{"receipt_id":"agent1-1","seq":1,"branch_id":"agent1","kind":"command","cmd":"git ls-files -z","path":null,"exit_code":0,"stdout_tail":".coveragerc\u0000.editorconfig\u0000.github/CODEOWNERS\u0000.github/ISSUE_TEMPLATE/bug_report.md\u0000.github/ISSUE_TEMPLATE/feature_request.md\u0000.github/ISSUE_TEMPLATE/question.md\u0000.github/PULL_REQUEST_TEMPLATE/new_transformer.md\u0000.github/workflows/integration.yml\u0000.github/workflows/lint.yml\u0000.github/workflows/minimum.yml\u0000.github/workflows/performance.yml\u0000.github/workflows/readme.yml\u0000.github/workflows/unit.yml\u0000.gitignore\u0000AUTHORS.rst\u0000CONTRIBUTING.rst\u0000DEVELOPMENT.rst\u0000HISTORY.md\u0000INSTALL.md\u0000LICENSE\u0000MANIFEST.in\u0000Makefile\u0000README.md\u0000RELEASE.md\u0000rdt/__init__.py\u0000rdt/errors.py\u0000rdt/hyper_transformer.py\u0000rdt/performance/__init__.py\u0000rdt/performance/datasets/__init__.py\u0000rdt/performance/datasets/base.py\u0000rdt/performance/datasets/boolean.py\u0000rdt/performance/datasets/categorical.py\u0000rdt/performance/datasets/datetime.py\u0000rdt/performance/datasets/numerical.py\u0000rdt/performance/datasets/pii.py\u0000rdt/performance/datasets/text.py\u0000rdt/performance/datasets/utils.py\u0000rdt/performance/performance.py\u0000rdt/performance/profiling.py\u0000rdt/transformers/__init__.py\u0000rdt/transformers/addons/README.md\u0000rdt/transformers/addons/addons_setup.py\u0000rdt/transformers/addons/identity/__init__.py\u0000rdt/transformers/addons/identity/config.json\u0000rdt/transformers/addons/identity/identity.py\u0000rdt/transformers/base.py\u0000rdt/transformers/boolean.py\u0000rdt/transformers/categorical.py\u0000rdt/transformers/datetime.py\u0000rdt/transformers/null.py\u0000rdt/transformers/numerical.py\u0000rdt/transformers/pii/__init__.py\u0000rdt/transformers/pii/anonymizer.py\u0000rdt/transformers/pii/utils.py\u0000rdt/transformers/text.py\u0000rdt/transformers/utils.py\u0000setup.cfg\u0000setup.py\u0000tasks.py\u0000tests/__init__.py\u0000tests/code_style.py\u0000tests/contributing.py\u0000tests/datasets/tests/test_boolean.py\u0000tests/datasets/tests/test_categorical.py\u0000tests/datasets/tests/test_datetime.py\u0000tests/datasets/tests/test_numerical.py\u0000tests/datasets/tests/test_utils.py\u0000tests/integration/__init__.py\u0000tests/integration/test_hyper_transformer.py\u0000tests/integration/test_transformers.py\u0000tests/integration/transformers/__init__.py\u0000tests/integration/transformers/pii/__init__.py\u0000tests/integration/transformers/pii/test_anonymizer.py\u0000tests/integration/transformers/test_base.py\u0000tests/integration/transformers/test_boolean.py\u0000tests/integration/transformers/test_categorical.py\u0000tests/integration/transformers/test_datetime.py\u0000tests/integration/transformers/test_numerical.py\u0000tests/integration/transformers/test_text.py\u0000tests/performance/README.md\u0000tests/performance/__init__.py\u0000tests/performance/test_performance.py\u0000tests/performance/tests/__init__.py\u0000tests/performance/tests/test_profiling.py\u0000tests/unit/__init__.py\u0000tests/unit/test___init__.py\u0000tests/unit/test_hyper_transformer.py\u0000tests/unit/transformers/__init__.py\u0000tests/unit/transformers/addons/__init__.py\u0000tests/unit/transformers/addons/identity/__init__.py\u0000tests/unit/transformers/addons/identity/test_identity.py\u0000tests/unit/transformers/pii/__init__.py\u0000tests/unit/transformers/pii/test_anonymizer.py\u0000tests/unit/transformers/pii/test_utils.py\u0000tests/unit/transformers/test___init__.py\u0000tests/unit/transformers/test_base.py\u0000tests/unit/transformers/test_boolean.py\u0000tests/unit/transformers/test_categorical.py\u0000tests/unit/transformers/test_datetime.py\u0000tests/unit/transformers/test_null.py\u0000tests/unit/transformers/test_numerical.py\u0000tests/unit/transformers/test_text.py\u0000tests/unit/transformers/test_utils.py\u0000tox.ini\u0000","stderr_tail":"","stdout_sha256":"35b2de6e184f79c23900411b0cac791443525017d9ca2e4c742149e37192c64d","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-1.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:25:29.702199Z","duration_s":0.003948,"timed_out":false,"image_before":"3d44e597-10c5-425f-8f74-424036cfe4c4","image_after":"7d63fa36-eb93-4214-a936-06a58cafc2a2","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-2","seq":2,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-b565d260bd994228b4144e0a8b63015e/bin/busybox sh -c 'mkdir -p /RDT/rdt/transformers && cp /opt/receipts-b565d260bd994228b4144e0a8b63015e/incoming/f94a3fa66533d65eecee485fc3958acadc4e3e7a46a709aa0a35d7b56ba86848 /RDT/rdt/transformers/numerical.py'","path":"rdt/transformers/numerical.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"f94a3fa66533d65eecee485fc3958acadc4e3e7a46a709aa0a35d7b56ba86848","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-2.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:26:14.313338Z","duration_s":0.004981,"timed_out":false,"image_before":"7d63fa36-eb93-4214-a936-06a58cafc2a2","image_after":"a0738be3-1faa-4030-9d70-2a11e1bb10e0","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-3","seq":3,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-07a2163b4b9d46cda795b09a1e5452c0/bin/busybox sh -c 'mkdir -p /RDT/rdt/transformers && cp /opt/receipts-07a2163b4b9d46cda795b09a1e5452c0/incoming/619e3805cfd3c2880e74d6b51d0e66a742ade801dc254efd72e2c07c7d1fd949 /RDT/rdt/transformers/numerical.py'","path":"rdt/transformers/numerical.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"619e3805cfd3c2880e74d6b51d0e66a742ade801dc254efd72e2c07c7d1fd949","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-3.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:26:18.337878Z","duration_s":0.005236,"timed_out":false,"image_before":"a0738be3-1faa-4030-9d70-2a11e1bb10e0","image_after":"c0631935-2366-46fe-849b-b4151f3e6737","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-4","seq":4,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-9c3c0b883cb64c30b9c703f0d9a18fa3/bin/busybox sh -c 'mkdir -p /RDT/rdt/transformers && cp /opt/receipts-9c3c0b883cb64c30b9c703f0d9a18fa3/incoming/9111cef8407d99e77ca2ea21da25fc28d3e28f9a9817fbc9c947eec678d49890 /RDT/rdt/transformers/numerical.py'","path":"rdt/transformers/numerical.