예제 #1
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파일: md_tools.py 프로젝트: Picchu/MD-tools
def prepare_for_md(dir):

    '''
    Filters out cif files with disorder.
    Creates new directories:
    ./md-ready
    ./disordered
    '''
    if not dir.endswith('/'):
        dir+='/'

    files = get_cif_files(dir)
    ordered, disordered = [], []

    for file in files:

        s = mg.read_structure(dir+file)
        if s.is_ordered:
            ordered.append(file)
        else:
            disordered.append(file)

    for subd in ['md-ready', 'disordered']:

        # This creates subdirectories if not already present
        if not os.path.isdir('{0}/{1}'.format(dir, subd)):
            os.makedirs('{0}/{1}'.format(dir, subd))

    for file in ordered:
        shutil.copy(dir + file, dir + 'md-ready/')

    for file in disordered:
        shutil.copy(dir + file, dir + 'disordered/')
        
    return
예제 #2
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def csvbuilder(target_dir, output, column_functions, nary=10):
    """
    Build a csv from structure files.

    Keyword arguments:
    target_dir -- string of path to look for structure files
    output -- filename for output csv
    column_functions -- list of function that build the csv.  Each function should take a pymatgen Structure as a parmeter and return a single numeric or categorical (string or character) value
    nary -- limit to n-ary structures (e.g. nary = 2 only binary and elemental, nary = 3 only ternary, binary, and elemental, etc.)
    """
    structure_files = os.listdir(target_dir)
    with open(output, 'wb') as csvfile:
        next_row = 0
        structurewriter = csv.writer(csvfile)
        for structure_filename in structure_files:
            a = pm.read_structure(os.path.join(target_dir, structure_filename))
            if next_row > 0 and numberOfSpecies(a) < nary: 
                row = [structure_filename] + [f(a) for f in column_functions]
                structurewriter.writerow(row)
                next_row += 1
            elif numberOfSpecies(a) < nary:
                colnames = ['fileNames'] + [f.func_name for f in column_functions]
                structurewriter.writerow(colnames)
                row = [structure_filename] + [f(a) for f in column_functions]
                structurewriter.writerow(row)
                next_row += 2
예제 #3
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def coordinationcsv(element, target_dir, output, column_functions):
    """
    Build a coordination csv from structure files. Writes a csv file, one line per structure, containing the average coordination value for 'element' in that sturcture. Any other data columns can be included, per csvbuilder

    Keyword arguments:
    element -- string for the element symbol
    target_dir -- string of path to look for structure files
    output -- filename for output csv
    column_functions -- list of function that build the csv.  Each function should take a pymatgen Structure as a parmeter and return a single numeric or categorical (string or character) value
    """
    structure_files = os.listdir(target_dir)
    with open(output, 'wb') as csvfile:
        next_row = 0
        structurewriter = csv.writer(csvfile)
        for structure_filename in structure_files:
            a = pm.read_structure(os.path.join(target_dir, structure_filename))
            elements = [x.symbol for x in a.species]
            coordination = a.site_properties['coordination_no']
            if next_row > 0 and element in elements:
                avg_coordination = np.mean([x[1] for x in zip(elements, coordination) if x[0]==element])
                row = [f(a) for f in column_functions] + [avg_coordination]
                structurewriter.writerow(row)
                next_row += 1 
            elif element in elements:
                avg_coordination = np.mean([x[1] for x in zip(elements, coordination) if x[0]==element])
                colnames = [f.func_name for f in column_functions] + ['avgCoordination']
                structurewriter.writerow(colnames)
                row = [f(a) for f in column_functions] + [avg_coordination]
                structurewriter.writerow(row)
                next_row += 2
예제 #4
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 def get_structure(self, directory):
     """Returns the final structure from an optimization"""
     abspath = '%s/%s/' % (self.directory, directory)
     
     if ('vasprun.xml' in os.listdir(abspath)):
         return Vasprun('%s/vasprun.xml' % abspath).final_structure
     elif ('CONTCAR' in os.listdir(abspath)):
         return pmg.read_structure('%s/CONTCAR' % abspath)
예제 #5
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    def get_structure(self, directory):
        """Returns the final structure from an optimization"""
        abspath = '%s/%s/' % (self.directory, directory)

        if ('vasprun.xml' in os.listdir(abspath)):
            return Vasprun('%s/vasprun.xml' % abspath).final_structure
        elif ('CONTCAR' in os.listdir(abspath)):
            return pmg.read_structure('%s/CONTCAR' % abspath)
예제 #6
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파일: scaling.py 프로젝트: zhenming-xu/MAST
def read(inp):
    my_struct = {}
    struct = mg.read_structure(inp)
    for i in range(len(struct)):
        try: my_struct[str(struct[i].specie)]
        except: my_struct[str(struct[i].specie)] = [] # New element specie added
        my_struct[str(struct[i].specie)].append([struct[i].a,struct[i].b,struct[i].c])
            
    return my_struct
예제 #7
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 def read_CARs(self,GGA,HSE):
     perfect = defaultdict(defaultdict)
     defect = defaultdict(lambda:defaultdict(defaultdict))
     PA = dict()
     CARs = os.listdir('.')
     perfect_tag = self.inputs['perfect']
     defect_tag = self.inputs['defect']
     for i in range(len(CARs)):
         keywords = CARs[i].split('_')
         if not 'CAR' in CARs[i]: continue
         if 'HSE' in CARs[i]:
             size = keywords[1]+'_HSE'
         elif keywords[1] in ' '.join(HSE['size']):
             size = keywords[1]+'_GGA'
         else: size =  keywords[1]
         
