Easy flake8 via yapf

Libensemble · Oct 5, 2021 · 9465e8f · 9465e8f
1 parent 685e6c4
commit 9465e8f
Showing 1 changed file with 12 additions and 16 deletions.
diff --git a/libensemble/tests/scaling_tests/persistent_gp/run_example.py b/libensemble/tests/scaling_tests/persistent_gp/run_example.py
@@ -10,14 +10,14 @@
 from libensemble.libE import libE
 from libensemble import logger
 from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens
-from libensemble.executors.mpi_executor import MPIExecutor
 from libensemble.tools import save_libE_output, add_unique_random_streams
 from libensemble.tools import parse_args
 from libensemble.message_numbers import WORKER_DONE
 from libensemble.gen_funcs.persistent_gp import persistent_gp_mf_gen_f
 
 nworkers, is_master, libE_specs, _ = parse_args()
 
+
 def run_simulation(H, persis_info, sim_specs, libE_info):
     # Extract input parameters
     values = list(H['x'][0])
@@ -30,15 +30,15 @@ def run_simulation(H, persis_info, sim_specs, libE_info):
     calc_status = WORKER_DONE
 
     # Function that depends on the resolution parameter
-    libE_output['f'] = -(x0 + 10*np.cos(x0 + 0.1*z))*(x1 + 5*np.cos(x1 - 0.2*z))
+    libE_output['f'] = -(x0 + 10 * np.cos(x0 + 0.1 * z)) * (x1 + 5 * np.cos(x1 - 0.2 * z))
 
     return libE_output, persis_info, calc_status
 
+
 sim_specs = {
     'sim_f': run_simulation,
     'in': ['x', 'z'],
-    'out': [ ('f', float) ],
-}
+    'out': [('f', float)], }
 
 gen_specs = {
     # Generator function. Will randomly generate new sim inputs 'x'.
@@ -48,27 +48,24 @@ def run_simulation(H, persis_info, sim_specs, libE_info):
     'persis_in': ['sim_id', 'x', 'f', 'z'],
     'out': [
         # parameters to input into the simulation.
-        ('x', float, (2,)),
+        ('x', float, (2, )),
         ('z', float),
-        ('resource_sets', int)
-    ],
+        ('resource_sets', int)],
     'user': {
         'range': [1, 8],
         'cost_func': lambda z: z[0],
         # Total max number of sims running concurrently.
-        'gen_batch_size': nworkers-1,
+        'gen_batch_size': nworkers - 1,
         # Lower bound for the n parameters.
-        'lb': np.array([ 0, 0 ]),
+        'lb': np.array([0, 0]),
         # Upper bound for the n parameters.
-        'ub': np.array([ 15, 15 ])
-    }
-}
+        'ub': np.array([15, 15])}}
 
 alloc_specs = {
     'alloc_f': only_persistent_gens,
     'out': [('given_back', bool)],
-    'user': {'async_return': True}
-}
+    'user': {
+        'async_return': True}, }
 
 # libE logger
 logger.set_level('INFO')
@@ -80,8 +77,7 @@ def run_simulation(H, persis_info, sim_specs, libE_info):
 persis_info = add_unique_random_streams({}, nworkers + 1)
 
 # Run LibEnsemble, and store results in history array H
-H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria,
-                            persis_info, alloc_specs, libE_specs)
+H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria, persis_info, alloc_specs, libE_specs)
 
 # Save results to numpy file
 if is_master: