Merge pull request #573 from ISISNeutronMuon/beta-release-2024

Beta release 2024

Author: MBartkowiakSTFC

CHANGELOG

@@ -1,3 +1,15 @@
+version 2.0.0b1 - 2024-10-15
+--------------------------
+* ADDED van Hove functions (self function and distinct function)
+* FIXED Eccentricity analysis to give correct results
+* ADDED Infrared analysis (only for molecules at the moment)
+* FIXED MolecularTrace analysis data axes to make data plottable
+* CHANGED the plotting interface to allow overplotting curves
+* ADDED instrument profiles for storing user parameters
+* ADDED logging in the code and a logger tab in the GUI
+* ADDED charge information to the stored trajectory data
+* ADDED support for H5MD trajectories
+
 version 2.0.0 - 2024-02-15
 --------------------------
 * CHANGED programming language to Python 3

Doc/conf.py

@@ -41,7 +41,7 @@
 # project = 'MDANSE'
 # copyright = '2015-2022, Eric Pellegrini'
 author = 'Eric Pellegrini'
-release = '2.0.0a1'
+release = '2.0.0b1'
 version = '2.0'
 
 # -- General configuration ---------------------------------------------------

Doc/index.rst

@@ -9,6 +9,7 @@ Welcome to MDANSE's documentation!
 .. note::
    This is the documentation of the MDANSE 2.0 release.
    The documentation, just like the code itself, is still under development.
+   MDANSE 2 has currently (October 2024) just reached the first beta release.
 
 **Useful links**: `MDANSE Project Website <https://www.isis.stfc.ac.uk/Pages/MDANSEproject.aspx>`_ | `MDANSE GitHub Page <https://github.com/ISISNeutronMuon/MDANSE>`_
 

Doc/pages/H_start.rst

@@ -57,6 +57,9 @@ Use `pip` to install the MDANSE package from the specified GitHub repository:
 
    pip install MDANSE
 
+The MDANSE package contains all the code needed to perform trajectory conversion
+and analysis using MDANSE, but none of the visualisation tools.
+
 Install MDANSE_GUI Package
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
@@ -66,14 +69,9 @@ Similarly, install the MDANSE_GUI package using `pip`:
 
    pip install MDANSE_GUI
 
-Run MDANSE
-~~~~~~~~~~
-
-You can now start using MDANSE by running the following command:
-
-.. code-block:: bash
-
-   mdanse_gui
+From now on, the `mdanse_gui` command will be available to start
+the graphical interface of MDANSE, which makes it easier to create
+valid inputs for different analysis types.
 
