Multivariate T #26
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Multivariate T #26
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hildensia
reviewed
Jan 28, 2021
setup.py
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| packages = ['bayesian_changepoint_detection'], | ||
| requires=['scipy', 'numpy'] | ||
| ) | ||
| setup( |
test.py
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| partial(offline.const_prior, l=(len(dataset) + 1)), | ||
| online.MultivariateT(10) | ||
| ) | ||
| # TODO: assertion |
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One possibility: just do a snapshot test here
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I'm not sure what you mean by this. Still, I've added an assertion based on #18 (comment)
…tection into multivariate
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Oops, a colleague just pointed out a huge flaw in my implementation. I'm putting this back to draft while I fix it. |
multimeric
commented
Feb 1, 2021
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Well, I don't love the accuracy of it, but does seem to output a meaningful signal for multiple changepoints. I also copied a plot function used in the notebook into the module for others' use. Here is an example calculated using the multivariate test data: |
hildensia
approved these changes
Feb 2, 2021
| dof = dims + 1 | ||
| # The default mean is all 0s | ||
| if mu is None: | ||
| mu = [0]*dims |
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pip install bayesian_changepoint_detection[dev]for development work (currently this installs pytest), orpip install bayesian_changepoint_detection[multivariate](enforces that you have a new enough scipy version for this new feature)