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"""
Tick locating and formatting
============================
This module contains classes to support completely configurable tick
locating and formatting. Although the locators know nothing about major
or minor ticks, they are used by the Axis class to support major and
minor tick locating and formatting. Generic tick locators and
formatters are provided, as well as domain specific custom ones.
Default Formatter
-----------------
The default formatter identifies when the x-data being plotted is a
small range on top of a large off set. To reduce the chances that the
ticklabels overlap the ticks are labeled as deltas from a fixed offset.
For example::
ax.plot(np.arange(2000, 2010), range(10))
will have tick of 0-9 with an offset of +2e3. If this is not desired
turn off the use of the offset on the default formatter::
ax.get_xaxis().get_major_formatter().set_useOffset(False)
set the rcParam ``axes.formatter.useoffset=False`` to turn it off
globally, or set a different formatter.
Tick locating
-------------
The Locator class is the base class for all tick locators. The locators
handle autoscaling of the view limits based on the data limits, and the
choosing of tick locations. A useful semi-automatic tick locator is
`MultipleLocator`. It is initialized with a base, e.g., 10, and it picks
axis limits and ticks that are multiples of that base.
The Locator subclasses defined here are
:class:`NullLocator`
No ticks
:class:`FixedLocator`
Tick locations are fixed
:class:`IndexLocator`
locator for index plots (e.g., where x = range(len(y)))
:class:`LinearLocator`
evenly spaced ticks from min to max
:class:`LogLocator`
logarithmically ticks from min to max
:class:`SymmetricalLogLocator`
locator for use with with the symlog norm, works like the
`LogLocator` for the part outside of the threshold and add 0 if
inside the limits
:class:`MultipleLocator`
ticks and range are a multiple of base; either integer or float
:class:`OldAutoLocator`
choose a MultipleLocator and dyamically reassign it for
intelligent ticking during navigation
:class:`MaxNLocator`
finds up to a max number of ticks at nice locations
:class:`AutoLocator`
:class:`MaxNLocator` with simple defaults. This is the default
tick locator for most plotting.
:class:`AutoMinorLocator`
locator for minor ticks when the axis is linear and the
major ticks are uniformly spaced. It subdivides the major
tick interval into a specified number of minor intervals,
defaulting to 4 or 5 depending on the major interval.
:class:`LogitLocator`
Locator for logit scaling.
There are a number of locators specialized for date locations - see
the dates module
You can define your own locator by deriving from Locator. You must
override the ``__call__`` method, which returns a sequence of locations,
and you will probably want to override the autoscale method to set the
view limits from the data limits.
If you want to override the default locator, use one of the above or a
custom locator and pass it to the x or y axis instance. The relevant
methods are::
ax.xaxis.set_major_locator( xmajorLocator )
ax.xaxis.set_minor_locator( xminorLocator )
ax.yaxis.set_major_locator( ymajorLocator )
ax.yaxis.set_minor_locator( yminorLocator )
The default minor locator is the NullLocator, e.g., no minor ticks on by
default.
Tick formatting
---------------
Tick formatting is controlled by classes derived from Formatter. The
formatter operates on a single tick value and returns a string to the
axis.
:class:`NullFormatter`
No labels on the ticks
:class:`IndexFormatter`
Set the strings from a list of labels
:class:`FixedFormatter`
Set the strings manually for the labels
:class:`FuncFormatter`
User defined function sets the labels
:class:`StrMethodFormatter`
Use string `format` method
:class:`FormatStrFormatter`
Use an old-style sprintf format string
:class:`ScalarFormatter`
Default formatter for scalars: autopick the format string
:class:`LogFormatter`
Formatter for log axes
:class:`LogFormatterExponent`
Format values for log axis using ``exponent = log_base(value)``.
:class:`LogFormatterMathtext`
Format values for log axis using ``exponent = log_base(value)``
using Math text.
:class:`LogFormatterSciNotation`
Format values for log axis using scientific notation.
:class:`LogitFormatter`
Probability formatter.
