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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 register with the Registry converter

dictionary and provide 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 units.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()

"""

from decimal import Decimal

from numbers import Number

import numpy as np

from numpy import ma

from matplotlib import cbook

class ConversionError(TypeError):

pass

def _is_natively_supported(x):

"""

Return whether *x* is of a type that Matplotlib natively supports or an

array of objects of such types.

"""

# Matplotlib natively supports all number types except Decimal.

if np.iterable(x):

# Assume lists are homogeneous as other functions in unit system.

for thisx in x:

if thisx is ma.masked:

continue

return isinstance(thisx, Number) and not isinstance(thisx, Decimal)

else:

return isinstance(x, Number) and not isinstance(x, Decimal)

class AxisInfo:

"""

Information to support default axis labeling, tick labeling, and limits.

An instance of this class must be returned by

`ConversionInterface.axisinfo`.

"""

def __init__(self, majloc=None, minloc=None,

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

class ConversionInterface:

"""

The minimal interface for a converter to take custom data types (or

sequences) and convert them to values Matplotlib can use.

"""

@staticmethod

def axisinfo(unit, axis):

"""Return an `.AxisInfo` for the 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 output must

be a sequence of scalars that can be used by the numpy array layer.

"""

return obj

class DecimalConverter(ConversionInterface):

"""Converter for decimal.Decimal data to float."""

@staticmethod

def convert(value, unit, axis):

"""

Convert Decimals to floats.

The *unit* and *axis* arguments are not used.

Parameters

----------

value : decimal.Decimal or iterable

Decimal or list of Decimal need to be converted

"""

if isinstance(value, Decimal):

return float(value)

# value is Iterable[Decimal]

elif isinstance(value, ma.MaskedArray):

return ma.asarray(value, dtype=float)

else:

return np.asarray(value, dtype=float)

# axisinfo and default_units can be inherited as Decimals are Numbers.

class Registry(dict):

"""Register types with conversion interface."""

def get_converter(self, x):

"""Get the converter interface instance for *x*, or None."""

# Unpack in case of e.g. Pandas or xarray object

x = cbook._unpack_to_numpy(x)

if isinstance(x, np.ndarray):

# In case x in a masked array, access the underlying data (only its

# type matters). If x is a regular ndarray, getdata() just returns

# the array itself.

x = np.ma.getdata(x).ravel()

# If there are no elements in x, infer the units from its dtype

if not x.size:

return self.get_converter(np.array([0], dtype=x.dtype))

for cls in type(x).__mro__: # Look up in the cache.

try:

return self[cls]

except KeyError:

pass

try: # If cache lookup fails, look up based on first element...

first = cbook._safe_first_finite(x)

except (TypeError, StopIteration):

pass

else:

# ... and avoid infinite recursion for pathological iterables for

# which indexing returns instances of the same iterable class.

if type(first) is not type(x):

return self.get_converter(first)

return None

registry = Registry()

registry[Decimal] = DecimalConverter()

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