Understanding phasing

Import the necessary libraries

import sys

from scipy.optimize import curve_fit

sys.path.append("../../src")

from relaxometrynmr.core import T1Functions

import numpy as np

import matplotlib.pyplot as plt

import pandas as pd

specify path to the data file and ensure that "\\" is appended to the end of the path

• create an instance t1 of T1Functions

filepath = r"..\..\data\T1_data\1\\"

t1 = T1Functions(filepath)

Read and convert Bruker NMR data to NMRPipe and CSDM formats: read_and_convert_bruker_data.

The function automatically detects and loads the variable delay list (vdlist, vplist, vclist) used in the experiment.

It returns a tuple containing three elements: a list of 1D NMR (spectra), the variable delay list (vd_list), and the complete dataset in CSDM format (csdm_ds)

spectra, vd_list, csdm_ds = t1.read_and_convert_bruker_data(filepath)

Process the returned 1D NMR spectra

• apply the Gaussian apodisation (fwhm)
• zero-filling for increased digital resolution (zero_fill_factor)
• 0^th order phase correction (ph0)
• 1^st order phase correction (ph1) -- this phase correction is a bit nuanced and so far, a value of 0 - 0.6 ° has worked quite well
• Here we will different ph1 values to see how this phasing works, showing the users how to pick a good value of ph1

df = pd.DataFrame(np.arange(0, 0.6, 0.01), columns=['ph1 Values'])

print(df.head())

   ph1 Values
0        0.00
1        0.01
2        0.02
3        0.03
4        0.04

So, we will be using 59 values of ph1 to phase the spectrum, and you will be the judge of how well the phase correction works.

phased_spectra = []
for i, spectrum in enumerate(spectra):
    if i == 14:
        for ph1 in np.arange(0, 0.6, 0.01):
            exp_spectrum = t1.process_spectrum(spectrum, fwhm = "500 Hz", zero_fill_factor = 10, ph0=50, ph1=ph1)
            phased_spectra.append(exp_spectrum)
    else:
        continue

trapz_ints = []
simps_ints = []
x_regions = []
y_regions = []
int_uncs = []

for i, exp_spectrum in enumerate(phased_spectra):
    trapz_int, simps_int, x_region, y_region, int_unc = t1.integrate_spectrum_region(exp_spectrum, ppm_start=500, ppm_end=650)
    trapz_ints.append(trapz_int)
    simps_ints.append(simps_int)
    x_regions.append(x_region)
    y_regions.append(y_region)
    int_uncs.append(int_unc)

max_x_zoom = 1000

min_x_zoom = 200

abs_ints = t1.plot_spectra_and_zoomed_regions(phased_spectra, x_regions, y_regions, max_x_zoom, min_x_zoom)