:class:`EngFormatter`
Format labels in engineering notation
:class:`PercentFormatter`
Format labels as a percentage
You can derive your own formatter from the Formatter base class by
simply overriding the ``__call__`` method. The formatter class has
access to the axis view and data limits.
To control the major and minor tick label formats, use one of the
following methods::
ax.xaxis.set_major_formatter( xmajorFormatter )
ax.xaxis.set_minor_formatter( xminorFormatter )
ax.yaxis.set_major_formatter( ymajorFormatter )
ax.yaxis.set_minor_formatter( yminorFormatter )
See :ref:`pylab_examples-major_minor_demo1` for an example of setting
major and minor ticks. See the :mod:`matplotlib.dates` module for
more information and examples of using date locators and formatters.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import decimal
import itertools
import locale
import math
import numpy as np
from matplotlib import rcParams
from matplotlib import cbook
from matplotlib import transforms as mtransforms
from matplotlib.cbook import mplDeprecation
import warnings
__all__ = ('TickHelper', 'Formatter', 'FixedFormatter',
'NullFormatter', 'FuncFormatter', 'FormatStrFormatter',
'StrMethodFormatter', 'ScalarFormatter', 'LogFormatter',
'LogFormatterExponent', 'LogFormatterMathtext',
'IndexFormatter', 'LogFormatterSciNotation',
'LogitFormatter', 'EngFormatter', 'PercentFormatter',
'Locator', 'IndexLocator', 'FixedLocator', 'NullLocator',
'LinearLocator', 'LogLocator', 'AutoLocator',
'MultipleLocator', 'MaxNLocator', 'AutoMinorLocator',
'SymmetricalLogLocator', 'LogitLocator')
if six.PY3:
long = int
# Work around numpy/numpy#6127.
def _divmod(x, y):
if isinstance(x, np.generic):
x = x.item()
if isinstance(y, np.generic):
y = y.item()
return six.moves.builtins.divmod(x, y)
def _mathdefault(s):
"""
For backward compatibility, in classic mode we display
sub/superscripted text in a mathdefault block. As of 2.0, the
math font already matches the default font, so we don't need to do
that anymore.
"""
if rcParams['_internal.classic_mode']:
return '\\mathdefault{%s}' % s
else:
return '{%s}' % s
class _DummyAxis(object):
def __init__(self, minpos=0):
self.dataLim = mtransforms.Bbox.unit()
self.viewLim = mtransforms.Bbox.unit()
self._minpos = minpos
def get_view_interval(self):
return self.viewLim.intervalx
def set_view_interval(self, vmin, vmax):
self.viewLim.intervalx = vmin, vmax
def get_minpos(self):
return self._minpos
def get_data_interval(self):
return self.dataLim.intervalx
def set_data_interval(self, vmin, vmax):
self.dataLim.intervalx = vmin, vmax
def get_tick_space(self):
# Just use the long-standing default of nbins==9
return 9
class TickHelper(object):
axis = None
def set_axis(self, axis):
self.axis = axis
def create_dummy_axis(self, **kwargs):
if self.axis is None:
self.axis = _DummyAxis(**kwargs)
def set_view_interval(self, vmin, vmax):
self.axis.set_view_interval(vmin, vmax)
def set_data_interval(self, vmin, vmax):
self.axis.set_data_interval(vmin, vmax)
def set_bounds(self, vmin, vmax):
self.set_view_interval(vmin, vmax)
self.set_data_interval(vmin, vmax)
class Formatter(TickHelper):
"""
Create a string based on a tick value and location.
"""
# some classes want to see all the locs to help format
# individual ones
locs = []
def __call__(self, x, pos=None):
"""
Return the format for tick value `x` at position pos.
``pos=None`` indicates an unspecified location.
"""
raise NotImplementedError('Derived must override')
def format_data(self, value):
"""
Returns the full string representation of the value with the
position unspecified.
"""
return self.__call__(value)
def format_data_short(self, value):
"""
Return a short string version of the tick value.
Defaults to the position-independent long value.
