ensembler.system package

Submodules

ensembler.system.basic_system module

Module: System

This module shall be used to implement subclasses of system. It wraps all information needed and generated by a simulation.

class ensembler.system.basic_system.system(potential: potential = <ensembler.potentials.OneD.harmonicOscillatorPotential object>, sampler: samplers = <ensembler.samplers.stochastic.metropolisMonteCarloIntegrator object>, conditions: Iterable[condition] = None, temperature: numbers.Number = 298.0, start_position: Iterable[numbers.Number] = None, mass: numbers.Number = 1, verbose: bool = True)[source]

Bases: ensembler.util.basic_class._baseClass

The system class is managing the simulation approaches and all system data as well as the simulation results.

__init__(potential: potential = <ensembler.potentials.OneD.harmonicOscillatorPotential object>, sampler: samplers = <ensembler.samplers.stochastic.metropolisMonteCarloIntegrator object>, conditions: Iterable[condition] = None, temperature: numbers.Number = 298.0, start_position: Iterable[numbers.Number] = None, mass: numbers.Number = 1, verbose: bool = True) → NoReturn[source]

The system class is wrapping all components needed for a simulation. It can be used as the control unit for executing a simulation (simulate) and also to manage the generated data or input data.

Parameters

  • potential (_potentialCls) – gives the potential function to be explored/sampled

  • sampler (_samplerCls) – gives the method of choice to sample/explore the potential function

  • conditions (Iterable[_conditionCls], optional) – apply the given conditions to the systems in a preset (tau) step iteration

  • temperature (float, optional) – temperature of the system

  • start_position (float, optional) – starting position of the system during the simulation

  • mass (float, optional) – mass of the single particle

  • verbose (bool, optional) – I can tell you a long iterative story…

_gen_rand_vel() → numbers.Number[source]
_gen_rand_vel

get a random velocity according to the temperature and mass.

Returns

a randomly selected velocity

Return type

Number, Iterable[Number]

_init_position(initial_position: Union[numbers.Number, Iterable[numbers.Number]] = None) → NoReturn[source]
_init_position

this function initializes the current position of the system.

Parameters

initial_position (Union[Number, Iterable[Number]], optional) – if None, a random position is selected else the given position is used.

_init_velocities() → NoReturn[source]

Initializes the initial velocity randomly.

_update_current_vars_from_current_state()[source]
_update_current_vars_from_current_state

update the _current Vars from the currentState

Returns

Return type

NoReturn

_update_energies() → NoReturn[source]
_updateEne

update all total energy terms.

Returns

Return type

NoReturn

_update_state_from_traj() → NoReturn[source]
_update_state_from_traj

replaces the current state and the currentstate vars by the last trajectory state.

Returns

Return type

NoReturn

_update_temperature() → NoReturn[source]

this looks like a thermostat like thing! not implemented!@ TODO calc temperature from velocity

Returns

Return type

NoReturn

append_state(new_position: Union[Iterable[numbers.Number], numbers.Number], new_velocity: Union[Iterable[numbers.Number], numbers.Number], new_forces: Union[Iterable[numbers.Number], numbers.Number]) → NoReturn[source]
append_state

appends a new state, based on the given arguments and updates the system to them.

Parameters

  • new_position (Union[Iterable[Number], Number]) – a new position

  • new_velocity (Union[Iterable[Number], Number]) – a new velocity

  • new_forces (Union[Iterable[Number], Number]) – a new Force

apply_conditions() → NoReturn[source]
applyConditions

this function applies the coupled conditions to the current state of system.

Returns

Return type

NoReturn

calculate_total_kinetic_energy() → Union[Iterable[numbers.Number], numbers.Number][source]
totKin

returns the total kinetic energy of the system.

Returns

total kinetic energy.

Return type

Union[Iterable[Number], Number, np.nan]

calculate_total_potential_energy() → Union[Iterable[numbers.Number], numbers.Number][source]
totPot

return the total potential energy

Returns

summed up total potential energies

Return type

Union[Iterable[Number], Number]

clear_trajectory()[source]

deletes all entries of trajectory and adds current state as first timestep to the trajectory :return: None

property conditions

conditions list contains the system conditions. These conditions are applied during the sampling of the potential energy function to add additional constraints.

