schrodinger.application.matsci.equilibrium_md module

Equilibrium molecular dynamics classes/function shared by transport property calculations using Einstein and Green-Kubo methods.

Copyright Schrodinger, LLC. All rights reserved.

schrodinger.application.matsci.equilibrium_md.log_debug(msg)

Add a message to debug logger file.

Parameters

msg (str) – The message to debug logging

schrodinger.application.matsci.equilibrium_md.get_core_num()

Return the number of the cores specified by users. None means not specified.

Returns

the number of cores specified by users.

Return type

int or None

schrodinger.application.matsci.equilibrium_md.get_reserves_cores_state(options)

Return the state of reserves cores so that some python standard library functions can have access to all CPU resources.

Parameters

check_runtype (bool) – If true, the FLAG_RUN_TYPE in the options is checked

Returns

True, if reserves_cores_state should be set as True to allow some python function to utilize multiple CPUs.

Return type

bool

schrodinger.application.matsci.equilibrium_md.clearProps(cms_model, str_in_key='Diffusion')

Clear the diffusion related properties and should be called before new calculations.

Parameters

cms_model ('schrodinger.application.desmond.cms.Cms') – A cms model to clear the properties

schrodinger.application.matsci.equilibrium_md.get_files(filename, ext)

Get all the files with same extension, if ext is provided.

Parameters

• filename (str) – file to be located and returned

• ext (str or None) – extension to search files of the same type

Return type

list of str

Returns

list of filenames with path

schrodinger.application.matsci.equilibrium_md.check_finite_molecules(struct, atom_ids=None)

Check whether the molecules in structure are finite.

Parameters

• struct (schrodinger.structure.Structure) – the structure whose molecules will be checked

• atom_ids (set of int, list of int, list of list, or None) – molecules sharing atoms with this set will be checked. If None, all the molecules are checked.

Returns

message if any molecules are infinite

Return type

string or None

schrodinger.application.matsci.equilibrium_md.get_md_results(basename, options, log, log_error, save_opts=None, smart_distribution=True)

From parsed options, setup and run md simulation.

Parameters

• basename (str) – basename for md simulation job

• options (Named tuple) – The parsed command line option

• log (function) – log information

• log_error (function) – log error information and exit

• smart_distribution (bool) – turn on / off the smart_distribution

Return type

str, str, str

Returns

output cms, trj folder, and enegrp_dat

schrodinger.application.matsci.equilibrium_md.setup_md_job(name_base, md_opts, enegrp_opts=None, save_opts=None, command_dir=None, **kwargs)

Write the .msj file, form the command, figure out the output filenames, and register files to backend for molecular dynamics simulations.

Note: if command_dir is not None, please call this method inside the command_dir as the returned ocms_name doesn’t have command_dir in the file path.

Parameters

• name_base (base name for the md job) – str

• md_opts – ‘type.SimpleNamespace’

• enegrp_opts (this data struct has attributes: energy_groups for the list of keywords for desmond energy_groups, interval for output time interval in ps, start for the output starting time in ps. If None, no enegrp file is generated.) – ‘type.SimpleNamespace’ or None

• save_opts (this data struct has boolean attributes to save files likes: msj, ene, multisim_log, ocms, log, trj, cfg, write_velocity, enegrp, last, autocorrelation_file, zip_outputs, viscosity_file. If None, use default settings to decide the files to be copied back.) – ‘type.SimpleNamespace’ or None

• command_dir (this is the path from the job start dir to the subjob dir. The setup function is expected to run in the subjob setup stage, and thus the subjob dir should be passed. If there is only one master job (no sub dir), current dir is used. In addition, the returned file paths are the the basename, and then users need to form the full file path when they decide to run in subfolder or master folder directly.) – str

Return type

‘type.SimpleNamespace’

Returns

data struct with cmd command to submit md, output cms, trj folder, enegrp file, jobname

schrodinger.application.matsci.equilibrium_md.type_model_file(arg, model_formats=None)

Validate that the argument is a file that contains a model.

Parameters

• arg (str) – the filename

• model_formats (list of str) – the supported formats of the model

Raises

ArgumentTypeError – when the file cannot be open by cms or structure reader

Returns

filename with path

Return type

str

schrodinger.application.matsci.equilibrium_md.add_md_basic_argument(parser, model_formats=None)

Add necessary parser arguments for setting up a MD simulation.

Parameters

• parser (argparse.ArgumentParser) – The parser to add additional options

• model_formats (list of str) – the supported formats of the model

Return type

‘argparse._ArgumentGroup’

Returns

argparse ArgumentGroup with MD setting options

schrodinger.application.matsci.equilibrium_md.add_md_output_argument(parser, extra_options)

Add parser arguments to record output information for MD simulations.

Parameters

• parser (argparse.ArgumentParser) – The parser to add additional options

• extra_options (extra options can be added according to these keywords) – list of str

Return type

‘argparse._ArgumentGroup’

Returns

argparse ArgumentGroup with MD output recording information

schrodinger.application.matsci.equilibrium_md.add_analysis_argument(parser, extra_options)

Add parser arguments for analysis.

Parameters

• parser (argparse.ArgumentParser) – The parser to add additional options

• extra_options (extra options can be added according to these keywords) – list of str

Return type

‘argparse._ArgumentGroup’

Returns

argparse ArgumentGroup with analysis options

schrodinger.application.matsci.equilibrium_md.add_parser_opts(parser, final_prop, mid_prop, use_tau=True, extra_options=None, model_formats=None)

Add all necessary parser arguments for setting up a MD simulation and optional arguments for certain green-kubo property calculation.

Parameters

• parser (argparse.ArgumentParser) – The parser for error information

• final_prop (the final property needs to be calculated) – str

• mid_prop (the property needs to be calculated before the final prop) – str

• use_tau (Tau limits are added, if True) – bool

• extra_options (extra options can be added according to these keywords) – None or list of str

• model_formats (list of str) – the supported formats of the model

Return type

‘argparse._ArgumentGroup’, ‘argparse._ArgumentGroup’, ‘argparse._ArgumentGroup’

Returns

argparse ArgumentGroups with setting options

schrodinger.application.matsci.equilibrium_md.check_options(options, parser, option_flag, min_data_point, check_tau=True, check_gpu=False)

Validate the options.

Parameters

• options (Named tuple) – The parsed command line options

• parser (argparser.ArgumentParser) – parser to log error information

• option_flag (str) – time interval is defined by this flag

• min_data_point (int) – minimum required data point

• check_tau (bool) – validate tau range against available time range

• check_gpu (bool) – check GPU/CPU resource availability. For a remote host, -gpu flag requires a GPU host, and no -gpu flag requires a CPU HOST. For localhost and no job control, only check whether GPU resource is available when -gpu flag exists.

schrodinger.application.matsci.equilibrium_md.check_tau_options(options, parser, option_flag, min_data_point)

Validate the Tau options.

Parameters

• options (Named tuple) – The parsed command line options

• parser (argparser.ArgumentParser) – parser to log error information

• option_flag (str) – time interval is defined by this flag

• min_data_point (int) – minimum required data point

class schrodinger.application.matsci.equilibrium_md.Model(filename)

Bases: object

Wrapper around a structure.

__init__(filename)

Parameters

filename (str) – file path pointing to a cms or mae file.

load()

Load a model.

setProperty(key, value)

Set the property to the model.

Parameters

• key (str) – property name

• value (str, float, int) – the value of the property

property property

Return the model property.

Returns

a dictionary

Return type

dict

getExtension()

Return the extension of the filename.

Returns

the extension of the filename

Return type

str

getStruct()

Return the ‘structure.Structure’ object.

Returns

structure of the model

Return type

‘structure.Structure’

class schrodinger.application.matsci.equilibrium_md.MaeModel(filename)

Bases: schrodinger.application.matsci.equilibrium_md.Model

Wrapper around Structure.

load()

Load a model from the mae file.

setProperty(key, value)

Set the property to the mae model.

Parameters

• key (str) – property name

• value (str, float, int) – the value of the property

removeTrajProp()

Remove the trajectory property.

write(fname, wam_type=21)

Write the model into a file with the source_path and feature’s WAM

Parameters

• fname (str) – filename to write out the model.

• wam_type (str) – default WAM type

__init__(filename)

Parameters

filename (str) – file path pointing to a cms or mae file.

getExtension()

Return the extension of the filename.

Returns

the extension of the filename

Return type

str

getStruct()

Return the ‘structure.Structure’ object.

Returns

structure of the model

Return type

‘structure.Structure’

property property

Return the model property.

Returns

a dictionary

Return type

dict

class schrodinger.application.matsci.equilibrium_md.CmsModel(filename)

Bases: schrodinger.application.matsci.equilibrium_md.Model

Wrapper around Cms.

load()

load a model from a cms file.

setProperty(key, value)

Set the property to the cms model.

Parameters

• key (str) – property name

• value (str, float, int) – the value of the property

removeTrajProp()

Remove the trajectory property.

write(fname, wam_type=21)

Write the model into a file with the source_path and feature’s WAM

Parameters

• fname (str) – filename to write out the model.

• wam_type (str) – default WAM type

setWam(wam_type=21)

Set the feature’s WAM for the model.

Parameters

wam_type (str) – default WAM type

getStruct()

Return the ‘structure.Structure’ object.

Returns

structure of the model

Return type

‘structure.Structure’

__init__(filename)

Parameters

filename (str) – file path pointing to a cms or mae file.

getExtension()

Return the extension of the filename.

Returns

the extension of the filename

Return type

str

property property

Return the model property.

Returns

a dictionary

Return type

dict

schrodinger.application.matsci.equilibrium_md.get_model(filename)

Get the model from a cms or mae file.

Parameters

filename (str) – file path pointing to a cms or mae file.

Returns

the model in the file.

Return type

‘CmsModel’ or ‘MaeModel’

class schrodinger.application.matsci.equilibrium_md.EquilibriumMdBase(input_cms, logger=False)

Bases: object

This is a base class for equilibrium MD subclass, and should be not be instantiated directly.

__init__(input_cms, logger=False)

Parameters

• input_cms (cms input file) – str

• logger (loggerobj.logger prints to logfilename; None prints to stdout; False mutes logging and raises errors) – logging.Logger, None or False

log(msg, **kwargs)

Add a message to the log file in driver mode, or ignore the logging in module mode.

Parameters

msg (str) – The information message

Additional keyword arguments are passed to the textlogger.log_msg function

log_error(msg)

Exit with the error printed in driver mode, or raise the error in module mode.

Parameters

str (msg) – The error message

Raise

RuntimeError in module mode

checkSetTimeInterval(time_intervals=None)

Time interval must be the same for all trajectery.

Parameters

time_intervals (list or None) – time intervals between every two frames.

checkConstantVol(allow_npt=True)

Calculate volume and check whether it changes.

Parameters

allow_npt (bool) – allow volume to change, if True

calDensity()

Caluate the average system density.

savePropAndCms(cms_out=None, wam_type=None)

Save properties to cms model, delete trj information if needed, and write out cms file.

Parameters

• cms_out (str) – name of the output cms.

• wam_type (int or None) – One of the enums defined in workflow_action_menu.h if the results should have a Workflow Action Menu in Maestro

class schrodinger.application.matsci.equilibrium_md.TrjBase(input_cms, logger=False)

Bases: schrodinger.application.matsci.equilibrium_md.EquilibriumMdBase

This is a base class for equilibrium MD subclass that uses trajectory, and should be not be instantiated directly.

readTrj(make_whole=False)

Read trj frames from trj folder.

Parameters

make_whole (bool) – if True, bond across PBCs are fixed so that two bonded particles won’t be on opposite sides of the system

trajFrames(make_whole=False)

Fix pbc bonds (if needed), yield the trajectory frame, and garbage-collect to release the occupied memory.

Parameters

make_whole (bool) – if True, bond across PBCs are fixed so that two bonded particles won’t be on opposite sides of the system

Return type

schrodinger.application.desmond.packages.traj.frame

Returns

a trajectory frame

checkTau(frame_num, min_tau_data_point)

Check whether trj frame number is large enough.

Parameters

• frame_num (number of total data point) – int

• min_tau_data_point (minimum requested data) – int

checkVel()

Check whether each frame contains velocity information.

__init__(input_cms, logger=False)

Parameters

• input_cms (cms input file) – str

• logger (loggerobj.logger prints to logfilename; None prints to stdout; False mutes logging and raises errors) – logging.Logger, None or False

calDensity()

Caluate the average system density.

checkConstantVol(allow_npt=True)

Calculate volume and check whether it changes.

Parameters

allow_npt (bool) – allow volume to change, if True

checkSetTimeInterval(time_intervals=None)

Time interval must be the same for all trajectery.

Parameters

time_intervals (list or None) – time intervals between every two frames.

log(msg, **kwargs)

Add a message to the log file in driver mode, or ignore the logging in module mode.

Parameters

msg (str) – The information message

Additional keyword arguments are passed to the textlogger.log_msg function

log_error(msg)

Exit with the error printed in driver mode, or raise the error in module mode.

Parameters

str (msg) – The error message

Raise

RuntimeError in module mode

savePropAndCms(cms_out=None, wam_type=None)

Save properties to cms model, delete trj information if needed, and write out cms file.

Parameters

• cms_out (str) – name of the output cms.

• wam_type (int or None) – One of the enums defined in workflow_action_menu.h if the results should have a Workflow Action Menu in Maestro

class schrodinger.application.matsci.equilibrium_md.MsdTrajBase(options, **kwargs)

Bases: schrodinger.application.matsci.equilibrium_md.TrjBase

Trajectory base class for Mean squared displacement method.

