pibronic.vibronic package

Scripts that handle data

pibronic.vibronic.VMK

alias of pibronic.vibronic.vibronic_model_keys.VibronicModelKeys

Subpackages

• pibronic.vibronic.orthonormal package
  • Code involved in the creation of orthonormal matrices
  • Submodules
  • pibronic.vibronic.orthonormal.create module
  • pibronic.vibronic.orthonormal.sequences module

Submodules

pibronic.vibronic.electronic_structure module

class pibronic.vibronic.electronic_structure.State

Bases: enum.Enum

An enumeration.

FINISHED = 7

IPEOMCC = 4

NIP = 2

OPT = 1

PREPVIB = 5

VIB = 3

VIBRON = 6

class pibronic.vibronic.electronic_structure.VibronExecutionClass(name, root, state=None)

Bases: object

handles all details related to the execution

advance()

increase state counter and log it IF not already at the highest state

calculate_vibronic_model()

file_in = {}

file_out = {}

geom()

wrapper method

hf(matching_state)

wrapper method

ip_calc()

wrapper method

name = None

parameter_dictionary = {'DROPMO': '', 'NIP': None, 'basis': None, 'calculation': None, 'ccConv': 10, 'estateTol': 10, 'gridVibron': 3, 'scfConv': 10, 'theory': None}

parse_input_parameters(file_path=None)

loads data into the object

path_root = None

prepVibron()

wrapper method

record_state()

setup_zmat(file_path=None)

assumes that you formatted the ZMAT file correctly

singles_cutoff = 85.0

state = None

triples_cutoff = 92.0

vib()

wrapper method

vibron_calc()

wrapper method

zmat = None

class pibronic.vibronic.electronic_structure.ZmatClass(file_path)

Bases: object

handles all details related to zmat file which represents the geometry of the molecule can hold internal or cartesian coordinates

get(opt_zmat=False)

returns a string which represents the coordinates

kind = 'cartesian'

set(geometry_new)

updates geometry data

pibronic.vibronic.electronic_structure.calculate_vibronic_model_wrapper_one(data_set_num, molecule_name='ch2o', inital_job_state=0)

executes jobs using exists data_set_# file structure

pibronic.vibronic.electronic_structure.calculations_list = ['IP']

get the functions name

pibronic.vibronic.electronic_structure.find_string_in_file(memmap_file, file_path, target_string)

wrapper that raises error if no substr can be found finds the first occurrence of a substring in memory mapped file

pibronic.vibronic.electronic_structure.geometry_optimization(path_root, name, zmat, parameter_dictionary)

creates and populates the input file and submission file for the job

pibronic.vibronic.electronic_structure.get_integer_from_user(message)

return the integer value of the users response to a input prompt

pibronic.vibronic.electronic_structure.get_yes_no_from_user(message)

return the Boolean value of the users response the a yes/no question

pibronic.vibronic.electronic_structure.hartree_fock_calculation(path_root, name, zmat, parameter_dictionary, hf_type)

creates and populates the input file and submission file for the job

pibronic.vibronic.electronic_structure.ip_calculation(path_root, name, zmat, parameter_dictionary)

creates and populates the input file and submission file for the job

pibronic.vibronic.electronic_structure.main()

pibronic.vibronic.electronic_structure.pairwise(iterable)

returns an iterator over pairs of elements in the iterable

pibronic.vibronic.electronic_structure.parse_hartree_fock_output(vibron, execution_state)

extracts relevant data from output of job

pibronic.vibronic.electronic_structure.parse_input_parameters(file_path=None)

pibronic.vibronic.electronic_structure.parse_ip_output(vibron)

extracts relevant data from output of job

pibronic.vibronic.electronic_structure.parse_opt_output(vibron)

extract substrings describing the optimized geometry from the output file generated by a geometry optimization calculation

pibronic.vibronic.electronic_structure.parse_prepVibron_output(vibron)

extracts relevant data from output of job

pibronic.vibronic.electronic_structure.parse_vibron_output(vibron)

extracts relevant data from output of job

pibronic.vibronic.electronic_structure.prepVibron_calculation(path_root, name, zmat, parameter_dictionary)

creates and populates the input file and submission file for the job

pibronic.vibronic.electronic_structure.pretty_print_job_status(path=None)

quick hack for scripting, path should look something like /**/data_set_{:d}/electronic_structure/execution_state.txt

pibronic.vibronic.electronic_structure.rfind_string_in_file(memmap_file, file_path, target_string)

wrapper that raises error if no substr can be found finds the last occurrence of a substring in memory mapped file

