def test_prey_only():
"""Tests simulations with Preys only.
The population is expected to grow exponentially.
"""
clean_outs()
sim_input = "./input/prey.xml"
holdsrtn = [1] # needed because nose does not send() to test generator
outfile = which_outfile()
cmd = ["cyclus", "-o", outfile, "--input-file", sim_input]
yield check_cmd, cmd, '.', holdsrtn
rtn = holdsrtn[0]
print("Confirming valid Cyclus execution.")
assert_equal(rtn, 0)
series = agent_time_series([prey, pred])
print("Prey:", series[prey], "Predators:", series[pred])
prey_exp = [2**n for n in range(10)]
pred_exp = [0 for n in range(10)]
assert_equal(series[prey], prey_exp)
assert_equal(series[pred], pred_exp)
clean_outs()
def test_predator_only():
"""Tests simulations with Predators only.
The population is expected to die off after a timestep.
"""
clean_outs()
# A reference simulation input for Lotka-Volterra simulation
sim_input = os.path.join(DIR, "input", "predator.xml")
holdsrtn = [1] # needed because nose does not send() to test generator
outfile = which_outfile()
cmd = ["cyclus", "-o", outfile, "--input-file", sim_input]
yield check_cmd, cmd, '.', holdsrtn
rtn = holdsrtn[0]
print("Confirming valid Cyclus execution.")
assert_equal(rtn, 0)
series = agent_time_series([prey, pred])
print("Prey:", series[prey], "Predators:", series[pred])
prey_exp = [0 for n in range(10)]
pred_exp = [1, 1] + [0 for n in range(8)]
assert_equal(series[prey], prey_exp)
assert_equal(series[pred], pred_exp)
clean_outs()
def test_predator_only():
"""Tests simulations with Predators only.
The population is expected to die off after a timestep.
"""
clean_outs()
# A reference simulation input for Lotka-Volterra simulation
sim_input = "./input/predator.xml"
holdsrtn = [1] # needed because nose does not send() to test generator
cmd = ["cyclus", "-o", h5out, "--input-file", sim_input]
yield check_cmd, cmd, '.', holdsrtn
rtn = holdsrtn[0]
print("Confirming valid Cyclus execution.")
assert_equal(rtn, 0)
output = tables.open_file(h5out, mode = "r")
series = agent_time_series(output, [prey, pred])
print("Prey:", series[prey], "Predators:", series[pred])
prey_exp = [0 for n in range(10)]
pred_exp = [1, 1] + [0 for n in range(8)]
assert_equal(series[prey], prey_exp)
assert_equal(series[pred], pred_exp)
output.close()
clean_outs()
def test_predator_only():
"""Tests simulations with Predators only.
The population is expected to die off after a timestep.
"""
clean_outs()
# A reference simulation input for Lotka-Volterra simulation
sim_input = "./input/predator.xml"
holdsrtn = [1] # needed because nose does not send() to test generator
cmd = ["cyclus", "-o", h5out, "--input-file", sim_input]
yield check_cmd, cmd, '.', holdsrtn
rtn = holdsrtn[0]
print("Confirming valid Cyclus execution.")
assert_equal(rtn, 0)
output = tables.open_file(h5out, mode = "r")
series = agent_time_series(output, [prey, pred])
print("Prey:", series[prey], "Predators:", series[pred])
prey_exp = [0 for n in range(10)]
pred_exp = [1, 1] + [0 for n in range(8)]
assert_equal(series[prey], prey_exp)
assert_equal(series[pred], pred_exp)
output.close()
clean_outs()
def test_lotka_volterra():
"""Tests simulations with Preys and Predators
Preys offer a resource representing itself. Predators acquire the resources
of the preys. When the prey's resource gets accepted, it decommissions
itself. Preys and predators have a fixed life expectancy. However, if
a predator does not get any resource for several time steps,
it must decommission itself as well.
After certain time steps, predators and preys reproduce and deploy new
predators and preys respectively.
A single oscillation is expected and the peak of the predator population is
expected to occur after the peak of the prey population.
"""
clean_outs()
sim_input = "./input/lotka_volterra_determ.xml"
holdsrtn = [1] # needed because nose does not send() to test generator
outfile = which_outfile()
cmd = ["cyclus", "-o", outfile, "--input-file", sim_input]
yield check_cmd, cmd, '.', holdsrtn
rtn = holdsrtn[0]
print("Confirming valid Cyclus execution.")
assert_equal(rtn, 0)
series = agent_time_series([prey, pred])
print("Prey:", series[prey], "Predators:", series[pred])
prey_max = series[prey].index(max(series[prey]))
pred_max = series[pred].index(max(series[pred]))
print("t_prey_max:", prey_max, "t_pred_max:", pred_max)
assert_true(prey_max < pred_max)
clean_outs()