ATOM = 'atom'

METHOD = 'MSD'

X = 'x'

Y = 'y'

Z = 'z'

TAU_PS = 'Tau(ps)'

MSD_ANG2 = 'MSD(angstrom^2)'

STDEV_ANG2 = 'Std Dev(angstrom^2)'

Y_HEADERS = ['MSD(angstrom^2)', 'Std Dev(angstrom^2)']

CSV_HEADER_3D = ['Tau(ps)', '3D MSD(angstrom^2)', '3D Std Dev(angstrom^2)']

ANISO_DIMS = ['1D', '1D', '2D', '2D']

CSV_HEADER_PLANE = ['1D MSD(angstrom^2)', '1D Std Dev(angstrom^2)', '2D MSD(angstrom^2)', '2D Std Dev(angstrom^2)']

AXES = ['x', 'x', 'y', 'y', 'z', 'z']

CSV_HEADER_AXIS = ['x MSD(angstrom^2)', 'x Std Dev(angstrom^2)', 'y MSD(angstrom^2)', 'y Std Dev(angstrom^2)', 'z MSD(angstrom^2)', 'z Std Dev(angstrom^2)']

TAU_START_PROP = 'r_matsci_Diffusion_Coefficient_MSD_Tau_Start_(ns)'

TAU_END_PROP = 'r_matsci_Diffusion_Coefficient_MSD_Tau_End_(ns)'

VECTOR_DELIM = ','

VECTOR_DELIM_WITH_SPACE = ', '

NORMAL = 'Normal'

DIFFUSION_FILE_PROP = 's_matsci_Diffusion_MSD_File'

DIFFUSIVITY_VECTOR_PROP = 's_matsci_Diffusion_Coefficient_MSD_Normal'

DIFFUSIVITY_1D_PROP = 'r_matsci_Diffusion_Coefficient_1D_MSD_(m^2/s)'

DIFFUSIVITY_2D_PROP = 'r_matsci_Diffusion_Coefficient_2D_MSD_(m^2/s)'

DIFFUSIVITY_3D_PROP = 'r_matsci_Diffusion_Coefficient_3D_MSD_(m^2/s)'

DIFFUSIVITY_X_PROP = 'r_matsci_Diffusion_Coefficient_X_MSD_(m^2/s)'

DIFFUSIVITY_Y_PROP = 'r_matsci_Diffusion_Coefficient_Y_MSD_(m^2/s)'

DIFFUSIVITY_Z_PROP = 'r_matsci_Diffusion_Coefficient_Z_MSD_(m^2/s)'

STDEV = 'stdev'

SD_EXT = 'MSD_stdev'

DIFFUSIVITY_1D_SD_PROP = 'r_matsci_Diffusion_Coefficient_1D_MSD_stdev_(m^2/s)'

DIFFUSIVITY_2D_SD_PROP = 'r_matsci_Diffusion_Coefficient_2D_MSD_stdev_(m^2/s)'

DIFFUSIVITY_3D_SD_PROP = 'r_matsci_Diffusion_Coefficient_3D_MSD_stdev_(m^2/s)'

DIFFUSIVITY_X_SD_PROP = 'r_matsci_Diffusion_Coefficient_X_MSD_stdev_(m^2/s)'

DIFFUSIVITY_Y_SD_PROP = 'r_matsci_Diffusion_Coefficient_Y_MSD_stdev_(m^2/s)'

DIFFUSIVITY_Z_SD_PROP = 'r_matsci_Diffusion_Coefficient_Z_MSD_stdev_(m^2/s)'

DIFFUSIVITY_1D_R2_PROP = 'r_matsci_Diffusion_Coefficient_1D_MSD_R2'

DIFFUSIVITY_2D_R2_PROP = 'r_matsci_Diffusion_Coefficient_2D_MSD_R2'

DIFFUSIVITY_3D_R2_PROP = 'r_matsci_Diffusion_Coefficient_3D_MSD_R2'

DIFFUSIVITY_X_R2_PROP = 'r_matsci_Diffusion_Coefficient_X_MSD_R2'

DIFFUSIVITY_Y_R2_PROP = 'r_matsci_Diffusion_Coefficient_Y_MSD_R2'

DIFFUSIVITY_Z_R2_PROP = 'r_matsci_Diffusion_Coefficient_Z_MSD_R2'

class DIFFUSIVITY(diffusivity, std_dev, r2)

Bases: tuple

__contains__(key, /)

Return key in self.

__len__()

Return len(self).

count(value, /)

Return number of occurrences of value.

diffusivity

Alias for field number 0

index(value, start=0, stop=9223372036854775807, /)

Return first index of value.

Raises ValueError if the value is not present.

r2

Alias for field number 2

std_dev

Alias for field number 1

ISOTROPIC = 'isotropic'

ANISOTROPIC = 'anisotropic'

ISOTROPIC_3D = 'isotropic:3D'

ANISOTROPIC_1D = 'anisotropic:1D'

ANISOTROPIC_2D = 'anisotropic:2D'

DIMENSION_MAP = {'anisotropic:1D': 1, 'anisotropic:2D': 2, 'isotropic:3D': 3}

DIFFUSION_PROPS_MAP = {1: DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_1D_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_1D_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_1D_MSD_R2'), 2: DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_2D_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_2D_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_2D_MSD_R2'), 3: DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_3D_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_3D_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_3D_MSD_R2'), 'x': DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_X_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_X_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_X_MSD_R2'), 'y': DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_Y_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_Y_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_Y_MSD_R2'), 'z': DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_Z_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_Z_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_Z_MSD_R2')}

DIFFUSION_COL_MAP = {1: (0, 3, 4), 2: (0, 5, 6), 3: (0, 1, 2), 'x': (0, 3, 4), 'y': (0, 5, 6), 'z': (0, 7, 8)}

__init__(options, **kwargs)

Parameters

options (Named tuple) – The parsed command line options

static fitMsd(time_msd_std, start_idx, end_idx, dimension=3)

Fit the mean squared displacement

Parameters

• time_msd_std (numpy.ndarray) – first column is time in ps, second column is mean squared displacement in angstrom^2.

• start_idx (int) – index to select the starting frame

• end_idx (int) – index to select the ending frame

• dimension (int) – 1 stands for 1D; 2 stands for 2D; 3 stands for 3D

Returns

diffusivity coefficient in m^2/s, diffusivity_std in m^2/s, R-squared in linear regression

Return type

float, float, float

classmethod vectorStr(vector)

Convert vector array to str format.

Parameters

vector (1 x 3 array of floats) – a vector

Returns

vector in str format

Return type

str

getMsdHeader()

Get the MSD csv header.

Returns

column labels separated by comma.

Return type

str

setTauFrame(tau_start=None, tau_end=None)

Set Tau frame start and end limits.

Parameters

• float (tau_end) – the starting tau value in ps

• float – the ending tau value in ps

setIsotropicMSD()

Set the isotropic 3d diffusion coefficients.

setPlaneMSD()

Set the anisotropic in-plane 2d diffusion coefficients.

setAxisMSD()

Set the anisotropic along-axis 1d diffusion coefficients.

calDensity()

Caluate the average system density.

checkConstantVol(allow_npt=True)

Calculate volume and check whether it changes.

