Added a test for fault insertion in Schroedinger problem and fixed

textwidth in plotting script

Author: Thomas Baumann

pySDC/projects/Resilience/fault_injection.py

@@ -127,6 +127,39 @@ def __init__(self):
         self.rnd_params = {}
         self.random_generator = np.random.RandomState(2187)  # number of the cell in which Princess Leia is held
 
+    @classmethod
+    def generate_fault_stuff_single_fault(cls, bit=0, iteration=1, problem_pos=None, level_number=0, node=1, time=None):
+        """
+        Generate a fault stuff object which will insert a single fault at the supplied parameters. Because there will
+        be some parameter set for everything, there is no randomization anymore.
+
+        Args:
+            bit (int): Which bit to flip
+            iteration (int): After which iteration to flip
+            problem_pos: Where in the problem to flip a bit, type depends on the problem
+            level_number (int): In which level you want to flip
+            node (int): In which node to flip
+            time (float): The bitflip will occur in the time step after this time is reached
+
+        Returns:
+            dict: Can be supplied to the run functions in the resilience project to generate the single fault
+        """
+        assert problem_pos is not None, "Please supply a spatial position for the fault as `problem_pos`!"
+        assert time is not None, "Please supply a time for the fault as `time`!"
+        fault_stuff = {
+            'rng': np.random.RandomState(0),
+            'args': {
+                'bit': bit,
+                'iteration': iteration,
+                'level_number': level_number,
+                'problem_pos': problem_pos,
+                'node': node,
+                'time': time,
+            },
+        }
+        fault_stuff['rnd_args'] = fault_stuff['args']
+        return fault_stuff
+
     def add_fault(self, args, rnd_args):
         if type(self.random_generator) == int:
             self.add_fault_from_combination(args, rnd_args)
@@ -320,7 +353,6 @@ def pre_step(self, step, level_number):
         Returns:
             None
         '''
-
         super(FaultInjector, self).pre_step(step, level_number)
 
         self.timestep_idx += 1

pySDC/projects/Resilience/notes/Lorenz/compare_strategies.png

@@ -17,6 +17,7 @@
 
 
 cm = 1 / 2.5
+TEXTWIDTH = 11.9446244611 * cm
 
 
 def get_stats(problem, path='data/stats'):
@@ -50,7 +51,7 @@ def get_stats(problem, path='data/stats'):
 
 def my_setup_mpl(**kwargs):
     setup_mpl(reset=True, font_size=8)
-    mpl.rcParams.update({'lines.markersize': 8})
+    mpl.rcParams.update({'lines.markersize': 6})
 
 
 def savefig(fig, name, format='pdf', base_path='data/paper'):  # pragma: no cover
@@ -98,7 +99,7 @@ def compare_strategies(stats_analyser, **kwargs):  # pragma: no cover
         None
     """
     my_setup_mpl()
-    fig, ax = plt.subplots(figsize=(16 * cm, 7 * cm))
+    fig, ax = plt.subplots(figsize=(TEXTWIDTH, 5 * cm))
     stats_analyser.compare_strategies(ax=ax)
     savefig(fig, 'compare_strategies', **kwargs)
 
@@ -114,7 +115,7 @@ def plot_recovery_rate(stats_analyser, **kwargs):  # pragma: no cover
         None
     """
     my_setup_mpl()
-    fig, axs = plt.subplots(1, 2, figsize=(16 * cm, 7 * cm), sharex=True, sharey=True)
+    fig, axs = plt.subplots(1, 2, figsize=(TEXTWIDTH, 5 * cm), sharex=True, sharey=True)
     stats_analyser.plot_things_per_things(
         'recovered', 'bit', False, op=stats_analyser.rec_rate, args={'ylabel': 'recovery rate'}, ax=axs[0]
     )
@@ -167,7 +168,7 @@ def compare_recovery_rate_problems():  # pragma no cover
     titles = ['Van der Pol', 'Lorenz attractor', r'Schr\"odinger']
 
