× ⚠️ You are reading the development version documentation.
Read here the documentation of the last stable release.

Mask a saturated region and transform an IR dataset

This example shows three common operations on a 2D infrared dataset: masking a saturated region, transposing the dataset, and converting axis units.

import spectrochempy as scp

Load a stacked IR dataset and convert the acquisition axis to hours.

dataset = scp.read_omnic("irdata/nh4y-activation.spg")
dataset.y -= dataset.y[0]
dataset.y.title = "time"

prefs = scp.preferences
prefs.figure.figsize = (7, 3.5)
prefs.colormap = "Dark2"
prefs.colorbar = True
_ = dataset.plot()

Mask the saturated region around 1100 cm^-1.

dataset[:, 1290.0:890.0] = scp.MASKED
_ = dataset.plot_stack()

The mask is then respected by subsequent operations such as reductions.

dataset.max()

3.8080601692199707 a.u.

Transposition exchanges the dataset axes while preserving the data and mask.

transposed = dataset.T
_ = transposed.plot()

Compatible unit conversions can be applied to coordinates in place.

dataset.y.ito("hours")
_ = dataset.plot()

This ends the example. Uncomment the next line to display the figures when running the script directly with Python.

# scp.show()