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A collection of utility functions and classes. Many (but not all)
from the Python Cookbook -- hence the name cbook
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Base class for handling string -> python type with support for
missing values
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todatetimec B s) e Z d Z d d d d � Z d � Z RS( s convert to a datetime or Nones %Y-%m-%dR c C s t j | | | � | | _ d S( s8 use a :func:`time.strptime` format string for conversionN( R R t fmt( R R! R R ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR k s c C s< | j | � r | j St j | | j � } t j | d � S( Ni ( R R t timet strptimeR! t datetime( R R t tup( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR p s N( R R R R R R ( ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR i s t todatec B s) e Z d Z d d d d � Z d � Z RS( s convert to a date or Nones %Y-%m-%dR c C s t j | | | � | | _ d S( s8 use a :func:`time.strptime` format string for conversionN( R R R! ( R R! R R ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR y s c C s< | j | � r | j St j | | j � } t j | d � S( Ni ( R R R" R# R! R$ t date( R R R% ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR ~ s N( R R R R R R ( ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR& w s t tofloatc B s& e Z d Z d d d � Z d � Z RS( s convert to a float or NoneR c C s t j | | � | | _ d S( N( R R R ( R R R ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR � s c C s | j | � r | j St | � S( N( R R t float( R R ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR � s N( R R R R R R ( ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR( � s t tointc B s& e Z d Z d d d � Z d � Z RS( s convert to an int or NoneR c C s t j | | � d S( N( R R ( R R R ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR � s c C s | j | � r | j St | � S( N( R R t int( R R ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR � s N( R R R R R R ( ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR* � s t _BoundMethodProxyc B sD e Z d Z d � Z d � Z d � Z d � Z d � Z d � Z RS( s�
Our own proxy object which enables weak references to bound and unbound
methods and arbitrary callables. Pulls information about the function,
class, and instance out of a bound method. Stores a weak reference to the
instance to support garbage collection.
@organization: IBM Corporation
@copyright: Copyright (c) 2005, 2006 IBM Corporation
@license: The BSD License
Minor bugfixes by Michael Droettboom
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Proxy for a call to the weak referenced object. Take
arbitrary params to pass to the callable.
Raises `ReferenceError`: When the weak reference refers to
a dead object
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Compare the held function and instance with that held by
another proxy.
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Inverse of __eq__.
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t CallbackRegistryc B sD e Z d Z d � Z d � Z d � Z d � Z d � Z d � Z RS( s&
Handle registering and disconnecting for a set of signals and
callbacks:
>>> def oneat(x):
... print 'eat', x
>>> def ondrink(x):
... print 'drink', x
>>> from matplotlib.cbook import CallbackRegistry
>>> callbacks = CallbackRegistry()
>>> id_eat = callbacks.connect('eat', oneat)
>>> id_drink = callbacks.connect('drink', ondrink)
>>> callbacks.process('drink', 123)
drink 123
>>> callbacks.process('eat', 456)
eat 456
>>> callbacks.process('be merry', 456) # nothing will be called
>>> callbacks.disconnect(id_eat)
>>> callbacks.process('eat', 456) # nothing will be called
In practice, one should always disconnect all callbacks when they
are no longer needed to avoid dangling references (and thus memory
leaks). However, real code in matplotlib rarely does so, and due
to its design, it is rather difficult to place this kind of code.
To get around this, and prevent this class of memory leaks, we
instead store weak references to bound methods only, so when the
destination object needs to die, the CallbackRegistry won't keep
it alive. The Python stdlib weakref module can not create weak
references to bound methods directly, so we need to create a proxy
object to handle weak references to bound methods (or regular free
functions). This technique was shared by Peter Parente on his
`"Mindtrove" blog
<http://mindtrove.info/articles/python-weak-references/>`_.
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register *func* to be called when a signal *s* is generated
func will be called
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disconnect the callback registered with callback id *cid*
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process signal *s*. All of the functions registered to receive
callbacks on *s* will be called with *\*args* and *\*\*kwargs*
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Base class for timeout and idle scheduling
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t Timeoutc B s e Z d Z d � Z d � Z RS( s?
Schedule recurring events with a wait time in seconds
c C s# t j | � | | _ | | _ d S( N( R` R t waitR1 ( R Rn R1 ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR q s
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Schedule callbacks when scheduler is idle
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override repr when returning a list of matplotlib artists to
prevent long, meaningless output. This is meant to be used for a
homogeneous list of a given type
c C s) | | _ | d k r% | j | � n d S( N( t typeR t extend( R Rw t seq( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR � s c C s d t | � | j f S( Ns <a list of %d %s objects>( RK Rw ( R ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt __repr__� s c C s
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t Bunchc B s e Z d Z d � Z d � Z RS( s�
Often we want to just collect a bunch of stuff together, naming each
item of the bunch; a dictionary's OK for that, but a small do- nothing
class is even handier, and prettier to use. Whenever you want to
group a few variables::
>>> point = Bunch(datum=2, squared=4, coord=12)
>>> point.datum
By: Alex Martelli
From: http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/52308
c K s | j j | � d S( N( R5 t update( R t kwds( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR � s c C sD | j j � } d d j g | D] } d | | j | f ^ q � S( Ns Bunch(%s)s , s %s=%s( R5 t iterkeysRh ( R t keyst k( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyRz � s ( R R R R Rz ( ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR� � s c C s) t g | D] } | d f ^ q
� j � S( s' Return a list of unique elements of *x*i ( RO R� ( t xt val( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt unique� s c C s' y t | � Wn t k
r" t SXt S( s return true if *obj* is iterable( t iterR/ RF Ri ( t obj( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt iterable� s
c C so t | t t f � r t St j | � rT | j d k rM | j j d k rM t St Sn y | d Wn t SXt S( s( Return True if *obj* looks like a stringi t SUR (
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isMaskedArrayt ndimt dtypet kindRF ( R� ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt is_string_like� s ! c C sE t | � s t St | � r t Sx | D] } t | � s' t Sq' Wt S( s@
Returns true if *obj* is iterable and contains strings
( R� RF R� Ri ( R� t o( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt is_sequence_of_strings� s
c C s t | d � o t | j � S( sC return true if *obj* looks like a file object with a *write* methodt write( t hasattrt callableR� ( R� ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt is_writable_file_like s c C s t | � o t | � S( s; return true if *obj* is not string like and is not iterable( R� R� ( R� ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt is_scalar s c C s y | d Wn t SXt Sd S( s( return true if *obj* looks like a numberi N( RF Ri ( R� ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt
is_numlike
s
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d � � | r� | | f S| S( s�
*fname* can be a filename or a file handle. Support for gzipped
files is automatic, if the filename ends in .gz. *flag* is a
read/write flag for :func:`file`
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return_openedR� t fhR� t opened( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt
to_filehandle s$
c C s t | � p t | � S( s; Return whether the given object is a scalar or string like.( R� R� ( R� ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt is_scalar_or_string2 s c C s� t j j t j j t � d d � } t j j | | � } | r� t j j | � d j � d k rj d } n d } t j j | � \ } } | d k r� t j | | � St | | � Sn | Sd
S( s
Return a sample data file. *fname* is a path relative to the
`mpl-data/sample_data` directory. If *asfileobj* is `True`
return a file object, otherwise just a file path.
If the filename ends in .gz, the file is implicitly ungzipped.
s mpl-datat sample_datai����s .csvs .xrcs .txtR� t rbs .gzN( s .csvs .xrcs .txt( t ost pathRh t dirnamet __file__t splitextt lowerR� R� ( R� t asfileobjt rootR� t modet baset ext( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt get_sample_data7 s $ c c sH xA | D]9 } | | � r! | Vq x t | | � D] } | Vq1 Wq Wd S( s�
Returns a generator of flattened nested containers
For example:
>>> from matplotlib.cbook import flatten
>>> l = (('John', ['Hunter']), (1, 23), [[([42, (5, 23)], )]])
>>> print list(flatten(l))
['John', 'Hunter', 1, 23, 42, 5, 23]
By: Composite of Holger Krekel and Luther Blissett
From: http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/121294
and Recipe 1.12 in cookbook
N( t flatten( Ry t scalarpt itemt subitem( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR� R s
t Sorterc B s> e Z d Z d � Z d d d � Z d d � Z e Z e Z RS( se
Sort by attribute or item
Example usage::
sort = Sorter()
list = [(1, 2), (4, 8), (0, 3)]
dict = [{'a': 3, 'b': 4}, {'a': 5, 'b': 2}, {'a': 0, 'b': 0},
{'a': 9, 'b': 9}]
sort(list) # default sort
sort(list, 1) # sort by index 1
sort(dict, 'a') # sort a list of dicts by key 'a'
c C sA | j � g | D] \ } } | | ^ q } | r= | | (n | S( N( t sort( R t datat auxt inplacet junkt it result( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt _helper| s
#
i c C s� | d k r: | r% | j � | } n | } | j � | Sg t t | � � D] } | | | | f ^ qM } | j | | | � Sd S( N( R R� t rangeRK R� ( R R� t itemindexR� R� R� R� ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt byItem� s
3c C sK g t t | � � D] } t | | | � | f ^ q } | j | | | � S( N( R� RK t getattrR� ( R R� t
attributenameR� R� R� ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyt byAttribute� s 8N( R R R R� R R� R� R� R ( ( ( s6 /usr/lib64/python2.7/site-packages/matplotlib/cbook.pyR� i s
t Xlatorc B s) e Z d Z d � Z d � Z d � Z RS( sm
All-in-one multiple-string-substitution class
Example usage::
text = "Larry Wall is the creator of Perl"
adict = {
"Larry Wall" : "Guido van Rossum",
"creator" : "Benevolent Dictator for Life",
"Perl" : "Python",
}
print multiple_replace(adict, text)
xlat = Xlator(adict)
print xlat.xlat(text)
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Remove excess indentation from docstring *s*.
