Figure.varea` * :func:`~bokeh.plotting.figure.Figure.vbar` * :func:`~bokeh.plotting.figure.Figure.wedge` * :func:`~bokeh.plotting.figure.Figure.x` There is a scatter function that can be parameterized by marker type: * :func:`~bokeh.plotting.figure.Figure.scatter` There are also specialized methods for stacking bars: * bars: :func:`~bokeh.plotting.figure.Figure.hbar_stack`, :func:`~bokeh.plotting.figure.Figure.vbar_stack` * lines: :func:`~bokeh.plotting.figure.Figure.hline_stack`, :func:`~bokeh.plotting.figure.Figure.vline_stack` * areas: :func:`~bokeh.plotting.figure.Figure.harea_stack`, :func:`~bokeh.plotting.figure.Figure.varea_stack` As well as one specialized method for making simple hexbin plots: * :func:`~bokeh.plotting.figure.Figure.hexbin` In addition to all the ``Figure`` property attributes, the following options are also accepted: .. 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, opts.tooltips) 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) """) dash = _glyph_function(_markers.Dash, """ Examples: .. bokeh-plot:: :source-position: above from bokeh.plotting import figure, output_file, show plot = figure(plot_width=300, plot_height=300) plot.dash(x=[1, 2, 3], y=[1, 2, 3], size=[10,20,25], color="#99D594", 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) """) harea = _glyph_function(_glyphs.HArea, """ Examples: .. bokeh-plot:: :source-position: above from bokeh.plotting import figure, output_file, show plot = figure(plot_width=300, plot_height=300) plot.harea(x1=[0, 0, 0], x2=[1, 4, 2], y=[1, 2, 3], fill_color="#99D594") 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) """) multi_polygons = _glyph_function(_glyphs.MultiPolygons, """ .. note:: For this glyph, the data is not simply an array of scalars, it is a nested array. Examples: .. bokeh-plot:: :source-position: above from bokeh.plotting import figure, output_file, show p = figure(plot_width=300, plot_height=300) p.multi_polygons(xs=[[[[1, 1, 2, 2]]], [[[1, 1, 3], [1.5, 1.5, 2]]]], ys=[[[[4, 3, 3, 4]]], [[[1, 3, 1], [1.5, 2, 1.5]]]], 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) """) varea = _glyph_function(_glyphs.VArea, """ Examples: .. bokeh-plot:: :source-position: above from bokeh.plotting import figure, output_file, show plot = figure(plot_width=300, plot_height=300) plot.varea(x=[1, 2, 3], y1=[0, 0, 0], y2=[1, 4, 2], fill_color="#99D594") 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) """) # ------------------------------------------------------------------------- _scatter = _glyph_function(_markers.Scatter) [docs] 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, or list[str]): values or field names of marker types 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], marker="square", fill_color="red") >>> p.scatter("data1", "data2", marker="mtype", source=data_source, ...) .. note:: When passing ``marker="circle"`` it is also possible to supply a ``radius`` value in data-space units. When configuring marker type from a data source column, *all* markers including circles may only be configured with ``size`` in screen units. ''' marker_type = kwargs.pop("marker", "circle") if isinstance(marker_type, string_types) and marker_type in _MARKER_SHORTCUTS: marker_type = _MARKER_SHORTCUTS[marker_type] # The original scatter implementation allowed circle scatters to set a # radius. We will leave this here for compatibility but note that it # only works when the marker type is "circle" (and not referencing a # data source column). Consider deprecating in the future. if marker_type == "circle" and "radius" in kwargs: return self.circle(*args, **kwargs) else: return self._scatter(*args, marker=marker_type, **kwargs) [docs] 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 sophisticated 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 hexagonal tiles. y (array[float]) : A NumPy array of y-coordinates to bin into hexagonal 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 aspect 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 (instead 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) [docs] def harea_stack(self, stackers, **kw): ''' Generate multiple ``HArea`` renderers for levels stacked left to right. Args: stackers (seq[str]) : a list of data source field names to stack successively for ``x1`` and ``x2`` harea coordinates. Additionally, the ``name`` of the renderer will be set to