Key features#

This page presents briefly DataLab key features.

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DataLab supports dark and light mode depending on your platform settings (this is handled by the guidata package, and may be overridden by setting the QT_COLOR_MODE environment variable to dark or light).#

Data visualization#

Signal

Image

Feature

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Screenshots (save, copy)

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Z-axis

Lin/log scales

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Data table editing

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Statistics on user-defined ROI

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Markers

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Aspect ratio (1:1, custom)

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50+ available colormaps (customizable)

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Intensity profiles (line, average, radial)

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Annotations

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Persistance of settings in workspace

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Distribute images on a grid

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Single or superimposed views

Data processing#

Signal

Image

Feature

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Process isolation for running computations

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Remote control from Jupyter, Spyder or any IDE

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Remote control from a third-party application

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Sum, average, difference, product…

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Operations with a constant

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Square root, power, logarithm, exponential…

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Average, standard deviation

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Derivative, integral

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ROI extraction, Swap X/Y axes

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Semi-automatic multi-peak detection

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Convolution, deconvolution

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Flat-field correction

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Flip, rotation, scaling…

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Intensity profiles (line, average, radial)

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Pixel binning

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Linear calibration

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Normalization, Clipping, Offset correction

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Reverse X-axis

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Replace X by other signal’s Y (calibration)

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X-Y mode

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Thresholding (manual, Otsu…)

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Gaussian filter, Wiener filter

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Moving average, moving median

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FFT, inverse FFT, Power/Phase/Magnitude spectrum, Power Spectral Density

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Interpolation, resampling

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Detrending

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Interactive fit: Gauss, Lorentz, Voigt, polynomial, CDF…

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Interactive multigaussian fit

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Frequency filters (low-pass, high-pass, band-pass, band-stop)

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Windowing (Hann, Hamming…)

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Butterworth filter

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Exposure correction (gamma, log…)

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Restauration (Total Variation, Bilateral…)

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Morphology (erosion, dilation…)

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Edges detection (Roberts, Sobel…)

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Analysis on custom ROI

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FWHM, FW @ 1/eΒ²

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Dynamic parameters (ENOB, SNR…), Sampling period/Rate

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Centroid (robust method w/r noise)

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Minimum enclosing circle center

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2D peak detection

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Contour detection

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Circle Hough transform

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Blob detection (OpenCV, Laplacian of Gaussian…)