def calc_ao(qc, drv=None, otype=None, ofid=None, numproc=None, slice_length=None): '''Computes and saves all atomic orbital or a derivative thereof. **Parameters:** qc.geo_spec, qc.geo_info, qc.ao_spec, qc.mo_spec : See :ref:`Central Variables` for details. drv : string or list of strings {None,'x','y', 'z', 'xx', 'xy', ...}, optional If not None, a derivative calculation of the atomic orbitals is requested. otype : str or list of str, optional Specifies output file type. See :data:`otypes` for details. ofid : str, optional Specifies output file name. If None, the filename will be based on :mod:`orbkit.options.outputname`. numproc : int, optional Specifies number of subprocesses for multiprocessing. If None, uses the value from :mod:`options.numproc`. slice_length : int, optional Specifies the number of points per subprocess. If None, uses the value from :mod:`options.slice_length`. **Returns:** ao_list : numpy.ndarray, shape=((NAO,) + N) Contains the computed NAO atomic orbitals on a grid. ''' slice_length = options.slice_length if slice_length is None else slice_length numproc = options.numproc if numproc is None else numproc datalabels = qc.ao_spec.get_labels() ao_list = core.rho_compute(qc, calc_ao=True, drv=drv, slice_length=options.slice_length, numproc=options.numproc) if otype is None: return ao_list if ofid is None: ofid = '%s_AO' % (options.outputname) if not options.no_output: output_written = main_output(ao_list, qc, outputname=ofid, datalabels=qc.ao_spec.get_labels(), otype=otype, drv=drv) return ao_list
def get_ao(x): ao_list = core.ao_creator(global_args['geo_spec'], [global_args['ao_spec'][int(x)]], drv=global_args['drv']) if global_args['otype'] is not None: drv = global_args['drv'] comments = '%03d.lxlylz=%s,at=%d' %(x, global_args['ao_spec'][x]['exp_list'][0], global_args['ao_spec'][x]['atom']) output.main_output(ao_list[0] if drv is None else ao_list, global_args['geo_info'], global_args['geo_spec'], comments=comments, outputname='%s_AO_%03d' % (global_args['ofid'],x), otype=global_args['otype'], omit=['h5','vmd','mayavi'], drv = None if drv is None else [drv]) return ao_list
def run_orbkit(use_qc=None, check_options=True, standalone=False): '''Controls the execution of all computational tasks. **Parameters:** use_qc : QCinfo, optional If not None, the reading of a quantum chemistry output is omitted and the given QCinfo class is used for all computational tasks. (See :ref:`Central Variables` in the manual for details on QCinfo.) check_options : bool, optional If True, the specified options will be validated. **Returns:** data : type and shape depend on the options. Contains orbkit's output. See :ref:`High-Level Interface` in the manual for details. ''' # Set some global variables global qc # Display program information display(lgpl_short) # Check for the correctness of orbkit.options if check_options: display('Checking orbkit.options...\n') options.check_options(display=display, interactive=False, info=True, check_io=(use_qc is None)) # Measurement of required execution time t = [time.time()] # Do we need to read out the info of all MOs? if (options.mo_set or options.calc_mo) is not False: options.all_mo = True if use_qc is None: # Read the input file qc = read.main_read(options.filename, itype=options.itype, all_mo=options.all_mo, spin=options.spin, cclib_parser=options.cclib_parser) else: # Use a user defined QCinfo class. qc = use_qc display('\nSetting up the grid...') if options.grid_file is not None: # Read the grid from an external file grid.read(options.grid_file) elif options.adjust_grid is not None: # Adjust the grid to geo_spec extend, step = options.adjust_grid grid.adjust_to_geo(qc, extend=extend, step=step) elif options.random_grid: # Create a randomized grid grid.random_grid(qc.geo_spec) # Initialize grid grid.grid_init(is_vector=options.is_vector) if options.is_vector: grid.is_regular = False display(grid.get_grid()) # Display the grid if not grid.is_regular and options.center_grid is not None: raise IOError( 'The option --center is only supported for regular grids.') elif options.center_grid is not None: atom = grid.check_atom_select(options.center_grid, qc.geo_info, qc.geo_spec, interactive=True, display=display) # Center the grid to a specific atom and (0,0,0) if requested grid.center_grid(qc.geo_spec[atom - 1], display=display) if check_options or standalone: options.check_grid_output_compatibilty() t.append(time.time()) # A new time step # The calculation of all AOs (--calc_ao) if options.calc_ao != False: data = extras.calc_ao(qc, drv=options.drv, otype=options.otype) t.append(time.time()) # Final time good_bye_message(t) return data # The calculation of selected MOs (--calc_mo) or # the density formed by selected MOs (--mo_set) if (options.mo_set or options.calc_mo) != False: # What should the program do? if options.calc_mo != False: fid_mo_list = options.calc_mo elif options.mo_set != False: fid_mo_list = options.mo_set # Call the function for actual calculation if options.calc_mo != False: data = extras.calc_mo(qc, fid_mo_list, drv=options.drv, otype=options.otype) elif options.mo_set != False: data = extras.mo_set(qc, fid_mo_list, drv=options.drv, laplacian=options.laplacian, otype=options.otype) t.append(time.time()) # Final time good_bye_message(t) return data if options.gross_atomic_density is not None: atom = options.gross_atomic_density rho_atom = extras.numerical_mulliken_charges(atom, qc) if not grid.is_vector: mulliken_num = rho_atom[1] rho_atom = rho_atom[0] if not options.no_output: fid = '%s.h5' % options.outputname display('\nSaving to Hierarchical Data Format file (HDF5)...' + '\n\t%(o)s' % {'o': fid}) output.hdf5_write(fid, mode='w', gname='', atom=core.numpy.array(atom), geo_info=qc.geo_info, geo_spec=qc.geo_spec, gross_atomic_density=rho_atom, x=grid.x, y=grid.y, z=grid.z) if not options.is_vector: output.hdf5_write( fid, mode='a', gname='/numerical_mulliken_population_analysis', **mulliken_num) t.append(time.time()) good_bye_message(t) return rho_atom if options.mo_tefd is not None: mos = options.mo_tefd ao_list = core.ao_creator(qc.geo_spec, qc.ao_spec) mo_tefd = [] index = [] for i, j in mos: mo_tefd.append([]) index.append([]) for ii_d in options.drv: display('\nMO-TEFD: %s->%s %s-component' % (i, j, ii_d)) tefd = extras.mo_transition_flux_density(i, j, qc, drv=ii_d, ao_list=ao_list) mo_tefd[-1].append(tefd) index[-1].append('%s->%s:%s' % (i, j, ii_d)) if not options.no_output: from numpy import array fid = '%s.h5' % options.outputname display('\nSaving to Hierarchical Data Format file (HDF5)...' + '\n\t%(o)s' % {'o': fid}) HDF5_File = output.hdf5_open(fid, mode='w') data = { 'geo_info': array(qc.geo_info), 'geo_spec': array(qc.geo_spec), 'mo_tefd:info': array(index), 'mo_tefd': array(mo_tefd), 'x': grid.x, 'y': grid.y, 'z': grid.z } output.hdf5_append(data, HDF5_File, name='') HDF5_File.close() t.append(time.time()) good_bye_message(t) return mo_tefd t.append(time.time()) # A new time step # Compute the (derivative of the) electron density if options.no_slice: data = core.rho_compute_no_slice(qc, drv=options.drv, laplacian=options.laplacian, return_components=False) else: data = core.rho_compute(qc, drv=options.drv, slice_length=options.slice_length, laplacian=options.laplacian, numproc=options.numproc) if options.drv is None: rho = data elif options.laplacian: rho, delta_rho, laplacian_rho = data else: rho, delta_rho = data # Compute the reduced electron density if requested if options.z_reduced_density: if grid.is_vector: display('\nSo far, reducing the density is not supported for ' + 'vector grids.\nSkipping the reduction...\n') elif options.drv is not None: display( '\nSo far, reducing the density is not supported for ' + 'the derivative of the density.\nSkipping the reduction...\n') else: from scipy import integrate display('\nReducing the density with respect to the z-axis.\n') rho = integrate.simps(rho, grid.x, dx=grid.delta_[0], axis=0, even='avg') rho = integrate.simps(rho, grid.y, dx=grid.delta_[1], axis=0, even='avg') t.append(time.time()) # A new time step # Generate the output requested if not options.no_output: output_written = output.main_output(rho, qc.geo_info, qc.geo_spec, outputname=options.outputname, otype=options.otype, data_id='rho', omit=['vmd', 'mayavi'], mo_spec=qc.mo_spec) if options.drv is not None: output_written.extend( output.main_output(delta_rho, qc.geo_info, qc.geo_spec, outputname=options.outputname, otype=options.otype, data_id='delta_rho', omit=['vmd', 'mayavi'], mo_spec=qc.mo_spec, drv=options.drv)) if options.laplacian: output_written.extend( output.main_output(laplacian_rho, qc.geo_info, qc.geo_spec, outputname=options.outputname + '_laplacian', otype=options.otype, data_id='laplacian_rho', omit=['vmd', 'mayavi'], mo_spec=qc.mo_spec)) if 'vmd' in options.otype: # Create VMD network display('\nCreating VMD network file...' + '\n\t%(o)s.vmd' % {'o': options.outputname}) cube_files = [] for i in output_written: if i.endswith('.cb'): cube_files.append(i) output.vmd_network_creator(options.outputname, cube_files=cube_files) t.append(time.time()) # Final time good_bye_message(t) if 'mayavi' in options.otype: plt_data = [rho] datalabels = ['rho'] if options.drv is not None: plt_data.extend(delta_rho) datalabels.extend( ['d/d%s of %s' % (ii_d, 'rho') for ii_d in options.drv]) if options.laplacian: plt_data.append(laplacian_rho) datalabels.append('laplacian of rho') output.main_output(plt_data, qc.geo_info, qc.geo_spec, otype='mayavi', datalabels=datalabels) # Return the computed data, i.e., rho for standard, and (rho,delta_rho) # for derivative calculations. For laplacian (rho,delta_rho,laplacian_rho) return data
def calc_jmo(qc, ij, drv=['x', 'y', 'z'], numproc=1, otype=None, ofid='', **kwargs): '''Calculate one component (e.g. drv='x') of the transition electoronic flux density between the molecular orbitals i and j. .. math:: moTEFD_{i,j}(r) = <mo_i|\delta(r-r')\\nabla_x|mo_j> **Parameters:** i: int index of the first mo (Bra) j: int index of the second mo (Ket) drv: {0,1,2,'x','y','z'} The desired component of the vector field of the transition electoronic flux density **Returns:** mo_tefd : numpy.ndarray ''' ij = numpy.asarray(ij) if ij.ndim == 1 and len(ij) == 2: ij.shape = (1, 2) assert ij.ndim == 2 assert ij.shape[1] == 2 u, indices = numpy.unique(ij, return_inverse=True) indices.shape = (-1, 2) mo_spec = qc.mo_spec[u] qc_select = qc.copy() qc_select.mo_spec = mo_spec labels = mo_spec.get_labels(format='short') mo_matrix = core.calc_mo_matrix(qc_select, drv=drv, numproc=numproc, **kwargs) jmo = numpy.zeros((len(drv), len(indices)) + grid.get_shape()) datalabels = [] for n, (i, j) in enumerate(indices): jmo[:, n] = -0.5 * (mo_matrix[:, i, j] - mo_matrix[:, j, i]) datalabels.append('j( %s , %s )' % (labels[i], labels[j])) if not options.no_output: output_written = main_output(jmo, qc, outputname=ofid, datalabels=datalabels, otype=otype, drv=drv) return jmo
def calc_mo(qc, fid_mo_list, drv=None, otype=None, ofid=None, numproc=None, slice_length=None): '''Calculates and saves the selected molecular orbitals or the derivatives thereof. **Parameters:** qc.geo_spec, qc.geo_info, qc.ao_spec, qc.mo_spec : See :ref:`Central Variables` for details. fid_mo_list : str Specifies the filename of the molecular orbitals list or list of molecular orbital labels (cf. :mod:`orbkit.read.mo_select` for details). If fid_mo_list is 'all_mo', creates a list containing all molecular orbitals. drv : string or list of strings {None,'x','y', 'z', 'xx', 'xy', ...}, optional If not None, a derivative calculation of the molecular orbitals is requested. otype : str or list of str, optional Specifies output file type. See :data:`otypes` for details. ofid : str, optional Specifies output file name. If None, the filename will be based on :mod:`orbkit.options.outputname`. numproc : int, optional Specifies number of subprocesses for multiprocessing. If None, uses the value from :mod:`options.numproc`. slice_length : int, optional Specifies the number of points per subprocess. If None, uses the value from :mod:`options.slice_length`. **Returns:** mo_list : numpy.ndarray, shape=((NMO,) + N) Contains the NMO=len(qc.mo_spec) molecular orbitals on a grid. ''' mo_spec = qc.mo_spec[fid_mo_list] qc_select = qc.copy() qc_select.mo_spec = mo_spec slice_length = options.slice_length if slice_length is None else slice_length numproc = options.numproc if numproc is None else numproc # Calculate the AOs and MOs mo_list = core.rho_compute(qc_select, calc_mo=True, drv=drv, slice_length=slice_length, numproc=numproc) if otype is None: return mo_list if ofid is None: if '@' in options.outputname: outputname, group = options.outputname.split('@') else: outputname, group = options.outputname, '' outputname, autootype = os.path.splitext(outputname) ofid = '%s_MO%s@%s' % (outputname, autootype, group) if not options.no_output: output_written = main_output(mo_list, qc_select, outputname=ofid, datalabels=qc_select.mo_spec.get_labels(), otype=otype, drv=drv) return mo_list
def mo_set(qc, fid_mo_list, drv=None, laplacian=None, otype=None, ofid=None, return_all=True, numproc=None, slice_length=None): '''Calculates and saves the density or the derivative thereof using selected molecular orbitals. **Parameters:** qc.geo_spec, qc.geo_info, qc.ao_spec, qc.mo_spec : See :ref:`Central Variables` for details. fid_mo_list : str Specifies the filename of the molecular orbitals list or list of molecular orbital labels (cf. :mod:`orbkit.orbitals.MOClass.select` for details). otype : str or list of str, optional Specifies output file type. See :data:`otypes` for details. ofid : str, optional Specifies output file name. If None, the filename will be based on :mod:`orbkit.options.outputname`. drv : string or list of strings {None,'x','y', 'z', 'xx', 'xy', ...}, optional If not None, a derivative calculation is requested. return_all : bool If False, no data will be returned. numproc : int, optional Specifies number of subprocesses for multiprocessing. If None, uses the value from :mod:`options.numproc`. slice_length : int, optional Specifies the number of points per subprocess. If None, uses the value from :mod:`options.slice_length`. **Returns:** datasets : numpy.ndarray, shape=((NSET,) + N) Contains the NSET molecular orbital sets on a grid. delta_datasets : numpy.ndarray, shape=((NSET,NDRV) + N) Contains the NDRV NSET molecular orbital set on a grid. This is only present if derivatives are requested. ''' #Can be an mo_spec or a list of mo_spec # For later iteration we'll make it into a list here if it is not mo_info_list = qc.mo_spec.select(fid_mo_list, flatten_input=False) drv = options.drv if drv is None else drv laplacian = options.laplacian if laplacian is None else laplacian slice_length = options.slice_length if slice_length is None else slice_length numproc = options.numproc if numproc is None else numproc if ofid is None: ofid = options.outputname datasets = [] datalabels = [] delta_datasets = [] delta_datalabels = [] cube_files = [] for i_file, mo_info in enumerate(mo_info_list): qc_select = qc.copy() qc_select.mo_spec = mo_info label = 'mo_set:' + mo_info.selection_string display('\nStarting with the molecular orbital list \n\t' + label + '\n\t(Only regarding existing and occupied mos.)\n') data = core.rho_compute(qc_select, drv=drv, laplacian=laplacian, slice_length=slice_length, numproc=numproc) if drv is None: rho = data delta_datasets = numpy.zeros((0, ) + rho.shape) elif laplacian: rho, delta_rho, laplacian_rho = data delta_datasets.extend(delta_rho) delta_datasets.append(laplacian_rho) delta_datalabels.extend( ['d^2/d%s^2 %s' % (i, label) for i in 'xyz']) delta_datalabels.append('laplacian_of_' + label) else: rho, delta_rho = data delta_datasets.extend(delta_rho) delta_datalabels.extend(['d/d%s %s' % (i, label) for i in drv]) datasets.append(rho) datalabels.append(label) datasets = numpy.array(datasets) delta_datasets = numpy.array(delta_datasets) delta_datalabels.append('mo_set') data = numpy.append(datasets, delta_datasets, axis=0) if not options.no_output: output_written = main_output(data, qc, outputname=ofid, datalabels=datalabels + delta_datalabels, otype=otype, drv=None) return data
def calc_mo(qc, fid_mo_list, drv=None, otype=None, ofid=None, numproc=None, slice_length=None): '''Calculates and saves the selected molecular orbitals or the derivatives thereof. **Parameters:** qc.geo_spec, qc.geo_info, qc.ao_spec, qc.mo_spec : See :ref:`Central Variables` for details. fid_mo_list : str Specifies the filename of the molecular orbitals list or list of molecular orbital labels (cf. :mod:`orbkit.read.mo_select` for details). If fid_mo_list is 'all_mo', creates a list containing all molecular orbitals. drv : int or string, {None, 'x', 'y', 'z', 0, 1, 2}, optional If not None, a derivative calculation of the atomic orbitals is requested. otype : str or list of str, optional Specifies output file type. See :data:`otypes` for details. ofid : str, optional Specifies output file name. If None, the filename will be based on :mod:`orbkit.options.outputname`. numproc : int, optional Specifies number of subprocesses for multiprocessing. If None, uses the value from :mod:`options.numproc`. slice_length : int, optional Specifies the number of points per subprocess. If None, uses the value from :mod:`options.slice_length`. **Returns:** mo_list : numpy.ndarray, shape=((NMO,) + N) Contains the NMO=len(qc.mo_spec) molecular orbitals on a grid. mo_info : dict Contains information of the selected molecular orbitals and has following Members: :mo: - List of molecular orbital labels. :mo_ii: - List of molecular orbital indices. :mo_spec: - Selected elements of mo_spec. See :ref:`Central Variables` for details. :mo_in_file: - List of molecular orbital labels within the fid_mo_list file. :sym_select: - If True, symmetry labels have been used. ''' mo_info = mo_select(qc.mo_spec, fid_mo_list, strict=True) qc_select = qc.todict() qc_select['mo_spec'] = mo_info['mo_spec'] slice_length = options.slice_length if slice_length is None else slice_length numproc = options.numproc if numproc is None else numproc # Calculate the AOs and MOs mo_list = core.rho_compute(qc_select, calc_mo=True, drv=drv, slice_length=slice_length, numproc=numproc) if otype is None: return mo_list, mo_info if ofid is None: ofid = '%s_MO' % (options.outputname) if not options.no_output: if 'h5' in otype: output.main_output(mo_list,qc.geo_info,qc.geo_spec,data_id='MO', outputname=ofid, mo_spec=qc_select['mo_spec'],drv=drv,is_mo_output=True) # Create Output cube_files = [] for i,j in enumerate(qc_select['mo_spec']): outputname = '%s_%s' % (ofid,mo_info['mo'][i]) comments = ('%s,Occ=%.1f,E=%+.4f' % (mo_info['mo'][i], j['occ_num'], j['energy'])) index = numpy.index_exp[:,i] if drv is not None else i output_written = output.main_output(mo_list[index], qc.geo_info,qc.geo_spec, outputname=outputname, comments=comments, otype=otype,omit=['h5','vmd','mayavi'], drv=drv) for i in output_written: if i.endswith('.cb'): cube_files.append(i) if 'vmd' in otype and cube_files != []: display('\nCreating VMD network file...' + '\n\t%(o)s.vmd' % {'o': ofid}) output.vmd_network_creator(ofid,cube_files=cube_files) if 'mayavi' in otype: datalabels = ['MO %(sym)s, Occ=%(occ_num).2f, E=%(energy)+.4f E_h' % i for i in qc_select['mo_spec']] if drv is not None: tmp = [] for i in drv: for j in datalabels: tmp.append('d/d%s of %s' % (i,j)) datalabels = tmp data = mo_list.reshape((-1,) + grid.get_shape()) output.main_output(data,qc.geo_info,qc.geo_spec, otype='mayavi',datalabels=datalabels) return mo_list, mo_info
def mo_set(qc, fid_mo_list, drv=None, laplacian=None, otype=None, ofid=None, return_all=True, numproc=None, slice_length=None): '''Calculates and saves the density or the derivative thereof using selected molecular orbitals. **Parameters:** qc.geo_spec, qc.geo_info, qc.ao_spec, qc.mo_spec : See :ref:`Central Variables` for details. fid_mo_list : str Specifies the filename of the molecular orbitals list or list of molecular orbital labels (cf. :mod:`orbkit.read.mo_select` for details). otype : str or list of str, optional Specifies output file type. See :data:`otypes` for details. ofid : str, optional Specifies output file name. If None, the filename will be based on :mod:`orbkit.options.outputname`. drv : int or string, {None, 'x', 'y', 'z', 0, 1, 2}, optional If not None, a derivative calculation of the atomic orbitals is requested. return_all : bool If False, no data will be returned. numproc : int, optional Specifies number of subprocesses for multiprocessing. If None, uses the value from :mod:`options.numproc`. slice_length : int, optional Specifies the number of points per subprocess. If None, uses the value from :mod:`options.slice_length`. **Returns:** datasets : numpy.ndarray, shape=((NSET,) + N) Contains the NSET molecular orbital sets on a grid. delta_datasets : numpy.ndarray, shape=((NSET,NDRV) + N) Contains the NDRV NSET molecular orbital set on a grid. This is only present if derivatives are requested. mo_info : dict Contains information of the selected molecular orbitals and has following Members: :mo: - List of molecular orbital labels. :mo_ii: - List of molecular orbital indices. :mo_spec: - Selected elements of mo_spec. See :ref:`Central Variables` for details. :mo_in_file: - List of molecular orbital labels within the fid_mo_list file. :sym_select: - If True, symmetry labels have been used. ''' mo_info = mo_select(qc.mo_spec, fid_mo_list, strict=False) qc_select = qc.todict() drv = options.drv if drv is None else drv laplacian = options.laplacian if laplacian is None else laplacian slice_length = options.slice_length if slice_length is None else slice_length numproc = options.numproc if numproc is None else numproc if ofid is None: ofid = options.outputname if 'h5' in otype and os.path.exists('%s.h5' % ofid): raise IOError('%s.h5 already exists!' % ofid) datasets = [] delta_datasets = [] cube_files = [] for i_file,j_file in enumerate(mo_info['mo_in_file']): display('Starting with the %d. element of the molecular orbital list (%s)...\n\t' % (i_file+1,fid_mo_list) + str(j_file) + '\n\t(Only regarding existing and occupied mos.)\n') qc_select['mo_spec'] = [] for i_mo,j_mo in enumerate(mo_info['mo']): if j_mo in j_file: if mo_info['sym_select']: ii_mo = numpy.argwhere(mo_info['mo_ii'] == j_mo) else: ii_mo = i_mo qc_select['mo_spec'].append(mo_info['mo_spec'][int(ii_mo)]) data = core.rho_compute(qc_select, drv=drv, laplacian=laplacian, slice_length=slice_length, numproc=numproc) datasets.append(data) if drv is None: rho = data elif laplacian: rho, delta_rho, laplacian_rho = data delta_datasets.extend(delta_rho) delta_datasets.append(laplacian_rho) else: rho, delta_rho = data delta_datasets.append(delta_rho) if options.z_reduced_density: if grid.is_vector: display('\nSo far, reducing the density is not supported for vector grids.\n') elif drv is not None: display('\nSo far, reducing the density is not supported for the derivative of the density.