         if keywords[0]==perfect_tag and keywords[-1]=='OSZICAR':
             perfect[size]['energy'] = float(open(CARs[i]).readlines()[-1].split('E0=')[1].split()[0])
         elif keywords[0]==defect_tag and keywords[-1]=='OSZICAR':
             defect[keywords[2]][keywords[3]][size] = float(open(CARs[i]).readlines()[-1].split('E0=')[1].split()[0])
         elif keywords[0]==perfect_tag and keywords[-1]=='OUTCAR':
             PA[size] = self.pa.read_outcar(CARs[i])
         elif keywords[0]==defect_tag and keywords[-1]=='OUTCAR':
             PA['%s_%s_%s'%(keywords[2],keywords[3],size)] = self.pa.read_outcar(CARs[i])
         elif keywords[0]==perfect_tag and (keywords[-1]=='POSCAR' or keywords[-1]=='CONTCAR'):
             shutil.copy(CARs[i],'POSCAR')
             Ele = pmg.read_structure('POSCAR').species
             ele = dict()
             for k in range(len(Ele)): 
                 if not Ele[k] in ele.keys():
                     ele[Ele[k]] = 1
                 else: ele[Ele[k]] += 1
             perfect[size]['ele'] = ele
         elif keywords[0]==defect_tag and (keywords[-1]=='POSCAR' or keywords[-1]=='CONTCAR'):
             shutil.copy(CARs[i],'POSCAR')
             Ele = pmg.read_structure('POSCAR').species
             ele = dict()
             os.system('rm POSCAR')
             for k in range(len(Ele)): 
                 if not Ele[k] in ele.keys():
                     ele[Ele[k]] = 1
                 else: ele[Ele[k]] += 1
             defect[keywords[2]]['ele'][size] = ele
     return [perfect,defect,PA]
예제 #8
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 def get_latt(self,model,latt):
     """Obtaining lattice information from the POSCAR.
         Args:
             types <dict>: type of frequency model, types={'types':<int>}
             lattice <str>: specific name of the POSCAR given by the user
     """
     data={'a':0,'c':0,'No.':0}
     os.system('cp '+latt+'_POSCAR POSCAR')
     struct = mg.read_structure('POSCAR')
     os.system('rm POSCAR')
     reduced = mg.symmetry.finder.SymmetryFinder(struct,0.001).get_primitive_standard_structure()   
     data['No.'] = len(struct)
     if model==5:
         data['a'] = reduced.lattice.abc[0]*np.sqrt(2)*10**(-8)
     if model==14:
         data['a'] = reduced.lattice.abc[0]*np.sqrt(2)*10**(-8)
     if model==8:
         data['a'] = reduced.lattice.abc[0]*10**(-8)
         data['c'] = reduced.lattice.abc[2]*10**(-8)
     return data
예제 #9
0
파일: md_tools.py 프로젝트: Picchu/MD-tools
def cif2cssr(cif, outfile = None, remove = ['Li+']):
    '''
    Converts cif files to Zeo++ CSSR files, deletes species specified in remove. 
    Must have pymatgen installed. Structure must be ordered and oxidation state decorated
    '''
    filename  = cif.rsplit('.',1)[0]
    s = mg.read_structure(cif)

    if remove != None:
        s.remove_species(remove)

    if outfile == None:
        outfile = filename + '.cssr'
        
    try:
        cssr = ZeoCssr(s)
        cssr.write_file(outfile)
    except:
        cssr = None
    return cssr
예제 #10
0
파일: scaling.py 프로젝트: zhenming-xu/MAST
def corrctReflection(relax,defect): 
    # Correct periodically reflected atoms according to the perfect cell.
    # relax is the CONTCAR (after relaxation) and defect is the POSCAR (before relaxation).
    shift = array([0,0,0])
    for ele in relax.keys():
        for i in range(len(relax[ele])):
            for j in range(3):
                shift[j] = shift[j] + relax[ele][i][j] - defect[ele][i][j]
    shift = shift/len(mg.read_structure('POSCAR_defect'))
            
    for ele in relax.keys(): 
        for i in range(len(relax[ele])):
            for j in range(3):
                relax[ele][i][j]=relax[ele][i][j]-shift[j]
                if abs(relax[ele][i][j]-defect[ele][i][j])>abs(relax[ele][i][j]+defect[ele][i][j]-1):
                    if abs(relax[ele][i][j]-defect[ele][i][j]-1)<abs(relax[ele][i][j]-defect[ele][i][j]+1):
                        relax[ele][i][j] = relax[ele][i][j] - 1
                    else:
                        relax[ele][i][j] = relax[ele][i][j] + 1
    return relax
예제 #11
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파일: scaling.py 프로젝트: zhenming-xu/MAST
def make_super(size,filename):
    shutil.copyfile('POSCAR_primitive', filename)
    struct = mg.read_structure(filename)
    Structure.make_supercell(struct,size)
    mg.write_structure(struct,filename)
예제 #12
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    def loop_structures(self, mode='i'):
        """
        reading the structures specified in spec, add special points, and excecute the specs
        mode:
        i: loop structures for input generation
        o: loop structures for output parsing
        w: print all results
        """
        print('loop structures mode ', mode)
        mp_key = os.environ['MP_KEY']

        mp_list_vasp = ['mp-149', 'mp-2534', 'mp-8062', 'mp-2469', 'mp-1550', 'mp-830', 'mp-1986', 'mp-10695', 'mp-66',
                        'mp-1639', 'mp-1265', 'mp-1138', 'mp-23155', 'mp-111']

        if self.data['source'] == 'mp-vasp':
            items_list = mp_list_vasp
        elif self.data['source'] in ['poscar', 'cif']:
            files = os.listdir('.')
            items_list = files
        elif self.data['source'] == 'mar_exp':
            items_list = []
            local_serv = pymongo.Connection("marilyn.pcpm.ucl.ac.be")
            local_db_gaps = local_serv.band_gaps
            pwd = os.environ['MAR_PAS']
            local_db_gaps.authenticate("setten", pwd)
            for c in local_db_gaps.exp.find():
                name = Structure.from_dict(c['icsd_data']['structure']).composition.reduced_formula, c['icsd_id'],\
                    c['MP_id']
                print(name)
                #Structure.from_dict(c['icsd_data']['structure']).to(fmt='cif',filename=name)
                items_list.append({'name': 'mp-' + c['MP_id'], 'icsd': c['icsd_id'], 'mp': c['MP_id']})
        else:
            items_list = [line.strip() for line in open(self.data['source'])]

