hoomd

Overview

Box

Define box dimensions.

Operations

A mutable collection of operations which act on a hoomd.Simulation.

Simulation

Define a simulation.

Snapshot

Self-contained copy of the simulation State.

State

The state of a hoomd.Simulation object.

Details

HOOMD-blue python API.

hoomd provides a high level user interface for defining and executing simulations using HOOMD.

class hoomd.Box(Lx, Ly, Lz=0, xy=0, xz=0, yz=0)

Define box dimensions.

Parameters

  • Lx (float) – box extent in the x direction \([\mathrm{length}]\).

  • Ly (float) – box extent in the y direction \([\mathrm{length}]\).

  • Lz (float) – box extent in the z direction \([\mathrm{length}]\).

  • xy (float) – tilt factor xy \([\mathrm{dimensionless}]\).

  • xz (float) – tilt factor xz \([\mathrm{dimensionless}]\).

  • yz (float) – tilt factor yz \([\mathrm{dimensionless}]\).

Simulation boxes in hoomd are specified by six parameters, Lx, Ly, Lz, xy, xz, and yz. Box provides a way to specify all six parameters for a given box and perform some common operations with them. A Box can be passed to an initialization method or to assigned to a saved State variable (state.box = new_box) to set the simulation box.

Access attributes directly:

box = hoomd.Box.cube(L=20)
box.xy = 1.0
box.yz = 0.5
box.Lz = 40

Two dimensional systems

2D simulations in HOOMD use boxes with Lz == 0. 2D boxes ignore xz and yz. If a new Box is assigned to a system with different dimensionality, a warning will be shown.

In 2D boxes, volume is in units of area.

Factory Methods

Box has factory methods to enable easier creation of boxes: cube, square, from_matrix, and from_box. See the method documentation for usage.

Examples: * Cubic box with given length: hoomd.Box.cube(L=1) * Square box with given length: hoomd.Box.square(L=1) * From an upper triangular matrix: hoomd.Box.from_matrix(matrix) * Specify values: hoomd.Box(Lx=1., Ly=2., Lz=3., xy=1., xz=2., yz=3.)

property L

The box lengths, [Lx, Ly, Lz] \([\mathrm{length}]\).

Can be set with a float which sets all lengths, or a length 3 vector.

Type

(3, ) numpy.ndarray of float

property Lx

The length of the box in the x dimension \([\mathrm{length}]\).

Type

float

property Ly

The length of the box in the y dimension \([\mathrm{length}]\).

Type

float

property Lz

The length of the box in the z dimension \([\mathrm{length}]\).

Type

float

__eq__(other)

Test if boxes are equal.

__neq__(other)

Test if boxes are not equal.

__reduce__()

Reduce values to picklable format.

__repr__()

Executable representation of the object.

classmethod cube(L)

Create a cube with side lengths L.

Parameters

L (float) – The box side length \([\mathrm{length}]\).

Returns

The created 3D box.

Return type

hoomd.Box

property dimensions

The dimensionality of the box.

If Lz == 0, the box is treated as 2D, otherwise it is 3D. This property is not settable.

Type

int

classmethod from_box(box)

Initialize a Box instance from a box-like object.

Parameters

box – A box-like object

Note

Objects that can be converted to HOOMD-blue boxes include lists like [Lx, Ly, Lz, xy, xz, yz], dictionaries with keys 'Lx', 'Ly', 'Lz', 'xy', 'xz', 'yz', objects with attributes Lx, Ly, Lz, xy, xz, yz, 3x3 matrices (see from_matrix), or existing hoomd.Box objects.

If any of Lz, xy, xz, yz are not provided, they will be set to 0.

If all values are provided, a triclinic box will be constructed. If only Lx, Ly, Lz are provided, an orthorhombic box will be constructed. If only Lx, Ly are provided, a rectangular (2D) box will be constructed.

Returns

The resulting box object.

Return type

hoomd.Box

classmethod from_matrix(box_matrix)

Create a box from an upper triangular matrix.

Parameters

box_matrix ((3, 3) numpy.ndarray of float) –

An upper triangular matrix representing a box. The values for Lx, Ly, Lz, xy, xz, and yz are related to the matrix by the following expressions.

[[Lx, Ly * xy, Lz * xz],
[0,  Ly,      Lz * yz],
[0,  0,       Lz]]

Returns

The created box.

Return type

hoomd.Box

property is2D

Flag whether the box is 2D.

