gmxapi Python module reference¶
The Gromacs Python package includes a high-level scripting interface implemented
in pure Python and a lower-level API implemented as a C++ extension module.
The pure Python implementation provides the basic gmxapi
module and
classes with a very stable syntax that can be maintained with maximal compatibility
while mapping to lower level interfaces that may take a while to sort out. The
separation also serves as a reminder that different execution contexts may be
implemented quite diffently, though Python scripts using only the high-level
interface should execute on all.
Package documentation is extracted from the gmxapi
Python module and is also available
directly, using either pydoc
from the command line or help()
from within Python, such
as during an interactive session.
Refer to the Python source code itself for additional clarification.
See also
gmxapi basic package¶
import gmxapi as gmx
gmxapi Python package for GROMACS.
This package provides Python access to GROMACS molecular simulation tools. Operations can be connected flexibly to allow high performance simulation and analysis with complex control and data flows. Users can define new operations in C++ or Python with the same tool kit used to implement this package.
-
class
gmxapi.
NDArray
(data=None)¶ N-Dimensional array type.
-
gmxapi.
commandline_operation
(executable=None, arguments=(), input_files: dict = None, output_files: dict = None, stdin: str = None, **kwargs)¶ Helper function to define a new operation that executes a subprocess in gmxapi data flow.
Define a new Operation for a particular executable and input/output parameter set. Generate a chain of operations to process the named key word arguments and handle input/output data dependencies.
Parameters: - executable – name of an executable on the path
- arguments – list of positional arguments to insert at
argv[1]
- input_files – mapping of command-line flags to input file names
- output_files – mapping of command-line flags to output file names
- stdin (str) – String input to send to STDIN (terminal input) of the executable (optional).
Multi-line text sent to stdin should be joined into a single string. E.g.:
commandline_operation(..., stdin='\n'.join(list_of_strings) + '\n')
If multiple strings are provided to stdin, gmxapi will assume an ensemble, and will run one operation for each provided string.
Only string input (
str()
) to stdin is currently supported. If you have a use case that requires streaming input or binary input, please open an issue or contact the author(s).- Output:
The output node of the resulting operation handle contains
file
: the mapping of CLI flags to filename strings resulting from theoutput_files
kwargerroroutput
: A string of error output (if any) if the process failed.returncode
: return code of the subprocess.
-
gmxapi.
concatenate_lists
(sublists: list = ()) → gmxapi.typing.Future[gmxapi.datamodel.NDArray]¶ Combine data sources into a single list.
A trivial data flow restructuring operation.
-
gmxapi.
function_wrapper
(output: dict = None)¶ Generate a decorator for wrapped functions with signature manipulation.
New function accepts the same arguments, with additional arguments required by the API.
The new function returns an object with an
output
attribute containing the named outputs.Example
>>> @function_wrapper(output={'spam': str, 'foo': str}) ... def myfunc(parameter: str = None, output=None): ... output.spam = parameter ... output.foo = parameter + ' ' + parameter ... >>> operation1 = myfunc(parameter='spam spam') >>> assert operation1.output.spam.result() == 'spam spam' >>> assert operation1.output.foo.result() == 'spam spam spam spam'
Parameters: output (dict) – output names and types If
output
is provided to the wrapper, a data structure will be passed to the wrapped functions with the named attributes so that the function can easily publish multiple named results. Otherwise, theoutput
of the generated operation will just capture the return value of the wrapped function.
-
gmxapi.
join_arrays
(*, front: gmxapi.datamodel.NDArray = (), back: gmxapi.datamodel.NDArray = ()) → gmxapi.datamodel.NDArray¶ Operation that consumes two sequences and produces a concatenated single sequence.
Note that the exact signature of the operation is not determined until this helper is called. Helper functions may dispatch to factories for different operations based on the inputs. In this case, the dtype and shape of the inputs determines dtype and shape of the output. An operation instance must have strongly typed output, but the input must be strongly typed on an object definition so that a Context can make runtime decisions about dispatching work and data before instantiating. # TODO: elaborate and clarify. # TODO: check type and shape. # TODO: figure out a better annotation.
-
gmxapi.
logical_not
(value: bool) → gmxapi.typing.Future¶ Boolean negation.
