fancytools.fcollections package¶

Submodules¶

fancytools.fcollections.FIFObuffer module¶

class fancytools.fcollections.FIFObuffer.FIFObuffer(shape, dtype=<type 'numpy.float32'>, filled=False)[source]¶

Bases: object

A circular FIFO buffer implemented on top of numpy.

>>> a = FIFObuffer(shape=3)
>>> a.add(2)
>>> a.add(33)
>>> a.add(124)
>>> print a
[   2.   33.  124.]
>>> a.add(21)
>>> a.add(2456)
>>> print a
[  124.    21.  2456.]

add(value)[source]¶: Add a value to the buffer.

array()[source]¶: Returns a numpy array containing the last stored values.

position¶

setNextLineEveryNValues(n)[source]¶

splitPos()[source]¶: return the position of where to split the array to get the values in the right order

fancytools.fcollections.MultiList module¶

class fancytools.fcollections.MultiList.MultiList(*names)[source]¶

Bases: object

create a list of named lists. can be used as like a normal list but allows to get entries from direct from sublists

>>> l = MultiList('spam','eggs')
>>> l.extend( ([1,2],[3,4]) )
>>> print l.spam
[1, 2]
>>> print l.eggs
[3, 4]
>>> print l[1]
[2, 4]

append(args)[source]¶

extend(args)[source]¶

insert(index, args)[source]¶

next()[source]¶

pop(index)[source]¶

fancytools.fcollections.NestedOrderedDict module¶

class fancytools.fcollections.NestedOrderedDict.NestedOrderedDict(*args, **kwargs)[source]¶

Bases: collections.OrderedDict

an OrderedDict allowing the access of nested items through a .path attribute

every item of the NestedOrderedDict that is also a NestedOrderedDict inherits the path information to the uppermost NestedOrderedDict

lets’ build a nested structure:

>>> parent = NestedOrderedDict()
>>> ch1 = 'foo'
>>> ch2 = NestedOrderedDict()
>>> ch2_1 = NestedOrderedDict()
>>> ch2_1_1 = NestedOrderedDict([['hello','world']])

set items:

>>> parent['2'] = ch1
>>> parent['3'] = ch2
>>> ch2['4'] = ch2_1
>>> ch2_1['5'] = ch2_1_1

get the path from the most nested item:

>>> p = ch2_1_1.path
>>> print p
3, 4, 5

access this item from the parent dict:

>>> print parent[p]
NestedOrderedDict({hello: world})

fancytools.fcollections.ProxyList module¶

fancytools.fcollections.ProxyList.AttributeNotFound(*args, **kwargs)[source]¶

class fancytools.fcollections.ProxyList.ProxyList[source]¶

Bases: list

forwards an attribute/method given to this instance to its list-entries

create a list >>> a = ProxyList((‘aa’,11,’cc’))

find ‘a’ in the list because ‘find’ is not a method of this instance all list-entries will be given this method

>>> print a.find('a')
[0, None, -1]

... this returns a list saying that... [0,... –> ‘a’ is in the first position of the first entry ..., None –> there is no fitting method for the second entry ... ,-1 ] –> ‘a’ is not found in the last entry

show indices of list entries that are of type string

>>> print a.where('__class__',str)
[0, 2]

...using _TestObject which has one one extra method ‘foo’

>>> p = ProxyList([_TestObject(),_TestObject(),_TestObject()])
>>> print p.foo[0].__name__
foo

each time ‘foo’ is called it returns (‘bar’, 99) therefore for each member of the ProxyList the output would be:

>>> print p.foo('bar')
[('bar', 99), ('bar', 99), ('bar', 99)]

Also this method sets an attribute ‘a’ to ‘bar’->

>>> print p.a
['bar', 'bar', 'bar']

- - / etc can also be forwarded to the members of a list:

>>> p = ProxyList([ 1, -20, 3 ])
>>> p += 10
>>> print p
[11, -10, 13]

>>> print p.__abs__()
[11, 10, 13]

If the members are mutable their id remains the same:

>>> p = ProxyList([ [1], [2], [3] ])
>>> oldID = id(p[0])
>>> p *= 4
>>> newID = id(p[0])
>>> print oldID == newID
True

A ProxyList can be used for a mathematical operation with another ProxyList:

>>> p1 = ProxyList([ 1, 2, 3 ])
>>> p2 = ProxyList([ 1, 2, 3 ])
>>> p1-p2
[0, 0, 0]

where(attr, value)[source]¶

fancytools.fcollections.TwoDArraySliceIterator module¶

class fancytools.fcollections.TwoDArraySliceIterator.TwoDArraySliceIterator(main_size, slice_size)[source]¶

Bases: object

a simple iterator that build small slices from a big array

>>> import numpy as np

>>> arr = np.random.rand(100,100)
>>> n_pieces = (2,4)
>>> i = TwoDArraySliceIterator( arr.shape, n_pieces )

than iterate through your array as follows:

for s1,s2 in i:: print s1,s2, arr[s1,s2] ...

next()[source]¶

fancytools.fcollections.WeakList module¶

class fancytools.fcollections.WeakList.WeakList(l=())[source]¶

Bases: list

a list that removes its entries, if they are originally removed

>>> import numpy as np
>>> arr = np.ones(100)
>>> l = WeakList([arr,arr])
>>> l.append(arr)
>>> assert len(l) == 3
>>> l[0] is arr
True
>>> arr in l
True
>>> del arr
>>> assert len(l) == 0

append(obj)[source]¶

insert(ind, obj)[source]¶

fancytools.fcollections.naturalSorting module¶

fancytools.fcollections.naturalSorting.naturalSorting(l)[source]¶

sorts in human order http://nedbatchelder.com/blog/200712/human_sorting.html (See Toothy’s implementation in the comments)

>>> alist = [              "something1",          "something12",         "something17",         "something2",          "something25",         "something29"]

>>> print naturalSorting(alist)
['something1', 'something2', 'something12', 'something17', 'something25', 'something29']

fancytools.fcollections.removeDuplicates module¶

fancytools.fcollections.removeDuplicates.removeDuplicates(seq, idfun=None)[source]¶

removal all duplicates from a list, preserving the order:

>>> a=list('ABeeECcc')
>>> removeDuplicates(a)
['A', 'B', 'e', 'E', 'C', 'c']

>>> removeDuplicates(a, lambda x: x.lower())
['A', 'B', 'e', 'C']