If Lz == 0, the box is treated as 2D, otherwise it is 3D. This property is not settable.

Type

bool

property lattice_vectors

Box lattice vectors.

The lattice vectors are read-only.

Type

(3, 3) numpy.ndarray of float

property matrix

The upper triangular matrix that defines the box.

Can be used to set the box to one defined by an upper triangular matrix.

[[Lx, Ly * xy, Lz * xz],
 [0,  Ly,      Lz * yz],
 [0,  0,       Lz]]
Type

(3, 3) numpy.ndarray float

property periodic

The periodicity of each dimension.

Type

(3, ) numpy.ndarray of bool

scale(s)

Scale box dimensions.

Scales the box in place by the given scale factors. Tilt factors are not modified.

Parameters

s (float or list[float]) – scale factors in each dimension. If a single float is given then scale all dimensions by s; otherwise, s must be a sequence of 3 values used to scale each dimension.

Returns

self

classmethod square(L)

Create a square with side lengths L.

Parameters

L (float) – The box side length \([\mathrm{length}]\).

Returns

The created 2D box.

Return type

hoomd.Box

property tilts

The box tilts, [xy, xz, yz].

Can be set using one tilt for all axes or three tilts. If the box is 2D xz and yz will automatically be set to zero.

Type

(3, ) numpy.ndarray of float

property volume

Volume of the box.

\([\mathrm{length}^{2}]\) in 2D and \([\mathrm{length}^{3}]\) in 3D.

When setting volume the aspect ratio of the box is maintained while the lengths are changed.

Type

float

property xy

The tilt for the xy plane.

Type

float

property xz

The tilt for the xz plane.

Type

float

property yz

The tilt for the yz plane.

Type

float

class hoomd.Operations

A mutable collection of operations which act on a hoomd.Simulation.

The Operations class contains all the operations acting on a simulation. These operations are classes that perform various actions on a hoomd.Simulation. Operations can be added and removed at any point from a hoomd.Operations instance. The class provides the interface defined by collections.abc.Collection. Other methods for manipulating instances attempt to mimic Python objects where possible, but the class is not simply a mutable list or set. Since there are multiple types of operations in HOOMD-blue, Operations objects manage multiple independent sequences described below.

The types of operations which can be added to an Operations object are tuners, updaters, integrators, writers, and computes. An Operations can only ever hold one integrator at a time. On the other hand, an Operations object can hold any number of tuners, updaters, writers, or computes. To see examples of these types of operations see hoomd.tune (tuners), hoomd.update (updaters), hoomd.hpmc.integrate or hoomd.md.Integrator (integrators), hoomd.write (writers), and hoomd.md.thermo (computes).

A given instance of an operation class can only be added to a single Operations container. Likewise, a single instance cannot be added to the same Operations container more than once.

All Operations instances start with a hoomd.tune.ParticleSorter instance in their tuners attribute. This increases simulation performance. However, users can choose to modify or remove this tuner if desired.

Note

An Operations object is created by default when a new simulation is created.

__contains__(operation)

Whether an operation is contained in this container.

Parameters

operation – Returns whether this exact operation is contained in the collection.

__getstate__()

Get the current state of the operations container for pickling.

__iadd__(operation)

Works the same as Operations.add.

Parameters

operation (hoomd.operation.Operation) – A HOOMD-blue tuner, updater, integrator, writer, or compute to add to the object.

__isub__(operation)

Works the same as Operations.remove.

Parameters

operation (hoomd.operation.Operation) – A HOOMD-blue integrator, tuner, updater, integrator, analzyer, or compute to remove from the collection.

__iter__()

Iterates through all contained operations.

__len__()

Return the number of operations contained in this collection.

add(operation)

Add an operation to this container.

Adds the provided operation to the appropriate attribute of the Operations instance.

Parameters

operation (hoomd.operation.Operation) – A HOOMD-blue tuner, updater, integrator, writer, or compute, to add to the collection.

Raises

Note

Since only one integrator can be associated with an Operations object at a time, this removes the current integrator when called with an integrator operation. Also, the integrator property cannot be set to None using this function. Use operations.integrator = None explicitly for this.

property computes

A list of tuner operations.

Holds the list of tuners associated with this collection. The list can be modified as a standard Python list.

Type

list[hoomd.operation.Compute]

property integrator

An MD or HPMC integrator object.

Operations objects have an initial integrator property of None. Can be set to MD or HPMC integrators. The property can also be set to None.