        for item in items_list:
            print('\n')
            # special case, this should be encaptulated
            if self.data['source'] == 'mar_exp':
                print('structure from marilyn', item['name'], item['icsd'], item['mp'])
                exp = local_db_gaps.exp.find({'MP_id': item['mp']})[0]
                structure = Structure.from_dict(exp['icsd_data']['structure'])
                structure = refine_structure(structure)
                structure.to(fmt='cif', filename=item['name'])
                try:
                    kpts = local_db_gaps.GGA_BS.find({'transformations.history.0.id': item['icsd']})[0]['calculations']\
                    [-1]['band_structure']['kpoints']
                except (IndexError, KeyError):
                    kpts = [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]
                structure.kpts = kpts
                print('kpoints:', structure.kpts[0], structure.kpts[1])
                structure.item = item['name']
            else:
                if item.startswith('POSCAR_'):
                    structure = pmg.read_structure(item)
                    comment = Poscar.from_file(item).comment
                    # print comment
                    if comment.startswith("gap"):
                        structure.vbm_l = comment.split(" ")[1]
                        structure.vbm = (comment.split(" ")[2], comment.split(" ")[3], comment.split(" ")[4])
                        structure.cbm_l = comment.split(" ")[5]
                        structure.cbm = (comment.split(" ")[6], comment.split(" ")[7], comment.split(" ")[8])
                    else:
                        # print "no bandstructure information available, adding GG as 'gap'"
                        structure = add_gg_gap(structure)
                elif 'xyz' in item:
                    structure = pmg.read_structure(item)
                    raise NotImplementedError
                elif item.startswith('mp-'):
                    with MPRester(mp_key) as mp_database:
                        print('structure from mp database', item)
                        structure = mp_database.get_structure_by_material_id(item, final=True)
                        try:
                            bandstructure = mp_database.get_bandstructure_by_material_id(item)
                            structure.vbm_l = bandstructure.kpoints[bandstructure.get_vbm()['kpoint_index'][0]].label
                            structure.cbm_l = bandstructure.kpoints[bandstructure.get_cbm()['kpoint_index'][0]].label
                            structure.cbm = tuple(bandstructure.kpoints[bandstructure.get_cbm()['kpoint_index'][0]].frac_coords)
                            structure.vbm = tuple(bandstructure.kpoints[bandstructure.get_vbm()['kpoint_index'][0]].frac_coords)
                        except (MPRestError, IndexError, KeyError) as err:
                            print(err.message)
                            structure = add_gg_gap(structure)
                else:
                    continue
                structure.kpts = [list(structure.cbm), list(structure.vbm)]
                structure.item = item
            print(item, s_name(structure))
            if mode == 'i':
                self.excecute_flow(structure)
            elif mode == 'w':
                self.print_results(structure)
            elif mode == 's':
                self.insert_in_database(structure)
            elif mode == 'o':
                # if os.path.isdir(s_name(structure)) or os.path.isdir(s_name(structure)+'.conv'):
                self.process_data(structure)

        if 'ceci' in self.data['mode'] and mode == 'i':
            os.chmod("job_collection", stat.S_IRWXU)
예제 #13
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파일: FSS.py 프로젝트: ZhewenSong/USIT
    for i in range(len(relax)):
        r_coords = relax[i].frac_coords
        index = find_atom(r_coords,supercell)
        supercell.replace(index,supercell[index].specie,r_coords)

if __name__=='__main__':
    center = [0.0, 0.0, 0.0]
    argv = sys.argv[1:]
    opts, args = getopt.getopt(argv,"s")
    Size = int(args[0])
    size = int(args[1])

    shift_vector = get_shift_vector(center,size,size)
    Shift_Vector = get_shift_vector(center,size,Size)

    supercell = mg.read_structure('POSCAR_super')
    shift_coords(supercell,Shift_Vector)

    relax = mg.read_structure('POSCAR_relax')
    shift_coords(relax,shift_vector)

    defect = mg.read_structure('POSCAR_defect')
    shift_coords(defect,shift_vector)

    compare_coords(relax,defect,supercell,size,Size)
    rescale(relax,size,Size)
    
    replace(supercell,relax)
    shift_coords(supercell,-Shift_Vector)

    mg.write_structure(supercell,'POSCAR_final')
예제 #14
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파일: md_tools.py 프로젝트: Picchu/MD-tools
def prepare_for_zeo(dir, remove_duplicates = False, separator = None):

    '''
    Takes a directory of cif files and filters zeo++ usable files. Requires pymatgen.
    Creates new directories:
    ./ready - oxidation state decorated files for zeo++ to use.  
    ./no-rad - structures with species having no corresponding ionic radii in pymatgen database
    ./fails - structures which cannot be assigned oxidation states

    If remove_duplicates is set to true, it runs the files through remove_duplicates. Files pulled out of the database are of the format <id><speparator><formula>. The separator is usually '_' or '-'.
    '''

    # TODO maybe let the user specify the location of the new directories
    
    files = [file for file in os.listdir(dir) if file.endswith('cif')]
    
 
    d = {} # Dictionary of the form d[<filename>]['struct'], d[<filename>]['mass'], d[<filename>]['radius']
           
    fails, no_rad = [], []

    for file in files:
        d[file] = {}
        # reading to pymatgen structure object
        s = mg.read_structure('{1}/{0}'.format(file, dir))
        
        # AutoOxidationStateDecorationObject
        ox = oxi()

        try:
            # Oxidation state decorated structure
            s_ox = ox.apply_transformation(s)

