| Author: | Andrew Tarzia |
|---|
Inflate a balloon inside a cavity to get the pore and windows.
Built for molecules with a single, central cavity.
Please contact me with any questions (<andrew.tarzia@gmail.com>) or submit an issue!
Clone this repository and python setup.py develop in this directory, or using pip:
$ pip install PoreMapper
Very simple algorithm:
- Define a sphere of radius 0.1 Angstrom at the centroid of the host with equally placed beads on the sphere. The number of beads is defined by the
host.get_maximum_diameter(). Beads havesigma, which define their radius, and the resolution of the calculation. Hosts have atoms, which have radii defined by Streussel atomic radii [citation]. - Define steps of inflation (simply moving each bead in the blob along a vector emanating from the centroid) at even step size from 0.1 Angstrom to maximum host radii.
- For each step, check if a bead will collide with the host (based on distance-(bead radii + atom radii)). If it collides, it becomes immovable and a pore bead. Else, continue on.
A pore, and blob, have a series of analysis methods, including:
- Measures of pore shape based on the inertia tensor.
- Measure of pore radii (based on distance to host) and volume (based on its convex hull).
- Calculation of windows based on the blob (a Pore contains a Blob), where movable beads are clustered using
sklearn.cluster.MeanShift[this may change and be improved] to calculate the number and size of windows.
Two examples in examples/ take .xyz files and either run the step-wise inflation (inflate_blob) or the single-step inflation (get_inflated_blob).
The step-wise process will produce a plot and .xyz structures, monitoring the pore and blob, while the single-step will run the full calculation and produce just the final pore and blob.
I developed this code as a post doc in the Jelfs research group at Imperial College London (<http://www.jelfs-group.org/>, <https://github.com/JelfsMaterialsGroup>).
This project is licensed under the MIT license.