# Simulate very long sequences once to see that LSA indeed goes toward 0.
import numpy as np

from simulate import simulate


for seqlen in [100, 1000, 2000, 3000]:
    print('\nSequences of length', seqlen)
    res, _ = simulate(seqlen, {'A': .5, 'B': .5}, remove_loops=False, verbose=True)
    for a in res['LSA']:
        for b in res['LSA'][a]:
            print(a, '=>', b, 'mean LSA =', np.nanmean(res['LSA'][a][b]))

aee18a737b6d1a1967ef79a25ccdb0c198c3a449
<mask token>

<mask token>
for seqlen in [100, 1000, 2000, 3000]:
    print('\nSequences of length', seqlen)
    res, _ = simulate(seqlen, {'A': 0.5, 'B': 0.5}, remove_loops=False,
        verbose=True)
    for a in res['LSA']:
        for b in res['LSA'][a]:
            print(a, '=>', b, 'mean LSA =', np.nanmean(res['LSA'][a][b]))

import numpy as np
from simulate import simulate
for seqlen in [100, 1000, 2000, 3000]:
    print('\nSequences of length', seqlen)
    res, _ = simulate(seqlen, {'A': 0.5, 'B': 0.5}, remove_loops=False,
        verbose=True)
    for a in res['LSA']:
        for b in res['LSA'][a]:
            print(a, '=>', b, 'mean LSA =', np.nanmean(res['LSA'][a][b]))

# Simulate very long sequences once to see that LSA indeed goes toward 0.
import numpy as np

from simulate import simulate


for seqlen in [100, 1000, 2000, 3000]:
    print('\nSequences of length', seqlen)
    res, _ = simulate(seqlen, {'A': .5, 'B': .5}, remove_loops=False, verbose=True)
    for a in res['LSA']:
        for b in res['LSA'][a]:
            print(a, '=>', b, 'mean LSA =', np.nanmean(res['LSA'][a][b]))
