def setUp(self):
     lennard_jones = """
                          float rsq = dot(r_ij, r_ij);
                          float rcut  = alpha_iso[0];
                          if (rsq <= rcut*rcut)
                             {{
                             float sigma = alpha_iso[1];
                             float eps   = alpha_iso[2];
                             float sigmasq = sigma*sigma;
                             float rsqinv = sigmasq / rsq;
                             float r6inv = rsqinv*rsqinv*rsqinv;
                             return 4.0f*eps*r6inv*(r6inv-1.0f);
                             }}
                          else
                             {{
                             return 0.0f;
                             }}
                          """
     self.dist = 2.0
     # distance between test particles
     snapshot = data.make_snapshot(N=2,
                                   box=data.boxdim(L=10, dimensions=3),
                                   particle_types=['A'])
     snapshot.particles.position[0, :] = (0, 0, 0)
     snapshot.particles.position[1, :] = (self.dist, 0, 0)
     system = init.read_snapshot(snapshot)
     mc = hpmc.integrate.sphere(seed=1, d=0)
     mc.shape_param.set('A', diameter=0)
     self.patch = jit.patch.user(mc=mc,
                                 r_cut=2.5,
                                 array_size=3,
                                 code=lennard_jones)
     self.logger = analyze.log(filename=None,
                               quantities=["hpmc_patch_energy"],
                               period=1)
    def test_head_to_tail_antiparallel(self):
        self.snapshot.particles.position[0, :] = (0, 0, 0)
        self.snapshot.particles.position[1, :] = (self.diameter, 0, 0)
        self.snapshot.particles.orientation[0, :] = (1, 0, 0, 0)
        self.snapshot.particles.orientation[1, :] = (0, 0, 1, 0)
        init.read_snapshot(self.snapshot)
        self.mc = hpmc.integrate.sphere(seed=10, a=0, d=0)
        self.mc.shape_param.set('A', diameter=self.diameter, orientable=True)
        self.patch = jit.patch.user(mc=self.mc,
                                    r_cut=self.r_cut,
                                    code=self.dipole_dipole)
        self.log = analyze.log(filename=None,
                               quantities=['hpmc_patch_energy'],
                               period=0,
                               overwrite=True)
        hoomd.run(0, quiet=True)
        self.assertEqual(self.log.query('hpmc_patch_energy'), self.lamb)

        # Disable patch with log = True and check logged energy is correct
        self.patch.disable(log=True)
        hoomd.run(2, quiet=True)
        self.assertEqual(self.log.query('hpmc_patch_energy'), self.lamb)

        # Re-enable patch and check energy is correct again
        self.patch.enable()
        hoomd.run(2, quiet=True)
        self.assertEqual(self.log.query('hpmc_patch_energy'), self.lamb)

        # Disable patch w/o log option and check energy is 0
        self.patch.disable()
        hoomd.run(2, quiet=True)
        self.assertEqual(self.log.query('hpmc_patch_energy'), 0)
    def setUp(self):
        # square well attraction on constituent spheres
        square_well = """float rsq = dot(r_ij, r_ij);
                              float r_cut = alpha_union[0];
                              if (rsq < r_cut*r_cut)
                                  return alpha_union[1];
                              else
                                  return 0.0f;
                           """

        # soft repulsion between centers of unions
        soft_repulsion = """float rsq = dot(r_ij, r_ij);
                                  float r_cut = alpha_iso[0];
                                  if (rsq < r_cut*r_cut)
                                    return alpha_iso[1];
                                  else
                                    return 0.0f;
                         """
        diameter = 1.0
        snapshot = data.make_snapshot(N=2,
                                      box=data.boxdim(L=10, dimensions=3),
                                      particle_types=['A'])
        snapshot.particles.position[0, :] = (0, 0, 0)
        snapshot.particles.position[1, :] = (diameter, 0, 0)
        system = init.read_snapshot(snapshot)
        mc = hpmc.integrate.sphere_union(d=0, a=0, seed=1)
        mc.shape_param.set('A',
                           diameters=[diameter] * 2,
                           centers=[(0, 0, -diameter / 2),
                                    (0, 0, diameter / 2)],
                           overlap=[0] * 2)
        self.patch = jit.patch.user_union(mc=mc, r_cut=2.5, array_size=2, r_cut_iso=2.5, array_size_iso=2, \
                                          code=square_well, code_iso=soft_repulsion)
        self.patch.set_params('A',
                              positions=[(0, 0, -diameter / 2),
                                         (0, 0, diameter / 2)],
                              typeids=[0, 0])
        self.logger = analyze.log(filename=None,
                                  quantities=["hpmc_patch_energy"],
                                  period=1)
Exemplo n.º 4
0
def simulate(traj_filename):

    with open(traj_filename, "r") as f:
        traj = json.load(f)

    seed = traj["seed"]
    len_chrom = traj["len_chrom"]
    Cent = traj["Cent"]
    p_ribo = traj["p_ribo"]
    R = traj["R"]
    micron = traj["micron"]
    data_folder = traj["data_folder"]

    # Diffusing elements
    N_diffu = traj["N_diffu"]
    cut_off_inte = traj["cut_off_inte"]
    p_inte = traj["p_inte"]
    dt = traj["dt"]
    p_origins = traj["p_origins"]

    # Yeast case
    spb = traj["spb"]
    nucleole = traj["nucleole"]
    telomere = traj["telomere"]
    microtubule_length = traj["microtubule_length"] * micron
    diameter_nuc = traj["diameter_nuc"] * micron
    special_start = traj["special_start"]
    Activ_Origins = traj["Activ_Origins"]
    visu = traj["visu"]
    dump_hic = traj["dump_hic"]

    # Scenari
    diff_alone = traj["diff_alone"]
    diff_bind_when_free = traj["diff_bind_when_free"]
    diff_bind_when_on_DNA = traj["diff_bind_when_on_DNA"]
    replicate_DNA = traj["replicate_DNA"]

    np.random.seed(seed)
    hoomd.context.initialize("--mode=cpu")

    if diff_alone:
        # Check
        assert (diff_bind_when_free is False)
        assert (diff_bind_when_on_DNA is False)

    # End of parameter
    ##########################################

    #########################################
    # Define polymer bonding and positions