Parameters

allow_npt (bool) – allow volume to change, if True

checkSetTimeInterval(time_intervals=None)

Time interval must be the same for all trajectery.

Parameters

time_intervals (list or None) – time intervals between every two frames.

checkTau(frame_num, min_tau_data_point)

Check whether trj frame number is large enough.

Parameters

• frame_num (number of total data point) – int

• min_tau_data_point (minimum requested data) – int

checkVel()

Check whether each frame contains velocity information.

log(msg, **kwargs)

Add a message to the log file in driver mode, or ignore the logging in module mode.

Parameters

msg (str) – The information message

Additional keyword arguments are passed to the textlogger.log_msg function

log_error(msg)

Exit with the error printed in driver mode, or raise the error in module mode.

Parameters

str (msg) – The error message

Raise

RuntimeError in module mode

readTrj(make_whole=False)

Read trj frames from trj folder.

Parameters

make_whole (bool) – if True, bond across PBCs are fixed so that two bonded particles won’t be on opposite sides of the system

savePropAndCms(cms_out=None, wam_type=None)

Save properties to cms model, delete trj information if needed, and write out cms file.

Parameters

• cms_out (str) – name of the output cms.

• wam_type (int or None) – One of the enums defined in workflow_action_menu.h if the results should have a Workflow Action Menu in Maestro

trajFrames(make_whole=False)

Fix pbc bonds (if needed), yield the trajectory frame, and garbage-collect to release the occupied memory.

Parameters

make_whole (bool) – if True, bond across PBCs are fixed so that two bonded particles won’t be on opposite sides of the system

Return type

schrodinger.application.desmond.packages.traj.frame

Returns

a trajectory frame

class schrodinger.application.matsci.equilibrium_md.MultiToOneConverter(msd_files, jobname, options, save=True)

Bases: schrodinger.application.matsci.equilibrium_md.MsdTrajBase

The class to gather multiple files and merge them into one.

__init__(msd_files, jobname, options, save=True)

Parameters

• msd_files (list of str) – the msd files (with path) for diffusion data.

• jobname (str) – the jobname

• options (SimpleNamespace or namedtuple) – commandline options

• save (bool) – If True, add output files to the backend

run()

Main function to load data, process data, and fit.

loadData()

Read in all msd files.

calWriteMeanAndStd()

Calculate and write mean and std of the diffusion from multi runs.

combineTrace()

Combine the trace files from MSD diffusion calculations.

combineOnsagerCsv()

Combine the onsager series

getMSDRelatedFiles(ext)

Get related files with given extension which are similar msd log file :param str ext: extension name

Return type

list

Returns

list of file names

ANISOTROPIC = 'anisotropic'

ANISOTROPIC_1D = 'anisotropic:1D'

ANISOTROPIC_2D = 'anisotropic:2D'

ANISO_DIMS = ['1D', '1D', '2D', '2D']

ATOM = 'atom'

AXES = ['x', 'x', 'y', 'y', 'z', 'z']

CSV_HEADER_3D = ['Tau(ps)', '3D MSD(angstrom^2)', '3D Std Dev(angstrom^2)']

CSV_HEADER_AXIS = ['x MSD(angstrom^2)', 'x Std Dev(angstrom^2)', 'y MSD(angstrom^2)', 'y Std Dev(angstrom^2)', 'z MSD(angstrom^2)', 'z Std Dev(angstrom^2)']

CSV_HEADER_PLANE = ['1D MSD(angstrom^2)', '1D Std Dev(angstrom^2)', '2D MSD(angstrom^2)', '2D Std Dev(angstrom^2)']

DIFFUSION_COL_MAP = {1: (0, 3, 4), 2: (0, 5, 6), 3: (0, 1, 2), 'x': (0, 3, 4), 'y': (0, 5, 6), 'z': (0, 7, 8)}

DIFFUSION_FILE_PROP = 's_matsci_Diffusion_MSD_File'

DIFFUSION_PROPS_MAP = {1: DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_1D_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_1D_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_1D_MSD_R2'), 2: DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_2D_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_2D_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_2D_MSD_R2'), 3: DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_3D_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_3D_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_3D_MSD_R2'), 'x': DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_X_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_X_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_X_MSD_R2'), 'y': DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_Y_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_Y_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_Y_MSD_R2'), 'z': DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_Z_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_Z_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_Z_MSD_R2')}

class DIFFUSIVITY(diffusivity, std_dev, r2)

Bases: tuple

__contains__(key, /)

Return key in self.

__len__()

Return len(self).

count(value, /)

Return number of occurrences of value.

diffusivity

Alias for field number 0

index(value, start=0, stop=9223372036854775807, /)

Return first index of value.

Raises ValueError if the value is not present.

r2

Alias for field number 2

std_dev

Alias for field number 1

DIFFUSIVITY_1D_PROP = 'r_matsci_Diffusion_Coefficient_1D_MSD_(m^2/s)'

DIFFUSIVITY_1D_R2_PROP = 'r_matsci_Diffusion_Coefficient_1D_MSD_R2'

DIFFUSIVITY_1D_SD_PROP = 'r_matsci_Diffusion_Coefficient_1D_MSD_stdev_(m^2/s)'

DIFFUSIVITY_2D_PROP = 'r_matsci_Diffusion_Coefficient_2D_MSD_(m^2/s)'

DIFFUSIVITY_2D_R2_PROP = 'r_matsci_Diffusion_Coefficient_2D_MSD_R2'

DIFFUSIVITY_2D_SD_PROP = 'r_matsci_Diffusion_Coefficient_2D_MSD_stdev_(m^2/s)'

DIFFUSIVITY_3D_PROP = 'r_matsci_Diffusion_Coefficient_3D_MSD_(m^2/s)'

DIFFUSIVITY_3D_R2_PROP = 'r_matsci_Diffusion_Coefficient_3D_MSD_R2'

DIFFUSIVITY_3D_SD_PROP = 'r_matsci_Diffusion_Coefficient_3D_MSD_stdev_(m^2/s)'

DIFFUSIVITY_VECTOR_PROP = 's_matsci_Diffusion_Coefficient_MSD_Normal'

DIFFUSIVITY_X_PROP = 'r_matsci_Diffusion_Coefficient_X_MSD_(m^2/s)'

DIFFUSIVITY_X_R2_PROP = 'r_matsci_Diffusion_Coefficient_X_MSD_R2'

DIFFUSIVITY_X_SD_PROP = 'r_matsci_Diffusion_Coefficient_X_MSD_stdev_(m^2/s)'

DIFFUSIVITY_Y_PROP = 'r_matsci_Diffusion_Coefficient_Y_MSD_(m^2/s)'

DIFFUSIVITY_Y_R2_PROP = 'r_matsci_Diffusion_Coefficient_Y_MSD_R2'

