corrLib

Autocorrelation functions

corrI(X, Y, I)	Compute pixel intensity spatial autocorrelation of an image.
corrS(X, Y, U, V)	Compute the spatial autocorrelations of a velocity field.
distance_corr(X, Y, C)	Convert 2d correlation matrix into 1d.
autocorr1d(x, t)	Compute the temporal autocorrelation of a 1-D signal.
vacf_piv(vstack, dt[, mode])	Compute averaged vacf from PIV data.

Density fluctuations

density_fluctuation(img8)	This is the first attempt to calculate density fluctuations in bacterial suspensions.
df2(imgstack[, size_min, step, method])	This is used for small scale test of temporal variation based density fluctuation analysis.
df2_(img_stack[, boxsize, size_min, step])	Compute number fluctuations of an image stack (3D np.array, frame*h*w)
plot_gnf(gnf_data)	Used for small scale test of gnf analysis.
local_df(img_folder[, seg_length, winsize, step])	Compute local density fluctuations of given image sequence in img_folder

Energy spectra

compute_energy_density(pivData[, d, MPP])	Compute kinetic energy density in k space from piv data.
compute_wavenumber_field(shape, d)	Compute the wave number field Kx and Ky, and magnitude field k.
energy_spectrum(pivData[, d])	Compute energy spectrum (E vs k) from pivData.

Flow field analysis

div_field(img, pivData, winsize, step)	Compute multiple divergence fields from PIV data and microscopy image.
divergence(pivData[, step, shape])	Compute divergence field based on piv data (x, y, u, v)
vorticity(pivData[, step, shape])	Compute vorticity field based on piv data (x, y, u, v)
convection(pivData, image, winsize[, step, ...])	Compute convection term u.grad(c) based on piv data (x, y, u, v) and image.

Misc

divide_windows(img[, windowsize, step])	Divide an image into windows with specified size and step.
divide_stack(img_stack[, winsize, step])	Divide image stack into several evenly spaced windows of stack.