def test_reactions_observable(self): fname = os.path.join(self.dir, "test_observables_particle_reactions.h5") sim = Simulation("CPU") sim.context.box_size = [10.,10.,10.] sim.context.particle_types.add("A", .0) sim.context.particle_types.add("B", .0) sim.context.particle_types.add("C", .0) sim.context.reactions.add_conversion("mylabel", "A", "B", .00001) sim.context.reactions.add_conversion("A->B", "A", "B", 1.) sim.context.reactions.add_fusion("B+C->A", "B", "C", "A", 1.0, 1.0, .5, .5) sim.add_particle("A", common.Vec(0, 0, 0)) sim.add_particle("B", common.Vec(1.0, 1.0, 1.0)) sim.add_particle("C", common.Vec(1.1, 1.0, 1.0)) n_timesteps = 1 handle = sim.register_observable_reactions(1) with closing(io.File.create(fname)) as f: handle.enable_write_to_file(f, u"reactions", int(3)) loop = sim.create_loop(1) loop.write_config_to_file(f) loop.run(n_timesteps) type_str_to_id = {k: x["type_id"] for k, x in ioutils.get_particle_types(fname).items()} with h5py.File(fname, "r") as f2: data = f2["readdy/observables/reactions"] time_series = f2["readdy/observables/reactions/time"] np.testing.assert_equal(time_series, np.array(range(0, n_timesteps+1))) def get_item(name, collection): return next(x for x in collection if x["name"] == name) import readdy.util.io_utils as io_utils reactions = io_utils.get_reactions(fname) mylabel_reaction = get_item("mylabel", reactions.values()) np.testing.assert_allclose(mylabel_reaction["rate"], .00001) np.testing.assert_equal(mylabel_reaction["n_educts"], 1) np.testing.assert_equal(mylabel_reaction["n_products"], 1) np.testing.assert_equal(mylabel_reaction["educt_types"], [type_str_to_id["A"], 0]) np.testing.assert_equal(mylabel_reaction["product_types"], [type_str_to_id["B"], 0]) atob_reaction = get_item("A->B", reactions.values()) np.testing.assert_equal(atob_reaction["rate"], 1.) np.testing.assert_equal(atob_reaction["n_educts"], 1) np.testing.assert_equal(atob_reaction["n_products"], 1) np.testing.assert_equal(mylabel_reaction["educt_types"], [type_str_to_id["A"], 0]) np.testing.assert_equal(mylabel_reaction["product_types"], [type_str_to_id["B"], 0]) fusion_reaction = get_item("B+C->A", reactions.values()) np.testing.assert_equal(fusion_reaction["rate"], 1.) np.testing.assert_equal(fusion_reaction["educt_distance"], 1.) np.testing.assert_equal(fusion_reaction["n_educts"], 2) np.testing.assert_equal(fusion_reaction["n_products"], 1) np.testing.assert_equal(fusion_reaction["educt_types"], [type_str_to_id["B"], type_str_to_id["C"]]) np.testing.assert_equal(fusion_reaction["product_types"], [type_str_to_id["A"], 0]) records = data["records"][:] np.testing.assert_equal(len(records), 2) # records of 1st time step for record in records[1]: np.testing.assert_equal(record["reaction_type"] == 0 or record["reaction_type"] == 1, True) if record["reaction_type"] == 0: np.testing.assert_equal(record["position"], np.array([.0, .0, .0])) np.testing.assert_equal(record["reaction_id"], atob_reaction["id"]) elif record["reaction_type"] == 1: # fusion np.testing.assert_allclose(record["position"], np.array([1.05, 1.0, 1.0])) np.testing.assert_equal(record["reaction_id"], fusion_reaction["id"])
def test_reactions_observable(self): common.set_logging_level("warn") fname = os.path.join(self.dir, "test_observables_particle_reactions.h5") sim = Simulation() sim.set_kernel("CPU") sim.box_size = common.Vec(10, 10, 10) sim.register_particle_type("A", .0, 5.0) sim.register_particle_type("B", .0, 6.0) sim.register_particle_type("C", .0, 6.0) sim.register_reaction_conversion("mylabel", "A", "B", .00001) sim.register_reaction_conversion("A->B", "A", "B", 1.) sim.register_reaction_fusion("B+C->A", "B", "C", "A", 1.0, 1.0, .5, .5) sim.add_particle("A", common.Vec(0, 0, 0)) sim.add_particle("B", common.Vec(1.0, 1.0, 1.0)) sim.add_particle("C", common.Vec(1.1, 1.0, 1.0)) n_timesteps = 1 handle = sim.register_observable_reactions(1) with closing( io.File(fname, io.FileAction.CREATE, io.FileFlag.OVERWRITE)) as f: handle.enable_write_to_file(f, u"reactions", int(3)) sim.run_scheme_readdy(True).write_config_to_file( f).configure_and_run(n_timesteps, 1) type_str_to_id = ioutils.get_particle_types(fname) with h5py.File(fname, "r") as f2: data = f2["readdy/observables/reactions"] time_series = f2["readdy/observables/reactions/time"] np.testing.assert_equal(time_series, np.array(range(0, n_timesteps + 1))) def get_item(name, collection): return next(x for x in collection if x["name"] == name) order_1_reactions = data["registered_reactions/order1_reactions"] mylabel_reaction = get_item("mylabel", order_1_reactions) np.testing.assert_equal(mylabel_reaction["rate"], .00001) np.testing.assert_equal(mylabel_reaction["n_educts"], 1) np.testing.assert_equal(mylabel_reaction["n_products"], 1) np.testing.assert_equal(mylabel_reaction["educt_types"], [type_str_to_id["A"], 0]) np.testing.assert_equal(mylabel_reaction["product_types"], [type_str_to_id["B"], 0]) atob_reaction = get_item("A->B", order_1_reactions) np.testing.assert_equal(atob_reaction["rate"], 1.) np.testing.assert_equal(atob_reaction["n_educts"], 1) np.testing.assert_equal(atob_reaction["n_products"], 1) np.testing.assert_equal(mylabel_reaction["educt_types"], [type_str_to_id["A"], 0]) np.testing.assert_equal(mylabel_reaction["product_types"], [type_str_to_id["B"], 0]) order_2_reactions = data["registered_reactions/order2_reactions"] fusion_reaction = get_item("B+C->A", order_2_reactions) np.testing.assert_equal(fusion_reaction["rate"], 1.) np.testing.assert_equal(fusion_reaction["educt_distance"], 1.) np.testing.assert_equal(fusion_reaction["n_educts"], 2) np.testing.assert_equal(fusion_reaction["n_products"], 1) np.testing.assert_equal(fusion_reaction["educt_types"], [type_str_to_id["B"], type_str_to_id["C"]]) np.testing.assert_equal(fusion_reaction["product_types"], [type_str_to_id["A"], 0]) records = data["records"][:] np.testing.assert_equal(len(records), 2) # records of 1st time step for record in records[1]: np.testing.assert_equal( record["reaction_type"] == 0 or record["reaction_type"] == 1, True) if record["reaction_type"] == 0: np.testing.assert_equal(record["position"], np.array([.0, .0, .0])) np.testing.assert_equal(record["reaction_index"], 1) elif record["reaction_type"] == 1: # fusion np.testing.assert_equal(record["position"], np.array([1.05, 1.0, 1.0])) np.testing.assert_equal(record["reaction_index"], 0) common.set_logging_level("warn")