 Run MDANSE
 ~~~~~~~~~~
@@ -84,13 +82,20 @@ You can now start using MDANSE by running the following command:
 
    mdanse_gui
 
-This will launch the MDANSE Graphical User Interface (GUI), and you can start using MDANSE for your
-analysis.
-
-Note for Windows Users: On Windows, the command to run MDANSE may need to be:
-
-.. code-block:: bash
-
-   python3 mdanse_gui
-
-That's it! You have successfully installed MDANSE and are ready to use it for your data analysis needs.
+This will launch the MDANSE Graphical User Interface (GUI),
+and you can start using MDANSE for your analysis.
+
+MDANSE Scripts
+~~~~~~~~~~~~~~
+
+If you intend to run your analysis on a remote platform
+(e.g. a cluster), most likely you will have limited options
+of using the GUI there. However, you can still prepare
+a script using MDANSE_GUI on your own computer, save it
+and transfer it to the other computer to run the analysis
+there. You will need to change the file paths in the script,
+but all the other parameters should be transferable. One 
+of the design principles of MDANSE 2 is that the scripts
+should not depend on any settings stored locally on
+a specific computer, but should instead contain all the
+information needed to run a specific analysis type.

MDANSE/Doc/_static/mdanse_logo.png

@@ -70,7 +70,7 @@
 # The full version, including alpha/beta/rc tags.
 release = "1.0"
 
-html_logo = "_static/mdanse_logo.png"
+# html_logo = "_static/mdanse_logo.png"
 
 inheritance_graph_attrs = dict(size='""')
 

MDANSE/Doc/conf_api.py

@@ -66,7 +66,7 @@
 # The full version, including alpha/beta/rc tags.
 release = "1.0"
 
-html_logo = "_static/mdanse_logo.png"
+# html_logo = "_static/mdanse_logo.png"
 
 inheritance_graph_attrs = dict(size='""')
 

MDANSE/Doc/conf_help.py

@@ -140,15 +140,42 @@ def parse(self):
                     self["bonds"].append([at1, at2])
                 self["bonds"] = np.array(self["bonds"], dtype=np.int32)
 
-            if re.match("^\s*Atoms\s*$", line):
+            if re.match("^\s*Atoms\s*$", line.split("#")[0]):
+                if not "#" in line:
+                    num_of_columns = len(lines[i + 2].split())
+                    if num_of_columns <= 5:
+                        type_index = 1
+                        charge_index = None
+                        line_limit = 6
+                    else:
+                        type_index = 2
+                        charge_index = 3
+                        line_limit = 7
+                else:
+                    if "charge" in line.split("#")[-1]:
+                        type_index = 1
+                        charge_index = 2
+                        line_limit = 6
+                    elif "atomic" in line.split("#")[-1]:
+                        type_index = 1
+                        charge_index = None
+                        line_limit = 6
+                    elif "full" in line.split("#")[-1]:
+                        type_index = 2
+                        charge_index = 3
+                        line_limit = 7
+                    else:
+                        type_index = 2
+                        charge_index = 3
+                        line_limit = 7
                 if self["n_atoms"] is not None:
                     self["atom_types"] = self["n_atoms"] * [0]
                     self["charges"] = self["n_atoms"] * [0.0]
                     for j in range(self["n_atoms"]):
                         atoks = lines[i + j + 1].split()
-                        self["atom_types"][j] = int(atoks[2])
-                        if len(atoks) >= 7:
-                            self["charges"][j] = float(atoks[3])
+                        self["atom_types"][j] = int(atoks[type_index])
+                        if len(atoks) >= line_limit and charge_index is not None:
+                            self["charges"][j] = float(atoks[charge_index])
 
         if np.trace(np.abs(self["unit_cell"])) < 1e-8:
             # print(f"Concatenated: {np.concatenate([x_inputs, y_inputs, z_inputs])}")

MDANSE/Doc/mdanse_logo.png

@@ -14,6 +14,7 @@
 #    along with this program.  If not, see <https://www.gnu.org/licenses/>.
 #
 from abc import abstractmethod
+import traceback
 
 from MDANSE.Framework.AtomMapping import AtomLabel
 from .InputFileConfigurator import InputFileConfigurator
@@ -35,7 +36,7 @@ def configure(self, filepath: str) -> None:
         try:
             self.parse()
         except Exception as e:
-            self.error_status = "File parsing error"
+            self.error_status = f"File parsing error {e}: {traceback.format_exc()}"
 
     @abstractmethod
     def parse(self) -> None:

MDANSE/Src/MDANSE/Framework/Configurators/ConfigFileConfigurator.py