    Np = len(len_chrom)
    assert (len(len_chrom) == len(Cent) == len(p_ribo))
    if special_start:
        Sim = create_init_conf_yeast(len_chrom=len_chrom,
                                     dist_centro=Cent,
                                     p_ribo=p_ribo,
                                     Radius=R,
                                     Mt=microtubule_length)
    else:
        Sim = []

    spbp = 0 if not spb else 1

    Total_particle = sum(len_chrom) + N_diffu * 2 + spbp
    list_nuc = [
        list(range(start, start + size)) if size != 0 else []
        for start, size in p_ribo
    ]
    # print(list_nuc)
    # exit()

    snapshot = data.make_snapshot(N=Total_particle,
                                  box=data.boxdim(L=2 * R),
                                  bond_types=['polymer'])

    spbb = Np if spb else 0

    if visu:
        spbb = 0

    bond_diffu = 0
    if diff_bind_when_free:
        bond_diffu = N_diffu

    snapshot.bonds.resize(sum(len_chrom) - len(len_chrom) + bond_diffu + spbb)

    bond_list = ['Mono_Mono', 'Diff_Diff', 'Mono_Diff']
    if spb:
        bond_list += ["Spb_Cen"]
    if nucleole:
        bond_list += ["Mono_Nuc", "Nuc_Nuc"]
    snapshot.bonds.types = bond_list

    plist = ['Mono', 'Ori', 'Diff', 'A_Ori', 'P_Ori', 'S_Diff', 'F_Diff']

    if spb:
        plist.append("Spb")
    if nucleole:
        plist += ['Nuc', 'A_Nuc', 'P_Nuc']

    if telomere:
        plist += ["Telo"]

    snapshot.particles.types = plist

    offset_bond = 0
    offset_particle = 0
    lPolymers = []

    ################################################
    # Polymer chains
    Cen_pos = []
    for i in range(Np):

        found_cen = False
        npp = len_chrom[i]  # Number of particles
        # Position of origin of replication
        pos_origins = p_origins[i]

        if Sim == []:
            initp = 2 * np.random.rand(3) - 1
        else:
            # print(i)
            initp = Sim.molecules[i].coords[0]

        for p in range(npp - 1):
            inuc = 0
            if nucleole:
                if p in list_nuc[i]:
                    inuc += 1
                if p + 1 in list_nuc[i]:
                    inuc += 1

            snapshot.bonds.group[offset_bond + p] = [
                offset_particle + p, offset_particle + p + 1
            ]
            if inuc == 0:
                snapshot.bonds.typeid[offset_bond + p] = bond_list.index(
                    'Mono_Mono')  # polymer_A
            if inuc == 1:
                snapshot.bonds.typeid[offset_bond + p] = bond_list.index(
                    'Mono_Nuc')  # polymer_A
            if inuc == 2:
                snapshot.bonds.typeid[offset_bond + p] = bond_list.index(
                    'Nuc_Nuc')  # polymer_A

        offset_bond += npp - 1

        for p in range(npp):
            # print(offset_bond, offset_bond + p)
            if Sim == []:
                new = 2 * (2 * np.random.rand(3) - 1)
                while linalg.norm(initp + new) > R - 1:
                    new = 2 * (2 * np.random.rand(3) - 1)

                initp += new
            else:
                initp = Sim.molecules[i].coords[p]

            snapshot.particles.position[offset_particle + p] = initp

            if p in pos_origins:
                snapshot.particles.typeid[offset_particle + p] = plist.index(
                    'Ori')  # Ori
            else:
                snapshot.particles.typeid[offset_particle + p] = plist.index(
                    'Mono')  # A

            if spb and p == Cent[i]:
                Cen_pos.append(offset_particle + p)

                found_cen = True

            if nucleole and p in list_nuc[i]:
                snapshot.particles.typeid[offset_particle +
                                          p] = plist.index('Nuc')

            if telomere and (p == 0 or p == npp - 1):
                snapshot.particles.typeid[offset_particle +
                                          p] = plist.index('Telo')

        lPolymers.append(
            Polymer(i, offset_particle, offset_particle + npp - 1,
                    [po + offset_particle for po in pos_origins]))
        offset_particle += npp

        assert (found_cen == spb)

    phic = 0
    if dump_hic:
        phic = 0 + offset_particle - 1
    ###################################################
    # SPD
    if spb:
        tag_spb = 0 + offset_particle
        # print(tag_spb)
        # print(snapshot.particles[offset_particle])
        snapshot.particles.position[offset_particle] = [-R + 0.1, 0, 0]
        snapshot.particles.typeid[offset_particle] = plist.index('Spb')
        offset_particle += 1

        if not visu:
            for i in range(Np):
                # print(offset_particle - 1, Cen_pos[i])
                snapshot.bonds.group[offset_bond] = [
                    offset_particle - 1, Cen_pos[i]
                ]
                snapshot.bonds.typeid[offset_bond] = bond_list.index(
                    'Spb_Cen')  # polymer_A

                offset_bond += 1

    ############################################################
    # Diffusing elements
    # Defining useful classes

    # Defining particles and bonds for the simulation

    for i in range(N_diffu):
        npp = 2  # Number of particles

        initp = (R - 2) * (2 * np.random.rand(3) - 1)
        while linalg.norm(initp) > R - 1:
            initp = (R - 2) * (2 * np.random.rand(3) - 1)
        if diff_bind_when_free:
            for p in range(npp - 1):
                snapshot.bonds.group[offset_bond + p] = [
                    offset_particle + p, offset_particle + p + 1
                ]
                snapshot.bonds.typeid[offset_bond + p] = bond_list.index(
                    'Diff_Diff')  # Diff_Diff
            offset_bond += npp - 1

        for p in range(npp):
            # print(offset_bond, offset_bond + p)
            if diff_bind_when_free:
                new = 2 * (2 * np.random.rand(3) - 1)
                while linalg.norm(initp + new) > R - 1:
                    new = 2 * (2 * np.random.rand(3) - 1)
                    # print(initp,new,R,linalg.norm(initp + new))
                    # exit()
                initp += new
            else:
                initp = (R - 1) * (2 * np.random.rand(3) - 1)

            snapshot.particles.position[offset_particle + p] = initp
            snapshot.particles.typeid[offset_particle + p] = plist.index(
                "Diff")  # Diffu

        offset_particle += npp

    # Load the configuration

    for i, p in enumerate(snapshot.bonds.group):
        if p[0] == p[1]:
            print(i, p)

    system = init.read_snapshot(snapshot)

    for i, p in enumerate(system.particles):
        # print(p)
        # exit()
        assert p.tag == i

    for i, b in enumerate(system.bonds):
        if b.a == b.b:
            print(b.a, b.b)

            raise
        # print(p)
        # exit()
        assert b.tag == i
    ###############################################

