ó mÜJ]c@`sGddlmZmZmZmZddlZejeƒZddl m Z ddl m Z m Z mZmZmZmZmZmZmZmZddlmZmZmZddlmZmZmZmZmZddlm Z!dd lm"Z#dd l$m%Z%m&Z&m'Z'm(Z(dd l)m*Z*dd l+m,Z,d dl-m.Z.m/Z/m0Z0m1Z1m2Z2m3Z3m4Z4m5Z5m6Z6dZ7ddddfZ8defd„ƒYZ9d„Z:e9j;e:_;idd6dd6dd6dd6dd 6d!d"6d#d$6d%d&6Z<d'„Z"d(e*fd)„ƒYZ=e>d*d+d,gƒZ?e>d-d.d/gƒZ@dS(0i(tabsolute_importtdivisiontprint_functiontunicode_literalsN(t string_typesi( tAnytAutotEithertEnumtInttListtSeqtInstancetStringtTuple(tHorizontalLocationt MarkerTypetVerticalLocation(tColumnDataSourcetPlottTitletToolt GraphRenderer(tglyphs(tmarkers(tDragt InspectiontScrolltTap(tOptions(t linear_cmapi( t _get_ranget _get_scalet_process_axis_and_gridt_process_tools_argt_glyph_functiont_process_active_toolst _single_stackt _double_stackt_graphu'pan,wheel_zoom,box_zoom,save,reset,helpuFigureufigureu FigureOptionsumarkerstFigurecB`s€eZdZdZdZd„ZeejƒZ eej dƒZ eej ƒZ eejdƒZeejƒZeejdƒZeejdƒZeejdƒZeejd ƒZeejd ƒZeejd ƒZeejd ƒZ eej!d ƒZ"eej#dƒZ$eej%dƒZ&eej'dƒZ(eej)dƒZ*eej+dƒZ,eej-dƒZ.eej/ƒZ0eej1dƒZ2eej3dƒZ4eej5dƒZ6eej7dƒZ8eej9dƒZ:eej;dƒZ<eej=dƒZ>eej?dƒZ@eejAƒZBeejCdƒZDeejEdƒZFeejGdƒZHeejIdƒZJeejKd ƒZLeejMd!ƒZNeejOd"ƒZPeejQd#ƒZReejSd$ƒZTeejUd%ƒZVeejWd&ƒZXeejYd'ƒZZeej[d(ƒZ\eej]ƒZ^d)„Z_d*d+d6d6d,d-„Zad.„Zbd/„Zcd0„Zdd1„Zed2„Zfd3„Zgd4„Zhd5„ZiRS(7uš 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 uFigureuPlotcO`sïd|kr'd|kr'tdƒ‚nd|krNd|krNtdƒ‚nd|krp|jdƒ|d>> 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 incuding circles may only be configured with ``size`` in screen units. umarkerucircleuradiustmarkerN(R+R/Rt_MARKER_SHORTCUTStcirclet_scatter(RFtargstkwargst marker_type((s4lib/python2.7/site-packages/bokeh/plotting/figure.pytscatterôs  u pointytopu Viridis256ic K`sÎddlm} | ||||d|ƒ} |dkrXtd|dt| jƒƒ}ntdtd| jd| j d | jƒƒ} |j dd dd d |d |d|d| d|d|| } | | fS(uê 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 i(thexbint aspect_scaleucitdatatqtrtcuqurtsizet orientationtsourcet line_colort fill_colorN( tutil.hexRUR.RtmaxtcountsRtdictRXRYthex_tile(RFtxtyR[R\tpaletteR^R_RVRRRUtbinsR]RY((s4lib/python2.7/site-packages/bokeh/plotting/figure.pyRU"sa !-'cK`s@g}x3t|dd|D]}|j|j|ƒqW|S(ut 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') ux1ux2(R&tappendtharea(RFtstackersRHtresult((s4lib/python2.7/site-packages/bokeh/plotting/figure.pyt harea_stack‘s%cK`s@g}x3t|dd|D]}|j|j|ƒqW|S(u 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 ``$name``) Any additional keyword arguments are passed to each call to ``hbar``. If a keyword value is a list or tuple, then each call will get one value from the sequence. Returns: list[GlyphRenderer] Examples: Assuming a ``ColumnDataSource`` named ``source`` with columns *2106* and *2017*, then the following call to ``hbar_stack`` will will create two ``HBar`` renderers that stack: .. code-block:: python p.hbar_stack(['2016', '2017'], x=10, width=0.9, color=['blue', 'red'], source=source) This is equivalent to the following two separate calls: .. code-block:: python p.hbar(bottom=stack(), top=stack('2016'), x=10, width=0.9, color='blue', source=source, name='2016') p.hbar(bottom=stack('2016'), top=stack('2016', '2017'), x=10, width=0.9, color='red', source=source, name='2017') ulefturight(R&Rithbar(RFRkRHRl((s4lib/python2.7/site-packages/bokeh/plotting/figure.pyt