Help plotting Bruker 2D spectra

[ndbryant21]

Help plotting Bruker 2D spectra

[kaustubhmote]

@ndbryant21 do you want to only plot the processed data, or process it from scratch and then plot it?

[ndbryant21]

@kaustubhmote For now I would like to plot the processed data. Though I have been generating a few hundred 2D spectra per year and would eventually like to process from scratch.

[kaustubhmote]

This should work:

# read data
dic, data = ng.bruker.read_pdata("datafolder/1/pdata/1")

# read in axis ppm parameters
udic = ng.bruker.guess_udic(dic, data, strip_fake=True)
uc = {i: ng.fileiobase.uc_from_udic(udic, dim=i) for i in (0, 1)}
axis_limits = [*uc[1].ppm_limits(), *uc[0].ppm_limits()]

# contour levels
levels = [data.max() / 20 * 1.4**i for i in range(10)]  # change as needed

# plot
fig, ax = plt.subplots()
ax.contour(
    data.real, 
    levels=levels, 
    extent=axis_limits, 
    cmap=plt.cm.Greys_r, # change as per your preference 
    linewidths=0.5, # change as per your preference
)

ax.set_xlim(11.5, 6)  # change as needed
ax.set_ylim(135, 105)  # change as needed

plt.show()

I will not recommend processing multidimensional data with nmrglue if you need to apply linear prediction to the indirect dimensions as nmrglue's linear prediction functions are not very well tested. It would be better process it in nmrpipe or some other software and then use nmrglue to convert the data to numpy arrays for plotting.