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"9111cef8407d99e77ca2ea21da25fc28d3e28f9a9817fbc9c947eec678d49890","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-4.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:26:24.880763Z","duration_s":0.005169,"timed_out":false,"image_before":"c0631935-2366-46fe-849b-b4151f3e6737","image_after":"bf67eaaf-3dcf-4fca-92c3-b3d759a0e02d","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-5","seq":5,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-bc7ccbe363d149a9ac97cc6c164193c4/bin/busybox sh -c 'mkdir -p /RDT/rdt/transformers && cp /opt/receipts-bc7ccbe363d149a9ac97cc6c164193c4/incoming/13ded215a560b2ba111c761d38bf5504597713b2003a04503c7941552bec43fa /RDT/rdt/transformers/numerical.py'","path":"rdt/transformers/numerical.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"13ded215a560b2ba111c761d38bf5504597713b2003a04503c7941552bec43fa","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-5.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:26:28.980467Z","duration_s":0.004671,"timed_out":false,"image_before":"bf67eaaf-3dcf-4fca-92c3-b3d759a0e02d","image_after":"0b03139c-caef-4197-a7fb-2d76888bbf71","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-6","seq":6,"branch_id":"agent1","kind":"command","cmd":"grep -n \"noqa\" rdt/transformers/numerical.py","path":null,"exit_code":1,"stdout_tail":"","stderr_tail":"","stdout_sha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-6.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:26:37.673878Z","duration_s":0.003362,"timed_out":false,"image_before":"0b03139c-caef-4197-a7fb-2d76888bbf71","image_after":"89b3fdab-4676-4b37-9183-a8cb2ec0e5a0","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-7","seq":7,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__fit -xvs 2>&1 | head -100","path":null,"exit_code":0,"stdout_tail":"============================= test session starts ==============================\nplatform linux -- Python 3.10.19, pytest-9.0.2, pluggy-1.6.0 -- /usr/local/bin/python\ncachedir: .pytest_cache\nrootdir: /RDT\nconfigfile: setup.cfg\nplugins: anyio-4.12.1, Faker-40.4.0, cov-7.0.0\ncollecting ... collected 1 item\n\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__fit PASSED\n\n=============================== warnings summary ===============================\n../usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428\n  /usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428: PytestConfigWarning: Unknown config option: collect_ignore\n  \n    self._warn_or_fail_if_strict(f\"Unknown config option: {key}\\n\")\n\n../usr/local/lib/python3.10/site-packages/copulas/__init__.py:18\n  /usr/local/lib/python3.10/site-packages/copulas/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n    from pkg_resources import iter_entry_points\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n======================== 1 passed, 2 warnings in 1.55s =========================\n","stderr_tail":"","stdout_sha256":"4ba4404c480b2c9a674b8a5e7b774a9fd6dde7219edb375c87256c4a75979a68","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-7.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:26:39.618612Z","duration_s":2.369305,"timed_out":false,"image_before":"89b3fdab-4676-4b37-9183-a8cb2ec0e5a0","image_after":"c286df50-7fa0-484a-800c-bcf77fcdd2f4","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-8","seq":8,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer -xvs 2>&1 | head -150","path":null,"exit_code":0,"stdout_tail":"ing_value_replacement PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__get_current_random_seed_random_states_is_none PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__reverse_transform PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__reverse_transform_helper PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__reverse_transform_missing_value_replacement_missing_value_replacement_from_col PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__reverse_transform_missing_value_replacement_missing_value_replacement_random PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform FAILED\n\n=================================== FAILURES ===================================\n__________________ TestClusterBasedNormalizer.test__transform __________________\n\nself = <tests.unit.transformers.test_numerical.TestClusterBasedNormalizer testMethod=test__transform>\n\n    def test__transform(self):\n        \"\"\"Test ``_transform``.\n    \n        Validate that the method produces the appropriate output when given a pandas Series.\n    \n        Setup:\n            - create an instance of the ``ClusterBasedNormalizer`` where:\n                - ``_bgm_transformer`` is mocked with the appropriate ``means_``, ``covariances_``\n                and ``predict_proba.return_value``.\n                - ``valid_component_indicator`` is set to ``np.array([True, True, False])``.\n    \n        Input:\n            - a pandas Series.\n    \n        Ouput:\n            - a numpy array with the transformed data.\n        \"\"\"\n        # Setup\n        random_state = np.random.get_state()\n        np.random.set_state(np.random.RandomState(10).get_state())\n        transformer = ClusterBasedNormalizer(max_clusters=3)\n        transformer._bgm_transformer = Mock()\n    \n        means = np.array([\n            [0.90138867],\n            [0.09169366],\n            [0.499]\n        ])\n        transformer._bgm_transformer.means_ = means\n    \n        covariances = np.array([\n            [[0.09024532]],\n            [[0.08587948]],\n            [[0.27487667]]\n        ])\n        transformer._bgm_transformer.covariances_ = covariances\n    \n        probabilities = np.array([\n            [0.01519528, 0.98480472, 0.],\n            [0.01659093, 0.98340907, 0.],\n            [0.012744, 0.987256, 0.],\n            [0.012744, 0.987256, 0.],\n            [0.01391614, 0.98608386, 0.],\n            [0.99220664, 0.00779336, 0.],\n            [0.99059634, 0.00940366, 0.],\n            [0.9941256, 0.0058744, 0.],\n            [0.99465502, 0.00534498, 0.],\n            [0.99059634, 0.00940366, 0.]