updated readme

Reviewed-on: #6

README.md

@@ -26,9 +26,13 @@ time, msd = md.correlation.shifted_correlation(
 
 ## Installation
 
+=== DEPRECATED: 2025-08-19 === 
 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.
+=== DEPRECATED: 2025-08-19 === 
+
+The package requires the Python package [pygmx](https://github.com/mdevaluate/pygmx),
 
 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

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

src/mdevaluate/__init__.py

@@ -16,7 +16,7 @@ from . import reader
 from . import system
 from . import utils
 from . import extra
-from .logging_util import logger
+from .logging import logger
 
 
 def open(

src/mdevaluate/autosave.py

@@ -5,7 +5,7 @@ from typing import Optional, Callable, Iterable
 
 import numpy as np
 from .checksum import checksum
-from .logging_util import logger
+from .logging import logger
 
 autosave_directory: Optional[str] = None
 load_autosave_data = False

src/mdevaluate/checksum.py

@@ -1,14 +1,9 @@
 import functools
 import hashlib
-from .logging_util import logger
+from .logging import logger
 from types import ModuleType, FunctionType
 import inspect
 from typing import Iterable
-import ast
-import io
-import tokenize
-import re
-import textwrap
 
 import numpy as np
 
@@ -33,46 +28,19 @@ def version(version_nr: int, calls: Iterable = ()):
     return decorator
 
 
-def strip_comments(source: str) -> str:
-    """Removes docstrings, comments, and irrelevant whitespace from Python source code."""
-
-    # Step 1: Remove docstrings using AST
-    def remove_docstrings(node):
-        if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef, ast.ClassDef, ast.Module)):
-            if (doc := ast.get_docstring(node, clean=False)):
-                first_stmt = node.body[0]
-                if isinstance(first_stmt, ast.Expr) and isinstance(first_stmt.value, ast.Constant):
-                    node.body.pop(0)  # Remove the docstring entirely
-        for child in ast.iter_child_nodes(node):
-            remove_docstrings(child)
-
-    tree = ast.parse(textwrap.dedent(source))
-    remove_docstrings(tree)
-    code_without_docstrings = ast.unparse(tree)
-
-    # Step 2: Remove comments using tokenize
-    tokens = tokenize.generate_tokens(io.StringIO(code_without_docstrings).readline)
-    result = []
-    last_lineno = -1
-    last_col = 0
-
-    for toknum, tokval, (srow, scol), (erow, ecol), line in tokens:
-        if toknum == tokenize.COMMENT:
+def strip_comments(s: str):
+    """Strips comment lines and docstring from Python source string."""
+    o = ""
+    in_docstring = False
+    for l in s.split("\n"):
+        if l.strip().startswith(("#", '"', "'")) or in_docstring:
+            in_docstring = l.strip().startswith(('"""', "'''")) + in_docstring == 1
             continue
-        if srow > last_lineno:
-            last_col = 0
-        if scol > last_col:
-            result.append(" " * (scol - last_col))
-        result.append(tokval)
-        last_lineno, last_col = erow, ecol
-
-    code_no_comments = ''.join(result)
-
-    # Step 3: Remove empty lines (whitespace-only or truly blank)
-    return "\n".join([line for line in code_no_comments.splitlines() if line.strip() != ""])
+        o += l + "\n"
+    return o
 
 
-def checksum(*args, csum=None, _seen=None):
+def checksum(*args, csum=None):
     """
     Calculate a checksum of any object, by sha1 hash.
 
@@ -92,15 +60,7 @@ def checksum(*args, csum=None, _seen=None):
         csum = hashlib.sha1()
         csum.update(str(SALT).encode())
 
-    if _seen is None:
-        _seen = set()
-
     for arg in args:
-        obj_id = id(arg)
-        if obj_id in _seen:
-            continue
-        _seen.add(obj_id)
-
         if hasattr(arg, "__checksum__"):
             logger.debug("Checksum via __checksum__: %s", str(arg))
             csum.update(str(arg.__checksum__()).encode())
@@ -117,15 +77,15 @@ def checksum(*args, csum=None, _seen=None):
             for key in sorted(merged):  # deterministic ordering
                 v = merged[key]
                 if v is not arg:
-                    checksum(v, csum=csum, _seen=_seen)
+                    checksum(v, csum=csum)
         elif isinstance(arg, functools.partial):
             logger.debug("Checksum via partial for %s", str(arg))
-            checksum(arg.func, csum=csum, _seen=_seen)
+            checksum(arg.func, csum=csum)
             for x in arg.args:
-                checksum(x, csum=csum, _seen=_seen)
+                checksum(x, csum=csum)
             for k in sorted(arg.keywords.keys()):
                 csum.update(k.encode())
-                checksum(arg.keywords[k], csum=csum, _seen=_seen)
+                checksum(arg.keywords[k], csum=csum)
         elif isinstance(arg, np.ndarray):
             csum.update(arg.tobytes())
         else:

src/mdevaluate/coordinates.py

@@ -1,6 +1,6 @@
 from functools import partial, wraps
 from copy import copy
-from .logging_util import logger
+from .logging import logger
 from typing import Optional, Callable, List, Tuple
 
 import numpy as np

src/mdevaluate/correlation.py

@@ -431,9 +431,9 @@ def non_gaussian_parameter(
     trajectory: Coordinates = None,
     axis: str = "all",
 ) -> float:
-    r"""
+    """
     Calculate the non-Gaussian parameter.
-    .. math:
+    ..math:
       \alpha_2 (t) =
         \frac{3}{5}\frac{\langle r_i^4(t)\rangle}{\langle r_i^2(t)\rangle^2} - 1
     """

src/mdevaluate/pbc.py

@@ -7,7 +7,7 @@ from numpy.typing import ArrayLike, NDArray
 
 from itertools import product
 
-from .logging_util import logger
+from .logging import logger
 
 if TYPE_CHECKING:
     from mdevaluate.coordinates import CoordinateFrame
@@ -149,32 +149,21 @@ def nojump(frame: CoordinateFrame, usecache: bool = True) -> CoordinateFrame:
             i0 = 0
             delta = 0
 
-        delta = (
-            delta
-            + np.array(
-                np.vstack(
+        delta = (delta
+            + np.vstack(
                 [m[i0 : abstep + 1].sum(axis=0) for m in reader.nojump_matrices]
-                ).T
-            )
-            @ frame.box
-        )
+            ).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
 
 

src/mdevaluate/reader.py

@@ -19,13 +19,13 @@ import MDAnalysis
 from scipy import sparse
 
 from .checksum import checksum
-from .logging_util import logger
+from .logging import logger
 from . import atoms
 from .coordinates import Coordinates
 
 CSR_ATTRS = ("data", "indices", "indptr")
 NOJUMP_MAGIC = 2016
-Group_RE = re.compile(r"\[ ([-+\w]+) \]")
+Group_RE = re.compile("\[ ([-+\w]+) \]")
 
 
 class NojumpError(Exception):

src/mdevaluate/utils.py

@@ -14,7 +14,7 @@ from scipy.ndimage import uniform_filter1d
 from scipy.interpolate import interp1d
 from scipy.optimize import curve_fit
 
-from .logging_util import logger
+from .logging import logger
 from .functions import kww, kww_1e