#-----------------------------------------------------------------------------
# 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.
#-----------------------------------------------------------------------------
''' Models for representing top-level plot objects.
'''
#-----------------------------------------------------------------------------
# Boilerplate
#-----------------------------------------------------------------------------
from __future__ import absolute_import, division, print_function, unicode_literals
import logging
log = logging.getLogger(__name__)
#-----------------------------------------------------------------------------
# Imports
#-----------------------------------------------------------------------------
# Standard library imports
import warnings
# External imports
from six import string_types
# Bokeh imports
from ..core.enums import Location, OutputBackend
from ..core.properties import Bool, Dict, Enum, Include, Instance, Int, List, Override, String, Float
from ..core.property_mixins import LineProps, FillProps
from ..core.query import find
from ..core.validation import error, warning
from ..core.validation.errors import BAD_EXTRA_RANGE_NAME, REQUIRED_RANGE, REQUIRED_SCALE, INCOMPATIBLE_SCALE_AND_RANGE
from ..core.validation.warnings import MISSING_RENDERERS
from ..model import Model
from ..util.string import nice_join
from .annotations import Legend, Title
from .axes import Axis
from .glyphs import Glyph
from .grids import Grid
from .layouts import LayoutDOM
from .ranges import Range, FactorRange, DataRange1d, Range1d
from .renderers import GlyphRenderer, Renderer, TileRenderer
from .scales import Scale, CategoricalScale, LinearScale, LogScale
from .sources import DataSource, ColumnDataSource
from .tools import Tool, Toolbar, HoverTool
#-----------------------------------------------------------------------------
# Globals and constants
#-----------------------------------------------------------------------------
__all__ = (
'Plot',
)
#-----------------------------------------------------------------------------
# General API
#-----------------------------------------------------------------------------
[docs]class Plot(LayoutDOM):
''' Model representing a plot, containing glyphs, guides, annotations.
'''
[docs] def select(self, *args, **kwargs):
''' Query this object and all of its references for objects that
match the given selector.
There are a few different ways to call the ``select`` method.
The most general is to supply a JSON-like query dictionary as the
single argument or as keyword arguments:
Args:
selector (JSON-like) : some sample text
Keyword Arguments:
kwargs : query dict key/values as keyword arguments
Additionally, for compatibility with ``Model.select``, a selector
dict may be passed as ``selector`` keyword argument, in which case
the value of ``kwargs['selector']`` is used for th query.
For convenience, queries on just names can be made by supplying
the ``name`` string as the single parameter:
Args:
name (str) : the name to query on
Also queries on just type can be made simply by supplying the
``Model`` subclass as the single parameter:
Args:
type (Model) : the type to query on
Returns:
seq[Model]
Examples:
.. code-block:: python
# These three are equivalent
p.select(selector={"type": HoverTool})
p.select({"type": HoverTool})
p.select(HoverTool)
# These two are also equivalent
p.select({"name": "mycircle"})
p.select("mycircle")
# Keyword arguments can be supplied in place of selector dict
p.select({"name": "foo", "type": HoverTool})
p.select(name="foo", type=HoverTool)
'''
selector = _select_helper(args, kwargs)
# Want to pass selector that is a dictionary
return _list_attr_splat(find(self.references(), selector, {'plot': self}))
[docs] def row(self, row, gridplot):
''' Return whether this plot is in a given row of a GridPlot.
Args:
row (int) : index of the row to test
gridplot (GridPlot) : the GridPlot to check
Returns:
bool
'''
return self in gridplot.row(row)
[docs] def column(self, col, gridplot):
''' Return whether this plot is in a given column of a GridPlot.
Args:
col (int) : index of the column to test
gridplot (GridPlot) : the GridPlot to check
Returns:
bool
'''
return self in gridplot.column(col)
def _axis(self, *sides):
objs = []
for s in sides:
objs.extend(getattr(self, s, []))
axis = [obj for obj in objs if isinstance(obj, Axis)]
return _list_attr_splat(axis)
@property
def xaxis(self):
''' Splattable list of :class:`~bokeh.models.axes.Axis` objects for the x dimension.
'''
return self._axis("above", "below")
@property
def yaxis(self):
''' Splattable list of :class:`~bokeh.models.axes.Axis` objects for the y dimension.
'''
return self._axis("left", "right")
@property
def axis(self):
''' Splattable list of :class:`~bokeh.models.axes.Axis` objects.