Returns

the list of conditions coupled to the system.

Return type

List[_conditionCls]

property current_state
initialise(withdraw_Traj: bool = True, init_position: bool = True, init_velocity: bool = True, set_initial_position: Union[numbers.Number, Iterable[numbers.Number]] = None) → NoReturn[source]
initialise

initialises the system, i.e. can set an initial position, initial velocities and initialize the forces.

Parameters

  • withdraw_Traj (bool, optional) – reset the simulation trajectory?

  • init_position (bool, optional) – reinitialize the start_position - currentPosition

  • init_velocity (bool, optional) – reinitialize the start_velocity - currentVelocity

  • set_initial_position (Union[Number, Iterable[Number]], optional) – set the start_position to the given one.

Returns

Return type

NoReturn

property mass
nDimensions: int
nParticles: int
nStates: int

Attributes

name: str = 'system'
property position
property potential

The potential energy function class can be explored in a simulation

Returns

systems potential energy class

Return type

_potentialCls

propagate()[source]
propagate

Do a single exploration step. Not stored in the trajectory and no energies returned or updated.

Returns

returns the new current position, the new current velocities and the new current forces

Return type

(Union[Iterable[Number], Number], Union[Iterable[Number], Number], Union[Iterable[Number], Number])

random_position() → Union[numbers.Number, Iterable[numbers.Number]][source]
randomPos

returns a randomly selected position for the system.

Returns

a random position

Return type

Union[Number, Iterable[Number]]

revert_step() → NoReturn[source]
revertStep

removes the last step which was performed from the trajectory and sets back the system to the one before.

Returns

Return type

NoReturn

property sampler

The sampler method is used by the system to explore the potential energy function.

Returns

the sampler method that can be used to explore the potential energy function.

Return type

_samplerCls

set_current_state(current_position: Union[numbers.Number, Iterable[numbers.Number]], current_velocities: Union[numbers.Number, Iterable[numbers.Number]] = 0, current_force: Union[numbers.Number, Iterable[numbers.Number]] = 0, current_temperature: numbers.Number = 298)[source]

set the current State of the system.

Parameters

  • current_position (Union[Number, Iterable[Number]]) – new current system position

  • current_velocities (Union[Number, Iterable[Number]], optional) – new current system velocity. (default: 0)

  • current_force (Union[Number, Iterable[Number]], optional) – new current system force. (default: 0)

  • current_temperature (Union[Number, Iterable[Number]], optional) – new current system temperature. (default: 298)

set_position(position: Union[numbers.Number, Iterable[numbers.Number]])[source]
set_temperature(temperature: numbers.Number)[source]
set Temperature

set the systems current temperature.

Parameters

temperature

set_velocities(velocities)[source]
simulate(steps: int, withdraw_traj: bool = False, save_every_state: int = 1, init_system: bool = False, verbosity: bool = True, _progress_bar_prefix: str = 'Simulation: ') → __main__.State[source]

this function executes the simulation, by exploring the potential energy function with the sampling method for the given n steps.

Parameters

  • steps (int) – number of integration steps

  • init_system (bool, optional) – initialize the system. (default: False)

  • withdraw_traj (bool, optional) – reset the current simulation trajectory. (default: False)

  • save_every_state (int, optional) – save every n step. (and leave out the rest) (default: 1 - each step)

  • verbosity (bool, optional) – change the verbosity of the simulation. (default: True)

  • _progress_bar_prefix (str, optional) – prefix of tqdm progress bar. (default: “Simulation”)

Returns

returns the last current state

Return type

state

state

alias of __main__.State

property temperature

The set temperature of the system

Returns

set temperature

Return type

Number

property total_kinetic_energy

the total kinetic energy of the current system

Returns

total kinetic energy of the current system

Return type

Number

property total_potential_energy

the total potential energy of the current system

Returns

total potential energy of the current system

Return type

Number

property total_system_energy

the total energy of the current system

Returns

total energy of the current system

Return type

Number

property trajectory
update_current_state() → NoReturn[source]
updateCurrentState

update current state from the _current vars.

Returns

Return type

NoReturn

update_system_properties() → NoReturn[source]
updateSystemProperties

updates the energies and temperature of the system

Returns

Return type

NoReturn

property velocity
velocity

The current velocity of the system

Returns

Return type

Union[Number, Iterable[Number]]

write_trajectory(out_path: str) → str[source]
writeTrajectory

Writes the trajectory out to a file.

