All combinations in a 2d Numpy - python

I am trying to modify the code provided as answer by Hilberts in below question to allow it for multiple values and not only binary.
All binary combinations in a 2d Numpy
So, rather than only allow 0 and 1 like in the previous example, i would like find all combinations without rotations for data like 0, 1, 2 and 3 .
I modified it in this way, mainly replacing the "2" in the original code by a variable and tried to replace it by the variable "m" to follow the initial formula. But I think the issue here is related to the numpy type of data "bitwise_and" . Does anyone have any advices about what would be problem or any hint?
def get_binary_mats(n,m):
# all possible n by n binary matrices up to rotation:
bin_mats = (np.bitwise_and(np.arange(m**(n*n))[:,None], m ** np.arange(n*n)) > 0)\
.reshape(-1, n, n)
# define a score for each matrix based on position of ones
score = m ** np.arange(n*n).reshape(n,n)
# array([[ 1, 2, 4],
# [ 8, 16, 32],
# [ 64, 128, 256]])
score_arr = np.stack([np.rot90(score, k=k) for k in range(4)])
# array([[[ 1, 2, 4],
# [ 8, 16, 32],
# [ 64, 128, 256]],
# [[ 4, 32, 256],
# [ 2, 16, 128],
# [ 1, 8, 64]],
# [[256, 128, 64],
# [ 32, 16, 8],
# [ 4, 2, 1]],
# [[ 64, 8, 1],
# [128, 16, 2],
# [256, 32, 4]]])
scores = np.einsum("ijk,ljk->il", bin_mats, score_arr)
_, idx = np.unique(scores.min(1), return_index=True)
return bin_mats[idx,...]
Thank you

from itertools import combinations_with_replacement as combn
list(combn([0,1,2,3], 4))
[(0, 0, 0, 0),
(0, 0, 0, 1),
(0, 0, 0, 2),
(0, 0, 0, 3),
(0, 0, 1, 1),
(0, 0, 1, 2),
(0, 0, 1, 3),
(0, 0, 2, 2),
(0, 0, 2, 3),
(0, 0, 3, 3),
(0, 1, 1, 1),
(0, 1, 1, 2),
(0, 1, 1, 3),
(0, 1, 2, 2),
(0, 1, 2, 3),
(0, 1, 3, 3),
(0, 2, 2, 2),
(0, 2, 2, 3),
(0, 2, 3, 3),
(0, 3, 3, 3),
(1, 1, 1, 1),
(1, 1, 1, 2),
(1, 1, 1, 3),
(1, 1, 2, 2),
(1, 1, 2, 3),
(1, 1, 3, 3),
(1, 2, 2, 2),
(1, 2, 2, 3),
(1, 2, 3, 3),
(1, 3, 3, 3),
(2, 2, 2, 2),
(2, 2, 2, 3),
(2, 2, 3, 3),
(2, 3, 3, 3),
(3, 3, 3, 3)]

Related

how to make pythonic Nested List

I'd like to make nested list
given_list = [[0, 1, 2], [0, 1, 2], [0, 1, 2]] # each element : range(0, n), num of element : m
new_list = [[0, 0, 0], [0, 0, 1], [0, 0, 2], [0, 1, 0], ..., [2, 2, 2]] # total num : n^m
How do I make it?
I tried to overlap the for statement m times, but I don't think it's pythonic.
Looks like you are trying to compute the product of the lists in given_list:
> from itertools import product
> list(product(*given_list))
[(0, 0, 0), (0, 0, 1), (0, 0, 2), (0, 1, 0), (0, 1, 1), (0, 1, 2), (0, 2, 0), (0, 2, 1), (0, 2, 2), (1, 0, 0), (1, 0, 1), (1, 0, 2), (1, 1, 0), (1, 1, 1), (1, 1, 2), (1, 2, 0), (1, 2, 1), (1, 2, 2), (2, 0, 0), (2, 0, 1), (2, 0, 2), (2, 1, 0), (2, 1, 1), (2, 1, 2), (2, 2, 0), (2, 2, 1), (2, 2, 2)]
If you really need a list of lists, rather than a list of tuples, you'll have to call list on each element.
[list(t) for t in product(*given_list)]