hbar_stack»s$cK`sótd„||fDƒƒr+tdƒ‚ng}t|ttfƒr‡||d su,Only one of x or y may be a list of stackersuxuy(tallR*R/RpRqR%Ritline(RFReRfRHRl((s4lib/python2.7/site-packages/bokeh/plotting/figure.pyt _line_stackäs'  cK`s|jd||S(uJ 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 ``$name``) Any additional keyword arguments are passed to each call to ``line``. If a keyword value is a list or tuple, then each call will get one value from the sequence. Returns: list[GlyphRenderer] Examples: Assuming a ``ColumnDataSource`` named ``source`` with columns *2106* and *2017*, then the following call to ``hline_stack`` with stackers for the x-coordinates will will create two ``Line`` renderers that stack: .. code-block:: python p.hline_stack(['2016', '2017'], y='y', color=['blue', 'red'], source=source) This is equivalent to the following two separate calls: .. code-block:: python p.line(x=stack('2016'), y='y', color='blue', source=source, name='2016') p.line(x=stack('2016', '2017'), y='y', color='red', source=source, name='2017') Re(Rv(RFRkRH((s4lib/python2.7/site-packages/bokeh/plotting/figure.pyt hline_stacks%cK`s@g}x3t|dd|D]}|j|j|ƒqW|S(ut Generate multiple ``VArea`` renderers for levels stacked bottom to top. Args: stackers (seq[str]) : a list of data source field names to stack successively for ``y1`` and ``y1`` varea coordinates. Additionally, the ``name`` of the renderer will be set to the value of each successive stacker (this is useful with the special hover variable ``$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') uy1uy2(R&Ritvarea(RFRkRHRl((s4lib/python2.7/site-packages/bokeh/plotting/figure.pyt varea_stackEs%cK`s@g}x3t|dd|D]}|j|j|ƒqW|S(u˜ 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 ``$name``) Any additional keyword arguments are passed to each call to ``vbar``. If a keyword value is a list or tuple, then each call will get one value from the sequence. Returns: list[GlyphRenderer] Examples: Assuming a ``ColumnDataSource`` named ``source`` with columns *2016* and *2017*, then the following call to ``vbar_stack`` will will create two ``VBar`` renderers that stack: .. code-block:: python p.vbar_stack(['2016', '2017'], x=10, width=0.9, color=['blue', 'red'], source=source) This is equivalent to the following two separate calls: .. code-block:: python p.vbar(bottom=stack(), top=stack('2016'), x=10, width=0.9, color='blue', source=source, name='2016') p.vbar(bottom=stack('2016'), top=stack('2016', '2017'), x=10, width=0.9, color='red', source=source, name='2017') ubottomutop(R&Ritvbar(RFRkRHRl((s4lib/python2.7/site-packages/bokeh/plotting/figure.pyt vbar_stackos%cK`s|jd||S(uH Generate multiple ``Line`` renderers for lines stacked vertically. Args: stackers (seq[str]) : a list of data source field names to stack successively for ``y`` line coordinates. Additionally, the ``name`` of the renderer will be set to the value of each successive stacker (this is useful with the special hover variable ``$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') Rf(Rv(RFRkRH((s4lib/python2.7/site-packages/bokeh/plotting/figure.pyt vline_stack™s%cK`s8t|||}td||}|jj|ƒ|S(u2 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` tlayout_provider(R'Rt renderersRi(RFt node_sourcet edge_sourceR}RRRHtgraph_renderer((s4lib/python2.7/site-packages/bokeh/plotting/figure.pytgraphÀsN(jt__name__t __module__t__doc__t __subtype__t__view_model__R1R#t_glyphst AnnularWedget annular_wedgetAnnulustannulustArctarct_markerstAsterisktasterisktBeziertbeziertCircleROt CircleCrosst circle_crosstCircleXtcircle_xtCrosstcrosstDashtdashtDiamondtdiamondt DiamondCrosst diamond_crosstHAreaRjtHBarRntEllipsetellipsetHexthextHexTileRdtImagetimaget ImageRGBAt image_rgbatImageURLt image_urltInvertedTriangletinverted_triangletLineRut MultiLinet multi_linet MultiPolygonstmulti_polygonstOvaltovaltPatchtpatchtPatchestpatchestQuadtquadt Quadratict quadratictRaytraytRecttrecttSteptsteptSegmenttsegmenttSquaretsquaret SquareCrosst square_crosstSquareXtsquare_xtTextR)tTrianglettriangletVAreaRxtVBarRztWedgetwedgetXRetScatterRPRTR.RURmRoRvRwRyR{R|R‚(((s4lib/python2.7/site-packages/bokeh/plotting/figure.pyR(8s¼K                                                                 .o * ) : ' * * 'cK`s t|S(N(R((RR((s4lib/python2.7/site-packages/bokeh/plotting/figure.pytfigureÙsuasterisku*ucrossu+ucircleuoucircle_xuoxu circle_crossuo+udashu-uinverted_triangleuvutriangleu^cC`sOtddjttƒƒƒtƒtddjd„tjƒDƒƒƒdS(uR Prints a list of valid marker types for scatter() Returns: None uAvailable markers: - u - u Shortcuts: u cs`s|]}d|VqdS(u %r: %sN((Rrtitem((s4lib/python2.7/site-packages/bokeh/plotting/figure.pys ðsN(tprinttjoinRpRRNtitems(((s4lib/python2.7/site-packages/bokeh/plotting/figure.pyRèsR,c B`sýeZeeeeeeeƒƒƒdeddƒZe ddƒZ e ddƒZ ee e ddddƒZee e ddddƒZeeddddƒZeedd dd ƒZedd dd ƒZedd dd ƒZee eeeƒddddƒZee eeeƒeeeƒƒddddƒZee eeeƒddddƒZee eeeƒddddƒZee eddddƒddddƒZee eddddƒddddƒZ eee!e"eeƒƒddƒZ#RS(tdefaultthelpu+ Tools the plot should start with. u, Customize the x-range of the plot. uautouD Number of minor ticks between adjacent x-axis major ticks. uD Number of minor ticks between adjacent y-axis major ticks. ubelowu- Where the x-axis should be located. uleftu- Where the y-axis should be located. uu! A label for the x-axis. u! A label for the y-axis. u5 Which drag tool should initially be active. u7 Which scroll tool should initially be active. u4 Which tap tool should initially be active. ulinearulogudatetimeumercatoru! The type of the x-axis. u! The type of the y-axis. u˜ 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. ($RƒR„RR R R Rt DEFAULT_TOOLSR>RR2R3RR R9R<RRR8RR;R:R=RRBRRCRRDRRER4R6R RR?(((s4lib/python2.7/site-packages/bokeh/plotting/figure.pyR,øs@'            *   ! ! ucoloru fill_coloru line_colorualphau fill_alphau line_alpha(At __future__RRRRtloggingt getLoggerRƒtlogtsixRtcore.propertiesRRRRR R R R R Rt core.enumsRRRtmodelsRRRRRRRˆRRt models.toolsRRRRt util.optionsRt transformRthelpersRR R!R"R#R$R%R&R'RÝt__all__R(RÖR…RNR,tsett _color_fieldst _alpha_fields(((s4lib/python2.7/site-packages/bokeh/plotting/figure.pyt sJ"  F("@  ÿÿÿÿ¥    K