import sys
import matplotlib.pyplot as plt
sys.path.append("../../src")
from nmrlineshapeanalyser.core import NMRProcessor
#create NMRProcessor object
processor = NMRProcessor()
#Load filepath
filepath = r"..\..\data\two_peaks\2\pdata\1"
# Load the data
processor.load_data(filepath)
#Select the region of interest
x_data, y_data = processor.select_region(-630, -540)
#Normalize the data and return normalised y_axis and the corresponding x_axis
x_data, y_normalized = processor.normalize_data(x_data, y_data)
#define initial parameters for the fitting
#this example is for a single peak
#format of the parameters is [x0, amplitude, width, eta, offset]
# x0 (position), amplitude, width, eta (mixing parameter), offset
#x0 has to be close to the peak position
initial_params = [
-576.4, 0.12, 40.51, 0.89, -143.115,
-597, 0.12, 40.51, 0.89, -143.115
]
number_of_peaks = 2
# fixed_x0 controls whether peak positions should be fixed during fitting
# False means position can vary, True means position is fixed
fixed_x0 = [False]*number_of_peaks
#alternatively as:
# fixed_x0 = [False, False]
#FIt the data
popt, metrics, fitted = processor.fit_peaks(x_data, y_normalized, initial_params, fixed_x0)
#popt is the optimized parameters
#metrics is the metrics of the fitting
#fitted is the fitted curve data
#Plot and examine the results of the fitting
fig, axes, components = processor.plot_results(x_data, y_normalized, fitted, popt)
#Save the figure as an png file and the results as a csv file
processor.save_results(filepath, x_data, y_normalized, fitted, metrics, popt, components)