\n') else: rho = integrate.simps(rho, grid.x, dx=grid.delta_[0], axis=0, even='avg') rho = integrate.simps(rho, grid.y, dx=grid.delta_[1], axis=0, even='avg') if not options.no_output: if 'h5' in otype: display('Saving to Hierarchical Data Format file (HDF5)...') group = '/mo_set:%03d' % (i_file+1) display('\n\t%s.h5 in the group "%s"' % (ofid,group)) output.HDF5_creator(rho,ofid,qc.geo_info,qc.geo_spec,data_id='rho', mode='w',group=group,mo_spec=qc_select['mo_spec']) if drv is not None: for i,j in enumerate(drv): data_id = 'rho_d%s' % j output.HDF5_creator(delta_rho[i],ofid,qc.geo_info,qc.geo_spec, data_id=data_id,data_only=True,mode='a', group=group,mo_spec=qc_select['mo_spec']) if laplacian: data_id = 'rho_laplacian' output.HDF5_creator(laplacian_rho,ofid,qc.geo_info,qc.geo_spec, data_id=data_id,data_only=True,mode='a', group=group,mo_spec=qc_select['mo_spec']) fid = '%s_%03d' % (ofid, i_file+1) cube_files.append('%s.cb' % fid) comments = ('mo_set:'+','.join(j_file)) output.main_output(rho,qc.geo_info,qc.geo_spec,outputname=fid, otype=otype,omit=['h5','vmd','mayavi'], comments=comments) if drv is not None: for i,j in enumerate(drv): fid = '%s_%03d_d%s' % (ofid, i_file+1, j) cube_files.append('%s.cb' % fid) comments = ('d%s_of_mo_set:' % j + ','.join(j_file)) output.main_output(delta_rho[i],qc.geo_info,qc.geo_spec,outputname=fid, otype=otype,omit=['h5','vmd','mayavi'], comments=comments) if laplacian: fid = '%s_%03d_laplacian' % (ofid, i_file+1) cube_files.append('%s.cb' % fid) comments = ('laplacian_of_mo_set:' + ','.join(j_file)) output.main_output(laplacian_rho,qc.geo_info,qc.geo_spec,outputname=fid, otype=otype,omit=['h5','vmd','mayavi'], comments=comments) if 'vmd' in otype and cube_files != []: display('\nCreating VMD network file...' + '\n\t%(o)s.vmd' % {'o': ofid}) output.vmd_network_creator(ofid,cube_files=cube_files) datasets = numpy.array(datasets) if drv is None: if 'mayavi' in otype: output.main_output(datasets,qc.geo_info,qc.geo_spec, otype='mayavi',datalabels=mo_info['mo_in_file']) return datasets, mo_info else: delta_datasets = numpy.array(delta_datasets) if 'mayavi' in otype: datalabels = [] for i in mo_info['mo_in_file']: datalabels.extend(['d/d%s of %s' % (j,i) for j in drv]) if laplacian: datalabels.append('laplacian of %s' % i) output.main_output(delta_datasets.reshape((-1,) + grid.get_shape()), qc.geo_info,qc.geo_spec,otype='mayavi',datalabels=datalabels) return datasets, delta_datasets, mo_info
def calc_ao(qc, drv=None, otype=None, ofid=None): '''Computes and saves all atomic orbital or a derivative thereof. **Parameters:** qc.geo_spec, qc.geo_info, qc.ao_spec : See :ref:`Central Variables` for details. otype : str or list of str, optional Specifies output file type. See :data:`otypes` for details. ofid : str, optional Specifies output file name. If None, the filename will be based on :mod:`orbkit.options.outputname`. drv : int or string, {None, 'x', 'y', 'z', 'xx', 'xy', ...}, optional If not None, a derivative calculation of the atomic orbitals is requested. **Returns:** ao_list : numpy.ndarray, shape=((NAO,) + N) Contains the computed NAO atomic orbitals on a grid. Is only returned, if otype is None. ''' from omp_functions import run if ofid is None: ofid = options.outputname dstr = '' if drv is None else '_d%s' % drv ao_spec = [] lxlylz = [] datalabels = [] for sel_ao in range(len(qc.ao_spec)): if 'exp_list' in qc.ao_spec[sel_ao].keys(): l = qc.ao_spec[sel_ao]['exp_list'] else: l = core.exp[core.lquant[qc.ao_spec[sel_ao]['type']]] lxlylz.extend(l) for i in l: ao_spec.append(qc.ao_spec[sel_ao].copy()) ao_spec[-1]['exp_list'] = [i] datalabels.append('lxlylz=%s,atom=%d' %(i,ao_spec[-1]['atom'])) global_args = {'geo_spec':qc.geo_spec, 'geo_info':qc.geo_info, 'ao_spec':ao_spec, 'drv':drv, 'x':grid.x, 'y':grid.y, 'z':grid.z, 'is_vector':grid.is_vector, 'otype':otype, 'ofid':ofid} display('Starting the computation of the %d atomic orbitals'%len(ao_spec)+ (' using %d subprocesses.' % options.numproc if options.numproc > 1 else '.' ) ) ao = run(get_ao,x=numpy.arange(len(ao_spec)).reshape((-1,1)), numproc=options.numproc,display=display, initializer=initializer,global_args=global_args) if otype is None or 'h5' in otype or 'mayavi' in otype: ao_list = [] for i in ao: ao_list.extend(i) ao_list = numpy.array(ao_list) if otype is None or options.no_output: return ao_list if 'h5' in otype: import h5py fid = '%s_AO%s.h5' % (ofid,dstr) display('Saving to Hierarchical Data Format file (HDF5)...\n\t%s' % fid) output.hdf5_write(fid,mode='w',gname='general_info', x=grid.x,y=grid.y,z=grid.z, geo_info=qc.geo_info,geo_spec=qc.geo_spec, lxlylz=numpy.array(lxlylz,dtype=numpy.int64), aolabels=numpy.array(datalabels), grid_info=numpy.array(grid.is_vector,dtype=int)) for f in output.hdf5_open(fid,mode='a'): output.hdf5_append(ao_spec,f,name='ao_spec') output.hdf5_append(ao_list,f,name='ao_list') if 'mayavi' in otype: output.main_output(ao_list,qc.geo_info,qc.geo_spec, otype='mayavi',datalabels=datalabels) if 'vmd' in otype and options.vector is None: fid = '%s_AO%s' % (ofid,dstr) display('\nCreating VMD network file...' + '\n\t%(o)s.vmd' % {'o': fid}) output.vmd_network_creator(fid, cube_files=['%s_AO%s_%03d.cb' % (ofid, dstr,x) for x in range(len(ao_spec))])