\n        ])\n        transformer._bgm_transformer.predict_proba.return_value = probabilities\n    \n        transformer.valid_component_indicator = np.array([True, True, False])\n        transformer.null_transformer = NullTransformer()\n        data = pd.Series([0.01, 0.02, -0.01, -0.01, 0.0, 0.99, 0.97, 1.02, 1.03, 0.97])\n    \n        # Run\n>       output = transformer._transform(data)\n\ntests/unit/transformers/test_numerical.py:1339: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = ClusterBasedNormalizer(max_clusters=3)\ndata = array([[ 0.01],\n       [ 0.02],\n       [-0.01],\n       [-0.01],\n       [ 0.  ],\n       [ 0.99],\n       [ 0.97],\n       [ 1.02],\n       [ 1.03],\n       [ 0.97]])\n\n    def _transform(self, data):\n        \"\"\"Transform the numerical data.\n    \n        Args:\n            data (pandas.Series):\n                Data to transform.\n    \n        Returns:\n            numpy.ndarray.\n        \"\"\"\n        data = super()._transform(data)\n        if data.ndim > 1:\n            data, model_missing_values = data[:, 0], data[:, 1]\n    \n        data = data.reshape((len(data), 1))\n        means = self._bgm_transformer.means_.reshape((1, self.max_clusters))\n    \n        stds = np.sqrt(self._bgm_transformer.covariances_).reshape((1, self.max_clusters))\n        component_probs = self._bgm_transformer.predict_proba(data)\n        component_probs = component_probs[:, self.valid_component_indicator]\n    \n        selected_component = np.zeros(len(data), dtype='int')\n        for i in range(len(data)):\n            component_prob_t = component_probs[i] + 1e-6\n            component_prob_t = component_prob_t / component_prob_t.sum()\n            selected_component[i] = np.random.choice(\n                np.arange(self.valid_component_indicator.sum()),\n                p=component_prob_t\n            )\n    \n        aranged = np.arange(len(data))\n>       selected_means = means[aranged, selected_component]\nE       IndexError: index 1 is out of bounds for axis 0 with size 1\n\nrdt/transformers/numerical.py:514: IndexError\n=============================== warnings summary ===============================\n../usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428\n  /usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428: PytestConfigWarning: Unknown config option: collect_ignore\n  \n    self._warn_or_fail_if_strict(f\"Unknown config option: {key}\\n\")\n\n../usr/local/lib/python3.10/site-packages/copulas/__init__.py:18\n  /usr/local/lib/python3.10/site-packages/copulas/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n    from pkg_resources import iter_entry_points\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n=========================== short test summary info ============================\nFAILED tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n=================== 1 failed, 8 passed, 2 warnings in 1.42s ====================\n","stderr_tail":"","stdout_sha256":"009d9ff932f1d4abbff34f4be5faad091e0770a032979d5d6488bab63f99cd04","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-8.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:26:46.360802Z","duration_s":1.927716,"timed_out":false,"image_before":"c286df50-7fa0-484a-800c-bcf77fcdd2f4","image_after":"4eee6fce-c2e2-4485-81d7-d5cf0701edc9","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-9","seq":9,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-d0b01bf372f44a73b9dd1af2dadf82c1/bin/busybox sh -c 'mkdir -p /RDT/rdt/transformers && cp /opt/receipts-d0b01bf372f44a73b9dd1af2dadf82c1/incoming/cdbdbd4052a4621133d19961292742e331a8f300a2aa57aa3e9ce38eb58205f3 /RDT/rdt/transformers/numerical.py'","path":"rdt/transformers/numerical.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"cdbdbd4052a4621133d19961292742e331a8f300a2aa57aa3e9ce38eb58205f3","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-9.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:26:56.773065Z","duration_s":0.00459,"timed_out":false,"image_before":"4eee6fce-c2e2-4485-81d7-d5cf0701edc9","image_after":"d5ebfa08-773e-4339-a5df-d01caf58ec9d","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-10","seq":10,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform -xvs 2>&1 | head -50","path":null,"exit_code":0,"stdout_tail":"============================= test session starts ==============================\nplatform linux -- Python 3.10.19, pytest-9.0.2, pluggy-1.6.0 -- /usr/local/bin/python\ncachedir: .pytest_cache\nrootdir: /RDT\nconfigfile: setup.cfg\nplugins: anyio-4.12.1, Faker-40.4.0, cov-7.0.0\ncollecting ... collected 1 item\n\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform FAILED\n\n=================================== FAILURES ===================================\n__________________ TestClusterBasedNormalizer.test__transform __________________\n\nself = <tests.unit.transformers.test_numerical.TestClusterBasedNormalizer testMethod=test__transform>\n\n    def test__transform(self):\n        \"\"\"Test ``_transform``.\n    \n        Validate that the method produces the appropriate output when given a pandas Series.\n    \n        Setup:\n            - create an instance of the ``ClusterBasedNormalizer`` where:\n                - ``_bgm_transformer`` is mocked with the appropriate ``means_``, ``covariances_``\n                and ``predict_proba.return_value``.\n                - ``valid_component_indicator`` is set to ``np.array([True, True, False])``.\n    \n        Input:\n            - a pandas Series.\n    \n        Ouput:\n            - a numpy array with the transformed data.