    ###############################################
    # Defining force field:
    harmonic = md.bond.harmonic()
    harmonic.bond_coeff.set(bond_list, k=330.0, r0=1)

    harmonic.bond_coeff.set('Mono_Diff', k=10.0, r0=1)

    if spb:
        harmonic.bond_coeff.set('Spb_Cen', k=1000.0, r0=microtubule_length)

    if nucleole:
        harmonic.bond_coeff.set('Nuc_Nuc', k=330, r0=diameter_nuc)
        harmonic.bond_coeff.set('Mono_Nuc',
                                k=330,
                                r0=diameter_nuc / 2. + 1. / 2)

    nl = md.nlist.tree(r_buff=0.4, check_period=1)

    # Potential for warmup
    gauss = md.pair.gauss(r_cut=3.0, nlist=nl)

    gauss.pair_coeff.set(plist, plist, epsilon=1.0, sigma=1.0)

    if nucleole:
        for ip1, p1 in enumerate(plist):
            for p2 in plist[ip1:]:
                inuc = 0
                if "Nuc" in p1:
                    inuc += 1
                if "Nuc" in p2:
                    inuc += 1
                if inuc == 1:
                    gauss.pair_coeff.set(p1,
                                         p2,
                                         epsilon=.5,
                                         sigma=0.5 + diameter_nuc / 2.,
                                         r_cut=(0.5 + diameter_nuc / 2.) * 3)
                if inuc == 2:
                    gauss.pair_coeff.set(p1,
                                         p2,
                                         epsilon=1.0,
                                         sigma=diameter_nuc,
                                         r_cut=3 * diameter_nuc)
    # gauss.pair_coeff.set('A', 'A', epsilon=1.0, sigma=1.0)
    # gauss.pair_coeff.set('A', 'A', epsilon=1.0, sigma=1.0)

    # Spherical confinement
    sphere = md.wall.group()
    sphere.add_sphere(r=R, origin=(0.0, 0.0, 0.0), inside=True)

    wall_force_slj = md.wall.slj(sphere, r_cut=3.0)
    wall_force_slj.force_coeff.set(plist, epsilon=1.0, sigma=1.0, r_cut=1.12)

    if nucleole:
        wall_force_slj.force_coeff.set('Nuc',
                                       epsilon=1.0,
                                       sigma=diameter_nuc,
                                       r_cut=diameter_nuc * 1.12)
    if telomere:
        wall_force_slj.force_coeff.set(plist, epsilon=2.0, sigma=1.5, r_cut=3)

    # Group;
    all_beads = group.all()
    if spb:
        Spb_g = group.tag_list(name="Spb", tags=[tag_spb])
        pspb = [p.position for p in Spb_g]
        print(pspb)

        all_move = group.difference(name="move", a=all_beads, b=Spb_g)
    else:
        all_move = all_beads
    # Log
    logger = analyze.log(filename=data_folder + 'mylog.log',
                         period=1000,
                         quantities=[
                             'temperature', 'potential_energy',
                             'kinetic_energy', 'volume', 'pressure'
                         ],
                         overwrite=True)

    # Warmup
    converged = False
    dt = 0.005
    while not converged and not visu:
        try:

            method = md.integrate.mode_minimize_fire(group=all_move, dt=dt)
            while not (method.has_converged()):

                if spb:
                    pspb = [p.position for p in Spb_g]
                    """
                    print(pspb)
                    for cen in Cen_pos:
                        cent_tmp = system.particles[cen]
                        print(cent_tmp.position)
                        print(linalg.norm(np.array(pspb[0])-np.array(cent_tmp.position)))
                        print(R * microtubule_length)
                    """
                # exit()
                hoomd.run(100)
            converged = True
        except:
            converged = False
            dt /= 2.
            print(dt)
            # Restore positions
            for ip, p in enumerate(snapshot.particles.position):

                system.particles[ip].position = p
    """
    gauss.disable()

    slj=md.pair.slj(r_cut=2, nlist=nl)
    slj.pair_coeff.set(plist,plist,sigma=1,epsilon=1,r_cut=1.12)
    print("Second minimizing")
    method=md.integrate.mode_minimize_fire(group=all_beads,dt=0.05)
    while not(method.has_converged()):
       hoomd.run(100)
    """
    # hoomd.run(1000000)
    # method.disable()

    # Dumping

    if visu:
        xml = deprecated.dump.xml(filename=data_folder + "atoms.hoomdxml",
                                  period=None,
                                  group=all_beads,
                                  vis=True)
        exit()
    # gsd = dump.gsd(filename=data_folder + "atoms.gsd",period=None,group=all_beads)
    dcd = dump.dcd(filename=data_folder + 'poly.dcd',
                   period=100,
                   overwrite=True)

    # Dynamics

    t0 = time.time()
    md.integrate.mode_standard(dt=0.01)
    method = md.integrate.langevin(group=all_move, kT=1, seed=seed)
    snp = system  # .take_snapshot()

    def Change_type(typep, particle_list, snp, msg=""):
        # print(particle_list)
        for p in particle_list:
            snp.particles[p].type = typep
        if particle_list != [] and msg != "":
            print(msg)

    def Bind(typeb, bondlist, snp):
        btags = []
        for b1, b2 in bondlist:
            btags.append(snp.bonds.add(typeb, b1, b2))
        return btags

    def Release(btags, snp):
        for bt in btags:
            snp.bonds.remove(bt)

    def AddParticle(position, type):
        snp.particles.add(type)
        snp.particles[-1].position = position

    def Shift(bonds, snp):
        for tag, new in bonds:
            b = snp.bonds.get(tag)
            btype = "" + b.type
            fork = b.b + 0
            snp.bonds.remove(tag)

            # print(b.type)
            snp.bonds.add(btype, new, fork)
            # print(new,b)
            # print(dir(snp.bonds))
            # b.a = new

    group_diffu = group.type(name="Diff", type='Diff')

    if Activ_Origins != []:
        group_origin = group.type(name="Activ_Ori", type=Activ_Origins[0])
        if len(Activ_Origins) > 1:
            for t in Activ_Origins[1:]:
                group_origin = group.union(name="Activ_origin",
                                           a=group_origin,
                                           b=group.type(name="tmp", type=t))

    r_hic = []
    if dump_hic:
        group_hic = group.tags(name="hic", tag_min=0, tag_max=phic)
    # nl.tune(warmup=1,steps=1000)

    for i in range(100):

        # Chek that the microtubule length is correct
        if spb:
            for cen in Cen_pos:
                cent_tmp = system.particles[cen]
                # print(cent_tmp.position)
                d = linalg.norm(
                    np.array(pspb[0]) - np.array(cent_tmp.position))
                if d > 2 * microtubule_length:
                    print("MT too long", d)
                    exit()

        # Dump the Hi-Cs

        # system.restore_snapshot(snp)
        hoomd.run(1000)

        if dump_hic:
            ph = np.array([p.position for p in group_hic])

            D = cdist(ph, ph)
            D[D < 2] = 1
            D[D >= 2] = 0
            np.fill_diagonal(D, 0)
            if r_hic != []:
                r_hic += D
            else:
                r_hic = D
            np.save(data_folder + "/hic", r_hic)

        # snp = system.take_snapshot()

        # update the position of the monomer by updating bonds

        for iP, P in enumerate(lPolymers):
            verbose = False
            # if iP == 9:
            #    verbose = True
            bind_diff, diff_diff, shifted_bonds, \
                passivated_origin, to_release, alone = P.increment_time(
                    1, verbose)

            Change_type('P_Ori', passivated_origin, snp,
                        msg="")  # Passivated origin

            if not diff_alone:
                Shift(shifted_bonds, snp)
                # Bond tags to release (Alone particle)
                Release(to_release, snp)

                if diff_bind_when_free:
                    # Pair of diffu to attach
                    Bind("Diff_Diff", bind_diff, snp)
                    # We cannot use the single diff anymore
                    Change_type("S_Diff", alone, snp)
                    # Change type for pair of diff diff
                    Change_type("Diff", diff_diff, snp)

        group_diffu.force_update()
        group_origin.force_update()
        # Update Type because of (Ori to passivated)

        # Update group

        # Find new interacting particles

        # First check if Dimer are close from one origin

        p_diffu = np.array([p.position for p in group_diffu])
        tag_diffu = [p.tag for p in group_diffu]

        p_origin = np.array([p.position for p in group_origin])
        tag_origin = [p.tag for p in group_origin]

        if tag_diffu != [] and tag_origin != []:
            distances = cdist(p_diffu, p_origin)
            print(distances.shape)
            # Reorder the distances with the dimer tags
            Indexes = []
            PTags = []
            # t0 = time.time()
            Btags = []
            # Groups Diff-Diff by bond to compute the distances

            if diff_bind_when_free:
                for b in system.bonds:
                    if b.type == 'Diff_Diff' and system.particles[
                            b.a].type == 'Diff':
                        Indexes.append(tag_diffu.index(b.a))
                        Indexes.append(tag_diffu.index(b.b))
                        Btags.append(b.tag)
                        PTags.append([b.a, b.b])

                # print(time.time() -t0)

                d2 = distances[Indexes][::2] / 2 + distances[Indexes][1::2] / 2
            else:
                n_diffu = len(tag_diffu)
                Indexes = list(range(n_diffu))
                Btags = [None] * n_diffu
                PTags = [[t] for t in tag_diffu]
                d2 = distances[Indexes]

            activated = []
            for iD, (btag, ptags) in enumerate(zip(Btags, PTags)):
                # print(d2.shape)
                # print(d2[iD])
                for iorigin, di in enumerate(d2[iD]):
                    if iorigin in activated:
                        # Needed because we don't want an origin to be activated
                        # twice
                        continue
                    if di > cut_off_inte:
                        continue
                    if np.random.rand() > p_inte:
                        continue

                    for P in lPolymers:
                        if not P.has_origin(tag_origin[iorigin]):
                            continue

                        if diff_bind_when_free and \
                           not diff_bind_when_on_DNA:
                            Release([btag], snp)  # Break the dimer
                            btag = None  # We need btag only in the case where they stays attached

                        if not diff_alone:
                            # Or attached separatly or already bound:

                            if diff_bind_when_free:

                                # We are sure they are two and we can
                                # start
                                Change_type('F_Diff', ptags,
                                            snp)  # Diffusive element attached
                                particular_origin = tag_origin[iorigin]
                                new_btags = Bind(
                                    "Mono_Diff",
                                    [[particular_origin, ptags[0]],
                                     [particular_origin, ptags[1]]], snp)
                                Change_type('A_Ori', [particular_origin], snp)
                                activated.append(iorigin)
                                P.add_fork(ptags, particular_origin, new_btags,
                                           btag)

                            else:
                                Change_type('F_Diff', ptags,
                                            snp)  # Diffusive element attached
                                particular_origin = tag_origin[iorigin]
                                new_btags = Bind(
                                    "Mono_Diff",
                                    [[particular_origin, ptags[0]]], snp)
                                start = P.attach_one_diff(
                                    ptags[0], particular_origin, new_btags[0])

                                if start:
                                    # get particles involves
                                    p1, p2 = P.get_diff_at_origin(
                                        particular_origin)
                                    if diff_bind_when_on_DNA:
                                        btag = Bind("Diff_Diff",
                                                    [[p1[0], p2[0]]], snp)[0]

                                    Change_type('A_Ori', [particular_origin],
                                                snp)
                                    P.add_fork([p1[0], p2[0]],
                                               particular_origin,
                                               [p1[1], p2[1]], btag)

                        else:
                            # start when touched and release
                            particular_origin = tag_origin[iorigin]
                            activated.append(iorigin)
                            Change_type('A_Ori', [particular_origin], snp)
                            P.add_fork([None, None], particular_origin,
                                       [None, None], None)

                        break
                    # If we arrive there it means that one interaction has beeen
                    # found
                    break
        # t0 = time.time()
        with open(data_folder + "polymer_timing.dat", "wb") as f:
            cPickle.dump(lPolymers, f)
        # print(time.time() -t0)
        # Then if it is the case attach them according to p law to the origin

    print(gauss.get_energy(all_beads), wall_force_slj.get_energy(all_beads))
    print(time.time() - t0)
Exemplo n.º 5
0
def simulate(traj):

    seed = traj["seed"]

    micron = traj["micron"]
    data_folder = traj["data_folder"]

    # Diffusing elements
    cut_off_inte = traj["cut_off_inte"]
    p_inte = traj["p_inte"]
    p_off = traj["p_off"]
    sim_dt = traj["sim_dt"]
    fork_speed = traj["fork_speed"]
    dt_speed = traj["dt_speed"]
    dscale = traj["dscale"]
    # Yeast case
    spb = traj["spb"]
    assert (type(spb) == bool)

    microtubule_length = traj["microtubule_length"] * micron
    Activ_Origins = traj["Activ_Origins"]
    visu = traj["visu"]
    dump_hic = traj["dump_hic"]
    two_types = traj.get("two_types", False)
    r_diffu = traj.get("diameter_diffu", 1) / 2

