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New versions, new Dockerimage
Including curve-curator by default now
New release
New version
Forgot to change version
New version: adapted hyperparameter files, faster GradientBoosting
New version v1.2.2
v1.2.3: bug fix cross study prediction SMRF
New version: v1.2.4
New version with various fixes: DIPK fix for batch size 1 MOLIR/SuperFELTR: removed VarianceThreshold selection. Now always selecting min(1000, n_features) most variable features from the dataset MOLIR/SuperFELTR fix for if self.model is None MOLIR/SuperFELTR: moved duplicated code to utils MultiOmicsNN: removed unused self.methylation_features test restructuring: now baseline tests, single drug model tests, neural network tests for non-single drug models Also adapted tests for the bugs updated requirements Force NaiveMeanEffectsPredictor if not already selected as baseline
New version: 1.2.7
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Pull Request Overview
This PR replaces the legacy top-level scripts with proper CLI entrypoints, reorganizes report generation into a module for better integration, updates tests to cover both experiment and report commands, and refreshes documentation to use the new drevalpy and drevalpy-report commands.
- Define
drevalpyanddrevalpy-reportentrypoints inpyproject.tomland removerun_suite.py/create_report.pyat the repo root. - Refactor report generation into
drevalpy.visualization.create_reportwith modular functions and streamline pipeline decorators in visualization code. - Replace old end-to-end test with a unified
tests/test_main.pyand update all docs to reference the new CLI.
Reviewed Changes
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Show a summary per file
| File | Description |
|---|---|
| pyproject.toml | Added [tool.poetry.scripts] for drevalpy and drevalpy-report. |
| run_suite.py, create_report.py | Removed legacy scripts in project root. |
| drevalpy/cli.py | New CLI entrypoint for drevalpy. |
| drevalpy/visualization/create_report.py | New module organizing report generation logic into functions. |
| tests/test_run_suite.py | Deleted obsolete test. |
| tests/test_main.py | New integrated test covering both main pipeline and report. |
| docs/ | Updated usage examples to use drevalpy/drevalpy-report. |
| drevalpy/visualization/*.py | Removed @pipeline_function decorators from plotting classes. |
Comments suppressed due to low confidence (2)
drevalpy/models/drp_model.py:107
- The
@pipeline_functiondecorator is applied here butpipeline_functionis not imported in this file. Please addfrom drevalpy.pipeline_function import pipeline_function(or the correct relative import) at the top.
@pipeline_function
drevalpy/datasets/dataset.py:46
- The
@pipeline_functiondecorator is used here butpipeline_functionis not imported. Please addfrom drevalpy.pipeline_function import pipeline_function(or the correct relative import) at the top of this module.
@pipeline_function
docs/usage.rst
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| * ``--measure MEASURE``: The name of the measure to use, default 'LN_IC50'. If using one of the available datasets (see ``--dataset_name``), this is restricted to one of ['LN_IC50', 'EC50', 'IC50', 'pEC50', 'AUC', 'response']. This corresponds to the names of the columns that contain theses measures in the provided input dataset. If providing a custom dataset, this may differ. If the option ``--curve_curator`` is set, the prefix '_curvecurator' is automatically appended, e.g. 'LN_IC50_curvecurator', to allow using the refit measures instead of the ones originally published for the available datasets, allowing for better dataset comparability (refit measures are already provided in the available datasets or computed as part of the fitting procedure when providing custom raw viability datasets, see ``--curve_curator`` for details). | ||
| * ``--curve_curator``: Default true. If set, the measure is appended with '_curvecurator'. If a custom dataset_name was provided, this will invoke the fitting procedure of raw viability data, which is expected to exist at ``<path_data>/<dataset_name>/<dataset_name>_raw.csv``. The fitted dataset will be stored in the same folder, in a file called ``<dataset_name>.csv``. Also check the :ref:`usage:Custom Datasets` section. | ||
| * ``--curve_curator_cores CORES``: Number of cores to use for CurveCurator fitting. Only used when ``--curve_curator`` is set. | ||
| * ``--curve_curator``: If set, the measure is appended with '_curvecurator'. If a custom dataset_name was provided, this will invoke the fitting procedure of raw viability data, which is expected to exist at ``<path_data>/<dataset_name>/<dataset_name>_raw.csv``. The fitted dataset will be stored in the same folder, in a file called ``<dataset_name>.csv``. Also check the :ref:`usage:Custom Datasets` section. Default is False. |
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The default is true. For the pipeline I changed this parameter to --no-refitting, default False because I thought it's weird to have true default. But for the package, I just left it this way. We can also change it to --no-refitting.
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done! do I need to change soemthing somwhere else?
| python run_suite.py [-h] [--run_id RUN_ID] [--path_data PATH_DATA] [--models MODELS [MODELS ...]] [--baselines BASELINES [BASELINES ...]] [--test_mode TEST_MODE [TEST_MODE ...]] | ||
| drevalpy [-h] [--run_id RUN_ID] [--path_data PATH_DATA] [--models MODELS [MODELS ...]] [--baselines BASELINES [BASELINES ...]] [--test_mode TEST_MODE [TEST_MODE ...]] | ||
| [--randomization_mode RANDOMIZATION_MODE [RANDOMIZATION_MODE ...]] [--randomization_type RANDOMIZATION_TYPE] [--n_trials_robustness N_TRIALS_ROBUSTNESS] [--dataset_name DATASET_NAME] | ||
| [--cross_study_datasets CROSS_STUDY_DATASETS [CROSS_STUDY_DATASETS ...]] [--path_out PATH_OUT] [--measure MEASURE] [--curve_curator] [--curve_curator_cores CORES] [--overwrite] [--optim_metric OPTIM_METRIC] [--n_cv_splits N_CV_SPLITS] |
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da steht noch curve_curator
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command line interface that is available after installing drevalpy.
to run the drug response experiment:
drevalpy --helpto create the report:
drevalpy-report --helpalso refactored create_report into functions for more harmony with the nf-core pipeline <3 and to make it available via
TODO:
closes #242
and sneaking in:
closes #241