DIFFUSIVITY_Y_SD_PROP = 'r_matsci_Diffusion_Coefficient_Y_MSD_stdev_(m^2/s)'

DIFFUSIVITY_Z_PROP = 'r_matsci_Diffusion_Coefficient_Z_MSD_(m^2/s)'

DIFFUSIVITY_Z_R2_PROP = 'r_matsci_Diffusion_Coefficient_Z_MSD_R2'

DIFFUSIVITY_Z_SD_PROP = 'r_matsci_Diffusion_Coefficient_Z_MSD_stdev_(m^2/s)'

DIMENSION_MAP = {'anisotropic:1D': 1, 'anisotropic:2D': 2, 'isotropic:3D': 3}

ISOTROPIC = 'isotropic'

ISOTROPIC_3D = 'isotropic:3D'

METHOD = 'MSD'

MSD_ANG2 = 'MSD(angstrom^2)'

NORMAL = 'Normal'

SD_EXT = 'MSD_stdev'

STDEV = 'stdev'

STDEV_ANG2 = 'Std Dev(angstrom^2)'

TAU_END_PROP = 'r_matsci_Diffusion_Coefficient_MSD_Tau_End_(ns)'

TAU_PS = 'Tau(ps)'

TAU_START_PROP = 'r_matsci_Diffusion_Coefficient_MSD_Tau_Start_(ns)'

VECTOR_DELIM = ','

VECTOR_DELIM_WITH_SPACE = ', '

X = 'x'

Y = 'y'

Y_HEADERS = ['MSD(angstrom^2)', 'Std Dev(angstrom^2)']

Z = 'z'

calDensity()

Caluate the average system density.

checkConstantVol(allow_npt=True)

Calculate volume and check whether it changes.

Parameters

allow_npt (bool) – allow volume to change, if True

checkSetTimeInterval(time_intervals=None)

Time interval must be the same for all trajectery.

Parameters

time_intervals (list or None) – time intervals between every two frames.

checkTau(frame_num, min_tau_data_point)

Check whether trj frame number is large enough.

Parameters

• frame_num (number of total data point) – int

• min_tau_data_point (minimum requested data) – int

checkVel()

Check whether each frame contains velocity information.

static fitMsd(time_msd_std, start_idx, end_idx, dimension=3)

Fit the mean squared displacement

Parameters

• time_msd_std (numpy.ndarray) – first column is time in ps, second column is mean squared displacement in angstrom^2.

• start_idx (int) – index to select the starting frame

• end_idx (int) – index to select the ending frame

• dimension (int) – 1 stands for 1D; 2 stands for 2D; 3 stands for 3D

Returns

diffusivity coefficient in m^2/s, diffusivity_std in m^2/s, R-squared in linear regression

Return type

float, float, float

getMsdHeader()

Get the MSD csv header.

Returns

column labels separated by comma.

Return type

str

log(msg, **kwargs)

Add a message to the log file in driver mode, or ignore the logging in module mode.

Parameters

msg (str) – The information message

Additional keyword arguments are passed to the textlogger.log_msg function

log_error(msg)

Exit with the error printed in driver mode, or raise the error in module mode.

Parameters

str (msg) – The error message

Raise

RuntimeError in module mode

readTrj(make_whole=False)

Read trj frames from trj folder.

Parameters

make_whole (bool) – if True, bond across PBCs are fixed so that two bonded particles won’t be on opposite sides of the system

savePropAndCms(cms_out=None, wam_type=None)

Save properties to cms model, delete trj information if needed, and write out cms file.

Parameters

• cms_out (str) – name of the output cms.

• wam_type (int or None) – One of the enums defined in workflow_action_menu.h if the results should have a Workflow Action Menu in Maestro

setAxisMSD()

Set the anisotropic along-axis 1d diffusion coefficients.

setIsotropicMSD()

Set the isotropic 3d diffusion coefficients.

setPlaneMSD()

Set the anisotropic in-plane 2d diffusion coefficients.

setTauFrame(tau_start=None, tau_end=None)

Set Tau frame start and end limits.

Parameters

• float (tau_end) – the starting tau value in ps

• float – the ending tau value in ps

trajFrames(make_whole=False)

Fix pbc bonds (if needed), yield the trajectory frame, and garbage-collect to release the occupied memory.

Parameters

make_whole (bool) – if True, bond across PBCs are fixed so that two bonded particles won’t be on opposite sides of the system

Return type

schrodinger.application.desmond.packages.traj.frame

Returns

a trajectory frame

classmethod vectorStr(vector)

Convert vector array to str format.

Parameters

vector (1 x 3 array of floats) – a vector

Returns

vector in str format

Return type

str

class schrodinger.application.matsci.equilibrium_md.TrajectoryFrame(frame, ids, com_type='atom', vel=False)

Bases: object

Container of cms_model and trajectory frame with custom functions and storage

ATOM = 'atom'

COL_NUM_POS = 3

cms_model = None

msys_model = None

__init__(frame, ids, com_type='atom', vel=False)

Crease a TrajectoryFrame object, update gids, mass, and positions.

Parameters

• frame (traj.Frame) – One trajectory frame

• ids (list) – atom id list [int1, int2…] or [(int1, int2…), (…)…]

• com_type (string) – mass center of atoms within each com_type group

• vel (bool) – velocity in trajectry frame is used to calculate system translation and shift the system before unwrapping displacements

setGids()

Get global ids of beads (atom or mass center) to extra positions and velocities.

setMass()

Set the mass of each bead (atom or mass center of atoms).

setGrpMass()

Set the total mass of each grouped atoms.

setFrame(frame)

Update trajectry, time, sel coordinates, box, and reduced positions.

Parameters

frame (traj.Frame objects) – Trajectory

setXYZ()

Set the xyz coordinates obtaioned from trajectory frame. If -com_type != ATOM, the the center of mass is calculated first.

setBox()

Set the stored pbc box size.

reducedUnitNumpyPos()

Convert the XYZ in real unit to reduced unit.

momentum2Velocity()

Calculate the mean velocity of system using velocity information from trajectory frame.

class schrodinger.application.matsci.equilibrium_md.DiffusivityMsdAnalysis(options, jobname, command_dir='.', save=True, **kwargs)

Bases: schrodinger.application.matsci.equilibrium_md.MsdTrajBase

Main class that performs coordinate unwrap, displacement calculation, and diffusivity fit.

MIN_TAU_DATA_POINT_NUM = 10

COL_NUM_POS = 3

ATOM = 'atom'

MOLECULE = 'molecule'

MONOMER = 'monomer'

SMARTS = 'SMARTS'

DIFFUSION_FILE_EXT = '_msd.log'

ONSAGER_FILE_EXT = '_onsager.csv'

TRACE_FILE_EXT = '_trace.csv'

TRACE_HEADER = 'X1, Y1, Z1, X2, Y2, Z2, ...'