    # Scenari
    diff_alone = traj["diff_alone"]
    diff_bind_when_free = traj["diff_bind_when_free"]
    diff_bind_when_on_DNA = traj["diff_bind_when_on_DNA"]
    assert (type(diff_alone) == bool)
    assert (type(diff_bind_when_on_DNA) == bool)
    assert (type(diff_bind_when_free) == bool)

    # Simulation parameters
    n_steps = traj["n_steps"]
    length_steps = traj["length_steps"]
    benchmark = traj["benchmark"]
    warmup = traj["warmup"]
    dcd_period = traj["dcd_period"]
    dump_inte = traj.get("dump_inte", False)

    np.random.seed(seed)
    hoomd.context.initialize()  # "--mode=cpu ")

    ramp_type = traj.get("ramp_type", "exp")
    ramp = traj.get("ramp_time", 3)

    if diff_alone:
        # Check
        assert (diff_bind_when_free is False)
        assert (diff_bind_when_on_DNA is False)

    # End of parameter
    ##########################################

    #########################################
    # Define polymer bonding and positions

    snapshot, phic, tag_spb, bond_list, plist, Cen_pos, lPolymers, list_ori, p_tag_list = \
        create_initial_configuration(traj)
    system = init.read_snapshot(snapshot)

    for i, p in enumerate(system.particles):
        # print(p)
        # exit()
        assert p.tag == i

    for i, b in enumerate(system.bonds):
        if b.a == b.b:
            print(b.a, b.b)

            raise
        assert b.tag == i
    ###############################################

    ###############################################
    # Defining force field:
    all_beads, all_move, Spb_g, nl = force_field(traj,
                                                 bond_list=bond_list,
                                                 plist=plist,
                                                 tag_spb=tag_spb,
                                                 two_types=two_types)

    # Log
    if not visu:
        logger = analyze.log(filename=data_folder + 'mylog.log',
                             period=1000,
                             quantities=[
                                 'temperature', 'potential_energy',
                                 'bond_harmonic_energy',
                                 'external_wall_lj_energy',
                                 "pair_table_energy", 'kinetic_energy',
                                 'volume', 'pressure'
                             ],
                             overwrite=True)

    # Warmup

    minimize(traj, all_move, system, snapshot, Spb_g, Cen_pos,
             microtubule_length)

    # Dumping

    if visu:
        xml = deprecated.dump.xml(filename=data_folder + "atoms.hoomdxml",
                                  period=None,
                                  group=all_beads,
                                  vis=True)
        # xml.disable()
        return
    # gsd = dump.gsd(filename=data_folder + "atoms.gsd",period=None,group=all_beads)

    # Dynamics

    def Change_type(typep, particle_list, snp, msg=""):
        # print(particle_list)
        for p in particle_list:
            if "Ori" in typep:
                # Remove it from the list activated
                # list_ori.remove(p)
                pass
            else:
                snp.particles[p].type = typep
        if particle_list != [] and msg != "":
            print(msg)

    def Bind(typeb, bondlist, snp):
        btags = []
        for b1, b2 in bondlist:
            btags.append(snp.bonds.add(typeb, b1, b2))
        return btags

    def Release(btags, snp):
        for bt in btags:
            snp.bonds.remove(bt)

    def AddParticle(position, type):
        snp.particles.add(type)
        snp.particles[-1].position = position

    def Shift(bonds, snp):
        for tag, new in bonds:
            b = snp.bonds.get(tag)
            btype = "" + b.type
            fork = b.b + 0
            snp.bonds.remove(tag)

            # print(b.type)
            snp.bonds.add(btype, new, fork)
            # print(new,b)
            # print(dir(snp.bonds))
            # b.a = new

    snp = system  # .take_snapshot()

    if ramp_type == "exp":
        for couple in p_tag_list:
            Change_type("I_Diff", couple, snp)

    group_diffu = group.type(name="Diff", type='Diff')

    # nl.tune(warmup=1,steps=1000)

    # Small warmup

    t0 = time.time()
    md.integrate.mode_standard(dt=sim_dt)
    method = md.integrate.langevin(group=all_move,
                                   kT=1,
                                   seed=seed,
                                   dscale=False)

    print(plist)
    for p in ['Diff', 'S_Diff', 'F_Diff', "I_Diff"]:
        print(p, dscale * r_diffu)
        method.set_gamma(p, dscale * r_diffu)
    for p in ['Mono', 'Ori']:
        method.set_gamma(p, dscale)
    if two_types:
        method.set_gamma(p, dscale)
    # exit()

    if benchmark:
        print(nl.tune(warmup=4000, r_min=0.3, r_max=0.8, jumps=5, steps=5000))
        return
    """

    md.integrate.mode_standard(dt=sim_dt / 4)
    hoomd.run(100)
    md.integrate.mode_standard(dt=sim_dt / 2)
    hoomd.run(100)
    md.integrate.mode_standard(dt=sim_dt)
    """
    if warmup != 0:
        hoomd.run(warmup)

    dcd = dump.dcd(filename=data_folder + 'poly.dcd',
                   period=dcd_period,
                   overwrite=True)

    r_hic = []
    # if dump_hic:
    group_hic = group.tags(name="hic", tag_min=0, tag_max=phic)

    if dump_inte:
        r_inte = []

    Ndiff_libre_t = []

    N_diffu = traj["N_diffu"]

    offset_diff = np.min(p_tag_list)
    print(offset_diff)

    record_diffusing = [Diffusing(d) for d in np.arange(N_diffu * 2)]

    global timeit
    timeit = True
    global t0
    t0 = time.time()

    def Timeit(where=""):
        global timeit
        global t0
        if timeit:
            if where == "":
                print(time.time() - t0)
            else:
                print(where, time.time() - t0)
            t0 = time.time()

    previous_actifs = 0
    for i in range(n_steps):

        # Chek that the microtubule length is correct
        if spb:
            for cen in Cen_pos:
                cent_tmp = system.particles[cen]
                # print(cent_tmp.position)
                pspb = [p.position for p in Spb_g]
                d = linalg.norm(
                    np.array(pspb[0]) - np.array(cent_tmp.position))
                if d > 2 * microtubule_length:
                    print("MT too long", d)
                    exit()