To generate a list, allowing duplicates and fitting a condition

From choices [1,2,3], I want to output all possible combinations, allowing duplicates in the choices, in a list of 5 elements.
In each of the lists, there must be at least one of 1, at least one of 2, and at least one of 3.
A clumsy way as below. It firstly generates a list of 5 using either in [1,2,3]. All generated lists are examined to have at least each of [1,2,3]. The qualified ones are put into a big list. Then the duplicates in the big list are removed (loop it many times to make sure good coverage):
import random
import itertools
choices = [1,2,3]
big_list = []
for a in range(10000):
new_list = [random.choice(choices) for i in range(5)]
if new_list.count(1) >= 1 and new_list.count(2) >= 1 and new_list.count(3) >= 1:
big_list.append(new_list)
big_list.sort()
final_list = list(big_list for big_list, _ in itertools.groupby(big_list))
# this line to remove the duplicates in the list of lists
print (final_list)
Considering the sequence matters, that is, [1,1,1,2,3] and [2,3,1,1,1] are two different lists.
What would be the smarter and more comprehensive way to do so?
Maybe you could could use itertools.combinations_with_replacement, itertools.permutations along with collections.Counter:
>>> from collections import Counter
>>> from itertools import combinations_with_replacement, permutations
>>>
>>> def is_valid_combination(comb: tuple) -> bool:
... digit_counts = Counter(comb)
... return digit_counts[1] >= 1 and \
... digit_counts[2] >= 1 and \
... digit_counts[3] >= 1
...
>>> choices = [1, 2, 3]
>>> valid_combinations = [
... c for c in combinations_with_replacement(choices, r=5)
... if is_valid_combination(c)
... ]
>>>
>>> valid_combinations
[(1, 1, 1, 2, 3), (1, 1, 2, 2, 3), (1, 1, 2, 3, 3), (1, 2, 2, 2, 3), (1, 2, 2, 3, 3), (1, 2, 3, 3, 3)]
>>>
>>> all_permutations_of_valid_combinations = {
... p
... for c in valid_combinations for p in permutations(c)
... }
>>>
>>> all_permutations_of_valid_combinations
{(2, 1, 3, 1, 2), (2, 1, 3, 2, 1), (3, 3, 2, 1, 3), (1, 2, 3, 2, 3), (1, 2, 1, 3, 1), (3, 1, 2, 3, 2), (3, 3, 3, 2, 1), (3, 2, 2, 1, 1), (1, 2, 2, 3, 1), (1, 3, 2, 2, 3), (1, 3, 2, 3, 2), (1, 2, 1, 1, 3), (3, 1, 3, 3, 2), (3, 1, 1, 2, 3), (2, 1, 3, 2, 3), (1, 2, 2, 1, 3), (1, 2, 1, 3, 3), (2, 3, 3, 1, 2), (2, 3, 3, 2, 1), (3, 3, 1, 2, 1), (3, 2, 3, 2, 1), (1, 2, 2, 3, 3), (3, 2, 1, 1, 1), (2, 2, 1, 3, 1), (2, 3, 1, 1, 1), (1, 3, 1, 2, 3), (3, 3, 1, 1, 2), (3, 