Support ContinuousFactor in likelihood weighted sampling #925
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Codecov Report
@@ Coverage Diff @@
## dev #925 +/- ##
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- Coverage 94.74% 94.66% -0.09%
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Files 114 114
Lines 11161 11219 +58
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+ Hits 10575 10620 +45
- Misses 586 599 +13
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khalibartan
reviewed
Nov 6, 2017
| @@ -96,6 +96,9 @@ def variables(self): | |||
| def variables(self, value): | |||
| self._variables = value | |||
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| def sample(self, size, evidence): | |||
| raise NotImplementedError('Coming soon...') | |||
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Message suggestion: Work in progress, maybe you can help us out :D
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OK. Let me know when you are ready, so I can rebase |
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@ankurankan I added continuous factor support in likelihood weighted sampling by encapsulating the sampling details in the corresponding factor classes. The same approach can be easily extended into other sampling methods.