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189 lines
5.0 KiB
189 lines
5.0 KiB
from sympy.utilities.misc import as_int
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def binomial_coefficients(n):
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"""Return a dictionary containing pairs :math:`{(k1,k2) : C_kn}` where
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:math:`C_kn` are binomial coefficients and :math:`n=k1+k2`.
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Examples
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========
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>>> from sympy.ntheory import binomial_coefficients
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>>> binomial_coefficients(9)
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{(0, 9): 1, (1, 8): 9, (2, 7): 36, (3, 6): 84,
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(4, 5): 126, (5, 4): 126, (6, 3): 84, (7, 2): 36, (8, 1): 9, (9, 0): 1}
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See Also
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========
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binomial_coefficients_list, multinomial_coefficients
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"""
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n = as_int(n)
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d = {(0, n): 1, (n, 0): 1}
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a = 1
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for k in range(1, n//2 + 1):
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a = (a * (n - k + 1))//k
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d[k, n - k] = d[n - k, k] = a
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return d
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def binomial_coefficients_list(n):
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""" Return a list of binomial coefficients as rows of the Pascal's
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triangle.
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Examples
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========
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>>> from sympy.ntheory import binomial_coefficients_list
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>>> binomial_coefficients_list(9)
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[1, 9, 36, 84, 126, 126, 84, 36, 9, 1]
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See Also
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========
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binomial_coefficients, multinomial_coefficients
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"""
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n = as_int(n)
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d = [1] * (n + 1)
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a = 1
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for k in range(1, n//2 + 1):
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a = (a * (n - k + 1))//k
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d[k] = d[n - k] = a
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return d
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def multinomial_coefficients(m, n):
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r"""Return a dictionary containing pairs ``{(k1,k2,..,km) : C_kn}``
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where ``C_kn`` are multinomial coefficients such that
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``n=k1+k2+..+km``.
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Examples
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========
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>>> from sympy.ntheory import multinomial_coefficients
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>>> multinomial_coefficients(2, 5) # indirect doctest
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{(0, 5): 1, (1, 4): 5, (2, 3): 10, (3, 2): 10, (4, 1): 5, (5, 0): 1}
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Notes
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=====
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The algorithm is based on the following result:
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.. math::
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\binom{n}{k_1, \ldots, k_m} =
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\frac{k_1 + 1}{n - k_1} \sum_{i=2}^m \binom{n}{k_1 + 1, \ldots, k_i - 1, \ldots}
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Code contributed to Sage by Yann Laigle-Chapuy, copied with permission
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of the author.
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See Also
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========
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binomial_coefficients_list, binomial_coefficients
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"""
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m = as_int(m)
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n = as_int(n)
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if not m:
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if n:
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return {}
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return {(): 1}
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if m == 2:
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return binomial_coefficients(n)
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if m >= 2*n and n > 1:
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return dict(multinomial_coefficients_iterator(m, n))
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t = [n] + [0] * (m - 1)
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r = {tuple(t): 1}
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if n:
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j = 0 # j will be the leftmost nonzero position
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else:
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j = m
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# enumerate tuples in co-lex order
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while j < m - 1:
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# compute next tuple
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tj = t[j]
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if j:
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t[j] = 0
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t[0] = tj
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if tj > 1:
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t[j + 1] += 1
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j = 0
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start = 1
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v = 0
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else:
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j += 1
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start = j + 1
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v = r[tuple(t)]
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t[j] += 1
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# compute the value
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# NB: the initialization of v was done above
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for k in range(start, m):
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if t[k]:
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t[k] -= 1
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v += r[tuple(t)]
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t[k] += 1
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t[0] -= 1
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r[tuple(t)] = (v * tj) // (n - t[0])
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return r
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def multinomial_coefficients_iterator(m, n, _tuple=tuple):
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"""multinomial coefficient iterator
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This routine has been optimized for `m` large with respect to `n` by taking
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advantage of the fact that when the monomial tuples `t` are stripped of
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zeros, their coefficient is the same as that of the monomial tuples from
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``multinomial_coefficients(n, n)``. Therefore, the latter coefficients are
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precomputed to save memory and time.
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>>> from sympy.ntheory.multinomial import multinomial_coefficients
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>>> m53, m33 = multinomial_coefficients(5,3), multinomial_coefficients(3,3)
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>>> m53[(0,0,0,1,2)] == m53[(0,0,1,0,2)] == m53[(1,0,2,0,0)] == m33[(0,1,2)]
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True
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Examples
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========
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>>> from sympy.ntheory.multinomial import multinomial_coefficients_iterator
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>>> it = multinomial_coefficients_iterator(20,3)
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>>> next(it)
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((3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), 1)
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"""
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m = as_int(m)
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n = as_int(n)
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if m < 2*n or n == 1:
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mc = multinomial_coefficients(m, n)
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yield from mc.items()
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else:
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mc = multinomial_coefficients(n, n)
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mc1 = {}
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for k, v in mc.items():
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mc1[_tuple(filter(None, k))] = v
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mc = mc1
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t = [n] + [0] * (m - 1)
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t1 = _tuple(t)
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b = _tuple(filter(None, t1))
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yield (t1, mc[b])
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if n:
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j = 0 # j will be the leftmost nonzero position
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else:
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j = m
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# enumerate tuples in co-lex order
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while j < m - 1:
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# compute next tuple
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tj = t[j]
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if j:
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t[j] = 0
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t[0] = tj
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if tj > 1:
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t[j + 1] += 1
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j = 0
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else:
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j += 1
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t[j] += 1
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t[0] -= 1
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t1 = _tuple(t)
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b = _tuple(filter(None, t1))
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yield (t1, mc[b])
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