def testCalculationNonOrthogonal(self): """ Test a calculation with the on-the-fly MSD analysis. """ # Setup a system, a periodic 10 atoms long 1D chain. unit_cell = KMCUnitCell(cell_vectors=numpy.array([[2.0,1.0,0.0], [0.0,1.0,0.0], [0.0,2.0,1.0]]), basis_points=[[0.0,0.0,0.0]]) # And a lattice. lattice = KMCLattice(unit_cell=unit_cell, repetitions=(10,10,10), periodic=(True,True,True)) # Setup an initial configuration with one B in a sea of A:s. types = ["A"]*10*10*10 types[5] = "B" config = KMCConfiguration(lattice=lattice, types=types, possible_types=["A","B"]) # Setup a diffusion process to the left. coordinates_p0 = [[0.0, 0.0, 0.0],[-1.0, 0.0, 0.0]] p0 = KMCProcess(coordinates=coordinates_p0, elements_before=["B","A"], elements_after=["A","B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p1 = [[0.0, 0.0, 0.0],[1.0, 0.0, 0.0]] p1 = KMCProcess(coordinates=coordinates_p1, elements_before=["B","A"], elements_after=["A","B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p2 = [[0.0, 0.0, 0.0],[0.0,-1.0, 0.0]] p2 = KMCProcess(coordinates=coordinates_p2, elements_before=["B","A"], elements_after=["A","B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p3 = [[0.0, 0.0, 0.0],[0.0, 1.0, 0.0]] p3 = KMCProcess(coordinates=coordinates_p3, elements_before=["B","A"], elements_after=["A","B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p4 = [[0.0, 0.0, 0.0],[0.0, 0.0,-1.0]] p4 = KMCProcess(coordinates=coordinates_p4, elements_before=["B","A"], elements_after=["A","B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p5 = [[0.0, 0.0, 0.0],[0.0, 0.0, 1.0]] p5 = KMCProcess(coordinates=coordinates_p5, elements_before=["B","A"], elements_after=["A","B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) interactions = KMCInteractions(processes=[p0, p1, p2, p3, p4, p5], implicit_wildcards=True) model = KMCLatticeModel(configuration=config, interactions=interactions) # Setup the analysis. msd = OnTheFlyMSD(history_steps=400, n_bins=10, t_max=25.0, track_type="B") # Setup the control parameters. control_parameters = KMCControlParameters(number_of_steps=4000, dump_interval=100, analysis_interval=1, seed=2013) # Run the model. model.run(control_parameters=control_parameters, analysis=[msd]) # Get the results out. results = msd.results() time_steps = msd.timeSteps() std_dev = msd.stdDev() bin_counters = msd.binCounters() # Compare against references. ref_results = numpy.array([[ 11.10849324 , 32.89332622 , 56.86314552 , 84.47799379 , 110.30394149, 135.26081658, 162.25612518, 189.40268295, 219.32538873, 252.00244119], [ 17.33153679 , 50.69982999 , 82.74958435 , 111.33382274 , 136.44824258, 164.84499628, 193.94367236, 234.25340515, 272.64453361, 302.94924061], [ 2.98786918 , 8.65022668 , 14.01808716 , 18.62678885 , 22.65708384, 26.03107861, 30.03937616, 35.1483 , 40.68319007, 47.21074474], [ 28.44003004 , 83.59315621 , 139.61272987 , 195.81181652 , 246.75218407, 300.10581285, 356.19979754, 423.65608811, 491.96992234, 554.95168181], [ 14.09636242 , 41.5435529 , 70.88123268 , 103.10478264 , 132.96102533, 161.29189519, 192.29550134, 224.55098295, 260.00857879, 299.21318593], [ 20.31940597 , 59.35005667 , 96.76767151 , 129.96061158 , 159.10532643, 190.87607489, 223.98304852, 269.40170515, 313.32772368, 350.15998535], [ 31.42789922 , 92.24338289 , 153.63081703 , 214.43860537 , 269.40926791, 326.13689146, 386.2391737 , 458.8043881 , 532.65311241, 602.16242655]]) diff = numpy.linalg.norm(ref_results - results) self.assertAlmostEqual(diff, 0.0, 6) ref_time_steps = numpy.array([ 1.25, 3.75, 6.25, 8.75, 11.25, 13.75, 16.25, 18.75, 21.25, 23.75]) diff = numpy.linalg.norm(ref_time_steps - time_steps) self.assertAlmostEqual(diff, 0.0, 8) ref_std_dev = numpy.array([[ 0.59348826 , 2.92235801 , 6.47651272 , 11.36067446 , 16.79740936, 22.78018427, 29.72954492, 37.27728411, 45.97782684, 55.88661276], [ 0.92596389 , 4.50435001 , 9.42488725 , 14.97226982 , 20.7787406, 27.76265504, 35.53552825, 46.10457783, 57.15527613, 67.18509081], [ 0.15963149 , 0.76851636 , 1.59661093 , 2.50494685 , 3.45028752, 4.38406911 , 5.5039955 , 6.91771175 , 8.52853689 , 10.46993274], [ 1.07441492 , 5.2514756 , 11.24398775 , 18.62020347 , 26.57035045, 35.73918442, 46.14937581, 58.95988 , 72.92611647, 87.02483617], [ 0.53253608 , 2.60984229 , 5.70856048 , 9.80447485 , 14.31728377, 19.20802777, 24.91387536, 31.25058126, 38.54181941, 46.9211633 ], [ 0.76763185 , 3.72847956 , 7.7933761 , 12.35825842 , 17.13251009, 22.73116664, 29.01932554, 37.49242051, 46.4454696 , 54.91039375], [ 0.96941939 , 4.731515 , 10.1024813 , 16.6495642 , 23.68662473, 31.71206536, 40.85854085, 52.13448317, 64.46787783, 77.10029967]]) diff = numpy.linalg.norm(ref_std_dev - std_dev) self.assertAlmostEqual(diff, 0.0, 6) ref_bin_counters = (59930, 59996, 59545, 59256, 59064, 59076, 58284, 58294, 57817, 57349) self.assertEqual(bin_counters, ref_bin_counters)
def testCalculation(self): """ Test a calculation with the on-the-fly MSD analysis. """ # Setup a system, a periodic 10 atoms long 1D chain. unit_cell = KMCUnitCell(cell_vectors=numpy.array([[1.0,0.0,0.0], [0.0,1.0,0.0], [0.0,0.0,1.0]]), basis_points=[[0.0,0.0,0.0]]) # And a lattice. lattice = KMCLattice(unit_cell=unit_cell, repetitions=(10,10,10), periodic=(True,True,True)) # Setup an initial configuration with one B in a sea of A:s. types = ["A"]*10*10*10 types[5] = "B" config = KMCConfiguration(lattice=lattice, types=types, possible_types=["A","B"]) # Setup a diffusion process to the left. coordinates_p0 = [[0.0, 0.0, 0.0],[-1.0, 0.0, 0.0]] p0 = KMCProcess(coordinates=coordinates_p0, elements_before=["B","A"], elements_after=["A","B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p1 = [[0.0, 0.0, 0.0],[1.0, 0.0, 0.0]] p1 = KMCProcess(coordinates=coordinates_p1, elements_before=["B","A"], elements_after=["A","B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p2 = [[0.0, 0.0, 0.0],[0.0,-1.0, 0.0]] p2 = KMCProcess(coordinates=coordinates_p2, elements_before=["B","A"], elements_after=["A","B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p3 = [[0.0, 0.0, 0.0],[0.0, 1.0, 0.0]] p3 = KMCProcess(coordinates=coordinates_p3, elements_before=["B","A"], elements_after=["A","B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p4 = [[0.0, 0.0, 0.0],[0.0, 0.0,-1.0]] p4 = KMCProcess(coordinates=coordinates_p4, elements_before=["B","A"], elements_after=["A","B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p5 = [[0.0, 0.0, 0.0],[0.0, 0.0, 1.0]] p5 = KMCProcess(coordinates=coordinates_p5, elements_before=["B","A"], elements_after=["A","B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) interactions = KMCInteractions(processes=[p0, p1, p2, p3, p4, p5], implicit_wildcards=True) model = KMCLatticeModel(configuration=config, interactions=interactions) # Setup the analysis. msd = OnTheFlyMSD(history_steps=400, n_bins=10, t_max=25.0, track_type="B") # Setup the control parameters. control_parameters = KMCControlParameters(number_of_steps=4000, dump_interval=100, analysis_interval=1, seed=2013) # Run the model. model.run(control_parameters=control_parameters, analysis=[msd]) # Get the results out. results = msd.results() time_steps = msd.timeSteps() std_dev = msd.stdDev() bin_counters = msd.binCounters() # Compare against references. ref_results = numpy.array([[ 2.77712331 , 8.22333156 , 14.21578638 , 21.11949845 , 27.57598537, 33.81520414, 40.5640313 , 47.35067074, 54.83134718, 63.0006103 ], [ 2.80810946 , 8.48503234 , 13.7997313 , 17.62812205 , 22.37202018, 29.12157221, 35.40750463, 41.44944591, 48.94392653, 56.67111894], [ 2.98786918 , 8.65022668 , 14.01808716 , 18.62678885 , 22.65708384, 26.03107861, 30.03937616, 35.1483 , 40.68319007, 47.21074474], [ 5.58523277 , 16.70836389 , 28.01551768 , 38.74762049 , 49.94800555, 62.93677636, 75.97153593, 88.80011665, 103.77527371, 119.67172924], [ 5.76499249 , 16.87355824 , 28.23387354 , 39.7462873 , 50.23306921, 59.84628275, 70.60340745, 82.49897073, 95.51453725, 110.21135504], [ 5.79597864 , 17.13525902 , 27.81781846 , 36.2549109 , 45.02910402, 55.15265082, 65.44688079, 76.59774591, 89.62711659, 103.88186368], [ 8.57310195 , 25.35859057 , 42.03360484 , 57.37440934 , 72.60508939, 88.96785497, 106.01091209, 123.94841665, 144.45846377, 166.88247398]]) diff = numpy.linalg.norm(ref_results - results) self.assertAlmostEqual(diff, 0.0, 6) ref_time_steps = numpy.array([ 1.25, 3.75, 6.25, 8.75, 11.25, 13.75, 16.25, 18.75, 21.25, 23.75]) diff = numpy.linalg.norm(ref_time_steps - time_steps) self.assertAlmostEqual(diff, 0.0, 8) ref_std_dev = numpy.array( [[ 0.14837207, 0.7305895 , 1.61912818, 2.84016862, 4.19935234, 5.69504607, 7.43238623, 9.31932103, 11.49445671, 13.97165319], [ 0.15002755, 0.75383991, 1.57174096, 2.37064526, 3.40687718, 4.90455993, 6.48757634, 8.15787162, 10.26025939, 12.5679611 ], [ 0.15963149, 0.76851636, 1.59661093, 2.50494685, 3.45028752, 4.38406911, 5.5039955 , 6.91771175, 8.52853689, 10.46993274], [ 0.21100039, 1.04965011, 2.25628521, 3.68460183, 5.37841647, 7.49505328, 9.84289993, 12.35824143, 15.38290727, 18.76634124], [ 0.2177914 , 1.06002792, 2.27387093, 3.77956739, 5.40911222, 7.12701069, 9.14740325, 11.48131598, 14.15839455, 17.28281115], [ 0.218962 , 1.07646844, 2.24036311, 3.44756425, 4.84874766, 6.56805258, 8.47932177, 10.66004723, 13.28568526, 16.29025096], [ 0.26444438, 1.30073885, 2.76405291, 4.45469653, 6.38348309, 8.65082886, 11.21442742, 14.08440462, 17.48404426, 21.36747194]]) diff = numpy.linalg.norm(ref_std_dev - std_dev) self.assertAlmostEqual(diff, 0.0, 6) ref_bin_counters = (59930, 59996, 59545, 59256, 59064, 59076, 58284, 58294, 57817, 57349) self.assertEqual(bin_counters, ref_bin_counters)
def testBackend(self): """ Test that the backend object is correctly constructed. """ # Setup a unitcell. unit_cell = KMCUnitCell(cell_vectors=numpy.array([[2.8,0.0,0.0], [0.0,3.2,0.0], [0.0,0.5,3.0]]), basis_points=[[0.0,0.0,0.0], [0.5,0.5,0.5], [0.25,0.25,0.75]]) # Setup the lattice. lattice = KMCLattice(unit_cell=unit_cell, repetitions=(4,4,1), periodic=(True,True,False)) types = ['A','A','A','A','B','B', 'A','A','A','B','B','B', 'B','B','A','A','B','A', 'B','B','B','A','B','A', 'B','A','A','A','B','B', 'B','B','B','B','B','B', 'A','A','A','A','B','B', 'B','B','A','B','B','A'] # Setup the configuration. config = KMCConfiguration(lattice=lattice, types=types, possible_types=['A','C','B']) # A first process. coords = [[1.0,2.0,3.4],[1.1,1.2,1.3]] types0 = ["A","B"] types1 = ["B","A"] sites = [0,1,2,3,4] rate_0_1 = 3.5 process_0 = KMCProcess(coords, types0, types1, basis_sites=sites, rate_constant=rate_0_1) # A second process. types0 = ["A","C"] types1 = ["C","A"] rate_0_1 = 1.5 process_1 = KMCProcess(coords, types0, types1, basis_sites=sites, rate_constant=rate_0_1) # Construct the interactions object. processes = [process_0, process_1] interactions = KMCInteractions(processes=processes) # Construct the model. model = KMCLatticeModel(config, interactions) # Get the c++ backend out. cpp_model = model._backend() # Check that this backend object is stored on the class. self.assertTrue(model._KMCLatticeModel__backend == cpp_model)
def testScript(self): """ Test that a script can be created. """ # Setup a unitcell. unit_cell = KMCUnitCell(cell_vectors=numpy.array([[2.8,0.0,0.0], [0.0,3.2,0.0], [0.0,0.5,3.0]]), basis_points=[[0.0,0.0,0.0], [0.5,0.5,0.5], [0.25,0.25,0.75]]) # Setup the lattice. lattice = KMCLattice(unit_cell=unit_cell, repetitions=(4,4,1), periodic=(True,True,False)) types = ['A','A','A','A','B','B', 'A','A','A','B','B','B', 'B','B','A','A','B','A', 'B','B','B','A','B','A', 'B','A','A','A','B','B', 'B','B','B','B','B','B', 'A','A','A','A','B','B', 'B','B','A','B','B','A'] # Setup the configuration. config = KMCConfiguration(lattice=lattice, types=types, possible_types=['A','C','B']) # A first process. coords = [[1.0,2.0,3.4],[1.1,1.2,1.3]] types0 = ["A","B"] types1 = ["B","A"] rate_0_1 = 3.5 process_0 = KMCProcess(coords, types0, types1, basis_sites=[0], rate_constant=rate_0_1) # A second process. types0 = ["A","C"] types1 = ["C","A"] rate_0_1 = 1.5 process_1 = KMCProcess(coords, types0, types1, basis_sites=[0], rate_constant=rate_0_1) # Construct the interactions object. processes = [process_0, process_1] interactions = KMCInteractions(processes) # Construct the model. model = KMCLatticeModel(config, interactions) # Get the script. script = model._script() ref_script = """ # ----------------------------------------------------------------------------- # Unit cell cell_vectors = [[ 2.800000e+00, 0.000000e+00, 0.000000e+00], [ 0.000000e+00, 3.200000e+00, 0.000000e+00], [ 0.000000e+00, 5.000000e-01, 3.000000e+00]] basis_points = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00], [ 5.000000e-01, 5.000000e-01, 5.000000e-01], [ 2.500000e-01, 2.500000e-01, 7.500000e-01]] unit_cell = KMCUnitCell( cell_vectors=cell_vectors, basis_points=basis_points) # ----------------------------------------------------------------------------- # Lattice lattice = KMCLattice( unit_cell=unit_cell, repetitions=(4,4,1), periodic=(True, True, False)) # ----------------------------------------------------------------------------- # Configuration