typos

README.md

@@ -8,21 +8,21 @@ The main features include:
   * All unique zero-dipole symmetric terminations of slabs are cleaved from a bulk structure.
   * Slabs can be sorted into separate labelled folders, optionally with or all the required VASP input files to run each calculation.
 
-2. **Raw data parsing:** Extracting data from convergence tests. 
+2. **Raw data parsing:** Extracting data from convergence tests.
   * Parsing the convergence testing folders created using the slab generation scripts.
   * Plotting scripts visualising convergence (with respect to slab and vacuum thickness).
 
 3. **Analysis:** Various scripts for surface and bulk calculations.
-  * Electrostatic potential tool, based on Keith Butler's [Macrodensity](https://github.com/WMD-group/MacroDensity) code, for the calculation of absolute electron energies (ionisation potential, electron affinity). 
+  * Electrostatic potential tool, based on Keith Butler's [MacroDensity](https://github.com/WMD-group/MacroDensity) code, for the calculation of absolute electron energies (ionisation potential, electron affinity).
   * Nearest neighbours and bond analysis scripts.
 
-Surfaxe primarily supports VASP, however we would like to add support for other solid-state codes in the future. 
+Surfaxe primarily supports VASP, however we would like to add support for other solid-state codes in the future.
 
 Development notes
 -----------------
 
 ### Bugs, features and questions
-Please use the Issue Tracker to report bugs or request features in the first instance. 
+Please use the Issue Tracker to report bugs or request features in the first instance.
 
 ### Code contributions
 Contributions to interface with this package are most welcome. Please use the ["Fork and Pull"](https://guides.github.com/activities/forking/) workflow to make contributions and stick as closely as possible to the following:
@@ -58,7 +58,7 @@ Analysis:
 ## Installation
 Surfaxe is a Python 3 package and requires pymatgen and other standard scientific python packages.
 
-Recommended istallation is to git clone and install with `pip`:
+Recommended installation is to git clone and install with `pip`:
 
 ```sh
 git clone https://github.com/brlec/slabby-stabby.git

slabbystabby/generation.py

@@ -114,7 +114,7 @@ def get_one_hkl_slabs(structure, hkl, thicknesses, vacuums, make_fols=False,
                                         's_index': i,
                                         'slab': slab})
 
-    # iterate though provisional slabs to extract the unique slabs
+    # Iterate though provisional slabs to extract the unique slabs
     unique_list = []
     unique_list_of_dicts = []
     repeat = []
@@ -124,13 +124,13 @@ def get_one_hkl_slabs(structure, hkl, thicknesses, vacuums, make_fols=False,
         if slab['slab'] not in unique_list:
             unique_list.append(slab['slab'])
             unique_list_of_dicts.append(slab)
-            #for large slab size warning
+            # For large slab size warning
             atoms = len(slab['slab'].atomic_numbers)
             if atoms > max_size:
                 large.append('{}_{}_{}_{}'.format(slab['hkl'], slab['slab_t'],
                              slab['vac_t'], slab['s_index']))
 
-        # for repeat slabs warning
+        # For repeat slabs warning
         else:
             repeat.append('{}_{}_{}_{}'.format(slab['hkl'], slab['slab_t'],
                           slab['vac_t'], slab['s_index']))
@@ -149,10 +149,9 @@ def get_one_hkl_slabs(structure, hkl, thicknesses, vacuums, make_fols=False,
 
     # Makes folders hkl/slab_vac_index
     if make_fols is True:
-        os.mkdir(os.path.join(os.getcwd(),slab['hkl']))
         for slab in unique_list_of_dicts:
-            os.mkdir(r'{}/{}_{}_{}'.format(slab['hkl'], slab['slab_t'],
-                                           slab['vac_t'], slab['s_index']))
+            os.makedirs(os.path.join(os.getcwd(), r'{}/{}_{}_{}'.format(slab['hkl'],
+            slab['slab_t'], slab['vac_t'], slab['s_index'])), exist_ok=True)
 
             # Makes all input files (KPOINTS, POTCAR, INCAR) based on the config
             # dictionary