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  1. import numpy as np
  2.  
  3. def generate_combos(n, k, z):
  4.     full_locs = np.arange(k + 1, dtype=np.uint)
  5.     full_locs[k] = n                      # makes partial vectorization easier
  6.     locs = full_locs[:k]                  # bit indices
  7.     counts = np.zeros(n, dtype=np.uint)   # counter buckets
  8.     values = np.arange(n, dtype=np.uint)  # values
  9.     min_index = 0                         # index of lowest non-exhausted bin
  10.  
  11.     for _ in range((n * z) // k):
  12.         counts[locs] += 1
  13.         yield values[locs]
  14.  
  15.         if counts[min_index] == z:
  16.             # if lowest bin filled, shift and reset
  17.             min_index += np.argmax(counts[min_index:] < z)
  18.             locs[:] = min_index + np.arange(k)
  19.         else:
  20.             # otherwise, increment highest available counter
  21.             i = np.flatnonzero(np.diff(full_locs))[-1]
  22.             locs[i] += 1
  23.             # reset the remainder
  24.             locs[i + 1:] = locs[i] + np.arange(1, k - i)
  25.  
  26. for i, v in enumerate(generate_combos(256, 3, 10)):
  27.     print(v)
  28.     if i == 99:
  29.         break
  30.  
  31.  
Success #stdin #stdout 0.23s 27264KB
comments (?)
stdin 
Standard input is empty
stdout 
[0 1 2]
[0 1 3]
[0 1 4]
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[0 1 6]
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[0 1 9]
[ 0  1 10]
[ 0  1 11]
[2 3 4]
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[2 3 8]
[2 3 9]
[ 2  3 10]
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[4 5 6]
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[6 7 8]
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[ 8  9 10]
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[10 11 12]
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[28 29 30]
[28 29 31]
https://ideone.com/t6M2rl
language:
Python 3 (python  3.12)
created:
5 years ago
visibility:
public

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