peakfinder.py

import numpy as np
from scipy.optimize import curve_fit
from scipy import signal

def gauss(x, mu, sigma, A):
    return A / (sigma * np.sqrt(2 * np.pi)) * np.exp(- .5 * np.power((x-mu)/sigma , 2))


peakind = signal.find_peaks_cwt(inten_na2, np.arange(2,5), noise_perc=90, min_length=2, min_snr=2)
# plt.plot(lamb_na2, inten_na2)
lamb_peaks = lamb_na2[peakind]
inten_peaks = inten_na2[peakind]
ra = (lamb_peaks > 400) & (lamb_peaks < 600)
l_peaks = lamb_peaks[ra]
for l in l_peaks:
    domain = (lamb_na2 > l - 1) & (lamb_na2 < l + 1)
    popt_peak, pcov_peak = curve_fit(gauss, lamb_na2[domain], inten_na2[domain], p0=[l, .5, 3e3])
    print(f"{l:.4} {popt_peak[1]:.2} ")