From 0dd8636c9865632f1d11527193eda3254685d5ee Mon Sep 17 00:00:00 2001
From: ejhigson <18406298+ejhigson@users.noreply.github.com>
Date: Mon, 1 Jul 2019 17:31:45 +0100
Subject: [PATCH] Fixing error in edge case where the optimum step at which to
 start the dynamic run is above zero but before the first available saved file
 from the initial exploratory run. In this case we do not reload the initial
 exporatory run and instead start the dynamic run by sampling the whole prior.

---
 dyPolyChord/run_dynamic_ns.py | 41 ++++++++++++++++++++---------------
 1 file changed, 23 insertions(+), 18 deletions(-)

diff --git a/dyPolyChord/run_dynamic_ns.py b/dyPolyChord/run_dynamic_ns.py
index 56e66de..fed52bd 100644
--- a/dyPolyChord/run_dynamic_ns.py
+++ b/dyPolyChord/run_dynamic_ns.py
@@ -49,10 +49,10 @@ def run_dypolychord(run_polychord, dynamic_goal, settings_dict_in, **kwargs):
     Further analysis, including estimating uncertainties, can be performed
     with ``nestcheck``.
 
-    Like for ``PolyChord``, the output files are saved in base_dir (specified in
-    settings_dict_in, default value is 'chains'). Their names are determined
-    by file_root (also specified in settings_dict_in). ``dyPolyChord`` ensures
-    the following following files are always produced:
+    Like for ``PolyChord``, the output files are saved in base_dir (specified
+    in settings_dict_in, default value is 'chains'). Their names are
+    determined by file_root (also specified in settings_dict_in).
+    ``dyPolyChord`` ensures the following following files are always produced:
 
         * [base_dir]/[file_root].stats: run statistics including an estimate of
           the Bayesian evidence;
@@ -270,20 +270,25 @@ def process_initial_run(settings_dict_in, **kwargs):
     if dyn_info['peak_start_ind'] != 0:
         # subtract 1 as ndead=1 corresponds to point 0
         resume_steps = np.asarray(step_ndead) - 1
-        # Work out which resume file to load
-        resume_ndead = step_ndead[np.where(
-            resume_steps < dyn_info['peak_start_ind'])[0][-1]]
-        # copy resume step to dynamic file root
-        shutil.copyfile(
-            root_name + '_init_' + str(resume_ndead) + '.resume',
-            root_name + '_dyn.resume')
-        # Save resume info
-        dyn_info['resume_ndead'] = resume_ndead
-        try:
-            dyn_info['resume_nlike'] = (
-                resume_outputs[resume_ndead]['nlike'])
-        except KeyError:
-            pass  # protect from error reading nlike from .stats file
+        # Work out which resume file to load. This is the first resume file
+        # before dyn_info['peak_start_ind']. If there are no such files then we
+        # do not reload and instead start the second dynamic run by samling
+        # from the entire prior.
+        indexes_before_peak = np.where(
+            resume_steps < dyn_info['peak_start_ind'])[0]
+        if indexes_before_peak.shape[0] > 0:
+            resume_ndead = step_ndead[indexes_before_peak[-1]]
+            # copy resume step to dynamic file root
+            shutil.copyfile(
+                root_name + '_init_' + str(resume_ndead) + '.resume',
+                root_name + '_dyn.resume')
+            # Save resume info
+            dyn_info['resume_ndead'] = resume_ndead
+            try:
+                dyn_info['resume_nlike'] = (
+                    resume_outputs[resume_ndead]['nlike'])
+            except KeyError:
+                pass  # protect from error reading nlike from .stats file
     nestcheck.io_utils.pickle_save(
         dyn_info, root_name + '_dyn_info', overwrite_existing=True)
     if dynamic_goal != 0: