def modify_input(input,
parameters: dict,
label: str = None,
context=None):
"""Modify simulation input with data flow operations.
Given simulation input *input*, override components of simulation input with
additional arguments, such as *parameters*.
"""
handle_context = context
if handle_context is not None:
raise gmxapi.exceptions.NotImplementedError(
'context must be None. This factory is only for the Python UI right now.')
target_context = _op.current_context()
assert isinstance(target_context, _op.Context)
# Get a director that will create a node in the standard context.
node_director = _op._get_operation_director(RegisteredOperation, context=target_context)
assert isinstance(node_director, StandardDirector)
# TODO: refine this protocol
assert handle_context is None
# Examine the input.
if isinstance(input, ModuleObject):
# The input is from read_tpr or modify_input.
source_context = input
else:
# Allow automatic dispatching
source_context = None
resource_factory = node_director.resource_factory(source=source_context, target=target_context)
resources = resource_factory(input=input, parameters=parameters)
handle = node_director(resources=resources, label=label)
return handle
def read_tpr(filename, label: str = None, context=None):
"""
Arguments:
filename: input file name
label: optional human-readable label with which to tag the new node
context: Context in which to return a handle to the new node.
Use default (None) for Python scripting interface
Returns:
Reference (handle) to the new operation instance (node).
"""
handle_context = context
if handle_context is not None:
raise gmxapi.exceptions.NotImplementedError(
'context must be None. This factory is only for the Python UI right now.')
# 1. Handle node creation in the scripting interface.
# When *context* input is None, dispatch to the current Context. Confirm that
# it is a standard context from the gmxapi.operation module, translate the
# input into that context, and create the node.
# 2. Dispatch to SimulationModuleContext.
# Operation is not fully implemented in gmxapi.operation context. When creating
# a node in a gmxapi.operation context, dispatch and subscribe to a SimulationModuleContext,
# in which
# 3. Handle consumption in SimulationModuleContext.
# When a consuming operation is native to the SimulationModuleContext,
# detect that a richer interface is available and use it. Possible implementation:
# Chain of Responsibility: subscribe() is serviced by the Context "closest"
# to the source. subscriber is the most native compatible Context for the consuming operation
# but decays to the context in which the handle is being created. subscribe()
# can accept a callback function and an indication of the form of the message
# to send (a consuming Context or ResourceFactory).
# TODO: Other types of input, such as File placeholders.
target_context = _op.current_context()
assert isinstance(target_context, _op.Context)
# Get a director that will create a node in the standard context.
node_director = _op._get_operation_director(RegisteredOperation, context=target_context)
assert isinstance(node_director, StandardDirector)
# TODO: refine this protocol
assert handle_context is None
resource_factory = node_director.resource_factory(source=handle_context, target=target_context)
resources = resource_factory(filename=filename)
handle = node_director(resources=resources, label=label)
# Note: One effect of the assertions above is to help the type checker infer
# the return type of the handle. It is hard to convince the type checker that
# the return value of the node builder is up-cast. We might be able to resolve
# this by making both get_operation_director and ReadTprImplementation
# generics of the handle type, or using the handle type as the key for
# get_operation_director.
return handle
def mdrun(input, label: str = None, context=None):
"""MD simulation operation.
Arguments:
input : valid simulation input
Returns:
runnable operation to perform the specified simulation
The *output* attribute of the returned operation handle contains dynamically
determined outputs from the operation.
`input` may be a TPR file name or a an object providing the SimulationInput interface.
Note:
New function names will be appearing to handle tasks that are separate
"simulate" is plausibly a dispatcher or base class for various tasks
dispatched by mdrun. Specific work factories are likely "minimize,"
"test_particle_insertion," "legacy_simulation" (do_md), or "simulation"
composition (which may be leap-frog, vv, and other algorithms)
"""
handle_context = context
if handle_context is not None:
raise gmxapi.exceptions.NotImplementedError(
'context must be None. This factory is only for the Python UI right now.'
)
target_context = _op.current_context()
assert isinstance(target_context, _op.Context)
# Get a director that will create a node in the standard context.
node_director = _op._get_operation_director(RegisteredOperation,
context=target_context)
assert isinstance(node_director, StandardDirector)
# TODO: refine this protocol
assert handle_context is None
# Examine the input.
if isinstance(input, ModuleObject):
# The input is from read_tpr or modify_input.
source_context = input
else:
# Allow automatic dispatching
source_context = None
resource_factory = node_director.resource_factory(source=source_context,
target=target_context)
resources = resource_factory(input)
handle = node_director(resources=resources, label=label)
# Note: One effect of the assertions above is to help the type checker infer
# the return type of the handle. It is hard to convince the type checker that
# the return value of the node builder is up-cast. We might be able to resolve
# this by making both get_operation_director and ReadTprImplementation
# generics of the handle type, or using the handle type as the key for
# get_operation_director.
return handle