format a bit

Author: RoyStegeman

validphys2/src/validphys/commondata.py

@@ -6,9 +6,12 @@
 :py:mod:`validphys.coredata`
 
 """
+
+import functools
+
 from reportengine import collect
 from validphys.commondataparser import load_commondata
-import functools
+
 
 @functools.lru_cache
 def loaded_commondata_with_cuts(commondata, cuts):
@@ -37,5 +40,5 @@ def loaded_commondata_with_cuts(commondata, cuts):
 )
 
 groups_dataset_inputs_loaded_cd_with_cuts_byprocess = collect(
-     "loaded_commondata_with_cuts", ("group_dataset_inputs_by_process", "data")
- )
+    "loaded_commondata_with_cuts", ("group_dataset_inputs_by_process", "data")
+)

validphys2/src/validphys/config.py

@@ -1156,8 +1156,7 @@ def produce_loaded_user_covmat_path(self, user_covmat_path: str = ""):
             l = self.loader
             fileloc = l.check_vp_output_file(user_covmat_path)
             return fileloc
-        
-    
+
     @configparser.explicit_node
     def produce_covmat_custom(self, use_ht_uncertainties: bool = False):
         if use_ht_uncertainties:
@@ -1225,15 +1224,13 @@ def res(*args, **kwargs):
         # Set this to get the same filename regardless of the action.
         res.__name__ = "theory_covmat"
         return res
-    
-  
+
     @configparser.explicit_node
     def produce_combine_by_type_custom(self, use_ht_uncertainties: bool = False):
         if use_ht_uncertainties:
             return validphys.theorycovariance.construction.combine_by_type_ht
         return validphys.theorycovariance.construction.combine_by_type
 
-
     def produce_fitthcovmat(
         self, use_thcovmat_if_present: bool = False, fit: (str, type(None)) = None
     ):
@@ -1779,9 +1776,9 @@ def produce_filter_data(self, fakedata: bool = False, theorycovmatconfig=None):
         if not fakedata:
             return validphys.filters.filter_real_data
         else:
-            #if theorycovmatconfig is not None and theorycovmatconfig.get(
+            # if theorycovmatconfig is not None and theorycovmatconfig.get(
             #    "use_thcovmat_in_sampling"
-            #):
+            # ):
             #    # NOTE: By the time we run theory covmat closure tests,
             #    # hopefully the generation of pseudodata will be done in python.
             #    raise ConfigError(

validphys2/src/validphys/dataplots.py

@@ -2,8 +2,6 @@
 Plots of relations between data PDFs and fits.
 """
 
-from __future__ import generator_stop
-
 from collections import defaultdict
 from collections.abc import Sequence
 import itertools
@@ -28,7 +26,7 @@
 from validphys.coredata import KIN_NAMES
 from validphys.plotoptions.core import get_info, kitable, transform_result
 from validphys.results import chi2_stat_labels, chi2_stats
-from validphys.sumrules import POL_LIMS, partial_polarized_sum_rules
+from validphys.sumrules import POL_LIMS
 from validphys.utils import sane_groupby_iter, scale_from_grid, split_ranges
 
 log = logging.getLogger(__name__)
@@ -301,9 +299,7 @@ def _plot_fancy_impl(
         min_vals = []
         max_vals = []
         fig, ax = plotutils.subplots()
-        ax.set_title(
-            "{} {}".format(info.dataset_label, info.group_label(samefig_vals, info.figure_by))
-        )
+        ax.set_title(f"{info.dataset_label} {info.group_label(samefig_vals, info.figure_by)}")
 
         lineby = sane_groupby_iter(fig_data, info.line_by)
 
@@ -1494,7 +1490,7 @@ def next_options():
             # if group is None then make sure that shows on legend.
             key = str(group)
         elif marker_by == "kinematics":
-          key = None
+            key = None
         else:
             raise ValueError('Unknown marker_by value')
 
@@ -1526,8 +1522,10 @@ def next_options():
             # This is to get the label key
             coords = [], []
         if marker_by == "kinematics":
-            ht_magnitude = np.concatenate( cvdict[key]) / (coords[1] * (1 - coords[0]) )
-            out = ax.scatter(*coords, marker='.', c=ht_magnitude, cmap="viridis", norm=mcolors.LogNorm())
+            ht_magnitude = np.concatenate(cvdict[key]) / (coords[1] * (1 - coords[0]))
+            out = ax.scatter(
+                *coords, marker='.', c=ht_magnitude, cmap="viridis", norm=mcolors.LogNorm()
+            )
             clb = fig.colorbar(out)
             clb.ax.set_title(r'$F_\mathrm{exp}\frac{1}{Q^2(1-x)}$')
         ax.plot(*coords, label=key, markeredgewidth=1, markeredgecolor=None, **key_options[key])

validphys2/src/validphys/results.py

@@ -276,22 +276,29 @@ def group_kin_table_no_table(groups_data, groups_index):
     """Generate a table containing the kinematics and the process_type."""
     result_records = []
     for group_data in groups_data:
-      group_cd = group_data.load_commondata()
-      cd = np.concatenate(
-        [group_cd[i].commondata_table[['kin1','kin2','kin3','process']] for i in range(len(group_cd))],
-        axis=0
-      )
-      for index, dataset in enumerate(cd):
-        try:
-          process_name = dataset[3].name
-        except AttributeError:
-          process_name = dataset[3]
-        result_records.append(
-          dict([("kin_1", dataset[0]), 
-                ("kin_2", dataset[1]), 
-                ("kin_3", dataset[2]),
-                ("process_type", process_name)])
+        group_cd = group_data.load_commondata()
+        cd = np.concatenate(
+            [
+                group_cd[i].commondata_table[['kin1', 'kin2', 'kin3', 'process']]
+                for i in range(len(group_cd))
+            ],
+            axis=0,
         )
+        for index, dataset in enumerate(cd):
+            try:
+                process_name = dataset[3].name
+            except AttributeError:
+                process_name = dataset[3]
+            result_records.append(
+                dict(
+                    [
+                        ("kin_1", dataset[0]),
+                        ("kin_2", dataset[1]),
+                        ("kin_3", dataset[2]),
+                        ("process_type", process_name),
+                    ]
+                )
+            )
 
     if not result_records:
         log.warning("Empty records for group results")