If the argument is a gmxapi compatible Data or Future object, a new View or Future is created that proxies the boolean opposite of the input.
If the argument is a callable, logical_not returns a wrapper function that returns a Future for the logical opposite of the callable’s result.
-
gmxapi.
make_constant
(value: Scalar) → gmxapi.typing.Future¶ Provide a predetermined value at run time.
This is a trivial operation that provides a (typed) value, primarily for internally use to manage gmxapi data flow.
Accepts a value of any type. The object returned has a definite type and provides same interface as other gmxapi outputs. Additional constraints or guarantees on data type may appear in future versions.
-
gmxapi.
mdrun
(input, label: str = None, context=None)¶ MD simulation operation.
Parameters: 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)
-
gmxapi.
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.
-
gmxapi.
ndarray
(data=None, shape=None, dtype=None)¶ Create an NDArray object from the provided iterable.
Parameters: data – object supporting sequence, buffer, or Array Interface protocol New in version 0.1: shape and dtype parameters
If
data
is provided,shape
anddtype
are optional. Ifdata
is not provided, bothshape
anddtype
are required.If
data
is provided and shape is provided,data
must be compatible with or convertible toshape
. See Broadcast Rules inData model
documentation.If
data
is provided anddtype
is not provided, data type is inferred as the narrowest scalar type necessary to hold any element indata
.dtype
, whether inferred or explicit, must be compatible with all elements ofdata
.The returned object implements the gmxapi N-dimensional Array Interface.
-
gmxapi.
read_tpr
(filename, label: str = None, context=None)¶ Parameters: - 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).
-
gmxapi.
subgraph
(variables=None)¶ Allow operations to be configured in a sub-context.
The object returned functions as a Python context manager. When entering the context manager (the beginning of the
with
block), the object has an attribute for each of the namedvariables
. Reading from these variables gets a proxy for the initial value or its update from a previous loop iteration. At the end of thewith
block, any values or data flows assigned to these attributes become the output for an iteration.After leaving the
with
block, the variables are no longer assignable, but can be called as bound methods to get the current value of a variable.When the object is run, operations bound to the variables are
reset
and run to update the variables.
-
gmxapi.
while_loop
(*, operation, condition, max_iteration=10)¶ Generate and run a chain of operations such that condition evaluates True.
Returns and operation instance that acts like a single node in the current work graph, but which is a proxy to the operation at the end of a dynamically generated chain of operations. At run time, condition is evaluated for the last element in the current chain. If condition evaluates False, the chain is extended and the next element is executed. When condition evaluates True, the object returned by
while_loop
becomes a proxy for the last element in the chain.Equivalent to calling operation.while(condition), where available.
Parameters: - operation – a callable that produces an instance of an operation when called with no arguments.
- condition – a callable that accepts an object (returned by
operation
) that returns a boolean. - max_iteration – execute the loop no more than this many times (default 10)
Warning
max_iteration is provided in part to minimize the cost of bugs in early versions of this software. The default value may be changed or removed on short notice.
Warning
The protocol by which
while_loop
interacts withoperation
andcondition
is very unstable right now. Please refer to this documentation when installing new versions of the package.- Protocol:
- Warning:
- This protocol will be changed before the 0.1 API is finalized.
When called,
while_loop
callsoperation
without arguments and captures the return value captured as_operation
. The object produced byoperation()
must have areset
, arun
method, and anoutput
attribute.This is inspected to determine the output data proxy for the operation produced by the call to
while_loop
. When that operation is called, it does the equivalent of- while(condition(self._operation)):
- self._operation.reset() self._operation.run()
Then, the output data proxy of
self
is updated with the results from self._operation.output.
Status messages and Logging¶
Python logging facilities use the built-in logging module.
Upon import, the gmxapi package sets a placeholder “NullHandler” to block propagation of log messages to the root logger (and sys.stderr, if not handled).
If you want to see gmxapi logging output on sys.stderr, attach a logging.StreamHandler to the ‘gmxapi’ logger.
