Artificial trajectory generator

MDANSE/Src/MDANSE/Framework/Configurable.py

@@ -42,7 +42,7 @@ class Configurable(object):
 
     settings = collections.OrderedDict()
 
-    def __init__(self, settings=None):
+    def __init__(self, settings=None, trajectory_input="mdasne"):
         """
         Constructor
         """
@@ -56,6 +56,29 @@ def __init__(self, settings=None):
         if settings is not None:
             self.set_settings(settings)
 
+        if trajectory_input == "mdmc":
+            self.mdmc_trajectory_input()
+        elif trajectory_input == "mock":
+            self.mock_trajectory_input()
+
+    def mdmc_trajectory_input(self):
+        """Remove the hdf_trajectory (file-based) from settings,
+        and introduce an MDMC trajectory instead.
+        """
+        for key, value in self.settings.items():
+            if key == "trajectory":
+                if value[0] == "HDFTrajectoryConfigurator":
+                    self.settings[key] = ("MDMCTrajectoryConfigurator", {})
+
+    def mock_trajectory_input(self):
+        """Remove the hdf_trajectory (file-based) from settings,
+        and introduce a mock trajectory instead.
+        """
+        for key, value in self.settings.items():
+            if key == "trajectory":
+                if value[0] == "HDFTrajectoryConfigurator":
+                    self.settings[key] = ("MockTrajectoryConfigurator", {})
+
     def build_configuration(self):
         self._configuration.clear()
 

MDANSE/Src/MDANSE/Framework/Configurators/IConfigurator.py

@@ -112,9 +112,11 @@ def __init__(self, name, **kwargs):
 
         self._label = kwargs.get(
             "label",
-            self.__class__._label
-            if hasattr(self.__class__, "_label")
-            else " ".join(name.split("_")).strip(),
+            (
+                self.__class__._label
+                if hasattr(self.__class__, "_label")
+                else " ".join(name.split("_")).strip()
+            ),
         )
 
         self._widget = kwargs.get("widget", self.__class__)

MDANSE/Src/MDANSE/Framework/Configurators/MDMCTrajectoryConfigurator.py

@@ -0,0 +1,86 @@
+# **************************************************************************
+#
+# MDANSE: Molecular Dynamics Analysis for Neutron Scattering Experiments
+#
+# @file      Src/Framework/Configurators/MDMCTrajectoryConfigurator.py
+# @brief     A way to take in a trajectory from MDMC in a wrapper
+#
+# @homepage  https://www.isis.stfc.ac.uk/Pages/MDANSEproject.aspx
+# @license   GNU General Public License v3 or higher (see LICENSE)
+# @copyright Institut Laue Langevin 2013-now
+# @copyright ISIS Neutron and Muon Source, STFC, UKRI 2021-now
+# @authors   Scientific Computing Group at ILL (see AUTHORS)
+#
+# **************************************************************************
+
+import os
+
+from MDANSE.Framework.Configurators.IConfigurator import IConfigurator
+
+
+class MDMCTrajectoryConfigurator(IConfigurator):
+    """
+    This is a replacement for a trajectory stored in and HDF5 file.
+    It is intended to be a drop-in replacement for HDFTrajectoryConfigurator,
+    even though it is NOT file-based.
+    """
+
+    _default = None
+
+    def __init__(self, name, wildcard="All files|*", **kwargs):
+        """
+        Initializes the configurator object.
+
+        :param name: the name of the configurator as it will appear in the configuration.
+        :type name: str
+        :param wildcard: the wildcard used to filter the file. This will be used in MDANSE GUI when
+        browsing for the input file.
+        :type wildcard: str
+        """
+
+        # The base class constructor.
+        IConfigurator.__init__(self, name, **kwargs)
+
+        self._wildcard = wildcard
+
+    def configure(self, value):
+        """
+        Configure a HDF trajectory file.
+
+        :param value: an instance of the MdanseTrajectory class
+        :type value: MdanseTrajectory from MDMC
+        """
+
+        self["value"] = value
+        self["filename"] = "MDMC.temp"
+
+        self["instance"] = value
+
+        self["basename"] = "MDMC"
+
+        self["length"] = len(self["instance"])
+
+        self["md_time_step"] = 1.0
+
+        self["has_velocities"] = self["instance"].has_velocity
+
+    def get_information(self):
+        """
+        Returns some basic informations about the contents of the HDF trajectory file.
+
+        :return: the informations about the contents of the HDF trajectory file.
+        :rtype: str
+        """
+
+        info = ["MDMC trajectory used as input"]
+        info.append("Number of steps: %d\n" % self["length"])
+        info.append(
+            "Size of the chemical system: %d\n"
+            % self["instance"].chemical_system.number_of_atoms
+        )
+        if self["has_velocities"]:
+            info.append("The trajectory contains atomic velocities\n")
+        else:
+            info.append("The trajectory does not contain atomic velocities\n")
+
+        return "".join(info)