            # Saving structure to dictionary
            d[file]['struct']  = s_ox

            # List of unique elements in the structure
            species = set(s_ox.species)

            radii = dict((str(sp), float(sp.ionic_radius)) for sp in species)
            masses = dict((str(sp), float(sp.atomic_mass)) for sp in species)
            d[file]['radii'] = radii
            d[file]['masses'] = masses
            for sp in species:
         
                if sp.ionic_radius == None:
                # These are charge decorated files which have an assigned oxidation state but no radius in pymatgen corresponding to that state
                # These files will have to be analyzed later, possibly using the crystal radius from the shannon table
                    no_rad.append(file)
                    break

        except:
            # These are files that cannot be assigned oxidation states - bond valence fails either due to disorder or is unable to find a charge neutral state       
            fails.append(file)
            d[file]['struct'] = s
            d[file]['radii'] = None
            d[file]['masses'] = None

    # This is a list of usable files for zeo++
    ready = list(set(files).difference(set(no_rad)).difference(set(fails)))

    for subd in ['zeo-ready', 'zeo-no-rad', 'zeo-fails']:

        # This creates subdirectories if not already present
        if not os.path.isdir('{0}/{1}'.format(dir, subd)):
            os.makedirs('{0}/{1}'.format(dir, subd))

    if remove_duplicates:
        d_ready = remove_duplicates(ready, separator)
        ready = [d_ready[key] for key in d_ready]
        
        d_no_rad = remove_duplicates(no_rad, separator)
        no_rad = [d_no_rad[key] for key in d_no_rad]

        d_fails = remove_duplicates(fails, separator)
        fails = [d_fails[key] for key in d_fails]


    
    # Writing files into respective sub-directories
    for file in ready:
        
        mg.write_structure(d[file]['struct'], '{0}/zeo-ready/{1}'.format(dir, file))
        # write the radius and the mass files also
        filename = file.rsplit('.cif',1)[0]
        write_rad_file(d[file]['radii'],'{0}/zeo-ready'.format(dir), filename)
        write_mass_file(d[file]['masses'],'{0}/zeo-ready'.format(dir), filename) 

    for file in no_rad:
        # These files do not have a radius for atleast one of the species
        mg.write_structure(d[file]['struct'], '{0}/zeo-no-rad/{1}'.format(dir,file))

    for file in fails:
        
        # Note: these files are not charge decorated and are simply the original cif files rewritten
        mg.write_structure(d[file]['struct'], '{0}/zeo-fails/{1}'.format(dir,file))

    return len(ready), len(no_rad), len(fails)
예제 #15
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def main(filename = 'mp-1368.mson', beta = 1.0, initial_temp = 1.0, precomputed_structure = False):
    def temperature(phi_, beta_, initial_temp_):
        #cooling profile. returns a temperature according to initial_temp*exp(-beta*phi), where phi is the current packing fraction, and beta is a free parameter
        return initial_temp_*np.exp(-beta_*phi_)
    #Filename of starting structure

    #Cutoff for tetrahedron distortion -- higher numbers will accept more distorted tetrahedra
    std_dev_cutoff = 0.50

    #Initial factor for increasing all axes
    initial_increase_factor = 2.5

    #Compression increment -- compress by fixed percentage:
    compression_factor = -0.01
    
    #Tetrahedra become distorted due compounding numerical error. Re-regularize every n steps:
    normalization_frequency = 1

    #Save structure every n steps:
    save_frequency = 1

    #Controls how much tetrahedra can jostle during packing
    temp = 1.

    #How many tries to fit a tetrahedra before skipping
    resolution_max = 5000

    #How far a tet can travel randomly
    distance_max = 1.0

    #Initialize sturcture and tetrahedra
    print '\nLoading initial structure...',
    sys.stdout.flush()
    initial_structure = pm.read_structure(filename)
    if not precomputed_structure:
        path = initial_structure.composition.alphabetical_formula.replace(' ', '') + '_beta_' + str(beta) + '_T_' + str(initial_temp) 
        if not os.path.exists(path):
            os.mkdir(path)
        print initial_structure.composition.alphabetical_formula + ' loaded.'
        print '\nExtracting tetrahedra...',
        sys.stdout.flush()
        tet_str, tet_reg = tetpack.tetrahedra_from_structure(initial_structure, stdcutoff=std_dev_cutoff)
        print str(len(tet_reg)) + ' initial tetrahedra extracted.'

        #Expand structure initally
        print '\nExpanding cell axes by factor of ' + str(initial_increase_factor) + '...',
        sys.stdout.flush()
        current_tet_str = tetpack.adjust_axes(tet_str, initial_increase_factor)
        current_tet_reg = map(tetpack.tetrahedron, [current_tet_str[5*i:5*i+5] for i in range(len(current_tet_str)/5)])
        print 'done: \na = ' + str(current_tet_str.lattice.a) + '\nb = ' + str(current_tet_str.lattice.b) + '\nc = '  + str(current_tet_str.lattice.c) 

        phi = tetpack.packing_density(current_tet_str)
        print '\nRelaxing structure via Ewald summation...'
        sys.stdout.flush()
        current_tet_str = tetpack.ewald_relaxation(current_tet_str, max_steps = 1, motion_factor = temperature(phi, beta, initial_temp))
    else:
        path = filename.rstrip('.mson') + '_beta_' + str(beta) + '_T_' + str(initial_temp)
        if not os.path.exists(path):
            os.mkdir(path)
        current_tet_str = initial_structure
        current_tet_reg = map(tetpack.tetrahedron, [current_tet_str[5*i:5*i+5] for i in range(len(current_tet_str)/5)])
    print '\nBeginning compression loop:'

