diff --git a/spine/io/read/hdf5.py b/spine/io/read/hdf5.py
index eb39f349..5f496ad5 100644
--- a/spine/io/read/hdf5.py
+++ b/spine/io/read/hdf5.py
@@ -1,6 +1,7 @@
 """Contains a reader class dedicated to loading data from HDF5 files."""
 
 import h5py
+import yaml
 import numpy as np
 from dataclasses import fields
 
@@ -123,6 +124,46 @@ def __init__(self, file_keys, limit_num_files=None, max_print_files=10,
         self.build_classes = build_classes
         self.skip_unknown_attrs = skip_unknown_attrs
 
+        # Process the configuration used to produce the HDF5 file
+        self.cfg = self.process_cfg()
+
+        # Process the SPINE version used to produced the HDF5 file
+        self.version = self.process_version()
+
+    def process_cfg(self):
+        """Fetches the SPINE configuration used to produce the HDF5 file.
+
+        Returns
+        -------
+        dict
+            Configuration dictionary
+        """
+        # Fetch the string-form configuration
+        with h5py.File(self.file_paths[0], 'r') as in_file:
+            cfg_str = in_file['info'].attrs['cfg']
+
+        # Attempt to parse it (need try for now for SPINE versions < v0.4.0)
+        try:
+            cfg = yaml.safe_load(cfg_str)
+        except:
+            return None
+
+        return cfg
+
+    def process_version(self):
+        """Returns the SPINE release version used to produce the HDF5 file.
+
+        Returns
+        -------
+        str
+            SPINE release tag
+        """
+        # Fetch the string-form configuration
+        with h5py.File(self.file_paths[0], 'r') as in_file:
+            version = in_file['info'].attrs['version']
+
+        return version
+
     def get(self, idx):
         """Returns a specific entry in the file.
 
diff --git a/spine/utils/gnn/cluster.py b/spine/utils/gnn/cluster.py
index 08de61a5..2d958470 100644
--- a/spine/utils/gnn/cluster.py
+++ b/spine/utils/gnn/cluster.py
@@ -1016,10 +1016,10 @@ def cluster_direction(voxels: nb.float64[:,:],
             # Get the eigenvalues, compute relative transverse spread
             w, _ = np.linalg.eigh(covk)
             labels[i] = np.sqrt(w[2] / (w[0] + w[1])) \
-                    if (w[0] + w[1]) / w[2] > 1e-9 else 0.
+                    if (w[0] + w[1]) / w[2] > 1e-6 else 0.
 
             # If the value is the same as the previous, choose this one
-            if dist_mat[i] == dist_mat[i-1]:
+            if labels[i] == labels[i-1]:
                 labels[i-1] = -1.
 
             # Increment mean and matrix