pibronic.vibronic.electronic_structure.skip_back_n_lines(memmap_file, n, start_index)

gives the byte location n lines before the given byte location start_index

pibronic.vibronic.electronic_structure.skip_forward_n_lines(memmap_file, n, start_index)

gives the byte location n lines after the given byte location start_index

pibronic.vibronic.electronic_structure.submit_job(parameter_dictionary)

wrapper for job_boss job submission

pibronic.vibronic.electronic_structure.temp_file_path(root)

pibronic.vibronic.electronic_structure.test_one(molecule_name='ch2o', inital_job_state=0)

runs the job in the current directory stores results in folder named by the molecule

pibronic.vibronic.electronic_structure.verify_aces2_completed(path_root, file_path, job_id)

verifies that the aces2 output file has completed successfully

pibronic.vibronic.electronic_structure.verify_file_exists(file_path)

raises FileNotFoundError exception if input is not a file, or does not exist

pibronic.vibronic.electronic_structure.verify_ip_states(job)

run calculations to verify the range of states selected

pibronic.vibronic.electronic_structure.vibrational_frequency(path_root, name, zmat, parameter_dictionary)

creates and populates the input file and submission file for the job

pibronic.vibronic.electronic_structure.vibron_calculation(path_root, name, zmat, parameter_dictionary)

creates and populates the input file and submission file for the job

pibronic.vibronic.electronic_structure.wait_on_results(job_id, job_type)

synchronizes with the submitted job and verifies that the job’s output is successful

pibronic.vibronic.model_auto module

module that handles parsing model.auto files

pibronic.vibronic.model_auto.confirm_symmetry_in_modes(mode_range, quadratic_couplings)

check for symmetry in modes

pibronic.vibronic.model_auto.confirm_symmetry_in_surfaces(el_range, linear_couplings, quadratic_couplings)

check for symmetry in surfaces

pibronic.vibronic.model_auto.fill_in_diagonal_quadratic_couplings(f_iter, el_range, mode_range, quadratic_couplings)

does what it says

pibronic.vibronic.model_auto.fill_in_excitation_energies(f_iter, el_range, excitation_energies)

does what it says

pibronic.vibronic.model_auto.fill_in_linear_couplings(f_iter, el_range, mode_range, linear_couplings)

does what it says

pibronic.vibronic.model_auto.fill_in_offdiagonal_quadratic_couplings(f_iter, el_range, mode_range, quadratic_couplings)

does what it says

pibronic.vibronic.model_auto.read_header(f_iter, nel, nmode, frequencies)

pibronic.vibronic.model_auto.read_model_auto_file(filename)

if the shift to MCTDH file structure is permanent this function will no longer be needed

Read Vibronic Model file (cp.auto) which contains all information on the approximate Born-Oppenheimer Ground State PES.

Returns: number of electronic states number of normal modes

Excitation energies: (nel, nel) frequencies (nmode) linear couplings: (nmode, nel, nel) quadratic couplings: (nmode, nmode, nel, nel)

pibronic.vibronic.model_h module

module that handles parsing model.h files

pibronic.vibronic.model_h.extract_cubic_couplings(path, memmap, coupling_terms, frequencies)

not implemented at this time

pibronic.vibronic.model_h.extract_energies(path, memmap, energies)

fill the array energies with appropriate values from the memmap’ed file

pibronic.vibronic.model_h.extract_linear_couplings(path, memmap, coupling_terms, frequencies)

fill the array coupling_terms with appropriate values from the memmap’ed file the frequencies need to be provided in wavenumbers

pibronic.vibronic.model_h.extract_normal_mode_frequencies(path, file, frequency_array, symmetric_modes)

fill the array frequency_array with appropriate values from the memmap’ed file

pibronic.vibronic.model_h.extract_offdiag_quadratic_couplings(path, memmap, coupling_terms, frequencies)

fill the array coupling_terms with appropriate values from the memmap’ed file the frequencies need to be provided in wavenumbers

pibronic.vibronic.model_h.extract_quadratic_couplings(path, memmap, coupling_terms, frequencies)

fill the array coupling_terms with appropriate values from the memmap’ed file the frequencies need to be provided in wavenumbers

pibronic.vibronic.model_h.extract_quartic_couplings(path, memmap, coupling_terms, frequencies)

not implemented at this time

pibronic.vibronic.model_h.get_number_of_electronic_states(path, file)

return the number of electronic states (int) taken from file

pibronic.vibronic.model_h.get_number_of_normal_modes(path, file)

return the total number of normal modes (int) and symmetric modes (int) taken from file

