Commit c0c45a5e authored by jdurrant's avatar jdurrant
Browse files

Updates to demo.

parent c88ff901
import itertools as it
import scoria
import numpy as np
import Contact as con
# Defining the input files
PSF = "../scoria/sample-files/test_sim.psf"
DCD = "../scoria/sample-files/test_sim.dcd"
# Defining the two subsections to compare by a list of resid identifiers.
residA = range(1, 181)
residB = range(182, 297)
# Defining the output locations for the two subsections
Component_A_out = "./Component_A.pdb"
Component_B_out = "./Component_B.pdb"
# Load in a DCD/PSF trajectory and create a contact object within it.
print("Loading Molecule... ",)
MOL = scoria.Molecule()
MOL.load_MDAnalysis_into(PSF, DCD)
contacts = con.Contact(MOL)
print(" done")
# Create the subsections based on the resid ranges defined previously
print("Creating Component Molecules... ",)
contacts.set_subsections(residA, residB)
print(" done")
# Calculate the contact points between the two subsections.
print("Calculating contacts... ",)
print(" done")
#Save pdbs (with those occupancies) to two different files
print("Writing output files... ",)
contacts.print_subcomponents("Part_A.pdb", "Part_B.pdb")
print(" done")
import scoria
import numpy as np
class Contact():
A class for managing molecule subsections and calculating where they
make contact.
def __init__(self, molecule):
Initializes the Contact object.
:param scoria.molecule molecule: A molecule from which to calculate
contact points.
self.__molecule = molecule
self.__serials1 = None
self.__serials2 = None
self.__subsection_1 = None
self.__subsection_2 = None
self.__contacts = None
self.__contact_count = [np.array([]), np.array([])]
def set_subsections(self, resids_1, resids_2):
Given two sets on indexes, creates the subsection molecules.
:param list resids_1: A list of indexes of the atoms to include in subsection one.
:param list resids_2: a list of indexes of the atoms to include in subsection two.
self.__serials1 = self.__molecule.select_atoms({'resseq':resids_1})
self.__serials2 = self.__molecule.select_atoms({'resseq':resids_2})
self.__subsection_1 = self.__get_molecule_from_serials(self.__serials1)
self.__subsection_2 = self.__get_molecule_from_serials(self.__serials2)
def __clean_contact_counts(self):
Reinitalizes the __contact_counts to full 0.0 dictionaries.
if (self.__serials1 is None) or (self.__serials2 is None):
Should be faster with numpy arrays...
for index in range(0, len(self.__serials1)):
self.__contact_count[0][index] = float(0.0)
for index in range(0, len(self.__serials2)):
self.__contact_count[1][index] = float(0.0)
self.__contact_count[0] = np.zeros(self.__subsection_1.get_total_number_of_atoms())
self.__contact_count[1] = np.zeros(self.__subsection_2.get_total_number_of_atoms())
def __get_molecule_from_serials(self, serial_list):
Creates a subsection molecule from a given list of serials.
:param list serial_list: A list of atom serial numbers.
criteria = {'serial':serial_list}
#import pdb; pdb.set_trace()
selection = self.__molecule.select_atoms(criteria)
return self.__molecule.get_molecule_from_selection(selection, False)
def calculate_contact(self):
Given the two subsections, steps through the trajectory and counts
the number of contacts between the two subsections.
trajectory_length = self.__molecule.get_trajectory_frame_count()
for frame in range(0, trajectory_length):
self.__contacts = self.__subsection_1.select_close_atoms_from_different_molecules(self.__subsection_2, 3)
for i, atoms in enumerate(self.__contacts):
for atom in atoms:
self.__contact_count[i][atom] += 1.0
def __normalize_counts(self):
Normalizes the counts between 0.0 - 1.0 by dividing against the
global maximum.
Will be faster using numpy...
max_value = max(max(self.__contact_count[0].values()),
for count in self.__contact_count:
for key in count.keys():
count[key] = float(count[key]) / max_value
max_value = max(self.__contact_count[0].max(), self.__contact_count[1].max())
self.__contact_count[0] = self.__contact_count[0] / max_value
self.__contact_count[1] = self.__contact_count[1] / max_value
def __save_contacts_to_occupancy(self):
Inserts normalized count data into the subsection's occupancy field.
atom_information = [self.__subsection_1.get_atom_information(),
numpy will be faster...
for i, atom_info in enumerate(atom_information):
for key in self.__contact_count[i].keys():
atom_info['occupancy'][int(key)] = self.__contact_count[i][key]
atom_information[0]["occupancy"] = self.__contact_count[0]
atom_information[1]["occupancy"] = self.__contact_count[1]
# print len(atom_information[0]["occupancy"])
# print len()
# print len(atom_information[1]["occupancy"])
# print len(self.__contact_count[1])
# print atom_information[0]["occupancy"]
# print self.__serials1
# print self.__contact_count[0]
# import pdb; pdb.set_trace()
def print_subcomponents(self, section_one_name, section_two_name):
Prints the subcomponents to two PDB files.
:param str section_one_name: Filename for the first component
:param str section_two_name: Filename for the second componenet
self.__subsection_1.save_pdb(section_one_name, False)
self.__subsection_2.save_pdb(section_two_name, False)
......@@ -3,8 +3,7 @@ import numpy as np
# Load in a DCD/PSF trajectory.
print("Loading Molecule...")
mol = scoria.Molecule()
mol = scoria.Molecule(
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