Comments (1)
Commit b93a548 fixes the issue.
Now all Markov chains with at least one well-defined transition matrix are correctly represented in the willow tree. For example, with n = 10, k = 5, and gamma = 0.2, we obtain:
Warning: P[0] wrongly specified.
Replacing with interpolated matrix if possible.
Warning: P[1] wrongly specified.
Replacing with interpolated matrix if possible.
P[2] successfully generated.
Warning: P[3] wrongly specified.
Replacing with interpolated matrix if possible.
Warning: t has been increased. t[1] = 0.60
Warning: t has been shortened. T = 0.80
So P[0]
, P[1]
, and P[3]
are automatically scrapped from the chain and now t = [0, 0.6, 0.8]
.
from willowtree.
Related Issues (9)
- Enhancement: Replace wrongly specified transition matrices. HOT 2
- Enhancement: Scrap last matrices in the chain if bad. HOT 1
- Bug: Last replaceable matrix in the chain not replaced; vector t always shortened. HOT 3
- Bug: LP algorithm occasionally returns probabilities outside range. HOT 3
- Enhancement: Scrap first matrices in the chain if bad. HOT 1
- Enhancement: Use Python's multiprocessing to speed up the algorithm.
- Bug: Probabilities on rows of transition matrices do not sum to 1. HOT 1
- Enhancement: Plot willow tree even if no transition matrix is well-defined. Case: k > 1. HOT 1
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from willowtree.