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""" The classes here provide support for using custom classes with Matplotlib, e.g., those that do not expose the array interface but know how to convert themselves to arrays. It also supports classes with units and units conversion. Use cases include converters for custom objects, e.g., 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 the register with the Registry converter dictionary and a `ConversionInterface`. For example, here is a complete implementation which supports 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 a datetime 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 the Matplotlib units registry. units.registry[datetime.date] = DateConverter()
"""
""" Information to support default axis labeling, tick labeling, and default limits. An instance of this class must be returned by :meth:`ConversionInterface.axisinfo`. """ majfmt=None, minfmt=None, label=None, default_limits=None): """ Parameters ---------- majloc, minloc : Locator, optional Tick locators for the major and minor ticks. majfmt, minfmt : Formatter, optional Tick formatters for the major and minor ticks. label : str, optional The default axis label. default_limits : optional The default min and max limits of the axis if no data has been plotted.
Notes ----- If any of the above are ``None``, the axis will simply use the default value. """ self.majloc = majloc self.minloc = minloc self.majfmt = majfmt self.minfmt = minfmt self.label = label self.default_limits = default_limits
""" The minimal interface for a converter to take custom data types (or sequences) and convert them to values Matplotlib can use. """ def axisinfo(unit, axis): """ Return an `~units.AxisInfo` instance for the axis with the specified units. """ return None
def default_units(x, axis): """ Return the default unit for *x* or ``None`` for the given axis. """ return None
def convert(obj, unit, axis): """ Convert *obj* using *unit* for the specified *axis*. If *obj* is a sequence, return the converted sequence. The output must be a sequence of scalars that can be used by the numpy array layer. """ return obj
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. """ else:
""" A register that maps types to conversion interfaces. """
""" Get the converter for data that has the same type as *x*. If no converters are registered for *x*, returns ``None``. """
return None # nothing registered # DISABLED idx = id(x) # DISABLED cached = self._cached.get(idx) # DISABLED if cached is not None: return cached
# this unpacks pandas series or dataframes... x = x.values
# If x is an array, look inside the array for data with units # pass the first value of x that is not masked back to # get_converter # some elements are not masked converter = self.get_converter( xravel[np.argmin(xravel.mask)]) return converter # not a masked_array # Make sure we don't recurse forever -- it's possible for # ndarray subclasses to continue to return subclasses and # not ever return a non-subclass for a single element. next_item.shape != x.shape):
# If we haven't found a converter yet, try to get the first element else:
# DISABLED self._cached[idx] = converter
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