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examples/DA_paper/1d_fes/fes.py

@@ -6,26 +6,39 @@
 mlt.Config.n_cores = 10
 
 if __name__ == '__main__':
-    us = mlt.UmbrellaSampling(zeta_func=mlt.AverageDistance((1,12), (6,11)),
-                              kappa=10)
+    us = mlt.UmbrellaSampling(
+        zeta_func=mlt.AverageDistance((1, 12), (6, 11)), kappa=10
+    )
     temp = 300
 
     neb = mlt.ConfigurationSet()
     neb.load_xyz(filename='neb_optimised.xyz', charge=0, mult=1)
-    
+
     irc = mlt.ConfigurationSet()
     for config in neb:
         config.box = Box([18.5, 18.5, 18.5])
         irc.append(config)
 
-    r112_reactant = np.linalg.norm(irc[0].atoms[1].coord-irc[0].atoms[12].coord)
-    r611_reactant = np.linalg.norm(irc[0].atoms[6].coord-irc[0].atoms[11].coord)
+    r112_reactant = np.linalg.norm(
+        irc[0].atoms[1].coord - irc[0].atoms[12].coord
+    )
+    r611_reactant = np.linalg.norm(
+        irc[0].atoms[6].coord - irc[0].atoms[11].coord
+    )
 
-    r112_product = np.linalg.norm(irc[-1].atoms[1].coord-irc[-1].atoms[12].coord)
-    r611_product = np.linalg.norm(irc[-1].atoms[6].coord-irc[-1].atoms[11].coord)
+    r112_product = np.linalg.norm(
+        irc[-1].atoms[1].coord - irc[-1].atoms[12].coord
+    )
+    r611_product = np.linalg.norm(
+        irc[-1].atoms[6].coord - irc[-1].atoms[11].coord
+    )
 
-    logger.info(f'average bond length in reactant is {(r112_reactant+r611_reactant)/2}')
-    logger.info(f'average bond length in product is {(r112_product+r611_product)/2}')
+    logger.info(
+        f'average bond length in reactant is {(r112_reactant+r611_reactant)/2}'
+    )
+    logger.info(
+        f'average bond length in product is {(r112_product+r611_product)/2}'
+    )
 
     irc.reverse()  # Go product -> reactant, the NEB path is from reactant -> product
 
@@ -37,31 +50,36 @@
 
     endo = mlt.potentials.ACE('endo_in_water_ace_wB97M', system)
 
-    us.run_umbrella_sampling(irc,
-                             mlp=endo,
-                             temp=temp,
-                             interval=5,
-                             dt=0.5,
-                             n_windows=15,
-                             init_ref=1.55,
-                             final_ref=4,
-                             ps=10)
+    us.run_umbrella_sampling(
+        irc,
+        mlp=endo,
+        temp=temp,
+        interval=5,
+        dt=0.5,
+        n_windows=15,
+        init_ref=1.55,
+        final_ref=4,
+        ps=10,
+    )
     us.save('wide_US')
 
     # Run a second, narrower US with a higher force constant
     us.kappa = 20
-    us.run_umbrella_sampling(irc,
-                             mlp=endo,
-                             temp=temp,
-                             interval=5,
-                             dt=0.5,
-                             n_windows=15,
-                             init_ref=1.7,
-                             final_ref=2.5,
-                             ps=10)
+    us.run_umbrella_sampling(
+        irc,
+        mlp=endo,
+        temp=temp,
+        interval=5,
+        dt=0.5,
+        n_windows=15,
+        init_ref=1.7,
+        final_ref=2.5,
+        ps=10,
+    )
 
     us.save('narrow_US')
 
-    total_us = mlt.UmbrellaSampling.from_folders('wide_US', 'narrow_US',
-                                                 temp=temp)
+    total_us = mlt.UmbrellaSampling.from_folders(
+        'wide_US', 'narrow_US', temp=temp
+    )
     total_us.wham()