Using the dnplab phase cycling function

This example demonstrates how to use the phase cycling function on dnpdata objects.

# The following example shows how and when the phase_cycle function can be conveniently used.
#
# To get started, first, setup the python environment:

import dnplab as dnp

Let's load some example data the data consists of 4 fid that are phase cycled (0-90-180-270)

data = dnp.load("../../data/prospa/water_phase_cycled/data.2d")

we are interested in the spectra and only the arbitrary part from -900 to -100 ppm

data = dnp.fourier_transform(data)["f2", (-900.0, -100.0)]

we look at the real part of the spectra

data_real = data.real

lets plot the spectrum for all 4 cycles

dnp.fancy_plot(data_real)
plot 04 phase cycling
[<matplotlib.lines.Line2D object at 0x7fe13dd03160>, <matplotlib.lines.Line2D object at 0x7fe13dd03d30>, <matplotlib.lines.Line2D object at 0x7fe13dd03a30>, <matplotlib.lines.Line2D object at 0x7fe13dd039a0>]

clearly the spectra are phase cycled, but we'd like to have them phased all the same we can use dnp.phase_cycle for that: Note that [0(X),1(Y),2(-X),3(-Y)] gives the phase cycle Axes.

data_phased = dnp.phase_cycle(data, "Average", [0, 1, 2, 3])
dnp.fancy_plot(data_phased)
plot 04 phase cycling
[<matplotlib.lines.Line2D object at 0x7fe13b93de80>, <matplotlib.lines.Line2D object at 0x7fe13b93dbb0>, <matplotlib.lines.Line2D object at 0x7fe13b93d2b0>, <matplotlib.lines.Line2D object at 0x7fe13b93d670>]

Total running time of the script: (0 minutes 0.255 seconds)

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