pairwise的python包示例allpairspy

Sample Code: 
from allpairspy import AllPairs

parameters = [
    ["Brand X", "Brand Y"],
    ["98", "NT", "2000", "XP"],
    ["Internal", "Modem"],
    ["Salaried", "Hourly", "Part-Time", "Contr."],
    [6, 10, 15, 30, 60],
]

print("PAIRWISE:")
for i, pairs in enumerate(AllPairs(parameters)):
    print("{:2d}: {}".format(i, pairs))
 
Output: 
PAIRWISE:
 0: ['Brand X', '98', 'Internal', 'Salaried', 6]
 1: ['Brand Y', 'NT', 'Modem', 'Hourly', 6]
 2: ['Brand Y', '2000', 'Internal', 'Part-Time', 10]
 3: ['Brand X', 'XP', 'Modem', 'Contr.', 10]
 4: ['Brand X', '2000', 'Modem', 'Part-Time', 15]
 5: ['Brand Y', 'XP', 'Internal', 'Hourly', 15]
 6: ['Brand Y', '98', 'Modem', 'Salaried', 30]
 7: ['Brand X', 'NT', 'Internal', 'Contr.', 30]
 8: ['Brand X', '98', 'Internal', 'Hourly', 60]
 9: ['Brand Y', '2000', 'Modem', 'Contr.', 60]
10: ['Brand Y', 'NT', 'Modem', 'Salaried', 60]
11: ['Brand Y', 'XP', 'Modem', 'Part-Time', 60]
12: ['Brand Y', '2000', 'Modem', 'Hourly', 30]
13: ['Brand Y', '98', 'Modem', 'Contr.', 15]
14: ['Brand Y', 'XP', 'Modem', 'Salaried', 15]
15: ['Brand Y', 'NT', 'Modem', 'Part-Time', 15]
16: ['Brand Y', 'XP', 'Modem', 'Part-Time', 30]
17: ['Brand Y', '98', 'Modem', 'Part-Time', 6]
18: ['Brand Y', '2000', 'Modem', 'Salaried', 6]
19: ['Brand Y', '98', 'Modem', 'Salaried', 10]
20: ['Brand Y', 'XP', 'Modem', 'Contr.', 6]
21: ['Brand Y', 'NT', 'Modem', 'Hourly', 10]

Filtering

You can restrict pairs by setting filtering function to filter_func at AllPairs constructor.

Sample Code: 
from allpairspy import AllPairs

def is_valid_combination(row):
    """
    This is a filtering function. Filtering functions should return True
    if combination is valid and False otherwise.

    Test row that is passed here can be incomplete.
    To prevent search for unnecessary items filtering function
    is executed with found subset of data to validate it.
    """

    n = len(row)

    if n > 1:
        # Brand Y does not support Windows 98
        if "98" == row[1] and "Brand Y" == row[0]:
            return False

        # Brand X does not work with XP
        if "XP" == row[1] and "Brand X" == row[0]:
            return False

    if n > 4:
        # Contractors are billed in 30 min increments
        if "Contr." == row[3] and row[4] < 30:
            return False

    return True

parameters = [
    ["Brand X", "Brand Y"],
    ["98", "NT", "2000", "XP"],
    ["Internal", "Modem"],
    ["Salaried", "Hourly", "Part-Time", "Contr."],
    [6, 10, 15, 30, 60]
]

print("PAIRWISE:")
for i, pairs in enumerate(AllPairs(parameters, filter_func=is_valid_combination)):
    print("{:2d}: {}".format(i, pairs))
Output: 
PAIRWISE:
 0: ['Brand X', '98', 'Internal', 'Salaried', 6]
 1: ['Brand Y', 'NT', 'Modem', 'Hourly', 6]
 2: ['Brand Y', '2000', 'Internal', 'Part-Time', 10]
 3: ['Brand X', '2000', 'Modem', 'Contr.', 30]
 4: ['Brand X', 'NT', 'Internal', 'Contr.', 60]
 5: ['Brand Y', 'XP', 'Modem', 'Salaried', 60]
 6: ['Brand X', '98', 'Modem', 'Part-Time', 15]
 7: ['Brand Y', 'XP', 'Internal', 'Hourly', 15]
 8: ['Brand Y', 'NT', 'Internal', 'Part-Time', 30]
 9: ['Brand X', '2000', 'Modem', 'Hourly', 10]
10: ['Brand Y', 'XP', 'Modem', 'Contr.', 30]
11: ['Brand Y', '2000', 'Modem', 'Salaried', 15]
12: ['Brand Y', 'NT', 'Modem', 'Salaried', 10]
13: ['Brand Y', 'XP', 'Modem', 'Part-Time', 6]
14: ['Brand Y', '2000', 'Modem', 'Contr.', 60]

Data Source: OrderedDict

You can use collections.OrderedDict instance as an argument for AllPairs constructor. Pairs will be returned as collections.namedtuple instances.

Sample Code: 
from collections import OrderedDict
from allpairspy import AllPairs

parameters = OrderedDict({
    "brand": ["Brand X", "Brand Y"],
    "os": ["98", "NT", "2000", "XP"],
    "minute": [15, 30, 60],
})

print("PAIRWISE:")
for i, pairs in enumerate(AllPairs(parameters)):
    print("{:2d}: {}".format(i, pairs))
Sample Code: 
PAIRWISE:
 0: Pairs(brand='Brand X', os='98', minute=15)
 1: Pairs(brand='Brand Y', os='NT', minute=15)
 2: Pairs(brand='Brand Y', os='2000', minute=30)
 3: Pairs(brand='Brand X', os='XP', minute=30)
 4: Pairs(brand='Brand X', os='2000', minute=60)
 5: Pairs(brand='Brand Y', os='XP', minute=60)
 6: Pairs(brand='Brand Y', os='98', minute=60)
 7: Pairs(brand='Brand X', os='NT', minute=60)
 8: Pairs(brand='Brand X', os='NT', minute=30)
 9: Pairs(brand='Brand X', os='98', minute=30)
10: Pairs(brand='Brand X', os='XP', minute=15)
11: Pairs(brand='Brand X', os='2000', minute=15)

posted on 2022-09-24 22:11  帅胡  阅读(369)  评论(0)    收藏  举报

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