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"""
Tick locating and formatting
============================
This module contains classes for configuring tick locating and formatting.
Generic tick locators and formatters are provided, as well as domain specific
custom ones.
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.
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:
======================= =======================================================
`AutoLocator` `MaxNLocator` with simple defaults. This is the default
tick locator for most plotting.
`MaxNLocator` Finds up to a max number of intervals with ticks at
nice locations.
`LinearLocator` Space ticks evenly from min to max.
`LogLocator` Space ticks logarithmically from min to max.
`MultipleLocator` Ticks and range are a multiple of base; either integer
or float.
`FixedLocator` Tick locations are fixed.
`IndexLocator` Locator for index plots (e.g., where
``x = range(len(y))``).
`NullLocator` No ticks.
`SymmetricalLogLocator` Locator for use with with the symlog norm; works like
`LogLocator` for the part outside of the threshold and
adds 0 if inside the limits.
`LogitLocator` Locator for logit scaling.
`AutoMinorLocator` Locator for minor ticks when the axis is linear and the
major ticks are uniformly spaced. Subdivides the major
tick interval into a specified number of minor
intervals, defaulting to 4 or 5 depending on the major
interval.
======================= =======================================================
There are a number of locators specialized for date locations - see
the :mod:`.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(xmajor_locator)
ax.xaxis.set_minor_locator(xminor_locator)
ax.yaxis.set_major_locator(ymajor_locator)
ax.yaxis.set_minor_locator(yminor_locator)
The default minor locator is `NullLocator`, i.e., no minor ticks on by default.
.. note::
`Locator` instances should not be used with more than one
`~matplotlib.axis.Axis` or `~matplotlib.axes.Axes`. So instead of::
locator = MultipleLocator(5)
ax.xaxis.set_major_locator(locator)
ax2.xaxis.set_major_locator(locator)
do the following instead::
ax.xaxis.set_major_locator(MultipleLocator(5))
ax2.xaxis.set_major_locator(MultipleLocator(5))
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.
========================= =====================================================
`NullFormatter` No labels on the ticks.
`FixedFormatter` Set the strings manually for the labels.
`FuncFormatter` User defined function sets the labels.
`StrMethodFormatter` Use string `format` method.
`FormatStrFormatter` Use an old-style sprintf format string.
`ScalarFormatter` Default formatter for scalars: autopick the format
string.
`LogFormatter` Formatter for log axes.
`LogFormatterExponent` Format values for log axis using
``exponent = log_base(value)``.
`LogFormatterMathtext` Format values for log axis using
``exponent = log_base(value)`` using Math text.
`LogFormatterSciNotation` Format values for log axis using scientific notation.
`LogitFormatter` Probability formatter.
`EngFormatter` Format labels in engineering notation.
`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(xmajor_formatter)
ax.xaxis.set_minor_formatter(xminor_formatter)
ax.yaxis.set_major_formatter(ymajor_formatter)
ax.yaxis.set_minor_formatter(yminor_formatter)
In addition to a `.Formatter` instance, `~.Axis.set_major_formatter` and
`~.Axis.set_minor_formatter` also accept a ``str`` or function. ``str`` input
will be internally replaced with an autogenerated `.StrMethodFormatter` with
the input ``str``. For function input, a `.FuncFormatter` with the input
function will be generated and used.
See :doc:`/gallery/ticks/major_minor_demo` 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.
"""
import itertools
import logging
import locale
import math
from numbers import Integral
import numpy as np
import matplotlib as mpl
from matplotlib import _api, cbook
from matplotlib import transforms as mtransforms
_log = logging.getLogger(__name__)
__all__ = ('TickHelper', 'Formatter', 'FixedFormatter',
'NullFormatter', 'FuncFormatter', 'FormatStrFormatter',
'StrMethodFormatter', 'ScalarFormatter', 'LogFormatter',
'LogFormatterExponent', 'LogFormatterMathtext',
'LogFormatterSciNotation',
'LogitFormatter', 'EngFormatter', 'PercentFormatter',
'Locator', 'IndexLocator', 'FixedLocator', 'NullLocator',
'LinearLocator', 'LogLocator', 'AutoLocator',
'MultipleLocator', 'MaxNLocator', 'AutoMinorLocator',
'SymmetricalLogLocator', 'LogitLocator')
class _DummyAxis:
__name__ = "dummy"
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:
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)
@_api.deprecated("3.5", alternative=".axis.set_view_interval")
def set_view_interval(self, vmin, vmax):
self.axis.set_view_interval(vmin, vmax)
@_api.deprecated("3.5", alternative=".axis.set_data_interval")
def set_data_interval(self, vmin, vmax):
self.axis.set_data_interval(vmin, vmax)
@_api.deprecated(
"3.5",
alternative=".axis.set_view_interval and .axis.set_data_interval")
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_ticks(self, values):
"""Return the tick labels for all the ticks at once."""
self.set_locs(values)
return [self(value, i) for i, value in enumerate(values)]
def format_data(self, value):
"""
Return 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):
"""
Set the locations of the ticks.
