fixed indentation

Author: gezmi

biopandas/align/tmalign.py

@@ -189,30 +189,30 @@ def run_tmalign(self, target: str, mobile: str, matrix_file_path: str=None) -> (
 
 
     def tmalign_in_stack(self, stack: PandasPdbStack, mobile_chains: dict, target: str=None) -> (PandasPdbStack, dict):
-      """For doing TMalign inside a stack, with one of its entries
-      :param stack: PandasPdbStack with the structures to align. All of them must have only one chain!
-      :param target: the target structure to align to. If not provided, the first structure in the stack will be used.
+        """For doing TMalign inside a stack, with one of its entries
+        :param stack: PandasPdbStack with the structures to align. All of them must have only one chain!
+        :param target: the target structure to align to. If not provided, the first structure in the stack will be used.
 
-      :return: matrix_file_path, tm_score
-      """
+        :return: matrix_file_path, tm_score
+        """
 
-      # if target is provided, check if it is in the stack and use it as the target
-      if target:
-          if target not in stack.pdbs:
-              raise ValueError("Target not found in the stack!")
-          else:
-              target_pdb_id = target
-      else:
-          # get one structure from the stack - this will be the target. sort by alphabet
-          target_pdb_id = sorted(stack.pdbs.keys())[0]
+        # if target is provided, check if it is in the stack and use it as the target
+        if target:
+            if target not in stack.pdbs:
+                raise ValueError("Target not found in the stack!")
+            else:
+                target_pdb_id = target
+        else:
+            # get one structure from the stack - this will be the target. sort by alphabet
+            target_pdb_id = sorted(stack.pdbs.keys())[0]
 
-      target_pdb = stack.pdbs[target_pdb_id]
-      target_chain_id = target_pdb.df['ATOM']['chain_id'].unique()[0]
+        target_pdb = stack.pdbs[target_pdb_id]
+        target_chain_id = target_pdb.df['ATOM']['chain_id'].unique()[0]
 
-      mobile_pdbs = PandasPdbStack()
-      mobile_pdbs.pdbs = {pdb_id: pdb for pdb_id, pdb in stack.pdbs.items() if pdb_id != target_pdb_id}
+        mobile_pdbs = PandasPdbStack()
+        mobile_pdbs.pdbs = {pdb_id: pdb for pdb_id, pdb in stack.pdbs.items() if pdb_id != target_pdb_id}
 
-      # align the structures
-      transformed_structures, tm_scores = self.tmalign_to(target_pdb, mobile_pdbs, target_chain_id, mobile_chains)
+        # align the structures
+        transformed_structures, tm_scores = self.tmalign_to(target_pdb, mobile_pdbs, target_chain_id, mobile_chains)
 
-      return target_pdb_id, transformed_structures, tm_scores
+        return target_pdb_id, transformed_structures, tm_scores