"""
return self.format_data(value)
def get_offset(self):
return ''
def set_locs(self, locs):
self.locs = locs
def fix_minus(self, s):
"""
Some classes may want to replace a hyphen for minus with the
proper unicode symbol (U+2212) for typographical correctness.
The default is to not replace it.
Note, if you use this method, e.g., in :meth:`format_data` or
call, you probably don't want to use it for
:meth:`format_data_short` since the toolbar uses this for
interactive coord reporting and I doubt we can expect GUIs
across platforms will handle the unicode correctly. So for
now the classes that override :meth:`fix_minus` should have an
explicit :meth:`format_data_short` method
"""
return s
class IndexFormatter(Formatter):
"""
Format the position x to the nearest i-th label where i=int(x+0.5)
"""
def __init__(self, labels):
self.labels = labels
self.n = len(labels)
def __call__(self, x, pos=None):
"""
Return the format for tick value `x` at position pos.
The position is ignored and the value is rounded to the nearest
integer, which is used to look up the label.
"""
i = int(x + 0.5)
if i < 0 or i >= self.n:
return ''
else:
return self.labels[i]
class NullFormatter(Formatter):
"""
Always return the empty string.
"""
def __call__(self, x, pos=None):
"""
Returns an empty string for all inputs.
"""
return ''
class FixedFormatter(Formatter):
"""
Return fixed strings for tick labels based only on position, not
value.
"""
def __init__(self, seq):
"""
Set the sequence of strings that will be used for labels.
"""
self.seq = seq
self.offset_string = ''
def __call__(self, x, pos=None):
"""
Returns the label that matches the position regardless of the
value.
For positions ``pos < len(seq)``, return `seq[i]` regardless of
`x`. Otherwise return empty string. `seq` is the sequence of
strings that this object was initialized with.
"""
if pos is None or pos >= len(self.seq):
return ''
else:
return self.seq[pos]
def get_offset(self):
return self.offset_string
def set_offset_string(self, ofs):
self.offset_string = ofs
class FuncFormatter(Formatter):
"""
Use a user-defined function for formatting.
The function should take in two inputs (a tick value ``x`` and a
position ``pos``), and return a string containing the corresponding
tick label.
"""
def __init__(self, func):
self.func = func
def __call__(self, x, pos=None):
"""
Return the value of the user defined function.
`x` and `pos` are passed through as-is.
"""
return self.func(x, pos)
class FormatStrFormatter(Formatter):
"""
Use an old-style ('%' operator) format string to format the tick.
The format string should have a single variable format (%) in it.
It will be applied to the value (not the position) of the tick.
"""
def __init__(self, fmt):
self.fmt = fmt
def __call__(self, x, pos=None):
"""
Return the formatted label string.
Only the value `x` is formatted. The position is ignored.
"""
return self.fmt % x
class StrMethodFormatter(Formatter):
"""
Use a new-style format string (as used by `str.format()`)
to format the tick.
The field used for the value must be labeled `x` and the field used
for the position must be labeled `pos`.
"""
def __init__(self, fmt):
self.fmt = fmt
def __call__(self, x, pos=None):
"""
Return the formatted label string.
`x` and `pos` are passed to `str.format` as keyword arguments
with those exact names.
"""
return self.fmt.format(x=x, pos=pos)
class OldScalarFormatter(Formatter):
"""
Tick location is a plain old number.
"""
def __call__(self, x, pos=None):
"""
Return the format for tick val `x` based on the width of the
axis.
The position `pos` is ignored.
"""
xmin, xmax = self.axis.get_view_interval()
d = abs(xmax - xmin)
return self.pprint_val(x, d)
def pprint_val(self, x, d):
"""
Formats the value `x` based on the size of the axis range `d`.