MAX_NUM_TRACE = 1000

DEFAULT_REF = 'all'

MAX_REDUCED_DISPLACEMENT = 0.45

__init__(options, jobname, command_dir='.', save=True, **kwargs)

Parameters

• options (SimpleNamespace or namedtuple) – commandline options

• jobname (str) – the jobname

• command_dir (str) – the command dir with respect to the launch dir

• save (bool) – If True, add output files to the backend

• log (function to log information) – function

• log_error (log error information and exit calculation) – function

run()

Calculate unwrapped displacement, check time interval, and calculate diffusivity.

setSelectionAndLoadTrj()

Set the atom selection and load trajectory.

setSquaredDisplacementTimeserial()

Set the atom selection and load trajectory.

static isIterable(item)

Whether the input is iterable. Currently, list, set, and tuple are treated as iterable.

Parameters

item – str, list, tuple, or other data type

Returns

Whether the input is iterable

Return type

bool

classmethod flatten(an_iterable_item)

Robust function to flatten list recursively.

Parameters

an_iterable_item (list, tuple or set) – The iterable item to be flatten. (an iterable that describes the whole or part of the workflow)

Returns

The flatten items in a list ([uniterable value 1, uniterable value 2, uniterable value 3 …])

Return type

list of uniterable values (str or dict)

setMakeWholeState()

Set the make_whole state. If true, the bonds across the PBCs will be fixed before trajectory analysis. This happens when the mass center of a group covalently bonded atoms (e.g molecule) is needed.

Only set state here as make_whole on per-frame reduces peak memory usage

readTrj(make_whole=False)

See parent methods for docs.

make_whole removes the bond broken by PBC.

checkVel()

See parent methods for docs.

checkSetTimeInterval(time_intervals=None)

See parent methods for docs.

savePropAndCms()

See parent methods for docs.

getIdx(asl, com_type='atom', smarts_pattern=None)

Get atom indices from asl selection.

Parameters

• asl (str) – ASL search string.

• com_type (string) – mass center of atoms within each com_type group is calculated

• smarts_pattern (string) – SMARTS pattern

Return type

list

Returns

index of atoms that matche the asl string. [int1, int2…], if use_type == ATOM; [(int1, int2…), (…)…], if if use_com != ATOM

classmethod groupIdx(struct, atom_ids, com_type='atom', smarts_atom_list=None)

Group atoms according to com_type, or find the SMARTS matches within the atom selection.

Parameters

• struct (schrodinger.structure) – structure containing atoms

• atom_ids (list) – atom id list of atom selection

• com_type (string) – atom, molecule, monomer, or SMARTS as in COM_TYPE

• smarts_atom_list (list) – [[a1, a2..],[b1, b2..]..], each sublist contains atom ids that match the SMARTS pattern.

Return type

list

Returns

[a1, a2, ..], if com_type=ATOM. [(a1, a2..), (c1, c2..)..], union of atom selection and SMARTS matches or each (..) is a subset of atom selection that belongs to one molecule or residue

setIds()

Evaluate asl string and save selected atom ids.

setFinalDisplacement()

Choose functions to get the displacement matrix if self.momentum=True, do recentering using ref atoms,

setMolDisplacement()

Compute the displacement of each molecule center of mass

writeOnsagerCoeff()

Write onsager coefficient to a file.

computeOnsagerCoefficient(mol_disp)

Compute time integrated Onsager coefficient.

Parameters

mol_disp (list) – Displacement of each molecule in a list

exportTrace()

Export trace to file

setFinalDisplacementCenter()

Calculate the displacement between adjacent trajectories, unwrap the coordinates, and correct the mass center.

setFinalDisplacementNoCenter()

Calculate the displacement between adjacent trajectories, unwrap the coordinates directly (no mass center shift).

getDisplacementFromConstTranslation(cur_frame, pre_frame)

Estimate the position shift between two frames by time x mean velocity.

Parameters

• cur_frame (traj.Frame objects) – current trajectory frame

• pre_frame (traj.Frame objects) – previous trajectory frame

Return type

list or None

Returns

list of float (xyz coordinates), if vel=True

unwrapReducedDisplacement(cur_frame, pre_frame, cons_acceleration_shift=None)

Calculate wrapped XYZ displacement, shift the mass center, and unwrap displacement.

Parameters

• cur_frame (traj.Frame objects) – current trajectory frame

• pre_frame (traj.Frame objects) – previous trajectory frame

• cons_acceleration_shift (list of float) – xyz shift of mass center due to ref atom collective translation assuming constant acceleration

Return type

numpy.matrix

Returns

unwrapped coordinates MXN matrix in reduced unit after const momentum shift

getShiftVectorByRecenterMass(mass, adj_displacement)

Get the XYZ shift vetor of the unwrapped mass center (reduced unit).

Parameters

• mass (list) – list of atom mass

• adj_displacement (numpy.matrix) – unwrapped displacement matrix in reduced unit

Return type

list

Returns

list of float

getAdjustedDisplacement(selected_adj_displacement, shift_centered_mass, box)

Get the “correct” displacement in xyz coordinates (real unit) for adjacent trajectory.

Parameters

• selected_adj_displacement (numpy.matrix) – wrapped adjacent trajectory displacement

• shift_centered_mass (list) – vector to zero mass center of ref atoms

• box (list) – list of float, the periodic boundary dimensions

Return type

numpy.matrix

Returns

MXN matrix in real unit, wrapped adjacent trajectory displacement

realUnitCoordinate(selected_adj_displacement, box)

Change reduced unit to real unit for displacement matrix.

Parameters

• selected_adj_displacement (numpy.matrix) – displacement matrix in reduced unit

• box (list) – pbc box size

Return type

numpy.matrix

Returns

displacement matrix in real unit

setSquaredDisplacement()

Loop over all adjacent displacement matrix to run MSD calculation

sdFromDisplacement(start_id)

Calculate the squared displacement from start_id trj frame to proper frame

Parameters

start_id (int) – calculation starts from the frame of start_id

collectData()

Collect the msd and std from displacement matrix.

# Std is calculated from sqrt(E[X^2] - (E[X])^2) and X is the mean # squared displacement at one Tau (one time point pair) # https://en.wikipedia.org/wiki/Standard_deviation#Definition_of_population_values

saveMsdTxt()

Save MSD matrix: [time(ps), MSD(Angstrom^2), STD(Angstrom^2)]

setTauRange()

Set Tau start and end limits.

