def test_colfunc():
data = ['a3', 'b2', 'c1']
assert list(map(colfunc(None), data)) == data
assert list(map(colfunc(0), data)) == ['a', 'b', 'c']
assert list(map(colfunc(1), data)) == ['3', '2', '1']
expected = [['3', 'a'], ['2', 'b'], ['1', 'c']]
assert list(map(colfunc((1, 0)), data)) == expected
def Mean(iterable, key=None, default=None):
"""
iterable >> Mean(key=None, default=None)
Return mean value of inputs (transformed or extracted by key function).
>>> [1, 2, 3] >> Mean()
2.0
>>> [] >> Mean(default=0)
0
>>> data = [(1, 10), (2, 20), (3, 30)]
>>> data >> Mean(key=0)
2.0
>>> data >> Mean(key=1)
20.0
:param iterable iterable: Iterable over numbers
:param object default: Value returned if iterable is empty.
:param int|tuple|function|None key: Key function to extract elements.
:return: Mean of numbers or default value
:rtype: number
"""
f = colfunc(key)
sum, n = 0, 0
for e in iterable:
sum += f(e)
n += 1
return float(sum) / n if n else default
def Sort(iterable, key=None, reverse=False):
"""
iterable >> Sort(key=None, reverse=False)
Sorts iterable with respect to key function or column index(es).
>>> [3, 1, 2] >> Sort()
[1, 2, 3]
>>> [3, 1, 2] >> Sort(reverse=True)
[3, 2, 1]
>>> [(1,'c'), (2,'b'), (3,'a')] >> Sort(1)
[(3, 'a'), (2, 'b'), (1, 'c')]
>>> ['a3', 'c1', 'b2'] >> Sort(key=lambda s: s[0])
['a3', 'b2', 'c1']
>>> ['a3', 'c1', 'b2'] >> Sort(key=0)
['a3', 'b2', 'c1']
>>> ['a3', 'c1', 'b2'] >> Sort(1)
['c1', 'b2', 'a3']
>>> ['a3', 'c1', 'b2'] >> Sort((1,0))
['c1', 'b2', 'a3']
:param iterable iterable: Iterable
:param int|tuple|function|None key: function to sort based on or
column index(es) tuples/vectors/strings are sorted by.
:param boolean reverse: True: reverse order.
:return: Sorted iterable
:rtype: list
"""
return sorted(iterable, key=colfunc(key), reverse=reverse)
def Min(iterable, key=None, default=None):
"""
iterable >> Min(key=None, default=None)
Return minimum of inputs (transformed or extracted by key function).
>>> [1, 2, 3, 2] >> Min()
1
>>> ['1', '123', '12'] >> Min(key=len)
'1'
>>> [] >> Min(default=0)
0
>>> data = [(3, 10), (2, 20), (1, 30)]
>>> data >> Min(key=0)
(1, 30)
>>> data >> Min(1)
(3, 10)
:param iterable iterable: Iterable over numbers
:param int|tuple|function|None key: Key function to extract or
transform elements. None = identity function.
:param object default: Value returned if iterable is empty.
:return: smallest element according to key function
:rtype: object
"""
try:
return min(iterable, key=colfunc(key))
except Exception:
return default
def ArgMin(iterable, key=None, default=None, retvalue=False):
"""
iterable >> ArgMin(key=None, default=None, retvalue=True)
Return index of first minimum element (and minimum) in input
(transformed or extracted by key function).
>>> [1, 2, 0, 2] >> ArgMin()
2
>>> ['12', '1', '123'] >> ArgMin(key=len, retvalue=True)
(1, '1')
>>> ['12', '1', '123'] >> ArgMin(key=len)
1
>>> [] >> ArgMin(default=0)
0
>>> [] >> ArgMin(default=(None, 0), retvalue=True)
(None, 0)
>>> data = [(3, 10), (2, 20), (1, 30)]
>>> data >> ArgMin(key=0)
2
>>> data >> ArgMin(1)
0
:param iterable iterable: Iterable over numbers
:param int|tuple|function|None key: Key function to extract or
transform elements. None = identity function.
:param object default: Value returned if iterable is empty.
:param bool retvalue: If True the index and the value of the
minimum element is returned.
:return: index of smallest element according to key function
and the smallest element itself if retvalue==True.
:rtype: object | tuple
"""
try:
f = colfunc(key)
i, v = min(enumerate(iterable), key=lambda i_e1: f(i_e1[1]))
return (i, v) if retvalue else i
except Exception:
return default
def Sum(iterable, key=None):
"""
iterable >> Sum(key=None)
Return sum over inputs (transformed or extracted by key function)
>>> [1, 2, 3] >> Sum()
6
>>> [1, 2, 3] >> Sum(lambda x: x*x)
14
>>> data = [(1, 10), (2, 20), (3, 30)]
>>> data >> Sum(key=0)
6
>>> data >> Sum(key=1)
60
:param iterable iterable: Iterable over numbers
:param int|tuple|function|None key: Key function to extract elements.
:return: Sum of numbers
:rtype: number
"""
return sum(map(colfunc(key), iterable))
def MeanStd(iterable, key=None, default=None, ddof=1):
"""
iterable >> MeanStd(key=None, default=None, ddof=1)
Return mean and standard deviation of inputs (transformed or extracted
by key function).
Standard deviation is with degrees of freedom = 1
>>> [1, 2, 3] >> MeanStd()
(2.0, 1.0)
>>> data = [(1, 10), (2, 20), (3, 30)]
>>> data >> MeanStd(key=0)
(2.0, 1.0)
>>> data >> MeanStd(1)
(20.0, 10.0)
:param iterable iterable: Iterable over numbers
:param object default: Value returned if iterable is empty.
:param int|tuple|function|None key: Key function to extract elements.
:param int ddof: Delta degrees of freedom (should 0 or 1)
:return: Mean and standard deviation of numbers or default value
:rtype: tuple (mean, std)
"""
f = colfunc(key)
sume, sqre, n = 0.0, 0.0, 0.0
for e in iterable:
e = f(e)
sume += e
sqre += e * e
n += 1.0
if n - ddof <= 0:
return default
avg = sume / n
dev = math.sqrt((n * sqre - sume * sume) / (n * (n - ddof)))
return avg, dev