"""
#if the number is not too big and it's an int, format it as an
#int
if abs(x) < 1e4 and x == int(x):
return '%d' % x
if d < 1e-2:
fmt = '%1.3e'
elif d < 1e-1:
fmt = '%1.3f'
elif d > 1e5:
fmt = '%1.1e'
elif d > 10:
fmt = '%1.1f'
elif d > 1:
fmt = '%1.2f'
else:
fmt = '%1.3f'
s = fmt % x
#print d, x, fmt, s
tup = s.split('e')
if len(tup) == 2:
mantissa = tup[0].rstrip('0').rstrip('.')
sign = tup[1][0].replace('+', '')
exponent = tup[1][1:].lstrip('0')
s = '%se%s%s' % (mantissa, sign, exponent)
else:
s = s.rstrip('0').rstrip('.')
return s
class ScalarFormatter(Formatter):
"""
Format tick values as a number.
Tick value is interpreted as a plain old number. If
``useOffset==True`` and the data range is much smaller than the data
average, then an offset will be determined such that the tick labels
are meaningful. Scientific notation is used for ``data < 10^-n`` or
``data >= 10^m``, where ``n`` and ``m`` are the power limits set
using ``set_powerlimits((n,m))``. The defaults for these are
controlled by the ``axes.formatter.limits`` rc parameter.
"""
def __init__(self, useOffset=None, useMathText=None, useLocale=None):
# useOffset allows plotting small data ranges with large offsets: for
# example: [1+1e-9,1+2e-9,1+3e-9] useMathText will render the offset
# and scientific notation in mathtext
if useOffset is None:
useOffset = rcParams['axes.formatter.useoffset']
self._offset_threshold = rcParams['axes.formatter.offset_threshold']
self.set_useOffset(useOffset)
self._usetex = rcParams['text.usetex']
if useMathText is None:
useMathText = rcParams['axes.formatter.use_mathtext']
self.set_useMathText(useMathText)
self.orderOfMagnitude = 0
self.format = ''
self._scientific = True
self._powerlimits = rcParams['axes.formatter.limits']
if useLocale is None:
useLocale = rcParams['axes.formatter.use_locale']
self._useLocale = useLocale
def get_useOffset(self):
return self._useOffset
def set_useOffset(self, val):
if val in [True, False]:
self.offset = 0
self._useOffset = val
else:
self._useOffset = False
self.offset = val
useOffset = property(fget=get_useOffset, fset=set_useOffset)
def get_useLocale(self):
return self._useLocale
def set_useLocale(self, val):
if val is None:
self._useLocale = rcParams['axes.formatter.use_locale']
else:
self._useLocale = val
useLocale = property(fget=get_useLocale, fset=set_useLocale)
def get_useMathText(self):
return self._useMathText
def set_useMathText(self, val):
if val is None:
self._useMathText = rcParams['axes.formatter.use_mathtext']
else:
self._useMathText = val
useMathText = property(fget=get_useMathText, fset=set_useMathText)
def fix_minus(self, s):
"""
Replace hyphens with a unicode minus.
"""
if rcParams['text.usetex'] or not rcParams['axes.unicode_minus']:
return s
else:
return s.replace('-', '\N{MINUS SIGN}')
def __call__(self, x, pos=None):
"""
Return the format for tick value `x` at position `pos`.
"""
if len(self.locs) == 0:
return ''
else:
s = self.pprint_val(x)
return self.fix_minus(s)
def set_scientific(self, b):
"""
Turn scientific notation on or off.
.. seealso:: Method :meth:`set_powerlimits`
"""
self._scientific = bool(b)
def set_powerlimits(self, lims):
"""
Sets size thresholds for scientific notation.
``lims`` is a two-element sequence containing the powers of 10
that determine the switchover threshold. Numbers below
``10**lims[0]`` and above ``10**lims[1]`` will be displayed in
scientific notation.
For example, ``formatter.set_powerlimits((-3, 4))`` sets the
pre-2007 default in which scientific notation is used for
numbers less than 1e-3 or greater than 1e4.
.. seealso:: Method :meth:`set_scientific`
"""
if len(lims) != 2:
raise ValueError("'lims' must be a sequence of length 2")
self._powerlimits = lims
def format_data_short(self, value):
"""
Return a short formatted string representation of a number.
