undo egregious newlines, remove unnecessary method (#95)

convexengineering · Jul 13, 2021 · 9e820cb · 9e820cb
1 parent 412e90c
commit 9e820cb
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Showing 2 changed files with 4 additions and 26 deletions.
diff --git a/gpfit/constraint_set.py b/gpfit/constraint_set.py
@@ -96,10 +96,6 @@ def __init__(self, fitdata, ivar=None, dvars=None, name="", err_margin=None):
 
         ConstraintSet.__init__(self, [self.constraint])
 
-    def get_fitdata(self):
-        "return fit data"
-        return self.fitdata
-
     def get_dataframe(self):
         "return a pandas DataFrame of fit parameters"
         import pandas as pd

diff --git a/gpfit/least_squares.py b/gpfit/least_squares.py
@@ -159,17 +159,8 @@ def levenberg_marquardt(
             # dsp here so that all grad info is for updated point,
             # but lambda not yet updated
             if verbose:
-                print(
-                    formatstr
-                    % (
-                        itr,
-                        trialrms,
-                        maxgrad,
-                        lamb,
-                        norm(step),
-                        max(diagJJ)/min(diagJJ),
-                    )
-                )
+                print(formatstr % (itr, trialrms, maxgrad, lamb, norm(step),
+                                   max(diagJJ)/min(diagJJ)))
 
             if maxgrad < tolgrad:
                 if verbose:
@@ -183,17 +174,8 @@ def levenberg_marquardt(
             params_updated = True
         else:
             if verbose:
-                print(
-                    formatstr
-                    % (
-                        itr,
-                        trialrms,
-                        maxgrad,
-                        lamb,
-                        norm(step),
-                        max(diagJJ)/min(diagJJ),
-                    )
-                )
+                print(formatstr % (itr, trialrms, maxgrad, lamb, norm(step),
+                                   max(diagJJ)/min(diagJJ)))
             lamb = lamb*10
             prev_trial_accepted = False
             params_updated = False