本文整理匯總了Python中Bio.Pathway.Rep.HashSet.list方法的典型用法代碼示例。如果您正苦於以下問題：Python HashSet.list方法的具體用法？Python HashSet.list怎麽用？Python HashSet.list使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類Bio.Pathway.Rep.HashSet的用法示例。
在下文中一共展示了HashSet.list方法的5個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: testList
# 需要導入模塊: from Bio.Pathway.Rep import HashSet [as 別名]
# 或者: from Bio.Pathway.Rep.HashSet import list [as 別名]
def testList(self):
a = HashSet(['a', 'b', 'c', 'd', 'e'])
l = a.list()
l.sort()
self.assertEqual(l, ['a', 'b', 'c', 'd', 'e'], "incorrect list")
l = []
self.assertTrue('e' in a, "set rep exposure")示例2: children
# 需要導入模塊: from Bio.Pathway.Rep import HashSet [as 別名]
# 或者: from Bio.Pathway.Rep.HashSet import list [as 別名]
def children(self, parent):
"""Returns a list of unique children for parent."""
s = HashSet([x[0] for x in self.child_edges(parent)])
return s.list()示例3: species
# 需要導入模塊: from Bio.Pathway.Rep import HashSet [as 別名]
# 或者: from Bio.Pathway.Rep.HashSet import list [as 別名]
def species(self):
"""Returns a list of the species in this system."""
s = HashSet(reduce(lambda s,x: s + x,
[x.species() for x in self.reactions()], []))
return s.list()示例4: parents
# 需要導入模塊: from Bio.Pathway.Rep import HashSet [as 別名]
# 或者: from Bio.Pathway.Rep.HashSet import list [as 別名]
def parents(self, child):
"""Returns a list of unique parents for child."""
s = HashSet([x[0] for x in self.parent_edges(child)])
return s.list()示例5: __init__
# 需要導入模塊: from Bio.Pathway.Rep import HashSet [as 別名]
# 或者: from Bio.Pathway.Rep.HashSet import list [as 別名]
class System:
"""Abstraction for a collection of reactions.
This class is used in the Bio.Pathway framework to represent an arbitrary
collection of reactions without explicitly defined links.
Attributes:
None
"""
def __init__(self, reactions = []):
"""Initializes a new System object."""
self.__reactions = HashSet(reactions)
def __repr__(self):
"""Returns a debugging string representation of self."""
return "System(" + ",".join(map(repr,self.__reactions.list())) + ")"
def __str__(self):
"""Returns a string representation of self."""
return "System of " + str(len(self.__reactions)) + \
" reactions involving " + str(len(self.species())) + \
" species"
def add_reaction(self, reaction):
"""Adds reaction to self."""
self.__reactions.add(reaction)
def remove_reaction(self, reaction):
"""Removes reaction from self."""
self.__reactions.remove(reaction)
def reactions(self):
"""Returns a list of the reactions in this system."""
return self.__reactions.list()
def species(self):
"""Returns a list of the species in this system."""
s = HashSet(reduce(lambda s,x: s + x,
[x.species() for x in self.reactions()], []))
return s.list()
def stochiometry(self):
"""Computes the stoichiometry matrix for self.
Returns (species, reactions, stoch) where
species = ordered list of species in this system
reactions = ordered list of reactions in this system
stoch = 2D array where stoch[i][j] is coef of the
jth species in the ith reaction, as defined
by species and reactions above
"""
# Note: This an inefficient and ugly temporary implementation.
# To be practical, stochiometric matrices should probably
# be implemented by sparse matrices, which would require
# NumPy dependencies.
#
# PS: We should implement automatic checking for NumPy here.
species = self.species()
reactions = self.reactions()
stoch = [] * len(reactions)
for i in range(len(reactions)):
stoch[i] = 0 * len(species)
for s in reactions[i].species():
stoch[species.index(s)] = reactions[i].reactants[s]
return (species, reactions, stoch)