"""
if self._useLocale:
return locale.format_string('%-12g', (value,))
else:
return '%-12g' % value
def format_data(self, value):
"""
Return a formatted string representation of a number.
"""
if self._useLocale:
s = locale.format_string('%1.10e', (value,))
else:
s = '%1.10e' % value
s = self._formatSciNotation(s)
return self.fix_minus(s)
def get_offset(self):
"""
Return scientific notation, plus offset.
"""
if len(self.locs) == 0:
return ''
s = ''
if self.orderOfMagnitude or self.offset:
offsetStr = ''
sciNotStr = ''
if self.offset:
offsetStr = self.format_data(self.offset)
if self.offset > 0:
offsetStr = '+' + offsetStr
if self.orderOfMagnitude:
if self._usetex or self._useMathText:
sciNotStr = self.format_data(10 ** self.orderOfMagnitude)
else:
sciNotStr = '1e%d' % self.orderOfMagnitude
if self._useMathText:
if sciNotStr != '':
sciNotStr = r'\times%s' % _mathdefault(sciNotStr)
s = ''.join(('$', sciNotStr, _mathdefault(offsetStr), '$'))
elif self._usetex:
if sciNotStr != '':
sciNotStr = r'\times%s' % sciNotStr
s = ''.join(('$', sciNotStr, offsetStr, '$'))
else:
s = ''.join((sciNotStr, offsetStr))
return self.fix_minus(s)
def set_locs(self, locs):
"""
Set the locations of the ticks.
"""
self.locs = locs
if len(self.locs) > 0:
vmin, vmax = self.axis.get_view_interval()
d = abs(vmax - vmin)
if self._useOffset:
self._compute_offset()
self._set_orderOfMagnitude(d)
self._set_format(vmin, vmax)
def _compute_offset(self):
locs = self.locs
if locs is None or not len(locs):
self.offset = 0
return
# Restrict to visible ticks.
vmin, vmax = sorted(self.axis.get_view_interval())
locs = np.asarray(locs)
locs = locs[(vmin <= locs) & (locs <= vmax)]
if not len(locs):
self.offset = 0
return
lmin, lmax = locs.min(), locs.max()
# Only use offset if there are at least two ticks and every tick has
# the same sign.
if lmin == lmax or lmin <= 0 <= lmax:
self.offset = 0
return
# min, max comparing absolute values (we want division to round towards
# zero so we work on absolute values).
abs_min, abs_max = sorted([abs(float(lmin)), abs(float(lmax))])
sign = math.copysign(1, lmin)
# What is the smallest power of ten such that abs_min and abs_max are
# equal up to that precision?
# Note: Internally using oom instead of 10 ** oom avoids some numerical
# accuracy issues.
oom_max = np.ceil(math.log10(abs_max))
oom = 1 + next(oom for oom in itertools.count(oom_max, -1)
if abs_min // 10 ** oom != abs_max // 10 ** oom)
if (abs_max - abs_min) / 10 ** oom <= 1e-2:
# Handle the case of straddling a multiple of a large power of ten
# (relative to the span).
# What is the smallest power of ten such that abs_min and abs_max
# are no more than 1 apart at that precision?
oom = 1 + next(oom for oom in itertools.count(oom_max, -1)
if abs_max // 10 ** oom - abs_min // 10 ** oom > 1)
# Only use offset if it saves at least _offset_threshold digits.
n = self._offset_threshold - 1
self.offset = (sign * (abs_max // 10 ** oom) * 10 ** oom
if abs_max // 10 ** oom >= 10**n
else 0)
def _set_orderOfMagnitude(self, range):
# if scientific notation is to be used, find the appropriate exponent
# if using an numerical offset, find the exponent after applying the
# offset
if not self._scientific:
self.orderOfMagnitude = 0
return
locs = np.abs(self.locs)
if self.offset:
oom = math.floor(math.log10(range))
else:
if locs[0] > locs[-1]:
val = locs[0]
else:
val = locs[-1]
if val == 0:
oom = 0
else:
oom = math.floor(math.log10(val))
if oom <= self._powerlimits[0]:
self.orderOfMagnitude = oom
elif oom >= self._powerlimits[1]:
self.orderOfMagnitude = oom
else:
self.orderOfMagnitude = 0
def _set_format(self, vmin, vmax):
# set the format string to format all the ticklabels
if len(self.locs) < 2:
# Temporarily augment the locations with the axis end points.
_locs = list(self.locs) + [vmin, vmax]
else:
_locs = self.locs
locs = (np.asarray(_locs) - self.offset) / 10. ** self.orderOfMagnitude
loc_range = np.ptp(locs)
# Curvilinear coordinates can yield two identical points.
if loc_range == 0:
loc_range = np.max(np.abs(locs))
# Both points might be zero.
if loc_range == 0:
loc_range = 1
if len(self.locs) < 2:
# We needed the end points only for the loc_range calculation.
locs = locs[:-2]
loc_range_oom = int(math.floor(math.log10(loc_range)))
# first estimate:
sigfigs = max(0, 3 - loc_range_oom)
# refined estimate:
thresh = 1e-3 * 10 ** loc_range_oom
while sigfigs >= 0:
if np.abs(locs - np.round(locs, decimals=sigfigs)).max() < thresh:
sigfigs -= 1
else:
break
sigfigs += 1
self.format = '%1.' + str(sigfigs) + 'f'
if self._usetex:
self.format = '$%s$' % self.format
elif self._useMathText:
self.format = '$%s$' % _mathdefault(self.format)
def pprint_val(self, x):
xp = (x - self.offset) / (10. ** self.orderOfMagnitude)
if np.abs(xp) < 1e-8:
xp = 0
if self._useLocale:
return locale.format_string(self.format, (xp,))
else:
return self.format % xp
def _formatSciNotation(self, s):
# transform 1e+004 into 1e4, for example
if self._useLocale:
decimal_point = locale.localeconv()['decimal_point']
positive_sign = locale.localeconv()['positive_sign']
else:
decimal_point = '.'
positive_sign = '+'
tup = s.split('e')
try:
significand = tup[0].rstrip('0').rstrip(decimal_point)
sign = tup[1][0].replace(positive_sign, '')
exponent = tup[1][1:].lstrip('0')
if self._useMathText or self._usetex:
if significand == '1' and exponent != '':
# reformat 1x10^y as 10^y
significand = ''
if exponent:
exponent = '10^{%s%s}' % (sign, exponent)
if significand and exponent:
return r'%s{\times}%s' % (significand, exponent)
else:
return r'%s%s' % (significand, exponent)
else:
s = ('%se%s%s' % (significand, sign, exponent)).rstrip('e')
return s
except IndexError:
return s
class LogFormatter(Formatter):
"""
Base class for formatting ticks on a log or symlog scale.
It may be instantiated directly, or subclassed.
Parameters
----------
base : float, optional, default: 10.
Base of the logarithm used in all calculations.
labelOnlyBase : bool, optional, default: False
If True, label ticks only at integer powers of base.
This is normally True for major ticks and False for
minor ticks.
minor_thresholds : (subset, all), optional, default: (1, 0.4)
If labelOnlyBase is False, these two numbers control
the labeling of ticks that are not at integer powers of
base; normally these are the minor ticks. The controlling
parameter is the log of the axis data range. In the typical
case where base is 10 it is the number of decades spanned
by the axis, so we can call it 'numdec'. If ``numdec <= all``,
all minor ticks will be labeled. If ``all < numdec <= subset``,
then only a subset of minor ticks will be labeled, so as to
avoid crowding. If ``numdec > subset`` then no minor ticks will
be labeled.
linthresh : None or float, optional, default: None
If a symmetric log scale is in use, its ``linthresh``
parameter must be supplied here.
Notes
-----
The `set_locs` method must be called to enable the subsetting
logic controlled by the ``minor_thresholds`` parameter.