'''
return _list_attr_splat(self.xaxis + self.yaxis)
@property
def legend(self):
''' Splattable list of :class:`~bokeh.models.annotations.Legend` objects.
'''
legends = [obj for obj in self.renderers if isinstance(obj, Legend)]
return _legend_attr_splat(legends)
@property
def hover(self):
''' Splattable list of :class:`~bokeh.models.tools.HoverTool` objects.
'''
hovers = [obj for obj in self.tools if isinstance(obj, HoverTool)]
return _list_attr_splat(hovers)
def _grid(self, dimension):
grid = [obj for obj in self.renderers if isinstance(obj, Grid) and obj.dimension==dimension]
return _list_attr_splat(grid)
@property
def xgrid(self):
''' Splattable list of :class:`~bokeh.models.grids.Grid` objects for the x dimension.
'''
return self._grid(0)
@property
def ygrid(self):
''' Splattable list of :class:`~bokeh.models.grids.Grid` objects for the y dimension.
'''
return self._grid(1)
@property
def grid(self):
''' Splattable list of :class:`~bokeh.models.grids.Grid` objects.
'''
return _list_attr_splat(self.xgrid + self.ygrid)
@property
def tools(self):
return self.toolbar.tools
@tools.setter
def tools(self, tools):
self.toolbar.tools = tools
[docs] def add_layout(self, obj, place='center'):
''' Adds an object to the plot in a specified place.
Args:
obj (Renderer) : the object to add to the Plot
place (str, optional) : where to add the object (default: 'center')
Valid places are: 'left', 'right', 'above', 'below', 'center'.
Returns:
None
'''
valid_places = ['left', 'right', 'above', 'below', 'center']
if place not in valid_places:
raise ValueError(
"Invalid place '%s' specified. Valid place values are: %s" % (place, nice_join(valid_places))
)
if hasattr(obj, 'plot'):
if obj.plot is not None:
raise ValueError("object to be added already has 'plot' attribute set")
obj.plot = self
self.renderers.append(obj)
if place != 'center':
getattr(self, place).append(obj)
[docs] def add_glyph(self, source_or_glyph, glyph=None, **kw):
''' Adds a glyph to the plot with associated data sources and ranges.
This function will take care of creating and configuring a Glyph object,
and then add it to the plot's list of renderers.
Args:
source (DataSource) : a data source for the glyphs to all use
glyph (Glyph) : the glyph to add to the Plot
Keyword Arguments:
Any additional keyword arguments are passed on as-is to the
Glyph initializer.
Returns:
GlyphRenderer
'''
if glyph is not None:
source = source_or_glyph
else:
source, glyph = ColumnDataSource(), source_or_glyph
if not isinstance(source, DataSource):
raise ValueError("'source' argument to add_glyph() must be DataSource subclass")
if not isinstance(glyph, Glyph):
raise ValueError("'glyph' argument to add_glyph() must be Glyph subclass")
g = GlyphRenderer(data_source=source, glyph=glyph, **kw)
self.renderers.append(g)
return g
[docs] def add_tile(self, tile_source, **kw):
''' Adds new ``TileRenderer`` into ``Plot.renderers``
Args:
tile_source (TileSource) : a tile source instance which contain tileset configuration
Keyword Arguments:
Additional keyword arguments are passed on as-is to the tile renderer
Returns:
TileRenderer : TileRenderer
'''
tile_renderer = TileRenderer(tile_source=tile_source, **kw)
self.renderers.append(tile_renderer)
return tile_renderer
@error(REQUIRED_RANGE)
def _check_required_range(self):
missing = []
if not self.x_range: missing.append('x_range')
if not self.y_range: missing.append('y_range')
if missing:
return ", ".join(missing) + " [%s]" % self
@error(REQUIRED_SCALE)
def _check_required_scale(self):
missing = []
if not self.x_scale: missing.append('x_scale')
if not self.y_scale: missing.append('y_scale')
if missing:
return ", ".join(missing) + " [%s]" % self
@error(INCOMPATIBLE_SCALE_AND_RANGE)
def _check_compatible_scale_and_ranges(self):
incompatible = []
x_ranges = list(self.extra_x_ranges.values())
if self.x_range: x_ranges.append(self.x_range)
y_ranges = list(self.extra_y_ranges.values())
if self.y_range: y_ranges.append(self.y_range)
if self.x_scale is not None:
for rng in x_ranges:
if isinstance(rng, (DataRange1d, Range1d)) and not isinstance(self.x_scale, (LinearScale, LogScale)):
incompatible.append("incompatibility on x-dimension: %s, %s" %(rng, self.x_scale))
elif isinstance(rng, FactorRange) and not isinstance(self.x_scale, CategoricalScale):
incompatible.append("incompatibility on x-dimension: %s/%s" %(rng, self.x_scale))
# special case because CategoricalScale is a subclass of LinearScale, should be removed in future
if isinstance(rng, (DataRange1d, Range1d)) and isinstance(self.x_scale, CategoricalScale):
incompatible.append("incompatibility on x-dimension: %s, %s" %(rng, self.x_scale))
if self.y_scale is not None:
for rng in y_ranges:
if isinstance(rng, (DataRange1d, Range1d)) and not isinstance(self.y_scale, (LinearScale, LogScale)):
incompatible.append("incompatibility on y-dimension: %s/%s" %(rng, self.y_scale))
elif isinstance(rng, FactorRange) and not isinstance(self.y_scale, CategoricalScale):
incompatible.append("incompatibility on y-dimension: %s/%s" %(rng, self.y_scale))
# special case because CategoricalScale is a subclass of LinearScale, should be removed in future
if isinstance(rng, (DataRange1d, Range1d)) and isinstance(self.y_scale, CategoricalScale):
incompatible.append("incompatibility on y-dimension: %s, %s" %(rng, self.y_scale))
if incompatible:
return ", ".join(incompatible) + " [%s]" % self
@warning(MISSING_RENDERERS)
def _check_missing_renderers(self):
if len(self.renderers) == 0:
return str(self)
@error(BAD_EXTRA_RANGE_NAME)
def _check_bad_extra_range_name(self):
msg = ""
for ref in self.references():
prop_names = ref.properties()
bad = []
if 'x_range_name' in prop_names and 'y_range_name' in prop_names:
if ref.x_range_name not in self.extra_x_ranges and ref.x_range_name != "default":
bad.append(('x_range_name', ref.x_range_name))
if ref.y_range_name not in self.extra_y_ranges and ref.y_range_name != "default":
bad.append(('y_range_name', ref.y_range_name))
if bad:
if msg: msg += ", "
msg += (", ".join("%s=%r" % (a, b) for (a,b) in bad) + " [%s]" % ref)
if msg:
return msg
x_range = Instance(Range, default=lambda: DataRange1d(), help="""
The (default) data range of the horizontal dimension of the plot.
""")
y_range = Instance(Range, default=lambda: DataRange1d(), help="""
The (default) data range of the vertical dimension of the plot.
""")
@classmethod
def _scale(cls, scale):
if scale in ["auto", "linear"]:
return LinearScale()
elif scale == "log":
return LogScale()
if scale == "categorical":
return CategoricalScale()
else:
raise ValueError("Unknown mapper_type: %s" % scale)
x_scale = Instance(Scale, default=lambda: LinearScale(), help="""
What kind of scale to use to convert x-coordinates in data space
into x-coordinates in screen space.
""")
y_scale = Instance(Scale, default=lambda: LinearScale(), help="""
What kind of scale to use to convert y-coordinates in data space
into y-coordinates in screen space.
""")
extra_x_ranges = Dict(String, Instance(Range), help="""
Additional named ranges to make available for mapping x-coordinates.
This is useful for adding additional axes.
""")
extra_y_ranges = Dict(String, Instance(Range), help="""
Additional named ranges to make available for mapping y-coordinates.
This is useful for adding additional axes.
""")
hidpi = Bool(default=True, help="""
Whether to use HiDPI mode when available.
""")
title = Instance(Title, default=lambda: Title(text=""), help="""
A title for the plot. Can be a text string or a Title annotation.
""")
title_location = Enum(Location, default="above", help="""
Where the title will be located. Titles on the left or right side
will be rotated.
""")
outline_props = Include(LineProps, help="""
The %s for the plot border outline.
""")
outline_line_color = Override(default="#e5e5e5")
renderers = List(Instance(Renderer), help="""
A list of all renderers for this plot, including guides and annotations
in addition to glyphs and markers.
This property can be manipulated by hand, but the ``add_glyph`` and
``add_layout`` methods are recommended to help make sure all necessary
setup is performed.
