#========================================================================
def sumDict(d):
return reduce(lambda x,y:x+y, d.values())
#========================================================================
def avgDict(d):
return reduce(lambda x,y:x+y, d.values()) / (len(d)*1.0)
#========================================================================
def mkDict(keyList, valueList, cond=None):
'''
Make a new dict out of two lists. The first list provides keys,
the 2nd provides values. The cond is a function taking 2 arguments:
key and value. Example: lambda k,v:v%2==0
A valid item means its cond(key, value) is true. Only valid items
are included in the returned dict.
>>> a
[0, 1, 2, 3, 4]
>>> b= [chr(x) for x in range(65,70)]
>>> b
['A', 'B', 'C', 'D', 'E']
>>> mkDict(b,a)
{'A': 0, 'C': 2, 'B': 1, 'E': 4, 'D': 3}
>>> mkDict(b,a,lambda x,y:y%2==0)
{'A': 0, 'C': 2, 'E': 4}
Note:
mkDict(a,b) (without the conditional check) is equavilant to
dict(zip(a,b)), which is much faster. If you know there's no
conditional check, better use dict(zip(a,b)) instead.
'''
if cond==None:
return dict(zip(keyList, valueList))
else:
return dict( [(k,v) for k,v in zip(keyList, valueList) if cond(k,v)] )
#========================================================================
def trimDict(aDict, cond=(lambda k,v:1)):
''' Return a new dict in which its items whose cond(k,v) == true
are removed (discarded) from aDict.
The cond is a function taking 2 arguments: key and value
>>> g
{'A': 0, 'C': 2, 'B': 1, 'E': 4, 'D': 3}
>>> trimDict(g, lambda x,y:y%2!=0)
{'A': 0, 'C': 2, 'E': 4}
'''
tmp={}
[tmp.setdefault(k,v) for k,v in aDict.items() if not cond(k,v)]
return tmp.copy()
#========================================================================
def reDict(aDict, func, cond=(lambda k,v:1), delUnchanged=0):
'''
Given aDict, return a new dict with valid items (= items whose
cond(key, value) is true) been modified by the function func.
if delUnchanged, then those invalid items are excluded from
the returned dict.
>>> d
{'B': 1, 'D': 3}
>>> reDict(d, lambda x:x**2)
{'B': 1, 'D': 9}
>>> g
{'A': 0, 'C': 2, 'B': 1, 'E': 4, 'D': 3}
>>> reDict(g, lambda x:-x, lambda k,v: v%2==0)
{'A': 0, 'C': -2, 'B': 1, 'E': -4, 'D': 3}
>>> reDict(g, lambda x:-x, lambda k,v: v%2==0, delUnchanged=1)
{'A': 0, 'C': -2, 'E': -4}
'''
tmp={}
if delUnchanged:
[tmp.setdefault(k,func(v)) for k,v in aDict.items() if cond(k,v)]
else:
[tmp.setdefault(k,(cond(k,v) and func(v) or v)) for k,v in aDict.items()]
return tmp.copy()
#========================================================================
def normDict(d, normalizeTo=1):
''' Normalize the values of d by setting the largest value in d.values
to normalizeTo. The return dict will have it's values spreading
between 0~normalizeTo'''
ks = d.keys()
vs = d.values()
vMax = max(vs)
vs= [ x/(vMax*1.0)*normalizeTo for x in vs]
return dict(zip(ks, vs))
#========================================================================
def normDictSumTo(d, sumTo=1):
''' Normalize the values of d to sumTo. The returned dict will
have value sum = sumTo
'''
ks = d.keys()
vs = d.values()
sum = reduce(lambda x,y:x+y, vs)
vs= [ x/(sum*1.0)*sumTo for x in vs]
return dict(zip(ks, vs))
#========================================================================
def accumDict(d, normalizeTo=None):
''' if d.values=[1,2,3,4,5]:
accumDict(d).values ==> [1, 3, 6, 10, 15]
if d.values=[0.25, 0.25, 0.25, 0.25]
accumDict(d).values ==> [0.25, 0.50, 0.75, 1.00]
Required: odict()
Ordered Dictionary Class
Dave Benjamin
http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/161403
'''
ks = d.keys()
vs = d.values()
if normalizeTo: vs = normListSumTo(vs, sumTo=normalizeTo)
r = range(1, len(vs))