Type

hoomd.integrate.BaseIntegrator

remove(operation)

Remove an operation from the Operations object.

Remove the item from the collection whose id is the same as operation. See https://docs.python.org/3/library/functions.html#id for the concept of a Python object id.

Parameters

operation (hoomd.operation.Operation) – A HOOMD-blue integrator, tuner, updater, integrator, or compute to remove from the container.

Raises

  • ValueError – If operation is not found in this container.

  • TypeError – If operation is not of a valid type.

property tuners

A list of tuner operations.

Holds the list of tuners associated with this collection. The list can be modified as a standard Python list.

Type

list[hoomd.operation.Tuner]

property updaters

A list of updater operations.

Holds the list of updaters associated with this collection. The list can be modified as a standard Python list.

Type

list[hoomd.operation.Updater]

property writers

A list of writer operations.

Holds the list of writers associated with this collection. The list can be modified as a standard Python list.

Type

list[hoomd.operation.Writer]

class hoomd.Simulation(device, seed=None)

Define a simulation.

Parameters

Simulation is the central class in HOOMD-blue that defines a simulation, including the state of the system, the operations that apply to the state during a simulation run, and the device to use when executing the simulation.

seed sets the seed for the random number generator used by all operations added to this Simulation.

property always_compute_pressure

Always compute the virial and pressure (defaults to False).

By default, HOOMD only computes the virial and pressure on timesteps where it is needed (when hoomd.write.GSD writes log data to a file or when using an NPT integrator). Set always_compute_pressure to True to make the per particle virial, net virial, and system pressure available to query any time by property or through the hoomd.logging.Logger interface.

Note

Enabling this flag will result in a moderate performance penalty when using MD pair potentials.

Type

bool

create_state_from_gsd(filename, frame=- 1, domain_decomposition=(None, None, None))

Create the simulation state from a GSD file.

Parameters

  • filename (str) – GSD file to read

  • frame (int) – Index of the frame to read from the file. Negative values index back from the last frame in the file.

  • domain_decomposition (tuple) – Choose how to distribute the state across MPI ranks with domain decomposition. Provide a tuple of 3 integers indicating the number of evenly spaced domains in the x, y, and z directions (e.g. (8,4,2)). Provide a tuple of 3 lists of floats to set the fraction of the simulation box to include in each domain. The sum of each list of floats must be 1.0 (e.g. ([0.25, 0.75], [0.2, 0.8], [1.0])).

Note

Set any or all of the domain_decomposition tuple elements to None and create_state_from_gsd will select a value that minimizes the surface area between the domains (e.g. (2,None,None)). The domains are spaced evenly along each automatically selected direction. The default value of (None, None, None) will automatically select the number of domains in all directions.

create_state_from_snapshot(snapshot, domain_decomposition=(None, None, None))

Create the simulation state from a Snapshot.

Parameters

  • snapshot (Snapshot or gsd.hoomd.Snapshot) – Snapshot to initialize the state from. A gsd.hoomd.Snapshot will first be converted to a hoomd.Snapshot.

  • domain_decomposition (tuple) – Choose how to distribute the state across MPI ranks with domain decomposition. Provide a tuple of 3 integers indicating the number of evenly spaced domains in the x, y, and z directions (e.g. (8,4,2)). Provide a tuple of 3 lists of floats to set the fraction of the simulation box to include in each domain. The sum of each list of floats must be 1.0 (e.g. ([0.25, 0.75], [0.2, 0.8], [1.0])).

When timestep is None before calling, create_state_from_snapshot sets timestep to 0.

Note

Set any or all of the domain_decomposition tuple elements to None and create_state_from_gsd will select a value that minimizes the surface area between the domains (e.g. (2,None,None)). The domains are spaced evenly along each automatically selected direction. The default value of (None, None, None) will automatically select the number of domains in all directions.

See also

State.get_snapshot

State.set_snapshot

property device

Device used to execute the simulation.

Type

hoomd.device.Device

property final_timestep

run will end at this timestep.

final_timestep is the timestep on which the currently executing run will complete.

(Loggable: category=”scalar”)

Type

float

property loggables

Name, category mapping of loggable quantities.

Type

dict[str, str]

property operations

The operations that apply to the state.

Type

hoomd.Operations

run(steps, write_at_start=False)

Advance the simulation a number of steps.

Parameters

  • steps (int) – Number of steps to advance the simulation.

  • write_at_start (bool) – When True, writers with triggers that evaluate True for the initial step will be executed before the time step loop.