ANISOTROPIC = 'anisotropic'

ANISOTROPIC_1D = 'anisotropic:1D'

ANISOTROPIC_2D = 'anisotropic:2D'

ANISO_DIMS = ['1D', '1D', '2D', '2D']

AXES = ['x', 'x', 'y', 'y', 'z', 'z']

CSV_HEADER_3D = ['Tau(ps)', '3D MSD(angstrom^2)', '3D Std Dev(angstrom^2)']

CSV_HEADER_AXIS = ['x MSD(angstrom^2)', 'x Std Dev(angstrom^2)', 'y MSD(angstrom^2)', 'y Std Dev(angstrom^2)', 'z MSD(angstrom^2)', 'z Std Dev(angstrom^2)']

CSV_HEADER_PLANE = ['1D MSD(angstrom^2)', '1D Std Dev(angstrom^2)', '2D MSD(angstrom^2)', '2D Std Dev(angstrom^2)']

DIFFUSION_COL_MAP = {1: (0, 3, 4), 2: (0, 5, 6), 3: (0, 1, 2), 'x': (0, 3, 4), 'y': (0, 5, 6), 'z': (0, 7, 8)}

DIFFUSION_FILE_PROP = 's_matsci_Diffusion_MSD_File'

DIFFUSION_PROPS_MAP = {1: DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_1D_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_1D_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_1D_MSD_R2'), 2: DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_2D_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_2D_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_2D_MSD_R2'), 3: DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_3D_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_3D_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_3D_MSD_R2'), 'x': DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_X_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_X_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_X_MSD_R2'), 'y': DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_Y_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_Y_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_Y_MSD_R2'), 'z': DIFFUSIVITY(diffusivity='r_matsci_Diffusion_Coefficient_Z_MSD_(m^2/s)', std_dev='r_matsci_Diffusion_Coefficient_Z_MSD_stdev_(m^2/s)', r2='r_matsci_Diffusion_Coefficient_Z_MSD_R2')}

class DIFFUSIVITY(diffusivity, std_dev, r2)

Bases: tuple

__contains__(key, /)

Return key in self.

__len__()

Return len(self).

count(value, /)

Return number of occurrences of value.

diffusivity

Alias for field number 0

index(value, start=0, stop=9223372036854775807, /)

Return first index of value.

Raises ValueError if the value is not present.

r2

Alias for field number 2

std_dev

Alias for field number 1

DIFFUSIVITY_1D_PROP = 'r_matsci_Diffusion_Coefficient_1D_MSD_(m^2/s)'

DIFFUSIVITY_1D_R2_PROP = 'r_matsci_Diffusion_Coefficient_1D_MSD_R2'

DIFFUSIVITY_1D_SD_PROP = 'r_matsci_Diffusion_Coefficient_1D_MSD_stdev_(m^2/s)'

DIFFUSIVITY_2D_PROP = 'r_matsci_Diffusion_Coefficient_2D_MSD_(m^2/s)'

DIFFUSIVITY_2D_R2_PROP = 'r_matsci_Diffusion_Coefficient_2D_MSD_R2'

DIFFUSIVITY_2D_SD_PROP = 'r_matsci_Diffusion_Coefficient_2D_MSD_stdev_(m^2/s)'

DIFFUSIVITY_3D_PROP = 'r_matsci_Diffusion_Coefficient_3D_MSD_(m^2/s)'

DIFFUSIVITY_3D_R2_PROP = 'r_matsci_Diffusion_Coefficient_3D_MSD_R2'

DIFFUSIVITY_3D_SD_PROP = 'r_matsci_Diffusion_Coefficient_3D_MSD_stdev_(m^2/s)'

DIFFUSIVITY_VECTOR_PROP = 's_matsci_Diffusion_Coefficient_MSD_Normal'

DIFFUSIVITY_X_PROP = 'r_matsci_Diffusion_Coefficient_X_MSD_(m^2/s)'

DIFFUSIVITY_X_R2_PROP = 'r_matsci_Diffusion_Coefficient_X_MSD_R2'

DIFFUSIVITY_X_SD_PROP = 'r_matsci_Diffusion_Coefficient_X_MSD_stdev_(m^2/s)'

DIFFUSIVITY_Y_PROP = 'r_matsci_Diffusion_Coefficient_Y_MSD_(m^2/s)'

DIFFUSIVITY_Y_R2_PROP = 'r_matsci_Diffusion_Coefficient_Y_MSD_R2'

DIFFUSIVITY_Y_SD_PROP = 'r_matsci_Diffusion_Coefficient_Y_MSD_stdev_(m^2/s)'

DIFFUSIVITY_Z_PROP = 'r_matsci_Diffusion_Coefficient_Z_MSD_(m^2/s)'

DIFFUSIVITY_Z_R2_PROP = 'r_matsci_Diffusion_Coefficient_Z_MSD_R2'

DIFFUSIVITY_Z_SD_PROP = 'r_matsci_Diffusion_Coefficient_Z_MSD_stdev_(m^2/s)'

DIMENSION_MAP = {'anisotropic:1D': 1, 'anisotropic:2D': 2, 'isotropic:3D': 3}

ISOTROPIC = 'isotropic'

ISOTROPIC_3D = 'isotropic:3D'

METHOD = 'MSD'

MSD_ANG2 = 'MSD(angstrom^2)'

NORMAL = 'Normal'

SD_EXT = 'MSD_stdev'

STDEV = 'stdev'

STDEV_ANG2 = 'Std Dev(angstrom^2)'

TAU_END_PROP = 'r_matsci_Diffusion_Coefficient_MSD_Tau_End_(ns)'

TAU_PS = 'Tau(ps)'

TAU_START_PROP = 'r_matsci_Diffusion_Coefficient_MSD_Tau_Start_(ns)'

VECTOR_DELIM = ','

VECTOR_DELIM_WITH_SPACE = ', '

X = 'x'

Y = 'y'

Y_HEADERS = ['MSD(angstrom^2)', 'Std Dev(angstrom^2)']

Z = 'z'

calDensity()

Caluate the average system density.

checkConstantVol(allow_npt=True)

Calculate volume and check whether it changes.

Parameters

allow_npt (bool) – allow volume to change, if True

checkTau(frame_num, min_tau_data_point)

Check whether trj frame number is large enough.

Parameters

• frame_num (number of total data point) – int

• min_tau_data_point (minimum requested data) – int

static fitMsd(time_msd_std, start_idx, end_idx, dimension=3)

Fit the mean squared displacement

Parameters

• time_msd_std (numpy.ndarray) – first column is time in ps, second column is mean squared displacement in angstrom^2.

• start_idx (int) – index to select the starting frame

• end_idx (int) – index to select the ending frame

• dimension (int) – 1 stands for 1D; 2 stands for 2D; 3 stands for 3D

Returns

diffusivity coefficient in m^2/s, diffusivity_std in m^2/s, R-squared in linear regression

Return type

float, float, float

getMsdHeader()

Get the MSD csv header.

Returns

column labels separated by comma.

Return type

str

log(msg, **kwargs)

Add a message to the log file in driver mode, or ignore the logging in module mode.

Parameters

msg (str) – The information message

Additional keyword arguments are passed to the textlogger.log_msg function

log_error(msg)

Exit with the error printed in driver mode, or raise the error in module mode.

Parameters

str (msg) – The error message

Raise

RuntimeError in module mode

setAxisMSD()

Set the anisotropic along-axis 1d diffusion coefficients.

setIsotropicMSD()

Set the isotropic 3d diffusion coefficients.

setPlaneMSD()

Set the anisotropic in-plane 2d diffusion coefficients.

setTauFrame(tau_start=None, tau_end=None)

Set Tau frame start and end limits.