This method is called before computing the tick labels because some
formatters need to know all tick locations to do so.
"""
self.locs = locs
@staticmethod
def fix_minus(s):
"""
Some classes may want to replace a hyphen for minus with the proper
unicode symbol (U+2212) for typographical correctness. This is a
helper method to perform such a replacement when it is enabled via
:rc:`axes.unicode_minus`.
"""
return (s.replace('-', '\N{MINUS SIGN}')
if mpl.rcParams['axes.unicode_minus']
else s)
def _set_locator(self, locator):
"""Subclasses may want to override this to set a locator."""
pass
class NullFormatter(Formatter):
"""Always return the empty string."""
def __call__(self, x, pos=None):
# docstring inherited
return ''
class FixedFormatter(Formatter):
"""
Return fixed strings for tick labels based only on position, not value.
.. note::
`.FixedFormatter` should only be used together with `.FixedLocator`.
Otherwise, the labels may end up in unexpected positions.
"""
def __init__(self, seq):
"""Set the sequence *seq* of strings that will be used for labels."""
self.seq = seq
self.offset_string = ''
def __call__(self, x, pos=None):
"""
Return 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
self.offset_string = ""
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)
def get_offset(self):
return self.offset_string
def set_offset_string(self, ofs):
self.offset_string = ofs
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.
Negative numeric values will use a dash not a unicode minus,
use mathtext to get a unicode minus by wrappping the format specifier
with $ (e.g. "$%g$").
"""
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 tick value must be labeled *x* and the field used
for the tick 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 ScalarFormatter(Formatter):
"""
Format tick values as a number.
Parameters
----------
useOffset : bool or float, default: :rc:`axes.formatter.useoffset`
Whether to use offset notation. See `.set_useOffset`.
useMathText : bool, default: :rc:`axes.formatter.use_mathtext`
Whether to use fancy math formatting. See `.set_useMathText`.
useLocale : bool, default: :rc:`axes.formatter.use_locale`.
Whether to use locale settings for decimal sign and positive sign.
See `.set_useLocale`.
Notes
-----
In addition to the parameters above, the formatting of scientific vs.
floating point representation can be configured via `.set_scientific`
and `.set_powerlimits`).
**Offset notation and scientific notation**
Offset notation and scientific notation look quite similar at first sight.
Both split some information from the formatted tick values and display it
at the end of the axis.
- The scientific notation splits up the order of magnitude, i.e. a
multiplicative scaling factor, e.g. ``1e6``.
- The offset notation separates an additive constant, e.g. ``+1e6``. The
offset notation label is always prefixed with a ``+`` or ``-`` sign
and is thus distinguishable from the order of magnitude label.
The following plot with x limits ``1_000_000`` to ``1_000_010`` illustrates
the different formatting. Note the labels at the right edge of the x axis.
.. plot::
lim = (1_000_000, 1_000_010)
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, gridspec_kw={'hspace': 2})
ax1.set(title='offset_notation', xlim=lim)
ax2.set(title='scientific notation', xlim=lim)
ax2.xaxis.get_major_formatter().set_useOffset(False)
ax3.set(title='floating point notation', xlim=lim)
ax3.xaxis.get_major_formatter().set_useOffset(False)
ax3.xaxis.get_major_formatter().set_scientific(False)
"""
def __init__(self, useOffset=None, useMathText=None, useLocale=None):
if useOffset is None:
useOffset = mpl.rcParams['axes.formatter.useoffset']
self._offset_threshold = \
mpl.rcParams['axes.formatter.offset_threshold']
self.set_useOffset(useOffset)
self._usetex = mpl.rcParams['text.usetex']
if useMathText is None:
useMathText = mpl.rcParams['axes.formatter.use_mathtext']
if useMathText is False:
try:
ufont = mpl.font_manager.findfont(
mpl.font_manager.FontProperties(
mpl.rcParams["font.family"]
),
fallback_to_default=False,
)
except ValueError:
ufont = None
if ufont == str(cbook._get_data_path("fonts/ttf/cmr10.ttf")):
_api.warn_external(
"cmr10 font should ideally be used with "
"mathtext, set axes.formatter.use_mathtext to True"
)
self.set_useMathText(useMathText)
self.orderOfMagnitude = 0
self.format = ''
self._scientific = True
self._powerlimits = mpl.rcParams['axes.formatter.limits']
if useLocale is None:
useLocale = mpl.rcParams['axes.formatter.use_locale']
self._useLocale = useLocale
def get_useOffset(self):
"""
Return whether automatic mode for offset notation is active.
