a bit of cleanup after code review

Author: segasai

py/dynesty/bounding.py

@@ -45,6 +45,35 @@
 # these are the exitsing bounds implemented here
 
 
+def _slogdet_checked(matrix):
+    """
+    Compute the log-determinant and check that it's positive.
+
+    Parameters
+    ----------
+    matrix : array_like
+        Matrix to compute determinant for.
+
+    Returns
+    -------
+    detln : float
+        Natural log of the absolute value of the determinant.
+
+    Raises
+    ------
+    ValueError
+        If the determinant is not positive.
+    """
+    detsign, detln = linalg.slogdet(matrix)
+    if detsign <= 0:
+        raise ValueError(
+            f"Invalid ellipsoid: covariance matrix has non-positive determinant "
+            f"(sign={detsign}). This may indicate degenerate live points or "
+            f"numerical instability. Matrix shape: {matrix.shape}"
+        )
+    return detln
+
+
 class Bound:
     """
     This is is master class for the all the bounds listing
@@ -729,8 +758,7 @@ def __init__(self, ndim, cov=None):
         self.axes = lalg.sqrtm(self.cov)
         self.axes_inv = lalg.pinvh(self.axes)
 
-        detsign, detln = linalg.slogdet(self.am)
-        assert detsign > 0
+        detln = _slogdet_checked(self.am)
         self.logvol = logvol_prefactor(self.ndim) - 0.5 * detln
         self.funit = 1
         self.ctrs = []  # placeholder
@@ -922,8 +950,7 @@ def update(self,
         self.ctrs = points
 
         # Compute volume.
-        detsign, detln = linalg.slogdet(self.am)
-        assert detsign > 0
+        detln = _slogdet_checked(self.am)
         self.logvol = (logvol_prefactor(self.ndim) - 0.5 * detln)
 
         # Estimate the volume and fractional overlap with the unit cube
@@ -997,8 +1024,7 @@ def __init__(self, ndim, cov=None):
         self.axes = lalg.sqrtm(self.cov)
         self.axes_inv = lalg.pinvh(self.axes)
 
-        detsign, detln = linalg.slogdet(self.am)
-        assert detsign > 0
+        detln = _slogdet_checked(self.am)
         self.logvol = self.ndim * np.log(2.) - 0.5 * detln
         self.funit = 1
         self.ctrs = []
@@ -1190,8 +1216,7 @@ def update(self,
         self.axes *= hsmax
         self.axes_inv /= hsmax
 
-        detsign, detln = linalg.slogdet(self.am)
-        assert detsign > 0
+        detln = _slogdet_checked(self.am)
         self.logvol = (self.ndim * np.log(2.) - 0.5 * detln)
 
         # Estimate the volume and fractional overlap with the unit cube

py/dynesty/plotting.py

@@ -660,7 +660,7 @@ def traceplot(results,
         try:
             ids = connect_highlight[0]
             ids = connect_highlight
-        except:
+        except Exception:
             ids = rstate.choice(uid, size=connect_highlight, replace=False)
 
     # Determine plotting bounds for marginalized 1-D posteriors.
@@ -1015,7 +1015,7 @@ def cornerpoints(results,
         for j, y in enumerate(samples[:-1]):
             try:
                 ax = axes[i, j]
-            except:
+            except Exception:
                 ax = axes
             # Setup axes.
             if span is not None:
@@ -1682,7 +1682,7 @@ def boundplot(results,
                 r = -(nlive + i)
                 uidx = samples_id[r]
                 live_u[uidx] = samples[r]
-        except:
+        except Exception:
             # In the dynamic sampling case, we will show the live points used
             # during the batch associated with a particular iteration/bound.
             batch = results['samples_batch'][it]  # select batch
@@ -1735,7 +1735,7 @@ def boundplot(results,
                     r = -(nlive + i)
                     uidx = samples_id[r]
                     live_u[uidx] = samples[r]
-            except:
+            except Exception:
                 raise ValueError("Live point tracking currently not "
                                  "implemented for dynamic sampling results.")
         # Draw samples.
@@ -2003,7 +2003,7 @@ def cornerbound(results,
                 r = -(nlive + i)
                 uidx = samples_id[r]
                 live_u[uidx] = samples[r]
-        except:
+        except Exception:
             # In the dynamic sampling case, we will show the live points used
             # during the batch associated with a particular iteration/bound.
             if it is not None:
@@ -2314,7 +2314,7 @@ def _hist2d(x,
     for i, v0 in enumerate(levels):
         try:
             V[i] = Hflat[sm <= v0][-1]
-        except:
+        except Exception:
             V[i] = Hflat[0]
     V.sort()
     m = (np.diff(V) == 0)

py/dynesty/sampler.py

@@ -228,7 +228,7 @@ def _initialize_live_points(live_points,
                         "log-likelihood.")
                 else:
                     # If we found nothing after many attempts, raise the alarm.
-                    warnings.warn(f"After {n_attempts} attempts, we cound not "
+                    warnings.warn(f"After {n_attempts} attempts, we could not "
                                   f"find at least {min_npoints} points "
                                   "that have a valid log-likelihood! "
                                   "The initial sampling is very inefficient!")