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Extend the top end of the adaptive time grid to include large values #7
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hyanwong
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Extend the top end of the adaptive grid to include large values
Extend the top end of the adaptive time grid to include large values
Sep 5, 2019
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Jan 9, 2023
Finally fixes tskit-dev#7 and produces a much nicer looking fit for large tree sequences, but leads to slightly worse performance for tiny tree sequences such as those tested in test_accuracy.py, because of tskit-dev#230. When we fix that, this PR should provide uniformly better performance, I hope
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Mar 21, 2023
Finally fixes tskit-dev#7 and produces a much nicer looking fit for large tree sequences, but leads to slightly worse performance for tiny tree sequences such as those tested in test_accuracy.py, because of tskit-dev#230. When we fix that, this PR should provide uniformly better performance, I hope
hyanwong
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Jun 14, 2023
Finally fixes tskit-dev#7 and produces a much nicer looking fit for large tree sequences, but leads to slightly worse performance for tiny tree sequences such as those tested in test_accuracy.py, because of tskit-dev#230. When we fix that, this PR should provide uniformly better performance, I hope
Simple fix is in #233 |
hyanwong
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Jul 13, 2023
Finally fixes tskit-dev#7 and produces a much nicer looking fit for large tree sequences, but leads to slightly worse performance for tiny tree sequences such as those tested in test_accuracy.py, because of tskit-dev#230. When we fix that, this PR should provide uniformly better performance, I hope
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At the moment we do not include the quantile=1 upper value, as (for the beta distribution) this is infinite. I think this might explain why we often truncate the oldest MRCAs to be too recent. There should be a relatively easy way to extend the time grid to incorporate a higher upper bound (probably something to ask Gil about)
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