"""
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 mpl is
entirely agnostic to what kind of units client packages use
"""
import matplotlib
matplotlib.rcParams['units'] = True
from matplotlib.cbook import iterable
import matplotlib.units as units
import matplotlib.ticker as ticker
from pylab import figure,show
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:
@staticmethod
def axisinfo(unit, axis):
'return the Foo AxisInfo'
if unit==1.0 or unit==2.0:
return units.AxisInfo(
majloc = ticker.IndexLocator( 4, 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) ) ]
# plot specifying units
fig = figure()
fig.subplots_adjust(bottom=0.2)
ax = fig.add_subplot(111)
ax.plot( x, y, 'o', xunits=2.0 )
for label in ax.get_xticklabels():
label.set_rotation(30)
label.set_ha('right')
#fig.savefig('plot1.png')
# plot without specifying units; will use the None branch for axisinfo
fig2 = figure()
ax = fig2.add_subplot(111)
ax.plot( x, y ) # uses default units
#p.savefig('plot2.png')
fig3 = figure()
ax = fig3.add_subplot(111)
ax.plot( x, y, xunits=0.5)
show()
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