Parameters

out_path (str) – the string, where the traj csv should be stored.

Returns

returns the out_path

Return type

str

See also

save()

ensembler.system.eds_system module

Module: System

This module shall be used to implement subclasses of system. It wraps all information needed and generated by a simulation.

class ensembler.system.eds_system.edsSystem(potential: ensembler.potentials.OneD.envelopedPotential = <ensembler.potentials.OneD.envelopedPotential object>, sampler: samplers = <ensembler.samplers.stochastic.metropolisMonteCarloIntegrator object>, conditions: Iterable[condition] = [], temperature: float = 298.0, start_position: Union[numbers.Number, Iterable[numbers.Number]] = None, eds_s: float = 1, eds_Eoff: Iterable[numbers.Number] = [0, 0])[source]

Bases: ensembler.system.basic_system.system

The EDS-System is collecting and providing information essential to EDS. The Trajectory contains s and Eoff values for each step. Functions like set_s (or simply access s) or set_eoff (or simply access Eoff) give direct acces to the EDS potential.

__init__(potential: ensembler.potentials.OneD.envelopedPotential = <ensembler.potentials.OneD.envelopedPotential object>, sampler: samplers = <ensembler.samplers.stochastic.metropolisMonteCarloIntegrator object>, conditions: Iterable[condition] = [], temperature: float = 298.0, start_position: Union[numbers.Number, Iterable[numbers.Number]] = None, eds_s: float = 1, eds_Eoff: Iterable[numbers.Number] = [0, 0])[source]
__init__

construct a eds-System that can be used to manage a simulation.

Parameters

  • potential (pot.envelopedPotential, optional) – potential function class to be explored by sampling

  • sampler (sampler, optional) – sampling method, that allows exploring the potential function

  • conditions (Iterable[condition], optional) – conditions that shall be applied to the system.

  • temperature (float, optional) – The temperature of the system (default: 298K)

  • start_position – starting position for the simulation and setup of the system.

  • eds_s (float, optional) – is the S-value of the EDS-Potential

  • eds_Eoff (Iterable[Number], optional) – giving the energy offsets for the

append_state(new_position: Union[numbers.Number, Iterable[numbers.Number]], new_velocity: Union[numbers.Number, Iterable[numbers.Number]], new_forces: Union[numbers.Number, Iterable[numbers.Number]], new_s: Union[numbers.Number, Iterable[numbers.Number]], new_eoff: Iterable[numbers.Number])[source]
append_state

Append a new state to the trajectory.

Parameters

  • new_position (Union[Number, Iterable[Number]]) – new position for the system

  • new_velocity (Union[Number, Iterable[Number]]) – new velocity for the system

  • new_forces (Union[Number, Iterable[Number]]) – new forces for the system

  • new_s (Union[Number, Iterable[Number]]) – new s-value for the system

  • new_eoff (Iterable[Number]) – new eoffs for the system

property eoff

Eoff Energy Offsets for the EDS-potential

name: str = 'eds system'
property s

smoothing parameter for the EDS-potential

set_current_state(current_position: Union[numbers.Number, Iterable[numbers.Number]], current_velocities: Union[numbers.Number, Iterable[numbers.Number]] = 0, current_force: Union[numbers.Number, Iterable[numbers.Number]] = 0, current_temperature: Union[numbers.Number, Iterable[numbers.Number]] = 298, current_s: Union[numbers.Number, Iterable[numbers.Number]] = 1.0, current_eoff: Iterable[numbers.Number] = None)[source]
set_current_state

set s the current state to the given variables.

Parameters

  • current_position (Union[Number, Iterable[Number]]) – The new Position

  • current_velocities (Union[Number, Iterable[Number]],) – The new Velocities

  • current_force (Union[Number, Iterable[Number]],) – The new Forces of the system

  • current_temperature (Union[Number, Iterable[Number]],) – The new S_value

  • current_s (Union[Number, Iterable[Number]],) – the new s values.

  • current_eoff (Iterable[Number],) – the new eoff values.

set_eoff(eoff: Iterable[numbers.Number])[source]
set_Eoff

setting new Energy offsets.

