def _compile_acceleration_eval(self, arrays): names = [x.name for x in self.particle_arrays] if self.equations is None: if self.method == 'shepard': equations = [ InterpolateFunction(dest='interpolate', sources=names) ] elif self.method == 'sph': equations = [InterpolateSPH(dest='interpolate', sources=names)] else: equations = [ Group(equations=[ SummationDensity(dest=name, sources=names) for name in names ], real=False), Group(equations=[ SPHFirstOrderApproximationPreStep(dest='interpolate', sources=names, dim=self.dim) ], real=True), Group(equations=[ SPHFirstOrderApproximation(dest='interpolate', sources=names, dim=self.dim) ], real=True) ] else: equations = self.equations self.func_eval = AccelerationEval(arrays, equations, self.kernel) compiler = SPHCompiler(self.func_eval, None) compiler.compile()
def __init__(self, arrays, equations, dim, kernel=None, domain_manager=None): """Constructor. Parameters ---------- arrays: list(ParticleArray) equations: list dim: int kernel: kernel instance. domain_manager: DomainManager """ self.arrays = arrays self.equations = equations self.domain_manager = domain_manager self.dim = dim if kernel is None: self.kernel = Gaussian(dim=dim) else: self.kernel = kernel self.func_eval = AccelerationEval(arrays, equations, self.kernel) compiler = SPHCompiler(self.func_eval, None) compiler.compile() self._create_nnps(arrays)
def _setup_integrator(self, equations, integrator): kernel = CubicSpline(dim=1) arrays = [self.pa] a_eval = AccelerationEval(particle_arrays=arrays, equations=equations, kernel=kernel) comp = SPHCompiler(a_eval, integrator=integrator) comp.compile() nnps = LinkedListNNPS(dim=kernel.dim, particles=arrays) a_eval.set_nnps(nnps) integrator.set_nnps(nnps)
def _compile_acceleration_eval(self, arrays): names = [x.name for x in self.particle_arrays] if self.equations is None: equations = [ InterpolateFunction(dest='interpolate', sources=names) ] else: equations = self.equations self.func_eval = AccelerationEval(arrays, equations, self.kernel) compiler = SPHCompiler(self.func_eval, None) compiler.compile()
def _make_accel_eval(self, equations, cache_nnps=False): arrays = [self.pa] kernel = CubicSpline(dim=self.dim) a_eval = AccelerationEval( particle_arrays=arrays, equations=equations, kernel=kernel ) comp = SPHCompiler(a_eval, integrator=None) comp.compile() nnps = NNPS(dim=kernel.dim, particles=arrays, cache=cache_nnps) nnps.update() a_eval.set_nnps(nnps) return a_eval
def _make_accel_eval(self, equations): arrays = [self.pa] kernel = CubicSpline(dim=self.dim) a_eval = AccelerationEval( particle_arrays=arrays, equations=equations, kernel=kernel ) comp = SPHCompiler(a_eval, integrator=None) comp.compile() nnps = NNPS(dim=kernel.dim, particles=arrays) nnps.update() a_eval.set_nnps(nnps) return a_eval
def _setup_integrator(self, equations, integrator): pytest.importorskip('pysph.base.gpu_nnps') kernel = CubicSpline(dim=1) arrays = [self.pa] from pysph.base.gpu_nnps import BruteForceNNPS as GPUNNPS a_eval = AccelerationEval( particle_arrays=arrays, equations=equations, kernel=kernel, backend='opencl' ) comp = SPHCompiler(a_eval, integrator=integrator) comp.compile() nnps = GPUNNPS(dim=kernel.dim, particles=arrays, cache=True) nnps.update() a_eval.set_nnps(nnps) integrator.set_nnps(nnps)
def _make_accel_eval(self, equations, cache_nnps=True): pytest.importorskip('pysph.base.gpu_nnps') from pysph.base.gpu_nnps import ZOrderGPUNNPS as GPUNNPS arrays = [self.pa] kernel = CubicSpline(dim=self.dim) a_eval = AccelerationEval( particle_arrays=arrays, equations=equations, kernel=kernel, backend='opencl' ) comp = SPHCompiler(a_eval, integrator=None) comp.compile() self.sph_compiler = comp nnps = GPUNNPS(dim=kernel.dim, particles=arrays, cache=cache_nnps) nnps.update() a_eval.set_nnps(nnps) return a_eval
def setup(self, particles, equations, nnps, kernel=None, fixed_h=False): """ Setup the solver. The solver's processor id is set if the in_parallel flag is set to true. The order of the integrating calcs is determined by the solver's order attribute. This is usually called at the start of a PySPH simulation. """ self.particles = particles if kernel is not None: self.kernel = kernel mode = 'mpi' if self.in_parallel else 'serial' self.acceleration_evals = make_acceleration_evals( particles, equations, self.kernel, mode) sep = '-' * 70 eqn_info = '[\n' + ',\n'.join([str(e) for e in equations]) + '\n]' logger.info('Using equations:\n%s\n%s\n%s' % (sep, eqn_info, sep)) logger.info('Using integrator:\n%s\n %s\n%s' % (sep, self.integrator, sep)) sph_compiler = SPHCompiler(self.acceleration_evals, self.integrator) sph_compiler.compile() # Set the nnps for all concerned objects. for ae in self.acceleration_evals: ae.set_nnps(nnps) self.integrator.set_nnps(nnps) # set the parallel manager for the integrator self.integrator.set_parallel_manager(self.pm) # Set the post_stage_callback. self.integrator.set_post_stage_callback(self._post_stage_callback) # set integrator option for constant smoothing length self.fixed_h = fixed_h self.integrator.set_fixed_h(fixed_h) logger.debug("Solver setup complete.")
