matplotlib/lib/matplotlib/ticker.py at v3.11.2 · matplotlib/matplotlib · GitHub

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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:

.. _locators:

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 the symlog norm; works like

`LogLocator` for the part outside of the threshold and

adds 0 if inside the limits.

`AsinhLocator` Locator for use with the asinh norm, attempting to

space ticks approximately uniformly.

`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))

.. _formatters:

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 string

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', 'AsinhLocator', 'LogitLocator')

class _DummyAxis:

__name__ = "dummy"

def __init__(self, minpos=0):

self._data_interval = (0, 1)

self._view_interval = (0, 1)

self._minpos = minpos

def get_view_interval(self):

return self._view_interval

def set_view_interval(self, vmin, vmax):

self._view_interval = (vmin, vmax)

def get_minpos(self):

return self._minpos

def get_data_interval(self):

return self._data_interval

def set_data_interval(self, vmin, vmax):

self._data_interval = (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)

class Formatter(TickHelper):

"""

Create a string based on a tick value and location.

The Formatter provides four formatting methods for different use cases:

- `format_ticks`: The public API for generating tick labels from a set of

tick values.

- `__call__`: The low-level primitive for formatting a single tick value,

potentially in the context of multiple values.

- `format_data`: Context-independent representation of a single value.

Used internally, e.g. for offset and scientific-notation strings.

- `format_data_short`: Concise plain-text representation of a single value

for the interactive mouseover tooltip.

"""

# some classes want to see all the locs to help format

# individual ones

_locs = []

locs = _api.deprecate_privatize_attribute("3.11")

def __call__(self, x, pos=None):

"""

Return the tick label strings for value *x* at tick index *pos*.

This is the low-level formatting primitive for a single tick in

the context of multiple ticks. Any context-dependent state

(e.g. locs, offset, order of magnitude) must already be configured,

typically by a prior call to ``format_ticks`` or ``set_locs``.

*pos* defines the index into ``self.locs`` so that the format can

depend on the location. ``pos=None`` indicates an unspecified

location.

The output may contain mathtext or LaTeX markup.

Subclasses must override this method.

"""

raise NotImplementedError('Derived must override')

def format_ticks(self, values):

"""

Return the tick label strings for all *values*.

This is the public API for generating tick labels. It calls

``set_locs`` to configure context-dependent formatting state before

delegating to ``__call__`` for each individual value.

The output may contain mathtext or LaTeX markup.

Use this method (rather than ``__call__``) whenever formatting a

complete set of tick values, so that formatters which need to see

all tick locations (e.g. to determine precision, offsets, or which

date components to display) can work correctly.

"""

self.set_locs(values)

return [self(value, i) for i, value in enumerate(values)]

def format_data(self, value):

"""

Return the context-independent string representation of a single *value*.

This is used internally, e.g. for constructing offset and

scientific-notation strings. It always formats with ``pos=None``

and should return a context-independent representation

rather than a concise tick label.

The output may contain mathtext or LaTeX markup.

"""

return self.__call__(value)

def format_data_short(self, value):

"""

Return a short string representation of *value* for the mouseover

tooltip (the coordinate display in the interactive figure window).

This should return concise, plain text (no mathtext / LaTeX).

The precision is typically adapted to the current axis resolution

so that neighbouring pixels produce distinguishable labels.

Defaults to `.Formatter.format_data`; subclasses should override

this to provide a plain-text representation that is independent

of the current tick locations.

Note: The mouseover text can be customized by setting the

``Axes.fmt_xdata`` and ``Axes.fmt_ydata`` attributes.

"""

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 (e.g., -1) will use a dash, not a Unicode minus;

use mathtext to get a Unicode minus by wrapping 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 _UnicodeMinusFormat(string.Formatter):

"""

A specialized string formatter so that `.StrMethodFormatter` respects

:rc:`axes.unicode_minus`. This implementation relies on the fact that the

format string is only ever called with kwargs *x* and *pos*, so it blindly

replaces dashes by unicode minuses without further checking.

"""

def format_field(self, value, format_spec):

return Formatter.fix_minus(super().format_field(value, format_spec))

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*.