Note

Initialize the simulation’s state before calling run.

During each step run, Simulation applies its operations to the state in the order: Tuners, Updaters, Integrator, then Writers following the logic in this pseudocode:

if write_at_start:
    for writer in operations.writers:
        if writer.trigger(timestep):
            writer.write(timestep)

end_step = timestep + steps
while timestep < end_step:
    for tuner in operations.tuners:
        if tuner.trigger(timestep):
            tuner.tune(timestep)

    for updater in operations.updaters:
        if updater.trigger(timestep):
            updater.update(timestep)

    if operations.integrator is not None:
        operations.integrator(timestep)

    timestep += 1

    for writer in operations.writers:
        if writer.trigger(timestep):
            writer.write(timestep)

This order of operations ensures that writers (such as hoomd.write.GSD) capture the final output of the last step of the run loop. For example, a writer with a trigger hoomd.trigger.Periodic(period=100, phase=0) active during a run(500) would write on steps 100, 200, 300, 400, and 500. Set write_at_start=True on the first call to run to also obtain output at step 0.

Warning

Using write_at_start=True in subsequent calls to run will result in duplicate output frames.

property seed

Random number seed.

Seeds are in the range [0, 65535]. When set, seed will take only the lowest 16 bits of the given value.

HOOMD-blue uses a deterministic counter based pseudorandom number generator. Any time a random value is needed, HOOMD-blue computes it as a function of the user provided seed seed (16 bits), the current timestep (lower 40 bits), particle identifiers, MPI ranks, and other unique identifying values as needed to sample uncorrelated values: random_value = f(seed, timestep, ...)

(Loggable: category=”scalar”)

Type

int

property state

The current simulation state.

Type

hoomd.State

property timestep

Current time step of the simulation.

Note

Functions like create_state_from_gsd will set the initial timestep from the input. Set timestep before creating the simulation state to override values from create_ methods:

sim.timestep = 5000
sim.create_state_from_gsd('gsd_at_step_10000000.gsd')
assert sim.timestep == 5000

(Loggable: category=”scalar”)

Type

int

property tps

The average number of time steps per second.

tps is the number of steps executed divided by the elapsed walltime in seconds. It is updated during the run loop and remains fixed after run completes.

Note

The start time and step are reset at the beginning of each call to run.

(Loggable: category=”scalar”)

Type

float

property walltime

The walltime spent during the last call to run.

walltime is the number seconds that the last call to run took to complete. It is updated during the run loop and remains fixed after run completes.

Note

walltime resets to 0 at the beginning of each call to run.

(Loggable: category=”scalar”)

Type

float

class hoomd.Snapshot(communicator=None)

Self-contained copy of the simulation State.

Parameters

communicator (Communicator) – MPI communicator to be used with the simulation.

communicator

MPI communicator.

Type

Communicator

Note

Snapshot is duck-type compatible with gsd.hoomd.Snapshot except that arrays in Snapshot are not assignable. You can edit their contents: e.g. snapshot.particles.typeid[:] == 0.

Warning

Data is only present on the root rank:

if snapshot.communicator.rank == 0:
    pos = snapshot.particles.position[0]

See also

State

Simulation.create_state_from_snapshot

State.get_snapshot

State.set_snapshot

property angles

Angles.

angles.N

Number of angles.

Type

int

angles.types

Names of the angle types

Type

list[str]

angles.typeid

Angle type id.

Type

(N,) numpy.ndarray of uint32

angles.group

Tags of the particles in the angle.

Type

(N, 3) numpy.ndarray of uint32

Note

Set N to change the size of the arrays.

property bonds

Bonds.

bonds.N

Number of bonds.

Type

int

bonds.types

Names of the bond types

Type

list[str]

bonds.typeid

Bond type id.

Type

(N,) numpy.ndarray of uint32

bonds.group

Tags of the particles in the bond.

Type

(N, 2) numpy.ndarray of uint32

Note

Set N to change the size of the arrays.

property configuration

Snapshot box configuration.

dimensions

Number of dimensions

Type

int

box

Simulation box parameters [Lx, Ly, Lz, xy, xz, yz].

Type

tuple[float, float, float, float, float, float]

Note

box accepts any values that Box.from_box allows when setting.

property constraints

Constraints.

constraints.N

Number of constraints.

Type

int

constraints.value

Constraint length.

Type

(N, ) numpy.ndarray of float

constraints.group

Tags of the particles in the constraint.

