8000 ENH: Added percent formatter and tests · matplotlib/matplotlib@06d6f41 · GitHub
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ENH: Added percent formatter and tests
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‎doc/users/whats_new/percent_formatter.rst

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Added `matplotlib.ticker.PercentFormatter`
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------------------------------------------
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The new formatter has some nice features like being able to convert from
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arbitrary data scales to percents, a customizable percent symbol and
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either automatic or manual control over the decimal points.

‎lib/matplotlib/tests/test_ticker.py

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@@ -366,6 +366,39 @@ def test_formatstrformatter():
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tmp_form = mticker.StrMethodFormatter('{x:05d}')
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nose.tools.assert_equal('00002', tmp_form(2))
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def _percent_format_helper(mx, decimals, symbol, x, d, expected):
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form = mticker.PercentFormatter(mx, decimals, symbol)
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nose.tools.assert_equal(form.format_pct(x, d), expected)
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def test_percentformatter():
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test_cases = (
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# Check explicitly set decimals over different intervals and values
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(100 10000 , 0, '%', 120, 100, '120%'),
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(100, 0, '%', 100, 90, '100%'),
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(100, 0, '%', 90, 50, '90%'),
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(100, 0, '%', 1.7, 40, '2%'),
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(100, 1, '%', 90.0, 100, '90.0%'),
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(100, 1, '%', 80.1, 90, '80.1%'),
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(100, 1, '%', 70.23, 50, '70.2%'),
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# 60.554 instead of 60.55: see https://bugs.python.org/issue5118
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(100, 1, '%', 60.554, 40, '60.6%'),
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# Check auto decimals over different intervals and values
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(100, None, '%', 95, 1, '95.00%'),
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(1.0, None, '%', 3, 6, '300%'),
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(17.0, None, '%', 1, 8.5, '6%'),
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(17.0, None, '%', 1, 8.4, '5.9%'),
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(5, None, '%', -100, 0.000001, '-2000.00000%'),
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# Check percent symbol
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(1.0, 2, None, 1.2, 100, '120.00'),
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(75, 3, '', 50, 100, '66.667'),
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(42, None, '^^Foobar$$', 21, 12, '50.0^^Foobar$$'),
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)
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for mx, decimals, symbol, x, d, expected in test_cases:
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yield _percent_format_helper, mx, decimals, symbol, x, d, expected
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if __name__ == '__main__':
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import nose
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nose.runmodule(argv=['-s', '--with-doctest'], exit=False)

‎lib/matplotlib/ticker.py

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:class:`LogFormatter`
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formatter for log axes
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:class:`PercentFormatter`
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Format labels as a percentage
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You can derive your own formatter from the Formatter base class by
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simply overriding the ``__call__`` method. The formatter class has access
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from __future__ import (absolute_import, division, print_function,
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unicode_literals)
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__all__ = ('TickHelper', 'Formatter', 'FixedFormatter',
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'NullFormatter', 'FuncFormatter', 'FormatStrFormatter',
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'StrMethodFormatter', 'ScalarFormatter', 'LogFormatter',
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'LogFormatterExponent', 'LogFormatterMathtext',
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'LogitFormatter', 'EngFormatter', 'PercentFormatter',
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'Locator', 'IndexLocator', 'FixedLocator', 'NullLocator',
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'LinearLocator', 'LogLocator', 'AutoLocator',
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'MultipleLocator', 'MaxNLocator', 'AutoMinorLocator',
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'SymmetricalLogLocator')
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from matplotlib.externals import six
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import decimal
@@ -973,6 +987,87 @@ def format_eng(self, num):
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return formatted.strip()
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class PercentFormatter(Formatter):
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"""
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Format numbers as a percentage.
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How the number is converted into a percentage is determined by the
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`max` parameter. `max` is the data value that corresponds to 100%.
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Percentages are computed as ``x / max * 100``. So if the data is
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already scaled to be percentages, `max` will be 100. Another common
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situation is where `max` is 1.0.
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"""
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def __init__(self, max=100, decimals=None, symbol='%'):
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"""
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Initializes the formatter.
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`max` is the data value that corresponds to 100%. `symbol` is
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a string which will be appended to the label. It may be `None`
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or empty to indicate that no symbol should be used. `decimals`
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is the number of decimal places to place after the
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"""
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self.max = max + 0.0
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self.decimals = decimals
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self.symbol = symbol
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def __call__(self, x, pos=None):
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"""
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Formats the tick as a percentage with the appropriate scaling.
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"""
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xmin, xmax = self.axis.get_view_interval()
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d = abs(xmax - xmin)
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return self.fix_minus(format_pct(x, d))
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def format_pct(self, x, d):
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"""
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Formats the number as a percentage number with the correct
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number of decimals and adds the percent symbol, if any.
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If `self.decimals` is `None`, the number of digits after the
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decimal point is set based on the width of the domain `d` as
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follows:
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+-------+----------+------------------------+
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| d | decimals | sample |
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+-------+----------+------------------------+
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+ >50 | 0 | ``x = 34.5`` => 34% |
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+-------+----------+------------------------+
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| >5 | 1 | ``x = 34.5`` => 34.5% |
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+-------+----------+------------------------+
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| >0.5 | 2 | ``x = 34.5`` => 34.50% |
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+-------+----------+------------------------+
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| ... | ... | ... |
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+-------+----------+------------------------+
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This method will not be very good for tiny ranges or extremely
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large ranges. It assumes that the values on the chart are
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percentages displayed on a reasonable scale.
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"""
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x = self.convert_to_pct(x)
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if self.decimals is None:
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# Luckily Python's built-in `ceil` rounds to +inf, not away
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# from zero. This is very important since the equation for
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# `decimals` starts out as `d > 0.5 * 10**(2 - decimals)`
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# and ends up with `decimals > 2 - log10(2 * d)`.
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d = self.convert_to_pct(d) # d is a difference, so this works fine
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decimals = math.ceil(2.0 - math.log10(2.0 * d))
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if decimals > 5:
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decimals = 5
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elif decimals < 0:
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decimals = 0
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else:
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decimals = self.decimals
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s = '{x:0.{decimals}f}'.format(x=x, decimals=int(decimals))
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if self.symbol:
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return s + self.symbol
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return s
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def convert_to_pct(self, x):
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return 100.0 * (x / self.max)
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class Locator(TickHelper):
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"""
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Determine the tick locations;
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return locator
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__all__ = ('TickHelper', 'Formatter', 'FixedFormatter',
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'NullFormatter', 'FuncFormatter', 'FormatStrFormatter',
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'StrMethodFormatter', 'ScalarFormatter', 'LogFormatter',
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'LogFormatterExponent', 'LogFormatterMathtext', 'Locator',
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'IndexLocator', 'FixedLocator', 'NullLocator',
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'LinearLocator', 'LogLocator', 'AutoLocator',
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'MultipleLocator', 'MaxNLocator', 'AutoMinorLocator',
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'SymmetricalLogLocator')

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