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Reviewed-on: #6

README.md

@@ -26,9 +26,6 @@ time, msd = md.correlation.shifted_correlation(
 
 ## Installation
 
-The package requires the Python package [pygmx](https://github.com/mdevaluate/pygmx),
-which handles reading of Gromacs file formats.
-Installation of pygmx is described in its own repository.
 
 The mdevaluate package itself is plain Python code and, hence, can be imported from its directory directly, 
 or may be installed via setuptools to the local Python environment by running
@@ -36,6 +33,14 @@ or may be installed via setuptools to the local Python environment by running
 	python setup.py install
 
 
+When you are using `uv` you can install it with:
+
+    uv venv some_folder
+    source some_folder/bin/activate
+    uv pip install git+https://gitea.pkm.physik.tu-darmstadt.de/IPKM/mdevaluate.git@2026.09
+
+Note: you can append a tag to get a specific release.
+
 ## Running the tests
 
 Mdevaluate includes a test suite that can be used to check if the installation was succesful.

create_mdevaluate_module.sh

@@ -0,0 +1,71 @@
+#!/bin/bash
+
+CONDA_VERSION=2024.10
+PYTHON_VERSION=3.12
+
+if [ -z "$1" ]; then
+    echo "No argument supplied, version to create expected"
+    exit 1
+fi
+
+
+if [ ! -w "/nfsopt/mdevaluate"]; then
+	echo "Please remount /nfsopt writable"
+	exit 2
+fi
+
+MD_VERSION=$1
+
+# purge evtl. loaded modules
+module purge
+
+
+echo "Create mdevaluate Python environemnt using conda"
+echo "Using conda version: $CONDA_VERSION"
+echo "Using Python version: $PYTHON_VERSION"
+
+module load anaconda3/$CONDA_VERSION
+conda create -y --prefix /nfsopt/mdevaluate/mdevaluate-${MD_VERSION} \
+             python=$PYTHON_VERSION
+module purge
+
+echo "Create modulefile for mdevaluate/$MD_VERSION"
+cat > /nfsopt/modulefiles/mdevaluate/$MD_VERSION <<EOF
+#%Module1.0#####################################################################
+##
+## dot modulefile
+##
+## modulefiles/dot.  Generated from dot.in by configure.
+##
+
+module-whatis	"Enables the mdevaluate Python environment."
+
+set version	${MD_VERSION}
+set module_path /nfsopt/mdevaluate/mdevaluate-\$version/bin
+
+prepend-path PATH \$module_path
+
+EOF
+
+echo "Loading mdevaluate environment and install packages"
+module load mdevaluate/${MD_VERSION}
+pip install jupyter \
+spyder \
+mdanalysis \
+pathos \
+pandas \
+dask \
+sqlalchemy \
+psycopg2-binary \
+trimesh \
+pyvista \
+seaborn \
+black \
+black[jupyter] \
+tables \
+pyedr \
+pytest
+
+pip install git+https://gitea.pkm.physik.tu-darmstadt.de/IPKM/mdevaluate.git
+pip install git+https://gitea.pkm.physik.tu-darmstadt.de/IPKM/python-store.git
+pip install git+https://gitea.pkm.physik.tu-darmstadt.de/IPKM/python-tudplot.git

pyproject.toml

@@ -4,12 +4,15 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "mdevaluate"
-version = "24.02"
+version = "2026.09"
+requires-python = ">=3.10"
 dependencies = [
     "mdanalysis",
     "pandas",
     "dask",
     "pathos",
     "tables",
-    "pyedr"
+    "pyedr",
+    "numpy<2.3",
+    "scipy<1.17",
 ]

src/mdevaluate/distribution.py

@@ -182,10 +182,10 @@ def tetrahedral_order(
     )
 
     # Connection vectors
-    neighbors_1 -= atoms
-    neighbors_2 -= atoms
-    neighbors_3 -= atoms
-    neighbors_4 -= atoms
+    neighbors_1 = pbc_diff(neighbors_1, atoms, box=atoms.box)
+    neighbors_2 = pbc_diff(neighbors_2, atoms, box=atoms.box)
+    neighbors_3 = pbc_diff(neighbors_3, atoms, box=atoms.box)
+    neighbors_4 = pbc_diff(neighbors_4, atoms, box=atoms.box)
 
     # Normed Connection vectors
     neighbors_1 /= np.linalg.norm(neighbors_1, axis=-1).reshape(-1, 1)

src/mdevaluate/pbc.py

@@ -149,32 +149,21 @@ def nojump(frame: CoordinateFrame, usecache: bool = True) -> CoordinateFrame:
             i0 = 0
             delta = 0
 
-        delta = (
-            delta
-            + np.array(
-                np.vstack(
-                    [m[i0 : abstep + 1].sum(axis=0) for m in reader.nojump_matrices]
-                ).T
-            )
-            @ frame.box
-        )
+        delta = (delta
+            + np.vstack(
+                [m[i0 : abstep + 1].sum(axis=0) for m in reader.nojump_matrices]
+            ).T)
 
         reader._nojump_cache[abstep] = delta
         while len(reader._nojump_cache) > NOJUMP_CACHESIZE:
             reader._nojump_cache.popitem(last=False)
-        delta = delta[selection, :]
     else:
-        delta = (
-            np.array(
-                np.vstack(
-                    [
-                        m[: frame.step + 1, selection].sum(axis=0)
-                        for m in reader.nojump_matrices
-                    ]
+        delta = np.vstack(
+                [m[: frame.step + 1, selection].sum(axis=0) for m in reader.nojump_matrices]
                 ).T
-            )
-            @ frame.box
-        )
+    
+    delta = delta[selection, :]
+    delta = np.array(delta @ frame.box)
     return frame - delta