        # Dump the Hi-Cs
        Timeit()
        # system.restore_snapshot(snp)

        N_actifs = int(len(p_tag_list) * (1 - np.exp(-i * dt_speed / ramp)))
        print(previous_actifs, N_actifs)
        for couple in p_tag_list[previous_actifs:N_actifs]:
            Change_type("Diff", couple, snp)
            print("Activated", couple)
        previous_actifs = N_actifs

        hoomd.run(length_steps // 2, profile=False)
        Timeit("After first half")

        if dump_hic and i % traj.get("hic_period", 1) == 0:
            ph = np.array([p.position for p in group_hic])

            D = cdist(ph, ph)
            D[D < 2] = 1
            D[D >= 2] = 0
            np.fill_diagonal(D, 0)
            if r_hic != []:
                r_hic += D
            else:
                r_hic = D
            if i % 32 == 0:
                np.save(data_folder + "/hic", r_hic)

        # snp = system.take_snapshot()

        # update the position of the monomer by updating bonds
        ended = 0
        for iP, P in enumerate(lPolymers):
            verbose = False
            # if iP == 9:
            #    verbose = True
            bind_diff, diff_diff, shifted_bonds, \
                passivated_origin, to_release, alone = P.increment_time(
                    dt_speed, verbose)

            ###################################################################
            # Only to keep track of the diffusing elements
            for diff1, diff2 in bind_diff:

                record_diffusing[diff1 - offset_diff].end_replication(
                    i * dt_speed, pos=snp.particles[diff1].position)
                record_diffusing[diff2 - offset_diff].end_replication(
                    i * dt_speed, pos=snp.particles[diff2].position)

            for diff in alone:
                if record_diffusing[diff - offset_diff].bound:
                    record_diffusing[diff - offset_diff].end_bound(
                        i * dt_speed, pos=snp.particles[diff].position)
                elif record_diffusing[diff - offset_diff].replicating:
                    record_diffusing[diff - offset_diff].end_replication(
                        i * dt_speed, pos=snp.particles[diff].position)
                else:
                    print(diff, record_diffusing[diff - offset_diff].free)
                    raise

            ###################################################################

            ###################################################################
            # take care of the bondings

            for ori in passivated_origin:
                list_ori.remove(ori)

            if not diff_alone:
                Shift(shifted_bonds, snp)
                # Bond tags to release (Alone particle)
                Release(to_release, snp)

                if diff_bind_when_free:
                    # Pair of diffu to attach
                    Bind("Diff_Diff", bind_diff, snp)
                    # We cannot use the single diff anymore
                    Change_type("S_Diff", alone, snp)
                    # Change type for pair of diff diff
                    Change_type("Diff", diff_diff, snp)

            # check for releasing alone binded elements

            for ori_not_started in P.get_free_origins():
                diff = P.get_diff_at_origin(ori_not_started)
                if diff != []:
                    if np.random.rand() > p_off:
                        continue
                    ptag, bond_tag = diff[0]
                    P.dettach_one_diff(ptag, ori_not_started)
                    Release([bond_tag], snp)
                    Change_type("Diff", [ptag], snp)

            if P.modules == []:
                ended += 1

        Timeit("AFter update")
        hoomd.run(length_steps // 2, profile=True)
        Timeit("AFter second half")

        group_diffu.force_update()

        p_diffu = np.array([p.position for p in group_diffu])
        tag_diffu = [p.tag for p in group_diffu]

        p_origin = np.array([snp.particles[ori].position for ori in list_ori])

        Ndiff_libre_t.append(len(tag_diffu))

        if not (tag_diffu != [] and list_ori != []):
            print("No interactions")

        # Generate the measures we are interested in
        # Matrice interaction DNA / particules
        if dump_inte and i % traj.get("inte_period",
                                      1) == 0 and len(group_diffu) != 0:
            ph = np.array([p.position for p in group_hic])
            pi = np.array([p.position for p in group_diffu])

            print(ph.shape, pi.shape)
            D = cdist(ph, pi)
            D[D < 2] = 0.5 + r_diffu
            D[D >= 2] = 0
            # np.fill_diagonal(D, 0)
            if r_inte != []:
                r_inte += D
            else:
                r_inte = D
            if i % 32 == 0:
                np.save(data_folder + "/inte", r_inte)

        start_replication = False
        if tag_diffu != [] and list_ori != [] and start_replication:
            distances = cdist(p_diffu, p_origin)
            print(distances.shape)
            # Reorder the distances with the dimer tags
            Indexes = []
            PTags = []
            # t0 = time.time()
            Btags = []
            # Groups Diff-Diff by bond to compute the distances

            if diff_bind_when_free:
                for b in system.bonds:
                    if b.type == 'Diff_Diff' and system.particles[
                            b.a].type == 'Diff':
                        if b.a in tag_diffu:
                            Indexes.append(tag_diffu.index(b.a))
                            Indexes.append(tag_diffu.index(b.b))
                            Btags.append(b.tag)
                            PTags.append([b.a, b.b])

                # print(time.time() -t0)

                d2 = distances[Indexes][::2] / 2 + distances[Indexes][1::2] / 2
            else:
                n_diffu = len(tag_diffu)
                Indexes = list(range(n_diffu))
                Btags = [None] * n_diffu
                PTags = [[t] for t in tag_diffu]
                d2 = distances[Indexes]

            activated = []
            for iD, (btag, ptags) in enumerate(zip(Btags, PTags)):
                # print(d2.shape)
                # print(d2[iD])
                lo = list(range(len(d2[iD])))
                np.random.shuffle(lo)
                for iorigin in lo:
                    di = d2[iD][iorigin]
                    if iorigin in activated:
                        # Needed because we don't want an origin to be activated
                        # twice
                        continue
                    if di > cut_off_inte:
                        continue

                    for P in lPolymers:
                        if not P.has_origin(list_ori[iorigin]):
                            continue

                        if np.random.rand(
                        ) > p_inte * P.o_strength[list_ori[iorigin]]:
                            continue

                        if diff_bind_when_free and \
                           not diff_bind_when_on_DNA:
                            Release([btag], snp)  # Break the dimer
                            btag = None  # We need btag only in the case where they stays attached

                        if not diff_alone:
                            # Or attached separatly or already bound:

                            if diff_bind_when_free:

                                # We are sure they are two and we can
                                # start
                                Change_type('F_Diff', ptags,
                                            snp)  # Diffusive element attached
                                particular_origin = list_ori[iorigin]
                                new_btags = Bind(
                                    "Mono_Diff",
                                    [[particular_origin, ptags[0]],
                                     [particular_origin, ptags[1]]], snp)

                                activated.append(0 + iorigin)
                                P.add_fork(ptags,
                                           particular_origin,
                                           new_btags,
                                           btag,
                                           fork_speed=fork_speed)