2, 3, 1, 2), (2, 1, 2, 3, 1), (2, 2, 1, 1, 3), (3, 2, 1, 3, 1), (2, 3, 1, 3, 1), (1, 1, 3, 2, 1), (2, 3, 2, 1, 2), (2, 3, 2, 2, 1), (2, 1, 2, 1, 3), (3, 2, 1, 1, 3), (2, 2, 1, 3, 3), (2, 3, 1, 1, 3), (2, 3, 1, 2, 2), (3, 2, 3, 3, 1), (1, 1, 3, 1, 2), (2, 1, 2, 3, 3), (3, 3, 2, 2, 1), (3, 1, 2, 1, 2), (3, 2, 1, 3, 3), (3, 1, 2, 2, 1), (2, 3, 1, 3, 3), (1, 1, 3, 2, 3), (3, 3, 3, 1, 2), (1, 2, 3, 1, 1), (1, 1, 3, 3, 2), (3, 1, 3, 1, 2), (2, 3, 2, 3, 1), (1, 3, 2, 1, 1), (2, 1, 3, 3, 1), (3, 2, 2, 3, 1), (3, 1, 2, 2, 3), (1, 3, 2, 2, 2), (1, 2, 3, 1, 3), (1, 3, 2, 3, 1), (3, 2, 2, 1, 3), (2, 2, 3, 2, 1), (3, 1, 1, 2, 2), (1, 1, 2, 2, 3), (2, 1, 3, 2, 2), (1, 3, 3, 2, 2), (3, 3, 1, 3, 2), (2, 1, 1, 3, 1), (1, 3, 2, 1, 3), (2, 1, 3, 3, 3), (3, 1, 3, 2, 2), (2, 2, 3, 1, 2), (1, 1, 2, 3, 1), (3, 2, 1, 2, 2), (1, 2, 2, 3, 2), (3, 3, 1, 2, 3), (1, 3, 2, 3, 3), (1, 2, 1, 2, 3), (3, 2, 3, 1, 1), (1, 3, 1, 2, 2), (1, 2, 2, 2, 3), (2, 1, 1, 3, 3), (3, 1, 1, 3, 2), (1, 1, 2, 3, 3), (1, 3, 3, 3, 2), (2, 3, 2, 1, 1), (2, 2, 1, 2, 3), (2, 2, 1, 3, 2), (1, 2, 3, 3, 1), (3, 2, 3, 1, 3), (2, 3, 1, 2, 1), (2, 1, 3, 1, 1), (3, 3, 2, 1, 2), (1, 2, 3, 2, 2), (1, 3, 1, 3, 2), (3, 1, 2, 3, 1), (2, 2, 2, 3, 1), (2, 1, 2, 2, 3), (1, 2, 3, 3, 3), (2, 3, 1, 2, 3), (2, 1, 3, 1, 3), (3, 2, 2, 2, 1), (1, 2, 1, 3, 2), (2, 3, 3, 1, 1), (3, 1, 2, 3, 3), (3, 2, 2, 1, 2), (3, 1, 1, 2, 1), (1, 3, 3, 2, 1), (2, 3, 3, 3, 1), (2, 1, 1, 1, 3), (1, 3, 2, 1, 2), (2, 1, 3, 3, 2), (1, 1, 1, 2, 3), (3, 1, 3, 2, 1), (1, 1, 1, 3, 2), (2, 2, 3, 1, 1), (3, 1, 1, 1, 2), (1, 1, 2, 1, 3), (1, 3, 3, 1, 2), (3, 2, 1, 2, 1), (2, 3, 3, 1, 3), (3, 3, 1, 2, 2), (2, 2, 3, 3, 1), (1, 3, 1, 2, 1), (1, 3, 3, 2, 3), (3, 2, 1, 1, 2), (2, 1, 1, 3, 2), (2, 3, 1, 1, 2), (3, 1, 3, 2, 3), (2, 2, 3, 1, 3), (1, 3, 1, 1, 2), (1, 1, 2, 3, 2), (2, 1, 2, 3, 2), (3, 2, 1, 2, 3), (3, 1, 2, 1, 1), (3, 2, 1, 3, 2), (2, 1, 1, 2, 3), (2, 3, 1, 3, 2), (1, 1, 3, 2, 2), (2, 3, 2, 1, 3), (3, 3, 2, 3, 1), (3, 3, 2, 1, 1), (1, 2, 3, 2, 1), (3, 1, 2, 1, 3), (2, 2, 2, 1, 3), (3, 1, 2, 2, 2), (1, 3, 2, 2, 1), (1, 2, 3, 1, 2), (1, 2, 3, 3, 2)}
Apart from the itertools.combinations itself, you could use some recursive logic:
def combinations(choices, n = 5):
if n == 1:
return [[x,] for x in choices]
else:
return [v + [x,] for v in combinations(choices, n = n -1) for x in choices]
To select only the combinations which contain at least one 1, 2 and 3:
[x for x in combinations(choices, n = 5) if all(c in x for c in choices)]