types = ['A','A','A','A','B','B','A','A','A','B','B','B','B', 'B','A','A','B','A','B','B','B','A','B','A','B','A', 'A','A','B','B','B','B','B','B','B','B','A','A','A', 'A','B','B','B','B','A','B','B','A'] possible_types = ['A','C','B'] configuration = KMCConfiguration( lattice=lattice, types=types, possible_types=possible_types) # ----------------------------------------------------------------------------- # Interactions coordinates = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00], [ 1.000000e-01, -8.000000e-01, -2.100000e+00]] elements_before = ['A','B'] elements_after = ['B','A'] move_vectors = [( 0,[ 1.000000e-01, -8.000000e-01, -2.100000e+00]), ( 1,[ -1.000000e-01, 8.000000e-01, 2.100000e+00])] basis_sites = [0] rate_constant = 3.500000e+00 process_0 = KMCProcess( coordinates=coordinates, elements_before=elements_before, elements_after=elements_after, move_vectors=move_vectors, basis_sites=basis_sites, rate_constant=rate_constant) coordinates = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00], [ 1.000000e-01, -8.000000e-01, -2.100000e+00]] elements_before = ['A','C'] elements_after = ['C','A'] move_vectors = [( 0,[ 1.000000e-01, -8.000000e-01, -2.100000e+00]), ( 1,[ -1.000000e-01, 8.000000e-01, 2.100000e+00])] basis_sites = [0] rate_constant = 1.500000e+00 process_1 = KMCProcess( coordinates=coordinates, elements_before=elements_before, elements_after=elements_after, move_vectors=move_vectors, basis_sites=basis_sites, rate_constant=rate_constant) processes = [process_0, process_1] interactions = KMCInteractions( processes=processes, implicit_wildcards=True) # ----------------------------------------------------------------------------- # Lattice model model = KMCLatticeModel( configuration=configuration, interactions=interactions) """ self.assertEqual(script, ref_script) # Get the script again, with a different variable name. script = model._script(variable_name="my_model") ref_script = """ # ----------------------------------------------------------------------------- # Unit cell cell_vectors = [[ 2.800000e+00, 0.000000e+00, 0.000000e+00], [ 0.000000e+00, 3.200000e+00, 0.000000e+00], [ 0.000000e+00, 5.000000e-01, 3.000000e+00]] basis_points = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00], [ 5.000000e-01, 5.000000e-01, 5.000000e-01], [ 2.500000e-01, 2.500000e-01, 7.500000e-01]] unit_cell = KMCUnitCell( cell_vectors=cell_vectors, basis_points=basis_points) # ----------------------------------------------------------------------------- # Lattice lattice = KMCLattice( unit_cell=unit_cell, repetitions=(4,4,1), periodic=(True, True, False)) # ----------------------------------------------------------------------------- # Configuration types = ['A','A','A','A','B','B','A','A','A','B','B','B','B', 'B','A','A','B','A','B','B','B','A','B','A','B','A', 'A','A','B','B','B','B','B','B','B','B','A','A','A', 'A','B','B','B','B','A','B','B','A'] possible_types = ['A','C','B'] configuration = KMCConfiguration( lattice=lattice, types=types, possible_types=possible_types) # ----------------------------------------------------------------------------- # Interactions coordinates = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00], [ 1.000000e-01, -8.000000e-01, -2.100000e+00]] elements_before = ['A','B'] elements_after = ['B','A'] move_vectors = [( 0,[ 1.000000e-01, -8.000000e-01, -2.100000e+00]), ( 1,[ -1.000000e-01, 8.000000e-01, 2.100000e+00])] basis_sites = [0] rate_constant = 3.500000e+00 process_0 = KMCProcess( coordinates=coordinates, elements_before=elements_before, elements_after=elements_after, move_vectors=move_vectors, basis_sites=basis_sites, rate_constant=rate_constant) coordinates = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00], [ 1.000000e-01, -8.000000e-01, -2.100000e+00]] elements_before = ['A','C'] elements_after = ['C','A'] move_vectors = [( 0,[ 1.000000e-01, -8.000000e-01, -2.100000e+00]), ( 1,[ -1.000000e-01, 8.000000e-01, 2.100000e+00])] basis_sites = [0] rate_constant = 1.500000e+00 process_1 = KMCProcess( coordinates=coordinates, elements_before=elements_before, elements_after=elements_after, move_vectors=move_vectors, basis_sites=basis_sites, rate_constant=rate_constant) processes = [process_0, process_1] interactions = KMCInteractions( processes=processes, implicit_wildcards=True) # ----------------------------------------------------------------------------- # Lattice model my_model = KMCLatticeModel( configuration=configuration, interactions=interactions) """ # Check. self.assertEqual(script, ref_script)
def testRunRngType(self): """ Test that it is possible to run with each of the supported PRNG:s. """ # Cell. cell_vectors = [[ 1.000000e+00, 0.000000e+00, 0.000000e+00], [ 0.000000e+00, 1.000000e+00, 0.000000e+00], [ 0.000000e+00, 0.000000e+00, 1.000000e+00]] basis_points = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] unit_cell = KMCUnitCell( cell_vectors=cell_vectors, basis_points=basis_points) # Lattice. lattice = KMCLattice( unit_cell=unit_cell, repetitions=(4,4,1), periodic=(True, True, False)) # Configuration. types = ['B']*16 possible_types = ['A','B'] configuration = KMCConfiguration( lattice=lattice, types=types, possible_types=possible_types) # Interactions. coordinates = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] process_0 = KMCProcess(coordinates, ['A'], ['B'], basis_sites=[0], rate_constant=4.0) process_1 = KMCProcess(coordinates, ['B'], ['A'], basis_sites=[0], rate_constant=1.0) processes = [process_0, process_1] interactions = KMCInteractions(processes) # Setup the models. ab_flip_model_MT = KMCLatticeModel(configuration, interactions) ab_flip_model_RANLUX24 = KMCLatticeModel(configuration, interactions) ab_flip_model_RANLUX48 = KMCLatticeModel(configuration, interactions) ab_flip_model_MINSTD = KMCLatticeModel(configuration, interactions) ab_flip_model_DEVICE = KMCLatticeModel(configuration, interactions) # Run the model for 10000 steps with MT. ab_flip_model_MT.run(KMCControlParameters(number_of_steps=10000, dump_interval=5000, seed=2013, rng_type="MT")) # Get the simulation time out. t_MT = ab_flip_model_MT._KMCLatticeModel__cpp_timer.simulationTime() # Run the model for 10000 steps with RANLUX24. ab_flip_model_RANLUX24.run(KMCControlParameters(number_of_steps=10000, dump_interval=5000, seed=2013, rng_type="RANLUX24")) # Get the simulation time out. t_RANLUX24 = ab_flip_model_RANLUX24._KMCLatticeModel__cpp_timer.simulationTime() # Run the model for 10000 steps with RANLUX48. ab_flip_model_RANLUX48.run(KMCControlParameters(number_of_steps=10000, dump_interval=5000, seed=2013, rng_type="RANLUX48")) # Get the simulation time out. t_RANLUX48 = ab_flip_model_RANLUX48._KMCLatticeModel__cpp_timer.simulationTime() # Run the model for 10000 steps with MINSTD. ab_flip_model_MINSTD.run(KMCControlParameters(number_of_steps=10000, dump_interval=5000, seed=2013, rng_type="MINSTD")) # Get the simulation time out. t_MINSTD = ab_flip_model_MINSTD._KMCLatticeModel__cpp_timer.simulationTime() # These values should be simillar but not equal. Check against hardcoded values. self.assertAlmostEqual(t_MT, 394.569398158, 5) self.assertAlmostEqual(t_RANLUX24, 389.712162523, 5) self.assertAlmostEqual(t_RANLUX48, 390.544423280, 5) self.assertAlmostEqual(t_MINSTD, 384.712302086, 5)
