Post Processing (pept.processing)#

The PEPT-oriented post-processing suite, including occupancy grid, vector velocity fields, etc.

This module contains fast, robust functions that operate on PEPT-like data and integrate with the pept library’s base classes.

Probability / Residence Distributions#

pept.processing.DynamicProbability2D(...[, ...])

Compute the 2D probability distribution of some tracer quantity (eg velocity in each cell).

pept.processing.DynamicProbability3D(...[, ...])

Compute the 3D probability distribution of some tracer quantity (eg velocity in each cell).

pept.processing.ResidenceDistribution2D(diameter)

Compute the 2D residence distribution of some tracer quantity (eg time spent in each cell).

pept.processing.ResidenceDistribution3D(diameter)

Compute the 3D residence distribution of some tracer quantity (eg time spent in each cell).

Vector Grids#

pept.processing.VectorField2D(diameter[, ...])

Compute a 2D vector field - effectively two 2D grids computed from two columns, for example X and Y velocities.

pept.processing.VectorGrid2D(xpixels, ypixels)

Object produced by VectorField2D storing 2 grids of voxels xpixels, ypixels, for example velocity vector fields / quiver plots.

pept.processing.VectorField3D(diameter[, ...])

Compute a 3D vector field - effectively three 3D grids computed from three columns, for example X, Y and Z velocities.

pept.processing.VectorGrid3D(xvoxels, ...)

Object produced by VectorField3D storing 3 grids of voxels xvoxels, yvoxels, zvoxels, for example velocity vector fields / quiver plots.

Mixing Quantification#

pept.processing.LaceyColors(p1, p2[, ax1, ...])

Compute Lacey-like mixing image, with streamlines passing through plane 1 being split into Red and Blue tracers, then evaluated into RGB pixels at a later point in plane 2.

pept.processing.LaceyColorsLinear(directory, ...)

Apply the LaceyColors mixing algorithm at num_divisions equidistant points between p1 and p2, saving images at each step in directory.

pept.processing.RelativeDeviations(p1, p2[, ...])

Compute a Lagrangian mixing measure - the changes in tracer distances to a point P1 as they pass through an "inlet" plane and another point P2 when reaching an "outlet" plane.

pept.processing.RelativeDeviationsLinear(...)

Apply the RelativeDeviations mixing algorithm at num_divisions equidistant points between p1 and p2, saving histogram images at each step in directory.

pept.processing.AutoCorrelation([lag, ...])

Compute autocorrelation of multiple measures (eg YZ velocities) as a function of a lagging variable (eg time).

pept.processing.SpatialProjections(...[, ...])

Project multiple tracer passes onto a moving 2D plane along a given direction between start and end coordinates, saving each frame in directory.