From a4b1105c54978a80363d0d73daa07dd6b41c0fff Mon Sep 17 00:00:00 2001
From: sebastiankloth <kloth@mailbox.org>
Date: Fri, 16 Jun 2023 08:41:19 +0200
Subject: [PATCH] Removed try except block from shifted_correlation.

---
 mdevaluate/correlation.py | 32 +++++++++++++++-----------------
 1 file changed, 15 insertions(+), 17 deletions(-)

diff --git a/mdevaluate/correlation.py b/mdevaluate/correlation.py
index 74a4bc3..fc7c931 100644
--- a/mdevaluate/correlation.py
+++ b/mdevaluate/correlation.py
@@ -10,10 +10,12 @@ from .utils import filon_fourier_transformation, coherent_sum, histogram
 from .pbc import pbc_diff
 from .logging import logger
 
+
 def set_has_counter(func):
     func.has_counter = True
     return func
 
+
 def log_indices(first, last, num=100):
     ls = np.logspace(0, np.log10(last - first + 1), num=num)
     return np.unique(np.int_(ls) - 1 + first)
@@ -26,7 +28,6 @@ def correlation(function, frames):
 
 
 def subensemble_correlation(selector_function, correlation_function=correlation):
-
     def c(function, frames):
         iterator = iter(frames)
         start_frame = next(iterator)
@@ -128,7 +129,7 @@ def shifted_correlation(function, frames, selector=None, segments=10,
         Calculating the mean square displacement of a coordinates object named ``coords``:
 
         >>> time, data = shifted_correlation(msd, coords)
-    """                        
+    """
     def get_correlation(start_frame, idx, selector=None):
         shifted_idx = idx + start_frame
         if selector:
@@ -156,26 +157,22 @@ def shifted_correlation(function, frames, selector=None, segments=10,
     idx = np.unique(np.int_(ls) - 1)
     t = np.array([frames[i].time for i in idx]) - frames[0].time
     
-    if nodes==1:
+    if nodes == 1:
         result = np.array([get_correlation(start_frame, idx=idx, 
-                                            selector=selector)
-                            for start_frame in start_frames])
+                                           selector=selector)
+                           for start_frame in start_frames])
     else:
         pool = ProcessPool(nodes=nodes)
-        try:
-            result = np.array(pool.map(partial(get_correlation, idx=idx, 
-                                               selector=selector), 
-                                       start_frames))
-        except Exception:
-            logger.warning("Something went wrong while calculating the shifted correlation!")
-        finally:
-            pool.terminate()
-            pool.restart()                           
+        result = np.array(pool.map(partial(get_correlation, idx=idx,
+                                           selector=selector),
+                                   start_frames))
+        pool.terminate()
+        pool.restart()
     
     if average == True:
         clean_result = []
         for entry in result:
-            if np.all(entry==0):
+            if np.all(entry == 0):
                 continue
             else:
                 clean_result.append(entry)      
@@ -206,14 +203,15 @@ def isf(start, frame, q, box=None):
 
 def rotational_autocorrelation(onset, frame, order=2):
     """
-    Compute the rotaional autocorrelation of the legendre polynamial for the given vectors.
+    Compute the rotational autocorrelation of the legendre polynomial for the
+    given vectors.
 
     Args:
         onset, frame: CoordinateFrames of vectors
         order (opt.): Order of the legendre polynomial.
 
     Returns:
-        Skalar value of the correltaion function.
+        Scalar value of the correlation function.
     """
     scalar_prod = (onset * frame).sum(axis=-1)
     poly = legendre(order)