Find all permutations of numbers of exactly 9 characters long

I have the numbers [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 15, 16].
I want to find all permutations of numbers of exactly 9 characters. For example, if I have 8 single digit numbers, the last one can't be a double digit, because it would exceed the character limit.
Clarifications:
The same number can be reused, so for example the number 1 nine times is valid.
There can be any number of double digit numbers, as long as the total character length of the digits is exactly 9. For example, 1, 10, 12, 15, 16 is valid.
I tried itertools.permutations, but I couldn't get it to work with two-digit numbers.
I would use a mixture of combination and permutations.
First find all of the combinations of the data which add up to the desired length. Then for each unique combination, find their permutations. There's probably some work to be done here which can limit the amount of incorrect combinations checked:
import itertools
def perm_of_length(data, length):
for i in range(len(data)):
for comb in itertools.combinations(data, i + 1):
if sum(map(len, (map(str, comb)))) == length:
for perm in itertools.permutations(comb):
yield perm
for perm in perm_of_length([0, 1, 2, 3, 10, 12], 4):
print(perm)
Outputs:
(10, 12)
(12, 10)
(0, 1, 10)
(0, 10, 1)
(1, 0, 10)
(1, 10, 0)
(10, 0, 1)
(10, 1, 0)
(0, 1, 12)
(0, 12, 1)
(1, 0, 12)
(1, 12, 0)
(12, 0, 1)
(12, 1, 0)
(0, 2, 10)
(0, 10, 2)
(2, 0, 10)
(2, 10, 0)
(10, 0, 2)
(10, 2, 0)
(0, 2, 12)
(0, 12, 2)
(2, 0, 12)
(2, 12, 0)
(12, 0, 2)
(12, 2, 0)
(0, 3, 10)
(0, 10, 3)
(3, 0, 10)
(3, 10, 0)
(10, 0, 3)
(10, 3, 0)
(0, 3, 12)
(0, 12, 3)
(3, 0, 12)
(3, 12, 0)
(12, 0, 3)
(12, 3, 0)
(1, 2, 10)
(1, 10, 2)
(2, 1, 10)
(2, 10, 1)
(10, 1, 2)
(10, 2, 1)
(1, 2, 12)
(1, 12, 2)
(2, 1, 12)
(2, 12, 1)
(12, 1, 2)
(12, 2, 1)
(1, 3, 10)
(1, 10, 3)
(3, 1, 10)
(3, 10, 1)
(10, 1, 3)
(10, 3, 1)
(1, 3, 12)
(1, 12, 3)
(3, 1, 12)
(3, 12, 1)
(12, 1, 3)
(12, 3, 1)
(2, 3, 10)
(2, 10, 3)
(3, 2, 10)
(3, 10, 2)
(10, 2, 3)
(10, 3, 2)
(2, 3, 12)
(2, 12, 3)
(3, 2, 12)
(3, 12, 2)
(12, 2, 3)
(12, 3, 2)
(0, 1, 2, 3)
(0, 1, 3, 2)
(0, 2, 1, 3)
(0, 2, 3, 1)
(0, 3, 1, 2)
(0, 3, 2, 1)
(1, 0, 2, 3)
(1, 0, 3, 2)
(1, 2, 0, 3)
(1, 2, 3, 0)
(1, 3, 0, 2)
(1, 3, 2, 0)
(2, 0, 1, 3)
(2, 0, 3, 1)
(2, 1, 0, 3)
(2, 1, 3, 0)
(2, 3, 0, 1)
(2, 3, 1, 0)
(3, 0, 1, 2)
(3, 0, 2, 1)
(3, 1, 0, 2)
(3, 1, 2, 0)
(3, 2, 0, 1)
(3, 2, 1, 0)
Proof this works:
for perm in perm_of_length([0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 15, 16], 9):
assert sum(map(len, map(str, perm))) == 9
NOTE: this is much slower than it needs to be.
A simple, non-performant, brute-force approach with filtering:
symbols = [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 15, 16]
symbols = [str(x) for x in symbols]
perms = itertools.chain.from_iterable(
itertools.permutations(symbols, i) for i in range(10)
)
perms = ("".join(x) for x in perms)
perms = [x for x in perms if len(x) <= 9]
>>> len(perms)
13600046
>>> perms[:4]
['', '0', '1', '2']
>>> perms[-4:]
['987643102', '987643120', '987643201', '987643210']
One can drop the empty string by simply skipping the first item in perms.
A similar approach which does not use strings:
symbols = [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 15, 16]
lengths = {k: int(math.log10(k)) + 1 if k != 0 else 1 for k in symbols}
perms = itertools.chain.from_iterable(
itertools.permutations(symbols, i) for i in range(10)
)
perms = [x for x in perms if sum(lengths[k] for k in x) <= 9]
>>> len(perms)
13600046
If numbers can be reused (as mentioned in the comments), I would consider itertools.product instead of itertools.permutations:
symbols = [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 15, 16]
lengths = {k: int(math.log10(k)) + 1 if k != 0 else 1 for k in symbols}
perms = itertools.product(symbols, repeat=9)
perms = [x for x in perms if sum(lengths[k] for k in x) <= 9]

