# Path: bmlingam/tests/test_pm3.py
# def _gen_data(i, gen_data_params):
# def _estimate_hparams(xs, infer_params):
# def _mainloop(n_trials, gen_data_params, infer_params, mcmc_params):
# def test_posterior_inference(
#     infer_params=None, mcmc_params=None, gen_data_params=None, 
#     n_trials=50, plot_result=False, plot_samples_all=False, show_result=False, 
#     show_result_all=False):


from copy import deepcopy
from bmlingam.tests.test_pm3 import test_posterior_inference, \
                                    infer_params_default, \
                                    mcmc_params_default, \
                                    gen_data_params_default
import six


    infer_params_scaling = deepcopy(infer_params_mp4)
    infer_params_scaling.standardize = 'scaling'

    infer_params_commonscaling = deepcopy(infer_params_mp4)
    infer_params_commonscaling.standardize = 'commonscaling'

    return {
        'default': infer_params_default, 
        'cache_mp4': infer_params_mp4, 
        'standardize': infer_params_standardize, 
        'keepratio': infer_params_keepratio, 
        'scaling': infer_params_scaling, 
        'commonscaling': infer_params_commonscaling
    }

def _get_mcmc_paramss():
    return {
        'default': mcmc_params_default
    }

def _get_gen_data_paramss():
    confounders0 = deepcopy(gen_data_params_default)
    confounders0.n_confounders = 0
    confounders1 = deepcopy(gen_data_params_default)
    confounders1.n_confounders = 1
    confounders12 = deepcopy(gen_data_params_default)
    confounders12.n_confounders = 12

    return {

# Path: bmlingam/tests/test_pm3.py
# def _gen_data(i, gen_data_params):
# def _estimate_hparams(xs, infer_params):
# def _mainloop(n_trials, gen_data_params, infer_params, mcmc_params):
# def test_posterior_inference(
#     infer_params=None, mcmc_params=None, gen_data_params=None, 
#     n_trials=50, plot_result=False, plot_samples_all=False, show_result=False, 
#     show_result_all=False):


# Path: bmlingam/tests/test_bmlingam.py
from copy import deepcopy
from bmlingam.tests.test_pm3 import test_posterior_inference, \
                                    infer_params_default, \
                                    mcmc_params_default, \
                                    gen_data_params_default
import six


    infer_params_scaling = deepcopy(infer_params_mp4)
    infer_params_scaling.standardize = 'scaling'

    infer_params_commonscaling = deepcopy(infer_params_mp4)
    infer_params_commonscaling.standardize = 'commonscaling'

    return {
        'default': infer_params_default, 
        'cache_mp4': infer_params_mp4, 
        'standardize': infer_params_standardize, 
        'keepratio': infer_params_keepratio, 
        'scaling': infer_params_scaling, 
        'commonscaling': infer_params_commonscaling
    }

def _get_mcmc_paramss():
    return {
        'default': mcmc_params_default
    }

def _get_gen_data_paramss():
    confounders0 = deepcopy(gen_data_params_default)
    confounders0.n_confounders = 0
    confounders1 = deepcopy(gen_data_params_default)
    confounders1.n_confounders = 1
    confounders12 = deepcopy(gen_data_params_default)
    confounders12.n_confounders = 12

    return {

        'default': gen_data_params_default, 
