# Coverage for pySDC/tutorial/step_3/A_getting_statistics.py: 100%

## 54 statements

, created at 2024-09-20 16:55 +0000

1from pathlib import Path

3from pySDC.helpers.stats_helper import get_list_of_types, get_sorted

5from pySDC.implementations.controller_classes.controller_nonMPI import controller_nonMPI

6from pySDC.implementations.problem_classes.HeatEquation_ND_FD import heatNd_forced

7from pySDC.implementations.sweeper_classes.imex_1st_order import imex_1st_order

10def main():

11 """

12 A simple test program to describe how to get statistics of a run

13 """

15 # run simulation

16 stats = run_simulation()

18 Path("data").mkdir(parents=True, exist_ok=True)

19 f = open('data/step_3_A_out.txt', 'w')

20 out = 'List of registered statistic types: %s' % get_list_of_types(stats)

21 f.write(out + '\n')

22 print(out)

24 # filter statistics by first time interval and type (residual)

25 residuals = get_sorted(stats, time=0.1, type='residual_post_iteration', sortby='iter')

27 for item in residuals:

28 out = 'Residual in iteration %2i: %8.4e' % item

29 f.write(out + '\n')

30 print(out)

32 # get and convert filtered statistics to list of iterations count, sorted by time

33 # the get_sorted function is just a shortcut for sort_stats(filter_stats()) with all the same arguments

34 iter_counts = get_sorted(stats, type='niter', sortby='time')

36 for item in iter_counts:

37 out = 'Number of iterations at time %4.2f: %2i' % item

38 f.write(out + '\n')

39 print(out)

41 f.close()

43 assert all(item[1] == 12 for item in iter_counts), (

44 'ERROR: number of iterations are not as expected, got %s' % iter_counts

45 )

48def run_simulation():

49 """

50 A simple test program to run IMEX SDC for a single time step

51 """

52 # initialize level parameters

53 level_params = {}

54 level_params['restol'] = 1e-10

55 level_params['dt'] = 0.1

57 # initialize sweeper parameters

58 sweeper_params = {}

60 sweeper_params['num_nodes'] = 3

62 # initialize problem parameters

63 problem_params = {}

64 problem_params['nu'] = 0.1 # diffusion coefficient

65 problem_params['freq'] = 4 # frequency for the test value

66 problem_params['nvars'] = 1023 # number of degrees of freedom

67 problem_params['bc'] = 'dirichlet-zero' # boundary conditions

69 # initialize step parameters

70 step_params = {}

71 step_params['maxiter'] = 20

73 # initialize controller parameters (<-- this is new!)

74 controller_params = {}

75 controller_params['logger_level'] = 30 # reduce verbosity of each run

77 # Fill description dictionary for easy hierarchy creation

78 description = {}

79 description['problem_class'] = heatNd_forced

80 description['problem_params'] = problem_params

81 description['sweeper_class'] = imex_1st_order

82 description['sweeper_params'] = sweeper_params

83 description['level_params'] = level_params

84 description['step_params'] = step_params

86 # instantiate the controller (no controller parameters used here)

87 controller = controller_nonMPI(num_procs=1, controller_params=controller_params, description=description)

89 # set time parameters

90 t0 = 0.1

91 Tend = 0.9

93 # get initial values on finest level

94 P = controller.MS[0].levels[0].prob

95 uinit = P.u_exact(t0)

97 # call main function to get things done...

98 uend, stats = controller.run(u0=uinit, t0=t0, Tend=Tend)

100 return stats

103if __name__ == "__main__":

104 main()