\n        \"\"\"\n        # Setup\n        random_state = np.random.get_state()\n        np.random.set_state(np.random.RandomState(10).get_state())\n        transformer = ClusterBasedNormalizer(max_clusters=3)\n        transformer._bgm_transformer = Mock()\n    \n        means = np.array([\n            [0.90138867],\n            [0.09169366],\n            [0.499]\n        ])\n        transformer._bgm_transformer.means_ = means\n    \n        covariances = np.array([\n            [[0.09024532]],\n            [[0.08587948]],\n            [[0.27487667]]\n        ])\n","stderr_tail":"","stdout_sha256":"e815ea8f9d1569ee7ff741202d98818722603b1a89119d14fe9fcbe1ad7b305d","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-10.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:26:58.931992Z","duration_s":1.9388869999999998,"timed_out":false,"image_before":"d5ebfa08-773e-4339-a5df-d01caf58ec9d","image_after":"81232909-bec3-4008-bfd0-8194bd09db45","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-11","seq":11,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform -xvs 2>&1 | tail -50","path":null,"exit_code":0,"stdout_tail":"            data (pandas.Series):\n                Data to transform.\n    \n        Returns:\n            numpy.ndarray.\n        \"\"\"\n        data = super()._transform(data)\n        if data.ndim > 1:\n            data, model_missing_values = data[:, 0], data[:, 1]\n    \n        data = data.reshape((len(data), 1))\n        means = self._bgm_transformer.means_.reshape((1, self.max_clusters))\n    \n        stds = np.sqrt(self._bgm_transformer.covariances_).reshape((1, self.max_clusters))\n        component_probs = self._bgm_transformer.predict_proba(data)\n        component_probs = component_probs[:, self.valid_component_indicator]\n    \n        selected_component = np.zeros(len(data), dtype='int')\n        for i in range(len(data)):\n            component_prob_t = component_probs[i] + 1e-6\n            component_prob_t = component_prob_t / component_prob_t.sum()\n            selected_component[i] = np.random.choice(\n                np.arange(self.valid_component_indicator.sum()),\n                p=component_prob_t\n            )\n    \n        # Map valid component indices to original cluster indices\n        valid_indices = np.where(self.valid_component_indicator)[0]\n        selected_cluster = valid_indices[selected_component]\n    \n        aranged = np.arange(len(data))\n>       selected_means = means[aranged, selected_cluster]\nE       IndexError: index 1 is out of bounds for axis 0 with size 1\n\nrdt/transformers/numerical.py:518: IndexError\n=============================== warnings summary ===============================\n../usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428\n  /usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428: PytestConfigWarning: Unknown config option: collect_ignore\n  \n    self._warn_or_fail_if_strict(f\"Unknown config option: {key}\\n\")\n\n../usr/local/lib/python3.10/site-packages/copulas/__init__.py:18\n  /usr/local/lib/python3.10/site-packages/copulas/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n    from pkg_resources import iter_entry_points\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n=========================== short test summary info ============================\nFAILED tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.45s =========================\n","stderr_tail":"","stdout_sha256":"a521aef8080144f8e98bb2191ee973df8473e043c28d6282a27d25523c017dc5","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-11.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:27:04.702136Z","duration_s":1.9112529999999999,"timed_out":false,"image_before":"81232909-bec3-4008-bfd0-8194bd09db45","image_after":"210860c0-7ab4-4234-81af-7554370512df","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-12","seq":12,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-d02af5e1b32a4e50bafb9890a5329345/bin/busybox sh -c 'mkdir -p /RDT/rdt/transformers && cp /opt/receipts-d02af5e1b32a4e50bafb9890a5329345/incoming/68a901a40f557e7b74749f4a22a0916648819ec9eaaa10f94de9bc755ecfd613 /RDT/rdt/transformers/numerical.py'","path":"rdt/transformers/numerical.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"68a901a40f557e7b74749f4a22a0916648819ec9eaaa10f94de9bc755ecfd613","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-12.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:27:14.741475Z","duration_s":0.005076,"timed_out":false,"image_before":"210860c0-7ab4-4234-81af-7554370512df","image_after":"4a731d1f-2da6-4311-b033-36c9f46cf4de","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-13","seq":13,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform -xvs 2>&1 | head -50","path":null,"exit_code":0,"stdout_tail":"============================= test session starts ==============================\nplatform linux -- Python 3.10.19, pytest-9.0.2, pluggy-1.6.0 -- /usr/local/bin/python\ncachedir: .pytest_cache\nrootdir: /RDT\nconfigfile: setup.cfg\nplugins: anyio-4.12.1, Faker-40.4.0, cov-7.0.0\ncollecting ... collected 1 item\n\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform FAILED\n\n=================================== FAILURES ===================================\n__________________ TestClusterBasedNormalizer.test__transform __________________\n\nself = <tests.unit.transformers.test_numerical.TestClusterBasedNormalizer testMethod=test__transform>\n\n    def test__transform(self):\n        \"\"\"Test ``_transform``.\n    \n        Validate that the method produces the appropriate output when given a pandas Series.\n    \n        Setup:\n            - create an instance of the ``ClusterBasedNormalizer`` where:\n                - ``_bgm_transformer`` is mocked with the appropriate ``means_``, ``covariances_``\n                and ``predict_proba.return_value``.\n                - ``valid_component_indicator`` is set to ``np.array([True, True, False])``.\n    \n        Input:\n            - a pandas Series.