bins¶

poreana.diffusion.bins(link, ax_area=[0.2, 0.8], is_norm=False)¶

This function calculates the axial (z-axis) diffusion coefficient as a function of the radial distance. This is done by sampling the mean square displacement for all molecules in a radial sub volume.

The mean square displacement is sampled in function poreana.sample.Sample._diffusion_bin().

For each bin, the msd is summed up, resulting into a msd slope for each bin. Thus, the axial diffusion coefficient can be calculated using

\[D_\text{axial}=\frac12\frac{\text{msd}_\text{axial}[i]-\text{msd}_\text{axial}[j]}{t_i-t_j}.\]

Note that the msd is evaluated in the area, where the slope is uniform, which means that the first twenty and last twenty percent should be neglected.

If is_norm is set to True, the radius will be normalized in respect to the effective radius which means, the last radius that has a Diffusion greater than zero is taken

\[r_\text{norm}=\frac{1}{r_\text{eff}}r.\]

Parameters:

linkstring: Link to hdf5 data file generated by the sample routine poreana.sample.Sample._diffusion_bin()
ax_arealist, optional: Bin area percentage to calculate the axial diffusion coefficient
intentstring, optional: Set to plot, for plotting or set to line to only return the lineplot, leave empty for nothing
is_normbool, optional: True to normalize x-axis

Returns:

diffusionlist: List of the slope of the non-normalized diffusion coefficient