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evans_test.py
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"""
==========
Evans test
==========
A mockup "Foo" units class which supports conversion and different tick
formatting depending on the "unit". Here the "unit" is just a scalar
conversion factor, but this example shows that Matplotlib is entirely agnostic
to what kind of units client packages use.
"""
import numpy as np
import matplotlib.units as units
import matplotlib.ticker as ticker
import matplotlib.pyplot as plt
class Foo:
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(units.ConversionInterface):
@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 np.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 np.iterable(x):
for thisx in x:
return thisx.unit
else:
return x.unit
units.registry[Foo] = FooConverter()
# create some Foos
x = [Foo(val, 1.0) for val in range(0, 50, 2)]
# 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()