    #Loop until collision
    collision = False
    step = 0
    while(not collision):
        phi = tetpack.packing_density(current_tet_str)
        if np.mod(step, normalization_frequency) == 0:
            print 'Normalizing tetrahedra...',
            sys.stdout.flush()
            [tet.regularize() for tet in current_tet_reg]
            print 'done.'
        current_tet_str, current_tet_reg = compress(current_tet_str, current_tet_reg,  temperature(phi, beta, initial_temp)*compression_factor)
        print 'Step '+ str(step) + ' packing fraction: ' + str(phi) + ' T:' +  str(temperature(phi, beta, initial_temp)) + '...',
        sys.stdout.flush()
        failed = check_and_resolve_collisions(current_tet_str, current_tet_reg, temperature(phi, beta, initial_temp), distance_max,  int(1./temperature(phi, beta, initial_temp)*resolution_max))
        if failed:
            print 'Relaxing structure...',
            sys.stdout.flush()
            current_tet_str, current_tet_reg = compress(current_tet_str, current_tet_reg, -1.5* temperature(phi, beta, initial_temp)* compression_factor)
            phi = tetpack.packing_density(current_tet_str)
            print 'done. Packing fraction: ' + str(phi)
            print 'Single-step Ewald relaxation...'
            sys.stdout.flush()
            current_tet_str = tetpack.ewald_relaxation(current_tet_str, max_steps = 1, motion_factor = temperature(phi, beta, initial_temp))
            print 'done.'
            failed = False
        else:
            if np.mod(step, save_frequency) == 0:
                print 'Writing structure...',
                sys.stdout.flush()
                pm.write_structure(current_tet_str, os.path.join(path, str(step) + '.cif'))
                tetpack.to_challenge_output(current_tet_str, os.path.join(path, str(step) + '.csv'))
                print 'done.'

        step += 1
예제 #16
0
def main(filename='mp-1368.mson',
         beta=1.0,
         initial_temp=1.0,
         precomputed_structure=False):
    def temperature(phi_, beta_, initial_temp_):
        #cooling profile. returns a temperature according to initial_temp*exp(-beta*phi), where phi is the current packing fraction, and beta is a free parameter
        return initial_temp_ * np.exp(-beta_ * phi_)

    #Filename of starting structure

    #Cutoff for tetrahedron distortion -- higher numbers will accept more distorted tetrahedra
    std_dev_cutoff = 0.50

    #Initial factor for increasing all axes
    initial_increase_factor = 2.5

    #Compression increment -- compress by fixed percentage:
    compression_factor = -0.01

    #Tetrahedra become distorted due compounding numerical error. Re-regularize every n steps:
    normalization_frequency = 1

    #Save structure every n steps:
    save_frequency = 1

    #Controls how much tetrahedra can jostle during packing
    temp = 1.

    #How many tries to fit a tetrahedra before skipping
    resolution_max = 5000

    #How far a tet can travel randomly
    distance_max = 1.0

    #Initialize sturcture and tetrahedra
    print '\nLoading initial structure...',
    sys.stdout.flush()
    initial_structure = pm.read_structure(filename)
    if not precomputed_structure:
        path = initial_structure.composition.alphabetical_formula.replace(
            ' ', '') + '_beta_' + str(beta) + '_T_' + str(initial_temp)
        if not os.path.exists(path):
            os.mkdir(path)
        print initial_structure.composition.alphabetical_formula + ' loaded.'
        print '\nExtracting tetrahedra...',
        sys.stdout.flush()
        tet_str, tet_reg = tetpack.tetrahedra_from_structure(
            initial_structure, stdcutoff=std_dev_cutoff)
        print str(len(tet_reg)) + ' initial tetrahedra extracted.'

        #Expand structure initally
        print '\nExpanding cell axes by factor of ' + str(
            initial_increase_factor) + '...',
        sys.stdout.flush()
        current_tet_str = tetpack.adjust_axes(tet_str, initial_increase_factor)
        current_tet_reg = map(tetpack.tetrahedron, [
            current_tet_str[5 * i:5 * i + 5]
            for i in range(len(current_tet_str) / 5)
        ])
        print 'done: \na = ' + str(current_tet_str.lattice.a) + '\nb = ' + str(
            current_tet_str.lattice.b) + '\nc = ' + str(
                current_tet_str.lattice.c)

        phi = tetpack.packing_density(current_tet_str)
        print '\nRelaxing structure via Ewald summation...'
        sys.stdout.flush()
        current_tet_str = tetpack.ewald_relaxation(current_tet_str,
                                                   max_steps=1,
                                                   motion_factor=temperature(
                                                       phi, beta,
                                                       initial_temp))
    else:
        path = filename.rstrip('.mson') + '_beta_' + str(beta) + '_T_' + str(
            initial_temp)
        if not os.path.exists(path):
            os.mkdir(path)
        current_tet_str = initial_structure
        current_tet_reg = map(tetpack.tetrahedron, [
            current_tet_str[5 * i:5 * i + 5]
            for i in range(len(current_tet_str) / 5)
        ])
    print '\nBeginning compression loop:'

    #Loop until collision
    collision = False
    step = 0
    while (not collision):
        phi = tetpack.packing_density(current_tet_str)
        if np.mod(step, normalization_frequency) == 0:
            print 'Normalizing tetrahedra...',
            sys.stdout.flush()
            [tet.regularize() for tet in current_tet_reg]
            print 'done.'
        current_tet_str, current_tet_reg = compress(
            current_tet_str, current_tet_reg,
            temperature(phi, beta, initial_temp) * compression_factor)
        print 'Step ' + str(step) + ' packing fraction: ' + str(
            phi) + ' T:' + str(temperature(phi, beta, initial_temp)) + '...',
        sys.stdout.flush()
        failed = check_and_resolve_collisions(
            current_tet_str, current_tet_reg,
            temperature(phi, beta, initial_temp), distance_max,
            int(1. / temperature(phi, beta, initial_temp) * resolution_max))
        if failed:
            print 'Relaxing structure...',
            sys.stdout.flush()
            current_tet_str, current_tet_reg = compress(
                current_tet_str, current_tet_reg, -1.5 *
                temperature(phi, beta, initial_temp) * compression_factor)
            phi = tetpack.packing_density(current_tet_str)
            print 'done. Packing fraction: ' + str(phi)
            print 'Single-step Ewald relaxation...'
            sys.stdout.flush()
            current_tet_str = tetpack.ewald_relaxation(
                current_tet_str,
                max_steps=1,
                motion_factor=temperature(phi, beta, initial_temp))
            print 'done.'
            failed = False
        else:
            if np.mod(step, save_frequency) == 0:
                print 'Writing structure...',
                sys.stdout.flush()
                pm.write_structure(current_tet_str,
                                   os.path.join(path,
                                                str(step) + '.cif'))
                tetpack.to_challenge_output(
                    current_tet_str, os.path.join(path,
                                                  str(step) + '.csv'))
                print 'done.'

