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"""
The Schur number S(k) is the largest integer n for which the interval [1,n]
can be partitioned into k sum-free sets.(https://mathworld.wolfram.com/SchurNumber.html)
"""
import math
from sympy.core import S
from sympy.core.basic import Basic
from sympy.core.function import Function
from sympy.core.numbers import Integer
class SchurNumber(Function):
r"""
This function creates a SchurNumber object
which is evaluated for `k \le 5` otherwise only
the lower bound information can be retrieved.
Examples
========
>>> from sympy.combinatorics.schur_number import SchurNumber
Since S(3) = 13, hence the output is a number
>>> SchurNumber(3)
13
We do not know the Schur number for values greater than 5, hence
only the object is returned
>>> SchurNumber(6)
SchurNumber(6)
Now, the lower bound information can be retrieved using lower_bound()
method
>>> SchurNumber(6).lower_bound()
536
"""
@classmethod
def eval(cls, k):
if k.is_Number:
if k is S.Infinity:
return S.Infinity
if k.is_zero:
return S.Zero
if not k.is_integer or k.is_negative:
raise ValueError("k should be a positive integer")
first_known_schur_numbers = {1: 1, 2: 4, 3: 13, 4: 44, 5: 160}
if k <= 5:
return Integer(first_known_schur_numbers[k])
def lower_bound(self):
f_ = self.args[0]
# Improved lower bounds known for S(6) and S(7)
if f_ == 6:
return Integer(536)
if f_ == 7:
return Integer(1680)
# For other cases, use general expression
if f_.is_Integer:
return 3*self.func(f_ - 1).lower_bound() - 1
return (3**f_ - 1)/2
def _schur_subsets_number(n):
if n is S.Infinity:
raise ValueError("Input must be finite")
if n <= 0:
raise ValueError("n must be a non-zero positive integer.")
elif n <= 3:
min_k = 1
else:
min_k = math.ceil(math.log(2*n + 1, 3))
return Integer(min_k)
def schur_partition(n):
"""
This function returns the partition in the minimum number of sum-free subsets
according to the lower bound given by the Schur Number.
Parameters
==========
n: a number
n is the upper limit of the range [1, n] for which we need to find and
return the minimum number of free subsets according to the lower bound
of schur number
Returns
=======
List of lists
List of the minimum number of sum-free subsets
Notes
=====
It is possible for some n to make the partition into less
subsets since the only known Schur numbers are:
S(1) = 1, S(2) = 4, S(3) = 13, S(4) = 44.
e.g for n = 44 the lower bound from the function above is 5 subsets but it has been proven
that can be done with 4 subsets.
Examples
========
For n = 1, 2, 3 the answer is the set itself
>>> from sympy.combinatorics.schur_number import schur_partition
>>> schur_partition(2)
[[1, 2]]
For n > 3, the answer is the minimum number of sum-free subsets:
>>> schur_partition(5)
[[3, 2], [5], [1, 4]]
>>> schur_partition(8)
[[3, 2], [6, 5, 8], [1, 4, 7]]
"""
if isinstance(n, Basic) and not n.is_Number:
raise ValueError("Input value must be a number")
number_of_subsets = _schur_subsets_number(n)
if n == 1:
sum_free_subsets = [[1]]
elif n == 2:
sum_free_subsets = [[1, 2]]
elif n == 3:
sum_free_subsets = [[1, 2, 3]]
else:
sum_free_subsets = [[1, 4], [2, 3]]
while len(sum_free_subsets) < number_of_subsets:
sum_free_subsets = _generate_next_list(sum_free_subsets, n)
missed_elements = [3*k + 1 for k in range(len(sum_free_subsets), (n-1)//3 + 1)]
sum_free_subsets[-1] += missed_elements
return sum_free_subsets
def _generate_next_list(current_list, n):
new_list = []
for item in current_list:
temp_1 = [number*3 for number in item if number*3 <= n]
temp_2 = [number*3 - 1 for number in item if number*3 - 1 <= n]
new_item = temp_1 + temp_2
new_list.append(new_item)
last_list = [3*k + 1 for k in range(len(current_list)+1) if 3*k + 1 <= n]
new_list.append(last_list)
current_list = new_list
return current_list