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refactor_l
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e124506d10 | ||
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8169e76964 | ||
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00043637e9 | ||
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7585e598dc | ||
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6d8b86c1ef | ||
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a2a0ae8d7b |
@@ -26,13 +26,9 @@ time, msd = md.correlation.shifted_correlation(
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## Installation
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=== DEPRECATED: 2025-08-19 ===
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The package requires the Python package [pygmx](https://github.com/mdevaluate/pygmx),
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which handles reading of Gromacs file formats.
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Installation of pygmx is described in its own repository.
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=== DEPRECATED: 2025-08-19 ===
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The package requires the Python package [pygmx](https://github.com/mdevaluate/pygmx),
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The mdevaluate package itself is plain Python code and, hence, can be imported from its directory directly,
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or may be installed via setuptools to the local Python environment by running
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@@ -1,71 +0,0 @@
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#!/bin/bash
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CONDA_VERSION=2024.10
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PYTHON_VERSION=3.12
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if [ -z "$1" ]; then
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echo "No argument supplied, version to create expected"
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exit 1
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fi
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if [ ! -w "/nfsopt/mdevaluate"]; then
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echo "Please remount /nfsopt writable"
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exit 2
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fi
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MD_VERSION=$1
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# purge evtl. loaded modules
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module purge
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echo "Create mdevaluate Python environemnt using conda"
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echo "Using conda version: $CONDA_VERSION"
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echo "Using Python version: $PYTHON_VERSION"
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module load anaconda3/$CONDA_VERSION
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conda create -y --prefix /nfsopt/mdevaluate/mdevaluate-${MD_VERSION} \
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python=$PYTHON_VERSION
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module purge
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echo "Create modulefile for mdevaluate/$MD_VERSION"
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cat > /nfsopt/modulefiles/mdevaluate/$MD_VERSION <<EOF
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#%Module1.0#####################################################################
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##
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## dot modulefile
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##
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## modulefiles/dot. Generated from dot.in by configure.
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##
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module-whatis "Enables the mdevaluate Python environment."
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set version ${MD_VERSION}
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set module_path /nfsopt/mdevaluate/mdevaluate-\$version/bin
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prepend-path PATH \$module_path
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EOF
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echo "Loading mdevaluate environment and install packages"
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module load mdevaluate/${MD_VERSION}
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pip install jupyter \
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spyder \
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mdanalysis \
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pathos \
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pandas \
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dask \
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sqlalchemy \
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psycopg2-binary \
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trimesh \
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pyvista \
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seaborn \
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black \
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black[jupyter] \
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tables \
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pyedr \
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pytest
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pip install git+https://gitea.pkm.physik.tu-darmstadt.de/IPKM/mdevaluate.git
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pip install git+https://gitea.pkm.physik.tu-darmstadt.de/IPKM/python-store.git
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pip install git+https://gitea.pkm.physik.tu-darmstadt.de/IPKM/python-tudplot.git
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@@ -16,7 +16,7 @@ from . import reader
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from . import system
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from . import utils
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from . import extra
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from .logging import logger
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from .logging_util import logger
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def open(
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@@ -5,7 +5,7 @@ from typing import Optional, Callable, Iterable
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import numpy as np
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from .checksum import checksum
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from .logging import logger
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from .logging_util import logger
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autosave_directory: Optional[str] = None
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load_autosave_data = False
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@@ -1,9 +1,14 @@
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import functools
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import hashlib
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from .logging import logger
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from .logging_util import logger
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from types import ModuleType, FunctionType
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import inspect
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from typing import Iterable
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import ast
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import io
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import tokenize
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import re
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import textwrap
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import numpy as np
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@@ -28,19 +33,46 @@ def version(version_nr: int, calls: Iterable = ()):
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return decorator
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def strip_comments(s: str):
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"""Strips comment lines and docstring from Python source string."""
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o = ""
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in_docstring = False
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for l in s.split("\n"):
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if l.strip().startswith(("#", '"', "'")) or in_docstring:
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in_docstring = l.strip().startswith(('"""', "'''")) + in_docstring == 1
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def strip_comments(source: str) -> str:
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"""Removes docstrings, comments, and irrelevant whitespace from Python source code."""
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# Step 1: Remove docstrings using AST
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def remove_docstrings(node):
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if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef, ast.ClassDef, ast.Module)):
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if (doc := ast.get_docstring(node, clean=False)):
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first_stmt = node.body[0]
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if isinstance(first_stmt, ast.Expr) and isinstance(first_stmt.value, ast.Constant):
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node.body.pop(0) # Remove the docstring entirely
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for child in ast.iter_child_nodes(node):
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remove_docstrings(child)
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tree = ast.parse(textwrap.dedent(source))
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remove_docstrings(tree)
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code_without_docstrings = ast.unparse(tree)
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# Step 2: Remove comments using tokenize
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tokens = tokenize.generate_tokens(io.StringIO(code_without_docstrings).readline)
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result = []
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last_lineno = -1
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last_col = 0
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for toknum, tokval, (srow, scol), (erow, ecol), line in tokens:
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if toknum == tokenize.COMMENT:
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continue
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o += l + "\n"
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return o
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if srow > last_lineno:
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last_col = 0
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if scol > last_col:
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result.append(" " * (scol - last_col))
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result.append(tokval)
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last_lineno, last_col = erow, ecol
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code_no_comments = ''.join(result)
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# Step 3: Remove empty lines (whitespace-only or truly blank)
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return "\n".join([line for line in code_no_comments.splitlines() if line.strip() != ""])
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def checksum(*args, csum=None):
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def checksum(*args, csum=None, _seen=None):
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"""
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Calculate a checksum of any object, by sha1 hash.
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@@ -60,7 +92,15 @@ def checksum(*args, csum=None):
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csum = hashlib.sha1()
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csum.update(str(SALT).encode())
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if _seen is None:
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_seen = set()
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for arg in args:
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obj_id = id(arg)
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if obj_id in _seen:
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continue
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_seen.add(obj_id)
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if hasattr(arg, "__checksum__"):
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logger.debug("Checksum via __checksum__: %s", str(arg))
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csum.update(str(arg.__checksum__()).encode())
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@@ -77,15 +117,15 @@ def checksum(*args, csum=None):
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for key in sorted(merged): # deterministic ordering
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v = merged[key]
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if v is not arg:
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checksum(v, csum=csum)
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checksum(v, csum=csum, _seen=_seen)
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elif isinstance(arg, functools.partial):
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logger.debug("Checksum via partial for %s", str(arg))
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checksum(arg.func, csum=csum)
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checksum(arg.func, csum=csum, _seen=_seen)
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for x in arg.args:
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checksum(x, csum=csum)
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checksum(x, csum=csum, _seen=_seen)
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for k in sorted(arg.keywords.keys()):
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csum.update(k.encode())
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checksum(arg.keywords[k], csum=csum)
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checksum(arg.keywords[k], csum=csum, _seen=_seen)
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elif isinstance(arg, np.ndarray):
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csum.update(arg.tobytes())
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else:
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@@ -1,6 +1,6 @@
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from functools import partial, wraps
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from copy import copy
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from .logging import logger
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from .logging_util import logger
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from typing import Optional, Callable, List, Tuple
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import numpy as np
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@@ -431,9 +431,9 @@ def non_gaussian_parameter(
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trajectory: Coordinates = None,
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axis: str = "all",
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) -> float:
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"""
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r"""
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Calculate the non-Gaussian parameter.
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..math:
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.. math:
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\alpha_2 (t) =
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\frac{3}{5}\frac{\langle r_i^4(t)\rangle}{\langle r_i^2(t)\rangle^2} - 1
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"""
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@@ -7,7 +7,7 @@ from numpy.typing import ArrayLike, NDArray
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from itertools import product
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from .logging import logger
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from .logging_util import logger
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if TYPE_CHECKING:
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from mdevaluate.coordinates import CoordinateFrame
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@@ -149,21 +149,32 @@ def nojump(frame: CoordinateFrame, usecache: bool = True) -> CoordinateFrame:
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i0 = 0
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delta = 0
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delta = (delta
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+ np.vstack(
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[m[i0 : abstep + 1].sum(axis=0) for m in reader.nojump_matrices]
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).T)
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delta = (
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delta
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+ np.array(
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np.vstack(
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[m[i0 : abstep + 1].sum(axis=0) for m in reader.nojump_matrices]
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).T
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)
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@ frame.box
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)
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reader._nojump_cache[abstep] = delta
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while len(reader._nojump_cache) > NOJUMP_CACHESIZE:
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reader._nojump_cache.popitem(last=False)
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delta = delta[selection, :]
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else:
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delta = np.vstack(
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[m[: frame.step + 1, selection].sum(axis=0) for m in reader.nojump_matrices]
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delta = (
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np.array(
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np.vstack(
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[
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m[: frame.step + 1, selection].sum(axis=0)
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for m in reader.nojump_matrices
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]
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).T
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delta = delta[selection, :]
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delta = np.array(delta @ frame.box)
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)
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@ frame.box
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)
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return frame - delta
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@@ -19,13 +19,13 @@ import MDAnalysis
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from scipy import sparse
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from .checksum import checksum
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from .logging import logger
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from .logging_util import logger
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from . import atoms
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from .coordinates import Coordinates
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CSR_ATTRS = ("data", "indices", "indptr")
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NOJUMP_MAGIC = 2016
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Group_RE = re.compile("\[ ([-+\w]+) \]")
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Group_RE = re.compile(r"\[ ([-+\w]+) \]")
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class NojumpError(Exception):
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@@ -275,7 +275,7 @@ def load_nojump_matrices(reader: BaseReader):
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"Loaded Nojump matrices: {}".format(nojump_load_filename(reader))
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)
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else:
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logger.info("Invlaid Nojump Data: {}".format(nojump_load_filename(reader)))
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logger.info("Invalid Nojump Data: {}".format(nojump_load_filename(reader)))
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except KeyError:
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logger.info("Removing zip-File: %s", zipname)
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os.remove(nojump_load_filename(reader))
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@@ -14,7 +14,7 @@ from scipy.ndimage import uniform_filter1d
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from scipy.interpolate import interp1d
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from scipy.optimize import curve_fit
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from .logging import logger
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from .logging_util import logger
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from .functions import kww, kww_1e
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