Comprehensive stress analysis

Comprehensive stress analysis#

To provide a means for easy, comprehensive analysis of reconstructed droplet data, napari-stress provides the stress analysis toolbox. As example data, you can use the 4D example dataset of a reconstructed pointcloud (File > Open Sample > napari-stress > 4d Droplet pointcloud):

The stress toolbox#

Open the stress toolbox from the plugins menu (Tools > Measurement > Measure stresses on droplet pointcloud (n-STRESS)):

The settings require the following input:

  • Input pointcloud: Layer of a reconstructed droplet. Can be 3D or 4D.

  • Degree: Degree of the spherical harmonics expansion fitted to the pointcloud. The higher the degree, the better the fit. For mor details, see glossary.

  • Number of quadrature points: Number of points on which curvature will be evaluated.

    Note 1: High values (>1000) can lead to signiicant computational expense on first time run.

    Note 2: Using high-order spherical harmonics requires a specific minimal number of quadrature points. The number of quadrature points can be higher than this number, but not lower.

  • Interfacial surface tension [mN/m]: Surface tension in mN/m of the evaluated droplet.

Analyzing the output#

The toolbox creates a number of layers when finished, some with attached features that can be displayed using the feature visualization utilities from napari-stress. These include:

  • Result of fit spherical harmonics: Result of the spherical harmonics expansion. Contains the fit_residues feature which denotes the residual distances between the raw points and the input points.

  • Result of expand points on ellipsoid: Result of the least-squares ellipsoidal fit. Contains the fit_residues feature which denotes the residual distances between the raw points and the input points.

  • Result of least squares ellipsoid: Vectors layer that visualizes the major axes of the fitted ellipsoid.

  • Result of lebedev quadrature (droplet): Result of the lebedev quadrature point determination. Contains the mean_curvature (\(H_i\)), anisotropic_stress_cell (\(\sigma^A_C\)) and anisotropic_stress (\(\sigma^A\)) features.

  • Result of lebedev quadrature on ellipsoid: Result of evaluating the determined quadrature points on the corresponding locations on surface of the previously determined least-squares ellipsoid. Contains the feature anisotropic_stress_tissue

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