Computing features on Signals#

This section describes the signal computing features available in DataLab.

See also

Operations on Signals for more information on operations that can be performed on signals, or Processing Signals for information on processing features on signals.

../../_images/s_computing.png

Screenshot of the “Computing” menu.#

When the “Signal Panel” is selected, the menus and toolbars are updated to provide signal-related actions.

The “Computing” menu allows you to perform various computations on the selected signals, such as statistics, full width at half-maximum, or full width at 1/e².

Note

In DataLab vocabulary, a “computing” is a feature that computes a scalar result from a signal. This result is stored as metadata, and thus attached to signal. This is different from a “processing” which creates a new signal from an existing one.

Edit regions of interest#

Open a dialog box to setup multiple Region Of Interests (ROI). ROI are stored as metadata, and thus attached to signal.

ROI definition dialog is exactly the same as ROI extraction (see above): the ROI is defined by moving the position and adjusting the width of an horizontal range.

../../_images/s_roi_signal.png

A signal with an ROI.#

Remove regions of interest#

Remove all defined ROI for selected object(s).

Statistics#

Compute statistics on selected signal and show a summary table.

../../_images/s_stats.png

Example of statistical summary table: each row is associated to an ROI (the first row gives the statistics for the whole data).#

Histogram#

Compute histogram of selected signal and show it.

Parameters are:

Parameter

Description

Bins

Number of bins

Lower limit

Lower limit of the histogram

Upper limit

Upper limit of the histogram

../../_images/s_histogram.png

Example of histogram.#

Full width at half-maximum#

Compute the Full Width at Half-Maximum (FWHM) of selected signal, using one of the following methods:

Method

Description

Zero-crossing

Find the zero-crossings of the signal after having centered its amplitude around zero

Gauss

Fit data to a Gaussian model using least-square method

Lorentz

Fit data to a Lorentzian model using least-square method

Voigt

Fit data to a Voigt model using least-square method

../../_images/s_fwhm.png

The computed result is displayed as an annotated segment.#

Full width at 1/e²#

Fit data to a Gaussian model using least-square method. Then, compute the full width at 1/e².

Note

Computed scalar results are systematically stored as metadata. Metadata is attached to signal and serialized with it when exporting current session in a HDF5 file.

X values at min/max#

Compute the X values at minimum and maximum of selected signal.

Peak detection#

Create a new signal from semi-automatic peak detection of each selected signal.

../../_images/s_peak_detection.png

Peak detection dialog: threshold is adjustable by moving the horizontal marker, peaks are detected automatically (see vertical markers with labels indicating peak position)#

Sampling rate and period#

Compute the sampling rate and period of selected signal.

Warning

This feature assumes that the X values are regularly spaced.

Dynamic parameters#

Compute the following dynamic parameters on selected signal:

Parameter

Description

f

Frequency (sinusoidal fit)

ENOB

Effective Number Of Bits

SNR

Signal-to-Noise Ratio

SINAD

Signal-to-Noise And Distortion Ratio

THD

Total Harmonic Distortion

SFDR

Spurious-Free Dynamic Range

Bandwidth at -3 dB#

Assuming the signal is a filter response, compute the bandwidth at -3 dB by finding the frequency range where the signal is above -3 dB.

Warning

This feature assumes that the signal is a filter response, already expressed in dB.

Contrast#

Compute the contrast of selected signal.

The contrast is defined as the ratio of the difference and the sum of the maximum and minimum values:

\[\text{Contrast} = \dfrac{\text{max}(y) - \text{min}(y)}{\text{max}(y) + \text{min}(y)}\]

Note

This feature assumes that the signal is a profile from an image, where the contrast is meaningful. This justifies the optical definition of contrast.

Show results#

Show the results of all computations performed on the selected signals. This shows the same table as the one shown after having performed a computation.

Plot results#

Plot the results of computations performed on the selected signals, with user-defined X and Y axes (e.g. plot the FWHM as a function of the signal index).