def testRunRngTypeDevice(self): """ Test to use the PRNG DEVICE. """ # Cell. cell_vectors = [[ 1.000000e+00, 0.000000e+00, 0.000000e+00], [ 0.000000e+00, 1.000000e+00, 0.000000e+00], [ 0.000000e+00, 0.000000e+00, 1.000000e+00]] basis_points = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] unit_cell = KMCUnitCell( cell_vectors=cell_vectors, basis_points=basis_points) # Lattice. lattice = KMCLattice( unit_cell=unit_cell, repetitions=(4,4,1), periodic=(True, True, False)) # Configuration. types = ['B']*16 possible_types = ['A','B'] configuration = KMCConfiguration( lattice=lattice, types=types, possible_types=possible_types) # Interactions. coordinates = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] process_0 = KMCProcess(coordinates, ['A'], ['B'], basis_sites=[0], rate_constant=4.0) process_1 = KMCProcess(coordinates, ['B'], ['A'], basis_sites=[0], rate_constant=1.0) processes = [process_0, process_1] interactions = KMCInteractions(processes) # Setup the model. ab_flip_model_DEVICE = KMCLatticeModel(configuration, interactions) support_device = False if (not support_device): # If DEVICE is not supported on your system this is the test you should run. self.assertRaises( Error, lambda: ab_flip_model_DEVICE.run(KMCControlParameters(number_of_steps=10000, dump_interval=5000, seed=2013, rng_type="DEVICE"))) else: # If DEVICE is supported the aboove test will fail, and you should run this tests instead. # Run the model for 10000 steps with DEVICE. ab_flip_model_DEVICE.run(KMCControlParameters(number_of_steps=10000, dump_interval=5000, seed=2013, rng_type="DEVICE")) # Get the simulation time out. t_DEVICE = ab_flip_model_DEVICE._KMCLatticeModel__cpp_timer.simulationTime() self.assertTrue(t_DEVICE < 410.0 and t_DEVICE > 370.0)
def testConstruction(self): """ Test the construction of the lattice model """ # Setup a unitcell. unit_cell = KMCUnitCell(cell_vectors=numpy.array([[2.8,0.0,0.0], [0.0,3.2,0.0], [0.0,0.5,3.0]]), basis_points=[[0.0,0.0,0.0], [0.5,0.5,0.5], [0.25,0.25,0.75]]) # Setup the lattice. lattice = KMCLattice(unit_cell=unit_cell, repetitions=(4,4,1), periodic=(True,True,False)) types = ['A','A','A','A','B','B', 'A','A','A','B','B','B', 'B','B','A','A','B','A', 'B','B','B','A','B','A', 'B','A','A','A','B','B', 'B','B','B','B','B','B', 'A','A','A','A','B','B', 'B','B','A','B','B','A'] # Setup the configuration. config = KMCConfiguration(lattice=lattice, types=types, possible_types=['A','C','B']) # A first process. coords = [[1.0,2.0,3.4],[1.1,1.2,1.3]] types0 = ["A","B"] types1 = ["B","A"] sites = [0,1,2] rate_0_1 = 3.5 process_0 = KMCProcess(coords, types0, types1, basis_sites=sites, rate_constant=rate_0_1) # A second process. coords = [[1.0,2.0,3.4],[1.1,1.2,1.3]] types0 = ["A","C"] types1 = ["C","A"] sites = [0,1,2] rate_0_1 = 1.5 process_1 = KMCProcess(coords, types0, types1, basis_sites=sites, rate_constant=rate_0_1) # Construct the interactions object. processes = [process_0, process_1] interactions = KMCInteractions(processes=processes) # Construct the model. model = KMCLatticeModel(config, interactions) # Check that it has the attribute _backend which is None self.assertTrue(hasattr(model,"_KMCLatticeModel__backend")) self.assertTrue(model._KMCLatticeModel__backend is None) # Check that it has the correct interactions stored. self.assertTrue(model._KMCLatticeModel__interactions == interactions) # Check that it has the correct configuration stored. self.assertTrue(model._KMCLatticeModel__configuration == config)
def testRunTrajectory(self): """ Test the run of an A-B flip model with trajectory output. """ # Cell. cell_vectors = [[ 1.000000e+00, 0.000000e+00, 0.000000e+00], [ 0.000000e+00, 1.000000e+00, 0.000000e+00], [ 0.000000e+00, 0.000000e+00, 1.000000e+00]] basis_points = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] unit_cell = KMCUnitCell( cell_vectors=cell_vectors, basis_points=basis_points) # Lattice. lattice = KMCLattice( unit_cell=unit_cell, repetitions=(4,4,1), periodic=(True, True, False)) # Configuration. types = ['B']*16 possible_types = ['A','B'] configuration = KMCConfiguration( lattice=lattice, types=types, possible_types=possible_types) # Interactions. coordinates = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] process_0 = KMCProcess(coordinates, ['A'], ['B'], basis_sites=[0], rate_constant=4.0) process_1 = KMCProcess(coordinates, ['B'], ['A'], basis_sites=[0], rate_constant=1.0) processes = [process_0, process_1] interactions = KMCInteractions(processes) # Setup the model. ab_flip_model = KMCLatticeModel(configuration, interactions) # Construct the trajectory fileames. name = os.path.abspath(os.path.dirname(__file__)) name = os.path.join(name, "..", "TestUtilities", "Scratch") lattice_trajectory_filename = os.path.join(name, "ab_flip_traj_lattice.py") xyz_trajectory_filename = os.path.join(name, "ab_flip_traj_xyz.xyz") self.__files_to_remove.append(lattice_trajectory_filename) self.