def test_population_can_gather_vs_survive(self):
assert hasattr(Pop(), "gatherAndSurvive")
assert callable(getattr(Pop(), "gatherAndSurvive"))
self.pop = Pop("test/test/parameters.txt")
self.pop.create()
try:
self.pop.gatherAndSurvive()
except ValueError as e:
assert False, "missing info: {0}".format(e)
def test_population_keeps_track_of_ecological_time(self):
self.pop = Pop(par="test/test/parameters.txt")
self.pop.create()
assert hasattr(
self.pop,
"ecoTime"), "population must keep track of its ecological time!"
def test_ecological_time_correctly_assessed(self):
self.pop = Pop(par="test/test/parameters.txt")
self.pop.create()
self.pop.lifeCycle()
ngen = 5
assert self.pop.ecoTime == self.pop.routineSteps, "one life cycle should be {0} units of ecological time, not {1}".format(
self.pop.routineSteps, self.pop.ecoTime)
self.pop = Pop(par="test/test/parameters.txt")
self.pop.create()
for i in range(ngen):
self.pop.lifeCycle()
assert self.pop.ecoTime == self.pop.routineSteps * ngen, "{2} life cycles should be {0} units of ecological time, not {1}".format(
self.pop.routineSteps * 10, self.pop.ecoTime, ngen)
def test_population_keeps_track_of_resources_over_life_cycle(self):
self.pop = Pop(par="test/test/parameters.txt")
self.pop.create()
assert hasattr(
self.pop, "ecologyShortHistory"
), "population must keep track of its ecological history!"
def test_population_keeps_track_of_exploration_over_life_cycle(self):
self.pop = Pop(par="test/test/parameters.txt")
self.pop.create()
assert hasattr(
self.pop, "explorationShortHistory"
), "population must keep track of its exploration history!"
def test_mutants_are_drawn_from_binomial(self, pseudorandom):
pseudorandom(0)
self.nIndividuals = 1000
self.fakepop = Pop("test/test/parameters.txt")
self.fakepop.create(n=self.nIndividuals)
self.mutationRate = 0.2
self.mutantCount = 0
for ind in self.fakepop.individuals:
ind.mutate(mutRate=self.mutationRate, mutStep=0.05)
if ind.mutant:
self.mutantCount += 1
stat1, pval1 = scistats.ttest_1samp(
[1] * self.mutantCount + [0] *
(self.nIndividuals - self.mutantCount), self.mutationRate)
assert pval1 > 0.05, "T-test mean failed. Observed: {0}, Expected: {1}".format(
self.mutantCount / self.nIndividuals, self.mutationRate)
self.test = scistats.binom_test(self.mutantCount,
self.nIndividuals,
self.mutationRate,
alternative="two-sided")
assert self.test > 0.05, "Success rate = {0} when mutation rate = {1}".format(
self.mutantCount / self.nIndividuals, self.mutationRate)
gc.collect()
def test_resources_info_augmented_at_each_routine(self):
self.pop = Pop(par="test/test/parameters.txt")
self.pop.create()
for i in range(self.pop.routineSteps):
self.pop.routine()
assert self.pop.ecologyShortHistory.shape == ((self.pop.gridSize**2) *
self.pop.routineSteps, 4)
def test_population_creates_grid(self):
self.pop = Pop("test/test/parameters.txt")
self.pop.create(n=20)
assert hasattr(self.pop, "grid")
assert type(self.pop.grid) is Grid
assert self.pop.grid.resources.shape == (self.pop.gridSize,
self.pop.gridSize)
def test_resources_crash_when_too_large(self):
self.pop = Pop(par="test/test/parameters.txt")
self.pop.initRes = 20
self.pop.growth = 100
self.pop.create()
self.pop.lifeCycle()
for cell in np.nditer(self.pop.grid.resources):
assert cell <= self.pop.initRes, "resources too large, should have crashed"
def test_exploration_info_augmented_at_each_routine(self):
self.pop = Pop(par="test/test/parameters.txt")
self.pop.predation = 0
self.pop.create()
for i in range(self.pop.routineSteps):
