def test_sampling_output(self):
""" Check that output generated by the sampling postprocessing goes to the correct path."""
# Setup parameters.
parameters = CancerSimulatorParameters(
matrix_size=1000,
number_of_generations=20,
division_probability=1,
adv_mutant_division_probability=1,
death_probability=0.1,
adv_mutant_death_probability=0.0,
mutation_probability=1,
adv_mutant_mutation_probability=1,
adv_mutation_wait_time=10,
number_of_initial_mutations=150,
number_of_mutations_per_division=1,
tumour_multiplicity=None,
sampling_fraction=0.5,
plot_tumour_growth=True,
export_tumour=True,
)
simulator = CancerSimulator(parameters=parameters, seed=1, outdir="casim_out")
# Cleanup (remove test output).
self._test_files.append(simulator.outdir)
# Run the simulation.
simulator.run()
# Check sampling file was written.
self.assertRegex(",".join(os.listdir(simulator._CancerSimulator__simdir)), re.compile(r"sample_out_[0-9]{3}_[0-9]{3}.txt"))
self.assertRegex(",".join(os.listdir(simulator._CancerSimulator__simdir)), re.compile(r"sampleHistogram_[0-9]{3}_[0-9]{3}.pdf"))
self.assertIn('growthCurve.pdf', os.listdir(simulator._CancerSimulator__simdir))
def test_init_step_increases(self):
""" Check the the internal step counter is propely updated. """
parameters = CancerSimulatorParameters()
cancer_sim = CancerSimulator(parameters, seed=1, outdir = mkdtemp())
self.assertEqual(cancer_sim._CancerSimulator__init_step, 0)
cancer_sim.run()
self.assertEqual(cancer_sim._CancerSimulator__init_step, 2)
def test_export_tumour_matrix(self):
""" Test exporting the tumour matrix. """
parameters = CancerSimulatorParameters()
cancer_sim = CancerSimulator(parameters, seed=1, outdir = mkdtemp())
cancer_sim.run()
# Check files where created.
listing = os.listdir(cancer_sim._CancerSimulator__simdir)
for f in ['mtx.p', 'mut_container.p', 'mtx_VAF.txt']:
self.assertIn(f, listing)
def test_high_sampling_fraction(self):
""" Test run with sampling_fraction=0.9 """
# Setup parameters.
parameters = CancerSimulatorParameters(
matrix_size=1000,
number_of_generations=20,
division_probability=1,
adv_mutant_division_probability=1,
death_probability=0.1,
adv_mutant_death_probability=0.0,
mutation_probability=1,
adv_mutant_mutation_probability=1,
adv_mutation_wait_time=10,
number_of_initial_mutations=150,
number_of_mutations_per_division=50,
tumour_multiplicity=None,
read_depth=100,
sampling_fraction=0.9,
)
# Setup the simulator.
simulator = CancerSimulator(parameters=parameters, seed=1, outdir=mkdtemp())
# Cleanup (remove test output).
self._test_files.append(simulator.outdir)
# Check run returns sanely.
self.assertEqual(simulator.run(), 0)
def test_reference_data_1mut(self):
""" Run a reference test and compare against reference data."""
""" 1 mutation per division."""
# Setup parameters. Values taken from casim/params.py.
parameters = CancerSimulatorParameters(
matrix_size=1000,
number_of_generations=20,
division_probability=1,
adv_mutant_division_probability=1,
death_probability=0.1,
adv_mutant_death_probability=0.0,
mutation_probability=1,
adv_mutant_mutation_probability=1,
adv_mutation_wait_time=10,
number_of_initial_mutations=150,
number_of_mutations_per_division=1,
tumour_multiplicity=None,
sampling_fraction=0.1,
sampling_positions=[(501,502)],
)
simulator = CancerSimulator(parameters=parameters, seed=1, outdir="reference_test_out")
self._test_files.append('reference_test_out')
simulator.run()
### Load results and reference data.
# Reference data.
ref_dir = os.path.join(os.path.abspath(os.path.dirname(__file__)), 'reference_test_data_1mut', 'cancer_1', 'simOutput')
with open(os.path.join(ref_dir, 'mtx.p'), 'rb') as fp:
ref_mtx = pickle.load(fp)
with open(os.path.join(ref_dir, 'mut_container.p'), 'rb') as fp:
ref_mutations = pickle.load(fp)
run_dir = os.path.join('reference_test_out', 'cancer_1', 'simOutput')
# Run data.
with open(os.path.join(run_dir, 'mtx.p'), 'rb') as fp:
run_mtx = pickle.load(fp)
with open(os.path.join(run_dir, 'mut_container.p'), 'rb') as fp:
run_mutations = pickle.load(fp)
# Check data is equal.
self.assertAlmostEqual(numpy.linalg.norm((ref_mtx - run_mtx).toarray()), 0.0)
self.assertEqual(ref_mutations, run_mutations)
def test_sampling_positions(self):
""" Check setting the sample positions generates the expected output."""
# Setup parameters.
parameters = CancerSimulatorParameters(
matrix_size=1000,
number_of_generations=20,
division_probability=1,
adv_mutant_division_probability=1,
death_probability=0.1,
adv_mutant_death_probability=0.0,
mutation_probability=1,
adv_mutant_mutation_probability=1,
adv_mutation_wait_time=10,
number_of_initial_mutations=150,
number_of_mutations_per_division=1,
tumour_multiplicity=None,
sampling_fraction=0.1,
sampling_positions=[
[500,500],
[450,550],
[450,550],
[550,450],
[550,550],
],
plot_tumour_growth=True,
export_tumour=True,
)
simulator = CancerSimulator(parameters=parameters, seed=1, outdir="casim_out")
# Cleanup (remove test output).
self._test_files.append(simulator.outdir)
# Run the simulation.
simulator.run()
# Check sampling file was written.
self.assertIn("sample_out_500_500.txt", os.listdir(simulator._CancerSimulator__simdir))
self.assertIn("sampleHistogram_500_500.pdf", os.listdir(simulator._CancerSimulator__simdir))
self.assertRegex(",".join(os.listdir(simulator._CancerSimulator__simdir)), re.compile(r"sampleHistogram_[0-9]{3}_[0-9]{3}.pdf"))
parameters = CancerSimulatorParameters(
matrix_size=4096,
number_of_generations=g, # vary
division_probability=dp, # 1 => exp. growth
adv_mutant_division_probability=0.3,
death_probability=0.0,
adv_mutant_death_probabilityability=0.0,
mutation_rate=1.0, # 1 =>
adv_mutant_mutation_probability=0.8,
mutations_per_division=
10, # if mutation event occurs, have this number of mutation
adv_mutation_interval=30000, # large to not kick in
number_of_initital_mutations=
2, # initial number of mutations in first cancer cell
tumour_multiplicity='single',
)
simulator = CancerSimulator(parameters,
seed=None,
outdir="%s" % (n_run))
t0 = time()
simulator.run()
T = time() - t0
with open(os.path.join(simulator.outdir, "log.txt"), 'a') as fp:
fp.write("%s\t%f\t%d\t%e\n" % (simulator.seed, dp, g, T))
simulator.dump()
sleep(1)