def fill_params_dict_list_dimensions(do_fast_mgc=False):
mcorr = DCorr(which_test='unbiased')
dcorr = DCorr(which_test='biased')
mantel = DCorr(which_test='mantel')
mgc = MGC()
rv_corr = RVCorr(which_test='rv')
hhg = HHG()
cca = RVCorr(which_test='cca')
mdmr = MDMR()
independence_tests = [] # [mgc, mcorr, dcorr, mantel, rv_corr, cca]
params_dict_list = []
for sim_name, sim_func in simulations.items():
for test in independence_tests:
params_dict = {
'independence_test': test,
'simulation_type': sim_func[1],
'dim': find_dim(sim_name),
'additional_params': {}
}
params_dict_list.append(params_dict)
if do_fast_mgc:
fast_mgc = MGC()
additional_params = {"is_fast": True}
params_dict = {
'independence_test': fast_mgc,
'simulation_type': sim_func[1],
'dim': find_dim(sim_name),
'additional_params': additional_params
}
params_dict_list.append(params_dict)
return params_dict_list
def fill_params_dict_list_sample_sizes(base_path, do_fast_mgc=False):
mcorr = DCorr(which_test='unbiased')
dcorr = DCorr(which_test='biased')
mantel = DCorr(which_test='mantel')
mgc = MGC()
hhg = HHG()
pearson = RVCorr(which_test='pearson')
mdmr = MDMR()
independence_tests = [mcorr, dcorr, mantel, mgc, hhg, pearson, mdmr]
params_dict_list = []
for sim_name, sim_func in simulations.items():
for test in independence_tests:
params_dict = {
'independence_test': test,
'simulation_type': sim_func[1],
'base_path': base_path,
'additional_params': {}
}
params_dict_list.append(params_dict)
if do_fast_mgc:
fast_mgc = MGC()
additional_params = {"is_fast": True}
params_dict = {
'independence_test': fast_mgc,
'simulation_type': sim_func[1],
'base_path': base_path,
'additional_params': additional_params
}
params_dict_list.append(params_dict)
return params_dict_list
def fill_params_dict_list_dimensions():
mcorr = DCorr(which_test='unbiased')
dcorr = DCorr(which_test='biased')
mantel = DCorr(which_test='mantel')
mgc = MGC()
rv_corr = RVCorr(which_test='rv')
hhg = HHG()
cca = RVCorr(which_test='cca')
mdmr = MDMR()
# initialize additional test
# add the test that you wish to run in the `independence_tests` list
independence_tests = [] # [mgc, mcorr, dcorr, mantel, rv_corr, cca]
params_dict_list = []
for sim_name, sim_func in simulations.items():
for test in independence_tests:
params_dict = {
'independence_test': test,
'simulation_type': sim_func[1],
'dim': find_dim(sim_name)
}
params_dict_list.append(params_dict)
return params_dict_list
def fill_params_dict_list_sample_sizes():
mcorr = DCorr(which_test='unbiased')
dcorr = DCorr(which_test='biased')
mantel = DCorr(which_test='mantel')
mgc = MGC()
hhg = HHG()
pearson = RVCorr(which_test='pearson')
independence_tests = [] # [mgc, mcorr, dcorr, mantel, pearson]
params_dict_list = []
for sim_name, sim_func in simulations.items():
for test in independence_tests:
params_dict = {
'independence_test': test,
'simulation_type': sim_func[1]
}
params_dict_list.append(params_dict)
return params_dict_list
def test_local_corr():
# Against a randomly defined data set
X = np.array([1.1728, 2.4941, 2.4101, 0.1814, 1.1978, 1.5806, 1.2504,
1.9706, 1.8839, 0.8760], dtype=np.float64).reshape(-1, 1)
Y = np.array([3.2311, 12.1113, 11.1350, 1.1989, 3.3127, 4.8580, 3.4917,
7.1748, 6.5792, 2.4012], dtype=np.float64).reshape(-1, 1)
rvcorr = RVCorr(None)
rvcorr2 = RVCorr(None, 'pearson')
rvcorr3 = RVCorr(None, 'cca')
test_stat1 = rvcorr.test_statistic(X, Y)[0]
test_stat2 = rvcorr2.test_statistic(X, Y)[0]
test_stat3 = rvcorr3.test_statistic(X, Y)[0]
assert np.round(test_stat1, decimals=2) == 0.90
assert np.round(test_stat2, decimals=2) == 0.95
assert np.round(test_stat3, decimals=2) == 0.90
# Against linear simulations
np.random.seed(0)
X, Y = sims.linear_sim(100, 1)
rvcorr = RVCorr(None)
rvcorr2 = RVCorr(None, 'pearson')
rvcorr3 = RVCorr(None, 'cca')
assert rvcorr.get_name() == 'rv'
assert rvcorr2.get_name() == 'pearson'
assert rvcorr3.get_name() == 'cca'
test_stat1 = rvcorr.test_statistic(X, Y)[0]
test_stat2 = rvcorr2.test_statistic(X, Y)[0]
test_stat3 = rvcorr3.test_statistic(X, Y)[0]
assert np.round(test_stat1, decimals=2) == 0.24
assert np.round(test_stat2, decimals=2) == 0.49
assert np.round(test_stat3, decimals=2) == 0.24