pibronic.pimc package

Scripts that run the PIMC code

Submodules

pibronic.pimc.pimc module

class pibronic.pimc.pimc.ModelClass(states=1, modes=1)

Bases: object

information describing a quantum mechanical system

cubic = None

energy = None

classmethod from_json_file(path)

constructor wrapper

linear = None

load_model(path)

x

modes = 0

omega = None

quadratic = None

quartic = None

states = 0

class pibronic.pimc.pimc.ModelVibronic(data)

Bases: pibronic.pimc.pimc.ModelClass

stores information about the system of interest

compute_linear_displacement(data)

compute the energy shift equivalent to a linear displacement

compute_weight_for_each_state(modified_energy)

these are the weights for the oscillators associated with each state

finish_folding_in_terms(data)

set the terms we ‘folded in’ to zero

initialize_TDP_object()

creates the TemperatureDependentClass object

optimize_energy()

shift the energy to reduce the order of the raw partition function value

precompute(data)

precompute some constants

class pibronic.pimc.pimc.ModelVibronicPM(data)

Bases: pibronic.pimc.pimc.ModelVibronic

plus minus version of ModelVibronic

beta_minus = 0.0

beta_plus = 0.0

delta_beta = 0.0

initialize_TDP_object()

creates the TemperatureDependentClass object

precompute(data)

precompute some constants

tau_minus = 0.0

tau_plus = 0.0

class pibronic.pimc.pimc.ModelSampling(data)

Bases: pibronic.pimc.pimc.ModelClass

stores information about the system of interest

compute_linear_displacement()

compute the energy shift equivalent to a linear displacement

compute_sampling_constants(data)

compute_weight_for_each_state()

these are the weights for the oscillators associated with each state

draw_sample(sample_view)

Generates collective co-ordinates and stores them in self.cc_samples with dimensions BNP

finish_folding_in_terms()

set the terms we ‘folded in’ to zero

initialize_TDP_object()

creates the TemperatureDependentClass object

load_model(filePath)

x

optimize_energy()

shift the energy to reduce the order of the raw partition function value

precompute(data)

precompute some constants

class pibronic.pimc.pimc.BoxData

Bases: object

use this to pass execution parameters back and forth between methods

beads = 0

beta = 0.0

block_size = 0

blocks = 0

classmethod build(id_data, id_rho)

constructor wrapper

delta_beta = 0.0

draw_sample(sample_view)

Draws samples from the distribution rho - the rho object fills its cc_samples parameter with collective co-ordinates which will be transformed to bead dependent co-ordinates by self.transform_sampled_coordinates()

encode_self(params=None)

encodes json str with member values or given params

classmethod from_FileStructure(FS)

constructor wrapper

classmethod from_json_file(path)

constructor wrapper

classmethod from_json_string(json_str)

constructor wrapper

generate_random_R_values(result, storage_array, sample_view)

Randomly generates R values that have no relation to the distribution rho or g they only have the correct dimensions BANP and are shifted appropriately

hash_rho = None

hash_vib = None

id_data = 0

id_rho = 0

initialize_models()

x

classmethod json_serialize(params)

load_json_string(json_str)

decodes the json_str and sets member parameters

modes = 0

path_rho_model = ''

path_vib_model = ''

preprocess()

x

rho = None

samples = 0

states = 0

tau = 0.0

temperature = 0.0

transform_sampled_coordinates(sample_view)

transform from collective co-ordinates to bead dependent co-ordinates

vib = None

class pibronic.pimc.pimc.BoxDataPM(delta_beta=None)

Bases: pibronic.pimc.pimc.BoxData

plus minus version of BoxData

beta_minus = 0.0

beta_plus = 0.0

delta_beta = 0.0

initialize_models()

preprocess()

tau_minus = 0.0

tau_plus = 0.0

class pibronic.pimc.pimc.BoxResult(data=None, X=None)

Bases: object

use this to pass results back and forth between methods

compute_path_to_file()

used by BoxResultPM as well

hash_rho = None

hash_vib = None

id_job = None

initialize_arrays()

key_list = ['number_of_samples', 's_rho', 's_g']

load_multiple_results(list_of_paths, desired_number_of_samples=None)

load results from more than one file the optional argument desired_number_of_samples can be provided the method will then try to load as many samples UPTO the desired_number_of_samples and no more

load_results(path)

load results from one file

classmethod read_number_of_samples(path_full)

x

classmethod result_keys_are_present_in(iterable)

x

save_results(number_of_samples)

x

classmethod verify_result_keys_are_present(path, fileObj)

x

class pibronic.pimc.pimc.BoxResultPM(data=None, X=None)

Bases: pibronic.pimc.pimc.BoxResult

plus minus version of BoxResult

initialize_arrays()

key_list = ['s_gP', 's_gM', 'number_of_samples', 's_rho', 's_g']

load_multiple_results(list_of_paths, desired_number_of_samples=None)

load results from more than one file the optional argument desired_number_of_samples can be provided the method will then try to load as many samples UPTO the desired_number_of_samples and no more

load_results(path)

x

classmethod result_keys_are_present_in(iterable)

x

save_results(number_of_samples)

x

classmethod verify_result_keys_are_present(path, fileObj)

x

pibronic.pimc.pimc.block_compute(data, result)

Compute the numerator and denominator for block_size # of sampled points in each loop

pibronic.pimc.pimc.block_compute_pm(data, result)