\n    \n        Ouput:\n            - a numpy array with the transformed data.\n        \"\"\"\n        # Setup\n        random_state = np.random.get_state()\n        np.random.set_state(np.random.RandomState(10).get_state())\n        transformer = ClusterBasedNormalizer(max_clusters=3)\n        transformer._bgm_transformer = Mock()\n    \n        means = np.array([\n            [0.90138867],\n            [0.09169366],\n            [0.499]\n        ])\n        transformer._bgm_transformer.means_ = means\n    \n        covariances = np.array([\n            [[0.09024532]],\n            [[0.08587948]],\n            [[0.27487667]]\n        ])\n","stderr_tail":"","stdout_sha256":"e815ea8f9d1569ee7ff741202d98818722603b1a89119d14fe9fcbe1ad7b305d","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-13.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:27:17.560345Z","duration_s":1.922541,"timed_out":false,"image_before":"4a731d1f-2da6-4311-b033-36c9f46cf4de","image_after":"35458b75-d5e1-4eff-ab05-739ac69ccc20","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-14","seq":14,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform -xvs 2>&1 | tail -50","path":null,"exit_code":0,"stdout_tail":"    \n        Examples\n        --------\n        >>> arrays = [np.random.randn(3, 4) for _ in range(10)]\n        >>> np.stack(arrays, axis=0).shape\n        (10, 3, 4)\n    \n        >>> np.stack(arrays, axis=1).shape\n        (3, 10, 4)\n    \n        >>> np.stack(arrays, axis=2).shape\n        (3, 4, 10)\n    \n        >>> a = np.array([1, 2, 3])\n        >>> b = np.array([4, 5, 6])\n        >>> np.stack((a, b))\n        array([[1, 2, 3],\n               [4, 5, 6]])\n    \n        >>> np.stack((a, b), axis=-1)\n        array([[1, 4],\n               [2, 5],\n               [3, 6]])\n    \n        \"\"\"\n        arrays = [asanyarray(arr) for arr in arrays]\n        if not arrays:\n            raise ValueError('need at least one array to stack')\n    \n        shapes = {arr.shape for arr in arrays}\n        if len(shapes) != 1:\n>           raise ValueError('all input arrays must have the same shape')\nE           ValueError: all input arrays must have the same shape\n\n/usr/local/lib/python3.10/site-packages/numpy/core/shape_base.py:449: ValueError\n=============================== warnings summary ===============================\n../usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428\n  /usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428: PytestConfigWarning: Unknown config option: collect_ignore\n  \n    self._warn_or_fail_if_strict(f\"Unknown config option: {key}\\n\")\n\n../usr/local/lib/python3.10/site-packages/copulas/__init__.py:18\n  /usr/local/lib/python3.10/site-packages/copulas/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n    from pkg_resources import iter_entry_points\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n=========================== short test summary info ============================\nFAILED tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.43s =========================\n","stderr_tail":"","stdout_sha256":"9624f203548aacb6a49ff6e6f45de500f4be985b775d462223b40b248a22c206","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-14.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:27:23.272623Z","duration_s":1.971736,"timed_out":false,"image_before":"35458b75-d5e1-4eff-ab05-739ac69ccc20","image_after":"496f8b23-234b-4ac9-8178-e4e27c33be68","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-15","seq":15,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python3 -c \"\nimport numpy as np\nfrom unittest.mock import Mock\nfrom rdt.transformers.numerical import ClusterBasedNormalizer\nimport pandas as pd\n\ntransformer = ClusterBasedNormalizer(max_clusters=3)\ntransformer._bgm_transformer = Mock()\n\nmeans = np.array([\n    [0.90138867],\n    [0.09169366],\n    [0.499]\n])\ntransformer._bgm_transformer.means_ = means\n\ncovariances = np.array([\n    [[0.09024532]],\n    [[0.08587948]],\n    [[0.27487667]]\n])\ntransformer._bgm_transformer.covariances_ = covariances\n\nprobabilities = np.array([\n    [0.01519528, 0.98480472, 0.],\n    [0.01659093, 0.98340907, 0.],\n    [0.012744, 0.987256, 0.],\n    [0.012744, 0.987256, 0.],\n    [0.01391614, 0.98608386, 0.],\n    [0.99220664, 0.00779336, 0.],\n    [0.99059634, 0.00940366, 0.],\n    [0.9941256, 0.0058744, 0.],\n    [0.99465502, 0.00534498, 0.],\n    [0.99059634, 0.00940366, 0.]\n])\ntransformer._bgm_transformer.predict_proba.return_value = probabilities\n\ntransformer.valid_component_indicator = np.array([True, True, False])\ntransformer.null_transformer = Mock()\ndata = pd.Series([0.01, 0.02, -0.01, -0.01, 0.0, 0.99, 0.97, 1.02, 1.03, 0.97])\n\n# Run transform\noutput = transformer._transform(data)\nprint('Output shape:', output.shape)\nprint('Output:', output)\n\" 2>&1","path":null,"exit_code":1,"stdout_tail":"/RDT/rdt/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n  from pkg_resources import iter_entry_points\nTraceback (most recent call last):\n  File \"<string>\", line 43, in <module>\n  File \"/RDT/rdt/transformers/numerical.py\", line 494, in _transform\n    if data.ndim > 1:\nTypeError: '>' not supported between instances of 'Mock' and 'int'\n","stderr_tail":"","stdout_sha256":"4a4f0fb4ae155c7d5503876bccddf5322c58fa56fbcab3fb83c3bc290f0e95a5","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-15.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:27:35.048504Z","duration_s":1.492084,"timed_out":false,"image_before":"496f8b23-234b-4ac9-8178-e4e27c33be68","image_after":"3b483868-a7a1-4201-bfea-1c7e32875596","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-16","seq":16,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform -xvs 2>&1 | grep -A 30 \"FAILED\"","path":null,"exit_code":0,"stdout_tail":"tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform FAILED\n\n=================================== FAILURES ===================================\n__________________ TestClusterBasedNormalizer.test__transform __________________\n\nself = <tests.unit.transformers.test_numerical.TestClusterBasedNormalizer testMethod=test__transform>\n\n    def test__transform(self):\n        \"\"\"Test ``_transform``.