Coverage for pySDC/helpers/visualization_tools.py: 100%

1import matplotlib 

2 

3matplotlib.use('Agg') 

4 

5from pySDC.helpers.stats_helper import filter_stats 

6 

7import numpy as np 

8 

9from matplotlib import rc 

10import matplotlib.pyplot as plt 

11 

12 

13# noinspection PyShadowingBuiltins 

14def show_residual_across_simulation(stats, fname='residuals.png'): 

15 """ 

16 Helper routine to visualize the residuals across the simulation (one block of PFASST) 

17 

18 Args: 

19 stats (dict): statistics object from a PFASST run 

20 fname (str): filename 

21 """ 

22 

23 # get residuals of the run 

24 extract_stats = filter_stats(stats, type='residual_post_iteration') 

25 

26 # find boundaries for x-,y- and c-axis as well as arrays 

27 maxprocs = 0 

28 maxiter = 0 

29 minres = 0 

30 maxres = -99 

31 for k, v in extract_stats.items(): 

32 maxprocs = max(maxprocs, k.process) 

33 maxiter = max(maxiter, k.iter) 

34 minres = min(minres, np.log10(v)) 

35 maxres = max(maxres, np.log10(v)) 

36 

37 # grep residuals and put into array 

38 residual = np.zeros((maxiter, maxprocs + 1)) 

39 residual[:] = -99 

40 for k, v in extract_stats.items(): 

41 step = k.process 

42 iter = k.iter 

43 if iter != -1: 

44 residual[iter - 1, step] = np.log10(v) 

45 

46 # Set up plotting stuff and fonts 

47 rc('font', **{"sans-serif": ["Arial"], "size": 30}) 

48 rc('legend', fontsize='small') 

49 rc('xtick', labelsize='small') 

50 rc('ytick', labelsize='small') 

51 

52 # create plot and save 

53 fig, ax = plt.subplots(figsize=(15, 10)) 

54 

55 cmap = plt.get_cmap('Reds') 

56 plt.pcolor(residual.T, cmap=cmap, vmin=minres, vmax=maxres) 

57 

58 cax = plt.colorbar() 

59 cax.set_label('log10(residual)') 

60 

61 ax.set_xlabel('iteration') 

62 ax.set_ylabel('process') 

63 

64 ax.set_xticks(np.arange(maxiter) + 0.5, minor=False) 

65 ax.set_yticks(np.arange(maxprocs + 1) + 0.5, minor=False) 

66 ax.set_xticklabels(np.arange(maxiter) + 1, minor=False) 

67 ax.set_yticklabels(np.arange(maxprocs + 1), minor=False) 

68 

69 plt.savefig(fname, transparent=True, bbox_inches='tight')