Get the frequency of values in a list of lists

l have the following input list composed of values which varies from k=0 to 4:
vector_input= [(3, 3, 3, 3, 3), (0, 0, 1), (3, 4, 3, 3, 4, 4), (1, 1, 1, 1), (1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), (1, 3, 3, 3, 1, 1, 3), (0, 0), (4, 4, 4, 4, 4), (1, 1), (3, 3), (1, 4, 3, 2), (3, 3, 4, 4, 4), (4, 4, 4, 4, 4), (3,), (2, 2), (2, 2, 2, 2, 2, 2), (0, 0, 0, 0, 1, 0), (1, 1, 1, 1, 1), (1, 1, 1, 1, 1), (0, 0, 0, 0, 0, 0, 1, 0, 0, 1)]
l want to transform this list into a list of frequency output of dimension of k (k=4) so that to get list output as follows :
vector_output=[
[0,0,0,5,0],[2,1,0,0,0],[0,0,0,3,3],[0,4,0,0,0],[0,16,0,0,0], [0,3,0,4,0],
[2,0,0,0,0],[0,0,0,0,5],[0,0,0,3,0],[0,0,2,0,0],[0,0,6,0,0],[5,1,0,0,0],[0,5,0,0,0],[0,5,0,0,0],[8,2,0,0,0]]
For instance : (3, 3, 3, 3, 3) becomes (0,0,0,5,0) because three is repeated five times and 0,1,2,4 zero times.
You could create a distribution function:
def distribution(vector, highest=5):
dist = [0] * highest
for i in vector:
dist[i] += 1
return dist
and apply it to every vector with a list comprehension:
vector_input= [(3, 3, 3, 3, 3), (0, 0, 1), (3, 4, 3, 3, 4, 4), (1, 1, 1, 1), (1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), (1, 3, 3, 3, 1, 1, 3), (0, 0), (4, 4, 4, 4, 4), (1, 1), (3, 3), (1, 4, 3, 2), (3, 3, 4, 4, 4), (4, 4, 4, 4, 4), (3,), (2, 2), (2, 2, 2, 2, 2, 2), (0, 0, 0, 0, 1, 0), (1, 1, 1, 1, 1), (1, 1, 1, 1, 1), (0, 0, 0, 0, 0, 0, 1, 0, 0, 1)]
print([distribution(v) for v in vector_input])
# [[0, 0, 0, 5, 0], [2, 1, 0, 0, 0], [0, 0, 0, 3, 3], [0, 4, 0, 0, 0], [0, 16, 0, 0, 0], [0, 3, 0, 4, 0], [2, 0, 0, 0, 0], [0, 0, 0, 0, 5], [0, 2, 0, 0, 0], [0, 0, 0, 2, 0], [0, 1, 1, 1, 1], [0, 0, 0, 2, 3], [0, 0, 0, 0, 5], [0, 0, 0, 1, 0], [0, 0, 2, 0, 0], [0, 0, 6, 0, 0], [5, 1, 0, 0, 0], [0, 5, 0, 0, 0], [0, 5, 0, 0, 0], [8, 2, 0, 0, 0]]
You can try this:
import itertools
vector_input= [(3, 3, 3, 3, 3), (0, 0, 1), (3, 4, 3, 3, 4, 4), (1, 1, 1, 1), (1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), (1, 3, 3, 3, 1, 1, 3), (0, 0), (4, 4, 4, 4, 4), (1, 1), (3, 3), (1, 4, 3, 2), (3, 3, 4, 4, 4), (4, 4, 4, 4, 4), (3,), (2, 2), (2, 2, 2, 2, 2, 2), (0, 0, 0, 0, 1, 0), (1, 1, 1, 1, 1), (1, 1, 1, 1, 1), (0, 0, 0, 0, 0, 0, 1, 0, 0, 1)]
full_listing = list(set(itertools.chain(*vector_input)))
final_data = [tuple(list(b).count(c) for c in range(min(full_listing), max(full_listing)+1)) for b in vector_input]
Output:
[(0, 0, 0, 5, 0), (2, 1, 0, 0, 0), (0, 0, 0, 3, 3), (0, 4, 0, 0, 0), (0, 16, 0, 0, 0), (0, 3, 0, 4, 0), (2, 0, 0, 0, 0), (0, 0, 0, 0, 5), (0, 2, 0, 0, 0), (0, 0, 0, 2, 0), (0, 1, 1, 1, 1), (0, 0, 0, 2, 3), (0, 0, 0, 0, 5), (0, 0, 0, 1, 0), (0, 0, 2, 0, 0), (0, 0, 6, 0, 0), (5, 1, 0, 0, 0), (0, 5, 0, 0, 0), (0, 5, 0, 0, 0), (8, 2, 0, 0, 0)]

product of variable number of range(n)'s

I am trying to understand how to write code that will output all the divisors of a number. The approach that I am most interested in taking begins with a function that returns a dictionary where the keys are the prime divisors and the values are the number of times divisible. I have already written this function like so:
def div_pair(num):
divPair = {}
for prime in prime_gen():
primeDegree = 0
while num % prime == 0:
num = int(num / prime)
primeDegree += 1
if primeDegree > 0:
divPair[prime] = primeDegree
if num == 1:
return divPair
As an example, the number 84,000 outputs the dictionary
{2: 5, 3: 1, 5: 3, 7: 1}
What I want to do from here is generate powersets(?) of any given values returned by the different numbers divPair would return, and then multiply these powersets by their matched primes. This is an example which uses the kind of code I am trying to use to generate the powersets:
from itertools import product
list(product(range(5+1), range(1+1), range(3+1), range(1+1)))
Outputs this:
[(0, 0, 0, 0),
(0, 0, 0, 1),
(0, 0, 1, 0),
(0, 0, 1, 1),
(0, 0, 2, 0),
(0, 0, 2, 1),
(0, 0, 3, 0),
(0, 0, 3, 1),
(0, 1, 0, 0),
(0, 1, 0, 1),
(0, 1, 1, 0),
(0, 1, 1, 1),
(0, 1, 2, 0),
(0, 1, 2, 1),
(0, 1, 3, 0),
(0, 1, 3, 1),
(1, 0, 0, 0),
(1, 0, 0, 1),
(1, 0, 1, 0),
(1, 0, 1, 1),
(1, 0, 2, 0),
(1, 0, 2, 1),
(1, 0, 3, 0),
(1, 0, 3, 1),
(1, 1, 0, 0),
(1, 1, 0, 1),
(1, 1, 1, 0),
(1, 1, 1, 1),
(1, 1, 2, 0),
(1, 1, 2, 1),
(1, 1, 3, 0),
(1, 1, 3, 1),
(2, 0, 0, 0),
(2, 0, 0, 1),
(2, 0, 1, 0),
(2, 0, 1, 1),
(2, 0, 2, 0),
(2, 0, 2, 1),
(2, 0, 3, 0),
(2, 0, 3, 1),
(2, 1, 0, 0),
(2, 1, 0, 1),
(2, 1, 1, 0),
(2, 1, 1, 1),
(2, 1, 2, 0),
(2, 1, 2, 1),
(2, 1, 3, 0),
(2, 1, 3, 1),
(3, 0, 0, 0),
(3, 0, 0, 1),
(3, 0, 1, 0),
(3, 0, 1, 1),
(3, 0, 2, 0),
(3, 0, 2, 1),
(3, 0, 3, 0),
(3, 0, 3, 1),
(3, 1, 0, 0),
(3, 1, 0, 1),
(3, 1, 1, 0),
(3, 1, 1, 1),
(3, 1, 2, 0),
(3, 1, 2, 1),
(3, 1, 3, 0),
(3, 1, 3, 1),
(4, 0, 0, 0),
(4, 0, 0, 1),
(4, 0, 1, 0),
(4, 0, 1, 1),
(4, 0, 2, 0),
(4, 0, 2, 1),
(4, 0, 3, 0),
(4, 0, 3, 1),
(4, 1, 0, 0),
(4, 1, 0, 1),
(4, 1, 1, 0),
(4, 1, 1, 1),
(4, 1, 2, 0),
(4, 1, 2, 1),
(4, 1, 3, 0),
(4, 1, 3, 1),
(5, 0, 0, 0),
(5, 0, 0, 1),
(5, 0, 1, 0),
(5, 0, 1, 1),
(5, 0, 2, 0),
(5, 0, 2, 1),
(5, 0, 3, 0),
(5, 0, 3, 1),
(5, 1, 0, 0),
(5, 1, 0, 1),
(5, 1, 1, 0),
(5, 1, 1, 1),
(5, 1, 2, 0),
(5, 1, 2, 1),
(5, 1, 3, 0),
(5, 1, 3, 1)]
which is really the output that I want. I just need to modify the code to accept divPair.values() in some way. So I write this:
from itertools import product
divPair = div_pair(84000)
list(product(range(i+1) for i in divPair.values()))
which seems to me as if it should be correct, but it outputs this mess:
[(range(0, 6),), (range(0, 2),), (range(0, 4),), (range(0, 2),)]
and I can't figure out how to fix it. There is a post here which offers fantastic solutions to what I am trying to do. I am just trying to work toward them with what I know.
product returns the product of its arguments, and you have passed it a single one, the (range(i+1) for i in divPair.values()) generator. The generator yielded a list of range objects. That's like doing this:
>>> list(product(['range', 'range', 'range']))
[('range',), ('range',), ('range',)]
You have to pass your ranges as individual arguments.
Do this:
list(product(*[range(i+1) for i in divPair.values()]))
(or this)
list(product(*(range(i+1) for i in divPair.values())))

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