Type

(N, 2) numpy.ndarray of uint32

Note

Set N to change the size of the arrays.

property dihedrals

Dihedrals.

dihedrals.N

Number of dihedrals.

Type

int

dihedrals.types

Names of the dihedral types

Type

list[str]

dihedrals.typeid

Dihedral type id.

Type

(N,) numpy.ndarray of uint32

dihedrals.group

Tags of the particles in the dihedral.

Type

(N, 4) numpy.ndarray of uint32

Note

Set N to change the size of the arrays.

classmethod from_gsd_snapshot(gsd_snap, communicator)

Constructs a hoomd.Snapshot from a gsd.hoomd.Snapshot object.

Parameters

Note

from_gsd_snapshot only accesses the gsd_snap argument on rank 0. In MPI simulations, avoid duplicating memory and file reads by reading GSD files only on rank 0 and passing gsd_snap=None on other ranks.

property impropers

Impropers.

impropers.N

Number of impropers.

Type

int

impropers.types

Names of the improper types

Type

list[str]

impropers.typeid

Improper type id.

Type

(N,) numpy.ndarray of uint32

impropers.group

Tags of the particles in the improper.

Type

(N, 4) numpy.ndarray of uint32

Note

Set N to change the size of the arrays.

property pairs

Special pairs.

pairs.N

Number of special pairs.

Type

int

pairs.types

Names of the special pair types

Type

list[str]

pairs.typeid

Special pair type id.

Type

(N,) numpy.ndarray of uint32

pairs.group

Tags of the particles in the special pair.

Type

(N, 2) numpy.ndarray of uint32

Note

Set N to change the size of the arrays.

property particles

Particles.

particles.N

Number of particles in the snapshot.

Type

int

particles.types

Names of the particle types.

Type

list[str]

particles.position

Particle position \([\mathrm{length}]\).

Type

(N, 3) numpy.ndarray of float

particles.orientation

Particle orientation.

Type

(N, 4) numpy.ndarray of float

particles.typeid

Particle type id.

Type

(N, ) numpy.ndarray of uint32

particles.mass

Particle mass \([\mathrm{mass}]\).

Type

(N, ) numpy.ndarray of float

particles.charge

Particle charge \([\mathrm{charge}]\).

Type

(N, ) numpy.ndarray of float

particles.diameter

Particle diameter \([\mathrm{length}]\).

Type

(N, ) numpy.ndarray of float

particles.body

Particle body.

Type

(N, ) numpy.ndarray of int32

particles.moment_inertia

Particle moment of inertia \([\mathrm{mass} \cdot \mathrm{length}^2]\).

Type

(N, 3) numpy.ndarray of float

particles.velocity

Particle velocity \([\mathrm{velocity}]\).

Type

(N, 3) numpy.ndarray of float

particles.angmom

Particle angular momentum \([\mathrm{mass} \cdot \mathrm{velocity} \cdot \mathrm{length}]\).

Type

(N, 4) numpy.ndarray of float

particles.image

Particle image.

Type

(N, 3) numpy.ndarray of int32

Note

Set N to change the size of the arrays.

replicate(nx, ny, nz=1)

Replicate the snapshot along the periodic box directions.

Parameters

  • nx (int) – Number of times to replicate in the x direction.

  • ny (int) – Number of times to replicate in the y direction.

  • nz (int) – Number of times to replicate in the z direction.

Performs the same operation as State.replicate on a Snapshot.

Returns

self

wrap()

Wrap particles into the snapshot box.

Returns

self

class hoomd.State(simulation, snapshot, domain_decomposition)

The state of a hoomd.Simulation object.

Note

This object cannot be directly instantiated. Use hoomd.Simulation.create_state_from_gsd and hoomd.Simulation.create_state_from_snapshot to instantiate a State object as part of a simulation.

Overview

State stores the data that describes the thermodynamic microstate of a hoomd.Simulation object. This data consists of the box, particles, bonds, angles, dihedrals, impropers, special pairs, and constraints.

Box

The simulation box describes the area in space that contains the particles and the periodic boundary conditions to apply. See Box for a full description.

Particles

The state contains N_particles particles. Each particle has a position, orientation, type id, body, mass, moment of inertia, charge, diameter, velocity, angular momentum, image, and tag:

  • \(\vec{r}\): position \([\mathrm{length}]\) - x,y,z cartesian coordinates defining the position of the particle in the box

  • \(\mathbf{q}\): orientation \([\mathrm{dimensionless}]\) - (s, \(\vec{a}\)), unit quaternion defining the rotation from the particle’s local reference frame to the box reference frame.

