Added option to select plotting colors.

DG_Approximation.py

@@ -24,28 +24,23 @@ TODO: Discuss name for quadrature mesh (now: grid)
 Urgent:
 TODO: Added sign change in stiffness and boundary matrix to accommodate
     negative wave speed -> Done
-TODO: Force input_size for each ANN model to be stencil length
-TODO: Induce shift in IC class
-TODO: Unify print commands (f vs no f)
-TODO: Add method and error info to Mesh
-TODO: Add use of discontinuity position to all ICs
-TODO: Change maximum training degree to 6
-TODO: Change minimum training mesh size to 2^5
-TODO: Enforce shift to be positive for two-sided Heaviside
-TODO: Remove option to choose training domain
-TODO: Fix VisibleDeprecationWarning for ndarray encoding
-TODO: Give option to select plotting color
+TODO: Unify print commands (f vs no f) -> Done
+TODO: Add method and error info to Mesh -> Done
+TODO: Add use of discontinuity position to all ICs -> Done
+TODO: Change maximum training degree to 6 -> Done
+TODO: Change minimum training mesh size to 2^5 -> Done
+TODO: Enforce shift to be positive for two-sided Heaviside -> Done
+TODO: Remove option to choose training domain -> Done
+TODO: Fix VisibleDeprecationWarning for ndarray decoding -> Done
+TODO: Give option to select plotting color -> Done
 TODO: Move scripts into separate directory
 TODO: Outsource run commands in SM rules into separate files
 TODO: Move plot_approximation_results() into plotting script
 TODO: Introduce env files for each SM rule
-TODO: Restructure directories
-TODO: Add images to report
-TODO: Add verbose output
 
 Critical, but not urgent:
 TODO: Restructure 'calculate_approximate_solution()'
-TODO: Rework Theoretical TC for efficiency
+TODO: Rework Theoretical TCD for efficiency
 TODO: Extract object initialization from DGScheme
 TODO: Replace loops with list comprehension if feasible
 TODO: Replace loops/list comprehension with vectorization if feasible
@@ -68,6 +63,12 @@ TODO: Add a default model state
 TODO: Look into validators for variable checks
 
 Not feasible yet or doc-related:
+TODO: Replace pop() with get() for dictionary access
+TODO: Induce shift in IC class
+TODO: Force input_size for each ANN model to be stencil length
+TODO: Restructure directories
+TODO: Add images to report
+TODO: Add verbose output
 TODO: Adjust definitions of each IC to be dependent on domain
 TODO: Add README for ANN training
 TODO: Give detailed description of wavelet detection

Plotting.py

@@ -314,7 +314,7 @@ def plot_evaluation_results(evaluation_file: str, directory: str,
 
 
 def plot_approximation_results(data_file: str, directory: str, plot_name: str,
-                               quadrature: Quadrature,
+                               colors: dict, quadrature: Quadrature,
                                init_cond: InitialCondition) -> None:
     """Plots given approximation results.
 
@@ -329,6 +329,8 @@ def plot_approximation_results(data_file: str, directory: str, plot_name: str,
         Path to directory in which plots will be saved.
     plot_name : str
         Name of plot.
+    colors: dict
+        Dictionary of colors used for plots.
     quadrature: Quadrature object
         Quadrature used for evaluation.
     init_cond : InitialCondition object
@@ -344,10 +346,12 @@ def plot_approximation_results(data_file: str, directory: str, plot_name: str,
                     for key in approx_stats.keys()}
     approx_stats['basis'] = OrthonormalLegendre(**approx_stats['basis'])
     approx_stats['mesh'] = Mesh(**approx_stats['mesh'])
+    print([key for key in approx_stats.keys()])
 
     # Plot exact/approximate results, errors, shock tubes,
     # and any detector-dependant plots
-    plot_results(quadrature=quadrature, init_cond=init_cond, **approx_stats)
+    plot_results(quadrature=quadrature, init_cond=init_cond,
+                 colors=colors, **approx_stats)
 
     # Set paths for plot files if not existing already
     if not os.path.exists(directory):

workflows/approximation.smk

@@ -85,9 +85,10 @@ rule plot_approximation_results:
             quadrature = getattr(Quadrature, detector_dict.pop(
                 'quadrature', 'Gauss'))(detector_dict.pop(
                 'quadrature_config', {}))
+            colors = detector_dict.pop('colors', None)
 
             plot_approximation_results(directory=params.plot_dir,
-                plot_name=wildcards.scheme,
+                plot_name=wildcards.scheme, colors=colors,
                 data_file=params.plot_dir+'/'+wildcards.scheme,
                 quadrature=quadrature, init_cond=init_cond)