Source code for bokeh.models.tickers

''' Models for computing good tick locations on different kinds
of plots.

'''
from __future__ import absolute_import

from ..core.enums import LatLon
from ..core.has_props import abstract
from ..core.properties import Enum, Float, Instance, Int, Override, Seq
from ..core.validation import error
from ..core.validation.errors import MISSING_MERCATOR_DIMENSION
from ..model import Model

[docs]@abstract class Ticker(Model): ''' A base class for all ticker types. '''
[docs]@abstract class ContinuousTicker(Ticker): ''' A base class for non-categorical ticker types. ''' num_minor_ticks = Int(5, help=""" The number of minor tick positions to generate between adjacent major tick values. """) desired_num_ticks = Int(6, help=""" A desired target number of major tick positions to generate across the plot range. .. note: This value is a suggestion, and ticker subclasses may ignore it entirely, or use it only as an ideal goal to approach as well as can be, in the context of a specific ticking strategy. """)
[docs]class FixedTicker(ContinuousTicker): ''' Generate ticks at fixed, explicitly supplied locations. .. note:: The ``desired_num_ticks`` property is ignored by this Ticker. ''' ticks = Seq(Float, default=[], help=""" List of tick locations. """)
[docs]class AdaptiveTicker(ContinuousTicker): ''' Generate "nice" round ticks at any magnitude. Creates ticks that are "base" multiples of a set of given mantissas. For example, with ``base=10`` and ``mantissas=[1, 2, 5]``, the ticker will generate the sequence:: ..., 0.1, 0.2, 0.5, 1, 2, 5, 10, 20, 50, 100, ... ''' base = Float(10.0, help=""" The multiplier to use for scaling mantissas. """) mantissas = Seq(Float, [1, 2, 5], help=""" The acceptable list numbers to generate multiples of. """) min_interval = Float(0.0, help=""" The smallest allowable interval between two adjacent ticks. """) max_interval = Float(help=""" The largest allowable interval between two adjacent ticks. .. note:: To specify an unbounded interval, set to ``None``. """)
[docs]class CompositeTicker(ContinuousTicker): ''' Combine different tickers at different scales. Uses the ``min_interval`` and ``max_interval`` interval attributes of the tickers to select the appropriate ticker at different scales. ''' tickers = Seq(Instance(Ticker), default=[], help=""" A list of Ticker objects to combine at different scales in order to generate tick values. The supplied tickers should be in order. Specifically, if S comes before T, then it should be the case that:: S.get_max_interval() < T.get_min_interval() """)
[docs]class SingleIntervalTicker(ContinuousTicker): ''' Generate evenly spaced ticks at a fixed interval regardless of scale. ''' interval = Float(help=""" The interval between adjacent ticks. """)
[docs]class DaysTicker(SingleIntervalTicker): ''' Generate ticks spaced apart by specific, even multiples of days. ''' days = Seq(Int, default=[], help=""" The intervals of days to use. """) num_minor_ticks = Override(default=0)
[docs]class MonthsTicker(SingleIntervalTicker): ''' Generate ticks spaced apart by specific, even multiples of months. ''' months = Seq(Int, default=[], help=""" The intervals of months to use. """)
[docs]class YearsTicker(SingleIntervalTicker): ''' Generate ticks spaced apart even numbers of years. '''
[docs]class BasicTicker(AdaptiveTicker): ''' Generate ticks on a linear scale. .. note:: This class may be renamed to ``LinearTicker`` in the future. '''
[docs]class LogTicker(AdaptiveTicker): ''' Generate ticks on a log scale. ''' mantissas = Override(default=[1, 5])
[docs]class MercatorTicker(BasicTicker): ''' Generate nice lat/lon ticks form underlying WebMercator coordinates. ''' dimension = Enum(LatLon, default=None, help=""" Specify whether to generate ticks for Latitude or Longitude. Projected coordinates are not separable, computing Latitude and Longitude tick locations from Web Mercator requires considering coordinates from both dimensions together. Use this property to specify which result should be returned. Typically, if the ticker is for an x-axis, then dimension should be ``"lon"`` and if the ticker is for a y-axis, then the dimension should be `"lat"``. In order to prevent hard to debug errors, there is no default value for dimension. Using an un-configured MercatorTicker will result in a validation error and a JavaScript console error. """) @error(MISSING_MERCATOR_DIMENSION) def _check_missing_dimension(self): if self.dimension is None: return str(self)
[docs]class CategoricalTicker(Ticker): ''' Generate ticks for categorical ranges. '''
ONE_MILLI = 1.0 ONE_SECOND = 1000.0 ONE_MINUTE = 60.0 * ONE_SECOND ONE_HOUR = 60 * ONE_MINUTE ONE_DAY = 24 * ONE_HOUR ONE_MONTH = 30 * ONE_DAY # An approximation, obviously. ONE_YEAR = 365 * ONE_DAY
[docs]class DatetimeTicker(CompositeTicker): ''' Generate nice ticks across different date and time scales. ''' num_minor_ticks = Override(default=0) tickers = Override(default=lambda: [ AdaptiveTicker( mantissas=[1, 2, 5], base=10, min_interval=0, max_interval=500*ONE_MILLI, num_minor_ticks=0 ), AdaptiveTicker( mantissas=[1, 2, 5, 10, 15, 20, 30], base=60, min_interval=ONE_SECOND, max_interval=30*ONE_MINUTE, num_minor_ticks=0 ), AdaptiveTicker( mantissas=[1, 2, 4, 6, 8, 12], base=24, min_interval=ONE_HOUR, max_interval=12*ONE_HOUR, num_minor_ticks=0 ), DaysTicker(days=list(range(1, 32))), DaysTicker(days=list(range(1, 31, 3))), DaysTicker(days=[1, 8, 15, 22]), DaysTicker(days=[1, 15]), MonthsTicker(months=list(range(0, 12, 1))), MonthsTicker(months=list(range(0, 12, 2))), MonthsTicker(months=list(range(0, 12, 4))), MonthsTicker(months=list(range(0, 12, 6))), YearsTicker(), ])