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`petab_files_1to2` keeps a stale model file when converting into a non-empty output directory

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技术栈
python
领域
backend

调研方向

从 petab/v2/petab1to2.py 中的 _copy_file 入手，追踪 petab1to2 如何处理输出目录，包括现有的 experiments.tsv 情况。使用 issue 中的复现代码检查向非空目录重复转换的情况。选定的行为保持一致即为完成：用 ValueError 拒绝非空输出目录，或者覆盖现有模型文件，除非源文件和目标文件是同一个文件。

由索引模型根据 Issue 内容生成。

描述

petab_files_1to2 (and petab1to2 with output_dir) doesn't overwrite an existing model file in the output directory. The other tables are overwritten, so the result mixes the new tables with the old model, without any warning.

The cause is _copy_file in petab/v2/petab1to2.py (since #328):

try:
    if dest.samefile(src):
        return
except FileNotFoundError:
    shutil.copy(str(src), str(dest))

If dest exists and is a different file, samefile returns False and nothing is copied.

Reproducer (two v1 problems that differ only in the model's value of k1, converted into the same directory):

import tempfile
from pathlib import Path

import pandas as pd

from petab import v1
from petab.v1.models.sbml_model import SbmlModel
from petab.v2 import Problem
from petab.v2.petab1to2 import petab1to2


def write_v1(path: Path, k1: float) -> Path:
    return v1.Problem(
        model=SbmlModel.from_antimony(f"A = 1; B = 0; k1 = {k1}; A -> B; k1 * A"),
        condition_df=v1.get_condition_df(pd.DataFrame({"conditionId": ["c1"]})),
        observable_df=v1.get_observable_df(
            pd.DataFrame(
                {"observableId": ["obs_B"], "observableFormula": ["B"], "noiseFormula": [0.1]}
            )
        ),
        measurement_df=v1.get_measurement_df(
            pd.DataFrame(
                {"observableId": ["obs_B"], "simulationConditionId": ["c1"], "time": [1.0], "measurement": [0.5]}
            )
        ),
        parameter_df=v1.get_parameter_df(
            pd.DataFrame(
                {"parameterId": ["k1"], "parameterScale": ["lin"], "lowerBound": [1e-3],
                 "upperBound": [1e3], "nominalValue": [0.5], "estimate": [1]}
            )
        ),
    ).to_files_generic(path)


with tempfile.TemporaryDirectory() as tmp:
    tmp = Path(tmp)
    out = tmp / "v2"
    out.mkdir()
    petab1to2(write_v1(tmp / "v1_a", k1=0.5), out)
    petab1to2(write_v1(tmp / "v1_b", k1=0.7), out)
    problem = Problem.from_yaml(out / "problem.yaml")
    print(problem.model.sbml_model.getParameter("k1").getValue())
    # 0.5, expected 0.7

With reparametrize="priors" or "all" (#539), converting the same problem twice into the same directory reparametrizes twice: the model left from the first run already contains log10_<id>, so the second run adds log10_<id>_1.

The behaviour for a non-empty output directory is inconsistent: if the problem has a non-empty condition table, the second conversion fails, because an existing experiments.tsv raises a ValueError. Without one, it silently succeeds as above.

Possible fixes:

  1. Require the output directory to be empty or non-existent (and create it), and raise a ValueError otherwise. This makes the behaviour consistent, replaces the special case for experiments.tsv, and avoids leftover files from earlier runs. It rules out converting in place (output directory = input directory), which the samefile check seems meant to support, but converting in place overwrites the v1 files anyway.
  2. Only fix _copy_file, i.e., overwrite dest unless it's the same file as src. This is the minimal change, but leaves the inconsistency with experiments.tsv.

I'd go with 1.

🤖 Generated with Claude Code

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