can now read (pdb) trajectories without topology

src/molearn/data/pdb_data.py

@@ -59,14 +59,21 @@ def __init__(self, filename=None, topology=None, fix_terminal=False, atoms=None)
             if atoms is not None:
                 self.atomselect(atoms=atoms)
 
-    def import_pdb(self, filename: str | list[str], topology: str):
+    def import_pdb(self, filename: str | list[str], topology: str | None):
         """
         Load one or multiple trajectory files
 
-        :parameter
-            * filename: the path the the trajectory as a str or a list of filepaths to multiple trajectories
+        :param str | list[str] filename: the path the trajectory as a str or a list of filepaths to multiple trajectories
+        :param str | None topology: the path the topology file for the trajector(y)ies
         """
-        self._mol = mda.Universe(topology, filename)
+
+        if isinstance(filename, list) and topology is None:
+            first_universe = mda.Universe(filename[0])
+            self._mol = mda.Universe(first_universe._topology, filename)
+        elif topology is None:
+            self._mol = mda.Universe(filename)
+        else:
+            self._mol = mda.Universe(topology, filename)
 
     def fix_terminal(self):
         """
@@ -118,7 +125,7 @@ def prepare_dataset(self):
         self.dataset /= self.std
         self.dataset = torch.from_numpy(self.dataset).float()
         self.dataset = self.dataset.permute(0, 2, 1)
-        print(f"Dataset shape: {', '.join([str(i) for i in self.dataset.shape])}")
+        print(f"Dataset shape: {self.dataset.shape}")
         print(f"mean: {str(self.mean)}\n std: {str(self.std)}")
 
     def get_atominfo(self):