Merge pull request #8 from NFFT/python-code-format-patches

Fixes by format action

Author: passscoed

simpleTest/exampleWavelet.py

@@ -84,7 +84,7 @@ def TestFunction(x):  # this function is of the form f_0 + f_1 + f_2 + f_3 + f_4
 gsis = ANOVAapprox.get_GSI(
     anova_model, 0.0
 )  # calculates indices for importance of terms (gsis is vector, with indices belonging to terms in anova_model.U)
-gsis_as_dict = ANOVAapprox.get_GSI(anova_model,0.0,dict=true)
+gsis_as_dict = ANOVAapprox.get_GSI(anova_model, 0.0, dict=true)
 
 y_min_calc = 10 ** (np.min(np.log10(gsis)) - 0.5)
 label = list(anova_model.U[1:])

src/pyANOVAapprox/__init__.py

@@ -9,6 +9,7 @@
 
 # from sklearn.metrics import roc_auc_score
 
+
 def bisection(l, r, fun, maxiter=1000):
     lval = fun(l)
     rval = fun(r)

src/pyANOVAapprox/errors.py

@@ -155,19 +155,20 @@ def _acc(a, lam, X, y):  # helpfunction for get_acc
 
     return np.sum(np.sign(y_eval) == y) / len(y) * 100.0
 
+
 def auc_score(y_true, y_pred_proba):
     combined_data = sorted(zip(y_pred_proba, y_true), key=lambda x: x[0], reverse=True)
-    
+
     P = sum(y_true)
     N = len(y_true) - P
-    
+
     tp, fp = 0, 0
     tpr, fpr = 0, 0
     auc = 0.0
 
     for i in range(len(combined_data)):
         score, label = combined_data[i]
-        
+
         current_tp = 0
         current_fp = 0
         j = i
@@ -177,12 +178,12 @@ def auc_score(y_true, y_pred_proba):
             else:
                 current_fp += 1
             j += 1
-        
+
         i = j - 1
 
         tp += current_tp
         fp += current_fp
-        
+
         new_tpr = tp / P
         new_fpr = fp / N
 
@@ -191,6 +192,7 @@ def auc_score(y_true, y_pred_proba):
         tpr, fpr = new_tpr, new_fpr
     return auc
 
+
 def get_acc(a, X=None, y=None, lam=None):
 
     if lam is not None:
@@ -216,9 +218,7 @@ def _auc(a, lam, X, y):
     return auc_score(y_int, y_sc)
 
 
-def get_auc(
-    a, X=None, y=None, lam=None
-):
+def get_auc(a, X=None, y=None, lam=None):
 
     if lam is not None:
         return _auc(a, lam, X, y)