self.pop.routine()
assert self.pop.explorationShortHistory.shape == (
self.pop.nIndiv * self.pop.routineSteps, 4)
def test_fertility_returns_positive_float(self):
self.fakepop = Pop("test/test/parameters.txt")
self.fakepop.create()
for ind in range(len(self.fakepop.individuals)):
indiv = self.fakepop.individuals[ind]
setattr(indiv, "storage", 1 + 9 * ind)
indiv.reproduce(fecundity=2)
assert type(indiv.fertility) is float
assert indiv.fertility >= 0
def test_update_replaces_old_gen_with_new_gen(self):
self.pop = Pop("test/test/parameters.txt")
self.pop.create()
self.pop.routine()
self.pop.reproduce()
oldgen = self.pop.individuals
self.pop.update()
assert len(self.pop.individuals) == self.pop.nIndiv
assert self.pop.individuals != oldgen
def test_mutation_does_not_affect_phenotype_type(self):
self.fakepop = Pop("test/test/parameters.txt")
self.fakepop.create(n=1)
self.indiv = self.fakepop.individuals[0]
self.phen = self.indiv.vigilance
self.indiv.mutate(mutRate=1, mutStep=0.05)
assert type(self.indiv.vigilance) is float
gc.collect()
def test_population_routine_changes_resources_grid(self):
self.pop = Pop("test/test/parameters.txt")
self.pop.create()
resG = self.pop.grid.resources
self.pop.routine()
compareGrids = self.pop.grid.resources != resG
assert compareGrids.all()
def test_update_returns_population_vigilance_info(self):
self.pop = Pop(par="test/test/parameters.txt")
self.pop.create()
self.pop.routine()
self.pop.reproduce()
self.pop.update()
assert hasattr(self.pop, "vigilance")
assert self.pop.vigilance is not None
assert type(self.pop.vigilance) is float
assert 0 <= self.pop.vigilance <= 1
def test_population_routine_changes_share_grid(self):
self.pop = Pop("test/test/parameters.txt")
self.pop.create()
shareG = self.pop.grid.share
self.pop.routine()
compareGrids = self.pop.grid.share == shareG
assert compareGrids.all() == False
def test_lam_error_when_resources_too_big(self):
self.pop = Pop(par="test/test/parameters.txt")
self.pop.initRes = 20000000000000000000
self.pop.create()
try:
self.pop.lifeCycle()
except ValueError as e:
assert str(
e
) == 'lam value too large', "This program should fail at poisson random draw, not '{0}'".format(
e)
def test_population_has_plotting_option(self):
self.pop = Pop("test/test/parameters.txt")
self.pop.create()
try:
self.pop.launch(dev='on')
except TypeError as e:
assert False, "allow for 'on' device to show plots"
os.remove("output/vigilance_out.txt")
os.remove("output/vigilance_out.gif")
os.remove('output/resources_out.txt')
os.remove('output/exploration_out.txt')
os.remove('output/grid_out.gif')
def test_grid_gif_is_created(self):
self.pop = Pop("test/test/parameters.txt")
self.pop.create()
self.pop.launch(dev='on')
self.filesListRootOut = os.listdir("./output")
assert "grid_out.gif" in self.filesListRootOut, "no output grid gif created"
os.remove("output/vigilance_out.txt")
os.remove("output/vigilance_out.gif")
os.remove('output/resources_out.txt')
os.remove('output/exploration_out.txt')
os.remove('output/grid_out.gif')
def test_mutants_are_defined(self):
self.pop = Pop("test/test/parameters.txt")
self.pop.create(n=1)
self.indiv = self.pop.individuals[0]
self.indiv.mutate(mutRate=0.5, mutStep=0.5)
assert hasattr(
self.indiv, "mutant"
), "We don't know if our individual is a mutant because it doesn't have this attribute"
assert type(self.indiv.mutant) is bool
gc.collect()
def test_fertility_increases_with_storage(self):
self.fakepop = Pop("test/test/parameters.txt")
self.fakepop.create()
fertility = 0
