Removed completed TODOs.

ANN_Training.py

@@ -6,15 +6,6 @@ Code-Style: E226, W503
 Docstring-Style: D200, D400
 
 TODO: Add README for ANN training
-TODO: Fix random seed -> Done
-TODO: Improve file structure and naming (e.g. use '.' instead of '__') -> Done
-TODO: Write-protect all data and models -> Done
-TODO: Put legend outside plot (bbox_to_anchor) -> Done
-TODO: Improve legend layout -> Done
-TODO: Put plotting into separate function -> Done
-TODO: Reduce number of testing epochs to 50 -> Done
-TODO: Rename 'data_directory' to 'data_dir' -> Done
-TODO: Add comments -> Done
 
 """
 import numpy as np

DG_Approximation.py

@@ -3,8 +3,6 @@
 @author: Laura C. Kühle
 
 Urgent:
-TODO: Add way of saving data (np.savez('data/' + name,
-    coefficients=projection, troubled_cells=troubled_cells)) -> Done
 TODO: Move plotting into separate function
 TODO: Adapt TCD from Soraya
     (Dropbox->...->TEST_troubled-cell-detector->Troubled_Cell_Detector)
@@ -17,7 +15,6 @@ TODO: Adjust code to allow classes for all equations
     (Burger, linear advection, 1D Euler)
 
 Currently not critical:
-TODO: Remove object inheritance from classes -> Done
 TODO: Replace loops with list comprehension if feasible
 TODO: Check whether 'projection' is always a np.array()
 TODO: Check whether all instance variables are sensible
@@ -375,7 +372,7 @@ class DGScheme:
         return np.transpose(np.array(output_matrix))
 
     def build_training_data(self, adjustment, stencil_length,
-                            initial_condition=None):
+                            add_reconstructions, initial_condition=None):
         """Builds training data set.
 
         Initializes projection and calculates cell averages and