@@ -131,11 +131,13 @@ def configure(self, value):
         elements = []
         masses = []
         names = []
+        group_indices = []
         for i, v in enumerate(groups.values()):
             names.append("group_%d" % i)
             elements.append(v["elements"])
             indexes.append(v["indexes"])
             masses.append(v["masses"])
+            group_indices.append(i)
 
         atomSelectionConfig["indexes"] = indexes
         atomSelectionConfig["elements"] = elements
@@ -145,6 +147,7 @@ def configure(self, value):
         atomSelectionConfig["unique_names"] = sorted(set(atomSelectionConfig["names"]))
 
         self["level"] = value
+        self["group_indices"] = group_indices
 
     @staticmethod
     def find_parent(atom, level):

MDANSE/Src/MDANSE/Framework/Configurators/FileWithAtomDataConfigurator.py

@@ -14,6 +14,7 @@
 #    along with this program.  If not, see <https://www.gnu.org/licenses/>.
 #
 
+import numpy as np
 
 from MDANSE.Framework.Configurators.IConfigurator import IConfigurator
 from MDANSE.Framework.Projectors.IProjector import IProjector
@@ -62,13 +63,26 @@ def configure(self, value):
             self.error_status = f"the projector {mode} is unknown"
             return
         else:
+            if mode == "NullProjector":
+                self.error_status = "OK"
+                return
             try:
-                self["projector"].set_axis(axis)
+                vector = [float(x) for x in axis]
+            except ValueError:
+                self.error_status = f"Could not convert {axis} to numbers"
+                return
+            else:
+                if np.allclose(vector, 0):
+                    self.error_status = f"Vector of 0 length does not define projection"
+                    return
+            try:
+                self["projector"].set_axis(vector)
             except ProjectorError:
-                self.error_status = f"Axis {axis} is wrong for this projector"
+                self.error_status = f"Axis {vector} is wrong for this projector"
                 return
             else:
                 self["axis"] = self["projector"].axis
+
         self.error_status = "OK"
 
     def get_information(self):

MDANSE/Src/MDANSE/Framework/Configurators/GroupingLevelConfigurator.py

@@ -72,10 +72,14 @@ def configure(self, value):
                 return
 
             try:
-                generator.generate()
+                generator_success = generator.generate()
             except:
                 self.error_status = "Q Vector parameters were parsed correctly, but caused an error. Invalid values?"
                 return
+            else:
+                if not generator_success:
+                    self.error_status = "Q Vector parameters were parsed correctly, but caused an error. Invalid values?"
+                    return
 
             if not "q_vectors" in generator.configuration:
                 self.error_status = "Wrong inputs for q-vector generation. At the moment there are no valid Q points."

MDANSE/Src/MDANSE/Framework/Configurators/ProjectionConfigurator.py

@@ -159,8 +159,18 @@ def parse_first_step(self, aliases, config):
             elif line.startswith("ITEM: ATOMS"):
                 keywords = line.split()[2:]
 
-                self._id = keywords.index("id")
-                self._type = keywords.index("type")
+                if "id" in keywords:
+                    self._id = keywords.index("id")
+                else:
+                    self._id = None
+                if "type" in keywords:
+                    self._type = keywords.index("type")
+                else:
+                    self._type = None
+                if "element" in keywords:
+                    self._element = keywords.index("element")
+                else:
+                    self._element = None
                 try:
                     self._charge = keywords.index("q")
                 except ValueError:
@@ -194,12 +204,28 @@ def parse_first_step(self, aliases, config):
                 self._itemsPosition["ATOMS"] = [comp + 1, comp + self._nAtoms + 1]
                 for i in range(self._nAtoms):
                     temp = self._file.readline().split()
-                    idx = int(temp[self._id]) - 1
-                    ty = int(temp[self._type]) - 1
+                    if self._id is not None:
+                        idx = int(temp[self._id]) - 1
+                    else:
+                        idx = int(i)
+                    if self._type is not None:
+                        ty = int(temp[self._type]) - 1
+                    else:
+                        try:
+                            ty = int(config["atom_types"][i]) - 1