  • \(t_\mathrm{id}\): type id \([\mathrm{dimensionless}]\) - integer in the range [0,len(particle_types)) that identifies the particle’s type. particle_types maps type ids to names with: name = particle_types[t_id].

  • \(b_\mathrm{id}\): body id \([\mathrm{dimensionless}]\) - integer that identifies the particle’s rigid body. A value of -1 indicates that this particle does not belong to a body. A positive value indicates that the particle belongs to the body \(b_\mathrm{id}\). This particle is the central particle of a body when the body id is equal to the tag \(b_\mathrm{id} = p_\mathrm{tag}\). (used by md.constrain.Rigid)

  • \(m\): mass \([\mathrm{mass}]\) - the particle’s mass.

  • \(I\): moment of inertia \([\mathrm{mass} \cdot \mathrm{length}^2]\) - \(I_{xx}\), \(I_{yy}\), \(I_{zz}\) elements of the diagonal moment of inertia tensor in the particle’s local reference frame. The off-diagonal elements are 0.

  • \(q\): charge \([\mathrm{charge}]\)

  • \(d\): diameter \([\mathrm{length}]\) - deprecated in v3.0.0. HOOMD-blue reads and writes particle diameters, but does not use them in any computations. As of the current beta release, diameter is still used in md.pair.SLJ and md.pair.DLVO.

  • \(\vec{v}\): velocity \([\mathrm{velocity}]\) - x,y,z components of the particle’s velocity in the box’s reference frame.

  • \(\mathbf{P_S}\): angular momentum \([\mathrm{mass} \cdot \mathrm{velocity} \cdot \mathrm{length}]\) - in a quaternion representation (see note).

  • \(\vec{n}\) : image \([\mathrm{dimensionless}]\) - integers x,y,z that record how many times the particle has crossed each of the periodic box boundaries.

  • \(p_\mathrm{tag}\) : tag \([\mathrm{dimensionless}]\) - integer that uniquely identifies a given particle. The particles are in tag order when writing and initializing to/from a GSD file or snapshot: \(p_\mathrm{tag,i} = i\). When accessing data in local snapshots, particles may be in any order.

Note

HOOMD stores angular momentum as a quaternion because that is the form used when integrating the equations of motion (see Kamberaj 2005). The angular momentum quaternion \(\mathbf{P_S}\) is defined with respect to the orientation quaternion of the particle \(\mathbf{q}\) and the vector angular momentum of the particle, lifted into pure imaginary quaternion form \(\mathbf{S}^{(4)}\) as:

\[\mathbf{P_S} = 2 \mathbf{q} \times \mathbf{S}^{(4)}\]

. Following this, the angular momentum vector \(\vec{S}\) in the particle’s local reference frame is:

\[\vec{S} = \frac{1}{2}im(\mathbf{q}^* \times \mathbf{P_S})\]

Bonds

The state contains N_bonds bonds, N_angles angles, N_dihedrals dihedrals, N_impropers impropers, and N_special_pairs special pairs. Each of these data structures is similar, differing in the number of particles in the group and what operations use them. Bonds, angles, dihedrals, and impropers contain 2, 3, 4, and 4 particles per group respectively. Bonds specify the toplogy used when computing energies and forces in md.bond, angles define the same for md.angle, dihedrals for md.dihedral and impropers for md.improper. These collectively implement bonding potentials used in molecular dynamics force fields. Like bonds, special pairs define connections between two particles, but special pairs are intended to adjust the 1-4 pairwise interactions in some molecular dynamics force fields: see md.special_pair. Each bonded group is defined by a type id, the group members, and a tag.

  • \(t_\mathrm{id}\): type id \([\mathrm{dimensionless}]\) - integer in the range [0,len(bond_types)) that identifies the bond’s type. bond_types maps type ids to names with: name = bond_types[t_id]. Similarly, angle_types lists the angle types, dihedral_types lists the dihedral types, improper_types lists the improper types, and special_pair_types lists the special pair types.

  • group members: a list of integers in the range [0,max(p_tag)] that defines the tags of the particles in the bond (2), angle (3), dihedral (4), improper (4), or special pair (2).

  • \(b_\mathrm{tag}\) : tag \([\mathrm{dimensionless}]\) - integer that uniquely identifies a given bond. The bonds are in tag order when writing and initializing to/from a GSD file or snapshot \(b_\mathrm{tag,i} = i\). When accessing data in local snapshots, bonds may be in any order.

