####################################################################
### ____ _ ____ _ ###
### | __ )(_) __ ) ___ _ __ ___| |__ ###
### | _ \| | _ \ / _ \ '_ \ / __| '_ \ ###
### | |_) | | |_) | __/ | | | (__| | | | ###
### |____/|_|____/ \___|_| |_|\___|_| |_| ###
### ###
###--------------------------------------------------------------###
### ###
### This file is part of the BiBench package for biclustering ###
### analysis. ###
### ###
### Copyright (c) 2011 by: ###
### * Kemal Eren, ###
### * Mehmet Deveci, ###
### * Umit V. Catalyurek ###
### ###
###--------------------------------------------------------------###
### ###
### For license info, please see the README and LICENSE files ###
### in the main directory. ###
### ###
###--------------------------------------------------------------###
import os
import itertools
import bibench
import numpy as np
import zlib
import cPickle
isiterable = lambda obj: isinstance(obj, basestring) or getattr(obj, '__iter__', False)
[docs]def flatten(nested):
"""
Flatten a list of lists into a single list.
>>> flatten([[1, 2, 3], [4, 5, 6]])
[1, 2, 3, 4, 5, 6]
"""
return [item for sublist in nested for item in sublist]
[docs]def grouper(iterable, n, fillvalue=None):
"""
Iterate over a list in chunks. From
'http://stackoverflow.com/questions/434287/what-is-the-most-pythonic-way-to-iterate-over-a-list-in-chunks'
>>> list(grouper([1, 2, 3, 4], 3, 'x'))
[(1, 2, 3), (4, 'x', 'x')]
"""
args = [iter(iterable)] * n
return itertools.izip_longest(*args, fillvalue=fillvalue)
[docs]def which(program):
"""
Check for an executable on the PATH; return its absolute path.
Taken from http://stackoverflow.com/questions/377017/test-if-executable-exists-in-python
"""
def is_exe(fpath):
return os.path.exists(fpath) and os.access(fpath, os.X_OK)
fpath, fname = os.path.split(program)
if fpath:
if is_exe(program):
return program
else:
for path in os.environ["PATH"].split(os.pathsep):
exe_file = os.path.join(path, program)
if is_exe(exe_file):
return exe_file
return None
[docs]def dict_combinations(d):
"""
Takes a dictionary containing lists. Generates all combinations of values from those lists.
Useful for ranges of parameters for functions.
>>> [i for i in dict_combinations(dict(first=[1,2]))]
[{'first': 1}, {'first': 2}]
"""
keys, values = zip(*d.items())
for x in itertools.product(*values):
yield dict(zip(keys, x))
[docs]def make_index_map(mylist):
"""Map each item in the list to its list index."""
d = dict()
for i, item in enumerate(mylist):
d[item] = i
return d
[docs]def bootstrap(data, size):
"""
Bootstrap a new dataset, of any size, from the given dataset, with
replacement.
Args:
* data: numpy.ndarray
* size: int or sequence of ints
Returns:
A numpy.ndarray
"""
choices = np.random.random_integers(low=0, high=data.size-1, size=size)
return np.array(data.flatten())[choices]
[docs]def shuffle(data):
"""Shuffle an array along all axes. Returns the shuffled array."""
fdata = data.flatten()
np.random.shuffle(fdata)
fdata.shape = data.shape
return fdata
[docs]def zdumps(obj):
"""dump an object, compressing as much as possible"""
return zlib.compress(cPickle.dumps(obj,cPickle.HIGHEST_PROTOCOL),9)
[docs]def zloads(zstr):
"""load a compressed string dumped by _zdumps_"""
return cPickle.loads(zlib.decompress(zstr))