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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"

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<title>matplotlib.units — Matplotlib 2.2.4 documentation</title>

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<h1>Source code for matplotlib.units</h1><div class="highlight"><pre>

"""

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()

"""

from __future__ import (absolute_import, division, print_function,

unicode_literals)

import six

from matplotlib.cbook import iterable, is_numlike, safe_first_element

import numpy as np

<div class="viewcode-block" id="AxisInfo"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.AxisInfo">[docs]</a>class AxisInfo(object):

"""

Information to support default axis labeling, tick labeling, and

default limits. An instance of this class must be returned by

:meth:`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</div>

<div class="viewcode-block" id="ConversionInterface"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.ConversionInterface">[docs]</a>class ConversionInterface(object):

"""

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

sequences) and convert them to values Matplotlib can use.

"""

<div class="viewcode-block" id="ConversionInterface.axisinfo"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.ConversionInterface.axisinfo">[docs]</a> @staticmethod

def axisinfo(unit, axis):

"""

Return an `~units.AxisInfo` instance for the axis with the

specified units.

"""

return None</div>

<div class="viewcode-block" id="ConversionInterface.default_units"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.ConversionInterface.default_units">[docs]</a> @staticmethod

def default_units(x, axis):

"""

Return the default unit for *x* or ``None`` for the given axis.

"""

return None</div>

<div class="viewcode-block" id="ConversionInterface.convert"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.ConversionInterface.convert">[docs]</a> @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</div>

<div class="viewcode-block" id="ConversionInterface.is_numlike"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.ConversionInterface.is_numlike">[docs]</a> @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.

"""

if iterable(x):

for thisx in x:

return is_numlike(thisx)

else:

return is_numlike(x)</div></div>

<div class="viewcode-block" id="Registry"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.Registry">[docs]</a>class Registry(dict):

"""

A register that maps types to conversion interfaces.

"""

def __init__(self):

dict.__init__(self)

self._cached = {}

<div class="viewcode-block" id="Registry.get_converter"><a class="viewcode-back" href="../../api/units_api.html#matplotlib.units.Registry.get_converter">[docs]</a> def get_converter(self, x):

"""

Get the converter for data that has the same type as *x*. If no

converters are registered for *x*, returns ``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)

if converter is None and hasattr(x, "values"):

# this unpacks pandas series or dataframes...

x = x.values

# If x is an array, look inside the array for data with units

if isinstance(x, np.ndarray) and x.size:

xravel = x.ravel()

try:

# pass the first value of x that is not masked back to

# get_converter

if not np.all(xravel.mask):

# some elements are not masked

converter = self.get_converter(

xravel[np.argmin(xravel.mask)])

return converter

except AttributeError:

# 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 = xravel[0]

if (not isinstance(next_item, np.ndarray) or

next_item.shape != x.shape):

converter = self.get_converter(next_item)

return converter

# If we haven't found a converter yet, try to get the first element

if converter is None:

try:

thisx = safe_first_element(x)

except (TypeError, StopIteration):

pass

else:

if classx and classx != getattr(thisx, '__class__', None):

return converter

# DISABLED self._cached[idx] = converter

return converter</div></div>

registry = Registry()

</pre></div>

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