Constraints

The state contains N_constraints distance constraints between particles. These constraints are enforced by md.constrain.Distance. Each distance constraint consists of a distance value and the group members.

  • group members: a list of 2 integers in the range [0,max(p_tag)] that defines the tags of the particles in the constraint.

  • \(d\): constraint value \([\mathrm{length}]\) - the distance between particles in the constraint.

MPI

When running in serial or on 1 MPI rank, the entire simulation state is stored in that process. When using more than 1 MPI rank, HOOMD-blue employs a domain decomposition approach to split the simulation box an integer number of times in the x, y, and z directions. Each MPI rank stores and operates on the particles local to that rank, those contained within the region defined by the split planes. Each MPI rank communicates with its neighbors to obtain the properties of particles near the boundary between ranks (ghost particles) so that it can compute interactions across the boundary.

Accessing Data

Two complementary APIs provide access to the state data: local snapshots that access data directly available on the local MPI rank (including the local and ghost particles) and global snapshots that collect the entire state on rank 0. See State.cpu_local_snapshot, State.gpu_local_snapshot, State.get_snapshot, and State.set_snapshot for information about these data access patterns.

property N_angles

The number of angles in the simulation state.

Type

int

property N_bonds

The number of bonds in the simulation state.

Type

int

property N_constraints

The number of constraints in the simulation state.

Type

int

property N_dihedrals

The number of dihedrals in the simulation state.

Type

int

property N_impropers

The number of impropers in the simulation state.

Type

int

property N_particles

The number of particles in the simulation state.

Type

int

property N_special_pairs

The number of special pairs in the simulation state.

Type

int

property angle_types

List of all angle types in the simulation state.

Type

list[str]

property bond_types

List of all bond types in the simulation state.

Type

list[str]

property box

A copy of the current simulation box.

Note

The box property cannot be set. Call set_box to set a new simulation box.

Type

hoomd.Box

property cpu_local_snapshot

Expose simulation data on the CPU.

Provides access directly to the system state’s particle, bond, angle, dihedral, improper, constaint, and pair data through a context manager. Data in State.cpu_local_snapshot is MPI rank local, and the hoomd.data.LocalSnapshot object is only usable within a context manager (i.e. with sim.state.cpu_local_snapshot as data:). Attempts to assess data outside the context manager will result in errors. The local snapshot interface is similar to that of hoomd.Snapshot.

The hoomd.data.LocalSnapshot data access is mediated through hoomd.array.HOOMDArray objects. This lets us ensure memory safety when directly accessing HOOMD-blue’s data. The interface provides zero-copy access (zero-copy is guaranteed on CPU, access may be zero-copy if running on GPU).

Changing the data in the buffers exposed by the local snapshot will change the data across the HOOMD-blue simulation. For a trivial example, this example would set all particle z-axis positions to 0.

with sim.state.cpu_local_snapshot as data:
    data.particles.position[:, 2] = 0

Note

The state’s box and the number of particles, bonds, angles, dihedrals, impropers, constaints, and pairs cannot change within the context manager.

Note

Getting a local snapshot object is order \(O(1)\) and setting a single value is of order \(O(1)\).

Type

hoomd.data.LocalSnapshot

property dihedral_types

List of all dihedral types in the simulation state.

Type

list[str]

property domain_decomposition

Number of domains in the x, y, and z directions.

Type

tuple(int, int, int)

property domain_decomposition_split_fractions

Box fractions of the domain split planes in the x, y, and z directions.

Type

tuple(list[float], list[float], list[float])

get_snapshot()

Make a copy of the simulation current state.

State.get_snapshot makes a copy of the simulation state and makes it available in a single object. State.set_snapshot resets the internal state to that in the given snapshot. Use these methods to implement techniques like hybrid MD/MC or umbrella sampling where entire system configurations need to be reset to a previous one after a rejected move.

Note

Data across all MPI ranks and from GPUs is gathered on the root MPI rank’s memory. When accessing data in MPI simulations, use a if snapshot.communicator.rank == 0: conditional to access data arrays only on the root rank.

Note

State.get_snapshot is an order \(O(N_{particles} + N_{bonds} + \ldots)\) operation.

See also

set_snapshot

Returns

The current simulation state

Return type

hoomd.Snapshot

property gpu_local_snapshot

Expose simulation data on the GPU.