MDANSE/Src/MDANSE/Framework/Configurators/MockTrajectoryConfigurator.py

@@ -0,0 +1,89 @@
+# **************************************************************************
+#
+# MDANSE: Molecular Dynamics Analysis for Neutron Scattering Experiments
+#
+# @file      Src/Framework/Configurators/MDMCTrajectoryConfigurator.py
+# @brief     A way to take in a trajectory from MDMC in a wrapper
+#
+# @homepage  https://www.isis.stfc.ac.uk/Pages/MDANSEproject.aspx
+# @license   GNU General Public License v3 or higher (see LICENSE)
+# @copyright Institut Laue Langevin 2013-now
+# @copyright ISIS Neutron and Muon Source, STFC, UKRI 2021-now
+# @authors   Scientific Computing Group at ILL (see AUTHORS)
+#
+# **************************************************************************
+
+import os
+
+from MDANSE.Framework.Configurators.IConfigurator import IConfigurator
+from MDANSE.MolecularDynamics.MockTrajectory import MockTrajectory
+
+
+class MockTrajectoryConfigurator(IConfigurator):
+    """
+    This is a replacement for a trajectory stored in and HDF5 file.
+    It is intended to be a drop-in replacement for HDFTrajectoryConfigurator,
+    even though it is NOT based on an HDF5 file.
+    It can use a JSON file with MockTrajectory parameters to create
+    a trajectory entirely in the RAM.
+    """
+
+    _default = None
+
+    def __init__(self, name, wildcard="JSON file|*.json", **kwargs):
+        """
+        Initializes the configurator object.
+
+        :param name: the name of the configurator as it will appear in the configuration.
+        :type name: str
+        :param wildcard: the wildcard used to filter the file. This will be used in MDANSE GUI when
+        browsing for the input file.
+        :type wildcard: str
+        """
+
+        # The base class constructor.
+        IConfigurator.__init__(self, name, **kwargs)
+
+        self._wildcard = wildcard
+
+    def configure(self, value: str):
+        """
+        Configure a mock trajectory file.
+
+        :param value: a JSON file with a MockTrajectory definition
+        :type value: str
+        """
+
+        self["value"] = value
+        self["filename"] = "Mock"
+
+        self["instance"] = MockTrajectory.from_json(value)
+
+        self["basename"] = "Mock"
+
+        self["length"] = len(self["instance"])
+
+        self["md_time_step"] = self["instance"]._time_step
+
+        self["has_velocities"] = self["instance"].has_velocities
+
+    def get_information(self):
+        """
+        Returns some basic informations about the contents of the HDF trajectory file.
+
+        :return: the informations about the contents of the HDF trajectory file.
+        :rtype: str
+        """
+
+        info = ["Mock trajectory used as input"]
+        info.append("Number of steps: %d\n" % self["length"])
+        info.append(
+            "Size of the chemical system: %d\n"
+            % self["instance"].chemical_system.number_of_atoms
+        )
+        if self["has_velocities"]:
+            info.append("The trajectory contains atomic velocities\n")
+        else:
+            info.append("The trajectory does not contain atomic velocities\n")
+
+        return "".join(info)

