"""
The classes here provide support for using custom classes with
matplotlib, eg those that do not expose the array interface but know
how to converter themselves to arrays. It also supoprts classes with
units and units conversion. Use cases include converters for custom
objects, eg a list of datetime objects, as well as for objects that
are unit aware. We don't assume any particular units implementation,
rather a units implementation must provide a ConversionInterface, and
the register with the Registry converter dictionary. For example,
here is a complete implementation which support plotting with native
datetime objects
import matplotlib.units as units
import matplotlib.dates as dates
import matplotlib.ticker as ticker
import datetime
class DateConverter(units.ConversionInterface):
@staticmethod
def convert(value, unit, axis):
'convert value to a scalar or array'
return dates.date2num(value)
@staticmethod
def axisinfo(unit, axis):
'return major and minor tick locators and formatters'
if unit!='date': return None
majloc = dates.AutoDateLocator()
majfmt = dates.AutoDateFormatter(majloc)
return AxisInfo(majloc=majloc,
majfmt=majfmt,
label='date')
@staticmethod
def default_units(x, axis):
'return the default unit for x or None'
return 'date'
# finally we register our object type with a converter
units.registry[datetime.date] = DateConverter()
"""
import numpy as np
from matplotlib.cbook import iterable,is_numlike,is_string_like
class AxisInfo:
'information to support default axis labeling and tick labeling'
def __init__(self, majloc=None, minloc=None,
majfmt=None, minfmt=None, label=None):
"""
majloc and minloc: TickLocators for the major and minor ticks
majfmt and minfmt: TickFormatters for the major and minor ticks
label: the default axis label
If any of the above are None, the axis will simply use the default
"""
self.majloc = majloc
self.minloc = minloc
self.majfmt = majfmt
self.minfmt = minfmt
self.label = label
class ConversionInterface:
"""
The minimal interface for a converter to take custom instances (or
sequences) and convert them to values mpl can use
"""
@staticmethod
def axisinfo(unit, axis):
'return an units.AxisInfo instance for axis with the specified units'
return None
@staticmethod
def default_units(x, axis):
'return the default unit for x or None for the given axis'
return None
@staticmethod
def convert(obj, unit, axis):
"""
convert obj using unit for the specified axis. If obj is a sequence,
return the converted sequence. The ouput must be a sequence of scalars
that can be used by the numpy array layer
"""
return obj
@staticmethod
def is_numlike(x):
"""
The matplotlib datalim, autoscaling, locators etc work with
scalars which are the units converted to floats given the
current unit. The converter may be passed these floats, or
arrays of them, even when units are set. Derived conversion
interfaces may opt to pass plain-ol unitless numbers through
the conversion interface and this is a helper function for
them.
"""
if iterable(x):
for thisx in x:
return is_numlike(thisx)
else:
return is_numlike(x)
class Registry(dict):
"""
register types with conversion interface
"""
def __init__(self):
dict.__init__(self)
self._cached = {}
def get_converter(self, x):
'get the converter interface instance for x, or None'
if not len(self): return None # nothing registered
#DISABLED idx = id(x)
#DISABLED cached = self._cached.get(idx)
#DISABLED if cached is not None: return cached
converter = None
classx = getattr(x, '__class__', None)
if classx is not None:
converter = self.get(classx)
# Check explicity for strings here because they would otherwise
# lead to an infinite recursion, because a single character will
# pass the iterable() check.
if converter is None and iterable(x) and not is_string_like(x):
# if this is anything but an object array, we'll assume
# there are no custom units
if isinstance(x, np.ndarray) and x.dtype != np.object:
return None
for thisx in x:
converter = self.get_converter( thisx )
return converter
#DISABLED self._cached[idx] = converter
return converter
registry = Registry()
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