pibronic.vibronic.model_h.read_model_h_file(path_file_h)

reads/parses molecule_vibron.h file

pibronic.vibronic.model_op module

module that handles parsing model.op files

pibronic.vibronic.model_op.extract_bicubic_couplings(path, memmap, coupling_terms)

x

pibronic.vibronic.model_op.extract_biquartic_couplings(path, memmap, coupling_terms)

x

pibronic.vibronic.model_op.extract_cubic_couplings(path, memmap, coupling_terms)

x

pibronic.vibronic.model_op.extract_energies(path, memmap)

x

pibronic.vibronic.model_op.extract_linear_couplings(path, memmap, coupling_terms)

x

pibronic.vibronic.model_op.extract_normal_mode_frequencies(path, memmap)

store output in frequency_array

pibronic.vibronic.model_op.extract_quadratic_couplings(path, memmap, coupling_terms)

x

pibronic.vibronic.model_op.extract_quartic_couplings(path, memmap, coupling_terms)

x

pibronic.vibronic.model_op.read_model_op_file(path_file_op)

reads/parses molecule_vibron.op file

pibronic.vibronic.vibronic_model_io module

vibronic_model_io.py should handle the majority of file I/O

pibronic.vibronic.vibronic_model_io.create_basic_diagonal_model(FS)

wrapper function to make the simplest diagonal(sampling) model

pibronic.vibronic.vibronic_model_io.create_coupling_from_h_file(FS, path_file_h)

assumes that the path_file_h is in electronic_structure

pibronic.vibronic.vibronic_model_io.create_coupling_from_op_file(FS, path_file_op)

assumes that the path_file_op is in electronic_structure

pibronic.vibronic.vibronic_model_io.create_coupling_from_op_hyperlink(FS, url)

assumes that the path_file_op is in electronic_structure

pibronic.vibronic.vibronic_model_io.create_diagonal_model_hash(FS=None, path=None)

create a hash of the sampling_model.json file’s contents this is used to confirm that result files were generated for the current model and not an older one uses a FileStructure or an absolute path to the file

pibronic.vibronic.vibronic_model_io.create_fake_coupled_model(FS, tuning_parameter=0.01, transformation_matrix=None)

take the diagonal coupled model and preform a unitary transformation on it to get a dense matrix

for a tuning_parameter of 0 the transformation matrix (U) is identity the larger the value of tuning_parameter the “farther” away from identity U becomes

if a numpy array of dim AxA is provided in the transformation_matrix then we won’t create a new matrix and instead use the provided one note: if transformation_matrix is provided then the tuning_parameter is ignored

pibronic.vibronic.vibronic_model_io.create_harmonic_model(FS)

wrapper function to refresh harmonic model

pibronic.vibronic.vibronic_model_io.create_model_hash(FS=None, path=None)

create a hash of the coupled_model.json file’s contents this is used to confirm that result files were generated for the current model and not an older one uses a FileStructure or an absolute path to the file

pibronic.vibronic.vibronic_model_io.create_orthonormal_matrix_lambda_close_to_identity(order, tuning_parameter)

a wrapper for the function defined in pibronic.vibronic.orthonormal

pibronic.vibronic.vibronic_model_io.create_random_diagonal_model()

returns a dictionary that is a valid diagonal model

pibronic.vibronic.vibronic_model_io.create_random_model()

returns a dictionary that is a valid model

pibronic.vibronic.vibronic_model_io.create_random_orthonormal_matrix(A)

returns a orthonormal matrix, just a wrapper for scipy.stats.ortho_group.rvs()

pibronic.vibronic.vibronic_model_io.diagonal_model_shape_dict(A, N)

returns a dictionary with the same keys as the .json file whose values are tuples representing the dimensionality of the associated value in the .json file Takes A - number of surfaces and N - number of modes

pibronic.vibronic.vibronic_model_io.diagonal_model_zeros_template_json_dict(A, N)

returns a dictionary that is a valid diagonal model, where all values (other than states and modes) are set to 0

pibronic.vibronic.vibronic_model_io.extract_dimensions_of_diagonal_model(FS=None, path=None)

returns A, N in that order A is the number_of_surfaces and N is the number_of_modes for sampling_model.json files by using a FileStructure or an absolute path to the file

pibronic.vibronic.vibronic_model_io.extract_dimensions_of_model(FS=None, path=None)

returns A, N in that order A is the number_of_surfaces and N is the number_of_modes for coupling_model.json files by using a FileStructure or an absolute path to the file