     my_setup_mpl()
-    fig, axs = plt.subplots(1, 3, figsize=(16 * cm, 5.5 * cm), sharex=False, sharey=True)
+    fig, axs = plt.subplots(1, 3, figsize=(TEXTWIDTH, 4 * cm), sharex=False, sharey=True)
 
     plot_recovery_rate_recoverable_only(vdp_stats, fig, axs[0], ylabel='recovery rate')
     plot_recovery_rate_recoverable_only(lorenz_stats, fig, axs[1], ylabel='', xlabel='')
@@ -206,13 +207,14 @@ def plot_efficiency_polar(problem, path='data/stats'):  # pragma no cover
     mask = stats_analyser.get_mask()  # get empty mask, potentially put in some other mask later
 
     my_setup_mpl()
-    fig, ax = plt.subplots(subplot_kw={'projection': 'polar'}, figsize=(8 * cm, 8 * cm))
+    fig, ax = plt.subplots(subplot_kw={'projection': 'polar'}, figsize=(7 * cm, 7 * cm))
 
     res = {}
     for strategy in stats_analyser.strategies:
         dat = stats_analyser.load(strategy=strategy, faults=True)
         dat_no_faults = stats_analyser.load(strategy=strategy, faults=False)
 
+        mask = stats_analyser.get_fixable_faults_only(strategy=strategy)
         fail_rate = 1.0 - stats_analyser.rec_rate(dat, dat_no_faults, 'recovered', mask)
         iterations_no_faults = np.mean(dat_no_faults['total_iteration'])
 
@@ -259,7 +261,7 @@ def plot_adaptivity_stuff():  # pragma no cover
     stats_analyser = get_stats(run_vdp, 'data/stats')
 
     my_setup_mpl()
-    fig, axs = plt.subplots(3, 1, figsize=(10 * cm, 11 * cm), sharex=True, sharey=False)
+    fig, axs = plt.subplots(3, 1, figsize=(TEXTWIDTH, TEXTWIDTH), sharex=True, sharey=False)
 
     def plot_error(stats, ax, iter_ax, strategy, **kwargs):
         """
@@ -328,9 +330,9 @@ def plot_fault_vdp(bit=0):  # pragma no cover
     )
 
     my_setup_mpl()
-    fig, ax = plt.subplots(1, 1, figsize=(10 * cm, 7 * cm))
+    fig, ax = plt.subplots(1, 1, figsize=(TEXTWIDTH * 3.0 / 4.0, 5 * cm))
     colors = ['blue', 'red', 'magenta']
-    ls = ['--', '--', '-', '-']
+    ls = ['--', '-']
     markers = ['*', '.', 'y']
     do_faults = [False, True]
     superscripts = ['*', '']

pySDC/projects/Resilience/notes/Lorenz/recovery_rate_compared.png

@@ -2,7 +2,7 @@
 
 
 @pytest.mark.mpi4py
-def test_schroedinger():
+def test_schroedinger_solution():
     from mpi4py import MPI
     import numpy as np
     from pySDC.projects.Resilience.Schroedinger import run_Schroedinger
@@ -13,3 +13,22 @@ def test_schroedinger():
     assert (
         k_mean < 17
     ), f"Got too many iterations in Schroedinger test! Expected less then 17 on average, but got {k_mean:.2f}!"
+
+
+@pytest.mark.mpi4py
+def test_schroedinger_fault_insertion():
+    from mpi4py import MPI
+    import numpy as np
+    from pySDC.projects.Resilience.Schroedinger import run_Schroedinger
+    from pySDC.projects.Resilience.fault_injection import FaultInjector
+    from pySDC.helpers.stats_helper import get_sorted
+
+    fault_stuff = FaultInjector.generate_fault_stuff_single_fault(
+        bit=0, iteration=5, problem_pos=[20, 30], level_number=0, node=3, time=0.1
+    )
+
+    stats, _, _ = run_Schroedinger(space_comm=MPI.COMM_WORLD, fault_stuff=fault_stuff)
+    k_mean = np.mean([me[1] for me in get_sorted(stats, type='k')])
+    assert (
+        k_mean > 17
+    ), f"Got too few iterations in Schroedinger test! Expected more then 17 on average because we need to fix the fault, but got {k_mean:.2f}!"