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total -> ['etapi::reZ::resAmp1', 'etapi::reZ::resAmp3', 'etapi::imZ::resAmp2', 'etapi::reZ::resAmp2', 'etapi::imZ::resAmp1', 'etapi::imZ::resAmp3']
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total -> ['etapi::imZ::resAmp1', 'etapi::reZ::resAmp2', 'etapi::imZ::resAmp2', 'etapi::reZ::resAmp1', 'etapi::reZ::resAmp3', 'etapi::imZ::resAmp3']
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<divclass="output stderr highlight-myst-ansi notranslate"><divclass="highlight"><pre><span></span>The chain is shorter than 50 times the integrated autocorrelation time for 5 parameter(s). Use this estimate with caution and run a longer chain!
@@ -744,7 +747,7 @@ <h1>Markov Chain Monte Carlo<a class="headerlink" href="#markov-chain-monte-carl
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MCMC intensity samples saved to mcmc/samples_intensity.feather
pa<spanclass="w"></span>run_momentPlotter<spanclass="w"></span><spanclass="nv">$yaml</span><spanclass="w"></span>-n<spanclass="w"></span><spanclass="m">10</span><spanclass="w"></span><spanclass="c1"># make a subdirectory at NiftyFits/plots/moments overlaying projected moments from nifty and amptools fits</span>
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pa<spanclass="w"></span>run_resultDump<spanclass="w"></span><spanclass="nv">$yaml</span><spanclass="w"></span>-n<spanclass="w"></span><spanclass="m">10</span><spanclass="w"></span><spanclass="c1"># dump all results to csv files (if possible, it will calculate the moments also)</span>
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