Class ParamModel

pyxrf/model/parameters.py:216–1236

The module used for maintain the set of fitting parameters. Attributes ---------- parameters : `atom.Dict` A list of `Parameter` objects, subclassed from the `Atom` base class. These `Parameter` objects hold all relevant xrf information. data : array 1D

class ParamModel(Atom):
    """
    The module used for maintain the set of fitting parameters.

    Attributes
    ----------
    parameters : `atom.Dict`
        A list of `Parameter` objects, subclassed from the `Atom` base class.
        These `Parameter` objects hold all relevant xrf information.
    data : array
        1D array of spectrum
    prefit_x : array
        xX axis with range defined by low and high limits.
    param_d : dict
        Parameters can be transferred into this dictionary.
    param_new : dict
        More information are saved, such as element position and width.
    total_y : dict
        Results from k lines
    total_y_l : dict
        Results from l lines
    total_y_m : dict
        Results from l lines
    e_list : str
        All elements used for fitting.
    file_path : str
        The path where file is saved.
    element_list : list
        The list of element lines selected for fitting
    n_selected_elines_for_fitting : Int
        The number of element lines selected for fitting
    n_selected_pure_elines_for_fitting : Int
        The number of element lines selected for fitting
            excluding pileup peaks and user defined peaks.
            Only 'pure' lines like Ca_K, K_K etc.
    """

    # Reference to FileIOModel object
    io_model = Typed(object)

    default_parameters = Dict()
    # data = Typed(np.ndarray)
    prefit_x = Typed(object)
    result_dict_names = List()
    param_new = Dict()
    total_y = Typed(object)
    # total_l = Dict()
    # total_m = Dict()
    # total_pileup = Dict()
    e_name = Str()  # Element line name selected in combo box
    add_element_intensity = Float(1000.0)
    element_list = List()
    # data_sets = Typed(OrderedDict)
    EC = Typed(object)
    x0 = Typed(np.ndarray)
    y0 = Typed(np.ndarray)
    max_area_dig = Int(2)
    auto_fit_all = Dict()