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characters from each line, where n is the number of leading
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from Parmar and Martelli in the Python Cookbook
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Condensed by Alex Martelli from this thread_ on c.l.python
.. _thread: http://groups.google.com/groups?q=all+pairs+group:*python*&hl=en&lr=&ie=UTF-8&selm=mailman.4028.1096403649.5135.python-list%40python.org&rnum=1
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A dictionary with a maximum size; this doesn't override all the
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Implement a stack where elements can be pushed on and you can move
back and forth. But no pop. Should mimic home / back / forward
in a browser
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push object onto stack at current position - all elements
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raise *o* to the top of the stack and return *o*. *o* must be
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s Unknown element o( RU R
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return all attributes of *o* which match string in match. if case
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*objects*
A list of objects to find cycles in. It is often useful to
pass in gc.garbage to find the cycles that are preventing some
objects from being garbage collected.
*outstream*
The stream for output.
*show_progress*
If True, print the number of objects reached as they are found.
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t Grouperc B sP e Z d Z g d � Z d � Z d � Z d � Z d � Z d � Z d � Z RS( s
This class provides a lightweight way to group arbitrary objects
together into disjoint sets when a full-blown graph data structure
would be overkill.
Objects can be joined using :meth:`join`, tested for connectedness
using :meth:`joined`, and all disjoint sets can be retreived by
using the object as an iterator.
The objects being joined must be hashable and weak-referenceable.
For example:
>>> from matplotlib.cbook import Grouper
>>> class Foo(object):
... def __init__(self, s):
... self.s = s
... def __repr__(self):
... return self.s
...
>>> a, b, c, d, e, f = [Foo(x) for x in 'abcdef']
>>> grp = Grouper()
>>> grp.join(a, b)
>>> grp.join(b, c)
>>> grp.join(d, e)
>>> sorted(map(tuple, grp))
[(d, e), (a, b, c)]
>>> grp.joined(a, b)
True
>>> grp.joined(a, c)
True
>>> grp.joined(a, d)
False
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Join given arguments into the same set. Accepts one or more
arguments.
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Returns True if *a* and *b* are members of the same set.
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Iterate over each of the disjoint sets as a list.
The iterator is invalid if interleaved with calls to join().
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Returns all of the items joined with *a*, including itself.
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Find all masked and/or non-finite points in a set of arguments,
and return the arguments with only the unmasked points remaining.
Arguments can be in any of 5 categories:
1) 1-D masked arrays
2) 1-D ndarrays
3) ndarrays with more than one dimension
4) other non-string iterables
5) anything else
The first argument must be in one of the first four categories;
any argument with a length differing from that of the first
argument (and hence anything in category 5) then will be
passed through unchanged.
Masks are obtained from all arguments of the correct length
in categories 1, 2, and 4; a point is bad if masked in a masked
array or if it is a nan or inf. No attempt is made to
extract a mask from categories 2, 3, and 4 if :meth:`np.isfinite`
does not yield a Boolean array.
All input arguments that are not passed unchanged are returned
as ndarrays after removing the points or rows corresponding to
masks in any of the arguments.
A vastly simpler version of this function was originally
written as a helper for Axes.scatter().
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Find index ranges where *mask* is *False*.
*mask* will be flattened if it is not already 1-D.
Returns Nx2 :class:`numpy.ndarray` with each row the start and stop
indices for slices of the compressed :class:`numpy.ndarray`
corresponding to each of *N* uninterrupted runs of unmasked
values. If optional argument *compressed* is *False*, it returns
the start and stop indices into the original :class:`numpy.ndarray`,
not the compressed :class:`numpy.ndarray`. Returns *None* if there
are no unmasked values.
Example::
y = ma.array(np.arange(5), mask = [0,0,1,0,0])
ii = unmasked_index_ranges(ma.getmaskarray(y))
# returns array [[0,2,] [2,4,]]
y.compressed()[ii[1,0]:ii[1,1]]
# returns array [3,4,]
ii = unmasked_index_ranges(ma.getmaskarray(y), compressed=False)
# returns array [[0, 2], [3, 5]]
y.filled()[ii[1,0]:ii[1,1]]
# returns array [3,4,]
Prior to the transforms refactoring, this was used to support
masked arrays in Line2D.
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This generator takes a bunch of iterables that are ordered by func
It sends out ordered tuples::
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It is used by :func:`matplotlib.mlab.recs_join` to join record arrays
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returncode
attribute and output in the output attribute.
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>>> check_output(["ls", "-l", "/dev/null"])
'crw-rw-rw- 1 root root 1, 3 Oct 18 2007 /dev/null\n'
The stdout argument is not allowed as it is used internally.
To capture standard error in the result, use stderr=STDOUT.::
>>> check_output(["/bin/sh", "-c",
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'ls: non_existent_file: No such file or directory\n'
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