How to use the orbitize.driver function in orbitize

import matplotlib.pyplot as plt
import time

import orbitize.sampler as sampler
import orbitize.driver
import orbitize.priors as priors
from orbitize.lnlike import chi2_lnlike
from orbitize.kepler import calc_orbit
import orbitize.system
import pdb

testdir = os.path.dirname(os.path.abspath(__file__))
input_file = os.path.join(testdir, 'HD4747.csv')

# perform scale-and-rotate
myDriver = orbitize.driver.Driver(input_file, 'OFTI',
                                  1, 0.84, 53.1836,
                                  mass_err=0.04, plx_err=0.1264,
                                  system_kwargs={'fit_secondary_mass': True, 'tau_ref_epoch': 0}
                                  )

s = myDriver.sampler
samples = s.prepare_samples(10)

if myDriver.system.fit_secondary_mass:
    sma, ecc, inc, argp, lan, tau, plx, gamma, sigma, m1, m0 = [samp for samp in samples]
    ra, dec, vc = orbitize.kepler.calc_orbit(
        s.epochs, sma, ecc, inc, argp, lan, tau, plx, mtot=m1 + m0,
        mass_for_Kamp=m0)
    v_star = vc*-(m1/m0)
else:
    sma, ecc, inc, argp, lan, tau, plx, mtot = [samp for samp in samples]

def test_scale_and_rotate():

    # perform scale-and-rotate
    myDriver = orbitize.driver.Driver(input_file, 'OFTI',
                                      1, 1.22, 56.95, mass_err=0.08, plx_err=0.26)

    s = myDriver.sampler
    samples = s.prepare_samples(100)

    sma, ecc, inc, argp, lan, tau, plx, mtot = [samp for samp in samples]

    ra, dec, vc = orbitize.kepler.calc_orbit(s.epochs, sma, ecc, inc, argp, lan, tau, plx, mtot)
    sep, pa = orbitize.system.radec2seppa(ra, dec)
    sep_sar, pa_sar = np.median(sep[s.epoch_idx]), np.median(pa[s.epoch_idx])

    # test to make sure sep and pa scaled to scale-and-rotate epoch
    sar_epoch = s.system.data_table[s.epoch_idx]
    assert sep_sar == pytest.approx(sar_epoch['quant1'], abs=sar_epoch['quant1_err'])
    assert pa_sar == pytest.approx(sar_epoch['quant2'], abs=sar_epoch['quant2_err'])

def test_scale_and_rotate():

    # perform scale-and-rotate
    myDriver = orbitize.driver.Driver(input_file, 'OFTI',
                                      1, 1.22, 56.95, mass_err=0.08, plx_err=0.26,
                                      system_kwargs={'fit_secondary_mass': True, 'tau_ref_epoch': 0}
                                      )

    s = myDriver.sampler
    samples = s.prepare_samples(100)

    sma, ecc, inc, argp, lan, tau, plx, gamma, sigma, m1, m0 = [samp for samp in samples]
    mtot = m0 + m1
    print('samples read')

    ra, dec, vc = orbitize.kepler.calc_orbit(s.epochs, sma, ecc, inc, argp, lan, tau, plx, mtot)
    sep, pa = orbitize.system.radec2seppa(ra, dec)
    sep_sar, pa_sar = np.median(sep[s.epoch_idx]), np.median(pa[s.epoch_idx])

    # test to make sure sep and pa scaled to scale-and-rotate epoch

def test_system_kwargs():
    """
    Test additional arguments to the system class
    """
    input_file = os.path.join(orbitize.DATADIR, 'test_val.csv')
    myDriver = driver.Driver(input_file, # path to data file
                             'MCMC', # name of algorith for orbit-fitting
                             1, # number of secondary bodies in system
                             1.0, # total system mass [M_sun]
                             50.0, # total parallax of system [mas]
                             mass_err=0.1, # mass error [M_sun]
                             plx_err=0.1,
                             system_kwargs={"tau_ref_epoch": 50000}) # parallax error [mas]
    assert myDriver.system.tau_ref_epoch == 50000

def test_fixed_sys_params_sampling():
    # test in case of fixed mass and parallax
    myDriver = orbitize.driver.Driver(input_file, 'OFTI',
                                      1, 1.22, 56.95)

    s = myDriver.sampler
    samples = s.prepare_samples(100)
    assert np.all(samples[-1] == s.priors[-1])
    assert isinstance(samples[-3], np.ndarray)

def test_fixed_sys_params_sampling():
    # test in case of fixed mass and parallax
    myDriver = orbitize.driver.Driver(input_file, 'OFTI',
                                      1, 1.22, 56.95)

    s = myDriver.sampler
    samples = s.prepare_samples(100)
    assert np.all(samples[-1] == s.priors[-1])
    assert isinstance(samples[-3], np.ndarray)