Data and Model

Classes to deal with input data

class data_model.Data(x, y, yerr, mask=[])

Class for input data

Stores input data from user

Parameters

  • x (array) – x data

  • y (array) – y data

  • yerr (array) – errors on y data

  • mask (array) – True where to include data, False otherwise

class data_model.Fit(Data_object, Model_object)

Class to perform a fit

Fit the data with a specified model

Parameters

  • Data_object (class) – a data object

  • Model_object (class) – a model object

run_fit()

Run fit

Performs a fit to the data with a minimization routine, currently uses scipy curve_fit

Returns

The best fit model popt (array): The best fit parameter values for the fitting function x_model (array): The x array of the model

Return type

y_model (array)

class data_model.Model(function_type, init_guess=[], poly_deg=4)

Class for model

Generates a model for fitting the data. Currently supports polynomials of arbitrary degreee

Parameters

  • function_type (string) – type of fitting function. Options are: poly

  • init_guess (list) – initial guesses for fit

  • poly_deg (int) – degree of the polynomial

static arbitrary_poly(x, *params)

Make a polynomial function

Function called by minimization routine to create polynomial

Parameters

  • x (array) – array of x values to compute poly model

  • params (array) – array of polynomial indices

Returns

The polynomial model

change_degree(new_degree)

Change polynomial degree

Function to change degree of the fitting polynomial

Parameters

new_degree (int) – the specified degree of polynomial