Evans测试

一个模型“Foo”单元类，它根据“单元”支持转换和不同的刻度格式。 这里的“单位”只是一个标量转换因子，但是这个例子表明Matplotlib完全不知道客户端软件包使用哪种单位。

Evans测试示例

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from matplotlib.cbook import iterable
import matplotlib.units as units
import matplotlib.ticker as ticker
import matplotlib.pyplot as plt


class Foo(object):
    def __init__(self, val, unit=1.0):
        self.unit = unit
        self._val = val * unit

    def value(self, unit):
        if unit is None:
            unit = self.unit
        return self._val / unit


class FooConverter(object):
    @staticmethod
    def axisinfo(unit, axis):
        'return the Foo AxisInfo'
        if unit == 1.0 or unit == 2.0:
            return units.AxisInfo(
                majloc=ticker.IndexLocator(8, 0),
                majfmt=ticker.FormatStrFormatter("VAL: %s"),
                label='foo',
                )

        else:
            return None

    @staticmethod
    def convert(obj, unit, axis):
        """
        convert obj using unit.  If obj is a sequence, return the
        converted sequence
        """
        if units.ConversionInterface.is_numlike(obj):
            return obj

        if iterable(obj):
            return [o.value(unit) for o in obj]
        else:
            return obj.value(unit)

    @staticmethod
    def default_units(x, axis):
        'return the default unit for x or None'
        if iterable(x):
            for thisx in x:
                return thisx.unit
        else:
            return x.unit


units.registry[Foo] = FooConverter()

# create some Foos
x = []
for val in range(0, 50, 2):
    x.append(Foo(val, 1.0))

# and some arbitrary y data
y = [i for i in range(len(x))]


fig, (ax1, ax2) = plt.subplots(1, 2)
fig.suptitle("Custom units")
fig.subplots_adjust(bottom=0.2)

# plot specifying units
ax2.plot(x, y, 'o', xunits=2.0)
ax2.set_title("xunits = 2.0")
plt.setp(ax2.get_xticklabels(), rotation=30, ha='right')

# plot without specifying units; will use the None branch for axisinfo
ax1.plot(x, y)  # uses default units
ax1.set_title('default units')
plt.setp(ax1.get_xticklabels(), rotation=30, ha='right')

plt.show()

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