MDANSE/Src/MDANSE/Framework/InputData/MockTrajectoryInputData.py

@@ -0,0 +1,80 @@
+# **************************************************************************
+#
+# MDANSE: Molecular Dynamics Analysis for Neutron Scattering Experiments
+#
+# @file      Src/Framework/InputData/HDFTrajectoryInputData.py
+# @brief     Implements module/class/test HDFTrajectoryInputData
+#
+# @homepage  https://mdanse.org
+# @license   GNU General Public License v3 or higher (see LICENSE)
+# @copyright Institut Laue Langevin 2013-now
+# @copyright ISIS Neutron and Muon Source, STFC, UKRI 2021-now
+# @authors   Scientific Computing Group at ILL (see AUTHORS)
+#
+# **************************************************************************
+
+from MDANSE.Framework.InputData.IInputData import InputDataError
+from MDANSE.Framework.InputData.InputFileData import InputFileData
+from MDANSE.MolecularDynamics.MockTrajectory import MockTrajectory
+
+
+class MockTrajectoryInputData(InputFileData):
+    """Imitates the HDFTrajectoryInputData,
+    but builds a MockTrajectory out of a JSON file instead.
+    """
+
+    extension = "json"
+
+    def load(self):
+        try:
+            traj = MockTrajectory.from_json(self._name)
+        except IOError as e:
+            raise InputDataError(str(e))
+        except ValueError as e:
+            raise InputDataError(str(e))
+
+        self._data = traj
+
+    def close(self):
+        self._data.close()
+
+    def info(self):
+        val = []
+
+        val.append("Path:")
+        val.append("%s\n" % self._name)
+        val.append("Number of steps:")
+        val.append("%s\n" % len(self._data))
+        mol_types = {}
+        val.append("\nMolecular types found:")
+        for ce in self._data.chemical_system.chemical_entities:
+            if ce.__class__.__name__ in mol_types:
+                mol_types[ce.__class__.__name__] += 1
+            else:
+                mol_types[ce.__class__.__name__] = 1
+
+        for k, v in mol_types.items():
+            val.append("\t- {:d} {}".format(v, k))
+
+        val = "\n".join(val)
+
+        return val
+
+    @property
+    def trajectory(self):
+        return self._data
+
+    @property
+    def chemical_system(self):
+        return self._data.chemical_system
+
+    @property
+    def hdf(self):
+        """There is no HDF5 file for a mock trajectory
+
+        Returns
+        -------
+        str
+            name of a nonexistent file
+        """
+        return self._data.file

MDANSE/Src/MDANSE/Framework/Jobs/IJob.py

@@ -117,12 +117,12 @@ def define_unique_name():
 
         return name
 
-    def __init__(self):
+    def __init__(self, trajectory_input="mdanse"):
         """
         The base class constructor.
         """
 
-        Configurable.__init__(self)
+        Configurable.__init__(self, trajectory_input=trajectory_input)
 
         self._outputData = OutputData()
 

MDANSE/Src/MDANSE/Framework/QVectors/SphericalLatticeQVectors.py

@@ -49,8 +49,7 @@ def _generate(self):
         )
 
         hklMax = (
-            np.ceil([qMax / np.sqrt(np.sum(v**2)) for v in self._inverseUnitCell.T])
-            + 1
+            np.ceil([qMax / np.sqrt(np.sum(v**2)) for v in self._inverseUnitCell.T]) + 1
         )
 
         vects = np.mgrid[

MDANSE/Src/MDANSE/IO/FortranFormat.py

@@ -61,7 +61,6 @@
 # which can be accessed as text or as a list of items.
 #
 class FortranLine:
-
     """Fortran-style record in formatted files
 
     FortranLine objects represent the content of one record of a
@@ -244,7 +243,6 @@ def _output(self):
 # little error checking.
 #
 class FortranFormat:
-
     """
     Parsed Fortran-style format string