the value of each successive stacker (this is useful with the special hover variable ``$name``) Any additional keyword arguments are passed to each call to ``harea``. If a keyword value is a list or tuple, then each call will get one value from the sequence. Returns: list[GlyphRenderer] Examples: Assuming a ``ColumnDataSource`` named ``source`` with columns *2016* and *2017*, then the following call to ``harea_stack`` will will create two ``HArea`` renderers that stack: .. code-block:: python p.harea_stack(['2016', '2017'], y='y', color=['blue', 'red'], source=source) This is equivalent to the following two separate calls: .. code-block:: python p.harea(x1=stack(), x2=stack('2016'), y='y', color='blue', source=source, name='2016') p.harea(x1=stack('2016'), x2=stack('2016', '2017'), y='y', color='red', source=source, name='2017') ''' result = [] for kw in _double_stack(stackers, "x1", "x2", **kw): result.append(self.harea(**kw)) return result [docs] def hbar_stack(self, stackers, **kw): ''' Generate multiple ``HBar`` renderers for levels stacked left to right. Args: stackers (seq[str]) : a list of data source field names to stack successively for ``left`` and ``right`` bar coordinates. Additionally, the ``name`` of the renderer will be set to the value of each successive stacker (this is useful with the special hover variable ``$name``) 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, name='2016') p.hbar(bottom=stack('2016'), top=stack('2016', '2017'), x=10, width=0.9, color='red', source=source, name='2017') ''' result = [] for kw in _double_stack(stackers, "left", "right", **kw): result.append(self.hbar(**kw)) return result def _line_stack(self, x, y, **kw): ''' Generate multiple ``Line`` renderers for lines stacked vertically or horizontally. Args: x (seq[str]) : y (seq[str]) : Additionally, the ``name`` of the renderer will be set to the value of each successive stacker (this is useful with the special hover variable ``$name``) Any additional keyword arguments are passed to each call to ``hbar``. If a keyword value is a list or tuple, then each call will get one value from the sequence. Returns: list[GlyphRenderer] Examples: Assuming a ``ColumnDataSource`` named ``source`` with columns *2106* and *2017*, then the following call to ``line_stack`` with stackers for the y-coordinates will will create two ``Line`` renderers that stack: .. code-block:: python p.line_stack(['2016', '2017'], x='x', color=['blue', 'red'], source=source) This is equivalent to the following two separate calls: .. code-block:: python p.line(y=stack('2016'), x='x', color='blue', source=source, name='2016') p.line(y=stack('2016', '2017'), x='x', color='red', source=source, name='2017') ''' if all(isinstance(val, (list, tuple)) for val in (x,y)): raise ValueError("Only one of x or y may be a list of stackers") result = [] if isinstance(y, (list, tuple)): kw['x'] = x for kw in _single_stack(y, "y", **kw): result.append(self.line(**kw)) return result if isinstance(x, (list, tuple)): kw['y'] = y for kw in _single_stack(x, "x", **kw): result.append(self.line(**kw)) return result return [self.line(x, y, **kw)] [docs] def hline_stack(self, stackers, **kw): ''' Generate multiple ``Line`` renderers for lines stacked horizontally. Args: stackers (seq[str]) : a list of data source field names to stack successively for ``x`` line coordinates. Additionally, the ``name`` of the renderer will be set to the value of each successive stacker (this is useful with the special hover variable ``$name``) Any additional keyword arguments are passed to each call to ``line``. 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 ``hline_stack`` with stackers for the x-coordinates will will create two ``Line`` renderers that stack: .. code-block:: python p.hline_stack(['2016', '2017'], y='y', color=['blue', 'red'], source=source) This is equivalent to the following two separate calls: .. code-block:: python p.line(x=stack('2016'), y='y', color='blue', source=source, name='2016') p.line(x=stack('2016', '2017'), y='y', color='red', source=source, name='2017') ''' return self._line_stack(x=stackers, **kw) [docs] def varea_stack(self, stackers, **kw): ''' Generate multiple ``VArea`` renderers for levels stacked bottom to top. Args: stackers (seq[str]) : a list of data source field names to stack successively for ``y1`` and ``y1`` varea coordinates. Additionally, the ``name`` of the renderer will be set to the value of each successive stacker (this is useful with the special hover variable ``$name``) Any additional keyword arguments are passed to each call to ``varea``. If a keyword value is a list or tuple, then each call will get one value from the sequence. Returns: list[GlyphRenderer] Examples: Assuming a ``ColumnDataSource`` named ``source`` with columns *2016* and *2017*, then the following call to ``varea_stack`` will will create two ``VArea`` renderers that stack: .. code-block:: python p.varea_stack(['2016', '2017'], x='x', color=['blue', 'red'], source=source) This is equivalent to the following two separate calls: .. code-block:: python p.varea(y1=stack(), y2=stack('2016'), x='x', color='blue', source=source, name='2016') p.varea(y1=stack('2016'), y2=stack('2016', '2017'), x='x', color='red', source=source, name='2017') ''' result = [] for kw in _double_stack(stackers, "y1", "y2", **kw): result.append(self.varea(**kw)) return result [docs] def vbar_stack(self, stackers, **kw): ''' Generate multiple ``VBar`` renderers for levels stacked bottom to top. Args: stackers (seq[str]) : a list of data source field names to stack successively for ``left`` and ``right`` bar coordinates. Additionally, the ``name`` of the renderer will be set to the value of each successive stacker (this is useful with the special hover variable ``$name``) 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, name='2016') p.vbar(bottom=stack('2016'), top=stack('2016', '2017'), x=10, width=0.9, color='red', source=source, name='2017') ''' result = [] for kw in _double_stack(stackers, "bottom", "top", **kw): result.append(self.vbar(**kw)) return result [docs] def vline_stack(self, stackers, **kw): ''' Generate multiple ``Line`` renderers for lines stacked vertically. Args: stackers (seq[str]) : a list of data source field names to stack successively for ``y`` line coordinates. Additionally, the ``name`` of the renderer will be set to the value of each successive stacker (this is useful with the special hover variable ``$name``) Any additional keyword arguments are passed to each call to ``line``. 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 ``vline_stack`` with stackers for the y-coordinates will will create two ``Line`` renderers that stack: .. code-block:: python p.vline_stack(['2016', '2017'], x='x', color=['blue', 'red'], source=source) This is equivalent to the following two separate calls: .. code-block:: python p.line(y=stack('2016'), x='x', color='blue', source=source, name='2016') p.line(y=stack('2016', '2017'), x='x', color='red', source=source, name='2017') ''' return self._line_stack(y=stackers, **kw) [docs] 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 [docs]def figure(**kwargs): return Figure(**kwargs) figure.__doc__ = Figure.__doc__ _MARKER_SHORTCUTS = { "*" : "asterisk", "+" : "cross", "o" : "circle", "ox" : "circle_x", "o+" : "circle_cross", "-" : "dash", "v" : "inverted_triangle", "^" : "triangle", } def markers(): ''' Prints a list of valid marker types for scatter() Returns: None ''' print("Available markers: \n\n - " + "\n - ".join(list(MarkerType))) print() print("Shortcuts: \n\n" + "\n".join(" %r: %s" % item for item in _MARKER_SHORTCUTS.items())) #----------------------------------------------------------------------------- # Dev API #----------------------------------------------------------------------------- # 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. """) tooltips = Either(String, List(Tuple(String, String)), help=""" An optional argument to configure tooltips for the Figure. This argument accepts the same values as the ``HoverTool.tooltips`` property. If a hover tool is specified in the ``tools`` argument, this value will override that hover tools ``tooltips`` value. If no hover tool is specified in the ``tools`` argument, then passing tooltips here will cause one to be created and added. """) #----------------------------------------------------------------------------- # Private API #----------------------------------------------------------------------------- _color_fields = set(["color", "fill_color", "line_color"]) _alpha_fields = set(["alpha", "fill_alpha", "line_alpha"]) #----------------------------------------------------------------------------- # Code #-----------------------------------------------------------------------------