\n    \n        Validate that the method produces the appropriate output when given a pandas Series.\n    \n        Setup:\n            - create an instance of the ``ClusterBasedNormalizer`` where:\n                - ``_bgm_transformer`` is mocked with the appropriate ``means_``, ``covariances_``\n                and ``predict_proba.return_value``.\n                - ``valid_component_indicator`` is set to ``np.array([True, True, False])``.\n    \n        Input:\n            - a pandas Series.\n    \n        Ouput:\n            - a numpy array with the transformed data.\n        \"\"\"\n        # Setup\n        random_state = np.random.get_state()\n        np.random.set_state(np.random.RandomState(10).get_state())\n        transformer = ClusterBasedNormalizer(max_clusters=3)\n        transformer._bgm_transformer = Mock()\n    \n        means = np.array([\n--\nFAILED tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.49s =========================\n","stderr_tail":"","stdout_sha256":"4355ff209219ab9f808bef0f7dcc9b6e09fc484942161605b815efd7b211e3d4","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-16.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:27:49.041044Z","duration_s":1.93719,"timed_out":false,"image_before":"3b483868-a7a1-4201-bfea-1c7e32875596","image_after":"453626d4-5d00-442b-870d-f81e2812dbe9","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-17","seq":17,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform -xvs 2>&1 | grep -A 50 \"FAILURES\"","path":null,"exit_code":0,"stdout_tail":"=================================== FAILURES ===================================\n__________________ TestClusterBasedNormalizer.test__transform __________________\n\nself = <tests.unit.transformers.test_numerical.TestClusterBasedNormalizer testMethod=test__transform>\n\n    def test__transform(self):\n        \"\"\"Test ``_transform``.\n    \n        Validate that the method produces the appropriate output when given a pandas Series.\n    \n        Setup:\n            - create an instance of the ``ClusterBasedNormalizer`` where:\n                - ``_bgm_transformer`` is mocked with the appropriate ``means_``, ``covariances_``\n                and ``predict_proba.return_value``.\n                - ``valid_component_indicator`` is set to ``np.array([True, True, False])``.\n    \n        Input:\n            - a pandas Series.\n    \n        Ouput:\n            - a numpy array with the transformed data.\n        \"\"\"\n        # Setup\n        random_state = np.random.get_state()\n        np.random.set_state(np.random.RandomState(10).get_state())\n        transformer = ClusterBasedNormalizer(max_clusters=3)\n        transformer._bgm_transformer = Mock()\n    \n        means = np.array([\n            [0.90138867],\n            [0.09169366],\n            [0.499]\n        ])\n        transformer._bgm_transformer.means_ = means\n    \n        covariances = np.array([\n            [[0.09024532]],\n            [[0.08587948]],\n            [[0.27487667]]\n        ])\n        transformer._bgm_transformer.covariances_ = covariances\n    \n        probabilities = np.array([\n            [0.01519528, 0.98480472, 0.],\n            [0.01659093, 0.98340907, 0.],\n            [0.012744, 0.987256, 0.],\n            [0.012744, 0.987256, 0.],\n            [0.01391614, 0.98608386, 0.],\n            [0.99220664, 0.00779336, 0.],\n            [0.99059634, 0.00940366, 0.],\n            [0.9941256, 0.0058744, 0.],\n","stderr_tail":"","stdout_sha256":"9827adc505d7340f0d6d6eeaa8eb115203e4c0a73fb223f9796f1485a62c09cc","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-17.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:27:55.000238Z","duration_s":2.006075,"timed_out":false,"image_before":"453626d4-5d00-442b-870d-f81e2812dbe9","image_after":"70c79152-f8cf-4f10-9dd9-6440d10be3b3","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-18","seq":18,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform -xvs 2>&1 | grep -A 80 \"ValueError\"","path":null,"exit_code":0,"stdout_tail":"            raise ValueError('need at least one array to stack')\n    \n        shapes = {arr.shape for arr in arrays}\n        if len(shapes) != 1:\n>           raise ValueError('all input arrays must have the same shape')\nE           ValueError: all input arrays must have the same shape\n\n/usr/local/lib/python3.10/site-packages/numpy/core/shape_base.py:449: ValueError\n=============================== warnings summary ===============================\n../usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428\n  /usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428: PytestConfigWarning: Unknown config option: collect_ignore\n  \n    self._warn_or_fail_if_strict(f\"Unknown config option: {key}\\n\")\n\n../usr/local/lib/python3.10/site-packages/copulas/__init__.py:18\n  /usr/local/lib/python3.10/site-packages/copulas/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n    from pkg_resources import iter_entry_points\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n=========================== short test summary info ============================\nFAILED tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.47s =========================\n","stderr_tail":"","stdout_sha256":"c6e3e632ca2a648f7c951bf43eabca7ddbc7be8f71b32e798ac5598e373e03a9","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-18.