def _make_integrator(self): arrays = [self.pa] kernel = CubicSpline(dim=self.dim) eqs = [[Eq1(dest='fluid', sources=['fluid'])], [Eq2(dest='fluid', sources=['fluid'])]] meqs = MultiStageEquations(eqs) a_evals = make_acceleration_evals(arrays, meqs, kernel, backend=self.backend) integrator = MyIntegrator(fluid=MyStepper()) comp = SPHCompiler(a_evals, integrator=integrator) comp.compile() nnps = self.NNPS_cls(dim=kernel.dim, particles=arrays) nnps.update() for ae in a_evals: ae.set_nnps(nnps) return integrator
def __init__(self, arrays, equations, dim, kernel=None, domain_manager=None, backend=None, nnps_factory=NNPS): """Constructor. Parameters ---------- arrays: list(ParticleArray) equations: list dim: int kernel: kernel instance. domain_manager: DomainManager backend: str: indicates the backend to use. one of ('opencl', 'cython', '', None) nnps_factory: A factory that creates an NNPSBase instance. """ self.arrays = arrays self.equations = equations self.domain_manager = domain_manager self.dim = dim if kernel is None: self.kernel = Gaussian(dim=dim) else: self.kernel = kernel self.nnps_factory = nnps_factory self.backend = backend self.func_eval = AccelerationEval(arrays, equations, self.kernel, backend=backend) compiler = SPHCompiler(self.func_eval, None) compiler.compile() self._create_nnps(arrays)
def test_detection_of_missing_arrays_for_integrator(self): # Given. x = np.asarray([1.0]) u = np.asarray([0.0]) h = np.ones_like(x) pa = get_particle_array(name='fluid', x=x, u=u, h=h, m=h) arrays = [pa] # When integrator = LeapFrogIntegrator(fluid=LeapFrogStep()) equations = [SHM(dest="fluid", sources=None)] kernel = CubicSpline(dim=1) a_eval = AccelerationEval(particle_arrays=arrays, equations=equations, kernel=kernel) comp = SPHCompiler(a_eval, integrator=integrator) # Then self.assertRaises(RuntimeError, comp.compile)
def test_detect_missing_arrays_for_many_particle_arrays(self): # Given. x = np.asarray([1.0]) u = np.asarray([0.0]) h = np.ones_like(x) fluid = get_particle_array_wcsph(name='fluid', x=x, u=u, h=h, m=h) solid = get_particle_array(name='solid', x=x, u=u, h=h, m=h) arrays = [fluid, solid] # When integrator = PECIntegrator(fluid=TwoStageRigidBodyStep(), solid=TwoStageRigidBodyStep()) equations = [SHM(dest="fluid", sources=None)] kernel = CubicSpline(dim=1) a_eval = AccelerationEval(particle_arrays=arrays, equations=equations, kernel=kernel) comp = SPHCompiler(a_eval, integrator=integrator) # Then self.assertRaises(RuntimeError, comp.compile)
], update_nnps=False ) ] from pysph.sph.acceleration_eval import AccelerationEval from pysph.sph.sph_compiler import SPHCompiler kernel = CubicSpline(dim=2) integrator = SWEIntegrator(fluid=SWEStep()) tf = 2 solver = Solver( kernel=kernel, dim=2, integrator=integrator, cfl=0.1, adaptive_timestep=True, output_at_times=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6], tf=tf ) part_arr = app.create_particles eqns = app.create_equations() app.setup(solver=solver, equations=eqns, particle_factory=part_arr) a_eval = AccelerationEval( solver.particles, equations=one_time_equations, kernel=CubicSpline(dim=2)) compiler = SPHCompiler(a_eval, None) compiler.compile() a_eval.set_nnps(app.nnps) a_eval.compute(0.0, 1e-4) app.run()
def __init__(self, all_particles, scheme, domain=None, innerloop=True, updates=True, parallel=False, steps=None, D=0): """The second integrator is a simple Euler-Integrator (accurate enough due to very small time steps; very fast) using EBGSteps. EBGSteps are basically the same as EulerSteps, exept for the fact that they work with an intermediate ebg velocity [eu, ev, ew]. This velocity does not interfere with the actual velocity, which is neseccery to not disturb the real velocity through artificial damping in this step. The ebg velocity is initialized for each inner loop again and reset in the outer loop.""" from math import ceil from pysph.base.kernels import CubicSpline from pysph.sph.integrator_step import EBGStep from compyle.config import get_config from pysph.sph.integrator import EulerIntegrator from pysph.sph.scheme import BeadChainScheme from pysph.sph.equation import Group from