def groups_from_folder(path, filename_templates, groupname_template="(*)", load=True):
"""Load a bunch of pdb files. Put them in groups with names taken from
the filename, name each object groupname.molecule. Return a dictionary
mapping group names to group objects.
ARGUMENTS:
Path in which the pdb files are stored
List of regular expressions that the filenames must match.
Template for the names of the groups. When creating a group name for a
file, the group name will be this template with each instance of '(*)'
replaced by a group from the regular expression, the first instance
replaced with the first group, etc. Defaults to '(*)'"""
dictionary = biodata.file_dict(path, filename_templates, groupname_template)
for key, value in dictionary.iteritems():
dictionary[key] = Group(key)
if load:
cmd.load(value, key + ".molecule")
cmd.disable(key)
return dictionary
import os
import sys
sys.path.append(os.getcwd()+'/calculator modules')
sys.path.append(os.getcwd()+'/pymol modules')
from useful import one_letter
from useful import CIDict
import csv
import warnings
import numpy as np
from Bio.PDB import PDBParser
from biodata import file_dict
import ezb
structure_files = file_dict('structures with 1qd5', ['aligned_(.*).pdb'])
parser = PDBParser()
with warnings.catch_warnings():
warnings.simplefilter('ignore')
structures = [(name, parser.get_structure(name, path)) \
for name, path in structure_files.items()]
structures = CIDict(structures)
with open('cored 1 selections with 1qd5.csv', 'rb') as f:
reader = csv.reader(f)
inclusive_selections = ezb.selections_by_resi(reader)
with open('beta_selections.csv', 'rb') as f:
reader = csv.reader(f)
beta_selections = ezb.selections_by_resi(reader)