__files_to_remove.append(xyz_trajectory_filename) # The control parameters. control_parameters = KMCControlParameters(number_of_steps=1000, dump_interval=500, seed=2013) # Run the model for 1000 steps with a lattice trajectory. ab_flip_model.run(control_parameters, trajectory_filename=lattice_trajectory_filename, trajectory_type='lattice') # Check the file content. ref_lattice = """ sites=[[ 0.000000, 0.000000, 0.000000], [ 0.000000, 1.000000, 0.000000], [ 0.000000, 2.000000, 0.000000], [ 0.000000, 3.000000, 0.000000], [ 1.000000, 0.000000, 0.000000], [ 1.000000, 1.000000, 0.000000], [ 1.000000, 2.000000, 0.000000], [ 1.000000, 3.000000, 0.000000], [ 2.000000, 0.000000, 0.000000], [ 2.000000, 1.000000, 0.000000], [ 2.000000, 2.000000, 0.000000], [ 2.000000, 3.000000, 0.000000], [ 3.000000, 0.000000, 0.000000], [ 3.000000, 1.000000, 0.000000], [ 3.000000, 2.000000, 0.000000], [ 3.000000, 3.000000, 0.000000]] times=[] steps=[] types=[] times.append( 0.0000000000e+00) steps.append(0) types.append(["B","B","B","B","B","B","B","B","B","B","B","B","B","B","B","B"]) times.append( 1.9093684175e+01) steps.append(500) types.append(["B","A","B","B","A","B","B","B","A","B","B","B","B","B","B","A"]) times.append( 4.0622006972e+01) steps.append(1000) types.append(["B","A","A","B","B","B","B","A","B","B","B","A","B","B","B","B"]) """ with open(lattice_trajectory_filename, "r") as t: lattice_data = t.read() # Check with "in" to avoid comparing dates. self.assertTrue(ref_lattice in lattice_data) # Run the model for 1000 steps with an xyz trajectory. ab_flip_model.run(control_parameters, trajectory_filename=xyz_trajectory_filename, trajectory_type='xyz') ref_xyz = """KMCLib XYZ FORMAT VERSION 2013.10.15 CELL VECTORS a: 1.0000000000e+00 0.0000000000e+00 0.0000000000e+00 b: 0.0000000000e+00 1.0000000000e+00 0.0000000000e+00 c: 0.0000000000e+00 0.0000000000e+00 1.0000000000e+00 REPETITIONS 4 1 1 PERIODICITY True True False STEP 0 16 TIME 4.0622006972e+01 B 0.0000000000e+00 0.0000000000e+00 0.0000000000e+00 0 A 0.0000000000e+00 1.0000000000e+00 0.0000000000e+00 1 A 0.0000000000e+00 2.0000000000e+00 0.0000000000e+00 2 B 0.0000000000e+00 3.0000000000e+00 0.0000000000e+00 3 B 1.0000000000e+00 0.0000000000e+00 0.0000000000e+00 4 B 1.0000000000e+00 1.0000000000e+00 0.0000000000e+00 5 B 1.0000000000e+00 2.0000000000e+00 0.0000000000e+00 6 A 1.0000000000e+00 3.0000000000e+00 0.0000000000e+00 7 B 2.0000000000e+00 0.0000000000e+00 0.0000000000e+00 8 B 2.0000000000e+00 1.0000000000e+00 0.0000000000e+00 9 B 2.0000000000e+00 2.0000000000e+00 0.0000000000e+00 10 A 2.0000000000e+00 3.0000000000e+00 0.0000000000e+00 11 B 3.0000000000e+00 0.0000000000e+00 0.0000000000e+00 12 B 3.0000000000e+00 1.0000000000e+00 0.0000000000e+00 13 B 3.0000000000e+00 2.0000000000e+00 0.0000000000e+00 14 B 3.0000000000e+00 3.0000000000e+00 0.0000000000e+00 15 STEP 500 16 TIME 5.9660935122e+01 B 0.0000000000e+00 0.0000000000e+00 0.0000000000e+00 0 A 0.0000000000e+00 1.0000000000e+00 0.0000000000e+00 1 B 0.0000000000e+00 2.0000000000e+00 0.0000000000e+00 2 B 0.0000000000e+00 3.0000000000e+00 0.0000000000e+00 3 B 1.0000000000e+00 0.0000000000e+00 0.0000000000e+00 4 B 1.0000000000e+00 1.0000000000e+00 0.0000000000e+00 5 B 1.0000000000e+00 2.0000000000e+00 0.0000000000e+00 6 A 1.0000000000e+00 3.0000000000e+00 0.0000000000e+00 7 B 2.0000000000e+00 0.0000000000e+00 0.0000000000e+00 8 B 2.0000000000e+00 1.0000000000e+00 0.0000000000e+00 9 B 2.0000000000e+00 2.0000000000e+00 0.0000000000e+00 10 B 2.0000000000e+00 3.0000000000e+00 0.0000000000e+00 11 A 3.0000000000e+00 0.0000000000e+00 0.0000000000e+00 12 A 3.0000000000e+00 1.0000000000e+00 0.0000000000e+00 13 B 3.0000000000e+00 2.0000000000e+00 0.0000000000e+00 14 B 3.0000000000e+00 3.0000000000e+00 0.0000000000e+00 15 STEP 1000 16 TIME 8.1189257919e+01 A 0.0000000000e+00 0.0000000000e+00 0.0000000000e+00 0 B 0.0000000000e+00 1.0000000000e+00 0.0000000000e+00 1 B 0.0000000000e+00 2.0000000000e+00 0.0000000000e+00 2 B 0.0000000000e+00 3.0000000000e+00 0.0000000000e+00 3 B 1.0000000000e+00 0.0000000000e+00 0.0000000000e+00 4 A 1.0000000000e+00 1.0000000000e+00 0.0000000000e+00 5 B 1.0000000000e+00 2.0000000000e+00 0.0000000000e+00 6 B 1.0000000000e+00 3.0000000000e+00 0.0000000000e+00 7 B 2.0000000000e+00 0.0000000000e+00 0.0000000000e+00 8 B 2.0000000000e+00 1.0000000000e+00 0.0000000000e+00 9 A 2.0000000000e+00 2.0000000000e+00 0.0000000000e+00 10 A 2.0000000000e+00 3.0000000000e+00 0.0000000000e+00 11 B 3.0000000000e+00 0.0000000000e+00 0.0000000000e+00 12 B 3.0000000000e+00 1.0000000000e+00 0.0000000000e+00 13 B 3.0000000000e+00 2.0000000000e+00 0.0000000000e+00 14 B 3.0000000000e+00 3.0000000000e+00 0.0000000000e+00 15 """ with open(xyz_trajectory_filename, "r") as t: xyz_data = t.read() self.assertEqual(ref_xyz, xyz_data) # Running with wrong trajectory_type input fails. self.assertRaises( Error, lambda : ab_flip_model.run(control_parameters, trajectory_filename=xyz_trajectory_filename, trajectory_type='abc') ) self.assertRaises( Error, lambda : ab_flip_model.run(control_parameters, trajectory_filename=xyz_trajectory_filename, trajectory_type=123) )
def testRunWithAnalysis(self): """ Test that the analyis plugins get called correctly. """ # Cell. cell_vectors = [[ 1.000000e+00, 0.000000e+00, 0.000000e+00], [ 0.000000e+00, 1.000000e+00, 0.000000e+00], [ 0.000000e+00, 0.000000e+00, 1.000000e+00]] basis_points = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] unit_cell = KMCUnitCell( cell_vectors=cell_vectors, basis_points=basis_points) # Lattice. lattice = KMCLattice( unit_cell=unit_cell, repetitions=(10,10,1), periodic=(True, True, False)) # Configuration. types = ['B']*100 possible_types = ['A','B'] configuration = KMCConfiguration( lattice=lattice, types=types, possible_types=possible_types) # Interactions. coordinates = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] process_0 = KMCProcess(coordinates, ['A'], ['B'], basis_sites=[0], rate_constant=4.0) process_1 = KMCProcess(coordinates, ['B'], ['A'], basis_sites=[0], rate_constant=1.0) processes = [process_0, process_1] interactions = KMCInteractions(processes) # Setup the model. ab_flip_model = KMCLatticeModel(configuration, interactions) # Run the model with a trajectory file. name = os.path.abspath(os.path.dirname(__file__)) name = os.path.join(name, "..", "TestUtilities", "Scratch") trajectory_filename = os.path.join(name, "ab_flip_traj.py") self.__files_to_remove.append(trajectory_filename) # The control parameters. control_parameters = KMCControlParameters(number_of_steps=1000, dump_interval=500, analysis_interval=300) # Setup a valid minimal analysis object. class AnalysisProxy1(KMCAnalysisPlugin): def __init__(self): pass # Setup a slightly larger analyis object. class AnalysisProxy2(KMCAnalysisPlugin): def __init__(self): self.setup_called = False self.finalize_called = False self.register_step_counts = 0 def setup(self, step, time, configuration): self.setup_called = True def registerStep(self, step, time, configuration): self.register_step_counts += 1 def finalize(self): self.finalize_called = True ap2 = AnalysisProxy2() analysis = [ AnalysisProxy1(), ap2 ] # Run the model for 1000 steps with the analysis objects. # With dump interval 500 the analysis objects should be # called on startup, the at step 300, 600 and step 900 and # a finalization after that. ab_flip_model.run(control_parameters, trajectory_filename=trajectory_filename, analysis=analysis) self.assertTrue(ap2.setup_called) self.assertTrue(ap2.finalize_called) self.assertEqual(ap2.register_step_counts, 3)