# Run orbkit rho,delta_rho = core.rho_compute(qc,drv=['x','y','z'],numproc=4) # Compute the reduced density gradient from numpy import sqrt,pi s = (1./(2*(3*pi**2)**(1/3.)) * sqrt((delta_rho**2).sum(axis=0))/(rho**(4/3.))) # Apply a density cutoff, i.e., consider only values for rho < 0.05 a.u. s[rho>0.05] = 1e3 # Write a cube file and vmd script for the reduced density gradient output.main_output(s, qc.geo_info, # atomic information qc.geo_spec, # atomic coordinates outputname='reduced_drho', otype=['cb','vmd'], iso=(-0.5,0.5) # isocontour value of s = 0.5 a.u. ) ''' Classify the interaction types using the second derivatives of the density ("the three eigenvalues of the electronic Hessian matrix") ''' # Compute the second derivatives of the density rho,delta2_rho = core.rho_compute(qc,drv=['xx','yy','zz'],numproc=4) # Sort the three components of the derivatives # The sign of the second value determines, if the interaction is bonding (negative) # non-bonding (positive)
of the gross atomic density. Hint: Use the VMD script file (ch2o.vmd) for depicting the results. ''' from orbkit import read, grid, extras, output, atomic_populations, display # Open molden file and read parameters qc = read.main_read('ch2o.molden', itype='molden') # Perform a Mulliken population analysis and write the output to a PDB file pop = atomic_populations.mulliken(qc) output.pdb_creator(qc.geo_info, qc.geo_spec, filename='ch2o', charges=pop['charge']) # Initialize the grid display.display('\nSetting up the grid...') grid.adjust_to_geo(qc, extend=5.0, step=0.1) grid.grid_init() display.display(grid.get_grid()) # Compute and save the gross atomic density of the C atom rho_atom = extras.gross_atomic_density(1, qc) output.main_output(rho_atom[0], qc.geo_info, qc.geo_spec, outputname='ch2o', otype='cb')
def run_orbkit(use_qc=None,check_options=True,standalone=False): '''Controls the execution of all computational tasks. **Parameters:** use_qc : QCinfo, optional If not None, the reading of a quantum chemistry output is omitted and the given QCinfo class is used for all computational tasks. (See :ref:`Central Variables` in the manual for details on QCinfo.) check_options : bool, optional If True, the specified options will be validated. **Returns:** data : type and shape depend on the options. Contains orbkit's output. See :ref:`High-Level Interface` in the manual for details. ''' # Set some global variables global qc # Display program information display(lgpl_short) # Check for the correctness of orbkit.options if check_options: display('Checking orbkit.options...\n') options.check_options(display=display, interactive=False, info=True,check_io=(use_qc is None)) # Measurement of required execution time t=[time.time()] # Do we need to read out the info of all MOs? if (options.mo_set or options.calc_mo) is not False: options.all_mo = True if use_qc is None: # Read the input file qc = read.main_read(options.filename, itype=options.itype, all_mo=options.all_mo, spin=options.spin, cclib_parser=options.cclib_parser) else: # Use a user defined QCinfo class. qc = use_qc if 'native' in options.otype: output.main_output(qc, outputname=options.outputname, otype='native', ftype=options.niotype) options.otype.remove('native') if not len(options.otype): t.append(time.time()) # Final time good_bye_message(t) return display('\nSetting up the grid...') if options.grid_file is not None: # Read the grid from an external file grid.read(options.grid_file) elif options.adjust_grid is not None: # Adjust the grid to geo_spec extend,step = options.adjust_grid grid.adjust_to_geo(qc,extend=extend,step=step) elif options.random_grid: # Create a randomized grid grid.random_grid(qc.geo_spec) # Initialize grid grid.grid_init(is_vector=options.is_vector) if options.is_vector: grid.is_regular = False display(grid.get_grid()) # Display the grid if not grid.is_regular and options.center_grid is not None: raise IOError('The option --center is only supported for regular grids.') elif options.center_grid is not None: atom = grid.check_atom_select(options.center_grid,qc.geo_info,qc.geo_spec, interactive=True,display=display) # Center the grid to a specific atom and (0,0,0) if requested grid.center_grid(qc.geo_spec[atom-1],display=display) if check_options or standalone: options.check_grid_output_compatibilty() t.append(time.time()) # A new time step # The calculation of all AOs (--calc_ao) if options.calc_ao != False: data = extras.calc_ao(qc, drv=options.drv, otype=options.otype) t.append(time.time()) # Final time good_bye_message(t) return data # The calculation of selected MOs (--calc_mo) or # the density formed by selected MOs (--mo_set) if (options.mo_set or options.calc_mo) != False: # What should the program do? if options.calc_mo != False: fid_mo_list = options.calc_mo elif options.mo_set != False: fid_mo_list = options.mo_set # Call the function for actual calculation if options.calc_mo != False: data = extras.calc_mo(qc, fid_mo_list, drv=options.drv, otype=options.otype) elif options.mo_set != False: data = extras.mo_set(qc, fid_mo_list, drv=options.drv, laplacian=options.laplacian, otype=options.otype) t.append(time.time()) # Final time good_bye_message(t) return data if options.gross_atomic_density is not None: rho_atom = extras.gross_atomic_density(options.gross_atomic_density,qc, drv=options.drv) if not options.no_output: output_written = output.main_output(rho_atom, qc, outputname=options.outputname, otype=options.otype) t.append(time.time()) good_bye_message(t) return rho_atom t.append(time.time()) # A new time step # Compute the (derivative of the) electron density if options.no_slice: data = core.rho_compute_no_slice(qc, drv=options.drv, laplacian=options.laplacian, return_components = False) else: data = core.rho_compute(qc, drv=options.drv, slice_length=options.slice_length, laplacian=options.laplacian, numproc=options.numproc) if options.drv is None: rho = data elif options.laplacian: rho, delta_rho, laplacian_rho = data else: rho, delta_rho = data t.append(time.time()) # A new time step # Generate the output requested if not options.no_output: if not (options.drv is not None or options.laplacian): plt_data = rho datalabels = 'rho' else: plt_data = [rho] datalabels = ['rho'] if options.drv is not None: plt_data.extend(delta_rho) datalabels.extend(['d/d%s of %s' % (ii_d,'rho') for ii_d in options.drv]) if options.laplacian: plt_data.append(laplacian_rho) datalabels.append('laplacian of rho') output.main_output(plt_data,qc,outputname=options.outputname, otype=options.otype,datalabels=datalabels) t.append(time.time()) # Final time good_bye_message(t) # Return the computed data, i.e., rho for standard, and (rho,delta_rho) # for derivative calculations. For laplacian (rho,delta_rho,laplacian_rho) return data
''' Partial Charges and Gross Atomic Density Example for the orbkit's non-grid based capabilities and for the computation of the gross atomic density. Hint: Use the VMD script file (ch2o.vmd) for depicting the results. ''' from orbkit import read, grid, extras, output, atomic_populations, display # Open molden file and read parameters qc = read.main_read('ch2o.molden', itype='molden') # Perform a Mulliken population analysis and write the output to a PDB file pop = atomic_populations.mulliken(qc) output.pdb_creator(qc.geo_info, qc.geo_spec, filename='ch2o', charges=pop['charge']) # Initialize the grid display.display('Setting up the grid...') grid.adjust_to_geo(qc, extend=5.0, step=0.1) grid.grid_init() display.display(grid.get_grid()) # Compute and save the gross atomic density of the C atom rho_atom = extras.gross_atomic_density(1, qc) output.main_output(rho_atom[0], qc, outputname='ch2o', otype='cb')
display.display(grid.get_grid()) # Run orbkit rho,delta_rho = core.rho_compute(qc,drv=['x','y','z'],numproc=4) # Compute the reduced density gradient from numpy import sqrt,pi s = (1./(2*(3*pi**2)**(1/3.)) * sqrt((delta_rho**2).sum(axis=0))/(rho**(4/3.))) # Apply a density cutoff, i.e., consider only values for rho < 0.05 a.u. s[rho>0.05] = 1e3 # Write a cube file and vmd script for the reduced density gradient output.main_output(s, qc, # atomic information outputname='reduced_drho', otype=['cb','vmd'], iso=(-0.5,0.5) # isocontour value of s = 0.5 a.u. ) ''' Classify the interaction types using the second derivatives of the density ("the three eigenvalues of the electronic Hessian matrix") ''' # Compute the second derivatives of the density rho,delta2_rho = core.rho_compute(qc,drv=['xx','yy','zz'],numproc=4) # Sort the three components of the derivatives # The sign of the second value determines, if the interaction is bonding (negative) # non-bonding (positive) delta2_rho.sort(axis=0)