1 %>@brief Pre-processing of Raman data: Wavelet-De-noising, Polynomial Baseline Correction, Vector Normalization
9 u.waveletname =
'haar';
11 u.thresholds = [0 0 0 20 20 100];
14 out = pre_wden01.use(ds01);
18 % Polynomial baseline correction
22 u.contaminant_data = [];
23 u.contaminant_idxs = 1;
26 out = pre_bc_poly01.use(ds01_wden01);
27 ds01_wden01_poly01 = out;
32 u.flag_complement = 0;
35 out = fsel01.use(ds01_wden01_poly01);
36 ds01_wden01_poly01_fsel01 = out;
39 pre_norm_vector01 = u;
40 out = pre_norm_vector01.use(ds01_wden01_poly01_fsel01);
41 ds01_wden01_poly01_fsel01_vector01 = out;
50 global SCALE FONTSIZE;
60 vis_alldata01.use(ds01);
61 title(
'Raw Raman spectra');
66 vis_alldata01.use(ds01_wden01);
67 title(
'1. After Wavelet de-noising, 5^{th}-order polynomial baselines');
69 h = plot(ds01_wden01.fea_x, (ds01_wden01.X-ds01_wden01_poly01.X)
', 'LineWidth
', scaled(1), 'Color
', find_color(2));
70 hl = legend(h, {'Baselines
'});
71 format_frank([], [], hl);
76 vis_alldata01.use(ds01_wden01_poly01);
77 title('2. After Polynomial baseline correction
');
81 vis_alldata01.use(ds01_wden01_poly01_fsel01_vector01);
82 title('3. After Cut 1725-600 cm^{-1} --> Vector normalization
');
Feature Selection (FSel) class.
Wavelet De-noising block.
Visualization - All curves in dataset.
Normalization - Vector Normalization.
Polynomial Baseline Correction.
function load_data_raman_sample()