adaptivemd.Engine

class adaptivemd.Engine

An generator for trajectory simulation tasks

__init__()

x.__init__(…) initializes x; see help(type(x)) for signature

Methods

__init__()	x.__init__(…) initializes x; see help(type(x)) for signature
add_output_type(name[, filename, stride, …])	Add an output type for a trajectory kind to be generated by this engine
args()	Return a list of args of the __init__ function of a class
base()	Return the most parent class actually derived from StorableMixin
descendants()	Return a list of all subclassed objects
extend(target, length)	Create a task that extends a trajectory given in the input
from_dict(dct)	Reconstruct an object from a dictionary representation
get_uuid()	Create a new unique ID :returns: the unique number for an object in the project :rtype: long
idx(store)	Return the index which is used for the object in the given store.
items()
named(name)	Attach a .name property to an object
objects()	Returns a dictionary of all storable objects
run(target)	Create a task that returns a trajectory given in the input
stage(obj[, target])	Short cut to add a file to be staged
to_dict()	Convert object into a dictionary representation

Attributes

ACTIVE_LONG
CREATION_COUNT
INSTANCE_UUID
base_cls	Return the base class
base_cls_name	Return the name of the base class
cls	Return the class name as a string
files
full_strides	list of strides for trajectories that have full coordinates
native_stride	The least common multiple stride of all generated trajectories.
stage_in	Return a list of actions needed before tasks can be generated

classmethod from_dict(dct)

Reconstruct an object from a dictionary representation

Parameters:dct (dict) – the dictionary containing a state representation of the class. Returns:the reconstructed storable object Return type:StorableMixin

to_dict()

Convert object into a dictionary representation

Used to convert the dictionary into JSON string for serialization

Returns:the dictionary representing the (immutable) state of the object Return type:dict

run(target)

Create a task that returns a trajectory given in the input

Parameters:target (Trajectory) – location of the created target trajectory Returns:the task object containing the job description Return type:Task

extend(target, length)

Create a task that extends a trajectory given in the input

Parameters:

• target (Trajectory) – location of the target trajectory to be extended
• length (int) – number of additional frames to be computed

Returns:

the task object containing the job description

Return type:

Task

add_output_type(name, filename=None, stride=1, selection=None)

Add an output type for a trajectory kind to be generated by this engine

Parameters:

• name (str) – the name to call the output type by
• filename (str) – a filename to be used for this output type
• stride (int) – the stride used by this particular trajectory relative to the native steps of the engine.
• selection (str) – an mdtraj.Topology.select type filter string to store only a subset of atoms

native_stride

The least common multiple stride of all generated trajectories.

If you want consistent trajectory length your simulation length need to be multiples of this number. The number is relative to the native time steps

Returns:the lcm stride relative to the engines timesteps Return type:int

full_strides

list of strides for trajectories that have full coordinates

this is useful to figure out from which frames you can restart a new trajectory. Usually you only have a single one with full frames.

Returns:the list of strides for full trajectories Return type:list of int