+                        except IndexError:
+                            LOG.error(
+                                f"Failed to find index [{i}] in list of len {len(config['atom_types'])}"
+                            )
                     label = str(config["elements"][ty][0])
                     mass = str(config["elements"][ty][1])
                     name = "{:s}_{:d}".format(str(config["elements"][ty][0]), idx)
-                    self._rankToName[int(temp[0]) - 1] = name
+                    try:
+                        temp_index = int(temp[0])
+                    except ValueError:
+                        self._rankToName[i] = name
+                    else:
+                        self._rankToName[temp_index - 1] = name
                     g.add_node(idx, label=label, mass=mass, atomName=name)
 
                 if config["n_bonds"] is not None:
@@ -335,7 +361,12 @@ def run_step(self, index):
             range(self._itemsPosition["ATOMS"][0], self._itemsPosition["ATOMS"][1])
         ):
             temp = self._file.readline().split()
-            idx = self._nameToIndex[self._rankToName[int(temp[0]) - 1]]
+            try:
+                temp_index = int(temp[0])
+            except ValueError:
+                idx = i
+            else:
+                idx = self._nameToIndex[self._rankToName[temp_index - 1]]
             coords[idx, :] = np.array(
                 [temp[self._x], temp[self._y], temp[self._z]], dtype=np.float64
             )

MDANSE/Src/MDANSE/Framework/Configurators/QVectorsConfigurator.py

@@ -107,7 +107,7 @@ def put_into_dict(name, obj):
             try:
                 string = obj[:][0].decode()
             except:
-                LOG.warning(f"Decode failed for {name}: {obj}")
+                LOG.debug(f"Decode failed for {name}: {obj}")
             else:
                 try:
                     meta_dict[name] = json_decoder.decode(string)

MDANSE/Src/MDANSE/Framework/Converters/LAMMPS.py

@@ -97,6 +97,26 @@ def initialize(self):
 
         self._ase_atoms = Atoms()
 
+        trajectory = self.configuration["trajectory"]["instance"]
+
+        frame_range = range(
+            self.configuration["frames"]["first"],
+            self.configuration["frames"]["last"] + 1,
+            self.configuration["frames"]["step"],
+        )
+
+        try:
+            unit_cells = [
+                trajectory.unit_cell(frame)._unit_cell for frame in frame_range
+            ]
+        except:
+            raise ValueError(
+                "Unit cell needs to be defined for the AverageStructure analysis. "
+                "You can add a unit cell using TrajectoryEditor."
+            )
+        else:
+            self._unit_cells = unit_cells
+
     def run_step(self, index):
         """
         Runs a single step of the job.
@@ -135,7 +155,10 @@ def combine(self, index, x):
         # The symbol of the atom.
         element = self.configuration["atom_selection"]["names"][index]
 
-        the_atom = Atom(element, x)
+        try:
+            the_atom = Atom(element, x)
+        except KeyError:
+            the_atom = Atom(str(element).strip("0123456789"), x)
 
         self._ase_atoms.append(the_atom)
 
@@ -152,17 +175,7 @@ def finalize(self):
             self.configuration["frames"]["step"],
         )
 
-        try:
-            unit_cells = [
-                trajectory.unit_cell(frame)._unit_cell for frame in frame_range
-            ]
-        except:
-            raise ValueError(
-                "Unit cell needs to be defined for the AverageStructure analysis. "
-                "You can add a unit cell using TrajectoryEditor."
-            )
-
-        average_unit_cell = np.mean(unit_cells, axis=0) * self._conversion_factor
+        average_unit_cell = np.mean(self._unit_cells, axis=0) * self._conversion_factor
 
         self._ase_atoms.set_cell(average_unit_cell)
 

MDANSE/Src/MDANSE/Framework/InputData/HDFTrajectoryInputData.py

@@ -137,6 +137,7 @@ def run_step(self, index):
         conf = self.configuration["trajectory"]["instance"].configuration(frame_index)
 
         box_coords = conf.to_box_coordinates()
+        box_coords = box_coords - np.floor(box_coords)
 
         axis_index = self.configuration["axis"]["index"]
         axis = conf.unit_cell.direct[axis_index, :]
@@ -146,7 +147,7 @@ def run_step(self, index):
 
         for k, v in self._indexes_per_element.items():
             h = np.histogram(
-                box_coords[v, axis_index], bins=self._n_bins, range=[-0.5, 0.5]
+                box_coords[v, axis_index], bins=self._n_bins, range=[0.0, 1.0]
             )
             dp_per_frame[k] = h[0]