pibronic.vibronic.vibronic_model_io.fill_offdiagonal_of_model_with_zeros(model)

takes a dictionary who must have values of dimensionality (…, A, A) and set the off-diagonal (surface) elements to zero

pibronic.vibronic.vibronic_model_io.generate_vibronic_model_data(input_parameters=None)

redo this one but otherwise its fine returns e,w,l,q filled with appropriate values

pibronic.vibronic.vibronic_model_io.load_diagonal_model_from_JSON(path, dictionary=None)

if kwargs is not provided then returns a dictionary filled with the values stored in the .json file located at path

if kwargs is provided then all values are overwritten (in place) with the values stored in the .json file located at path

pibronic.vibronic.vibronic_model_io.load_model_from_JSON(path, dictionary=None)

if kwargs is not provided then returns a dictionary filled with the values stored in the .json file located at path

if kwargs is provided then all values are overwritten (in place) with the values stored in the .json file located at path

pibronic.vibronic.vibronic_model_io.main()

currently does nothing

pibronic.vibronic.vibronic_model_io.model_parameters_are_symmetric_in_modes(kwargs)

Boolean function that returns true if the provided model’s quadratic and quartic arrays are symmetric in their mode dimensions this is a bit trickier than the surface dimension this function assumes that the arrays is properly formatted

pibronic.vibronic.vibronic_model_io.model_parameters_are_symmetric_in_surfaces(kwargs)

Boolean function that returns true if the provided model’s arrays are all symmetric in the surface dimension where the surface dimensions (A) are by convention the last two dimensions this function assumes that the arrays is properly formatted

pibronic.vibronic.vibronic_model_io.model_shape_dict(A, N)

returns a dictionary with the same keys as the .json file whose values are tuples representing the dimensionality of the associated value in the .json file Takes A - number of surfaces and N - number of modes

pibronic.vibronic.vibronic_model_io.model_zeros_template_json_dict(A, N)

returns a dictionary that is a valid model, where all values (other than states and modes) are set to 0

pibronic.vibronic.vibronic_model_io.read_model_auto_file(path_file_auto)

wrapper function to maintain functionality - possible remove in the future

pibronic.vibronic.vibronic_model_io.read_model_h_file(path_file_h)

wrapper function to maintain functionality - possible remove in the future

pibronic.vibronic.vibronic_model_io.read_model_op_file(path_file_op)

wrapper function to maintain functionality - possible remove in the future

pibronic.vibronic.vibronic_model_io.recalculate_energy_values_of_diagonal_model(FS, path)

x

pibronic.vibronic.vibronic_model_io.remove_coupling_from_model(path_source, path_destination)

reads in a model from path_source whose values can have dimensionality (…, A, A) creates a new model whose values have dimensionality (…, A) from the diagonal of the A dimension of the input model saves the new model to the provided path_destination

pibronic.vibronic.vibronic_model_io.save_diagonal_model_to_JSON(path, dictionary)

wrapper for _save_to_JSON calls verify_sample_parameters() before calling _save_to_JSON()

pibronic.vibronic.vibronic_model_io.save_model_to_JSON(path, dictionary)

wrapper for _save_to_JSON calls verify_model_parameters() before calling _save_to_JSON()

pibronic.vibronic.vibronic_model_io.simple_single_point_energy_calculation(FS, path)

generate new energy values for the diagonal model stored at the arg ‘path’ this is intended to be used for re-weighting the oscillators created using the iterative method

returns a list of energy values in eV which

pibronic.vibronic.vibronic_model_io.verify_diagonal_model_parameters(kwargs)

make sure the provided sample parameters follow the file conventions

pibronic.vibronic.vibronic_model_io.verify_model_parameters(kwargs)

make sure the provided model parameters follow the file conventions

pibronic.vibronic.vibronic_model_keys module

contains the VibronicModelKeys

class pibronic.vibronic.vibronic_model_keys.VibronicModelKeys

Bases: enum.Enum

The VibronicModelKeys, which are the keys (strings) used in the .json files to identify the corresponding values

A = 'number of surfaces'

E = 'energies'

G1 = 'linear couplings'

G2 = 'quadratic couplings'

G3 = 'cubic couplings'

G4 = 'quartic couplings'

N = 'number of modes'

cubic_couplings = 'cubic couplings'

energies = 'energies'

frequencies = 'frequencies'

linear_couplings = 'linear couplings'

number_of_modes = 'number of modes'

number_of_surfaces = 'number of surfaces'

quadratic_couplings = 'quadratic couplings'

quartic_couplings = 'quartic couplings'

w = 'frequencies'