""")
toolbar = Instance(Toolbar, default=lambda: Toolbar(), help="""
The toolbar associated with this plot which holds all the tools. It is
automatically created with the plot if necessary.
""")
toolbar_location = Enum(Location, default="right", help="""
Where the toolbar will be located. If set to None, no toolbar
will be attached to the plot.
""")
toolbar_sticky = Bool(default=True, help="""
Stick the toolbar to the edge of the plot. Default: True. If False,
the toolbar will be outside of the axes, titles etc.
""")
left = List(Instance(Renderer), help="""
A list of renderers to occupy the area to the left of the plot.
""")
right = List(Instance(Renderer), help="""
A list of renderers to occupy the area to the right of the plot.
""")
above = List(Instance(Renderer), help="""
A list of renderers to occupy the area above of the plot.
""")
below = List(Instance(Renderer), help="""
A list of renderers to occupy the area below of the plot.
""")
plot_height = Int(600, help="""
Total height of the entire plot (including any axes, titles,
border padding, etc.)
.. note::
This corresponds directly to the height of the HTML
canvas that will be used.
""")
plot_width = Int(600, help="""
Total width of the entire plot (including any axes, titles,
border padding, etc.)
.. note::
This corresponds directly to the width of the HTML
canvas that will be used.
""")
inner_width = Int(readonly=True, help="""
This is the exact width of the plotting canvas, i.e. the width of
the actual plot, without toolbars etc. Note this is computed in a
web browser, so this property will work only in backends capable of
bidirectional communication (server, notebook).
.. note::
This is an experimental feature and the API may change in near future.
""")
inner_height = Int(readonly=True, help="""
This is the exact height of the plotting canvas, i.e. the height of
the actual plot, without toolbars etc. Note this is computed in a
web browser, so this property will work only in backends capable of
bidirectional communication (server, notebook).
.. note::
This is an experimental feature and the API may change in near future.
""")
layout_width = Int(readonly=True, help="""
This is the exact width of the layout, i.e. the height of
the actual plot, with toolbars etc. Note this is computed in a
web browser, so this property will work only in backends capable of
bidirectional communication (server, notebook).
.. note::
This is an experimental feature and the API may change in near future.
""")
layout_height = Int(readonly=True, help="""
This is the exact height of the layout, i.e. the height of
the actual plot, with toolbars etc. Note this is computed in a
web browser, so this property will work only in backends capable of
bidirectional communication (server, notebook).
.. note::
This is an experimental feature and the API may change in near future.
""")
background_props = Include(FillProps, help="""
The %s for the plot background style.
""")
background_fill_color = Override(default='#ffffff')
border_props = Include(FillProps, help="""
The %s for the plot border style.
""")
border_fill_color = Override(default='#ffffff')
min_border_top = Int(help="""
Minimum size in pixels of the padding region above the top of the
central plot region.
.. note::
This is a *minimum*. The padding region may expand as needed to
accommodate titles or axes, etc.
""")
min_border_bottom = Int(help="""
Minimum size in pixels of the padding region below the bottom of
the central plot region.
.. note::
This is a *minimum*. The padding region may expand as needed to
accommodate titles or axes, etc.
""")
min_border_left = Int(help="""
Minimum size in pixels of the padding region to the left of
the central plot region.
.. note::
This is a *minimum*. The padding region may expand as needed to
accommodate titles or axes, etc.
""")
min_border_right = Int(help="""
Minimum size in pixels of the padding region to the right of
the central plot region.
.. note::
This is a *minimum*. The padding region may expand as needed to
accommodate titles or axes, etc.
""")
min_border = Int(5, help="""
A convenience property to set all all the ``min_border_X`` properties
to the same value. If an individual border property is explicitly set,
it will override ``min_border``.
""")
h_symmetry = Bool(True, help="""
Whether the total horizontal padding on both sides of the plot will
be made equal (the left or right padding amount, whichever is larger).
""")
v_symmetry = Bool(False, help="""
Whether the total vertical padding on both sides of the plot will
be made equal (the top or bottom padding amount, whichever is larger).
""")
lod_factor = Int(10, help="""
Decimation factor to use when applying level-of-detail decimation.
""")
lod_threshold = Int(2000, help="""
A number of data points, above which level-of-detail downsampling may
be performed by glyph renderers. Set to ``None`` to disable any
level-of-detail downsampling.