        step += 1
예제 #17
0
    def loop_structures(self, mode='i'):
        """
        reading the structures specified in spec, add special points, and excecute the specs
        mode:
        i: loop structures for input generation
        o: loop structures for output parsing
        w: print all results
        """
        print('loop structures mode ', mode)
        mp_key = os.environ['MP_KEY']

        mp_list_vasp = ['mp-149', 'mp-2534', 'mp-8062', 'mp-2469', 'mp-1550', 'mp-830', 'mp-1986', 'mp-10695', 'mp-66',
                        'mp-1639', 'mp-1265', 'mp-1138', 'mp-23155', 'mp-111']

        if self.data['source'] == 'mp-vasp':
            items_list = mp_list_vasp
        elif self.data['source'] == 'poscar':
            files = os.listdir('.')
            items_list = files
        elif self.data['source'] == 'mar_exp':
            items_list = []
            local_serv = pymongo.Connection("marilyn.pcpm.ucl.ac.be")
            local_db_gaps = local_serv.band_gaps
            pwd = os.environ['MAR_PAS']
            local_db_gaps.authenticate("setten", pwd)
            for c in local_db_gaps.exp.find():
                print(Structure.from_dict(c['icsd_data']['structure']).composition.reduced_formula, c['icsd_id'],\
                    c['MP_id'])
                items_list.append({'name': 'mp-' + c['MP_id'], 'icsd': c['icsd_id'], 'mp': c['MP_id']})
        else:
            items_list = [line.strip() for line in open(self.data['source'])]

        for item in items_list:
            print('\n')
            # special case, this should be encaptulated
            if self.data['source'] == 'mar_exp':
                print('structure from marilyn', item['name'], item['icsd'], item['mp'])
                exp = local_db_gaps.exp.find({'MP_id': item['mp']})[0]
                structure = Structure.from_dict(exp['icsd_data']['structure'])
                structure = refine_structure(structure)
                try:
                    kpts = local_db_gaps.GGA_BS.find({'transformations.history.0.id': item['icsd']})[0]['calculations']\
                    [-1]['band_structure']['kpoints']
                except (IndexError, KeyError):
                    kpts = [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]
                structure.kpts = kpts
                print('kpoints:', structure.kpts[0], structure.kpts[1])
                structure.item = item['name']
            else:
                if item.startswith('POSCAR_'):
                    structure = pmg.read_structure(item)
                    comment = Poscar.from_file(item).comment
                    # print comment
                    if comment.startswith("gap"):
                        structure.vbm_l = comment.split(" ")[1]
                        structure.vbm = (comment.split(" ")[2], comment.split(" ")[3], comment.split(" ")[4])
                        structure.cbm_l = comment.split(" ")[5]
                        structure.cbm = (comment.split(" ")[6], comment.split(" ")[7], comment.split(" ")[8])
                    else:
                        # print "no bandstructure information available, adding GG as 'gap'"
                        structure = add_gg_gap(structure)
                elif 'xyz' in item:
                    structure = pmg.read_structure(item)
                    raise NotImplementedError
                elif item.startswith('mp-'):
                    with MPRester(mp_key) as mp_database:
                        print('structure from mp database', item)
                        structure = mp_database.get_structure_by_material_id(item, final=True)
                        try:
                            bandstructure = mp_database.get_bandstructure_by_material_id(item)
                            structure.vbm_l = bandstructure.kpoints[bandstructure.get_vbm()['kpoint_index'][0]].label
                            structure.cbm_l = bandstructure.kpoints[bandstructure.get_cbm()['kpoint_index'][0]].label
                            structure.cbm = tuple(bandstructure.kpoints[bandstructure.get_cbm()['kpoint_index'][0]].frac_coords)
                            structure.vbm = tuple(bandstructure.kpoints[bandstructure.get_vbm()['kpoint_index'][0]].frac_coords)
                        except (MPRestError, IndexError, KeyError) as err:
                            print(err.message)
                            structure = add_gg_gap(structure)
                else:
                    continue
                structure.kpts = [list(structure.cbm), list(structure.vbm)]
                structure.item = item
            print(item, s_name(structure))
            if mode == 'i':
                self.excecute_flow(structure)
            elif mode == 'w':
                self.print_results(structure)
            elif mode == 's':
                self.insert_in_database(structure)
            elif mode == 'o':
                # if os.path.isdir(s_name(structure)) or os.path.isdir(s_name(structure)+'.conv'):
                self.process_data(structure)

        if 'ceci' in self.data['mode'] and mode == 'i':
            os.chmod("job_collection", stat.S_IRWXU)
예제 #18
0
Created on September 10, 2013

@author: Qimin
'''
import sys
import pymatgen
import math
from pymatgen.symmetry.finder import SymmetryFinder

file = str(sys.argv[1])
spacegroup = str(sys.argv[2])
max = float(sys.argv[3])
min = float(sys.argv[4])
iter = float(sys.argv[5])

s = pymatgen.read_structure(file)

def getLowSymPrec(s,max,min,spacegroup,iter):
	SG = str(spacegroup)
	if SG!=str(SymmetryFinder(s,symprec=max).get_spacegroup_number()):
		print "Not reasonable spacegroup or max too large"
		return -1
	elif SG==str(SymmetryFinder(s,symprec=min).get_spacegroup_number()):
		return min
	else:
		upperbound = max
		lowerbound = min
		i=0
		while i<iter:
			trial = 10**((math.log(upperbound,10)+math.log(lowerbound,10))/2)
			if SG==str(SymmetryFinder(s,symprec=trial).get_spacegroup_number()):
예제 #19
0
    seg = np.concatenate([pts[:-1], pts[1:]], axis=1)
 
    nseg = len(k)-1
    r = [0.5*(red[i]+red[i+1]) for i in range(nseg)]
    g = [0.5*(green[i]+green[i+1]) for i in range(nseg)]
    b = [0.5*(blue[i]+blue[i+1]) for i in range(nseg)]
    a = np.ones(nseg, np.float)*alpha
    lc = LineCollection(seg, colors=zip(r,g,b,a), linewidth = 2)
    ax.add_collection(lc)
 
if __name__ == "__main__":
    # read data
    # ---------
 
    # kpoints labels
    path = HighSymmKpath(mg.read_structure("./CONTCAR")).kpath["path"]
    labels = [r"$%s$" % lab for lab in path[0][0:4]]
 
