''' Plots histogram from a desc_merged.txt file. INPUT: file_path OUTPUT: *descriptorname.pdf ARGUMENTS: file_path USAGE: python pdb2descriptors.py file_path ''' #import stuff from enri import Enri import sys e = Enri() filepath = sys.argv[1] path, name, name_ext = e.path2names(filepath) data, headers = e.parse_desc_merged_txt(filepath) p1, p1headers = e.get_pocket2(data,headers) e.plot_hist_nolabel(p1, p1headers,path)
''' writes a descriptor file based on a certain selection kewords arguments output is written to outfiles directory INPUT: desc_merged.txt OUTPUT: *variable*.txt ARGUMENTS: input_path, pocket_name, variable_name USAGE: python select_descriptors.py path/to/train3.txt P_1 volume ''' #import stuff from enri import Enri import sys e = Enri() input_path = sys.argv[1] pocket = sys.argv[2] variable = sys.argv[3] e.select_adescriptor(input_path, pocket, variable)
''' Extracts pockets and descriptors from pdb files. Interfaces with DoGSiteScorer. Please make sure you have fully funtional DoGSiteScorer. INPUT: pdb_path OUTPUT: desc_merged.txt ARGUMENTS: pdb_path USAGE: python pdb2descriptors.py pdb_path ''' #import stuff import sys from enri import Enri e = Enri() e.pdb2desc_from_path(sys.argv[1]) e.name2firstcol_from_path(sys.argv[1]) e.merge_edt_from_path(sys.argv[1])
''' Predicts and writes an output file for top n predicted conformations. The output file is writen to the input directory INPUT: desc_merged.txt OUTPUT: *predicted*.txt ARGUMENTS: input_path, number of desired output (n), beta, ranker (wp or p) USAGE: python descriptors2predictions desc_merged.txt, n, beta,ranker ''' #import stuff from enri import Enri import sys e = Enri() input_path = sys.argv[1] n = int(sys.argv[2]) beta = float(sys.argv[3]) ranker = sys.argv[4] path, name, name_ext = e.path2names(input_path) outdir = path e.file2top_predicted2(input_path, n, beta, ranker, outdir)