for ind in range(len(self.fakepop.individuals)):
indiv = self.fakepop.individuals[ind]
setattr(indiv, "storage", 1 + 9 * ind)
indiv.reproduce(fecundity=2)
assert indiv.fertility > fertility
fertility = indiv.fertility
def test_deviation_function_returns_float(self):
self.fakepop = Pop("test/test/parameters.txt")
self.fakepop.create(n=1)
self.indiv = self.fakepop.individuals[0]
self.v = self.indiv.vigilance
for mutationBool in [True, False]:
self.indiv.mutant = mutationBool
self.indiv.deviate(mutStep=0.05)
assert type(self.indiv.mutationDeviation) is float
gc.collect()
def test_mutants_get_deviation_from_phenotype(self):
self.fakepop = Pop("test/test/parameters.txt")
self.fakepop.create(n=1)
self.indiv = self.fakepop.individuals[0]
self.indiv.mutate(mutRate=1, mutStep=0.05)
assert hasattr(
self.indiv, "mutationDeviation"
), "Individual is a mutant: it needs to be set a deviation from phenotype"
assert -1 < self.indiv.mutationDeviation < 1
gc.collect()
def test_population_exploration_gives_share_info(self):
self.pop = Pop("test/test/parameters.txt")
self.pop.create()
self.pop.explore()
m = self.pop.gridSize
assert hasattr(self.pop, "ncell")
assert type(self.pop.ncell) is np.ndarray
assert self.pop.ncell.shape == (m, m)
assert hasattr(self.pop, "vcell")
assert type(self.pop.vcell) is np.ndarray
assert self.pop.vcell.shape == (m, m)
def test_gathering_gives_individuals_storage(self):
self.pop = Pop(par="test/test/parameters.txt")
self.pop.create()
self.pop.grid.share = np.full([self.pop.gridSize, self.pop.gridSize],
0.8)
for i in self.pop.individuals:
i.vigilance = 0
self.pop.gatherAndSurvive()
for i in self.pop.individuals:
assert i.storage > 0
def test_only_live_individuals_gather_and_survive(self):
self.pop = Pop("test/test/parameters.txt")
self.pop.create()
self.pop.explore()
for ind in self.pop.individuals:
ind.alive = False
self.pop.gatherAndSurvive()
for ind in self.pop.individuals:
assert ind.alive == False
assert ind.storage == 0
def test_individual_mutation_can_be_unbounded(self):
self.fakepop = Pop("test/test/parameters.txt")
self.fakepop.nIndiv = 100
self.fakepop.initialVigilance = 1
self.fakepop.create()
collectPhenotypes = []
for ind in self.fakepop.individuals:
ind.mutate(1, 0.5, bounded=False)
collectPhenotypes.append(ind.vigilance)
assert any([i > 1 for i in collectPhenotypes
]), "no phenotype went over 1, even when unbounded."
def test_population_vigilance_is_correct(self):
self.pop = Pop(par="test/test/parameters.txt")
self.pop.create()
self.pop.routine()
self.pop.reproduce()
self.pop.update()
collectVigilances = []
for ind in self.pop.individuals:
collectVigilances.append(ind.vigilance)
assert self.pop.vigilance == pytest.approx(np.mean(collectVigilances),
0.1)
def test_mutation_function_takes_and_returns_phenotype(self):
self.pop = Pop("test/test/parameters.txt")
self.pop.create(n=1)
self.indiv = self.pop.individuals[0]
self.indiv.mutate(mutRate=0.5, mutStep=0.5)
x = self.indiv.vigilance
assert type(
x
) is float, "Phenotypic values ({0}) must be of type float, and not {1}".format(
x, type(x))
assert 0 <= x <= 1, "Phenotypic values must be in range [0,1]"
gc.collect()
def test_mutants_depend_on_seed(self, pseudorandom):
self.nIndividuals = 1000
self.fakepop = Pop("test/test/parameters.txt")
self.fakepop.create(n=self.nIndividuals)
mutants = []
for ind in self.fakepop.individuals:
pseudorandom(0)
ind.mutate(mutRate=0.3, mutStep=0.1)
mutants.append(ind.mutant)
assert all(mutants) or not any(
mutants), "Mutant does not depend on seed: {0}".format(
set(mutants))
