Creates a signal1D from tabular data

This example creates a signal from tabular data, where the signal axis is given by an array of data values (the x column) and the tabular data are ordered in columns with 5 columns containing each 20 values and each column corresponding to a position in the navigation space (linescan).

import numpy as np
import hyperspy.api as hs

Create a set of tabular data:

x = np.linspace(0, 10, 20)
y = np.random.default_rng().random((20, 5))

Define the axes of the signal and then create the signal:

axes = [
    # length of the navigation axis
    dict(size=y.shape[1], scale=0.1, name="Position", units="nm"),
    # use values to define non-uniform axis for the signal axis
    dict(axis=x, name="Energy", units="eV"),
    ]

s = hs.signals.Signal1D(y.T, axes=axes)

Convert the non-uniform signal axis to a uniform axis, because non-uniform axes do not support all functionalities of HyperSpy. In this case, the error introduced during conversion to uniform scale is negligeable.

s.axes_manager.signal_axes[0].convert_to_uniform_axis()

Set title of the dataset and label for the data axis:

s.metadata.set_item("General.title", "Random test data")
s.metadata.set_item("Signal.quantity", "Intensity (counts)")

Plot the dataset:

s.plot()
# Choose the second figure as gallery thumbnail:
# sphinx_gallery_thumbnail_number = 2

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