This returns True if ``set_useOffset(True)``; it returns False if an
explicit offset was set, e.g. ``set_useOffset(1000)``.
See Also
--------
ScalarFormatter.set_useOffset
"""
return self._useOffset
def set_useOffset(self, val):
"""
Set whether to use offset notation.
When formatting a set numbers whose value is large compared to their
range, the formatter can separate an additive constant. This can
shorten the formatted numbers so that they are less likely to overlap
when drawn on an axis.
Parameters
----------
val : bool or float
- If False, do not use offset notation.
- If True (=automatic mode), use offset notation if it can make
the residual numbers significantly shorter. The exact behavior
is controlled by :rc:`axes.formatter.offset_threshold`.
- If a number, force an offset of the given value.
Examples
--------
With active offset notation, the values
``100_000, 100_002, 100_004, 100_006, 100_008``
will be formatted as ``0, 2, 4, 6, 8`` plus an offset ``+1e5``, which
is written to the edge of the axis.
"""
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 whether locale settings are used for formatting.
See Also
--------
ScalarFormatter.set_useLocale
"""
return self._useLocale
def set_useLocale(self, val):
"""
Set whether to use locale settings for decimal sign and positive sign.
Parameters
----------
val : bool or None
*None* resets to :rc:`axes.formatter.use_locale`.
"""
if val is None:
self._useLocale = mpl.rcParams['axes.formatter.use_locale']
else:
self._useLocale = val
useLocale = property(fget=get_useLocale, fset=set_useLocale)
def _format_maybe_minus_and_locale(self, fmt, arg):
"""
Format *arg* with *fmt*, applying unicode minus and locale if desired.
"""
return self.fix_minus(locale.format_string(fmt, (arg,), True)
if self._useLocale else fmt % arg)
def get_useMathText(self):
"""
Return whether to use fancy math formatting.
See Also
--------
ScalarFormatter.set_useMathText
"""
return self._useMathText
def set_useMathText(self, val):
r"""
Set whether to use fancy math formatting.
If active, scientific notation is formatted as :math:`1.2 \times 10^3`.
Parameters
----------
val : bool or None
*None* resets to :rc:`axes.formatter.use_mathtext`.
"""
if val is None:
self._useMathText = mpl.rcParams['axes.formatter.use_mathtext']
else:
self._useMathText = val
useMathText = property(fget=get_useMathText, fset=set_useMathText)
def __call__(self, x, pos=None):
"""
Return the format for tick value *x* at position *pos*.
"""
if len(self.locs) == 0:
return ''
else:
xp = (x - self.offset) / (10. ** self.orderOfMagnitude)
if abs(xp) < 1e-8:
xp = 0
return self._format_maybe_minus_and_locale(self.format, xp)
def set_scientific(self, b):
"""
Turn scientific notation on or off.
See Also
--------
ScalarFormatter.set_powerlimits
"""
self._scientific = bool(b)
def set_powerlimits(self, lims):
r"""
Set size thresholds for scientific notation.
Parameters
----------
lims : (int, int)
A tuple *(min_exp, max_exp)* containing the powers of 10 that
determine the switchover threshold. For a number representable as
:math:`a \times 10^\mathrm{exp}`` with :math:`1 <= |a| < 10`,
scientific notation will be used if ``exp <= min_exp`` or
``exp >= max_exp``.
The default limits are controlled by :rc:`axes.formatter.limits`.
In particular numbers with *exp* equal to the thresholds are
written in scientific notation.
Typically, *min_exp* will be negative and *max_exp* will be
positive.
For example, ``formatter.set_powerlimits((-3, 4))`` will provide
the following formatting:
:math:`1 \times 10^{-3}, 9.9 \times 10^{-3}, 0.01,`
:math:`9999, 1 \times 10^4`.