Provides access directly to the system state’s particle, bond, angle, dihedral, improper, constaint, and pair data through a context manager. Data in State.gpu_local_snapshot is GPU local, and the hoomd.data.LocalSnapshotGPU object is only usable within a context manager (i.e. with sim.state.gpu_local_snapshot as data:). Attempts to assess data outside the context manager will result in errors. The local snapshot interface is similar to that of hoomd.Snapshot.

The hoomd.data.LocalSnapshotGPU data access is mediated through hoomd.array.HOOMDGPUArray objects. This helps us maintain memory safety when directly accessing HOOMD-blue’s data. The interface provides zero-copy access on the GPU (assuming data was last accessed on the GPU).

Changing the data in the buffers exposed by the local snapshot will change the data across the HOOMD-blue simulation. For a trivial example, this example would set all particle z-axis positions to 0.

with sim.state.gpu_local_snapshot as data:
    data.particles.position[:, 2] = 0

Warning

This property is only available when running on a GPU(s).

Note

The state’s box and the number of particles, bonds, angles, dihedrals, impropers, constaints, and pairs cannot change within the context manager.

Note

Getting a local snapshot object is order \(O(1)\) and setting a single value is of order \(O(1)\).

Type

hoomd.data.LocalSnapshotGPU

property improper_types

List of all improper types in the simulation state.

Type

list[str]

property particle_types

List of all particle types in the simulation state.

Type

list[str]

replicate(nx, ny, nz=1)

Replicate the state of the system along the periodic box directions.

Parameters

  • nx (int) – Number of times to replicate in the x direction.

  • ny (int) – Number of times to replicate in the y direction.

  • nz (int) – Number of times to replicate in the z direction.

replicate makes the system state nx * ny * nz times larger. In each of the new periodic box images, it places a copy of the initial state with the particle positions offset to locate them in the image and the bond, angle, dihedral, improper, and pair group tags offset to apply to the copied particles. All other particle properties (mass, typeid, velocity, charge, …) are copied to the new particles without change.

After placing the particles, replicate expands the simulation box by a factor of nx, ny, and nz in the direction of the first, second, and third box lattice vectors respectively and adjusts the particle positions to center them in the new box.

set_box(box)

Set a new simulation box.

Parameters

box (Box) – New simulation box.

Note

All particles must be inside the new box. set_box does not change any particle properties.

See also

hoomd.update.BoxResize.update

set_snapshot(snapshot)

Restore the state of the simulation from a snapshot.

Parameters

snapshot (hoomd.Snapshot) – Snapshot of the system from get_snapshot

Warning

set_snapshot can only make limited changes to the simulation state. While it can change the number of particles/bonds/etc… or their properties, it cannot change the number or names of the particle/bond/etc.. types.

Note

State.set_snapshot is an order \(O(N_{particles} + N_{bonds} + \ldots)\) operation and is very expensive when the simulation device is a GPU.

See also

get_snapshot

Simulation.create_state_from_snapshot

property special_pair_types

List of all special pair types in the simulation state.

Type

list[str]

thermalize_particle_momenta(filter, kT)

Assign random values to particle momenta.

Parameters

thermalize_particle_momenta assigns the selected particle’s velocities and angular momentum to random values drawn from a Gaussian distribution consistent with the given thermal energy kT.

Velocity

thermalize_particle_momenta assigns random velocities to the x and y components of each particle’s velocity. When the simulation box is 3D, it also assigns a random velocity to the z component. When the simulation box is 2D, it sets the z component to 0. Finally, sets the center of mass velocity of the selected particles to 0.

Angular momentum

thermalize_particle_momenta assigns random angular momenta to each rotational degree of freedom that has a non-zero moment of intertia. Each particle can have 0, 1, 2, or 3 rotational degrees of freedom as determine by its moment of inertia.

See also

md.methods.NVT.thermalize_thermostat_dof

md.methods.NPT.thermalize_thermostat_and_barostat_dof

property types

dictionary of all types in the state.

Combines the data from State.particle_types, State.bond_types, State.angle_types, State.dihedral_types, State.improper_types, and State.special_pair_types into a dictionary with keys matching the property names.

Type

dict[str, list[str]]

update_group_dof()

Update the number of degrees of freedom in each group.

The groups of particles selected by filters each need to know the number of degrees of freedom given to that group by the simulation’s Integrator. This method is called automatically when:

  • The Integrator is attached to the simulation

Call it manually to force an update.

Modules