Example:
ch = logging.StreamHandler()
# Optional: Set log level.
ch.setLevel(logging.DEBUG)
# Optional: create formatter and add to character stream handler
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
ch.setFormatter(formatter)
# add handler to logger
logging.getLogger('gmxapi').addHandler(ch)
To handle log messages that are issued while importing gmxapi
and its submodules,
attach the handler before importing gmxapi
Each module in the gmxapi package uses its own hierarchical logger to allow
granular control of log handling (e.g. logging.getLogger('gmxapi.operation')
).
Refer to the Python logging
module for information on connecting to and handling
logger output.
Exceptions module¶
Exceptions and Warnings raised by gmxapi module operations.
Errors, warnings, and other exceptions used in the GROMACS
Python package are defined in the exceptions
submodule.
The gmxapi Python package defines a root exception, exceptions.Error, from which all Exceptions thrown from within the module should derive. If a published component of the gmxapi package throws an exception that cannot be caught as a gmxapi.exceptions.Error, please report the bug.
-
exception
gmxapi.exceptions.
ApiError
¶ An API operation was attempted with an incompatible object.
-
exception
gmxapi.exceptions.
DataShapeError
¶ An object has an incompatible shape.
This exception does not imply that the Type or any other aspect of the data has been checked.
-
exception
gmxapi.exceptions.
Error
¶ Base exception for gmx.exceptions classes.
-
exception
gmxapi.exceptions.
FeatureNotAvailableError
¶ Requested feature not available in the current environment.
This exception will usually indicate an issue with the user’s environment or run time details. There may be a missing optional dependency, which should be specified in the exception message.
-
exception
gmxapi.exceptions.
NotImplementedError
¶ Specified feature is not implemented in the current code.
This exception indicates that the implemented code does not support the API as specified. The calling code has used valid syntax, as documented for the API, but has reached incompletely implemented code, which should be considered a bug.
-
exception
gmxapi.exceptions.
ProtocolError
¶ Unexpected API behavior or protocol violation.
This exception generally indicates a gmxapi bug, since it should only occur through incorrect assumptions or misuse of API implementation internals.
-
exception
gmxapi.exceptions.
TypeError
¶ Incompatible type for gmxapi data.
Reference datamodel.rst for more on gmxapi data typing.
-
exception
gmxapi.exceptions.
UsageError
¶ Unsupported syntax or call signatures.
Generic usage error for gmxapi module.
-
exception
gmxapi.exceptions.
ValueError
¶ A user-provided value cannot be interpreted or doesn’t make sense.
-
exception
gmxapi.exceptions.
Warning
¶ Base warning class for gmx.exceptions.
gmx.version module¶
gmxapi version and release information.
The gmxapi.__version__
attribute contains a version string.
The more general way to access the package version is with the
pkg_resources
module:
pkg_resources.get_distribution('gmxapi').version
gmxapi.version
module functions api_is_at_least()
and has_feature()
support additional convenience and introspection.
Changed in version 0.2: This module no longer provides public data attributes.
Instead, use the module functions or
packaging.version
.
See also
Consider https://packaging.pypa.io/en/latest/version/ for programmatic handling of the version string. For example:
from packaging.version import parse
gmxapi_version = pkg_resources.get_distribution('gmxapi').version
if parse(gmxapi_version).is_prerelease:
print('The early bird gets the worm.')
-
gmxapi.version.
api_is_at_least
(major_version, minor_version=0, patch_version=0)¶ Allow client to check whether installed module supports the requested API level.
Parameters: Returns: True if installed gmx package is greater than or equal to the input level
Note that if gmxapi.version.release is False, the package is not guaranteed to correctly or fully support the reported API level.
-
gmxapi.version.
has_feature
(name=’’, enable_exception=False) → bool¶ Query whether a named feature is available in the installed package.
Between updates to the API specification, new features or experimental aspects may be introduced into the package and need to be detectable. This function is intended to facilitate code testing and resolving differences between development branches. Users should refer to the documentation for the package modules and API level.
