Tutorial 2: Plotting data

In this tutorial (as well as all the following ones), we will reuse the data_1d and data_2d objects that we imported in the previous tutorial.

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The three stages of plotting

Plotting spectra using penguins is accomplished through three distinct steps:

1. Staging. In this step, a spectrum (i.e. the dataset returned by read()) is associated with an Axes which it will be plotted on.

   Individual spectrum-level options (e.g. the plot bounds and line colour) are specified here.

2. Construction. Here, all the spectra that were previously staged on a particular Axes are plotted.

   Plot-level options (e.g. horizontal / vertical separation between spectra, and axis labels) are specified here.

3. Display. The plot just needs to be displayed, and that’s what we do here.

We will now illustrate each of these steps using a basic example.

Note

If this is your first experience with matplotlib, it’s okay: these first few tutorials are designed to not require any explicit understanding of matplotlib.

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A minimal 1D example

Staging in general simply refers to calling the stage() method on the Dataset objects:

>>> data_1d    # we imported this in tutorial 1
Dataset1D('/Users/yongrenjie/penguins/tests/nmrdata/1/pdata/1')
>>> data_1d.stage()

This doesn’t produce any visible output (yet); what it has done is it has “registered” the spectrum above, so that it will be plotted in the future.

Construction uses the mkplot() function:

>>> pg.mkplot()
(<Figure size 600x400 with 1 Axes>, <AxesSubplot:xlabel='$\\rm ^{1}H$ (ppm)'>)

When we call mkplot(), we can see from the output that a Figure and an Axes (technically an AxesSubplot) have been set up for us. The x-axis label of the plot has automatically been set to a string which renders as \(\mathrm{^1H~(ppm)}\).

Finally, display the plot using show():

>>> pg.show()

Once you type this, the 1D plot above should be displayed in a new window. You can manipulate this plot, zoom in/out, or save it as a picture using the various buttons available.

As you may expect, penguins provides a number of options that can be passed in order to customise these plots. These will be described shortly in Tutorial 3: Customising 1D plots, but before that, a quick 2D example.

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A minimal 2D example

2D spectra are plotted in exactly the same way:

>>> data_2d   # we imported this earlier, too
Dataset2D('/Users/yongrenjie/penguins/tests/nmrdata/2/pdata/1')
>>> data_2d.stage()
>>> pg.mkplot()
(<Figure size 500x500 with 1 Axes>, <AxesSubplot:xlabel='$\\rm ^{1}H$ (ppm)', ylabel='$\\rm ^{1}H$ (ppm)'>)
>>> pg.show()

Notice that the Axes is set to a square shape: penguins does this automatically for 2D spectra. However, there are some aspects of this plot which are clearly undesirable. In Tutorial 5: Customising 2D plots we will see how to improve it.

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Axis labels and titles

Before moving on, let’s take a moment to look at one of the most basic ways of customising a plot. The x-axis label, y-axis label, and title can be specified as arguments to the mkplot() function during the construction stage. An example will likely be the clearest way of illustrating this. The following plot is exactly the same as the 2D plot above, just with several new arguments passed to mkplot().

>>> data_2d.stage()
>>> pg.mkplot(xlabel="My xlabel", ylabel="My ylabel", title="My title")
>>> pg.show()