In some cases such as the colorbar, there is no distinction between
major and minor ticks; the tick locations might be set manually,
or by a locator that puts ticks at integer powers of base and
at intermediate locations. For this situation, disable the
minor_thresholds logic by using ``minor_thresholds=(np.inf, np.inf)``,
so that all ticks will be labeled.
To disable labeling of minor ticks when 'labelOnlyBase' is False,
use ``minor_thresholds=(0, 0)``. This is the default for the
"classic" style.
Examples
--------
To label a subset of minor ticks when the view limits span up
to 2 decades, and all of the ticks when zoomed in to 0.5 decades
or less, use ``minor_thresholds=(2, 0.5)``.
To label all minor ticks when the view limits span up to 1.5
decades, use ``minor_thresholds=(1.5, 1.5)``.
"""
def __init__(self, base=10.0, labelOnlyBase=False,
minor_thresholds=None,
linthresh=None):
self._base = float(base)
self.labelOnlyBase = labelOnlyBase
if minor_thresholds is None:
if rcParams['_internal.classic_mode']:
minor_thresholds = (0, 0)
else:
minor_thresholds = (1, 0.4)
self.minor_thresholds = minor_thresholds
self._sublabels = None
self._linthresh = linthresh
def base(self, base):
"""
change the `base` for labeling.
.. warning::
Should always match the base used for :class:`LogLocator`
"""
self._base = base
def label_minor(self, labelOnlyBase):
"""
Switch minor tick labeling on or off.
Parameters
----------
labelOnlyBase : bool
If True, label ticks only at integer powers of base.
"""
self.labelOnlyBase = labelOnlyBase
def set_locs(self, locs=None):
"""
Use axis view limits to control which ticks are labeled.
The ``locs`` parameter is ignored in the present algorithm.
"""
if np.isinf(self.minor_thresholds[0]):
self._sublabels = None
return
# Handle symlog case:
linthresh = self._linthresh
if linthresh is None:
try:
linthresh = self.axis.get_transform().linthresh
except AttributeError:
pass
vmin, vmax = self.axis.get_view_interval()
if vmin > vmax:
vmin, vmax = vmax, vmin
if linthresh is None and vmin <= 0:
# It's probably a colorbar with
# a format kwarg setting a LogFormatter in the manner
# that worked with 1.5.x, but that doesn't work now.
self._sublabels = set((1,)) # label powers of base
return
b = self._base
if linthresh is not None: # symlog
# Only compute the number of decades in the logarithmic part of the
# axis
numdec = 0
if vmin < -linthresh:
rhs = min(vmax, -linthresh)
numdec += math.log(vmin / rhs) / math.log(b)
if vmax > linthresh:
lhs = max(vmin, linthresh)
numdec += math.log(vmax / lhs) / math.log(b)
else:
vmin = math.log(vmin) / math.log(b)
vmax = math.log(vmax) / math.log(b)
numdec = abs(vmax - vmin)
if numdec > self.minor_thresholds[0]:
# Label only bases
self._sublabels = {1}
elif numdec > self.minor_thresholds[1]:
# Add labels between bases at log-spaced coefficients;
# include base powers in case the locations include
# "major" and "minor" points, as in colorbar.
c = np.logspace(0, 1, int(b)//2 + 1, base=b)
self._sublabels = set(np.round(c))
# For base 10, this yields (1, 2, 3, 4, 6, 10).
else:
# Label all integer multiples of base**n.
self._sublabels = set(np.arange(1, b + 1))
def _num_to_string(self, x, vmin, vmax):
if x > 10000:
s = '%1.0e' % x
elif x < 1:
s = '%1.0e' % x
else:
s = self.pprint_val(x, vmax - vmin)
def __call__(self, x, pos=None):
"""
Return the format for tick val `x`.
"""
if x == 0.0: # Symlog
return '0'
sign = np.sign(x)
x = abs(x)
b = self._base
# only label the decades
fx = math.log(x) / math.log(b)
is_x_decade = is_close_to_int(fx)