The primary use case is, in conjunction with
api_is_at_least()
, to allow client code to robustly identify expected behavior and API support through conditional execution and branching. Note that behavior is strongly specified by the API major version number. Features that have become part of the specification and bug-fixes referring to previous major versions should not be checked with has_feature(). Using has_feature() with old feature names will produce a DeprecationWarning for at least one major version, and client code should be updated to avoid logic errors in future versions.For convenience, setting
enable_exception = True
causes the function to instead raise a gmxapi.exceptions.FeatureNotAvailableError for unrecognized feature names. This allows extension code to cleanly produce a gmxapi exception instead of first performing a boolean check. Also, some code may be unexecutable for more than one reason, and sometimes it is cleaner to catch allgmxapi.exceptions.Error
exceptions for a code block, rather than to construct complex conditionals.Returns: True if named feature is recognized by the installed package, else False. Raises: gmxapi.exceptions.FeatureNotAvailableError
– Ifenable_exception == True
and feature is not found.
Core API¶
gmxapi core module¶
gmxapi._gmxapi provides Python access to the GROMACS C++ API so that client code can be implemented in Python, C++, or a mixture. The classes provided are mirrored on the C++ side in the gmxapi namespace as best as possible.
This documentation is generated from C++ extension code. Refer to C++ source code and developer documentation for more details.
Exceptions¶
-
exception
gmxapi._gmxapi.
Exception
¶ Root exception for the C++ extension module. Derives from
gmxapi.exceptions.Error
.
-
exception
gmxapi._gmxapi.
NotImplementedError
¶ Expected feature is not implemented.
-
exception
gmxapi._gmxapi.
ProtocolError
¶ Behavioral protocol violated.
-
exception
gmxapi._gmxapi.
UnknownException
¶ GROMACS library produced an exception that is not mapped in gmxapi or which should have been caught at a lower level. I.e. a bug. (Please report.)
-
exception
gmxapi._gmxapi.
UsageError
¶ Unacceptable API usage.
Functions¶
Tools for launching simulations¶
-
gmxapi._gmxapi.
from_tpr
(arg0: str) → gmxapi._gmxapi.MDSystem¶ Return a system container initialized from the given input record.
Tools to manipulate TPR input files¶
-
gmxapi._gmxapi.
copy_tprfile
(source: gmxapi._gmxapi.TprFile, destination: str) → bool¶ Copy a TPR file from
source
todestination
.
-
gmxapi._gmxapi.
read_tprfile
(filename: str) → gmxapi._gmxapi.TprFile¶ Get a handle to a TPR file resource for a given file name.
-
gmxapi._gmxapi.
write_tprfile
(filename: str, parameters: gmxapi._gmxapi.SimulationParameters) → None¶ Write a new TPR file with the provided data.
Classes¶
-
class
gmxapi._gmxapi.
Context
¶ -
add_mdmodule
(self: gmxapi._gmxapi.Context, arg0: object) → None¶ Add an MD plugin for the simulation.
-
setMDArgs
(self: gmxapi._gmxapi.Context, arg0: gmxapi._gmxapi.MDArgs) → None¶ Set MD runtime parameters.
-
-
class
gmxapi._gmxapi.
MDArgs
¶ -
set
(self: gmxapi._gmxapi.MDArgs, arg0: dict) → None¶ Assign parameters in MDArgs from Python dict.
-
-
class
gmxapi._gmxapi.
MDSession
¶ -
close
(self: gmxapi._gmxapi.MDSession) → gmxapi._gmxapi.Status¶ Shut down the execution environment and close the session.
-
run
(self: gmxapi._gmxapi.MDSession) → gmxapi._gmxapi.Status¶ Run the simulation workflow
-
-
class
gmxapi._gmxapi.
MDSystem
¶ -
launch
(self: gmxapi._gmxapi.MDSystem, arg0: gmxapi._gmxapi.Context) → gmxapi._gmxapi.MDSession¶ Launch the configured workflow in the provided context.
-
-
class
gmxapi._gmxapi.
SimulationParameters
¶ -
extract
(self: gmxapi._gmxapi.SimulationParameters) → dict¶ Get a dictionary of the parameters.
-
set
(*args, **kwargs)¶ Overloaded function.
- set(self: gmxapi._gmxapi.SimulationParameters, key: str, value: int) -> None
Use a dictionary to update simulation parameters.
- set(self: gmxapi._gmxapi.SimulationParameters, key: str, value: float) -> None
Use a dictionary to update simulation parameters.
- set(self: gmxapi._gmxapi.SimulationParameters, key: str, value: none) -> None
Use a dictionary to update simulation parameters.
-