Integrate Slice Sampling: Generalised Elliptical. #900
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@@ Coverage Diff @@
## master #900 +/- ##
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- Coverage 100% 99.6% -0.4%
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Files 55 56 +1
Lines 5673 5839 +166
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+ Hits 5673 5816 +143
- Misses 0 23 +23
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MichaelClerx
reviewed
Oct 8, 2019
| self._ready_for_tell = True | ||
| return np.array(self._proposed_sample, copy=True) | ||
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| def tell(self, reply): |
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reply can just be called fx here
MichaelClerx
reviewed
Oct 8, 2019
| # Unpack reply | ||
| fx = np.asarray(reply, dtype=float) | ||
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| # Very first call |
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# Ensure fx is a float
fx = float(fx)
MichaelClerx
reviewed
Oct 8, 2019
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| # First run | ||
| x = mcmc.ask() | ||
| fx = log_pdf.evaluateS1(x)[0] |
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fx = log_pdf(x0) --> don't calculate sensitivities!
MichaelClerx
reviewed
Oct 8, 2019
| # Second run | ||
| x = mcmc.ask() | ||
| self.assertTrue(np.all(x == x0)) | ||
| fx = log_pdf.evaluateS1(x)[0] |
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fx = log_pdf(x0) --> don't calculate sensitivities!
etc
MichaelClerx
reviewed
Oct 8, 2019
| Sets mean of the Gaussian distribution from which we | ||
| draw the starting samples. | ||
| """ | ||
| if type(mean) == int or float: |
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@ben18785 how's it going with all the slice samplers? I thought they were all nearly done but it seems to have slowed down |
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See #772