seismicrna.cluster.tests package

Submodules

class seismicrna.cluster.tests.em_test.TestCalcBic(methodName='runTest')

Bases: TestCase

test_formula()
test_large_n_data()
test_negative_n_data_raises()
test_negative_n_params_raises()
test_positive_log_like_raises()
test_returns_float()
test_zero_log_like()
test_zero_n_data_returns_nan()
test_zero_params()
class seismicrna.cluster.tests.em_test.TestCalcLogLike(methodName='runTest')

Bases: TestCase

test_multiple_uniqs()
test_returns_float()
test_single_read()
test_single_uniq_multiple_counts()
test_zero_counts()
class seismicrna.cluster.tests.emk_test.TestAssignClusterings(methodName='runTest')

Bases: TestCase

compare_result(x: ndarray, y: ndarray, expect: ndarray)
test_0_clusters()
test_0_positions()
test_1_cluster()
test_more_clusters()
class seismicrna.cluster.tests.emk_test.TestCalcMeanArcsineDistanceClusters(methodName='runTest')

Bases: TestCase

test_identical_clusters_distance_zero()
test_nonnegative()
test_permuted_columns_same_result()
test_single_cluster()
test_symmetry()
class seismicrna.cluster.tests.emk_test.TestCalcMeanPearsonClusters(methodName='runTest')

Bases: TestCase

test_identical_clusters_correlation_one()
test_permuted_columns_same_result()
test_returns_float()
test_single_cluster()
class seismicrna.cluster.tests.emk_test.TestGetCommonK(methodName='runTest')

Bases: TestCase

test_empty_raises()
test_mixed_ks_raises()
test_multiple_runs_same_k()
test_returns_correct_k()
test_single_run()
class seismicrna.cluster.tests.emk_test.TestSortRuns(methodName='runTest')

Bases: TestCase

test_already_sorted()
test_best_run_first()
test_empty_list()
test_mixed_ks_raises()
test_reverse_order()
test_single_run()
class seismicrna.cluster.tests.jackpot_test.TestBootstrapJackpotScores(*args, **kwargs)

Bases: TestCase

REF = 'test_ref'
REFS = 'test_refs'
SAMPLE = 'test_sample'
static calc_confidence_interval(log_jackpot_quotients: list[float], confidence_level: float)
run_ideal_jackpot(min_mut_gap: int, mut_collisions: str, mut_probs: str | None = None)

Test that bootstrapping “perfect” data correctly returns a jackpotting quotient that is expected to be 1.

setUp()

Hook method for setting up the test fixture before exercising it.

property sim_dir
sim_jackpot_quotient(min_mut_gap: int, mut_collisions: str, seed: int, mut_probs: str | None = None)

Simulate a dataset and return its jackpotting quotient.

tearDown()

Hook method for deconstructing the test fixture after testing it.

test_ideal_jackpot_drop()
test_ideal_jackpot_merge()
test_ideal_jackpot_uncorrected()
class seismicrna.cluster.tests.jackpot_test.TestCalcJackpotQuotient(methodName='runTest')

Bases: TestCase

test_equal_scores_returns_one()
test_formula()
test_real_greater_than_null()
test_real_less_than_null()
test_zero_scores_returns_one()
class seismicrna.cluster.tests.jackpot_test.TestCalcJackpotScore(methodName='runTest')

Bases: TestCase

test_formula()
test_single_unique_read()
test_uniform_obs_eq_exp()
test_zero_reads_empty_anomalies()
test_zero_reads_nonempty_raises()
class seismicrna.cluster.tests.jackpot_test.TestCalcJackpotScoreCi(methodName='runTest')

Bases: TestCase

test_accepts_numpy_array()
test_identical_scores_zero_width()
test_interval_contains_mean()
test_single_score_returns_nan()
test_wider_ci_for_higher_confidence()
class seismicrna.cluster.tests.jackpot_test.TestCalcSemiGAnomaly(methodName='runTest')

Bases: TestCase

test_array_all_equal()
test_array_all_unequal()
test_float_equal()
test_float_unequal()
class seismicrna.cluster.tests.jackpot_test.TestLinearizeEndsMatrix(methodName='runTest')

Bases: TestCase

test_diagonal_only()
test_empty_matrix()
test_multiple_entries_values()
test_only_upper_triangle()
test_single_entry()
class seismicrna.cluster.tests.jackpot_test.TestSimClusters(methodName='runTest')

Bases: TestCase

test_sim_clusters_dropped()
test_sim_clusters_merged()
class seismicrna.cluster.tests.jackpot_test.TestSimReads(methodName='runTest')

Bases: TestCase

static count_reads(reads: ndarray, clusts: ndarray, n_clust: int)

Count reads for each cluster and position.

test_sim_reads_dropped()
test_sim_reads_merged()
class seismicrna.cluster.tests.marginal_test.TestCalcMarginalSimulated(methodName='runTest')

Bases: TestCase

Verify that calc_marginal returns log probabilities that match the empirical frequencies of simulated reads to within statistical tolerance, for both mut_collisions=”drop” and “merge”.

test_5pos_gap2_drop()
test_5pos_gap2_merge()
class seismicrna.cluster.tests.marginal_test.TestMarginalResps(methodName='runTest')

Bases: TestCase

compare(p_mut: ndarray, p_ends: ndarray, p_clust: ndarray, end5s: ndarray, end3s: ndarray, unmasked: ndarray, muts_per_pos: list[ndarray], min_mut_gap: int, mut_collisions: str, expect_log_marginals: ndarray, expect_resps: ndarray)
test_1pos()
test_1pos_2clusters()
test_2pos_gap0()
test_2pos_gap0_2clusters()
test_2pos_gap1_drop()
test_2pos_gap1_merge()
test_2pos_masked0()
test_2pos_masked1()
test_6pos_gap2_2clusters_drop()
test_6pos_gap2_2clusters_merge()