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:28:00.632190Z","duration_s":2.0738890000000003,"timed_out":false,"image_before":"70c79152-f8cf-4f10-9dd9-6440d10be3b3","image_after":"6e16846b-4878-44af-a4a5-9dad1e7d26f7","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-19","seq":19,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python3 -c \"\nimport numpy as np\nfrom unittest.mock import Mock\nfrom rdt.transformers.numerical import ClusterBasedNormalizer\nimport pandas as pd\n\ntransformer = ClusterBasedNormalizer(max_clusters=3)\ntransformer._bgm_transformer = Mock()\n\nmeans = np.array([\n    [0.90138867],\n    [0.09169366],\n    [0.499]\n])\ntransformer._bgm_transformer.means_ = means\n\ncovariances = np.array([\n    [[0.09024532]],\n    [[0.08587948]],\n    [[0.27487667]]\n])\ntransformer._bgm_transformer.covariances_ = covariances\n\nprobabilities = np.array([\n    [0.01519528, 0.98480472, 0.],\n    [0.01659093, 0.98340907, 0.],\n    [0.012744, 0.987256, 0.],\n    [0.012744, 0.987256, 0.],\n    [0.01391614, 0.98608386, 0.],\n    [0.99220664, 0.00779336, 0.],\n    [0.99059634, 0.00940366, 0.],\n    [0.9941256, 0.0058744, 0.],\n    [0.99465502, 0.00534498, 0.],\n    [0.99059634, 0.00940366, 0.]\n])\ntransformer._bgm_transformer.predict_proba.return_value = probabilities\n\ntransformer.valid_component_indicator = np.array([True, True, False])\ntransformer.null_transformer = Mock()\ndata = pd.Series([0.01, 0.02, -0.01, -0.01, 0.0, 0.99, 0.97, 1.02, 1.03, 0.97])\n\n# Simulate the transform logic\ndata_arr = super()._transform(data) if hasattr(transformer, 'null_transformer') else np.array(data).reshape(-1, 1)\nprint('data after super transform shape:', data_arr.shape if hasattr(data_arr, 'shape') else 'N/A')\n\n# Manually do what _transform does\ndata_reshaped = data_arr.reshape((len(data_arr), 1)) if len(data_arr.shape) == 1 else data_arr\nprint('data_reshaped shape:', data_reshaped.shape)\n\nmeans_reshaped = transformer._bgm_transformer.means_.reshape((1, transformer.max_clusters))\nprint('means_reshaped shape:', means_reshaped.shape)\n\nstds_reshaped = np.sqrt(transformer._bgm_transformer.covariances_).reshape((1, transformer.max_clusters))\nprint('stds_reshaped shape:', stds_reshaped.shape)\n\ncomponent_probs = transformer._bgm_transformer.predict_proba(data_reshaped)\nprint('component_probs shape before filter:', component_probs.shape)\n\ncomponent_probs = component_probs[:, transformer.valid_component_indicator]\nprint('component_probs shape after filter:', component_probs.shape)\n\nselected_component = np.zeros(len(data_arr), dtype='int')\nfor i in range(len(data_arr)):\n    component_prob_t = component_probs[i] + 1e-6\n    component_prob_t = component_prob_t / component_prob_t.sum()\n    selected_component[i] = np.random.choice(\n        np.arange(transformer.valid_component_indicator.sum()),\n        p=component_prob_t\n    )\nprint('selected_component:', selected_component)\n\nvalid_indices = np.where(transformer.valid_component_indicator)[0]\nprint('valid_indices:', valid_indices)\n\nselected_cluster = valid_indices[selected_component]\nprint('selected_cluster:', selected_cluster)\n\nselected_means = means_reshaped[0, selected_cluster]\nprint('selected_means shape:', selected_means.shape)\n\nselected_stds = stds_reshaped[0, selected_cluster]\nprint('selected_stds shape:', selected_stds.shape)\n\ndata_minus_means = data_reshaped - selected_means\nprint('data_minus_means shape:', data_minus_means.shape)\n\nnormalized = (data_minus_means) / (transformer.STD_MULTIPLIER * selected_stds)\nprint('normalized shape:', normalized.shape)\n\nnormalized = np.clip(normalized, -.99, .99)\nprint('normalized after clip shape:', normalized.shape)\n\nnormalized_reshaped = normalized.reshape([-1, 1])[:, 0]\nprint('normalized_reshaped shape:', normalized_reshaped.shape)\n\nrows = [normalized_reshaped, selected_component]\nprint('rows[0] shape:', rows[0].shape)\nprint('rows[1] shape:', rows[1].shape)\n\ntry:\n    result = np.stack(rows, axis=1)\n    print('result shape:', result.shape)\nexcept Exception as e:\n    print('Error stacking:', e)\n\" 2>&1","path":null,"exit_code":1,"stdout_tail":"/RDT/rdt/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n  from pkg_resources import iter_entry_points\nTraceback (most recent call last):\n  File \"<string>\", line 43, in <module>\nRuntimeError: super(): no arguments\n","stderr_tail":"","stdout_sha256":"1dba11b2c6422ac1d165f9108a58cc9afaaa529c9355b639b564aabff2d7973c","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-19.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:28:12.134944Z","duration_s":1.5406710000000001,"timed_out":false,"image_before":"6e16846b-4878-44af-a4a5-9dad1e7d26f7","image_after":"79769f63-5f38-468b-956c-79ba86c0853d","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-20","seq":20,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python3 -c \"\nimport numpy as np\nfrom rdt.transformers.numerical import ClusterBasedNormalizer\n\ntransformer = ClusterBasedNormalizer(max_clusters=3)\n\nmeans = np.array([\n    [0.90138867],\n    [0.09169366],\n    [0.499]\n])\ntransformer._bgm_transformer = Mock()\ntransformer._bgm_transformer.means_ = means\n\ncovariances = np.array([\n    [[0.09024532]],\n    [[0.08587948]],\n    [[0.27487667]]\n])\ntransformer._bgm_transformer.covariances_ = covariances\n\nprobabilities = np.array([\n    [0.01519528, 0.98480472, 0.],\n])\ntransformer._bgm_transformer.predict_proba.return_value = probabilities\n\ntransformer.valid_component_indicator = np.array([True, True, False])\n\ndata = np.array([0.01]).reshape(-1, 1)\nprint('data shape:', data.shape)\n\ndata_reshaped = data.reshape((len(data), 1))\nprint('data_reshaped shape:', data_reshaped.shape)\n\nmeans_reshaped = transformer._bgm_transformer.means_.reshape((1, transformer.max_clusters))\nprint('means_reshaped shape:', means_reshaped.shape)\n\nstds_reshaped = np.sqrt(transformer._bgm_transformer.covariances_).reshape((1, transformer.max_clusters))\nprint('stds_reshaped shape:', stds_reshaped.shape)\n\ncomponent_probs = transformer._bgm_transformer.predict_proba(data_reshaped)\nprint('component_probs shape before filter:', component_probs.shape)\n\ncomponent_probs = component_probs[:, transformer.valid_component_indicator]\nprint('component_probs shape after filter:', component_probs.shape)\n\nselected_component = np.zeros(len(data), dtype='int')\nfor