    # bands
    bands = Vasprun("./vasprun.xml").get_band_structure("./KPOINTS", line_mode = True)
 
    # projected bands
    data = Procar("./PROCAR").data
 
    # density of states
    dosrun = Vasprun("./vasprun.xml")
 
    # set up matplotlib plot
    # ----------------------
 
    # general options for plot
예제 #20
0
파일: FSS.py 프로젝트: zhenming-xu/MAST
        r_coords = relax[i].frac_coords
        index = find_atom(r_coords, supercell)
        supercell.replace(index, supercell[index].specie, r_coords)


if __name__ == '__main__':
    center = [0.0, 0.0, 0.0]
    argv = sys.argv[1:]
    opts, args = getopt.getopt(argv, "s")
    Size = int(args[0])
    size = int(args[1])

    shift_vector = get_shift_vector(center, size, size)
    Shift_Vector = get_shift_vector(center, size, Size)

    supercell = mg.read_structure('POSCAR_super')
    shift_coords(supercell, Shift_Vector)

    relax = mg.read_structure('POSCAR_relax')
    shift_coords(relax, shift_vector)

    defect = mg.read_structure('POSCAR_defect')
    shift_coords(defect, shift_vector)

    compare_coords(relax, defect, supercell, size, Size)
    rescale(relax, size, Size)

    replace(supercell, relax)
    shift_coords(supercell, -Shift_Vector)

    mg.write_structure(supercell, 'POSCAR_final')
예제 #21
0
파일: primitive.py 프로젝트: blondegeek/UO2
import pymatgen
from pymatgen.symmetry.finder import SymmetryFinder

s = pymatgen.read_structure('POSCAR')

#print SymmetryFinder(s).find_primitive()
structure = SymmetryFinder(s).find_primitive()
pymatgen.write_structure(structure, "POSCAR")
예제 #22
0
import pymatgen as mg
from pymatgen.core.structure import Structure

filename = raw_input('file name:')
l = raw_input('x scale:')
m = raw_input('y scale:')
n = raw_input('z scale:')

struct = mg.read_structure(filename)
Structure.make_supercell(struct, [l, m, n])
mg.write_structure(struct, "poscar_temp")

f = open("poscar_temp")
w = open("mast.inp", "w")


def getinfo(line):
    line = line.strip('\n')
    data = line.split(' ')
    while 1:
        try:
            data.remove('')
        except:
            break
    return data


line = []
elenum = []

line.append(f.readline())
예제 #23
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# read args
if len(sys.argv) > 1:
    if len(sys.argv) == 2:
        fstruct = sys.argv[1]
    else:
        fstruct = sys.argv[-1]
    if "-d" in sys.argv:
        try:
            ndiv = int(sys.argv[sys.argv.index("-d") + 1])
        except ValueError, IndexError:
            print("-d must be followed by an integer")
            exit(1)

# read structure
if os.path.exists(fstruct):
    struct = mg.read_structure(fstruct)
else:
    print("File %s does not exist" % fstruct)
    exit(1)

# symmetry information
struct_sym = SymmetryFinder(struct)
print("lattice type : {0}".format(struct_sym.get_lattice_type()))
print("space group  : {0} ({1})".format(struct_sym.get_spacegroup_symbol(),
                                     struct_sym.get_spacegroup_number()))

# Compute first brillouin zone
ibz = HighSymmKpath(struct)
ibz.get_kpath_plot(savefig="path.png")
print("ibz type     : {0}".format(ibz.name))
예제 #24
0
    def loop_structures(self, mode="i"):
        """
        reading the structures specified in spec, add special points, and excecute the specs
        mode:
        i: loop structures for input generation
        o: loop structures for output parsing
        w: print all results
        """
        print("loop structures mode ", mode)
        mp_key = os.environ["MP_KEY"]

        mp_list_vasp = [
            "mp-149",
            "mp-2534",
            "mp-8062",
            "mp-2469",
            "mp-1550",
            "mp-830",
            "mp-1986",
            "mp-10695",
            "mp-66",
            "mp-1639",
            "mp-1265",
            "mp-1138",
            "mp-23155",
            "mp-111",
        ]

        if self.data["source"] == "mp-vasp":
            items_list = mp_list_vasp
        elif self.data["source"] in ["poscar", "cif"]:
            files = os.listdir(".")
            items_list = files
        elif self.data["source"] == "mar_exp":
            items_list = []
            local_serv = pymongo.Connection("marilyn.pcpm.ucl.ac.be")
            local_db_gaps = local_serv.band_gaps
            pwd = os.environ["MAR_PAS"]
            local_db_gaps.authenticate("setten", pwd)
            for c in local_db_gaps.exp.find():
                name = (
                    Structure.from_dict(c["icsd_data"]["structure"]).composition.reduced_formula,
                    c["icsd_id"],
                    c["MP_id"],
                )
                print(name)
                # Structure.from_dict(c['icsd_data']['structure']).to(fmt='cif',filename=name)
                items_list.append({"name": "mp-" + c["MP_id"], "icsd": c["icsd_id"], "mp": c["MP_id"]})
        else:
            items_list = [line.strip() for line in open(self.data["source"])]