The formatter will respect :rc:`axes.unicode_minus` when formatting

negative numeric values.

It is typically unnecessary to explicitly construct `.StrMethodFormatter`

objects, as `~.Axis.set_major_formatter` directly accepts the format string

itself.

Examples

--------

>>> formatter = StrMethodFormatter("{x} km")

>>> formatter(10)

"10 km"

"""

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 _UnicodeMinusFormat().format(self.fmt, 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`.

usetex : bool, default: :rc:`text.usetex`

To enable/disable the use of TeX's math mode for rendering the

numbers in the formatter.

.. versionadded:: 3.10

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)

"""

orderOfMagnitude = _api.deprecate_privatize_attribute("3.11")

format = _api.deprecate_privatize_attribute("3.11")

def __init__(self, useOffset=None, useMathText=None, useLocale=None, *,

usetex=None):

useOffset = mpl._val_or_rc(useOffset, 'axes.formatter.useoffset')

self._offset_threshold = mpl.rcParams['axes.formatter.offset_threshold']

self.set_useOffset(useOffset)

self.set_usetex(usetex)

self.set_useMathText(useMathText)

self._orderOfMagnitude = 0

self._format = ''

self._scientific = True

self._powerlimits = mpl.rcParams['axes.formatter.limits']

self.set_useLocale(useLocale)

def get_usetex(self):

"""Return whether TeX's math mode is enabled for rendering."""

return self._usetex

def set_usetex(self, val):

"""Set whether to use TeX's math mode for rendering numbers in the formatter."""

self._usetex = mpl._val_or_rc(val, 'text.usetex')

usetex = property(fget=get_usetex, fset=set_usetex)

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 isinstance(val, bool):

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`.

"""

self._useLocale = mpl._val_or_rc(val, 'axes.formatter.use_locale')

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(

# Escape commas introduced by locale.format_string if using math text,

# but not those present from the beginning in fmt.

(",".join(locale.format_string(part, (arg,), True).replace(",", "{,}")

for part in fmt.split(",")) if self._useMathText

else 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']

if self._useMathText is False:

try:

from matplotlib import font_manager

ufont = font_manager.findfont(

font_manager.FontProperties(

family=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"

)

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 value is np.ma.masked:

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 = f"%-#.{cbook._g_sig_digits(value, delta)}g"

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)

significand = self._format_maybe_minus_and_locale(

"%d" if s % 1 == 0 else "%1.10g", s)

if e == 0:

return significand

exponent = self._format_maybe_minus_and_locale("%d", e)

if 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 ''

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 = fr'${sciNotStr}\mathdefault{{{offsetStr}}}$'

else:

s = ''.join((sciNotStr, offsetStr))

return self.fix_minus(s)

return ''

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 a 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 = f'%1.{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 first number (*subset*) is the largest number of major ticks for

which minor ticks are labeled; e.g., the default, 1, means that minor

ticks are labeled as long as there is no more than 1 major tick. (It

is assumed that major ticks are at integer powers of *base*.)

The second number (*all*) is a threshold, in log-units of the axis

limit range, over which only a subset of the minor ticks are labeled,

so as to avoid crowding; e.g., with the default value (0.4) and the

usual ``base=10``, all minor ticks are shown only if the axis limit

range spans less than 0.4 decades.

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 there are up to 2 major ticks,

and all of the ticks when zoomed in to 0.5 decades or less, use

``minor_thresholds=(2, 0.5)``.

"""

def __init__(self, base=10.0, labelOnlyBase=False,

minor_thresholds=None,

linthresh=None):

self.set_base(base)

self.set_label_minor(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 set_base(self, base):

"""

Change the *base* for labeling.

.. warning::

Should always match the base used for :class:`LogLocator`

"""

self._base = float(base)

def set_label_minor(self, labelOnlyBase):

"""

Switch minor tick labeling on or off.

Parameters

----------

labelOnlyBase : bool

If True, label ticks only at integer powers of base.

View remainder of file in raw view

matplotlib/lib/matplotlib/ticker.py at v3.11.2 · matplotlib/matplotlib · GitHub

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