Automatic Fitting
In this example, the auto-peak-detection is introduced. The auto-peak-detection is a feature that automatically detects the peaks in the spectra. The routine is based on SciPy's find_peaks routine. As described in section advanced usage, the auto-peak-detection can be used via command line or explicit definitions of attributes in the section block of the input file.
In the following example the in example the section block looks like:
JSON
{
"settings": {
"column": ["Energy", "Intensity"],
"decimal": ".",
"energy_start": -1,
"energy_stop": 4,
"header": 0,
"infile": "data.csv",
"outfile": "example_7",
"oversampling": false,
"separator": ",",
"shift": 0,
"smooth": 0,
"autopeak": {
"modeltype": "gaussian",
"height": [0.0, 16],
"threshold": [0.0, 16],
"distance": 2,
"prominence": [0.002, 12],
"width": [0.002, 12],
"wlen": 100
},
"verbose": 1
}
}
This results in an automatic peak detection with the following results as shown in the figure shown below.
Automatic detection of peaks in the spectra. In summary, 8 Gaussian distributions are used to fit this spectra.
No found peaks
In case no peaks are found, the routine will return an error and SpectraFit will not be able to continue.
About the automatic peak detection proposed models
Based on the find_peaks routine, the auto-peak-detection suggests the following intial models:
JSON
"auto_generated_models": {
"models": {
"gaussian_amplitude_1": {
"value": 1.0,
"min": -1.25,
"max": 1.25,
"vary": true
},
"gaussian_center_1": {
"value": 0.0166666666666608,
"min": 0.0083333333333304,
"max": 0.0333333333333216,
"vary": true
},
"gaussian_fwhmg_1": {
"value": 0.5986279251394535,
"min": 0,
"max": 1.197255850278907,
"vary": true
},
"gaussian_amplitude_2": {
"value": 0.1105553529287392,
"min": -0.13819419116092402,
"max": 0.13819419116092402,
"vary": true
},
"gaussian_center_2": {
"value": 1.6666666666666548,
"min": 0.8333333333333274,
"max": 3.3333333333333095,
"vary": true
},
"gaussian_fwhmg_2": {
"value": 0.31772487166969654,
"min": 0,
"max": 0.6354497433393931,
"vary": true
},
"gaussian_amplitude_3": {
"value": 0.1361582465387924,
"min": -0.1701978081734905,
"max": 0.1701978081734905,
"vary": true
},
"gaussian_center_3": {
"value": 1.916666666666654,
"min": 0.958333333333327,
"max": 3.833333333333308,
"vary": true
},
"gaussian_fwhmg_3": {
"value": 0.2807028277094332,
"min": 0,
"max": 0.5614056554188664,
"vary": true
},
"gaussian_amplitude_4": {
"value": 0.1431947128186528,
"min": -0.178993391023316,
"max": 0.178993391023316,
"vary": true
},
"gaussian_center_4": {
"value": 2.1499999999999866,
"min": 1.0749999999999933,
"max": 4.299999999999973,
"vary": true
},
"gaussian_fwhmg_4": {
"value": 0.1519356228913864,
"min": 0,
"max": 0.3038712457827728,
"vary": true
},
"gaussian_amplitude_5": {
"value": 0.1814951542166284,
"min": -0.2268689427707855,
"max": 0.2268689427707855,
"vary": true
},
"gaussian_center_5": {
"value": 2.349999999999985,
"min": 1.1749999999999925,
"max": 4.69999999999997,
"vary": true
},
"gaussian_fwhmg_5": {
"value": 1.443660360679985,
"min": 0,
"max": 2.88732072135997,
"vary": true
},
"gaussian_amplitude_6": {
"value": 0.1277625583305999,
"min": -0.15970319791324988,
"max": 0.15970319791324988,
"vary": true
},
"gaussian_center_6": {
"value": 2.983333333333317,
"min": 1.4916666666666585,
"max": 5.966666666666634,
"vary": true
},
"gaussian_fwhmg_6": {
"value": 0.4363360040696307,
"min": 0,
"max": 0.8726720081392614,
"vary": true
},
"gaussian_amplitude_7": {
"value": 0.1601857154835972,
"min": -0.2002321443544965,
"max": 0.2002321443544965,
"vary": true
},
"gaussian_center_7": {
"value": 3.483333333333315,
"min": 1.7416666666666576,
"max": 6.96666666666663,
"vary": true
},
"gaussian_fwhmg_7": {
"value": 1.1042527611053288,
"min": 0,
"max": 2.2085055222106575,
"vary": true
},
"gaussian_amplitude_8": {
"value": 0.142942940095969,
"min": -0.17867867511996124,
"max": 0.17867867511996124,
"vary": true
},
"gaussian_center_8": {
"value": 3.716666666666648,
"min": 1.858333333333324,
"max": 7.433333333333296,
"vary": true
},
"gaussian_fwhmg_8": {
"value": 0.18031229508920887,
"min": 0,
"max": 0.36062459017841775,
"vary": true
}
},
"positions": [
60,
159,
174,
188,
200,
238,
268,
282
],
"properties": {
"plateau_sizes": [
1,
1,
1,
1,
1,
1,
1,
1
],
"left_edges": [
60,
159,
174,
188,
200,
238,
268,
282
],
"right_edges": [
60,
159,
174,
188,
200,
238,
268,
282
],
"peak_heights": [
1.0,
0.1105553529287392,
0.1361582465387924,
0.1431947128186528,
0.1814951542166284,
0.1277625583305999,
0.1601857154835972,
0.142942940095969
],
"left_thresholds": [
0.02702702702704396,
0.0035696947991552125,
0.003691875598146821,
0.00045265871677968583,
0.0012037545263766103,
0.002382680877353105,
0.0020216169513442017,
0.0009018152296055015
],
"right_thresholds": [
0.027027027027006767,
0.0007936900971818039,
0.0009852120569291967,
0.0020910651786809897,
0.0017121005592188043,
0.0020892844213151185,
0.0012311588060028023,
0.0015135608394682143
],
"prominences": [
0.9825400111971746,
0.02505732635976661,
0.026513865406715603,
0.0068667793315602965,
0.12393423500090289,
0.0589944372688672,
0.10262479626787169,
0.012376077562765209
],
"left_bases": [
10,
125,
125,
138,
150,
221,
221,
276
],
"right_bases": [
110,
166,
180,
191,
221,
249,
299,
299
],
"widths": [
0.5986279251394535,
0.31772487166969654,
0.2807028277094332,
0.1519356228913864,
1.443660360679985,
0.4363360040696307,
1.1042527611053288,
0.18031229508920887
],
"width_heights": [
0.9919104334440619,
0.11034904793658504,
0.13593994939422985,
0.1431381764254326,
0.18047476397177975,
0.12727683823647862,
0.15934077267186683,
0.1428410438861409
],
"left_ips": [
59.70068603743048,
158.94220654600417,
173.9408709370727,
187.87510150335248,
199.1523269715794,
237.79614555237424,
267.58204603935053,
281.88700988131166
],
"right_ips": [
60.29931396256993,
159.25993141767387,
174.22157376478214,
188.02703712624387,
200.5959873322594,
238.23248155644387,
268.68629880045586,
282.06732217640086
]
}
},