pybaselines.Baseline.modpoly
- Baseline.modpoly(data, poly_order=2, tol=0.001, max_iter=250, weights=None, use_original=False, mask_initial_peaks=False, return_coef=False)[source]
The modified polynomial (ModPoly) baseline algorithm.
- Parameters:
- dataarray_like, shape (N,)
The y-values of the measured data, with N data points.
- x_dataarray_like, shape (N,), optional
The x-values of the measured data. Default is None, which will create an array from -1 to 1 with N points.
- poly_order
int, optional The polynomial order for fitting the baseline. Default is 2.
- tol
float, optional The exit criteria. Default is 1e-3.
- max_iter
int, optional The maximum number of iterations. Default is 250.
- weightsarray_like, shape (N,), optional
The weighting array. If None (default), then will be an array with size equal to N and all values set to 1.
- use_originalbool, optional
If False (default), will compare the baseline of each iteration with the y-values of that iteration [1] when choosing minimum values. If True, will compare the baseline with the original y-values given by data [2].
- mask_initial_peaksbool, optional
If True, will mask any data where the initial baseline fit + the standard deviation of the residual is less than measured data [3]. Default is False.
- return_coefbool, optional
If True, will convert the polynomial coefficients for the fit baseline to a form that fits the input x_data and return them in the params dictionary. Default is False, since the conversion takes time.
- Returns:
- baseline
numpy.ndarray, shape (N,) The calculated baseline.
- params
dict A dictionary with the following items:
- 'weights': numpy.ndarray, shape (N,)
The weight array used for fitting the data.
- 'tol_history': numpy.ndarray
An array containing the calculated tolerance values for each iteration. The length of the array is the number of iterations completed. If the last value in the array is greater than the input tol value, then the function did not converge.
- 'coef': numpy.ndarray, shape (poly_order + 1,)
Only if return_coef is True. The array of polynomial parameters for the baseline, in increasing order. Can be used to create a polynomial using
numpy.polynomial.polynomial.Polynomial.
- baseline
Notes
Algorithm originally developed in [2] and then slightly modified in [1].
References
[1] (1,2)Gan, F., et al. Baseline correction by improved iterative polynomial fitting with automatic threshold. Chemometrics and Intelligent Laboratory Systems, 2006, 82, 59-65.
[2] (1,2)Lieber, C., et al. Automated method for subtraction of fluorescence from biological raman spectra. Applied Spectroscopy, 2003, 57(11), 1363-1367.
[3]Zhao, J., et al. Automated Autofluorescence Background Subtraction Algorithm for Biomedical Raman Spectroscopy, Applied Spectroscopy, 2007, 61(11), 1225-1232.