        for item in items_list:
            print("\n")
            # special case, this should be encaptulated
            if self.data["source"] == "mar_exp":
                print("structure from marilyn", item["name"], item["icsd"], item["mp"])
                exp = local_db_gaps.exp.find({"MP_id": item["mp"]})[0]
                structure = Structure.from_dict(exp["icsd_data"]["structure"])
                structure = refine_structure(structure)
                structure.to(fmt="cif", filename=item["name"])
                try:
                    kpts = local_db_gaps.GGA_BS.find({"transformations.history.0.id": item["icsd"]})[0]["calculations"][
                        -1
                    ]["band_structure"]["kpoints"]
                except (IndexError, KeyError):
                    kpts = [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]
                structure.kpts = kpts
                print("kpoints:", structure.kpts[0], structure.kpts[1])
                structure.item = item["name"]
            else:
                if item.startswith("POSCAR_"):
                    structure = pmg.read_structure(item)
                    comment = Poscar.from_file(item).comment
                    # print comment
                    if comment.startswith("gap"):
                        structure.vbm_l = comment.split(" ")[1]
                        structure.vbm = (comment.split(" ")[2], comment.split(" ")[3], comment.split(" ")[4])
                        structure.cbm_l = comment.split(" ")[5]
                        structure.cbm = (comment.split(" ")[6], comment.split(" ")[7], comment.split(" ")[8])
                    else:
                        # print "no bandstructure information available, adding GG as 'gap'"
                        structure = add_gg_gap(structure)
                elif "xyz" in item:
                    structure = pmg.read_structure(item)
                    raise NotImplementedError
                elif item.startswith("mp-"):
                    with MPRester(mp_key) as mp_database:
                        print("structure from mp database", item)
                        structure = mp_database.get_structure_by_material_id(item, final=True)
                        try:
                            bandstructure = mp_database.get_bandstructure_by_material_id(item)
                            structure.vbm_l = bandstructure.kpoints[bandstructure.get_vbm()["kpoint_index"][0]].label
                            structure.cbm_l = bandstructure.kpoints[bandstructure.get_cbm()["kpoint_index"][0]].label
                            structure.cbm = tuple(
                                bandstructure.kpoints[bandstructure.get_cbm()["kpoint_index"][0]].frac_coords
                            )
                            structure.vbm = tuple(
                                bandstructure.kpoints[bandstructure.get_vbm()["kpoint_index"][0]].frac_coords
                            )
                        except (MPRestError, IndexError, KeyError) as err:
                            print(err.message)
                            structure = add_gg_gap(structure)
                else:
                    continue
                structure.kpts = [list(structure.cbm), list(structure.vbm)]
                structure.item = item
            print(item, s_name(structure))
            if mode == "i":
                try:
                    self.excecute_flow(structure)
                except Exception as exc:
                    print("input generation failed")
                    print(exc)
            elif mode == "w":
                try:
                    self.print_results(structure)
                except:
                    print("writing output failed")
            elif mode == "s":
                try:
                    self.insert_in_database(structure)
                except:
                    print("database insertion failed")
            elif mode == "o":
                # if os.path.isdir(s_name(structure)) or os.path.isdir(s_name(structure)+'.conv'):
                try:
                    self.process_data(structure)
                except:
                    print("output parsing failed")

        if "ceci" in self.data["mode"] and mode == "i":
            os.chmod("job_collection", stat.S_IRWXU)
예제 #25
0
    nseg = len(k) - 1
    r = [0.5 * (red[i] + red[i + 1]) for i in range(nseg)]
    g = [0.5 * (green[i] + green[i + 1]) for i in range(nseg)]
    b = [0.5 * (blue[i] + blue[i + 1]) for i in range(nseg)]
    a = np.ones(nseg, np.float) * alpha
    lc = LineCollection(seg, colors=zip(r, g, b, a), linewidth=2)
    ax.add_collection(lc)


if __name__ == "__main__":
    # read data
    # ---------

    # kpoints labels
    path = HighSymmKpath(mg.read_structure("./POSCAR")).kpath["path"]
    labels = list()
    for p in path:
        if len(labels) != 0:
            labels[-1] = r"$%s,%s$" % (labels[-1].strip("$"), p[0])
        else:
            labels.append(r"$%s$" % p[0])
        for kp in p[1:]:
            labels.append(r"$%s$" % kp)

    # density of state
    dosrun = Vasprun("../../DOS/Cu/vasprun.xml")
    spd_dos = dosrun.complete_dos.get_spd_dos()

    # bands
    run = Vasprun("vasprun.xml", parse_projected_eigen=True)
예제 #26
0
import numpy as np
import math
import pymatgen
from pymatgen.symmetry.finder import SymmetryFinder

s = pymatgen.read_structure('POSCAR')

# composition
print "Formula:\t"+str(s.composition.formula)
# spacegroup
print "Spacegroup:\t"+str(SymmetryFinder(s).get_spacegroup())
# lattice constant lengths
print "---------"
print "a\tb\tc"
print "\t".join(str(round(each,2)) for each in s.lattice.abc)
# and angles
print "alpha\tbeta\tgamma"
print "\t".join(str(round(each,2)) for each in s.lattice.angles)
print "---------"
# total number of sites
print "Num. of Sites: "+str(s.num_sites)
print "---------"

# print symmetrically distinct atoms and their wyckoff positions
print "Wyckoff Postions"
equiv=SymmetryFinder(s).get_symmetry_dataset()["equivalent_atoms"]
wy=SymmetryFinder(s).get_symmetry_dataset()["wyckoffs"]

# GROUP ATOMS BY EQUIVALENT POSITIONS
#
예제 #27
0
파일: supercell.py 프로젝트: uw-cmg/MAST
import pymatgen as mg
from pymatgen.core.structure import Structure

filename = raw_input("file name:")
l = raw_input("x scale:")
m = raw_input("y scale:")
n = raw_input("z scale:")

struct = mg.read_structure(filename)
Structure.make_supercell(struct, [l, m, n])
mg.write_structure(struct, "poscar_temp")

f = open("poscar_temp")
w = open("mast.inp", "w")


def getinfo(line):
    line = line.strip("\n")
    data = line.split(" ")
    while 1:
        try:
            data.remove("")
        except:
            break
    return data


line = []
elenum = []

line.append(f.readline())