def testRunFailAnalysis(self): """ Test that the analyis plugins get called correctly. """ # Cell. cell_vectors = [[ 1.000000e+00, 0.000000e+00, 0.000000e+00], [ 0.000000e+00, 1.000000e+00, 0.000000e+00], [ 0.000000e+00, 0.000000e+00, 1.000000e+00]] basis_points = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] unit_cell = KMCUnitCell( cell_vectors=cell_vectors, basis_points=basis_points) # Lattice. lattice = KMCLattice( unit_cell=unit_cell, repetitions=(10,10,1), periodic=(True, True, False)) # Configuration. types = ['B']*100 possible_types = ['A','B'] configuration = KMCConfiguration( lattice=lattice, types=types, possible_types=possible_types) # Interactions. coordinates = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] process_0 = KMCProcess(coordinates, ['A'], ['B'], basis_sites=[0], rate_constant=4.0) process_1 = KMCProcess(coordinates, ['B'], ['A'], basis_sites=[0], rate_constant=1.0) processes = [process_0, process_1] interactions = KMCInteractions(processes) # Setup the model. ab_flip_model = KMCLatticeModel(configuration, interactions) # The control parameters. control_parameters = KMCControlParameters(number_of_steps=1000, dump_interval=500) # Setup a valid minimal analysis object. class AnalysisProxy1(KMCAnalysisPlugin): def __init__(self): pass # Fail because of not instantitated analysis. self.assertRaises( Error, lambda : ab_flip_model.run(control_parameters, analysis=[AnalysisProxy1]) ) # Fail because of empty analyis list. self.assertRaises( Error, lambda : ab_flip_model.run(control_parameters, analysis=[]) ) # Fail because of not list. self.assertRaises( Error, lambda : ab_flip_model.run(control_parameters, analysis=AnalysisProxy1()) ) # Fail because of wrong type. self.assertRaises( Error, lambda : ab_flip_model.run(control_parameters, analysis=[AnalysisProxy1(), "AP3"]) )
def testCustomRatesRun(self): """ Test the run of an A-B flip model with custom rates. """ # Cell. cell_vectors = [[ 1.000000e+00, 0.000000e+00, 0.000000e+00], [ 0.000000e+00, 1.000000e+00, 0.000000e+00], [ 0.000000e+00, 0.000000e+00, 1.000000e+00]] basis_points = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] unit_cell = KMCUnitCell( cell_vectors=cell_vectors, basis_points=basis_points) # Lattice. lattice = KMCLattice( unit_cell=unit_cell, repetitions=(10,10,1), periodic=(True, True, False)) # Configuration. types = ['B']*100 possible_types = ['A','B'] configuration = KMCConfiguration( lattice=lattice, types=types, possible_types=possible_types) # Interactions. coordinates = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] process_0 = KMCProcess(coordinates, ['A'], ['B'], None, [0], 4.0) process_1 = KMCProcess(coordinates, ['B'], ['A'], None, [0], 1.0) processes = [process_0, process_1] interactions = KMCInteractions(processes, implicit_wildcards=True) # Custom rates. rate_calculator = CustomRateCalculator interactions.setRateCalculator(rate_calculator) # Setup the model. ab_flip_model = KMCLatticeModel(configuration, interactions) # Run the model with a trajectory file. name = os.path.abspath(os.path.dirname(__file__)) name = os.path.join(name, "..", "TestUtilities", "Scratch") trajectory_filename = os.path.join(name, "ab_flip_traj_custom.py") self.__files_to_remove.append(trajectory_filename) # The control parameters. control_parameters = KMCControlParameters(number_of_steps=1000, dump_interval=500, seed=2013) # Run the model for 1000 steps. ab_flip_model.run(control_parameters, trajectory_filename=trajectory_filename) # Read the first last frames from the trajectory file and check that # the fraction of A is close to 75% in the last, and 0 in the first. if MPICommons.isMaster(): global_dict = {} local_dict = {} execfile(trajectory_filename, global_dict, local_dict) # Count the first frame. elem = local_dict["types"][0] nA = len([ ee for ee in elem if ee == "A" ]) nB = len([ ee for ee in elem if ee == "B" ]) self.assertEqual(nA, 0) self.assertEqual(nB, 100) # Count the last frame. elem = local_dict["types"][-1] nA = len([ ee for ee in elem if ee == "A" ]) nB = len([ ee for ee in elem if ee == "B" ]) # Note that the average over a long simulation should be # 75% A using the modified rate function. In this particular # step the A population is 74%. value = 1.0 * nA / (nA + nB) self.assertAlmostEqual(0.74, value, 2)
def testRun2(self): """ Test the run of an A-B flip model. """ # Cell. cell_vectors = [[ 1.000000e+00, 0.000000e+00, 0.000000e+00], [ 0.000000e+00, 1.000000e+00, 0.000000e+00], [ 0.000000e+00, 0.000000e+00, 1.000000e+00]] basis_points = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] unit_cell = KMCUnitCell( cell_vectors=cell_vectors, basis_points=basis_points) # Lattice. lattice = KMCLattice( unit_cell=unit_cell, repetitions=(10,10,1), periodic=(True, True, False)) # Configuration. types = ['B']*100 possible_types = ['A','B'] configuration = KMCConfiguration( lattice=lattice, types=types, possible_types=possible_types) # Interactions. coordinates = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00]] process_0 = KMCProcess(coordinates, ['A'], ['B'], basis_sites=[0], rate_constant=4.0) process_1 = KMCProcess(coordinates, ['B'], ['A'], basis_sites=[0], rate_constant=1.0) processes = [process_0, process_1] interactions = KMCInteractions(processes) # Setup the model. ab_flip_model = KMCLatticeModel(configuration, interactions) # Run the model with a trajectory file. name = os.path.abspath(os.path.dirname(__file__)) name = os.path.join(name, "..", "TestUtilities", "Scratch") trajectory_filename = os.path.join(name, "ab_flip_traj.py") self.__files_to_remove.append(trajectory_filename) # The control parameters. control_parameters = KMCControlParameters(number_of_steps=1000, dump_interval=500, seed=2013) # Run the model for 1000 steps. ab_flip_model.run(control_parameters, trajectory_filename=trajectory_filename) # Read the first last frames from the trajectory file and check that # the fraction of A is close to 20% in the last, and 0 in the first. if MPICommons.isMaster(): global_dict = {} local_dict = {} execfile(trajectory_filename, global_dict, local_dict) # Count the first frame. elem = local_dict["types"][0] nA = len([ ee for ee in elem if ee == "A" ]) nB = len([ ee for ee in elem if ee == "B" ]) self.assertEqual(nA, 0) self.assertEqual(nB, 100) # Count the last frame. elem = local_dict["types"][-1] nA = len([ ee for ee in elem if ee == "A" ]) nB = len([ ee for ee in elem if ee == "B" ]) # Note that the average should be 20.0% over a long run. # It is pure luck that it is exact at this particular # step with the presently used random number seed. fraction = nA * 100.0 / (nA + nB) target = 20.0 self.assertAlmostEqual(fraction, target, 3)