Parameters

• float (tau_end) – the starting tau value in ps

• float – the ending tau value in ps

trajFrames(make_whole=False)

Fix pbc bonds (if needed), yield the trajectory frame, and garbage-collect to release the occupied memory.

Parameters

make_whole (bool) – if True, bond across PBCs are fixed so that two bonded particles won’t be on opposite sides of the system

Return type

schrodinger.application.desmond.packages.traj.frame

Returns

a trajectory frame

classmethod vectorStr(vector)

Convert vector array to str format.

Parameters

vector (1 x 3 array of floats) – a vector

Returns

vector in str format

Return type

str

class schrodinger.application.matsci.equilibrium_md.SingleMDJob(jobname, md_opts, enegrp_opts, save_opts, command_dir='.', **kwargs)

Bases: schrodinger.application.matsci.jobutils.RobustSubmissionJob

Job class to submit a molecular dynamics simulation.

__init__(jobname, md_opts, enegrp_opts, save_opts, command_dir='.', **kwargs)

Parameters

• jobname (str) – The basename for the job

• md_opts ('SimpleNamespace') – molecular dynamics options

• enegrp_opts ('SimpleNamespace') – enegrp options

• save_opts ('SimpleNamespace') – files to save

• command_dir (str) – the job launch dir

setup()

Over write parent class method.

addFinalizer(function: Callable[[schrodinger.job.queue.BaseJob], None], run_dir: Optional[str] = None)

Add a function to be invoked when the job completes successfully.

See also the add_multi_job_finalizer function.

addGroupPrereq(job: schrodinger.job.queue.BaseJob)

Make all jobs connected to job prerequisites of all jobs connected to this Job.

addPrereq(job: schrodinger.job.queue.BaseJob)

Add a job that is an immediate prerequisite for this one.

cancel()

Send kill request to jobcontrol managed job. This method will eventually deprecate JobControlJob.kill

cancelSubmitted() → bool

If the job is still in the ‘submitted’ state, cancel it, purge the jobrecord and set the job handle to None.

Return True if this was successful, False otherwise.

doCommand(host: str, local: bool = False)

Launch job on specified host using jobcontrol.launch_job().

Parameters

• host – Host on which the job will be executed.

• local – Removed in JOB_SERVER.

finalize()

Clean up after a job successfully runs.

genAllJobs(seen: Optional[Set[schrodinger.job.queue.BaseJob]] = None) → Generator[schrodinger.job.queue.BaseJob, None, None]

A generator that yields all jobs connected to this one.

genAllPrereqs(seen=None) → Generator[schrodinger.job.queue.BaseJob, None, None]

A generator that yields all jobs that are prerequisites on this one.

getCommand() → List[str]

Return the command used to run this job.

getCommandDir() → str

Return the launch/command directory name. If None is returned, the job will be launched in the current directory.

getDuration() → Optional[int]

Return the duration of the Job as recorded by job server. The duration does not include queue wait time.

If the job is running or has not launched, returns None.

Note that this method makes a blocking call to the job server.

getJob() → Optional[schrodinger.job.jobcontrol.Job]

Return the job record as a schrodinger.job.jobcontrol.Job instance.

Returns None if the job hasn’t been launched.

getJobDJ() → schrodinger.job.queue.JobDJ

Return the JobDJ instance that this job has been added to.

getPrereqs()

Return a set of all immediate prerequisites for this job.

getStatusStrings() → Tuple[str, str, str]

Return a tuple of status strings for printing by JobDJ.

The strings returned are (status, jobid, host).

hasExited() → bool

Returns True if this job finished, successfully or not.

hasStarted() → bool

Returns True if this job has started (not waiting)

init_count = 0

isComplete() → bool

Returns True if this job finished successfully

kill()

Send kill request to jobcontrol managed job

maxFailuresReached(msg: str)

Print an error summary, including the last 20 lines from each log file in the LogFiles list of the job record.

postCommand()

A method to restore things to the pre-command state.

preCommand()

A method to make pre-command changes, like cd’ing to the correct directory to run the command in.

retryFailure(max_retries=0)

Determine if the job should be retried or not. This overwrites the parent method to not retry jobs that have a status of “died” as that will indicate that Jaguar failed, which it almost certainly will again.

Parameters

max_retries (int) – The queue’s max_retries parameter

Return type

bool

Returns

True if the job should be retried, False if not

run(*args, **kwargs)

Run the job.

The steps taken are as follows:

1. Execute the preCommand method for things like changing the working directory.

2. Call the doCommand to do the actual work of computation or job launching.

3. Call the postCommand method to undo the changes from the preCommand that need to be undone.

runsLocally() → bool

Return True if the job runs on the JobDJ control host, False if not. Jobs that run locally don’t need hosts.

There is no limit on the number of locally run jobs.

property state: schrodinger.job.queue.JobState

Return the current state of the job.

Note that this method can be overridden by subclasses that wish to provide for restartability at a higher level than unpickling BaseJob instances. For example, by examining some external condition (e.g. presence of output files) the state JobState.DONE could be returned immediately and the job would not run.

update()

Checks for changes in job status, and updates the object appropriately (marks for restart, etc).

Raises

RuntimeError – if an unknown Job Status or ExitStatus is encountered.

usesJobServer() → bool

Detect, by looking at the jobId, whether this job uses a job server.

class schrodinger.application.matsci.equilibrium_md.MultiDriver(options, jobname_base, logger=None, smart_jdj=False)

Bases: object

Class to fire off multiple subjobs.

__init__(options, jobname_base, logger=None, smart_jdj=False)

Parameters

• options (Named tuple) – The parsed command line options

• jobname_base (str) – base name of this job

• logger (logging.Logger) – The logger for this builder

• smart_jdj (bool) – whether to use smart distribution of jobs

run()

Run multiple calculation and perform ensemble average.

convertMultiToOne()

Convert data from files from multiple subjobs into one single file.

loadDataFromAllInOneFile()

Set the all-in-one file based on user input.

setUpQue()

Setup job queue.

initiateAndAddMdJobs(SingleMDJob=<class 'schrodinger.application.matsci.equilibrium_md.SingleMDJob'>, has_enegrp=False, additional_save_info=None, **kwargs)

Construct options, and initiate SingleMDJob jobs, and added them to jobdj.

Parameters

• SingleMDJob ('queue.JobControlJob') – instantiate this class to an object that can be added to jobdj

• has_enegrp (bool) – if False, no enegrp file is generated.

• additional_save_info ('types.SimpleNamespace') – additional information on what files to be copied back.

log(msg, **kwargs)

Add a message to the log file

Parameters

msg (str) – The message to log

Additional keyword arguments are passed to the textlogger.log_msg function

log_error(msg)

Add a message to the log file and exit with an error code

Parameters

msg (str) – The message to log

runSubjobs()

Run molecular dynamics jobs and Summarize the status of the runs.