How to use the plenopticam.cfg.PlenopticamConfig function in plenopticam

def setUp(self):
        self.root = tk.Tk()
        self.cfg = PlenopticamConfig()
        self.sta = PlenopticamStatus()
        self.root.cfg = self.cfg
        self.root.sta = self.sta
        self.set_file_path()
        self.pump_events()

def setUp(self):

        # set config for unit test purposes
        self.sta = PlenopticamStatus()
        self.cfg = PlenopticamConfig()
        self.cfg.reset_values()
        self.cfg.params[self.cfg.opt_dbug] = True
        self.cfg.params[self.cfg.opt_prnt] = True

def __init__(self, *args, **kwargs):

        self.cfg = kwargs['cfg'] if 'cfg' in kwargs else PlenopticamConfig()
        self.sta = kwargs['sta'] if 'sta' in kwargs else PlenopticamStatus()

        self._bay_img = kwargs['bay_img'] if 'bay_img' in kwargs else np.array([])

def __init__(self, img, cfg, sta=None, M=None):

        # input variables
        self._img = img
        self.cfg = cfg if cfg is not None else PlenopticamConfig()
        self.sta = sta if sta is not None else PlenopticamStatus()
        self._M = M if M is not None else self.cfg.params[self.cfg.ptc_leng]

        # private variables
        self._peak_img = self._img.copy()
        self._centroids = []

"""

        This class takes a list of integer coordinates as centroids and an intensity map as inputs and re-computes

        :param img: image used as basis for coordinate refinement calculation
        :param centroids: iterable (list or np.ndarray) with coordinates of integer type
        :param cfg: PlenoptiCam configuration object
        :param sta: PlenoptiCam status object
        :param M: micro image size
        :param method: 'area' or 'peak'
        """

        # input variables
        self._img = img
        self._centroids = centroids #np.round(centroids).astype('uint64')
        self.cfg = cfg if cfg is not None else PlenopticamConfig()
        self.sta = sta if sta is not None else PlenopticamStatus()
        self._M = M
        self._method = method if method is not None else 'area'

        # internal variables
        self._t = self._s = 0

        # output variables
        self._centroids_refined = []

fig.text(0.5, 0.2, 'Horizontal dimension [px]', ha='center', va='center', fontsize=14)
    fig.text(0.06, 0.5, 'Vertical dimension [px]', ha='center', va='center', rotation='vertical', fontsize=14)

    #import tikzplotlib
    #tikzplotlib.save('input+mics' + fn + '.tex')
    plt.savefig('input+mics'+fn+'.pdf', bbox_inches='tight', format='pdf')

    plt.show()

    return True


if __name__ == "__main__":

    # create config object
    cfg = PlenopticamConfig()
    #cfg.default_values()
    #cfg.reset_values()

    cfg.params[cfg.cal_path] = r"/Users/Admin/Pictures/Plenoptic/CalibFolder/caldata-B5144000580.tar"
    cfg.params[cfg.lfp_path] = r"/Users/Admin/Pictures/Plenoptic/INRIA_SIROCCO/Building.LFR"
    #cfg.params[cfg.cal_path] = r"../../../../test/data/caldata-B5144402350.tar"
    #cfg.params[cfg.lfp_path] = r"../../../../test/data/gradient_rose_far.lfr"
    cfg.lfpimg['bay'] = "GRBG"
    cfg.params[cfg.opt_cali] = True
    cfg.params[cfg.opt_rota] = True
    cfg.params[cfg.opt_dbug] = False
    cfg.params[cfg.cal_meth] = 'grid-fit'

    cal_opt = False

    if cal_opt:

def __init__(self, cfg=None, sta=None):

        # input variables
        self.cfg = cfg if sta is not None else PlenopticamConfig()
        self.sta = sta if sta is not None else PlenopticamStatus()

        # internal variables
        self._lfp_json = {}
        self._georef = None
        self._lensref = None
        self._serial = None
        self._cam_model = ''
        self._cal_fn = None
        self._raw_data = None
        self._file_found = None
        self._opt_prnt = True if sta is not None else self.cfg.params[self.cfg.opt_prnt]
        self._path = self.cfg.params[self.cfg.cal_path]

        # output variables
        self._wht_bay = None

def __init__(self, bay_img=None, wht_img=None, cfg=None, sta=None):

        # input variables
        self.cfg = cfg if cfg is not None else PlenopticamConfig()
        self.sta = sta if sta is not None else misc.PlenopticamStatus()
        self._bay_img = bay_img.astype('float32') if isinstance(bay_img, np.ndarray) else None
        self._wht_img = wht_img.astype('float32') if isinstance(wht_img, np.ndarray) else None

        self._bit_pac = self.cfg.lfpimg['bit'] if 'bit' in self.cfg.lfpimg else 10
        self._gains = self.cfg.lfpimg['awb'] if 'awb' in self.cfg.lfpimg else [1, 1, 1, 1]
        self._bay_pat = self.cfg.lfpimg['bay'] if 'bay' in self.cfg.lfpimg else None

        # output variables
        self._rgb_img = np.array([])

def __init__(self, cfg=None, sta=None, *args, **kwargs):
        super(PropagatingThread, self).__init__(*args, **kwargs)

        # init
        self.cfg = cfg if cfg is not None else PlenopticamConfig()
        self.sta = sta if sta is not None else misc.PlenopticamStatus()
        self.exc = None
        self.ret = None

def __init__(self, img, centroids, cfg=None, sta=None):

        # input variables
        self._img = rgb2gry(img.copy())[..., 0] if len(img.shape) == 3 else img.copy()
        self._img = Normalizer(self._img).uint8_norm()
        self._centroids = np.asarray(centroids)
        self.cfg = cfg if cfg is not None else PlenopticamConfig()
        self.sta = sta if sta is not None else PlenopticamStatus()