pysph.sph.fiber.utils import (HoldPoints, Contact, ComputeDistance) from pysph.sph.fiber.beadchain import (Tension, Bending, ArtificialDamping) from pysph.base.nnps import DomainManager, LinkedListNNPS from pysph.sph.acceleration_eval import AccelerationEval from pysph.sph.sph_compiler import SPHCompiler if not isinstance(scheme, BeadChainScheme): raise TypeError("Scheme must be BeadChainScheme") self.innerloop = innerloop self.dt = scheme.dt self.fiber_dt = scheme.fiber_dt self.domain_updates = updates self.steps = steps self.D = D self.eta0 = scheme.rho0 * scheme.nu # if there are more than 1 particles involved, elastic equations are # iterated in an inner loop. if self.innerloop: # second integrator # self.fiber_integrator = EulerIntegrator(fiber=EBGStep()) steppers = {} for f in scheme.fibers: steppers[f] = EBGStep() self.fiber_integrator = EulerIntegrator(**steppers) # The type of spline has no influence here. It must be large enough # to contain the next particle though. kernel = CubicSpline(dim=scheme.dim) equations = [] g1 = [] for fiber in scheme.fibers: g1.append(ComputeDistance(dest=fiber, sources=[fiber])) equations.append(Group(equations=g1)) g2 = [] for fiber in scheme.fibers: g2.append( Tension(dest=fiber, sources=None, ea=scheme.E * scheme.A)) g2.append( Bending(dest=fiber, sources=None, ei=scheme.E * scheme.Ip)) g2.append( Contact(dest=fiber, sources=scheme.fibers, E=scheme.E, d=scheme.dx, dim=scheme.dim, k=scheme.k, lim=scheme.lim, eta0=self.eta0)) g2.append(ArtificialDamping(dest=fiber, sources=None, d=self.D)) equations.append(Group(equations=g2)) g3 = [] for fiber in scheme.fibers: g3.append(HoldPoints(dest=fiber, sources=None, tag=100)) equations.append(Group(equations=g3)) # These equations are applied to fiber particles only - that's the # reason for computational speed up. particles = [p for p in all_particles if p.name in scheme.fibers] # A seperate DomainManager is needed to ensure that particles don't # leave the domain. if domain: xmin = domain.manager.xmin ymin = domain.manager.ymin zmin = domain.manager.zmin xmax = domain.manager.xmax ymax = domain.manager.ymax zmax = domain.manager.zmax periodic_in_x = domain.manager.periodic_in_x periodic_in_y = domain.manager.periodic_in_y periodic_in_z = domain.manager.periodic_in_z gamma_yx = domain.manager.gamma_yx gamma_zx = domain.manager.gamma_zx gamma_zy = domain.manager.gamma_zy n_layers = domain.manager.n_layers N = self.steps or int(ceil(self.dt / self.fiber_dt)) # dt = self.dt/N self.domain = DomainManager(xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, periodic_in_x=periodic_in_x, periodic_in_y=periodic_in_y, periodic_in_z=periodic_in_z, gamma_yx=gamma_yx, gamma_zx=gamma_zx, gamma_zy=gamma_zy, n_layers=n_layers, dt=self.dt, calls_per_step=N) else: self.domain = None # A seperate list for the nearest neighbourhood search is # benefitial since it is much smaller than the original one. nnps = LinkedListNNPS(dim=scheme.dim, particles=particles, radius_scale=kernel.radius_scale, domain=self.domain, fixed_h=False, cache=False, sort_gids=False) # The acceleration evaluator needs to be set up in order to compile # it together with the integrator. if parallel: self.acceleration_eval = AccelerationEval( particle_arrays=particles, equations=equations, kernel=kernel) else: self.acceleration_eval = AccelerationEval( particle_arrays=particles, equations=equations, kernel=kernel, mode='serial') # Compilation of the integrator not using openmp, because the # overhead is too large for those few fiber particles. comp = SPHCompiler(self.acceleration_eval, self.fiber_integrator) if parallel: comp.compile() else: config = get_config() config.use_openmp = False comp.compile() config.use_openmp = True self.acceleration_eval.set_nnps(nnps) # Connecting neighbourhood list to integrator. self.fiber_integrator.set_nnps(nnps)
def _compile_acceleration_eval(self, arrays): names = [x.name for x in self.particle_arrays] equations = [InterpolateFunction(dest='interpolate', sources=names)] self.func_eval = AccelerationEval(arrays, equations, self.kernel) compiler = SPHCompiler(self.func_eval, None) compiler.compile()