""")
lod_interval = Int(300, help="""
Interval (in ms) during which an interactive tool event will enable
level-of-detail downsampling.
""")
lod_timeout = Int(500, help="""
Timeout (in ms) for checking whether interactive tool events are still
occurring. Once level-of-detail mode is enabled, a check is made every
``lod_timeout`` ms. If no interactive tool events have happened,
level-of-detail mode is disabled.
""")
output_backend = Enum(OutputBackend, default="canvas", help="""
Specify the output backend for the plot area. Default is HTML5 Canvas.
.. note::
When set to ``webgl``, glyphs without a WebGL rendering implementation
will fall back to rendering onto 2D canvas.
""")
match_aspect = Bool(default=False, help="""
Specify the aspect ratio behavior of the plot. Aspect ratio is defined as
the ratio of width over height. This property controls whether Bokeh should
attempt the match the (width/height) of *data space* to the (width/height)
in pixels of *screen space*.
Default is ``False`` which indicates that the *data* aspect ratio and the
*screen* aspect ratio vary independently. ``True`` indicates that the plot
aspect ratio of the axes will match the aspect ratio of the pixel extent
the axes. The end result is that a 1x1 area in data space is a square in
pixels, and conversely that a 1x1 pixel is a square in data units.
.. note::
This setting only takes effect when there are two dataranges. This
setting only sets the initial plot draw and subsequent resets. It is
possible for tools (single axis zoom, unconstrained box zoom) to
change the aspect ratio.
.. warning::
This setting is incompatible with linking dataranges across multiple
plots. Doing so may result in undefined behaviour.
""")
aspect_scale = Float(default=1, help="""
A value to be given for increased aspect ratio control. This value is added
multiplicatively to the calculated value required for ``match_aspect``.
``aspect_scale`` is defined as the ratio of width over height of the figure.
For example, a plot with ``aspect_scale`` value of 2 will result in a
square in *data units* to be drawn on the screen as a rectangle with a
pixel width twice as long as its pixel height.
.. note::
This setting only takes effect if ``match_aspect`` is set to ``True``.
""")
#-----------------------------------------------------------------------------
# Dev API
#-----------------------------------------------------------------------------
#-----------------------------------------------------------------------------
# Private API
#-----------------------------------------------------------------------------
def _check_conflicting_kwargs(a1, a2, kwargs):
if a1 in kwargs and a2 in kwargs:
raise ValueError("Conflicting properties set on plot: %r and %r" % (a1, a2))
class _list_attr_splat(list):
def __setattr__(self, attr, value):
for x in self:
setattr(x, attr, value)
def __dir__(self):
if len(set(type(x) for x in self)) == 1:
return dir(self[0])
else:
return dir(self)
_LEGEND_EMPTY_WARNING = """
You are attemptings to set `plot.legend.%s` on a plot that has zero legends added, this will have no effect.
Before legend properties can be set, you must add a Legend explicitly, or call a glyph method with the 'legend' parameter set.
"""
class _legend_attr_splat(_list_attr_splat):
def __setattr__(self, attr, value):
if not len(self):
warnings.warn(_LEGEND_EMPTY_WARNING % attr)
return super(_legend_attr_splat, self).__setattr__(attr, value)
def _select_helper(args, kwargs):
""" Allow flexible selector syntax.
Returns:
dict
"""
if len(args) > 1:
raise TypeError("select accepts at most ONE positional argument.")
if len(args) > 0 and len(kwargs) > 0:
raise TypeError("select accepts EITHER a positional argument, OR keyword arguments (not both).")
if len(args) == 0 and len(kwargs) == 0:
raise TypeError("select requires EITHER a positional argument, OR keyword arguments.")
if args:
arg = args[0]
if isinstance(arg, dict):
selector = arg
elif isinstance(arg, string_types):
selector = dict(name=arg)
elif isinstance(arg, type) and issubclass(arg, Model):
selector = {"type": arg}
else:
raise TypeError("selector must be a dictionary, string or plot object.")
elif 'selector' in kwargs:
if len(kwargs) == 1:
selector = kwargs['selector']
else:
raise TypeError("when passing 'selector' keyword arg, not other keyword args may be present")
else:
selector = kwargs
return selector
#-----------------------------------------------------------------------------
# Code
#-----------------------------------------------------------------------------