                                for diff in ptags:
                                    record_diffusing[
                                        diff - offset_diff].start_replication(
                                            particular_origin,
                                            i * dt_speed,
                                            pos=snp.particles[diff].position)

                            else:
                                Change_type('F_Diff', ptags,
                                            snp)  # Diffusive element attached
                                particular_origin = list_ori[iorigin]
                                new_btags = Bind(
                                    "Mono_Diff",
                                    [[particular_origin, ptags[0]]], snp)
                                start = P.attach_one_diff(
                                    ptags[0], particular_origin, new_btags[0])

                                if start:
                                    # get particles involves
                                    p1, p2 = P.get_diff_at_origin(
                                        particular_origin)
                                    if diff_bind_when_on_DNA:
                                        btag = Bind("Diff_Diff",
                                                    [[p1[0], p2[0]]], snp)[0]

                                    activated.append(0 + iorigin)
                                    P.add_fork([p1[0], p2[0]],
                                               particular_origin,
                                               [p1[1], p2[1]],
                                               btag,
                                               fork_speed=fork_speed)

                                    record_diffusing[
                                        p1[0] - offset_diff].start_replication(
                                            particular_origin,
                                            i * dt_speed,
                                            pos=snp.particles[p1[0]].position)
                                    record_diffusing[
                                        p2[0] - offset_diff].start_replication(
                                            particular_origin,
                                            i * dt_speed,
                                            pos=snp.particles[p2[0]].position)
                                else:
                                    record_diffusing[
                                        ptags[0] - offset_diff].start_bound(
                                            particular_origin,
                                            i * dt_speed,
                                            pos=snp.particles[
                                                ptags[0]].position)

                        else:
                            # start when touched and release
                            particular_origin = list_ori[iorigin]
                            activated.append(iorigin)

                            P.add_fork([None, None],
                                       particular_origin, [None, None],
                                       None,
                                       fork_speed=fork_speed)

                        break
                    # If we arrive there it means that one interaction has beeen
                    # found
                    break
            activated.sort()
            print(activated)
            print(list_ori)

            for io in activated[::-1]:
                print(io)
                list_ori.pop(io)
        Timeit("After binding")
        # t0 = time.time()
        with open(data_folder + "polymer_timing.dat", "wb") as f:
            cPickle.dump(lPolymers, f, protocol=2)
        with open(data_folder + "Ndiff_libre_t.dat", "wb") as f:
            cPickle.dump(Ndiff_libre_t, f, protocol=2)

        with open(data_folder + "record_diffusing.dat", "wb") as f:
            cPickle.dump(record_diffusing, f, protocol=2)

        Timeit("After writing")

        if traj.get("early_stop",
                    True) and list_ori == [] and ended == len(lPolymers):
            break

        # print(time.time() -t0)
        # Then if it is the case attach them according to p law to the origin

    # print(gauss.get_energy(all_beads), wall_force_slj.get_energy(all_beads))
    print(time.time() - t0)
    logger.disable()
    method.disable()
    dcd.disable()
Exemplo n.º 6
0
        snapshot.particles.typeid[p] = np.random.randint(2)
    for p in range(len(snapshot.bonds.typeid)):
        snapshot.bonds.typeid[p] = 0

    system = init.read_snapshot(snapshot)

    xml = deprecated.dump.xml(filename=data_folder + "atoms.hoomdxml",
                              period=None,
                              group=group.all(),
                              vis=True)

    logger = analyze.log(filename=data_folder + 'mylog.log',
                         period=1000,
                         quantities=[
                             'temperature', 'potential_energy',
                             'bond_harmonic_energy', 'external_wall_lj_energy',
                             "pair_table_energy", 'kinetic_energy', 'volume',
                             'pressure'
                         ],
                         overwrite=True)
    # xml.disable()

    # Force_field:

    harmonic = md.bond.harmonic()
    harmonic.bond_coeff.set(bond_list, k=20.0, r0=1)

    def cos_soft(r, rmin, rmax, epsilon, sigma):

        V = epsilon * (1 + np.cos(r * 3.1415 / (rmax)))
        F = epsilon * 3.1415 / (rmax) * np.sin(r * 3.1415 / (rmax))
Exemplo n.º 7
0
def simulate(traj):

    seed = traj["seed"]

    micron = traj["micron"]
    data_folder = traj["data_folder"]

    # Diffusing elements
    cut_off_inte = traj["cut_off_inte"]
    p_inte = traj["p_inte"]
    p_off = traj["p_off"]
    sim_dt = traj["sim_dt"]

    dscale = traj["dscale"]
    # Yeast case
    spb = traj["spb"]
    assert (type(spb) == bool)

    microtubule_length = traj["microtubule_length"] * micron
    visu = traj["visu"]
    dump_hic = traj["dump_hic"]
    two_types = traj.get("two_types", False)

    # Scenari
    diff_alone = traj["diff_alone"]
    diff_bind_when_free = traj["diff_bind_when_free"]
    diff_bind_when_on_DNA = traj["diff_bind_when_on_DNA"]
    assert (type(diff_alone) == bool)
    assert (type(diff_bind_when_on_DNA) == bool)
    assert (type(diff_bind_when_free) == bool)

    # Simulation parameters
    n_steps = traj["n_steps"]
    length_steps = traj["length_steps"]
    benchmark = traj["benchmark"]
    warmup = traj["warmup"]
    dcd_period = traj["dcd_period"]

    np.random.seed(seed)
    hoomd.context.initialize()  # "--mode=cpu ")

    if diff_alone:
        # Check
        assert (diff_bind_when_free is False)
        assert (diff_bind_when_on_DNA is False)

    # End of parameter
    ##########################################

    #########################################
    # Define polymer bonding and positions

    snapshot, phic, tag_spb, bond_list, plist, Cen_pos, lPolymers, list_ori, p_tag_list = \
        create_initial_configuration(traj)
    system = init.read_snapshot(snapshot)

    for i, p in enumerate(system.particles):
        # print(p)
        # exit()
        assert p.tag == i

    for i, b in enumerate(system.bonds):
        if b.a == b.b:
            print(b.a, b.b)

            raise
        assert b.tag == i
    ###############################################

    ###############################################
    # Defining force field:
    all_beads, all_move, Spb_g, nl = force_field(traj,
                                                 bond_list=bond_list,
                                                 plist=plist,
                                                 tag_spb=tag_spb,
                                                 two_types=two_types)