def testRunImplicitWildcards(self): """ Test that ta valid model can run for a few steps. """ # Setup a unitcell. unit_cell = KMCUnitCell(cell_vectors=numpy.array([[1.0,0.0,0.0], [0.0,1.0,0.0], [0.0,0.0,1.0]]), basis_points=[[0.0,0.0,0.0]]) # And a lattice. lattice = KMCLattice(unit_cell=unit_cell, repetitions=(10,10,1), periodic=(True,True,False)) # Set the stating configuration types. types = ['B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'A', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'A', 'B', 'B', 'B', 'B', 'B', 'A', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'A', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'A', 'B', 'B', 'A', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'A'] # Setup the configuration. config = KMCConfiguration(lattice=lattice, types=types, possible_types=["A","B"]) # Generate the interactions with a distance so large that we get a # layer of implicite wildcards in the C++ matchlists. sites = [0] coordinates = [[ 0.000000e+00, 0.000000e+00, 0.000000e+00], [ 1.000000e+00, 0.000000e+00, 0.000000e+00], [ -1.000000e+00, 0.000000e+00, 0.000000e+00], [ 0.000000e+00, -1.000000e+00, 0.000000e+00], [ 0.000000e+00, 1.000000e+00, 0.000000e+00], [ 2.000000e+00, 2.000000e+00, 0.000000e+00]] types0 = ['A', 'B', 'B', 'B', 'B', 'A'] types1 = ['B', 'B', 'A', 'B', 'B', 'A'] process_0 = KMCProcess(coordinates, types0, types1, None, sites, 1.0) types0 = ['A', 'B', 'B', 'B', 'B', 'B'] types1 = ['B', 'B', 'A', 'B', 'B', 'B'] process_1 = KMCProcess(coordinates, types0, types1, None, sites, 1.0) types0 = ['A', 'B', 'B', 'B', 'B', 'B'] types1 = ['B', 'B', 'B', 'A', 'B', 'B'] process_2 = KMCProcess(coordinates, types0, types1, None, sites, 1.0) types0 = ['A', 'B', 'B', 'B', 'B', 'B'] types1 = ['B', 'B', 'B', 'B', 'A', 'B'] process_3 = KMCProcess(coordinates, types0, types1, None, sites, 1.0) # Processes. processes = [process_0, process_1, process_2, process_3] # No implicit wildcards. interactions = KMCInteractions(processes=processes, implicit_wildcards=False) # Create the model. model = KMCLatticeModel(config, interactions) # Get the match types out. match_types = [ l.match_type for l in model._backend().interactions().processes()[0].minimalMatchList() ] # This does not have wildcards added. ref_match_types = [1, 2, 2, 2, 2, 1] self.assertEqual( match_types, ref_match_types ) # Create with implicit wildcards - this is default behavior. interactions = KMCInteractions(processes=processes) # Create the model. model = KMCLatticeModel(config, interactions) # Check the process matchlists again. match_types = [ l.match_type for l in model._backend().interactions().processes()[0].minimalMatchList() ] ref_match_types = [1, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1] # This one has the wildcards (zeroes) added. self.assertEqual( match_types, ref_match_types ) # Setup the run paramters. control_parameters = KMCControlParameters(number_of_steps=10, dump_interval=1) model.run(control_parameters)
def testCalculationNonOrthogonal(self): """ Test a calculation with the on-the-fly MSD analysis. """ # Setup a system, a periodic 10 atoms long 1D chain. unit_cell = KMCUnitCell(cell_vectors=numpy.array([[2.0, 1.0, 0.0], [0.0, 1.0, 0.0], [0.0, 2.0, 1.0]]), basis_points=[[0.0, 0.0, 0.0]]) # And a lattice. lattice = KMCLattice(unit_cell=unit_cell, repetitions=(10, 10, 10), periodic=(True, True, True)) # Setup an initial configuration with one B in a sea of A:s. types = ["A"] * 10 * 10 * 10 types[5] = "B" config = KMCConfiguration(lattice=lattice, types=types, possible_types=["A", "B"]) # Setup a diffusion process to the left. coordinates_p0 = [[0.0, 0.0, 0.0], [-1.0, 0.0, 0.0]] p0 = KMCProcess(coordinates=coordinates_p0, elements_before=["B", "A"], elements_after=["A", "B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p1 = [[0.0, 0.0, 0.0], [1.0, 0.0, 0.0]] p1 = KMCProcess(coordinates=coordinates_p1, elements_before=["B", "A"], elements_after=["A", "B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p2 = [[0.0, 0.0, 0.0], [0.0, -1.0, 0.0]] p2 = KMCProcess(coordinates=coordinates_p2, elements_before=["B", "A"], elements_after=["A", "B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p3 = [[0.0, 0.0, 0.0], [0.0, 1.0, 0.0]] p3 = KMCProcess(coordinates=coordinates_p3, elements_before=["B", "A"], elements_after=["A", "B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p4 = [[0.0, 0.0, 0.0], [0.0, 0.0, -1.0]] p4 = KMCProcess(coordinates=coordinates_p4, elements_before=["B", "A"], elements_after=["A", "B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p5 = [[0.0, 0.0, 0.0], [0.0, 0.0, 1.0]] p5 = KMCProcess(coordinates=coordinates_p5, elements_before=["B", "A"], elements_after=["A", "B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) interactions = KMCInteractions(processes=[p0, p1, p2, p3, p4, p5], implicit_wildcards=True) model = KMCLatticeModel(configuration=config, interactions=interactions) # Setup the analysis. msd = OnTheFlyMSD(history_steps=400, n_bins=10, t_max=25.0, track_type="B") # Setup the control parameters. control_parameters = KMCControlParameters(number_of_steps=4000, dump_interval=100, analysis_interval=1, seed=2013) # Run the model. model.run(control_parameters=control_parameters, analysis=[msd]) # Get the results out. results = msd.results() time_steps = msd.timeSteps() std_dev = msd.stdDev() bin_counters = msd.binCounters() # Compare against references. ref_results = numpy.array( [[ 10.36856672, 28.37170047, 44.38285764, 58.94374243, 72.11121737, 85.02318805, 98.58352498, 115.27324368, 126.49573433, 138.47100039 ], [ 16.05138132, 44.90792913, 68.59720617, 93.35093194, 123.68147594, 148.63693439, 172.54794759, 203.0082052, 232.5195128, 267.73366007 ], [ 2.59976568, 7.35085681, 11.8568078, 16.56678774, 21.77700882, 26.34223625, 30.40786814, 35.09199292, 40.24434182, 46.48414664 ], [ 26.41994804, 73.2796296, 112.98006381, 152.29467437, 195.79269332, 233.66012244, 271.13147258, 318.28144888, 359.01524713, 406.20466046 ], [ 12.9683324, 35.72255728, 56.23966543, 75.51053018, 93.88822619, 111.3654243, 128.99139313, 150.3652366, 166.74007615, 184.95514703 ], [ 18.651147, 52.25878594, 80.45401397, 109.91771968, 145.45848476, 174.97917064, 202.95581574, 238.10019812, 272.76385461, 314.21780672 ], [ 29.01971372, 80.63048641, 124.8368716, 168.86146212, 217.56970213, 260.0023587, 301.53934072, 353.3734418, 399.25958894, 452.68880711 ]]) diff = numpy.linalg.norm(ref_results - results) self.assertAlmostEqual(diff, 0.0, 6) ref_time_steps = numpy.array( [1.25, 3.75, 6.25, 8.75, 11.25, 13.75, 16.25, 18.75, 21.25, 23.75]) diff = numpy.linalg.norm(ref_time_steps - time_steps) self.assertAlmostEqual(diff, 0.0, 8) ref_std_dev = numpy.array([ [ 0.55062327, 2.49729593, 4.98805342, 7.82646477, 10.85497401, 14.13906215, 17.83387379, 22.42069464, 26.20482295, 30.35650154 ], [ 0.85240944, 3.95282576, 7.70942988, 12.39500157, 18.61789684, 24.71780818, 31.21412347, 39.48518175, 48.16868093, 58.69429153 ], [ 0.13806069, 0.6470273, 1.33255031, 2.19971409, 3.27811502, 4.38062279, 5.50081855, 6.82540746, 8.33700723, 10.19055301 ], [ 0.99209394, 4.56092478, 8.97847654, 14.29873598, 20.84046684, 27.47595651, 34.68217147, 43.77406499, 52.59000894, 62.96841965 ], [ 0.4869731, 2.22337228, 4.46934176, 7.08957906, 9.99360309, 13.09539481, 16.50011919, 20.68011712, 24.42476236, 28.67109723 ], [ 0.70036814, 3.25258729, 6.3936455, 10.32002241, 15.48281847, 20.57569786, 25.96138447, 32.74653167, 39.95555528, 48.70894069 ], [ 0.88975069, 4.09754088, 8.10024368, 12.94487456, 18.90879051, 24.96317829, 31.49377349, 39.68202523, 47.75293586, 57.29701788 ] ]) diff = numpy.linalg.norm(ref_std_dev - std_dev) self.assertAlmostEqual(diff, 0.0, 6) ref_bin_counters = (58893, 58531, 57985, 58641, 57509, 57659, 57396, 57037, 56732, 56518) self.assertEqual(bin_counters, ref_bin_counters)
def testCalculation(self): """ Test a calculation with the on-the-fly MSD analysis. """ # Setup a system, a periodic 10 atoms long 1D chain. unit_cell = KMCUnitCell(cell_vectors=numpy.array([[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]]), basis_points=[[0.0, 0.0, 0.0]]) # And a lattice. lattice = KMCLattice(unit_cell=unit_cell, repetitions=(10, 10, 10), periodic=(True, True, True)) # Setup an initial configuration with one B in a sea of A:s. types = ["A"] * 10 * 10 * 10 types[5] = "B" config = KMCConfiguration(lattice=lattice, types=types, possible_types=["A", "B"]) # Setup a diffusion process to the left. coordinates_p0 = [[0.0, 0.0, 0.0], [-1.0, 0.0, 0.0]] p0 = KMCProcess(coordinates=coordinates_p0, elements_before=["B", "A"], elements_after=["A", "B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p1 = [[0.0, 0.0, 0.0], [1.0, 0.0, 0.0]] p1 = KMCProcess(coordinates=coordinates_p1, elements_before=["B", "A"], elements_after=["A", "B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p2 = [[0.0, 0.0, 0.0], [0.0, -1.0, 0.0]] p2 = KMCProcess(coordinates=coordinates_p2, elements_before=["B", "A"], elements_after=["A", "B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p3 = [[0.0, 0.0, 0.0], [0.0, 1.0, 0.0]] p3 = KMCProcess(coordinates=coordinates_p3, elements_before=["B", "A"], elements_after=["A", "B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p4 = [[0.0, 0.0, 0.0], [0.0, 0.0, -1.0]] p4 = KMCProcess(coordinates=coordinates_p4, elements_before=["B", "A"], elements_after=["A", "B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) coordinates_p5 = [[0.0, 0.0, 0.0], [0.0, 0.0, 1.0]] p5 = KMCProcess(coordinates=coordinates_p5, elements_before=["B", "A"], elements_after=["A", "B"], move_vectors=None, basis_sites=[0], rate_constant=1.0) interactions = KMCInteractions(processes=[p0, p1, p2, p3, p4, p5], implicit_wildcards=True) model = KMCLatticeModel(configuration=config, interactions=interactions) # Setup the analysis. msd = OnTheFlyMSD(history_steps=400, n_bins=10, t_max=25.0, track_type="B") # Setup the control parameters. control_parameters = KMCControlParameters(number_of_steps=4000, dump_interval=100, analysis_interval=1, seed=2013) # Run the model. model.run(control_parameters=control_parameters, analysis=[msd]) # Get the results out. results = msd.results() time_steps = msd.timeSteps() std_dev = msd.stdDev() bin_counters = msd.binCounters() # Compare against references. ref_results = numpy.array([ [ 2.59214168, 7.09292512, 11.09571441, 14.73593561, 18.02780434, 21.25579701, 24.64588125, 28.81831092, 31.62393358, 34.6177501 ], [ 2.65374493, 7.10317609, 10.90626886, 14.87948705, 18.25169973, 21.00603548, 22.97611332, 25.57822115, 28.87848128, 32.2240879 ], [ 2.59976568, 7.35085681, 11.8568078, 16.56678774, 21.77700882, 26.34223625, 30.40786814, 35.09199292, 40.24434182, 46.48414664 ], [ 5.24588661, 14.19610121, 22.00198327, 29.61542266, 36.27950408, 42.2618325, 47.62199456, 54.39653208, 60.50241486, 66.841838 ], [ 5.19190736, 14.44378193, 22.9525222, 31.30272335, 39.80481316, 47.59803326, 55.05374939, 63.91030384, 71.8682754, 81.10189674 ], [ 5.2535106, 14.45403291, 22.76307666, 31.44627479, 40.02870855, 47.34827174, 53.38398146, 60.67021407, 69.1228231, 78.70823454 ], [ 7.84565228, 21.54695802, 33.85879107, 46.1822104, 58.05651289, 68.60406875, 78.02986271, 89.48852499, 100.74675668, 113.32598464 ] ]) diff = numpy.linalg.norm(ref_results - results) self.assertAlmostEqual(diff, 0.0, 6) ref_time_steps = numpy.array( [1.25, 3.75, 6.25, 8.75, 11.25, 13.75, 16.25, 18.75, 21.25, 23.75]) diff = numpy.linalg.norm(ref_time_steps - time_steps) self.assertAlmostEqual(diff, 0.0, 8) ref_std_dev = numpy.array( [[ 0.13765582, 0.62432398, 1.24701335, 1.95661619, 2.7137435, 3.53476554, 4.45846845, 5.60517366, 6.55120574, 7.58912539 ], [ 0.14092726, 0.62522628, 1.22572215, 1.97567674, 2.7474467, 3.49323106, 4.1564055, 4.97497483, 5.98245856, 7.06437139 ], [ 0.13806069, 0.6470273, 1.33255031, 2.19971409, 3.27811502, 4.38062279, 5.50081855, 6.82540746, 8.33700723, 10.19055301 ], [ 0.19698798, 0.88356546, 1.74848804, 2.780551, 3.86164462, 4.96954405, 6.09163579, 7.48129474, 8.86263902, 10.36158694 ], [ 0.19496101, 0.89898111, 1.82402696, 2.93896933, 4.23688379, 5.59702476, 7.04227937, 8.7897482, 10.52755635, 12.57213116 ], [ 0.19727427, 0.89961913, 1.8089718, 2.95244717, 4.26071555, 5.56765545, 6.82868861, 8.34413034, 10.12539137, 12.20107405 ], [ 0.24054939, 1.09498957, 2.19698279, 3.54031591, 5.04564022, 6.58676948, 8.14969886, 10.04910241, 12.04968783, 14.34371883 ]]) diff = numpy.linalg.norm(ref_std_dev - std_dev) self.assertAlmostEqual(diff, 0.0, 6) ref_bin_counters = (58893, 58531, 57985, 58641, 57509, 57659, 57396, 57037, 56732, 56518) self.assertEqual(bin_counters, ref_bin_counters)