Parameters

eoff (Iterable[Number]) – vector of new energy offsets

set_s(s: numbers.Number)[source]
set_s

setting a new s-value to the system.

Parameters

s (Number) – the new smoothing parameter s

state

alias of __main__.EDS_State

update_current_state()[source]
updateCurrentState

This function updates the current state from the _current Variables.

ensembler.system.perturbed_system module

Module: System

This module shall be used to implement subclasses of system. It wraps all information needed and generated by a simulation.

class ensembler.system.perturbed_system.perturbedSystem(potential: ensembler.potentials._basicPotentials._potential1DClsPerturbed = <ensembler.potentials.OneD.linearCoupledPotentials object>, sampler: samplers = <ensembler.samplers.stochastic.metropolisMonteCarloIntegrator object>, conditions: Iterable[condition] = [], temperature: float = 298.0, start_position: Iterable[numbers.Number] = None, lam: float = 0.0)[source]

Bases: ensembler.system.basic_system.system

__init__(potential: ensembler.potentials._basicPotentials._potential1DClsPerturbed = <ensembler.potentials.OneD.linearCoupledPotentials object>, sampler: samplers = <ensembler.samplers.stochastic.metropolisMonteCarloIntegrator object>, conditions: Iterable[condition] = [], temperature: float = 298.0, start_position: Iterable[numbers.Number] = None, lam: float = 0.0)[source]
__init__

construct a eds-System that can be used to manage a simulation.

Parameters

  • potential (pot.envelopedPotential, optional) – potential function class to be explored by sampling

  • sampler (sampler, optional) – sampling method, that allows exploring the potential function

  • conditions (Iterable[condition], optional) – conditions that shall be applied to the system.

  • temperature (float, optional) – The temperature of the system (default: 298K)

  • start_position – starting position for the simulation and setup of the system.

  • lam (Number, optional) – the value of the copuling lambda

_update_dHdLambda() → numbers.Number[source]
_update_dHdlambda

update the current dHdLambda value

Returns

dHdlambda

Return type

Number

append_state(new_position: Union[numbers.Number, Iterable[numbers.Number]], new_velocity: Union[numbers.Number, Iterable[numbers.Number]], new_forces: Union[numbers.Number, Iterable[numbers.Number]], new_lambda: numbers.Number) → NoReturn[source]
append_state

Append a new state to the trajectory.

Parameters

  • new_position (Union[Number, Iterable[Number]]) – new position for the system

  • new_velocity (Union[Number, Iterable[Number]]) – new velocity for the system

  • new_forces (Union[Number, Iterable[Number]]) – new forces for the system

  • new_lambda (Union[Number, Iterable[Number]]) – new lambda for the system

currentState: __main__.Lambda_State
property lam
name: str = 'perturbed system'
set_current_state(current_position: Union[numbers.Number, Iterable[numbers.Number]], current_velocities: Union[numbers.Number, Iterable[numbers.Number]] = 0, current_force: Union[numbers.Number, Iterable[numbers.Number]] = 0, current_temperature: Union[numbers.Number, Iterable[numbers.Number]] = 298, current_lambda: Union[numbers.Number, Iterable[numbers.Number]] = 0, current_dHdLambda: Union[numbers.Number, Iterable[numbers.Number]] = 0)[source]
set_current_state

set s the current state to the given variables.

Parameters

  • current_position (Union[Number, Iterable[Number]]) – new current system position

  • current_velocities (Union[Number, Iterable[Number]], optional) – new current system velocity. (default: 0)

  • current_force (Union[Number, Iterable[Number]], optional) – new current system force. (default: 0)

  • current_temperature (Union[Number, Iterable[Number]], optional) – new current system temperature. (default: 298)

  • current_lam (Union[Number, Iterable[Number]],) – The new lambda value (default: 0)

  • current_dHdLam (Union[Number, Iterable[Number]],) – The new dHdLam(default: 0)

set_lambda(lam: numbers.Number)[source]
state

alias of __main__.Lambda_State

update_current_state()[source]
updateCurrentState

This function updates the current state from the _current Variables.

update_system_properties() → NoReturn[source]
updateSystemProperties

update all system properties

Module contents

Systems wrap the sampler and the potential class to allow easy orchestration of simulations.