See Also
--------
ScalarFormatter.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):
# docstring inherited
if isinstance(value, np.ma.MaskedArray) and value.mask:
return ""
if isinstance(value, Integral):
fmt = "%d"
else:
if getattr(self.axis, "__name__", "") in ["xaxis", "yaxis"]:
if self.axis.__name__ == "xaxis":
axis_trf = self.axis.axes.get_xaxis_transform()
axis_inv_trf = axis_trf.inverted()
screen_xy = axis_trf.transform((value, 0))
neighbor_values = axis_inv_trf.transform(
screen_xy + [[-1, 0], [+1, 0]])[:, 0]
else: # yaxis:
axis_trf = self.axis.axes.get_yaxis_transform()
axis_inv_trf = axis_trf.inverted()
screen_xy = axis_trf.transform((0, value))
neighbor_values = axis_inv_trf.transform(
screen_xy + [[0, -1], [0, +1]])[:, 1]
delta = abs(neighbor_values - value).max()
else:
# Rough approximation: no more than 1e4 divisions.
a, b = self.axis.get_view_interval()
delta = (b - a) / 1e4
fmt = "%-#.{}g".format(cbook._g_sig_digits(value, delta))
return self._format_maybe_minus_and_locale(fmt, value)
def format_data(self, value):
# docstring inherited
e = math.floor(math.log10(abs(value)))
s = round(value / 10**e, 10)
exponent = self._format_maybe_minus_and_locale("%d", e)
significand = self._format_maybe_minus_and_locale(
"%d" if s % 1 == 0 else "%1.10f", s)
if e == 0:
return significand
elif self._useMathText or self._usetex:
exponent = "10^{%s}" % exponent
return (exponent if s == 1 # reformat 1x10^y as 10^y
else rf"{significand} \times {exponent}")
else:
return f"{significand}e{exponent}"
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 or self._usetex:
if sciNotStr != '':
sciNotStr = r'\times\mathdefault{%s}' % sciNotStr
s = r'$%s\mathdefault{%s}$' % (sciNotStr, offsetStr)
else:
s = ''.join((sciNotStr, offsetStr))
return self.fix_minus(s)
def set_locs(self, locs):
# docstring inherited
self.locs = locs
if len(self.locs) > 0:
if self._useOffset:
self._compute_offset()
self._set_order_of_magnitude()
self._set_format()
def _compute_offset(self):
locs = self.locs
# 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_order_of_magnitude(self):
# if scientific notation is to be used, find the appropriate exponent
# if using an numerical offset, find the exponent after applying the
# offset. When lower power limit = upper <> 0, use provided exponent.
if not self._scientific:
self.orderOfMagnitude = 0
return
if self._powerlimits[0] == self._powerlimits[1] != 0:
# fixed scaling when lower power limit = upper <> 0.
self.orderOfMagnitude = self._powerlimits[0]
return
# restrict to visible ticks
vmin, vmax = sorted(self.axis.get_view_interval())
locs = np.asarray(self.locs)
locs = locs[(vmin <= locs) & (locs <= vmax)]
locs = np.abs(locs)
if not len(locs):
self.orderOfMagnitude = 0
return
if self.offset:
oom = math.floor(math.log10(vmax - vmin))
else:
val = locs.max()
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):
# set the format string to format all the ticklabels
if len(self.locs) < 2:
# Temporarily augment the locations with the axis end points.
_locs = [*self.locs, *self.axis.get_view_interval()]
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 or self._useMathText:
self.format = r'$\mathdefault{%s}$' % self.format
class LogFormatter(Formatter):
"""
Base class for formatting ticks on a log or symlog scale.
It may be instantiated directly, or subclassed.
Parameters
----------
base : float, default: 10.
Base of the logarithm used in all calculations.
labelOnlyBase : bool, 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), 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, 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 mpl.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 = {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.geomspace(1, b, int(b)//2 + 1)
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)
return s
def __call__(self, x, pos=None):
# docstring inherited
if x == 0.0: # Symlog
return '0'
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)
exponent = round(fx) if is_x_decade else np.floor(fx)
coeff = round(b ** (fx - exponent))
if self.labelOnlyBase and not is_x_decade:
return ''
if self._sublabels is not None and coeff not in self._sublabels:
return ''
vmin, vmax = self.axis.get_view_interval()
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