precommit to exec script

Author: scarlehoff

n3fit/src/n3fit/scripts/evolven3fit.py

@@ -1,4 +1,5 @@
 """
+
 This module contains the CLI for evolven3fit
 """
 
@@ -177,11 +178,7 @@ def main():
 
         if args.actions == "produce_eko":
             tcard, opcard = eko_utils.construct_eko_cards(
-                nnpdf_theory,
-                x_grid,
-                op_card_info,
-                theory_card_info,
-                args.legacy40,
+                nnpdf_theory, x_grid, op_card_info, theory_card_info, args.legacy40
             )
         elif args.actions == "produce_eko_photon":
             tcard, opcard = eko_utils.construct_eko_photon_cards(

n3fit/src/n3fit/scripts/n3fit_exec.py

@@ -9,19 +9,19 @@
 import re
 import shutil
 import sys
-import pandas as pd
 
+import pandas as pd
 from ruamel.yaml import error
 
 from reportengine import colors
 from reportengine.namespaces import NSList
+from validphys.api import API
 from validphys.app import App
 from validphys.config import Config, ConfigError, Environment, EnvironmentError_
 from validphys.core import FitSpec
-from validphys.utils import yaml_safe
-from validphys.loader import FallbackLoader, HyperscanNotFound
-from validphys.api import API
 from validphys.hyperoptplot import generate_dictionary
+from validphys.loader import FallbackLoader, HyperscanNotFound
+from validphys.utils import yaml_safe
 
 loader = FallbackLoader()
 
@@ -240,38 +240,42 @@ def produce_hyperscanner(self, parameters, hyperscan_config=None, hyperopt=None)
                 "db_path": db_path,
             }
         return HyperScanner(parameters, hyperscan_config, **extra_args)
-    
+
     def parse_trial_specs(self, trial_specs):
         return trial_specs
-        
+
     def produce_trials(self, trial_specs={}):
-        """Read the input hyperscan and produce a dictionary containing 
+        """Read the input hyperscan and produce a dictionary containing
         the settings of the best trials"""
-        
+
         if not trial_specs:
             return {}
         else:
             try:
                 hyperscan = loader.check_hyperscan(trial_specs['hyperscan'])
             except HyperscanNotFound as e:
                 log.warning(e)
-            dict_trials = generate_dictionary(hyperscan.tries_files[1].parent,"average")
+            dict_trials = generate_dictionary(hyperscan.tries_files[1].parent, "average")
             hyperopt_dataframe = pd.DataFrame(dict_trials)
             n_termalization = trial_specs['thermalization']
             n_best = trial_specs['number_of_trials']
-            best = hyperopt_dataframe[n_termalization:].sort_values('loss')[:n_best].to_dict(orient='list')
+            best = (
+                hyperopt_dataframe[n_termalization:]
+                .sort_values('loss')[:n_best]
+                .to_dict(orient='list')
+            )
             best['number_of_trials'] = n_best
             return best
-        
+
 
 class N3FitApp(App):
     """The class which parsers and performs the fit"""
 
     environment_class = N3FitEnvironment
     config_class = N3FitConfig
 
-    def __init__(self):
-        super().__init__(name="n3fit", providers=N3FIT_PROVIDERS)
+    def __init__(self, name="n3fit", providers=N3FIT_PROVIDERS):
+        super().__init__(name=name, providers=providers)
 
     @property
     def argparser(self):

n3fit/src/n3fit/scripts/vp_setupfit.py

@@ -217,7 +217,7 @@ def from_yaml(cls, o, *args, **kwargs):
         trials_config = file_content.get('trial_specs', {})
         if trials_config:
             loader.check_hyperscan(trials_config['hyperscan'])
-    
+
         # Sets default values if they are not present in the runcard
         for k, v in SETUPFIT_DEFAULTS.items():
             file_content.setdefault(k, v)