Merge pull request #505 from joshspeagle/eta_branch

Show the ETA during sampling using an estimate of expected number of iterations

Author: segasai

CHANGELOG.md

@@ -7,10 +7,12 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 [Unreleased]
 ### Added
 ### Changed
+- Show the ETA and expected number of iterations when sampling.
 - When restoring the sampler with the pool, use an updated value of `queue_size` based on the pool size
 - Use `chunksize=1` for the dynesty pool, as that is better behaved for `queue_size > nthreads` and unequal durations of function evaluations
 - When starting dynesty with a multiprocessing pool, dynesty now tries to use the `_processes` keyword to determine how many CPUs are available. This should reduce the need for manual `queue_size` specification
 ### Fixed
+- Previously when restoring a saved sampler and starting running the it/s speeds shown in the progress bar were incorrect, because they did not take into account the previously evaluated iterations.
 
 [3.0.0 - 2025-10-04]
 ### Added

docs/source/faq.rst

@@ -261,6 +261,11 @@ with (3) a large number of varying live points can make the stopping criteria
 difficult to evaluate quickly. See 
 :ref:`Nested Sampling Errors` for additional details.
 
+**When fitting, the estimated time of sampling varies a lot from iteration to
+iteration**
+
+This is normal. There is no way to accurately know how many iterations of nested sampling will be needed and how long it will take. The estimate of total time is particularly uncertaintain in the beginning of the sampling. The time can also jump significantly every time a new location of the in the posterior with a particularly high log(l) value is discovered.
+
 
 Live Point Questions
 --------------------

py/dynesty/dynamicsampler.py

@@ -447,6 +447,7 @@ def _configure_batch_sampler(main_sampler,
                                     boundidx=0,
                                     bounditer=0,
                                     eff=main_sampler.eff,
+                                    delta_logz=np.nan,
                                     proposal_stats=None))
         batch_sampler.update_bound_if_needed(logl_min)
         # Trigger an update of the internal bounding distribution based
@@ -583,6 +584,7 @@ def _configure_batch_sampler(main_sampler,
                                     boundidx=live_bound[i],
                                     bounditer=live_bound[i],
                                     eff=main_sampler.eff,
+                                    delta_logz=np.nan,
                                     proposal_stats=live_proposal_stats[i]))
     niter += nlive_new
     # Overwrite the previous set of live points in our internal sampler
@@ -1410,6 +1412,7 @@ def sample_batch(self,
                                       boundidx=results.boundidx,
                                       bounditer=results.bounditer,
                                       eff=self.eff,
+                                      delta_logz=results.delta_logz,
                                       proposal_stats=results.proposal_stats)
         if iterated_batch and results.loglstar < logl_max and np.isfinite(
                 logl_max) and maxiter_left > 0 and maxcall_left > 0:
@@ -1456,6 +1459,7 @@ def sample_batch(self,
                                       boundidx=results.boundidx,
                                       bounditer=results.bounditer,
                                       eff=self.eff,
+                                      delta_logz=np.nan,
                                       proposal_stats=None)
         del self.batch_sampler
         self.batch_sampler = None
@@ -1822,7 +1826,9 @@ def run_nested(self,
                 return
 
         # Baseline run.
-        pbar, print_func = get_print_func(print_func, print_progress)
+        pbar, print_func = get_print_func(print_func,
+                                          print_progress,
+                                          initial=self.it - 1)
         self.checkpoint_timer = DelayTimer(checkpoint_every)
         try:
             # the init should be the first default stage, all other ones
@@ -2088,7 +2094,7 @@ def add_batch(self,
                         boundidx=cur_results.boundidx,
                         bounditer=cur_results.bounditer,
                         eff=cur_results.eff,
-                        delta_logz=np.nan,
+                        delta_logz=cur_results.delta_logz,
                         proposal_stats=cur_results.proposal_stats)
 
                     # Print progress.
@@ -2097,6 +2103,7 @@ def add_batch(self,
                                    niter,
                                    ncall,
                                    nbatch=n + 1,
+                                   dlogz=dlogz,
                                    stop_val=stop_val,
                                    logl_min=logl_min,
                                    logl_max=logl_max)

py/dynesty/sampler.py

@@ -1295,7 +1295,9 @@ def run_nested(self,
             return
 
         # Run the main nested sampling loop.
-        pbar, print_func = get_print_func(print_func, print_progress)
+        pbar, print_func = get_print_func(print_func,
+                                          print_progress,
+                                          initial=self.it - 1)
         if checkpoint_file is not None:
             timer = DelayTimer(checkpoint_every)
         try: