예제 #1
1
파일: write_pop.py 프로젝트: m-yu/MAST
def update_structfile(ind, structfile, Optimizer):
    if Optimizer.structure == 'Defect' or Optimizer.structure == 'Surface':
        sols = Atoms()
        sols.extend(ind[0])
        sols.extend(ind.bulki)
    elif Optimizer.structure == 'Crystal':
        sols = ind[0].repeat((3,3,3))
    else:
        sols = ind[0].copy()
    positions = sols.get_positions()
    if Optimizer.vacancy_output:
        for one in ind.vacancies:
            sols.append(Atom(symbol='X',position=one.position))
    #Optimizer.output.write('Number of positions = {0}\n'.format(len(positions)))
    write_xyz(structfile, sols, ind.energy)
    return positions
예제 #2
0
 def getUnitCell(self):
     sideLen = self.sideLen
     edge = Atoms()
     nAtom = 2 * sideLen + 1
     for i in range(nAtom):
         if i % 2 == 0:
             label = 'C'
             y = 0.5
         else:
             label = 'N'
             if len(self.elements) == 1: label = 'C'
             y = 1.0
         x = (-sideLen + i) * 0.5 * sqrt(3)
         y -= (sideLen + 1) * 1.5
         atom = Atom(label, (x, y, 0.0))
         edge.append(atom)
     unitCell = Atoms()
     for i in range(6):
         newEdge = edge.copy()
         newEdge.rotate('z', i * 2 * pi / 6.0)
         unitCell.extend(newEdge)
     #get cell
     dist = (self.sideLen + 1) * 3.0  #the distance between  2 hole center
     if self.cubic:
         newAtoms = unitCell.copy()
         newAtoms.translate([dist * sqrt(3) / 2, dist / 2.0, 0])
         unitCell.extend(newAtoms)
         unitCell.set_cell([dist * sqrt(3), dist, 10.0])
     else:
         cell = np.diag([dist * sqrt(3) / 2, dist, 10])
         cell[0, 1] = dist / 2.0
         unitCell.set_cell(cell)
     return unitCell
예제 #3
0
파일: C2Nh2d.py 프로젝트: vanceeasleaf/aces
	def getUnitCell(self):
		sideLen=self.sideLen	
		edge=Atoms()
		nAtom=2*sideLen+1
		for i in range(nAtom):
			if i%2==0:
				label='C'
				y=0.5
			else:
				label='N'
				if len(self.elements)==1:label='C'
				y=1.0
			x=(-sideLen+i)*0.5*sqrt(3)
			y-=(sideLen+1)*1.5
			atom=Atom(label,(x,y,0.0))
			edge.append(atom)
		unitCell=Atoms()
		for i in range(6):
			newEdge=edge.copy()
			newEdge.rotate('z',i*2*pi/6.0)
			unitCell.extend(newEdge)
		#get cell
		dist=(self.sideLen+1)*3.0 #the distance between  2 hole center
		if self.cubic:
			newAtoms=unitCell.copy()
			newAtoms.translate([dist*sqrt(3)/2,dist/2.0,0])
			unitCell.extend(newAtoms)
			unitCell.set_cell([dist*sqrt(3),dist,10.0])
		else:
			cell=np.diag([dist*sqrt(3)/2,dist,10])
			cell[0,1]=dist/2.0
			unitCell.set_cell(cell)
		return unitCell
예제 #4
0
파일: CNnp.py 프로젝트: vanceeasleaf/aces
	def structure(self):
		latysmall,latExtend,latxsmall,latxbig,bond=[int(self.latysmall),int(self.latExtend),int(self.latxsmall),int(self.latxbig),float(self.bond)]
		if(latxsmall%2==0):latxsmall+=1;
		if(latxbig%2==1):latxbig+=1;
		atoms=self.agnr(latysmall,latxsmall+1,0);
		unit=self.agnr(latysmall-1+2*latExtend,latxbig,0)
		unit.translate([latxsmall*1.5,-(latExtend-0.5)*sqrt(3),0])
		atoms.extend(unit)
		unit=self.agnr(latysmall,latxsmall+1,0);
		unit.translate([(latxsmall+latxbig-1)*1.5,0,0])
		atoms.extend(unit)
		temp=Atoms()	
		for i in range(self.seg):
			unit=atoms.copy()
			unit.translate([(latxsmall+latxbig-1)*1.5*i,0,0])
			temp.extend(unit)
		atoms.extend(temp)
		atoms=get_unique_atoms(atoms)
		lx,ly=self.extent(atoms)
		atoms.set_cell([lx,ly,100])
		atoms.set_cell([lx*bond,ly*bond,100],scale_atoms=True)
		atoms.set_pbc([1,1,1])
		atoms.center(vacuum=10*bond)
		self.atoms=atoms
		
		self.write()
		print 'read_data structure'
예제 #5
0
    def structure(self):
        latysmall, latExtend, latxsmall, latxbig, bond = [
            int(self.latysmall),
            int(self.latExtend),
            int(self.latxsmall),
            int(self.latxbig),
            float(self.bond)
        ]
        if (latxsmall % 2 == 0): latxsmall += 1
        if (latxbig % 2 == 1): latxbig += 1
        atoms = self.agnr(latysmall, latxsmall + 1, 0)
        unit = self.agnr(latysmall - 1 + 2 * latExtend, latxbig, 0)
        unit.translate([latxsmall * 1.5, -(latExtend - 0.5) * sqrt(3), 0])
        atoms.extend(unit)
        unit = self.agnr(latysmall, latxsmall + 1, 0)
        unit.translate([(latxsmall + latxbig - 1) * 1.5, 0, 0])
        atoms.extend(unit)
        temp = Atoms()
        for i in range(self.seg):
            unit = atoms.copy()
            unit.translate([(latxsmall + latxbig - 1) * 1.5 * i, 0, 0])
            temp.extend(unit)
        atoms.extend(temp)
        atoms = get_unique_atoms(atoms)
        lx, ly = self.extent(atoms)
        atoms.set_cell([lx, ly, 100])
        atoms.set_cell([lx * bond, ly * bond, 100], scale_atoms=True)
        atoms.set_pbc([1, 1, 1])
        atoms.center(vacuum=10 * bond)
        self.atoms = atoms

        self.write()
        print 'read_data structure'
예제 #6
0
def atoms_2co():
    """Simple atoms object for testing with 2x CO molecules"""
    d = 1.14
    atoms = Atoms('CO', positions=[(0, 0, 0), (0, 0, d)], pbc=True)
    atoms.extend(Atoms('CO', positions=[(0, 2, 0), (0, 2, d)]))

    atoms.center(vacuum=5.)
    return atoms
예제 #7
0
def create_random_atoms(gd, nmolecules=10, name='NH2', mindist=4.5 / Bohr):
    """Create gas-like collection of atoms from randomly placed molecules.
    Applies rigid motions to molecules, translating the COM and/or rotating
    by a given angle around an axis of rotation through the new COM. These
    atomic positions obey the minimum distance requirement to zero-boundaries.

    Warning: This is only intended for testing parallel grid/LFC consistency.
    """
    atoms = Atoms(cell=gd.cell_cv * Bohr, pbc=gd.pbc_c)

    # Store the original state of the random number generator
    randstate = np.random.get_state()
    seed = np.array([md5_array(data, numeric=True)
                     for data in
                     [nmolecules, gd.cell_cv, gd.pbc_c, gd.N_c]]).astype(int)
    np.random.seed(seed % 4294967296)

    for m in range(nmolecules):
        amol = molecule(name)
        amol.set_cell(gd.cell_cv * Bohr)

        # Rotate the molecule around COM according to three random angles
        # The rotation axis is given by spherical angles phi and theta
        v,phi,theta = np.random.uniform(0.0, 2*np.pi, 3) # theta [0,pi[ really
        axis = np.array([cos(phi)*sin(theta), sin(phi)*sin(theta), cos(theta)])
        amol.rotate(axis, v)

        # Find the scaled length we must transverse along the given axes such
        # that the resulting displacement vector is `mindist` from the cell
        # face corresponding to that direction (plane with unit normal n_v).
        sdist_c = np.empty(3)
        if not gd.orthogonal:
            for c in range(3):
                n_v = gd.xxxiucell_cv[c] / np.linalg.norm(gd.xxxiucell_cv[c])
                sdist_c[c] = mindist / np.dot(gd.cell_cv[c], n_v)
        else:
            sdist_c[:] = mindist / gd.cell_cv.diagonal()
        assert np.all(sdist_c > 0), 'Displacment vectors must be inside cell.'

        # Scaled dimensions of the smallest possible box centered on the COM
        spos_ac = amol.get_scaled_positions() # NB! must not do a "% 1.0"
        scom_c = np.dot(gd.icell_cv, amol.get_center_of_mass())
        sbox_c = np.abs(spos_ac-scom_c[np.newaxis,:]).max(axis=0)
        sdelta_c = (1-np.array(gd.pbc_c)) * (sbox_c + sdist_c)
        assert (sdelta_c < 1.0-sdelta_c).all(), 'Box is too tight to fit atoms.'
        scenter_c = [np.random.uniform(d,1-d) for d in sdelta_c]
        center_v = np.dot(scenter_c, gd.cell_cv)

        # Translate the molecule such that COM is located at random center
        offset_av = (center_v-amol.get_center_of_mass()/Bohr)[np.newaxis,:]
        amol.set_positions(amol.get_positions()+offset_av*Bohr)
        assert np.linalg.norm(center_v-amol.get_center_of_mass()/Bohr) < 1e-9
        atoms.extend(amol)

    # Restore the original state of the random number generator
    np.random.set_state(randstate)
    assert compare_atoms(atoms)
    return atoms
예제 #8
0
def ellipsoid(atomlist,
              fill_factor=0.74,
              radii=None,
              ratio=[1, 1, 1],
              cell=None):
    """Generates a random ellipsoid by rejection sampling. Not the most efficient
    code but good at garaunteeing an even distribution inside the ellipsoid.

    Parameters
    ----------
    fill_factor : float
        Determines how "close" the atoms are packed. 
        See structopt.tools.get_particle_radius for description
    radii : list (3 elements)
        The size, in angstroms, of the ellipsoid in the x, y and z
        direction
    ratio : list (3 elements)
        The ratio of the dimensions of the ellipsoid in the x, y
        and z direction.
    cell : list (3  elements)
        The size, in angstroms, of the dimensions that holds the
        atoms object
    """

    # Get the dimensions of the ellipsoid if required
    if radii is None:
        radius = get_particle_radius(atomlist, fill_factor)
        a = radius / ((ratio[1] / ratio[0])**(1.0 / 3.0) *
                      (ratio[2] / ratio[0])**(1.0 / 3.0))
        b = radius / ((ratio[0] / ratio[1])**(1.0 / 3.0) *
                      (ratio[2] / ratio[1])**(1.0 / 3.0))
        c = radius / ((ratio[0] / ratio[2])**(1.0 / 3.0) *
                      (ratio[1] / ratio[2])**(1.0 / 3.0))
    else:
        a, b, c = radii

    # Create a list of random order of the atoms
    chemical_symbols = []
    for atom in atomlist:
        chemical_symbols += [atom[0]] * atom[1]
    random.shuffle(chemical_symbols)

    # Add atoms iteratively only if they fall inside the ellipsoid
    indiv = Atoms()
    while len(chemical_symbols) > 0:
        x, y, z = random.uniform(-a,
                                 a), random.uniform(-b,
                                                    b), random.uniform(-c, c)
        if x**2 / a**2 + y**2 / b**2 + z**2 / c**2 <= 1:
            indiv.extend(Atom(chemical_symbols.pop(), [x, y, z]))

    if cell is not None:
        indiv.set_cell(cell)
        indiv.center()
        indiv.set_pbc(True)

    return indiv
예제 #9
0
def ase_minimization(indiv, Optimizer):
    """Function to use built in ASE minimizers to minimize atomic positions in structure.
    Input:
        indiv = Individual class object to be optimized
        Optimizer = Optimizer class object with needed parameters
    Output:
        indiv = Optimized Individual class object.
    """
    if 'MU' in Optimizer.debug:
        debug = True
    else:
        debug = False
    cwd1=os.getcwd()
    olammpsmin = Optimizer.lammps_min
    if Optimizer.lammps_min:
        Optimizer.lammps_min = None
    calc2 = setup_calculator(Optimizer)
#     if 'mass' in indiv[0].get_calculator():
#         mass2 = ['1 '+ str(Optimizer.atomlist[0][2])]
#         if len(Optimizer.atomlist) > 1:
#             for i in range(len(Optimizer.atomlist)-1):
#                 mass2.append(str(i+2) + ' ' + str(Optimizer.atomlist[i+1][2]))
#         calc2=LAMMPS(parameters={ 'pair_style' : Optimizer.pair_style, 'pair_coeff' : Optimizer.pair_coeff , 'mass' : mass2 },files=[ Optimizer.pot_file ])
#     else:
#         calc2=LAMMPS(parameters={ 'pair_style' : Optimizer.pair_style, 'pair_coeff' : Optimizer.pair_coeff},files=[ Optimizer.pot_file ])
    if Optimizer.structure==Defect:
        nat=indiv[0].get_number_of_atoms
        sol=Atoms()
        sol.extend(indiv[0])
        sol.extend(indiv.bulko)
        sol.set_calculator(calc2)
        sol.set_cell(indiv.bulko.get_cell())
        sol.set_pbc(True)
        dyn=BFGS(sol)
        dyn.run(fmax=0.001, steps=2500)
        positions=sol[0:nat].get_positions()
        indiv[0].set_positions(positions)
    else:
        atomsdup=indiv[0].copy()
        atomsdup.set_calculator(calc2)
        dyn=BFGS(indiv[0])
        dyn.run(fmax=0.001, steps=2500)
        positions=atomsdup.get_positions()
        indiv[0].set_positions(positions)
    os.chdir(cwd1)
    calc2.clean()
    Optimizer.lammps_min = olammpsmin
    Optimizer.output.write('ASE Minimization mutation performed on individual = '+repr(indiv.index)+'\n')
    muttype='ASEM'
    if indiv.energy==0:
        indiv.history_index=indiv.history_index+'m'+muttype
    else:
        indiv.history_index=repr(indiv.index)+'m'+muttype
    return indiv
		
		
예제 #10
0
def create_random_atoms(gd, nmolecules=10, name='H2O', mindist=4.5 / Bohr):
    """Create gas-like collection of atoms from randomly placed molecules.
    Applies rigid motions to molecules, translating the COM and/or rotating
    by a given angle around an axis of rotation through the new COM. These
    atomic positions obey the minimum distance requirement to zero-boundaries.

    Warning: This is only intended for testing parallel grid/LFC consistency.
    """
    atoms = Atoms(cell=gd.cell_cv * Bohr, pbc=gd.pbc_c)

    # Store the original state of the random number generator
    randstate = np.random.get_state()
    np.random.seed(np.array([md5_array(data, numeric=True) for data
        in [nmolecules, gd.cell_cv, gd.pbc_c, gd.N_c]]).astype(int))

    for m in range(nmolecules):
        amol = molecule(name)
        amol.set_cell(gd.cell_cv * Bohr)

        # Rotate the molecule around COM according to three random angles
        # The rotation axis is given by spherical angles phi and theta
        v,phi,theta = np.random.uniform(0.0, 2*np.pi, 3) # theta [0,pi[ really
        axis = np.array([cos(phi)*sin(theta), sin(phi)*sin(theta), cos(theta)])
        amol.rotate(axis, v)

        # Find the scaled length we must transverse along the given axes such
        # that the resulting displacement vector is `mindist` from the cell
        # face corresponding to that direction (plane with unit normal n_v).
        sdist_c = np.empty(3)
        if not gd.orthogonal:
            for c in range(3):
                n_v = gd.xxxiucell_cv[c] / np.linalg.norm(gd.xxxiucell_cv[c])
                sdist_c[c] = mindist / np.dot(gd.cell_cv[c], n_v)
        else:
            sdist_c[:] = mindist / gd.cell_cv.diagonal()
        assert np.all(sdist_c > 0), 'Displacment vectors must be inside cell.'

        # Scaled dimensions of the smallest possible box centered on the COM
        spos_ac = amol.get_scaled_positions() # NB! must not do a "% 1.0"
        scom_c = np.dot(gd.icell_cv, amol.get_center_of_mass())
        sbox_c = np.abs(spos_ac-scom_c[np.newaxis,:]).max(axis=0)
        sdelta_c = (1-np.array(gd.pbc_c)) * (sbox_c + sdist_c)
        assert (sdelta_c < 1.0-sdelta_c).all(), 'Box is too tight to fit atoms.'
        scenter_c = [np.random.uniform(d,1-d) for d in sdelta_c]
        center_v = np.dot(scenter_c, gd.cell_cv)

        # Translate the molecule such that COM is located at random center
        offset_av = (center_v-amol.get_center_of_mass()/Bohr)[np.newaxis,:]
        amol.set_positions(amol.get_positions()+offset_av*Bohr)
        assert np.linalg.norm(center_v-amol.get_center_of_mass()/Bohr) < 1e-9
        atoms.extend(amol)

    # Restore the original state of the random number generator
    np.random.set_state(randstate)
    assert compare_atoms(atoms)
    return atoms
예제 #11
0
	def lmp_structure(self):
		ribbon=graphene(dict(latx=self.latx,laty=self.laty,latz=1,gnrtype=self.gnrtype)).lmp_structure()

		for atom in ribbon:
			atom.position=self.trans(atom.position)
		atoms=Atoms()
		atoms.extend(ribbon)
		atoms.center(vacuum=10)
		
		return atoms
예제 #12
0
	def lmp_structure(self):
		ribbon=graphene(dict(latx=self.latx,laty=self.laty,latz=1,gnrtype=self.gnrtype)).lmp_structure()

		for atom in ribbon:
			atom.position=self.trans(atom.position)
		atoms=Atoms()
		atoms.extend(ribbon)
		atoms.center(vacuum=10)
		
		return atoms
예제 #13
0
 def unitcell(self, latx, laty):
     unit = Atoms('C2', [(0.5, 0.5, 0.0),
                         (0.5 + sqrt(2) / 2, 0.5 + sqrt(2) / 2, 0)])
     atoms = Atoms()
     for i in range(4):
         a = unit.copy()
         a.rotate('z', pi / 2 * i)
         atoms.extend(a)
     atoms.set_cell([2 + sqrt(2), 2 + sqrt(2), 10.0])
     col = unit.repeat((latx, laty, 1))
     return col
예제 #14
0
 def testget_unique_atoms(self):
     unit = Atoms("C4",
                  positions=[(0, 0, 0), (0, 1, 0), (1, 1, 0), (1, 0, 0)])
     unit1 = unit.copy()
     unit1.translate([1, 0, 0])
     atoms = Atoms()
     atoms.extend(unit)
     atoms.extend(unit1)
     self.assertEqual(len(atoms), 8)
     atoms = get_unique_atoms(atoms)
     self.assertEqual(len(atoms), 6)
예제 #15
0
파일: graphene.py 프로젝트: xiexingzhu/aces
	def ring(self):
		#armchair ring
		atoms=Atoms()
		atom=Atoms('C',[(1.0,0.0,0.0)])
		for i in range(6):			
			atom.rotate('z',pi/3*i)
			atoms.extend(atom.copy())
		atoms.set_cell([3.0,sqrt(3),self.az])
		return atoms
			
		
예제 #16
0
	def ring(self):
		#armchair ring
		b=3.134/self.bond/2
		atoms=Atoms()
		atom=Atoms('MoS2',[(1.0,0.0,0.0),(-1.0,0,b),(-1.0,0,-b)])
		for i in range(3):			
			atom.rotate('z',pi*2.0/3*i)
			atoms.extend(atom.copy())
		atoms.set_cell([3.0,sqrt(3),10.0])
		return atoms
			
		
예제 #17
0
 def ring(self):
     # armchair ring
     atoms = Atoms()
     atom = Atoms('C', positions=[(1.0, 0.0, 0.0)])
     for i in range(6):
         unit = atom.copy()
         unit.rotate('z', pi / 3 * i)
         atoms.extend(unit)
     atoms.set_cell([3.0, sqrt(3), self.az])
     atoms.center()
     wrap(atoms)
     return atoms
예제 #18
0
def get_atoms_adsorbate():
    # We need the relaxed slab here!
    slab = Atoms([
        Atom('Cu',
             [-1.028468159509163, -0.432387156877267, -0.202086055768265]),
        Atom('Cu', [0.333333333333333, 0.333333333333333, -2.146500000000000]),
        Atom('Cu',
             [1.671531840490805, -0.432387156877287, -0.202086055768242]),
        Atom('Cu', [3.033333333333334, 0.333333333333333, -2.146500000000000]),
        Atom('Cu',
             [4.371531840490810, -0.432387156877236, -0.202086055768261]),
        Atom('Cu', [5.733333333333333, 0.333333333333333, -2.146500000000000]),
        Atom('Cu',
             [7.071531840490944, -0.432387156877258, -0.202086055768294]),
        Atom('Cu', [8.433333333333335, 0.333333333333333, -2.146500000000000]),
        Atom('Cu', [0.321531840490810, 1.905881433340708, -0.202086055768213]),
        Atom('Cu', [1.683333333333333, 2.671601923551318, -2.146500000000000]),
        Atom('Cu', [3.021531840490771, 1.905881433340728, -0.202086055768250]),
        Atom('Cu', [4.383333333333334, 2.671601923551318, -2.146500000000000]),
        Atom('Cu', [5.721531840490857, 1.905881433340735, -0.202086055768267]),
        Atom('Cu', [7.083333333333333, 2.671601923551318, -2.146500000000000]),
        Atom('Cu', [8.421531840490820, 1.905881433340739, -0.202086055768265]),
        Atom('Cu', [9.783333333333335, 2.671601923551318, -2.146500000000000]),
        Atom('Cu', [1.671531840490742, 4.244150023558601, -0.202086055768165]),
        Atom('Cu', [3.033333333333334, 5.009870513769302, -2.146500000000000]),
        Atom('Cu', [4.371531840490840, 4.244150023558694, -0.202086055768265]),
        Atom('Cu', [5.733333333333333, 5.009870513769302, -2.146500000000000]),
        Atom('Cu', [7.071531840490880, 4.244150023558786, -0.202086055768352]),
        Atom('Cu', [8.433333333333335, 5.009870513769302, -2.146500000000000]),
        Atom('Cu', [9.771531840491031, 4.244150023558828, -0.202086055768371]),
        Atom('Cu',
             [11.133333333333335, 5.009870513769302, -2.146500000000000]),
        Atom('Cu', [3.021531840490714, 6.582418613776583, -0.202086055768197]),
        Atom('Cu', [4.383333333333334, 7.348139103987287, -2.146500000000000]),
        Atom('Cu', [5.721531840490814, 6.582418613776629, -0.202086055768203]),
        Atom('Cu', [7.083333333333333, 7.348139103987287, -2.146500000000000]),
        Atom('Cu', [8.421531840490985, 6.582418613776876, -0.202086055768357]),
        Atom('Cu', [9.783333333333335, 7.348139103987287, -2.146500000000000]),
        Atom('Cu',
             [11.121531840490929, 6.582418613776676, -0.202086055768221]),
        Atom('Cu',
             [12.483333333333334, 7.348139103987287, -2.146500000000000]),
    ])
    mask = [a.position[2] < -1 for a in slab]
    slab.set_constraint(FixAtoms(mask=mask))

    h = 1.85
    d = 1.10

    molecule = Atoms('2N', positions=[(0., 0., h), (0., 0., h + d)])
    molecule.set_calculator(EMT())
    slab.extend(molecule)
    return slab
예제 #19
0
 def testget_unique_atoms(self):
     unit = Atoms(
         "C4", positions=[
             (0, 0, 0), (0, 1, 0), (1, 1, 0), (1, 0, 0)])
     unit1 = unit.copy()
     unit1.translate([1, 0, 0])
     atoms = Atoms()
     atoms.extend(unit)
     atoms.extend(unit1)
     self.assertEqual(len(atoms), 8)
     atoms = get_unique_atoms(atoms)
     self.assertEqual(len(atoms), 6)
예제 #20
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def ellipsoid(atomlist, fill_factor=0.74, radii=None, ratio=[1, 1, 1], cell=None):
    """Generates a random ellipsoid by rejection sampling.

    Parameters
    ----------
    atomlist : list
        A list of [sym, n] pairs where sym is the chemical symbol
        and n is the number of of sym's to include in the individual
    fill_factor : float
        Determines how "close" the atoms are packed. 
        See structopt.tools.get_particle_radius for description
    radii : list
        The size, in angstroms, of the ellipsoid in the x, y and z
        direction. If None, with ratio parameters and the average
        atomic radii, radii is automatically calculated.
    ratio : list
        The ratio of the dimensions of the ellipsoid in the x, y
        and z direction.
    cell : list
        The size, in angstroms, of the dimensions that holds the
        atoms object. Must be an orthogonal box.
    """
    

    # Get the dimensions of the ellipsoid if required
    if radii is None:
        radius = get_particle_radius(atomlist, fill_factor)
        a = radius / ((ratio[1]/ratio[0])**(1.0/3.0) * (ratio[2]/ratio[0])**(1.0/3.0))
        b = radius / ((ratio[0]/ratio[1])**(1.0/3.0) * (ratio[2]/ratio[1])**(1.0/3.0))
        c = radius / ((ratio[0]/ratio[2])**(1.0/3.0) * (ratio[1]/ratio[2])**(1.0/3.0))
    else:
        a, b, c = radii

    # Create a list of random order of the atoms
    chemical_symbols = []
    for atom in atomlist:
        chemical_symbols += [atom[0]] * atom[1]
    random.shuffle(chemical_symbols)

    # Add atoms iteratively only if they fall inside the ellipsoid
    indiv = Atoms()
    while len(chemical_symbols) > 0:
        x, y, z = random.uniform(-a, a), random.uniform(-b, b), random.uniform(-c, c)
        if x**2/a**2 + y**2/b**2 + z**2/c**2 <= 1:
            indiv.extend(Atom(chemical_symbols.pop(), [x, y, z]))

    if cell is not None:
        indiv.set_cell(cell)
        indiv.center()
        indiv.set_pbc(True)

    return indiv
예제 #21
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def permutation_crystal_multi(indiv, Optimizer):
    """Move function to perform Permutation of multiple atom based on atomlist with entire crystal in Defect
    Inputs:
        indiv = Individual class object to be altered
        Optimizer = Optimizer class object with needed parameters
    Outputs:
        indiv = Altered Individual class object
    """
    if 'MU' in Optimizer.debug:
        debug = True
    else:
        debug = False
    if Optimizer.structure != 'Defect':
        Optimizer.output.write('WARNING: Crystal extended permutation attempted on non-Defect system. Skipping Mutation\n')
    else:
        indexbulk=len(indiv[0])
        solid=Atoms()
        solid.extend(indiv[0])
        solid.extend(indiv.bulki)
        solid.set_pbc(True)
        solid.set_cell(indiv[0].get_cell())
        a1=solid[random.randint(0,indiv[0].get_number_of_atoms()-1)]
        opts=[inds for inds in solid if inds.symbol != a1.symbol]
        inpts=[inds for inds in solid if inds.symbol == a1.symbol]
        maxperm=len(inpts)
        if maxperm > len(opts):
            maxperm=len(opts)
        Optimizer.output.write('Multiatom Crystal-wide Permutation Mutation performed on individual\n')
        Optimizer.output.write('Index = '+repr(indiv.index)+'\n')
        if maxperm==0:
            Optimizer.output.write('WARNING: Permutation Mutation attempted on single atom structure system\n')
            natperm=0
        else:
            natperm=random.randint(1,maxperm/2)
        Optimizer.output.write('Number of atoms permutated = '+repr(natperm)+'\n')
        for i in range(natperm):
            a1=inpts[random.randint(0,len(inpts)-1)]
            a2=opts[random.randint(0,len(opts)-1)]
            solid[a1.index].symbol, solid[a2.index].symbol=a2.symbol, a1.symbol
            Optimizer.output.write(repr(a1.symbol) + ' swapped with ' + repr(a2.symbol)+'\n')
        indiv.bulki=solid[indexbulk::]
        indiv[0]=solid[0:indexbulk]
        Optimizer.output.write(repr(indiv[0])+'\n')
        for sym,c,m,u in Optimizer.atomlist:
            nc=len([atm for atm in solid if atm.symbol==sym])
            Optimizer.output.write('Defect configuration contains '+repr(nc)+' '+repr(sym)+' atoms\n')
        muttype='PCMA'+repr(natperm)
        if indiv.energy==0:
            indiv.history_index=indiv.history_index+'m'+muttype
        else:
            indiv.history_index=repr(indiv.index)+'m'+muttype
    return indiv
예제 #22
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def permutation_crystal(indiv, Optimizer):
    """Move function to perform Permutation of one atom based on atomlist with entire crystal in Defect
    Inputs:
        indiv = Individual class object to be altered
        Optimizer = Optimizer class object with needed parameters
    Outputs:
        indiv = Altered Individual class object
    """
    if 'MU' in Optimizer.debug:
        debug = True
    else:
        debug = False
    if Optimizer.structure != 'Defect':
        Optimizer.output.write(
            'WARNING: Crystal extended permutation attempted on non-Defect system. Skipping Mutation\n'
        )
    else:
        indexbulk = len(indiv[0])
        solid = Atoms()
        solid.extend(indiv[0])
        solid.extend(indiv.bulki)
        solid.set_pbc(True)
        solid.set_cell(indiv.bulko.get_cell())
        a1 = solid[random.randint(0, indiv[0].get_number_of_atoms() - 1)]
        opts = [inds for inds in solid if inds.symbol != a1.symbol]
        try:
            a2 = opts[random.randint(0, len(opts) - 1)]
        except ValueError:
            a2 = indiv[0][random.randint(0,
                                         indiv[0].get_number_of_atoms() - 1)]
            Optimizer.output.write(
                'WARNING: Permutation Mutation attempted on single atom structure system\n'
            )
        solid[a1.index].symbol, solid[a2.index].symbol = a2.symbol, a1.symbol
        indiv.bulki = solid[indexbulk::]
        indiv[0] = solid[0:indexbulk]
        Optimizer.output.write(
            'Crystal-wide Permutation Mutation performed on individual\n')
        Optimizer.output.write('Index = ' + repr(indiv.index) + '\n')
        Optimizer.output.write(
            repr(a1.symbol) + ' swapped with ' + repr(a2.symbol) + '\n')
        Optimizer.output.write(repr(indiv[0]) + '\n')
        for sym, c, m, u in Optimizer.atomlist:
            nc = len([atm for atm in solid if atm.symbol == sym])
            Optimizer.output.write('Defect configuration contains ' +
                                   repr(nc) + ' ' + repr(sym) + ' atoms\n')
        muttype = 'PC'
        if indiv.energy == 0:
            indiv.history_index = indiv.history_index + 'm' + muttype
        else:
            indiv.history_index = repr(indiv.index) + 'm' + muttype
    return indiv
예제 #23
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	def unitcell(self,latx,laty):
		unit=Atoms('C2',[(0.5,0.5,0.0),(0.5+sqrt(2)/2,0.5+sqrt(2)/2,0)])
		atoms=Atoms()
		for i in range(4):
			a=unit.copy()
			a.rotate('z',pi/2*i)
			atoms.extend(a)
		atoms.set_cell([2+sqrt(2),2+sqrt(2),10.0])
		col=unit.repeat((latx,laty,1))
		return col
		
			
		
예제 #24
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def get_atoms_adsorbate():
    # We need the relaxed slab here! 
    slab = Atoms([
        Atom('Cu', [     -1.028468159509163,     -0.432387156877267,     -0.202086055768265]),
        Atom('Cu', [      0.333333333333333,      0.333333333333333,     -2.146500000000000]),
        Atom('Cu', [      1.671531840490805,     -0.432387156877287,     -0.202086055768242]),
        Atom('Cu', [      3.033333333333334,      0.333333333333333,     -2.146500000000000]),
        Atom('Cu', [      4.371531840490810,     -0.432387156877236,     -0.202086055768261]),
        Atom('Cu', [      5.733333333333333,      0.333333333333333,     -2.146500000000000]),
        Atom('Cu', [      7.071531840490944,     -0.432387156877258,     -0.202086055768294]),
        Atom('Cu', [      8.433333333333335,      0.333333333333333,     -2.146500000000000]),
        Atom('Cu', [      0.321531840490810,      1.905881433340708,     -0.202086055768213]),
        Atom('Cu', [      1.683333333333333,      2.671601923551318,     -2.146500000000000]),
        Atom('Cu', [      3.021531840490771,      1.905881433340728,     -0.202086055768250]),
        Atom('Cu', [      4.383333333333334,      2.671601923551318,     -2.146500000000000]),
        Atom('Cu', [      5.721531840490857,      1.905881433340735,     -0.202086055768267]),
        Atom('Cu', [      7.083333333333333,      2.671601923551318,     -2.146500000000000]),
        Atom('Cu', [      8.421531840490820,      1.905881433340739,     -0.202086055768265]),
        Atom('Cu', [      9.783333333333335,      2.671601923551318,     -2.146500000000000]),
        Atom('Cu', [      1.671531840490742,      4.244150023558601,     -0.202086055768165]),
        Atom('Cu', [      3.033333333333334,      5.009870513769302,     -2.146500000000000]),
        Atom('Cu', [      4.371531840490840,      4.244150023558694,     -0.202086055768265]),
        Atom('Cu', [      5.733333333333333,      5.009870513769302,     -2.146500000000000]),
        Atom('Cu', [      7.071531840490880,      4.244150023558786,     -0.202086055768352]),
        Atom('Cu', [      8.433333333333335,      5.009870513769302,     -2.146500000000000]),
        Atom('Cu', [      9.771531840491031,      4.244150023558828,     -0.202086055768371]),
        Atom('Cu', [     11.133333333333335,      5.009870513769302,     -2.146500000000000]),
        Atom('Cu', [      3.021531840490714,      6.582418613776583,     -0.202086055768197]),
        Atom('Cu', [      4.383333333333334,      7.348139103987287,     -2.146500000000000]),
        Atom('Cu', [      5.721531840490814,      6.582418613776629,     -0.202086055768203]),
        Atom('Cu', [      7.083333333333333,      7.348139103987287,     -2.146500000000000]),
        Atom('Cu', [      8.421531840490985,      6.582418613776876,     -0.202086055768357]),
        Atom('Cu', [      9.783333333333335,      7.348139103987287,     -2.146500000000000]),
        Atom('Cu', [     11.121531840490929,      6.582418613776676,     -0.202086055768221]),
        Atom('Cu', [     12.483333333333334,      7.348139103987287,     -2.146500000000000]),
    ])
    mask = [a.position[2] < -1 for a in slab]
    slab.set_constraint(FixAtoms(mask=mask))

    a = 2.70
    c = 1.59 * a
    h = 1.85
    d = 1.10
    x = slab.positions[0, 2] / (c / 2) * 100

    molecule = Atoms('2N', positions=[(0., 0., h),
                                      (0., 0., h + d)])
    molecule.set_calculator(EMT())
    slab.extend(molecule)
    return slab
예제 #25
0
파일: C2Ntri.py 프로젝트: vanceeasleaf/aces
 def unitcell(self, latx, laty):
     unit = Atoms('C2N', [(1 / 2 * sqrt(3), 0.5, 0.0),
                          (1 / 2 * sqrt(3), -0.5, 0),
                          (1 / 2 * sqrt(3), 1.5, 0)])
     atoms = Atoms()
     for i in range(3):
         a = unit.copy()
         a.rotate('z', pi * 2 / 3 * i)
         atoms.extend(a)
     if self.centerN:
         atoms.append(Atom('N', (0, 0, 0)))
     atoms.set_cell([6 * sqrt(3) / 2, 6, 10.0])
     col = unit.repeat((latx, laty, 1))
     return col
예제 #26
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def get_fingerprint(Optimizer, indiv, binsize, cutoffdist):
    """Function to calculate the fingerprint of a structure
    """
    rs = numpy.linspace(0.0, cutoffdist, cutoffdist / binsize)
    indi = indiv[0]
    Vuc = indi.get_volume()
    if Optimizer.structure == 'Defect':
        solid = Atoms()
        solid.extend(indi)
        solid.extend(indiv.bulki)
    elif Optimizer.structure == 'Crystal':
        solid = indi.repeat([3, 3, 3])
    else:
        solid = indi.copy()
    syms = sorted(list(set([atm.symbol for atm in solid])))
    fingerprints = []
    for i in range(len(syms)):
        for j in range(i, len(syms)):
            indl = [atm for atm in indi if atm.symbol == syms[i]]
            ind = Atoms()
            for one in indl:
                ind.append(one)
            soll = [atm for atm in solid if atm.symbol == syms[j]]
            sol = Atoms()
            for one in soll:
                sol.append(one)
            soli = [atm for atm in solid if atm.symbol == syms[i]]
            value = []
            for R in rs:
                value2 = []
                for k in range(len(ind)):
                    value1 = []
                    for m in range(len(sol)):
                        if k != m:
                            rij = sol.get_distance(k, m, mic=True)
                            if rij == 0:
                                pass
                                #pdb.set_trace()
                            value1.append(
                                dirac(R, a=rij, sig=0.02) * 1 /
                                (4 * math.pi * rij**2 * binsize * len(soli) *
                                 len(sol) / Vuc))
                    value2.append(sum(value1))
                value.append(sum(value2))
            fingerprints.append(value)
    fpt = []
    for one in fingerprints:
        fpt.extend(one)
    return fpt
예제 #27
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def get_fingerprint(Optimizer, indiv, binsize, cutoffdist):
    """Function to calculate the fingerprint of a structure"""

    rs = numpy.linspace(0.0, cutoffdist, cutoffdist/binsize)
    indi = indiv[0]
    Vuc = indi.get_volume()
    if Optimizer.structure == 'Defect':
        solid = Atoms()
        solid.extend(indi)
        solid.extend(indiv.bulki)
    elif Optimizer.structure == 'Crystal':
        solid = indi.repeat([3, 3, 3])
    else:
        solid = indi.copy()

    syms = sorted(list(set([atm.symbol for atm in solid])))
    fingerprints = []
    for i in range(len(syms)):
        for j in range(i, len(syms)):
            indl = [atm for atm in indi if atm.symbol == syms[i]]
            ind = Atoms()
            for one in indl:
                ind.append(one)
            soll = [atm for atm in solid if atm.symbol == syms[j]]
            sol = Atoms()
            for one in soll:
                sol.append(one)
            soli = [atm for atm in solid if atm.symbol == syms[i]]
            value = []
            for R in rs:
                value2 = []
                for k in range(len(ind)):
                    value1 = []
                    for m in range(len(sol)):
                        if k != m:
                            rij = sol.get_distance(k, m, mic = True)
                            if rij == 0:
                                pass
                                #pdb.set_trace()
                            value1.append(dirac(R, a=rij, sig=0.02) * 1. / (4*math.pi * rij** 2*binsize * len(soli) * len(sol) / Vuc))
                    value2.append(sum(value1))
                value.append(sum(value2))
            fingerprints.append(value)

    fpt = []
    for one in fingerprints:
        fpt.extend(one)

    return fpt
예제 #28
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def make_supercell(prim, P, wrap=True, tol=1e-5):
    r"""Generate a supercell by applying a general transformation (*P*) to
    the input configuration (*prim*).

    The transformation is described by a 3x3 integer matrix
    `\mathbf{P}`. Specifically, the new cell metric
    `\mathbf{h}` is given in terms of the metric of the input
    configuraton `\mathbf{h}_p` by `\mathbf{P h}_p =
    \mathbf{h}`.

    Parameters:

    prim: ASE Atoms object
        Input configuration.
    P: 3x3 integer matrix
        Transformation matrix `\mathbf{P}`.
    wrap: bool
        wrap in the end
    tol: float
        tolerance for wrapping
    """

    supercell_matrix = P
    supercell = clean_matrix(supercell_matrix @ prim.cell)

    # cartesian lattice points
    lattice_points_frac = lattice_points_in_supercell(supercell_matrix)
    lattice_points = np.dot(lattice_points_frac, supercell)

    superatoms = Atoms(cell=supercell, pbc=prim.pbc)

    for lp in lattice_points:
        shifted_atoms = prim.copy()
        shifted_atoms.positions += lp
        superatoms.extend(shifted_atoms)

    # check number of atoms is correct
    n_target = int(np.round(np.linalg.det(supercell_matrix) * len(prim)))
    if n_target != len(superatoms):
        msg = "Number of atoms in supercell: {}, expected: {}".format(
            n_target, len(superatoms)
        )
        raise SupercellError(msg)

    if wrap:
        superatoms.wrap(eps=tol)

    return superatoms
예제 #29
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def update_structfile(ind, structfile, Optimizer):
    if Optimizer.structure == 'Defect' or Optimizer.structure == 'Surface':
        sols = Atoms()
        sols.extend(ind[0])
        sols.extend(ind.bulki)
    elif Optimizer.structure == 'Crystal':
        sols = ind[0].repeat((3, 3, 3))
    else:
        sols = ind[0].copy()
    positions = sols.get_positions()
    if Optimizer.vacancy_output:
        for one in ind.vacancies:
            sols.append(Atom(symbol='X', position=one.position))
    #Optimizer.output.write('Number of positions = {0}\n'.format(len(positions)))
    write_xyz(structfile, sols, ind.energy)
    return positions
예제 #30
0
파일: C2Ntri.py 프로젝트: vanceeasleaf/aces
	def unitcell(self,latx,laty):
		unit=Atoms('C2N',[(1/2*sqrt(3),0.5,0.0),
			(1/2*sqrt(3),-0.5,0),
			(1/2*sqrt(3),1.5,0)])
		atoms=Atoms()
		for i in range(3):
			a=unit.copy()
			a.rotate('z',pi*2/3*i)
			atoms.extend(a)
		if self.centerN:
			atoms.append(Atom('N',(0,0,0)))
		atoms.set_cell([6*sqrt(3)/2,6,10.0])
		col=unit.repeat((latx,laty,1))
		return col
		
			
		
예제 #31
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def get_atoms():
    srf = Atoms('Cu64', [(1.2763, 1.2763, 4.0000), (3.8290, 1.2763, 4.0000),
                         (6.3816, 1.2763, 4.0000), (8.9343, 1.2763, 4.0000),
                         (1.2763, 3.8290, 4.0000), (3.8290, 3.8290, 4.0000),
                         (6.3816, 3.8290, 4.0000), (8.9343, 3.8290, 4.0000),
                         (1.2763, 6.3816, 4.0000), (3.8290, 6.3816, 4.0000),
                         (6.3816, 6.3816, 4.0000), (8.9343, 6.3816, 4.0000),
                         (1.2763, 8.9343, 4.0000), (3.8290, 8.9343, 4.0000),
                         (6.3816, 8.9343, 4.0000), (8.9343, 8.9343, 4.0000),
                         (0.0000, 0.0000, 5.8050), (2.5527, 0.0000, 5.8050),
                         (5.1053, 0.0000, 5.8050), (7.6580, 0.0000, 5.8050),
                         (0.0000, 2.5527, 5.8050), (2.5527, 2.5527, 5.8050),
                         (5.1053, 2.5527, 5.8050), (7.6580, 2.5527, 5.8050),
                         (0.0000, 5.1053, 5.8050), (2.5527, 5.1053, 5.8050),
                         (5.1053, 5.1053, 5.8050), (7.6580, 5.1053, 5.8050),
                         (0.0000, 7.6580, 5.8050), (2.5527, 7.6580, 5.8050),
                         (5.1053, 7.6580, 5.8050), (7.6580, 7.6580, 5.8050),
                         (1.2409, 1.2409, 7.6081), (3.7731, 1.2803, 7.6603),
                         (6.3219, 1.3241, 7.6442), (8.8935, 1.2669, 7.6189),
                         (1.2803, 3.7731, 7.6603), (3.8188, 3.8188, 7.5870),
                         (6.3457, 3.8718, 7.6649), (8.9174, 3.8340, 7.5976),
                         (1.3241, 6.3219, 7.6442), (3.8718, 6.3457, 7.6649),
                         (6.3945, 6.3945, 7.6495), (8.9576, 6.3976, 7.6213),
                         (1.2669, 8.8935, 7.6189), (3.8340, 8.9174, 7.5976),
                         (6.3976, 8.9576, 7.6213), (8.9367, 8.9367, 7.6539),
                         (0.0582, 0.0582, 9.4227), (2.5965, -0.2051, 9.4199),
                         (5.1282, 0.0663, 9.4037), (7.6808, -0.0157, 9.4235),
                         (-0.2051, 2.5965, 9.4199), (2.1913, 2.1913, 9.6123),
                         (5.0046, 2.5955, 9.4873), (7.5409, 2.5336, 9.4126),
                         (0.0663, 5.1282, 9.4037), (2.5955, 5.0046, 9.4873),
                         (5.3381, 5.3381, 9.6106), (7.8015, 5.0682, 9.4237),
                         (-0.0157, 7.6808, 9.4235), (2.5336, 7.5409, 9.4126),
                         (5.0682, 7.8015, 9.4237), (7.6155, 7.6155, 9.4317)])
    c2 = Atoms('C2', [(3.2897, 3.2897, 10.6627), (4.2113, 4.2113, 10.6493)])
    srf.extend(c2)
    srf.pbc = (1, 1, 0)
    srf.set_cell([10.2106, 10.2106, 20.6572], scale_atoms=False)

    mask = [a.index < 32 for a in srf]
    c1 = FixedPlane(-1, (1 / np.sqrt(2), 1 / np.sqrt(2), 1))
    c2 = FixedPlane(-2, (1 / np.sqrt(2), 1 / np.sqrt(2), 1))
    constraint = FixAtoms(mask=mask)
    srf.set_constraint([constraint, c1, c2])
    return srf
예제 #32
0
	def ori_structure(self):
		lead1=self.lead1=graphene(dict(latx=1,laty=self.laty,latz=1)).lmp_structure()
		n=len(lead1)
		center=graphene(dict(latx=self.latx,laty=self.laty,latz=1)).lmp_structure()
		center.translate(lead1.cell[0])
		lead2=lead1.copy()
		lead2.translate(lead1.cell[0]+center.cell[0])
		atoms=Atoms()
		atoms.extend(lead1)
		atoms.extend(center)
		atoms.extend(lead2)
		atoms.cell=center.cell
		atoms.cell[0]=lead1.cell[0]+center.cell[0]+lead2.cell[0]

		lx=self.extent(atoms)[0]
		self.getScale(lx/2)
		self.center_box(atoms)
		self.writeatoms(atoms,'graphene')
		low=atoms.positions[:,0].min()+2
		hi=atoms.positions[:,0].max()-2
		self.leftgroup=np.arange(len(atoms),dtype='int')[:n]+1
		self.rightgroup=np.arange(len(atoms),dtype='int')[-n:]+1
		self.fmag=self.strain/float(len(self.leftgroup))

		self.posleft=atoms.positions[self.leftgroup[0]-1].copy()+(50,50,50)
		self.posright=atoms.positions[self.rightgroup[0]-1].copy()+(50,50,50)
		self.posleft[0]*=10
		self.posright[0]*=10
		for atom in atoms:
			atom.position=self.trans(atom.position)
		atoms.center(vacuum=50)
		return atoms
예제 #33
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    def select_atoms(self, atoms):
        subset = None
        subset_map = {}
        subset_weights = []
        k = 0
        ids = Mixer.get_atom_ids(atoms)
        for i in range(len(atoms)):
            if ids[i] not in self._atom_ids:
                continue

            if not subset:
                subset = Atoms(atoms[i:i + 1])
            else:
                subset.extend(atoms[i:i + 1])

            subset_map[k] = i
            subset_weights.append(self._weights[ids[i]])
            k += 1
        wa = np.zeros((len(subset_weights), 3))
        for i in range(len(subset_weights)):
            wa[i] += subset_weights[i]
        return subset, subset_map, wa
예제 #34
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	def lmp_structure(self):
		ribbon=graphene(dict(latx=20,laty=3,latz=1,gnrtype='zigzag')).lmp_structure()
		
		self.length=ribbon.cell[0,0]
		self.center_box(ribbon)
		self.w=.2
		self.getW(self.length/2)
		newlx=2*self.phase(self.length/2,self.w)
		for atom in ribbon:
			atom.position=self.trans(atom.position)
		atoms=ribbon
		#atoms.center(vacuum=10,axis=[1,2])
		#atoms.cell[0,0]=newlx
		#atoms.center(axis=[0])
		newatoms=Atoms()
		for i in range(4):
			atoms.rotate('z',i*pi/2,center=[0,-newlx/4,0])
			newatoms.extend(atoms.copy())
		newatoms.cell[0,0]=newatoms.cell[1,1]=newlx
		newatoms.center()
		atoms=newatoms#.repeat([self.latx,self.laty,1])
		return atoms
예제 #35
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파일: selector.py 프로젝트: csmm/multiase
    def select_atoms(self, atoms):
        subset = None
        subset_map = {}
        subset_weights = []
        k = 0
        ids = Mixer.get_atom_ids(atoms)
        for i in range(len(atoms)):
            if ids[i] not in self._atom_ids:
                continue

            if not subset:
                subset = Atoms(atoms[i:i+1])
            else:
                subset.extend(atoms[i:i+1])

            subset_map[k] = i
            subset_weights.append(self._weights[ids[i]])
            k += 1
        wa = np.zeros((len(subset_weights), 3))
        for i in range(len(subset_weights)):
            wa[i] += subset_weights[i]
        return subset, subset_map, wa
예제 #36
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    def lmp_structure(self):
        ribbon = graphene(dict(latx=20, laty=3, latz=1,
                               gnrtype='zigzag')).lmp_structure()

        self.length = ribbon.cell[0, 0]
        self.center_box(ribbon)
        self.w = .2
        self.getW(self.length / 2)
        newlx = 2 * self.phase(self.length / 2, self.w)
        for atom in ribbon:
            atom.position = self.trans(atom.position)
        atoms = ribbon
        #atoms.center(vacuum=10,axis=[1,2])
        #atoms.cell[0,0]=newlx
        #atoms.center(axis=[0])
        newatoms = Atoms()
        for i in range(4):
            atoms.rotate('z', i * pi / 2, center=[0, -newlx / 4, 0])
            newatoms.extend(atoms.copy())
        newatoms.cell[0, 0] = newatoms.cell[1, 1] = newlx
        newatoms.center()
        atoms = newatoms  #.repeat([self.latx,self.laty,1])
        return atoms
예제 #37
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파일: glassC.py 프로젝트: vanceeasleaf/aces
    def lmp_structure(self):
        atoms = Atoms()
        unit = graphene(
            dict(
                latx=2,
                laty=1,
                latz=1,
                gnrtype='zigzag')).lmp_structure()
        # del unit[unit.positions[:,0].argsort()[-2:]]
        ly = unit.cell[1][1]
        lidx = unit.positions[:, 0].argsort()[0]
        left_of_unit = unit[lidx].position
        # the center must be assign because the atoms are centered
        unit.rotate('y', 30.0 / 180 * np.pi, center=left_of_unit)
        ridx = unit.positions[:, 0].argsort()[-1]
        right_of_unit = unit[ridx].position
        unit1 = unit.copy()
        unit1.rotate('y', 120.0 / 180 * np.pi, center=right_of_unit)
        ridx1 = unit1.positions[:, 0].argsort()[-1]
        right_of_unit1 = unit1[ridx1].position
        # cell[0,0]
        lx = right_of_unit1[0] - left_of_unit[0]

        unit2 = unit.copy()
        # translate unit2 but don't traslate along y
        deta = right_of_unit1 - right_of_unit + [0, 0, 1.42 * np.sqrt(3) / 2]
        deta[1] = 0
        unit2.translate(deta)
        lidx2 = unit2.positions[:, 0].argsort()[0]
        left_of_unit2 = unit2.positions[lidx2]
        unit3 = unit2.copy()
        unit3.rotate('y', 120.0 / 180 * np.pi, center=left_of_unit2)

        lz = left_of_unit2[2] - right_of_unit[2] + 1.42 * np.sqrt(3) / 2

        atoms.extend(unit)
        atoms.extend(unit1)
        atoms.extend(unit2)
        atoms.extend(unit3)
        atoms.set_cell([lx, ly, lz])
        # important for distance calculation,default all False
        atoms.set_pbc([True] * 3)
        atoms.center()
        atoms = atomic.get_unique_atoms(atoms)

        # prevent xs~=1.0
        atoms.translate([0.01, 0, 0])
        atomic.wrap(atoms)

        return atoms
예제 #38
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파일: lead.py 프로젝트: xiexingzhu/aces
	def lmp_structure(self):
		atoms=Atoms()
		lead1=self.m.lmp_structure()
		self.hatom=len(lead1)
		lead2=lead1.copy()
		lead3=lead1.copy()
		atoms.extend(lead1)
		lead2.translate(lead1.cell[0])
		atoms.extend(lead2)
		lead3.translate(lead1.cell[0]*2)
		atoms.extend(lead3)
		atoms.cell=lead1.cell.copy()
		atoms.cell[0]=lead1.cell[0]*3
		atoms.center()
		return atoms
예제 #39
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파일: lead.py 프로젝트: vanceeasleaf/aces
	def lmp_structure(self):
		atoms=Atoms()
		lead1=self.m.lmp_structure()
		self.hatom=len(lead1)
		lead2=lead1.copy()
		lead3=lead1.copy()
		atoms.extend(lead1)
		lead2.translate(lead1.cell[0])
		atoms.extend(lead2)
		lead3.translate(lead1.cell[0]*2)
		atoms.extend(lead3)
		atoms.cell=lead1.cell.copy()
		atoms.cell[0]=lead1.cell[0]*3
		atoms.center()
		return atoms
예제 #40
0
파일: glassC.py 프로젝트: vanceeasleaf/aces
    def lmp_structure(self):
        atoms = Atoms()
        unit = graphene(dict(latx=2, laty=1, latz=1,
                             gnrtype='zigzag')).lmp_structure()
        # del unit[unit.positions[:,0].argsort()[-2:]]
        ly = unit.cell[1][1]
        lidx = unit.positions[:, 0].argsort()[0]
        left_of_unit = unit[lidx].position
        # the center must be assign because the atoms are centered
        unit.rotate('y', 30.0 / 180 * np.pi, center=left_of_unit)
        ridx = unit.positions[:, 0].argsort()[-1]
        right_of_unit = unit[ridx].position
        unit1 = unit.copy()
        unit1.rotate('y', 120.0 / 180 * np.pi, center=right_of_unit)
        ridx1 = unit1.positions[:, 0].argsort()[-1]
        right_of_unit1 = unit1[ridx1].position
        # cell[0,0]
        lx = right_of_unit1[0] - left_of_unit[0]

        unit2 = unit.copy()
        # translate unit2 but don't traslate along y
        deta = right_of_unit1 - right_of_unit + [0, 0, 1.42 * np.sqrt(3) / 2]
        deta[1] = 0
        unit2.translate(deta)
        lidx2 = unit2.positions[:, 0].argsort()[0]
        left_of_unit2 = unit2.positions[lidx2]
        unit3 = unit2.copy()
        unit3.rotate('y', 120.0 / 180 * np.pi, center=left_of_unit2)

        lz = left_of_unit2[2] - right_of_unit[2] + 1.42 * np.sqrt(3) / 2

        atoms.extend(unit)
        atoms.extend(unit1)
        atoms.extend(unit2)
        atoms.extend(unit3)
        atoms.set_cell([lx, ly, lz])
        # important for distance calculation,default all False
        atoms.set_pbc([True] * 3)
        atoms.center()
        atoms = atomic.get_unique_atoms(atoms)

        # prevent xs~=1.0
        atoms.translate([0.01, 0, 0])
        atomic.wrap(atoms)

        return atoms
예제 #41
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파일: device.py 프로젝트: vanceeasleaf/aces
	def lmp_structure(self):
		atoms=Atoms()
		lead1=self.m1.lmp_structure()
		center=self.m.lmp_structure()
		lead2=self.m2.lmp_structure()
		atoms.extend(lead1)
		center.translate(lead1.cell[0])
		atoms.extend(center)
		lead2.translate(lead1.cell[0]+center.cell[0])
		atoms.extend(lead2)
		atoms.cell=lead1.cell.copy()
		#atoms.set_pbc([0,0,0])
		atoms.cell[0]=lead1.cell[0]+center.cell[0]+lead2.cell[0]
		#atoms.center(10.0,axis=[1,2])
		#atoms.center()
		x=atoms.positions[:,0]

		return center
예제 #42
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    def lmp_structure(self):
        atoms = Atoms()
        lead1 = self.m1.lmp_structure()
        center = self.m.lmp_structure()
        lead2 = self.m2.lmp_structure()
        atoms.extend(lead1)
        center.translate(lead1.cell[0])
        atoms.extend(center)
        lead2.translate(lead1.cell[0] + center.cell[0])
        atoms.extend(lead2)
        atoms.cell = lead1.cell.copy()
        #atoms.set_pbc([0,0,0])
        atoms.cell[0] = lead1.cell[0] + center.cell[0] + lead2.cell[0]
        #atoms.center(10.0,axis=[1,2])
        #atoms.center()
        x = atoms.positions[:, 0]

        return center
예제 #43
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    def ori_structure(self):
        lead1 = self.lead1 = graphene(dict(latx=1, laty=self.laty,
                                           latz=1)).lmp_structure()
        n = len(lead1)
        center = graphene(dict(latx=self.latx, laty=self.laty,
                               latz=1)).lmp_structure()
        center.translate(lead1.cell[0])
        lead2 = lead1.copy()
        lead2.translate(lead1.cell[0] + center.cell[0])
        atoms = Atoms()
        atoms.extend(lead1)
        atoms.extend(center)
        atoms.extend(lead2)
        atoms.cell = center.cell
        atoms.cell[0] = lead1.cell[0] + center.cell[0] + lead2.cell[0]

        lx = self.extent(atoms)[0]
        self.getScale(lx / 2)
        self.center_box(atoms)
        self.writeatoms(atoms, 'graphene')
        low = atoms.positions[:, 0].min() + 2
        hi = atoms.positions[:, 0].max() - 2
        self.leftgroup = np.arange(len(atoms), dtype='int')[:n] + 1
        self.rightgroup = np.arange(len(atoms), dtype='int')[-n:] + 1
        self.fmag = self.strain / float(len(self.leftgroup))

        self.posleft = atoms.positions[self.leftgroup[0] - 1].copy() + (50, 50,
                                                                        50)
        self.posright = atoms.positions[self.rightgroup[0] -
                                        1].copy() + (50, 50, 50)
        self.posleft[0] *= 10
        self.posright[0] *= 10
        for atom in atoms:
            atom.position = self.trans(atom.position)
        atoms.center(vacuum=50)
        return atoms
예제 #44
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파일: eval_energy2.py 프로젝트: uw-cmg/MAST
def eval_energy(input):
    """Function to evaluate energy of an individual
    Inputs:
        input = [Optimizer class object with parameters, Individual class structure to be evaluated]
    Outputs:
        energy, bul, individ, signal
        energy = energy of Individual evaluated
        bul = bulk structure of Individual if simulation structure is Defect
        individ = Individual class structure evaluated
        signal = string of information about evaluation
    """
    if input[0]==None:
        energy=0
        bul=0
        individ=0
        rank = MPI.COMM_WORLD.Get_rank()
        signal='Evaluated none individual on '+repr(rank)+'\n'
    else:
        [Optimizer, individ]=input
    if Optimizer.calc_method=='MAST':
        energy = individ.energy
        bul = individ.energy
        signal = 'Recieved MAST structure\n'
    else:
        if Optimizer.parallel: rank = MPI.COMM_WORLD.Get_rank()
        if not Optimizer.genealogy:
            STR='----Individual ' + str(individ.index)+ ' Optimization----\n'
        else:
            STR='----Individual ' + str(individ.history_index)+ ' Optimization----\n'
        indiv=individ[0]
        if 'EE' in Optimizer.debug:
            debug = True
        else:
            debug = False
        if debug: 
            write_xyz(Optimizer.debugfile,indiv,'Recieved by eval_energy')
            Optimizer.debugfile.flush()
        if Optimizer.structure=='Defect':
            indi=indiv.copy()
            if Optimizer.alloy==True:
                bulk=individ.bulki
            else:
                bulk=individ.bulko
            nat=indi.get_number_of_atoms()
            csize=bulk.get_cell()                                                                                                         
            totalsol=Atoms(cell=csize, pbc=True)
            totalsol.extend(indi)
            totalsol.extend(bulk)
            for sym,c,m,u in Optimizer.atomlist:
                nc=len([atm for atm in totalsol if atm.symbol==sym])
                STR+='Defect configuration contains '+repr(nc)+' '+repr(sym)+' atoms\n'
    
        elif Optimizer.structure=='Surface':
            totalsol=Atoms()
            totalsol.extend(indiv)
            nat=indiv.get_number_of_atoms()
            totalsol.extend(individ.bulki)
            for sym,c,m,u in Optimizer.atomlist:
                nc=len([atm for atm in totalsol if atm.symbol==sym])
                STR+='Surface-Bulk configuration contains '+repr(nc)+' '+repr(sym)+' atoms\n'
            cell=numpy.maximum.reduce(indiv.get_cell())
            totalsol.set_cell([cell[0],cell[1],500])
            totalsol.set_pbc([True,True,False])
    
        if Optimizer.constrain_position:
            ts = totalsol.copy()
            indc,indb,vacant,swap,stro = find_defects(ts,Optimizer.solidbulk,0)
            sbulk = Optimizer.solidbulk.copy()
            bcom = sbulk.get_center_of_mass()
            #totalsol.translate(-bulkcom)
            #indc.translate(-bulkcom)
            #totalsol.append(Atom(position=[0,0,0]))
    # 			for one in indc:
    # 				index = [atm.index for atm in totalsol if atm.position[0]==one.position[0] and atm.position[1]==one.position[1] and atm.position[2]==one.position[2]][0]
    # 				if totalsol.get_distance(-1,index) > Optimizer.sf:
    # 					r = random.random()
    # 					totalsol.set_distance(-1,index,Optimizer.sf*r,fix=0)
    # 			totalsol.pop()
    # 			totalsol.translate(bulkcom)
            com = indc.get_center_of_mass()
            dist = (sum((bcom[i] - com[i])**2 for i in range(3)))**0.5
            if dist > Optimizer.sf:
                STR+='Shifting structure to within region\n'
                r = random.random()*Optimizer.sf
                comv = numpy.linalg.norm(com)
                ncom = [one*r/comv for one in com]
                trans = [ncom[i]-com[i] for i in range(3)]
                indices = []
                for one in indc:
                    id = [atm.index for atm in totalsol if atm.position[0]==one.position[0] and atm.position[1]==one.position[1] and atm.position[2]==one.position[2]][0]
                    totalsol[id].position += trans
    
        # Check for atoms that are too close
        min_len=0.7
        #pdb.set_trace()
        if not Optimizer.fixed_region:
            if Optimizer.structure=='Defect' or Optimizer.structure=='Surface':
                cutoffs=[2.0 for one in totalsol]
                nl=NeighborList(cutoffs,bothways=True,self_interaction=False)
                nl.update(totalsol)
                for one in totalsol[0:nat]:
                    nbatoms=Atoms()
                    nbatoms.append(one)
                    indices, offsets=nl.get_neighbors(one.index)
                    for index, d in zip(indices,offsets):
                        index = int(index)
                        sym=totalsol[index].symbol
                        pos=totalsol[index].position + numpy.dot(d,totalsol.get_cell())
                        at=Atom(symbol=sym,position=pos)
                        nbatoms.append(at)
                    while True:
                        dflag=False
                        for i in range(1,len(nbatoms)):
                            d=nbatoms.get_distance(0,i)
                            if d < min_len:
                                nbatoms.set_distance(0,i,min_len+.01,fix=0.5)
                                STR+='--- WARNING: Atoms too close (<0.7A) - Implement Move ---\n'
                                dflag=True
                        if dflag==False:
                            break
                    for i in range(len(indices)):
                        totalsol[indices[i]].position=nbatoms[i+1].position
                    totalsol[one.index].position=nbatoms[0].position
                    nl.update(totalsol)
                if debug:
                    write_xyz(Optimizer.debugfile,totalsol,'After minlength check')
                    Optimizer.debugfile.flush()
            else:
                for i in range(len(indiv)):
                    for j in range(len(indiv)):
                        if i != j:
                            d=indiv.get_distance(i,j)
                            if d < min_len:
                                indiv.set_distance(i,j,min_len,fix=0.5)
                                STR+='--- WARNING: Atoms too close (<0.7A) - Implement Move ---\n'
                if debug:
                    write_xyz(Optimizer.debugfile,indiv,'After minlength check')
                    Optimizer.debugfile.flush()
    
        # Set calculator to use to get forces/energies
        if Optimizer.parallel:
            calc = setup_calculator(Optimizer)
            if Optimizer.fixed_region:
                pms=copy.deepcopy(calc.parameters)
                try:
                    pms['mass'][len(pms['mass'])-1] += '\ngroup RO id >= '+repr(nat)+'\nfix freeze RO setforce 0.0 0.0 0.0\n'
                except KeyError:
                    pms['pair_coeff'][0] += '\ngroup RO id >= '+repr(nat)+'\nfix freeze RO setforce 0.0 0.0 0.0\n'
                calc = LAMMPS(parameters=pms, files=calc.files, keep_tmp_files=calc.keep_tmp_files, tmp_dir=calc.tmp_dir)
                lmin = copy.copy(Optimizer.lammps_min)
                Optimizer.lammps_min = None
                Optimizer.static_calc = setup_calculator(Optimizer)
                Optimizer.lammps_min = lmin
        else:
            calc=Optimizer.calc
        if Optimizer.structure=='Defect' or Optimizer.structure=='Surface':
            totalsol.set_calculator(calc)
            totalsol.set_pbc(True)
        else:
            indiv.set_calculator(calc)
            indiv.set_pbc(True)	#Current bug in ASE optimizer-Lammps prevents pbc=false 
            if Optimizer.structure=='Cluster':
                indiv.set_cell([500,500,500])
                indiv.translate([250,250,250])
    
        cwd=os.getcwd()
        # Perform Energy Minimization
        if not Optimizer.parallel:
            Optimizer.output.flush()
        if Optimizer.ase_min == True:
            try:
                if Optimizer.structure=='Defect' or Optimizer.structure=='Surface':
                    dyn=BFGS(totalsol)
                else:
                    dyn=BFGS(indiv)
                dyn.run(fmax=Optimizer.ase_min_fmax, steps=Optimizer.ase_min_maxsteps)
            except OverflowError:
                STR+='--- Error: Infinite Energy Calculated - Implement Random ---\n'
                box=Atoms()
                indiv=gen_pop_box(Optimizer.natoms, Optimizer.atomlist, Optimizer.size)
                indiv.set_calculator(calc)
                dyn=BFGS(indiv)
                dyn.run(fmax=fmax, steps=steps)
            except numpy.linalg.linalg.LinAlgError:
                STR+='--- Error: Singular Matrix - Implement Random ---\n'
                indiv=gen_pop_box(Optimizer.natoms, Optimizer.atomlist, Optimizer.size)
                indiv.set_calculator(calc)
                dyn=BFGS(indiv)
                dyn.run(fmax=fmax, steps=steps)
            # Get Energy of Minimized Structure
            if Optimizer.structure=='Defect' or Optimizer.structure=='Surface':
                en=totalsol.get_potential_energy()
                #force=numpy.maximum.reduce(abs(totalsol.get_forces()))
                if Optimizer.fitness_scheme == 'enthalpyfit':
                    pressure=totalsol.get_isotropic_pressure(totalsol.get_stress())
                    cell_max=numpy.maximum.reduce(totalsol.get_positions())
                    cell_min=numpy.minimum.reduce(totalsol.get_positions())
                    cell=cell_max-cell_min
                    volume=cell[0]*cell[1]*cell[2]
                else:
                    pressure=0
                    volume=0
                na=totalsol.get_number_of_atoms()
                ena=en/na
                energy=en
                individ[0]=totalsol[0:nat]
                bul=totalsol[(nat):len(totalsol)]
                STR+='Number of positions = '+repr(len(bul)+len(individ[0]))+'\n'
                individ[0].set_cell(csize)
                indiv=individ[0]
            else:
                en=indiv.get_potential_energy()
                if Optimizer.fitness_scheme == 'enthalpyfit':
                    pressure=indiv.get_isotropic_pressure(indiv.get_stress())
                    cell_max=numpy.maximum.reduce(indiv.get_positions())
                    cell_min=numpy.minimum.reduce(indiv.get_positions())
                    cell=cell_max-cell_min
                    volume=cell[0]*cell[1]*cell[2]
                else: 
                    pressure=0
                    volume=0
                na=indiv.get_number_of_atoms()
                ena=en/na
                energy=ena
                individ[0]=indiv
                bul=0
        else:
            if Optimizer.structure=='Defect' or Optimizer.structure=='Surface':
                if Optimizer.calc_method=='VASP':
                    en=totalsol.get_potential_energy()
                    calcb=Vasp(restart=True)
                    totalsol=calcb.get_atoms()
                    stress=calcb.read_stress()
                else:
                    try:
                        totcop=totalsol.copy()
                        if debug: write_xyz(Optimizer.debugfile,totcop,'Individual sent to lammps')
                        OUT=totalsol.calc.calculate(totalsol)
                        totalsol=OUT['atoms']
                        totalsol.set_pbc(True)
                        if Optimizer.fixed_region:
                            if debug:
                                print 'Energy of fixed region calc = ', OUT['thermo'][-1]['pe']
                            totalsol.set_calculator(Optimizer.static_calc)
                            OUT=totalsol.calc.calculate(totalsol)
                            totalsol=OUT['atoms']
                            totalsol.set_pbc(True)
                            if debug:
                                print 'Energy of static calc = ', OUT['thermo'][-1]['pe']
                        en=OUT['thermo'][-1]['pe']
                        stress=numpy.array([OUT['thermo'][-1][i] for i in ('pxx','pyy','pzz','pyz','pxz','pxy')])*(-1e-4*GPa)
                        #force=numpy.maximum.reduce(abs(totalsol.get_forces()))
                        if debug:
                            write_xyz(Optimizer.debugfile,totalsol,'After Lammps Minimization')
                            Optimizer.debugfile.flush()
                    except Exception, e:
                        os.chdir(cwd)
                        STR+='WARNING: Exception during energy eval:\n'+repr(e)+'\n'
                        f=open('problem-structures.xyz','a')
                        write_xyz(f,totcop,data='Starting structure hindex='+individ.history_index)
                        write_xyz(f,totalsol,data='Lammps Min structure')
                        en=10
                        stress=0
                        f.close()
                if Optimizer.fitness_scheme == 'enthalpyfit':
                    pressure=totalsol.get_isotropic_pressure(stress)
                    cell_max=numpy.maximum.reduce(totalsol.get_positions())
                    cell_min=numpy.minimum.reduce(totalsol.get_positions())
                    cell=cell_max-cell_min
                    volume=cell[0]*cell[1]*cell[2]
                else:
                    pressure=totalsol.get_isotropic_pressure(stress)
                    volume=0
                na=totalsol.get_number_of_atoms()
                ena=en/na
                energy=en
                if Optimizer.structure=='Defect':
                    if Optimizer.fixed_region==True or Optimizer.finddefects==False:
                        individ[0]=totalsol[0:nat]
                        bul=totalsol[(nat):len(totalsol)]
                        individ[0].set_cell(csize)
                    else:
                        if 'FI' in Optimizer.debug:
                            outt=find_defects(totalsol,Optimizer.solidbulk,Optimizer.sf,atomlistcheck=Optimizer.atomlist,trackvacs=Optimizer.trackvacs,trackswaps=Optimizer.trackswaps,debug=Optimizer.debugfile)
                        else:
                            outt=find_defects(totalsol,Optimizer.solidbulk,Optimizer.sf,atomlistcheck=Optimizer.atomlist,trackvacs=Optimizer.trackvacs,trackswaps=Optimizer.trackswaps,debug=False)
                        individ[0]=outt[0]
                        bul=outt[1]
                        individ.vacancies = outt[2]
                        individ.swaps = outt[3]
                        STR += outt[4]
                    indiv=individ[0]
                else:
                    top,bul=find_top_layer(totalsol,Optimizer.surftopthick)
                    indiv=top.copy()
                    individ[0]=top.copy()
            else:
예제 #45
0
def rotct_rand(ind1, ind2, Optimizer):
    """Rotate atoms cut and splice
    Rotates atoms randomly around center of mass and cuts with xy plane
    Maintains number of atoms
    Maintains concentration of atoms
    Returns individuals to standard positions at end (un-rotates)
    """
    if 'CX' in Optimizer.debug:
        debug = True
    else:
        debug = False
    Optimizer.output.write('Random Rotate Cut/Splice Cx between individual '+repr(ind1.index)+' and individual '+repr(ind2.index)+'\n')
    
    #Perserve starting conditions of individual
    indi1 = ind1[0].copy()
    indi2 =ind2[0].copy()
    #Translate individuals so COM is at (0,0,0)
    com1 = indi1.get_center_of_mass()
    indi1.translate(-1*com1)
    com2 = indi2.get_center_of_mass()
    indi2.translate(-1*com2)
    #Select random axis, random angle, and random position and rotate individuals
    cmax = [min(numpy.maximum.reduce(indi1.get_positions())[i],numpy.maximum.reduce(indi2.get_positions())[i]) for i in range(3)]
    cmin = [min(numpy.minimum.reduce(indi1.get_positions())[i],numpy.minimum.reduce(indi2.get_positions())[i]) for i in range(3)]
    n=0
    while n<10:
        rax = random.choice(['x', '-x','y','-y','z','-z'])
        rang = random.random()*90
        rpos = [random.uniform(cmin[i]*0.8,cmax[i]*0.8) for i in range(3)]
        indi1.rotate(rax,a=rang,center=rpos,rotate_cell=False)
        #Search for atoms in individual 1 that are above the xy plane
        group1 = Atoms(cell=ind1[0].get_cell(),pbc=ind1[0].get_pbc())
        indices1=[]
        for one in indi1:
            if one.position[2] >= 0:
                group1.append(one)
                indices1.append(one.index)
        if len(group1) > 2 and len(group1) < len(indi1):
            break
        else:
            n+=1
            indi1.rotate(rax,a=-1*rang,center=rpos, rotate_cell=False)
    indi2.rotate(rax,a=rang,center=rpos,rotate_cell=False)
    if debug: 
        print 'Group1 size = ', len(group1)
        print 'Position = ', rpos
        print 'Angle = ', rang
        print 'Axis = ', rax
        print 'Number of tries = ', n
    if len(group1) != 0:
        #Apply concentration forcing if needed
        group2 = Atoms(cell=ind2[0].get_cell(),pbc=ind2[0].get_pbc())
        indices2 = []
        dellist = []
        for one in indi2:
            if one.position[2] >= 0:
                group2.append(one)
                indices2.append(one.index)
        if Optimizer.forcing=='Concentration':
            symlist = list(set(indi1.get_chemical_symbols()))
            seplist = [[atm for atm in group2 if atm.symbol == sym] for sym in symlist]
            group2n=Atoms(cell=group2.get_cell(),pbc=group2.get_pbc())
            indices2n = []
            dellist = []
            for one in group1:
                sym1=one.symbol
                listpos=[i for i,s in enumerate(symlist) if s==sym1][0]
                if len(seplist[listpos]) > 0:
                    pos = random.choice(range(len(seplist[listpos])))
                    group2n.append(seplist[listpos][pos])
                    indices2n.append(indices2[seplist[listpos][pos].index])
                    del seplist[listpos][pos]
                else:
                    dellist.append(one.index)
            if len(dellist) != 0:
                dellist.sort(reverse=True)
                for one in dellist:
                    del group1[one]
                    del indices1[one]
            indices2=indices2n
            group2=group2n.copy()
        else:
            dellist = []
            while len(group2) < len(group1)-len(dellist):
                #Too many atoms in group 1
                dellist.append(random.choice(group1).index)
            if len(dellist) != 0:
                dellist.sort(reverse=True)
                for one in dellist:
                    del group1[one]
                    del indices1[one]
            dellist = []
            while len(group1) < len(group2)-len(dellist):
                #Too many atoms in group 2
                dellist.append(random.choice(group2).index)
            if len(dellist) != 0:
                dellist.sort(reverse=True)
                for one in dellist:
                    del group2[one]
                    del indices2[one]
    
        other2 = Atoms(cell=ind2[0].get_cell(),pbc=ind2[0].get_pbc())
        for one in indi2:
            if one.index not in indices2:
                other2.append(one)
        other1 = Atoms(cell=ind1[0].get_cell(),pbc=ind1[0].get_pbc())
        for one in indi1:
            if one.index not in indices1:
                other1.append(one)
        indi1 = group2.copy()
        indi1.extend(other1)
        indi2 = group1.copy()
        indi2.extend(other2)
    
        #DEBUG: Write crossover to file
        if debug: 
            write_xyz(Optimizer.debugfile, group1,'group1')
            write_xyz(Optimizer.debugfile, other1,'other1')
            write_xyz(Optimizer.debugfile, group2,'group2')
            write_xyz(Optimizer.debugfile, other2,'other2')
            print 'Length of group1 = ',len(group1),'Length of group2',len(group2)
    
        #DEBUG: Check structure of atoms exchanged
        for sym,c,m,u in Optimizer.atomlist:
            nc=len([atm for atm in indi1 if atm.symbol==sym])
            Optimizer.output.write('CX RANDROTCT: Individual 1 contains '+repr(nc)+' '+repr(sym)+' atoms\n')
            nc=len([atm for atm in indi2 if atm.symbol==sym])
            Optimizer.output.write('CX RANDROTCT: Individual 2 contains '+repr(nc)+' '+repr(sym)+' atoms\n')
        if Optimizer.forcing !='Concentration':
            for i in range(len(Optimizer.atomlist)):
                atms1=[inds for inds in indi1 if inds.symbol==Optimizer.atomlist[i][0]]
                atms2=[inds for inds in indi2 if inds.symbol==Optimizer.atomlist[i][0]]
                if len(atms1)==0:
                    if len(atms2)==0:
                        indi1[random.randint(0,len(indi1)-1)].symbol==Optimizer.atomlist[i][0]
                        indi2[random.randint(0,len(indi2)-1)].symbol==Optimizer.atomlist[i][0]
                    else:
                        indi1.append(atms2[random.randint(0,len(atms2)-1)])
                        indi1.pop(random.randint(0,len(indi1)-2))
                else:
                    if len(atms2)==0:
                        indi2.append(atms1[random.randint(0,len(atms1)-1)])
                        indi2.pop(random.randint(0,len(indi2)-2))	
        indi1.rotate(rax,a=-1*rang,center=rpos, rotate_cell=False)
        indi2.rotate(rax,a=-1*rang,center=rpos, rotate_cell=False)
        indi1.translate(com1)
        indi2.translate(com2)
    
    #DEBUG: Check structure and number of atoms in crystal
    if Optimizer.structure=='Defect':
        solid1=Atoms()
        solid1.extend(indi1)
        solid1.extend(ind1.bulki)
        solid2=Atoms()
        solid2.extend(indi2)
        solid2.extend(ind2.bulki)
        for sym,c,m,u in Optimizer.atomlist:
            nc=len([atm for atm in solid1 if atm.symbol==sym])
            Optimizer.output.write('CX RANDROTCT: Defect 1 configuration contains '+repr(nc)+' '+repr(sym)+' atoms\n')
            nc=len([atm for atm in solid2 if atm.symbol==sym])
            Optimizer.output.write('CX RANDROTCT: Defect 2 configuration contains '+repr(nc)+' '+repr(sym)+' atoms\n')
    if debug: Optimizer.output.flush()
    #pdb.set_trace()
    ind1[0]=indi1
    ind2[0]=indi2
    
    return ind1, ind2
예제 #46
0
def eval_energy(Optimizer, individ):
    """Function to evaluate energy of an individual
    Inputs:
        input = [Optimizer class object with parameters, Individual class structure to be evaluated]
    Outputs:
        energy, bul, individ, signal
        energy = energy of Individual evaluated
        bul = bulk structure of Individual if simulation structure is Defect
        individ = Individual class structure evaluated
        signal = string of information about evaluation
    """
    #logger = initialize_logger(Optimizer.loggername)
    logger = logging.getLogger(Optimizer.loggername)
    if 'MAST' in Optimizer.calc_method:
        energy = individ.energy
        bul = individ.bulki
        signal = 'Received MAST structure\n'
        logger.info('Received individual index = {0} from MAST with energy {1}. Returning with no evaluation'.format(
            individ.index, individ.energy))
    else:
        if Optimizer.parallel: 
            rank = MPI.COMM_WORLD.Get_rank()
        logger.info('Received individual HI = {0} with energy {1} for energy evaluation'.format(
            individ.history_index, individ.energy))
        STR='----Individual ' + str(individ.history_index)+ ' Optimization----\n'
        indiv=individ[0]
        if 'EE' in Optimizer.debug:
            debug = True
        else:
            debug = False
        if debug: 
            write_xyz(Optimizer.debugfile,indiv,'Received by eval_energy')
            Optimizer.debugfile.flush()
            logger.debug('Writing recieved individual to debug file')
        # Establish individual structure for evaluation.  Piece together regions when necessary.
        if Optimizer.structure=='Defect':
            indi=indiv.copy()
            bulk=individ.bulki
            nat=indi.get_number_of_atoms()
            if debug: 
                logger.info('Extending defect structure to include bulk len(r1+r2)={0} len(bulk)={1}'.format(nat,len(bulk)))
            csize=bulk.get_cell()                                                                                                         
            totalsol=Atoms(cell=csize, pbc=True)
            totalsol.extend(indi)
            totalsol.extend(bulk)
            for sym,c,m,u in Optimizer.atomlist:
                nc=len([atm for atm in totalsol if atm.symbol==sym])
                STR+='Defect configuration contains '+repr(nc)+' '+repr(sym)+' atoms\n'
        elif Optimizer.structure=='Surface':
            totalsol=Atoms()
            totalsol.extend(indiv)
            nat=indiv.get_number_of_atoms()
            totalsol.extend(individ.bulki)
            if debug:
                logger.info('Extending surface structure to include bulk len(r1+r2)={0} len(bulk)={1}'.format(nat,len(individ.bulki)))
            for sym,c,m,u in Optimizer.atomlist:
                nc=len([atm for atm in totalsol if atm.symbol==sym])
                STR+='Surface-Bulk configuration contains '+repr(nc)+' '+repr(sym)+' atoms\n'
            cell=numpy.maximum.reduce(indiv.get_cell())
            totalsol.set_cell([cell[0],cell[1],500])
            totalsol.set_pbc([True,True,False])
        elif Optimizer.structure=='Cluster':
            totalsol = indiv.copy()
            nat = len(totalsol)
            if debug:
                logger.info('Extending cluster with {0} atoms to center of evaluation box of size {1}'.format(nat,Optimizer.large_box_size))
            origcell = indiv.get_cell()
            totalsol.set_cell([Optimizer.large_box_size,Optimizer.large_box_size,Optimizer.large_box_size])
            totalsol.translate([Optimizer.large_box_size/2.0,Optimizer.large_box_size/2.0,Optimizer.large_box_size/2.0])
        elif Optimizer.structure=='Crystal':
            totalsol = indiv.copy()
            nat = len(totalsol)
        else:
            print 'WARNING: In EvalEnergy. Optimizer.structure not recognized'
            logger.warning('Optimizer.structure not recognized')
        
        # Check for atoms that are too close or out of constrained location
        if Optimizer.constrain_position:
            if Optimizer.structure=='Defect':
                if debug:
                    logger.info('Constraining positions of defect')
                totalsol, stro = constrain_positions(totalsol, Optimizer.solidbulk, Optimizer.sf)
                if debug:
                    logger.info(stro)
                STR+=str0
        min_len=0.7
        if not Optimizer.fixed_region:
            if debug:
                logger.info('Running check minimum distance')
            totalsol, STR = check_min_dist(totalsol, Optimizer.structure, nat, min_len, STR)
            if debug:
                write_xyz(Optimizer.debugfile,totalsol,'After minlength check')
                Optimizer.debugfile.flush()
                logger.debug('Writing individual after checking minimum length')
        
        # Set calculator to use to get forces/energies
        if Optimizer.parallel:
            calc = setup_calculator(Optimizer)
            if Optimizer.fixed_region:
                if debug:
                    logger.info('Setting up fixed region calculator')
                pms=copy.deepcopy(calc.parameters)
                try:
                    pms['mass'][len(pms['mass'])-1] += '\ngroup RO id >= {0}\nfix freeze RO setforce 0.0 0.0 0.0\n'.format(nat)
                except KeyError:
                    pms['pair_coeff'][0] += '\ngroup RO id >= {0}\nfix freeze RO setforce 0.0 0.0 0.0\n'.format(nat)
                calc = LAMMPS(parameters=pms, files=calc.files, keep_tmp_files=calc.keep_tmp_files, tmp_dir=calc.tmp_dir)
                lmin = copy.copy(Optimizer.lammps_min)
                if debug:
                    logger.info('Setting up no local minimization calculator')
                Optimizer.lammps_min = None
                Optimizer.static_calc = setup_calculator(Optimizer)
                Optimizer.lammps_min = lmin
        else:
            calc=Optimizer.calc
        totalsol.set_calculator(calc)
        totalsol.set_pbc(True)
        
        # Perform Energy Minimization
        if not Optimizer.parallel:
            if debug: 
                write_xyz(Optimizer.debugfile,totalsol,'Individual sent to Energy Minimizer')
                logger.debug('Writing structure sent to energy minimizer')
        try:
            cwd = os.getcwd()
            if Optimizer.ase_min == True:
                if debug:
                    logger.info('Running ASE minimizer')
                if Optimizer.calc_method=='LennardJones':
                    logger.warn('Must run ase LJ calculator with pbc=False')
                    totalsol.set_pbc(False)
                totalsol, energy, pressure, volume, STR = run_ase_min(totalsol, Optimizer.ase_min_fmax, Optimizer.ase_min_maxsteps, Optimizer.fitness_scheme, STR)
            else:
                if debug:
                    logger.info('Running local energy calculator')
                if Optimizer.fixed_region:
                    totalsol, energy, pressure, volume, STR = run_energy_eval(totalsol, Optimizer.calc_method, Optimizer.fixed_region, Optimizer.fitness_scheme, STR, Optimizer.static_calc)
                else:
                    totalsol, energy, pressure, volume, STR = run_energy_eval(totalsol, Optimizer.calc_method, False, Optimizer.fitness_scheme, STR)
        except Exception, e:
            logger.critical('Error in energy evaluation: {0}'.format(e), exc_info=True)
            path = os.path.join(cwd,'TroubledLammps')
            if not os.path.exists(path):
                os.mkdir(path)
            #Copy files over
            shutil.copyfile(calc.trajfile,os.path.join(path,os.path.basename(calc.trajfile)))
            shutil.copyfile(calc.infile,os.path.join(path,os.path.basename(calc.infile)))
            shutil.copyfile(calc.logfile,os.path.join(path,os.path.basename(calc.logfile)))
            shutil.copyfile(calc.datafile,os.path.join(path,os.path.basename(calc.datafile)))
            raise RuntimeError('{0}:{1}'.format(Exception,e))
        if not Optimizer.parallel:
            if debug:
                write_xyz(Optimizer.debugfile,totalsol,'Individual after Energy Minimization')
                Optimizer.debugfile.flush()
                logger.debug('Writing structure recieved from energy minimizer')
       
        # Separate structures into distinct pieces
        if Optimizer.structure=='Defect':
            if Optimizer.fixed_region==True or Optimizer.finddefects==False:
                if debug:
                    logger.info('Identifying atoms in defect structure based on ID')
                individ[0]=totalsol[0:nat]
                bul=totalsol[(nat):len(totalsol)]
                individ[0].set_cell(csize)
            else:
                if debug:
                    logger.info('Applying find defects scheme to identify R1 and R2 for Defect')
                if 'FD' in Optimizer.debug:
                    outt=find_defects(totalsol,Optimizer.solidbulk,Optimizer.sf,atomlistcheck=Optimizer.atomlist,trackvacs=Optimizer.trackvacs,trackswaps=Optimizer.trackswaps,debug=Optimizer.debugfile)
                else:
                    outt=find_defects(totalsol,Optimizer.solidbulk,Optimizer.sf,atomlistcheck=Optimizer.atomlist,trackvacs=Optimizer.trackvacs,trackswaps=Optimizer.trackswaps,debug=False)
                individ[0]=outt[0]
                bul=outt[1]
                individ.vacancies = outt[2]
                individ.swaps = outt[3]
                STR += outt[4]
            indiv=individ[0]
        elif Optimizer.structure=='Surface':
            if debug:
                logger.info('Finding surface top layer')
            top,bul=find_top_layer(totalsol,Optimizer.surftopthick)
            indiv=top.copy()
            individ[0]=top.copy()
            bul = Atoms()
        elif Optimizer.structure=='Crystal':
            if debug:
                logger.info('Checking crystal cell type')
            celltype = check_cell_type(totalsol)
            STR+='Cell structure = {0}\n'.format(celltype)
            bul = Atoms()
            individ[0] = totalsol.copy()
        elif Optimizer.structure=='Cluster':
            volume = get_cluster_volume(totalsol)
            bul = Atoms()
            if debug:
                logger.info('Translating cluster back to smaller box size location')
            totalsol.translate([-Optimizer.large_box_size/2.0,-Optimizer.large_box_size/2.0,-Optimizer.large_box_size/2.0])
            totalsol.set_cell(origcell)
            individ[0] = totalsol.copy()
        
        # Add concentration energy dependence
        if Optimizer.forcing=='energy_bias':
            if debug:
                logger.info('Applying energy bias for atoms with different number of atoms of type than in atomlist')
            n=[0]*len(Optimizer.atomlist)
            for i in range(len(Optimizer.atomlist)):
                n[i]=len([inds for inds in totalsol if inds.symbol==Optimizer.atomlist[i][0]])
                n[i]=abs(n[i]-Optimizer.atomlist[i][1])
            factor=sum(n)**3
            energy=(energy+factor)/totalsol.get_number_of_atoms()
            STR+='Energy with Bias = {0}\n'.format(energy)
        elif Optimizer.forcing=='chem_pot':
            if debug:
                logger.info('Applying chemical potential bias for atoms with different number of atoms of type than in atomlist')
            n=[0]*len(Optimizer.atomlist)
            for i in range(len(Optimizer.atomlist)):
                n[i]=len([inds for inds in totalsol if inds.symbol==Optimizer.atomlist[i][0]])
                n[i]=n[i]*Optimizer.atomlist[i][3]
            factor=sum(n)
            energy=(energy+factor)/totalsol.get_number_of_atoms()
            STR+='Energy with Chemical Potential = {0}\n'.format(energy)

        individ.energy=energy
        individ.buli=bul
        individ.pressure=pressure
        individ.volume=volume
    
        if Optimizer.fingerprinting:
            if debug:
                logger.info('Identifying fingerprint of new structure')
            individ.fingerprint=get_fingerprint(Optimizer,individ,Optimizer.fpbin,Optimizer.fpcutoff)
        if Optimizer.parallel:
            calc.clean()
            signal = 'Evaluated individual {0} on {1}\n'.format(individ.index,rank)
            signal +=STR
        else:
            signal=STR
예제 #47
0
        fit = 10000
        message = 'Warning: Found oddly large energy from Lammps in structure HI={0}'.format(
            indiv.history_index)
        logger.warn(message)
        print message
        print '    Setting fitness to 10000'
        passflag = False
    if math.isnan(fit):
        logger.warn('Found NAN energy structure HI={0}'.format(
            indiv.history_index))
        fit = 10000
        passflag = False
        indiv.energy = 10000
    if passflag:
        if Optimizer.structure == 'Defect':
            solid = Atoms()
            solid.extend(indiv[0])
            solid.extend(indiv.bulki)
        else:
            solid = indiv[0]
        for sym, c, m, u in Optimizer.atomlist:
            for sy, cs in indiv.swaplist:
                if sy == sym:
                    en -= cs * u
                    nc = len([atm for atm in solid if atm.symbol == sym])
                    en -= float(nc) * float(u)
        indiv.fitness = en
    else:
        indiv.fitness = fit
    return indiv, stro
예제 #48
0
파일: BestInds.py 프로젝트: ZhewenSong/USIT
def BestInds(pop, bests, Optimizer, writefile=False, fname=None):
    """Function to keep track of the best individuals throughout an optimization
    Inputs:
        pop = list of Individual class structures to be compared
        bests = list of previously obtained best structures
        Optimizer = Optimizer class structure that contains key parameters
        writefile = True/False boolean to tell function whether or not to output structures
        fname = filename to output structures
    Outputs:
        bests = list of Individual class structures updated with new options
    """
    #logger = initialize_logger(Optimizer.loggername)
    logger = logging.getLogger(Optimizer.loggername)
    logger.info('best_inds_list recieved population with length = {0} and best list with length = {1} for generation {2}'.format(
        len(pop),len(bests),Optimizer.generation))
    pop = sorted(pop, key=attrgetter('fitness'))
    tol=Optimizer.demin
    if len(bests)!=0:
        bfits=[ind.fitness for ind in bests]
        #Identify the fitnesses in the population
        popfits=[ind.fitness for ind in pop]
        #Initialize a list for individuals to not be added to best list
        indices=[]
        for i in range(len(popfits)):
            for j in range(len(bfits)):
                if popfits[i]==bfits[j]:
                    indices.append(i)
                if popfits[i] < bfits[j]:
                    diff = abs(bfits[j] - popfits[i])
                    diff2 = abs(bfits[j-1] - popfits[i])
                    if diff > tol:
                        if diff2 > tol:
                            if i not in indices:
                                bests.append(pop[i])
                                logger.info('Best list found new structure for List HI = {0}'.format(pop[i].history_index))
                                indices.append(i)
                                b=bfits[0:j]
                                b.append(pop[i].fitness)
                                b.extend(bfits[j::])
                                bfits=b
                        else:
                            indices.append(i)
        bests = sorted(bests, key=attrgetter('fitness'))
        if len(bests) < Optimizer.number_of_bests:
            bmax = bests[len(bests)-1].fitness
            for i in range(len(popfits)):
                if popfits[i] > bmax:
                    diff = abs(popfits[i]-bmax)
                    if diff > tol:
                        bests.append(pop[i])
                        logger.info('Appending best list with lower energy structure')
                        bmax = pop[i].fitness
        else:
            logger.info('Removing extra {0} structures from best list'.format(len(bests)-Optimizer.number_of_bests))
            bests = bests[0:Optimizer.number_of_bests]
        bfits=[ind.fitness for ind in bests]
    else:
        bests = []
        bfits = []
        for one in pop:
            fit = one.fitness
            if len(bfits) == 0:
                bests.append(one)
                logger.info('Adding new structure to best list HI = {0}'.format(one.history_index))
                bfits.append(fit)
            else:
                diff = abs(bfits[-1]-fit)
                if diff > tol:
                    bests.append(one)
                    bfits.append(fit)
        if len(bests) > Optimizer.number_of_bests:
            logger.info('Removing extra {0} structures from best list'.format(len(bests)-Optimizer.number_of_bests))
            bests = bests[0:Optimizer.number_of_bests]
    if writefile==True:
        if fname==None:
            try:
                rank = MPI.COMM_WORLD.Get_rank()
            except:
                rank = 0
            path = os.path.join(os.getcwd(),'{0}-rank{1}'.format(Optimizer.filename,rank))
            logger.info('Writing Best lists to {0}'.format(path))
            fxyzname=os.path.join(path,'Bests-{0}.xyz'.format(Optimizer.filename))
            ffitname=os.path.join(path,'Bests-fitnesses-{0}.txt'.format(Optimizer.filename))
        else:
            fxyzname='{0}.xyz'.format(fname)
            ffitname='{0}-fitnesses.txt'.format(fname)
        bestfile=open(fxyzname,'w')
        bestfitfile=open(ffitname,'w')
        for one in bests:
            if Optimizer.structure=='Defect':
                cbulk=Atoms()
                cbulk.extend(one[0])
                cbulk.extend(one.bulki)
                write_xyz(bestfile,cbulk,one.energy)
            else:
                write_xyz(bestfile,one[0],one.energy)
            bestfitfile.write(repr(one.fitness)+'\n')
        bestfile.close()
        bestfitfile.close()
    return bests
    
예제 #49
0
파일: rotate.py 프로젝트: uw-cmg/StructOpt
def rotate(individual1, individual2, center_at_atom=True, repair_composition=True):
    """Rotates the two individuals around their centers of mass,
    splits them in half at the xy-plane, then splices them together.
    Maintains number of atoms. Note, both individuals are rotated
    in the same way.

    Parameters
    ----------
    individual1 : Individual
        The first parent
    individual2 : Individual 
        The second parent
    center_at_atom : bool
        This centers the cut at an atom. This is particularly useful 
        when one desires a crystalline solution. If both parents
        are crystalline, the children will likely not have grain boundaries.
    repair_composition : bool 
        If True, conserves composition. For crossovers that create children
        with more (less) atoms, atoms are taken from (added to) the surface
        of the particle. For incorrect atomic ratios, atomic symbols are
        randomly interchanged throughout the particle

    Returns
    -------
    Individual: The first child
    Individual: The second child
    """

    # Translate individuals so COP is at (0, 0, 0)
    ind1c = individual1.copy()
    ind2c = individual2.copy()
    cop1 = ind1c.get_positions().mean(axis=0)
    cop2 = ind2c.get_positions().mean(axis=0)

    if center_at_atom:
        offset = get_offset(ind1c, ind2c, r=1.0, HWHM=0.4)
        ind1c.translate(offset)
        cop = ind1c.get_positions().mean(axis=0)

        ind1c.translate(-cop)
        ind2c.translate(-cop)
    else:
        ind1c.translate(ind1c.get_positions().mean(axis=0))
        ind2c.translate(ind2c.get_positions().mean(axis=0))

    # Pick a random rotation angle and vector
    rot_vec = random_three_vector()
    rot_angle = random.uniform(0, 180) * np.pi / 180.0

    # Rotate both individuals
    ind1c.rotate(rot_vec, a=rot_angle, center=(0, 0, 0))
    ind2c.rotate(rot_vec, a=rot_angle, center=(0, 0, 0))

    # Create the children
    child1 = Atoms(cell=ind1c.get_cell())
    child2 = Atoms(cell=ind2c.get_cell())
    child1.extend(ind1c[ind1c.positions[:,2] >= 0])
    child1.extend(ind2c[ind2c.positions[:,2] < 0])
    child2.extend(ind2c[ind2c.positions[:,2] >= 0])
    child2.extend(ind1c[ind1c.positions[:,2] < 0])

    # Repair the children
    if repair_composition:
        syms = ind1c.get_chemical_symbols()
        atomlist = [[sym, syms.count(sym)] for sym in set(syms)]
        repair_cluster(child1, atomlist)
        repair_cluster(child2, atomlist)

    # Reorient the children
    child1.rotate(rot_vec, a=-rot_angle, center=(0, 0, 0))
    child1.center()
    child2.rotate(rot_vec, a=-rot_angle, center=(0, 0, 0))
    child2.center()

    # Convert the children to an Individual with the parent
    # module parameters
    full_child1 = ind1c.copy(include_atoms=False)
    full_child1.extend(child1)
    full_child2 = ind2c.copy(include_atoms=False)
    full_child2.extend(child2)
    
    return full_child1, full_child2
예제 #50
0
def get_defect_indiv_random(Optimizer):
    """
    Function to generate a structopt Individual class structure with a defect structure.
    Inputs:
        Optimizer = structopt Optimizer class object
    Outputs:
        individ = structopt Individual class object containing defect structure data
    """
    #Initialize Bulk - Generate or load positions of bulk solid
    if not Optimizer.solidbulk:
        if 'Island_Method' not in Optimizer.algorithm_type:
            outfilename = os.path.join(os.path.join(os.getcwd(),Optimizer.filename),'Bulkfile.xyz')
        else:
            from mpi4py import MPI
            rank = MPI.COMM_WORLD.Get_rank()
            outfilename = os.path.join(os.path.join(os.getcwd(),Optimizer.filename+'-rank'+repr(rank)),'Bulkfile.xyz')
        if Optimizer.evalsolid:
            if Optimizer.parallel:
                from StructOpt.tools.setup_energy_calculator import setup_energy_calculator
                Optimizer.calc = setup_energy_calculator(Optimizer)
            bulk1, PureBulkEnpa, stro = gen_solid(Optimizer.solidfile,
                Optimizer.solidcell,outfilename,Optimizer.calc,Optimizer.calc_method)
            Optimizer.output.write(stro)
        else:
            bulk1 = gen_solid(Optimizer.solidfile,Optimizer.solidcell,outfilename)
            PureBulkEnpa = 0
        natomsbulk = len(bulk1)
        Optimizer.solidbulk = bulk1.copy()
        Optimizer.purebulkenpa = PureBulkEnpa
        Optimizer.natomsbulk = natomsbulk
    # Identify nearby atoms for region 2 inclusion
    bulk = Optimizer.solidbulk.copy()
    bulkcom = bulk.get_center_of_mass()
    bulk.translate(-bulkcom)
    if Optimizer.sf != 0:
        bulk.append(Atom(position=[0,0,0]))
        nbulk = Atoms(pbc=True, cell=bulk.get_cell())
        nr2 = Atoms(pbc=True, cell=bulk.get_cell())
        for i in range(len(bulk)-1):
            dist = bulk.get_distance(-1,i)
            if dist <= Optimizer.sf:
                nr2.append(bulk[i])
            else:
                nbulk.append(bulk[i])
    else:
        nbulk = bulk.copy()
        nr2 = Atoms(pbc=True, cell=bulk.get_cell())
    #Update atom list with atoms in region 2
    natlist = []
    for sym,c,m,u in Optimizer.atomlist:
        atsym = [atm for atm in nr2 if atm.symbol==sym]
        natlist.append((sym,len(atsym),m,u))
    # Generate random individual and region 2
    if 'sphere' in Optimizer.generate_flag:
        ind = gen_pop_sphere(Optimizer.atomlist,Optimizer.size)
    elif 'dumbbell' in Optimizer.generate_flag:
        ind = Atoms(cell=[Optimizer.size for i in range(3)], pbc=True)
        for sym,c,m,u in Optimizer.atomlist:
            if c > 0:
                dums = generate_dumbbells(c, dumbbellsym=sym, nindiv=1, solid = Optimizer.solidbulk, size=Optimizer.size)[0]
                ind.extend(dums)
    else:
        ind = gen_pop_box(Optimizer.atomlist,Optimizer.size)
    nnr2 = gen_pop_sphere(natlist, Optimizer.sf*2.0)
    nnr2.translate([-Optimizer.sf,-Optimizer.sf,-Optimizer.sf])
    nnr2.set_pbc(True)
    nnr2.set_cell(bulk.get_cell())
    # Initialize class individual with known values
    individ = Individual(ind)
    individ.purebulkenpa = Optimizer.purebulkenpa
    individ.natomsbulk = Optimizer.natomsbulk
    # Combine individual with R2
    icom = ind.get_center_of_mass()
    ind.translate(-icom)
    ind.extend(nnr2)
    ind.set_pbc(True)
    ind.set_cell(bulk.get_cell())
    # Recenter structure
    nbulk.translate(bulkcom)
    ind.translate(bulkcom)
    individ[0] = ind.copy()
    individ.bulki = nbulk.copy()
    individ.bulko = nbulk.copy()
    bulk = nbulk.copy()
    bul = bulk.copy()
    for atm in individ[0]:
        bul.append(atm)
    indices = []
    for sym,c,m,u in Optimizer.atomlist:
        if c < 0:
            if Optimizer.randvacst:
                alist = [one for one in bul if one.symbol==sym]
                count = abs(c)
                while count > 0:
                    indices.append(random.choice(alist).index)
                    count -= 1
            else:
                pos = individ[0][0:Optimizer.natoms].get_center_of_mass()
                count = abs(c)
                bul.append(Atom(position=pos))
                alist = [one for one in bul if one.symbol==sym]
                alistd = [(bul.get_distance(len(bul)-1,one.index),one.index)
                			for one in alist]
                alistd.sort(reverse=True)
                bul.pop()
                while count > 0:
                    idx = alistd.pop()[1]
                    indices.append(idx)
                    count-=1
    if len(indices) !=0:
        nbulklist = [at for at in bul if at.index not in indices and at.index<len(bulk)]
        nalist = [at for at in bul if at.index not in indices and at.index>=len(bulk)]
        bulkn = Atoms(cell=bulk.get_cell(),pbc=True)
        for atm in nbulklist:
            bulkn.append(atm)
        individ.bulki = bulkn.copy()
        individ.bulko = bulkn.copy()
        newind = Atoms()
        for atm in nalist:
            newind.append(atm)
        newind.set_cell(individ[0].get_cell())
        newind.set_pbc(True)									
        individ[0] = newind
    return individ
예제 #51
0
a = 2.70
c = 1.59 * a
h = 1.85
d = 1.10

slab = Atoms('2Cu', [(0., 0., 0.), (1 / 3., 1 / 3., -0.5 * c)],
             tags=(0, 1),
             pbc=(1, 1, 0))
slab.set_cell([(a, 0, 0), (a / 2, 3**0.5 * a / 2, 0), (0, 0, 1)])
slab = slab.repeat((4, 4, 1))
slab.set_calculator(EMT())
mask = [a.tag == 1 for a in slab]
slab.set_constraint(FixAtoms(mask=mask))
dyn = QuasiNewton(slab)
dyn.run(fmax=0.05)

e_slab = slab.get_potential_energy()
x = slab.positions[0, 2] / (c / 2) * 100
print 'Relaxation of the top layer: %f %%' % x

molecule = Atoms('2N', positions=[(0., 0., h), (0., 0., h + d)])
molecule.set_calculator(EMT())
e_N2 = molecule.get_potential_energy()
slab.extend(molecule)

dyn = QuasiNewton(slab)
dyn.run(fmax=0.05)

print 'Adsorption energy:', e_slab + e_N2 - slab.get_potential_energy()
예제 #52
0
from ase import units

"""
This script generates a cube evenly, but randomly filled out with
CH4 molecules, and two "trains" of CH4 molecules that are set in motion.
"""


atoms = Atoms()
# First do the random molecules
methane_cube_pos = 100.0 * np.random.rand(100, 3) - 50.0

for i in range(len(methane_cube_pos)):
    m = molecule("CH4")
    m.set_positions(m.get_positions() + methane_cube_pos[i])
    atoms.extend(m)

MaxwellBoltzmannDistribution(atoms, 100*units.kB)

# random completed, now the two trains

v = 100.0 / (0.1 * units.fs * 1000) # 1000 simulation steps to cover
                                    # from edge to edge
spread = np.linspace(-50.0, 50.0, 10)
v_array = np.array([v] * (len(spread)))

t1_x = spread
t1_y = np.zeros_like(spread)
t1_z = np.zeros_like(spread)
v1_x = v_array
v1_y = np.zeros_like(v_array)
예제 #53
0
 def check_pop(self, pop):
     # Gather all the energies/fitnesses
     if self.output_format=='totalenergy':
         complist = [ind.energy for ind in pop]
     elif self.output_format=='formation_energy':
         complist = []
         for ind in pop:
             solid=Atoms()
             solid.extend(ind[0])
             solid.extend(ind.bulki)
             energy=ind.energy
             for sym,c,m,u in self.atomlist:
                 nc=len([atm for atm in solid if atm.symbol==sym])
                 energy-= float(nc)*float(u)
             complist.append(energy)
     elif self.output_format=='formation_energy_per_int':
         complist = []
         for ind in pop:
             solid=Atoms()
             solid.extend(ind[0])
             solid.extend(ind.bulki)
             energy=ind.energy
             for sym,c,m,u in self.atomlist:
                 nc=len([atm for atm in solid if atm.symbol==sym])
                 energy-= float(nc)*float(u)
             energy=energy/self.natoms
             complist.append(energy)
     elif self.output_format=='formation_energy2':
         complist = [(ind.energy - ind.purebulkenpa*(ind[0].get_number_of_atoms()+ind.bulki.get_number_of_atoms()))/(ind[0].get_number_of_atoms()+ind.bulki.get_number_of_atoms()-ind.natomsbulk) for ind in pop]
     elif self.output_format=='energy_per_atom':
         complist = [ind.energy/(ind[0].get_number_of_atoms()+ind.bulki.get_number_of_atoms()) for ind in pop]
     else:
         complist = [ind.fitness for ind in pop]
 
     # Calcluate and print the Stats
     length = len(pop)
     mean = sum(complist) / length
     complist.sort()
     medium = complist[length/2]
     sum2 = sum(x*x for x in complist)
     std = abs(sum2 / length - mean**2)**0.5
     mine = min(complist)
     maxe = max(complist)
 
     self.output.write('\n----Stats----\n')
     self.output.write('  Min '+repr(mine)+'\n')
     self.output.write('  Max '+repr(maxe)+'\n')
     self.output.write('  Avg '+repr(mean)+'\n')
     self.output.write('  Medium '+repr(medium)+'\n')
     self.output.write('  Std '+repr(std)+'\n')
     self.output.write('  Genrep '+repr(self.genrep)+'\n')
     self.summary.write('{Gen} {Fitmin} {Fitavg} {Fitmed} {Fitmax} {Std} {time}\n'.format(
         Gen=str(self.generation),Fitmin=repr(mine),Fitavg=repr(mean),Fitmed=repr(medium),Fitmax=repr(maxe),
         Std=repr(std),time=repr(time.asctime( time.localtime(time.time()) ))))
 
     # Set new index values and write population
     index1 = 0
     for ind in pop:
         ind.index=index1
         index1+=1
     inp_out.write_pop(self,pop)
 
     if self.allenergyfile:
         for ind in pop:
             self.tenergyfile.write(repr(ind.energy)+' ')
         self.tenergyfile.write('\n')
 
     #Check Convergence of population based on fitness
     fitnesses = [ind.fitness for ind in pop]
     popmin = min(fitnesses)
     popmean = sum(fitnesses) / len(fitnesses)
     sum2 = sum(x*x for x in fitnesses)
     popstd = abs(sum2 / len(fitnesses) - popmean**2)**0.5
     convergence = False
     if self.convergence_scheme=='gen_rep_min':
         if self.generation < self.maxgen:
             if self.generation == 0:
                 self.minfit = popmin
             if abs(self.minfit - popmin) < self.tolerance:
                 self.genrep += 1
             else:
                 self.genrep = 0
                 self.minfit = popmin
             if self.genrep > self.reqrep:
                 self.convergence = True
         else:
             self.convergence = True
     elif self.convergence_scheme=='gen_rep_avg':
         if self.generation < self.maxgen:
             if self.generation == 0:
                 self.minfit = popmean
             if abs(self.minfit - popmean) < self.tolerance:
                 self.genrep += 1
             else:
                 self.genrep = 0
                 self.minfit = popmean
             if self.genrep > self.reqrep:
                 self.convergence = True
         else:
             self.convergence = True
     elif self.convergence_scheme=='std':
         if popstd < self.tolerance:
             self.convergence = True
     else:#self.convergence_scheme=='max_gen':
         if self.generation > self.maxgen:
             self.convergence = True
 
     #Flush output to files
     self.output.flush()
     self.summary.flush()
     for ind in self.files:
         ind.flush()
     if self.indiv_defect_write:
         for ind in self.ifiles:
             ind.flush()
     if self.genealogy: self.Genealogyfile.flush()
     if self.allenergyfile: self.tenergyfile.flush()
     if 'MA' in self.debug: self.debugfile.flush()
     if self.fingerprinting: 
         self.fpfile.flush()
         self.fpminfile.flush()
     return self
예제 #54
0
def rotate_fixed(individual1,
                 individual2,
                 align_cutoff=0.1,
                 repair_composition=True):
    """Similar to rotate except the children aren't borne out of cut out
    versions.

    Parameters
    ----------
    individual1 : Individual
        The first parent
    individual2 : Individual 
        The second parent
    center_at_atom : bool
        This centers the cut at an atom. This is particularly useful 
        when one desires a crystalline solution. If both parents
        are crystalline, the children will likely not have grain boundaries.
    repair_composition : bool 
        If True, conserves composition. For crossovers that create children
        with more (less) atoms, atoms are taken from (added to) the surface
        of the particle. For incorrect atomic ratios, atomic symbols are
        randomly interchanged throughout the particle

    Returns
    -------
    Individual: The first child
    Individual: The second child
    """

    # Translate individuals so atoms are most aligned

    # Pick a random rotation angle and vector
    rot_vec = random_three_vector()
    rot_angle = random.uniform(0, 180) * np.pi / 180.0

    # Rotate both individuals
    ind1c.rotate(rot_vec, a=rot_angle, center=(0, 0, 0))
    ind2c.rotate(rot_vec, a=rot_angle, center=(0, 0, 0))

    # Create the children
    child1 = Atoms(cell=ind1c.get_cell())
    child2 = Atoms(cell=ind2c.get_cell())
    child1.extend(ind1c[ind1c.positions[:, 2] >= 0])
    child1.extend(ind2c[ind2c.positions[:, 2] < 0])
    child2.extend(ind2c[ind2c.positions[:, 2] >= 0])
    child2.extend(ind1c[ind1c.positions[:, 2] < 0])

    # Repair the children
    if repair_composition:
        syms = ind1c.get_chemical_symbols()
        atomlist = [[sym, syms.count(sym)] for sym in set(syms)]
        repair_cluster(child1, atomlist)
        repair_cluster(child2, atomlist)

    # Reorient the children
    child1.rotate(rot_vec, a=-rot_angle, center=(0, 0, 0))
    child1.center()
    child2.rotate(rot_vec, a=-rot_angle, center=(0, 0, 0))
    child2.center()

    # Convert the children to an Individual with the parent
    # module parameters
    full_child1 = ind1c.copy(include_atoms=False)
    full_child1.extend(child1)
    full_child2 = ind2c.copy(include_atoms=False)
    full_child2.extend(child2)

    return full_child1, full_child2
예제 #55
0
파일: chempotswap.py 프로젝트: uw-cmg/MAST
    if abs(fit) > Optimizer.energy_cutoff_factor*(len(indiv[0])+len(indiv.bulki)):
        fit=10000
        message = 'Warning: Found oddly large energy from Lammps in structure HI={0}'.format(indiv.history_index)
        logger.warn(message)
        print message
        print '    Setting fitness to 10000'
        passflag = False
    if math.isnan(fit):
        logger.warn('Found NAN energy structure HI={0}'.format(indiv.history_index))
        fit=10000
        passflag = False
        indiv.energy = 10000
    if passflag:
        if Optimizer.structure=='Defect':
            solid=Atoms()
            solid.extend(indiv[0])
            solid.extend(indiv.bulki)
        else:
            solid = indiv[0]
        for sym,c,m,u in Optimizer.atomlist:
            for sy,cs in indiv.swaplist:
                if sy==sym:
                    en -= cs * u
                    nc=len([atm for atm in solid if atm.symbol==sym])
                    en -= float(nc)*float(u)
        indiv.fitness = en
    else:
        indiv.fitness = fit
    return indiv, stro