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Using LAMMPS for HiC Guido Polles <guido.polles@gmail.com> This is my module for performing Population Modeling from HiC data using LAMMPS. The lammps_hic module is based on ipyparallel. The UI -if ever- will be based on Tornado (as a web interface). Needs: numpy h5py cloudpickle ipyparallel tornado Sub-modules: 1. lammps Contains scripts to generate lammps inputs, call lammps and extract coordinates and info from the lammps output. The main function here is lammps.lammps_minimize(crd, radius, chrom, crd_id, tmp_files_dir='/dev/shm', log_dir='.', **kwargs) crd: numpy array of coordinates radius: float single radius # TODO: handle multiple radiuses chrom: list of chromosome string for each bead (not only the haploid) crd_id: a string to identify the run, used in filenames tmp_files_dir: directory where to store temporary lammps files (they are removed before function returns) log_dir: directory where to store log files in case of error **kwargs: dictionary with arguments for the minimization, default values are in lammps.ARG_DEFAULT returns a pair (crd, info): crd: numpy array of minimized coordinates info: dictionary with information about the run 2. actdist Contains the parallel version of the functions to compute the activation distances. actdist.get_actdists(parallel_client, crd_fname, probability_matrix, theta, last_ad, save_to=None) parallel_client: an instance to an ipyparallel.Client() crd_fname: the h5py file of the population probability_matrix: 2D HiC input matrix theta: the ptobability parameter last_ad: the last activation distance structure or an empty iterable. Activation distances are considered here as numpy recarrays with the following items ('i', int), ('j', int), ('pwish', float), ('actdist', float), ('pclean', float), ('pnow', float)] save_to: filename where to save a text file of the computed activation distances Sub-packages: 1. webui
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