newList=[vs[0]]
for i in r:
newList.append( newList[-1]+ vs[i] )
odic = odict()
for i in range(len(newList)):
odic[ks[i]] =newList[i]
return odic
#========================================================================
def fallInDict(val, aDict, baseValue=0):
'''
oo:
{
'a':3,
'b':5,
'c':2
}
accumDict(oo):
{
'a':3,
'b':8,
'c':10
}
fallInDict(0, oo)=0
fallInDict(1, oo)=0
fallInDict(2, oo)=0
fallInDict(3, oo)=0
fallInDict(4, oo)=1
fallInDict(5, oo)=1
fallInDict(6, oo)=1
fallInDict(7, oo)=1
fallInDict(8, oo)=1
fallInDict(9, oo)=2
fallInDict(10, oo)=2
When val out of range:
fallInDict(-1, oo)= -1
fallInDict(11, oo)= -2
fallInDict(12, oo)= -2
'''
if val<baseValue: return -1
acd = accumDict(aDict)
if val>acd.values()[-1]: return -2
ra = range(len(acd))
for i in ra:
vInDict = acd.values()[i]
if val <= vInDict: break
return aDict.keys()[i]
#========================================================================
def randomPickDict(d):
''' given a diictionary d, with all values are numbers,
randomly pick an item and return it's key according
to the percentage of its values'''
ks = d.keys()
vs = accumList(d.values(),1)
return ks[ findIndex( vs, random.random()) ]
#========================================================================
def sumInDict(L):
''' Given a list L:
[ {'S': [s11,s12,s13], 'V':[v11,v12,v13], ...},
{'S': [s21,s22,s23], 'V':[v21,v22,v23], ...},
{'S': [s31,s32,s33], 'V':[v31,v32,v33], ...},
... ]
Return a dict:
{'S': [s1,s2,s3], 'V':[v1,v2,v3], ...}
where s1 = s11 + s21 + s31 + ...
s2 = s12 + s22 + s32 + ...
'''
keys = L[0].keys()
new={}
for k in keys:
new[k] = [] # Init 'S':[]
for x in L: # x = {'S': [s11,s12,s13], 'V':[v11,v12,v13], ...}
y = x[k] # y = [s11,s12,s13]
new[k].append(y)
''' new[k] = [ [s11,s12,s13],[s21,s22,s23],[s31,s32,s33], ...]
Then use sumInList=> {'S': [s1,s2,s3],'V': [v1,v2,v3],... }'''
new[k] = sumInList(new[k])
return new
#========================================================================
def avgInDict(L):
''' Given a list L:
[ {'S': [s11,s12,s13], 'V':[v11,v12,v13], ...},
{'S': [s21,s22,s23], 'V':[v21,v22,v23], ...},
{'S': [s31,s32,s33], 'V':[v31,v32,v33], ...},
... ]
Return a dict:
{'S': [s1,s2,s3], 'V':[v1,v2,v3], ...}
where s1 = avg of (s11 + s21 + s31 + ...)
s2 = avg of (s12 + s22 + s32 + ...)
'''
''' First turn L into:
{'S': [ [s11,s12,s13],[s21,s22,s23],[s31,s32,s33], ...],
'V': [ [v11,v12,v13],[v21,v22,v23],[v31,v32,v33], ...],
... } '''
keys = L[0].keys()
new={}
for k in keys:
new[k] = [] # Init 'S':[]
for x in L: # x = {'S': [s11,s12,s13], 'V':[v11,v12,v13], ...}
y = x[k] # y = [s11,s12,s13]
new[k].append(y)
''' new[k] = [ [s11,s12,s13],[s21,s22,s23],[s31,s32,s33], ...]
Then use avgInList=> {'S': [s1,s2,s3],'V': [v1,v2,v3],... }'''
new[k] = avgInList(new[k])
return new
#========================================================================
def sumInDict2(D):
''' Given a dict:
{'A':{'S': [s11,s12,s13], 'V':[v11,v12,v13], ...},
'B':{'S': [s21,s22,s23], 'V':[v21,v22,v23], ...},
'C':{'S': [s31,s32,s33], 'V':[v31,v32,v33], ...}, ...
}
Return a dict:
{'S': [s1,s2,s3], 'V':[v1,v2,v3], ...}
where s1 = s11 + s21 + s31 + ...
s2 = s12 + s22 + s32 + ...
'''
return sumInDict(D.values())
#========================================================================
def avgInDict2(D):
''' Given a dict:
{'A':{'S': [s11,s12,s13], 'V':[v11,v12,v13], ...},
'B':{'S': [s21,s22,s23], 'V':[v21,v22,v23], ...},
'C':{'S': [s31,s32,s33], 'V':[v31,v32,v33], ...}, ...
}
Return a dict:
{'S': [s1,s2,s3], 'V':[v1,v2,v3], ...}
where s1 = avg of (s11 + s21 + s31 + ...)
s2 = avg of (s12 + s22 + s32 + ...)
'''
return avgInDict(D.values())
#========================================================================
