Merge pull request #97 from vladislavivanistsev/master

Some compatibility updates

catlearn/optimize/io.py

@@ -29,7 +29,7 @@ def ase_to_catlearn(list_atoms):
  images = []
  constraints = first_image.constraints
  number_images = len(list_atoms)
- num_atoms = first_image.get_number_of_atoms()
+ num_atoms = first_image.get_global_number_of_atoms()
  list_train = []
  list_targets = []
  list_gradients = []

catlearn/optimize/mlneb.py

@@ -7,7 +7,7 @@
 from ase.neb import NEBTools
 from ase.io import read, write
 from ase.optimize import MDMin
-from ase.parallel import parprint, rank, parallel_function
+from ase.parallel import parprint, world, parallel_function
 from scipy.spatial import distance
 import os
 from catlearn.regression import GaussianProcess
@@ -611,7 +611,7 @@ def run(self, fmax=0.05, unc_convergence=0.050, steps=500,
  parprint('The optimized predicted path can be found in: ',
  trajectory)
  # Clean up:
- if rank == 0:
+ if world.rank == 0:
  os.remove('./last_predicted_path.traj')
  os.remove('./all_predicted_paths.traj')
  break

tutorials/12_MLMin/3_GPAW/min_gpaw.py

@@ -63,7 +63,7 @@
 # 3. Summary of the results:
 ###############################################################################
 
-print('\n Summary of the results:\n ------------------------------------')
+parprint('\n Summary of the results:\n ------------------------------------')
 
 fire_results = read('results_fire.traj', ':')
 parprint('Number of function evaluations using FIRE:',