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")