    # Log
    if not visu:
        logger = analyze.log(filename=data_folder + 'mylog.log',
                             period=1000,
                             quantities=[
                                 'temperature', 'potential_energy',
                                 'bond_harmonic_energy',
                                 'external_wall_lj_energy',
                                 "pair_table_energy", 'kinetic_energy',
                                 'volume', 'pressure'
                             ],
                             overwrite=True)

    # Warmup

    minimize(traj, all_move, system, snapshot, Spb_g, Cen_pos,
             microtubule_length)

    # Dumping

    if visu:
        xml = deprecated.dump.xml(filename=data_folder + "atoms.hoomdxml",
                                  period=None,
                                  group=all_beads,
                                  vis=True)
        # xml.disable()
        return
    # gsd = dump.gsd(filename=data_folder + "atoms.gsd",period=None,group=all_beads)

    # Dynamics

    def Change_type(typep, particle_list, snp, msg=""):
        # print(particle_list)
        for p in particle_list:
            if "Ori" in typep:
                # Remove it from the list activated
                # list_ori.remove(p)
                pass
            else:
                snp.particles[p].type = typep
        if particle_list != [] and msg != "":
            print(msg)

    def Bind(typeb, bondlist, snp):
        btags = []
        for b1, b2 in bondlist:
            btags.append(snp.bonds.add(typeb, b1, b2))
        return btags

    def Release(btags, snp):
        for bt in btags:
            snp.bonds.remove(bt)

    def AddParticle(position, type):
        snp.particles.add(type)
        snp.particles[-1].position = position

    def Shift(bonds, snp):
        for tag, new in bonds:
            b = snp.bonds.get(tag)
            btype = "" + b.type
            fork = b.b + 0
            snp.bonds.remove(tag)

            # print(b.type)
            snp.bonds.add(btype, new, fork)
            # print(new,b)
            # print(dir(snp.bonds))
            # b.a = new

    snp = system  # .take_snapshot()

    # nl.tune(warmup=1,steps=1000)

    # Small warmup

    t0 = time.time()
    md.integrate.mode_standard(dt=sim_dt)
    method = md.integrate.langevin(group=all_move,
                                   kT=1,
                                   seed=seed,
                                   dscale=dscale)

    if benchmark:
        print(nl.tune(warmup=4000, r_min=0.3, r_max=0.8, jumps=5, steps=5000))
        return

    md.integrate.mode_standard(dt=sim_dt / 4)
    hoomd.run(100)
    md.integrate.mode_standard(dt=sim_dt / 2)
    hoomd.run(100)
    md.integrate.mode_standard(dt=sim_dt)

    if warmup != 0:
        hoomd.run(warmup)

    dcd = dump.dcd(filename=data_folder + 'poly.dcd',
                   period=dcd_period,
                   overwrite=True)

    r_hic = []
    if dump_hic:
        group_hic = group.tags(name="hic", tag_min=0, tag_max=phic)

    global timeit
    timeit = True
    global t0
    t0 = time.time()

    def Timeit(where=""):
        global timeit
        global t0
        if timeit:
            if where == "":
                print(time.time() - t0)
            else:
                print(where, time.time() - t0)
            t0 = time.time()

    bonds = []
    for i in range(n_steps):

        # Chek that the microtubule length is correct
        if spb:
            for cen in Cen_pos:
                cent_tmp = system.particles[cen]
                # print(cent_tmp.position)
                pspb = [p.position for p in Spb_g]
                d = linalg.norm(
                    np.array(pspb[0]) - np.array(cent_tmp.position))
                if d > 2 * microtubule_length:
                    print("MT too long", d)
                    exit()

        # Dump the Hi-Cs
        Timeit()
        # system.restore_snapshot(snp)

        hoomd.run(length_steps // 2, profile=False)
        Timeit("After first half")

        if dump_hic and i % traj.get("hic_period", 1) == 0:
            ph = np.array([p.position for p in group_hic])

            D = cdist(ph, ph)
            D[D < 2] = 1
            D[D >= 2] = 0
            np.fill_diagonal(D, 0)
            if r_hic != []:
                r_hic += D
            else:
                r_hic = D
            if i % 32 == 0:
                np.save(data_folder + "/hic", r_hic)

        # snp = system.take_snapshot()

        # Bond tags to release (Alone particle)
        remv = []
        for ib, b in enumerate(bonds):
            if np.random.rand() > p_off:
                continue

            p_tag_list.append(b[2])
            list_ori.append(b[1])

            Release([b[0]], snp)
            remv.append(ib)

        remv.sort()
        for ib in remv[::-1]:
            bonds.pop(ib)

        Timeit("AFter update")
        hoomd.run(length_steps // 2, profile=True)
        Timeit("AFter second half")

        # Update Type because of (Ori to passivated)

        # Update group

        # Find new interacting particles

        # First check if Dimer are close from one origin

        print("LAAAAAAAAAAAAAAA", p_tag_list, list_ori, bonds)
        p_diffu = np.array(
            [snp.particles[diff].position for diff in p_tag_list])

        p_origin = np.array([snp.particles[ori].position for ori in list_ori])

        if not (p_tag_list != [] and list_ori != []):
            print("No interactions")

        if p_tag_list != [] and list_ori != []:
            distances = cdist(p_diffu, p_origin)
            print(distances.shape)
            # Reorder the distances with the dimer tags

            # Groups Diff-Diff by bond to compute the distances

            activated_ori = []
            activated_p = []

            for iD, ptag in enumerate(p_tag_list):
                # print(d2.shape)
                # print(d2[iD])
                lo = list(range(len(distances[iD])))
                np.random.shuffle(lo)

                for iorigin in lo:
                    di = distances[iD][iorigin]
                    if iorigin in activated_ori:
                        # Needed because we don't want an origin to be activated
                        # twice
                        continue
                    if di > cut_off_inte:
                        continue

                    if np.random.rand() > p_inte:
                        continue
                    activated_ori.append(iorigin + 0)
                    activated_p.append(iD)

                    new_btags = Bind("Mono_Diff", [[list_ori[iorigin], ptag]],
                                     snp)

                    bonds.append([new_btags[0], list_ori[iorigin], ptag])

                    break
            activated_ori.sort()
            for ori in activated_ori[::-1]:
                list_ori.pop(ori)

            activated_p.sort()
            for p in activated_p[::-1]:
                p_tag_list.pop(p)

        Timeit("After binding")
        # t0 = time.time()

        # print(time.time() -t0)
        # Then if it is the case attach them according to p law to the origin

    # print(gauss.get_energy(all_beads), wall_force_slj.get_energy(all_beads))
    print(time.time() - t0)
    logger.disable()
    method.disable()
    dcd.disable()