i in range(len(data)):\n    component_prob_t = component_probs[i] + 1e-6\n    component_prob_t = component_prob_t / component_prob_t.sum()\n    selected_component[i] = np.random.choice(\n        np.arange(transformer.valid_component_indicator.sum()),\n        p=component_prob_t\n    )\nprint('selected_component:', selected_component)\n\nvalid_indices = np.where(transformer.valid_component_indicator)[0]\nprint('valid_indices:', valid_indices)\n\nselected_cluster = valid_indices[selected_component]\nprint('selected_cluster:', selected_cluster)\n\nselected_means = means_reshaped[0, selected_cluster]\nprint('selected_means shape:', selected_means.shape)\n\nselected_stds = stds_reshaped[0, selected_cluster]\nprint('selected_stds shape:', selected_stds.shape)\n\ndata_minus_means = data_reshaped - selected_means\nprint('data_minus_means shape:', data_minus_means.shape)\n\nnormalized = (data_minus_means) / (transformer.STD_MULTIPLIER * selected_stds)\nprint('normalized shape:', normalized.shape)\n\nnormalized = np.clip(normalized, -.99, .99)\nprint('normalized after clip shape:', normalized.shape)\n\nnormalized_reshaped = normalized.reshape([-1, 1])[:, 0]\nprint('normalized_reshaped shape:', normalized_reshaped.shape)\n\nrows = [normalized_reshaped, selected_component]\nprint('rows[0] shape:', rows[0].shape)\nprint('rows[1] shape:', rows[1].shape)\n\ntry:\n    result = np.stack(rows, axis=1)\n    print('result shape:', result.shape)\nexcept Exception as e:\n    print('Error stacking:', type(e).__name__, e)\n\" 2>&1","path":null,"exit_code":1,"stdout_tail":"/RDT/rdt/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n  from pkg_resources import iter_entry_points\nTraceback (most recent call last):\n  File \"<string>\", line 12, in <module>\nNameError: name 'Mock' is not defined\n","stderr_tail":"","stdout_sha256":"042cc9e64e35d4ec6777a0a135f58efef5d2b0ba550d1d3492790b27d8a67e79","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-20.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:28:33.280096Z","duration_s":1.5369800000000002,"timed_out":false,"image_before":"79769f63-5f38-468b-956c-79ba86c0853d","image_after":"44825034-a93b-4b9a-b3cc-d8ea874ec80c","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-21","seq":21,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python3 -c \"\nimport numpy as np\nfrom unittest.mock import Mock\nfrom rdt.transformers.numerical import ClusterBasedNormalizer\n\ntransformer = ClusterBasedNormalizer(max_clusters=3)\n\nmeans = np.array([\n    [0.90138867],\n    [0.09169366],\n    [0.499]\n])\ntransformer._bgm_transformer = Mock()\ntransformer._bgm_transformer.means_ = means\n\ncovariances = np.array([\n    [[0.09024532]],\n    [[0.08587948]],\n    [[0.27487667]]\n])\ntransformer._bgm_transformer.covariances_ = covariances\n\nprobabilities = np.array([\n    [0.01519528, 0.98480472, 0.],\n])\ntransformer._bgm_transformer.predict_proba.return_value = probabilities\n\ntransformer.valid_component_indicator = np.array([True, True, False])\n\ndata = np.array([0.01]).reshape(-1, 1)\nprint('data shape:', data.shape)\n\ndata_reshaped = data.reshape((len(data), 1))\nprint('data_reshaped shape:', data_reshaped.shape)\n\nmeans_reshaped = transformer._bgm_transformer.means_.reshape((1, transformer.max_clusters))\nprint('means_reshaped shape:', means_reshaped.shape)\n\nstds_reshaped = np.sqrt(transformer._bgm_transformer.covariances_).reshape((1, transformer.max_clusters))\nprint('stds_reshaped shape:', stds_reshaped.shape)\n\ncomponent_probs = transformer._bgm_transformer.predict_proba(data_reshaped)\nprint('component_probs shape before filter:', component_probs.shape)\n\ncomponent_probs = component_probs[:, transformer.valid_component_indicator]\nprint('component_probs shape after filter:', component_probs.shape)\n\nselected_component = np.zeros(len(data), dtype='int')\nfor i in range(len(data)):\n    component_prob_t = component_probs[i] + 1e-6\n    component_prob_t = component_prob_t / component_prob_t.sum()\n    selected_component[i] = np.random.choice(\n        np.arange(transformer.valid_component_indicator.sum()),\n        p=component_prob_t\n    )\nprint('selected_component:', selected_component)\n\nvalid_indices = np.where(transformer.valid_component_indicator)[0]\nprint('valid_indices:', valid_indices)\n\nselected_cluster = valid_indices[selected_component]\nprint('selected_cluster:', selected_cluster)\n\nselected_means = means_reshaped[0, selected_cluster]\nprint('selected_means shape:', selected_means.shape)\n\nselected_stds = stds_reshaped[0, selected_cluster]\nprint('selected_stds shape:', selected_stds.shape)\n\ndata_minus_means = data_reshaped - selected_means\nprint('data_minus_means shape:', data_minus_means.shape)\n\nnormalized = (data_minus_means) / (transformer.STD_MULTIPLIER * selected_stds)\nprint('normalized shape:', normalized.shape)\n\nnormalized = np.clip(normalized, -.99, .99)\nprint('normalized after clip shape:', normalized.shape)\n\nnormalized_reshaped = normalized.reshape([-1, 1])[:, 0]\nprint('normalized_reshaped shape:', normalized_reshaped.shape)\n\nrows = [normalized_reshaped, selected_component]\nprint('rows[0] shape:', rows[0].shape)\nprint('rows[1] shape:', rows[1].shape)\n\ntry:\n    result = np.stack(rows, axis=1)\n    print('result shape:', result.shape)\nexcept Exception as e:\n    print('Error stacking:', type(e).__name__, e)\n\" 2>&1","path":null,"exit_code":0,"stdout_tail":"/RDT/rdt/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n  from pkg_resources import iter_entry_points\ndata shape: (1, 1)\ndata_reshaped shape: (1, 1)\nmeans_reshaped shape: (1, 3)\nstds_reshaped shape: (1, 3)\ncomponent_probs shape before filter: (1, 3)\ncomponent_probs shape after filter: (1, 2)\nselected_component: [1]\nvalid_indices: [0 1]\nselected_cluster: [1]\nselected_means shape: (1,)\nselected_stds shape: (1,)\ndata_minus_means shape: (1, 1)\nnormalized shape: (1, 1)\nnormalized after clip shape: (1, 1)\nnormalized_reshaped shape: (1,)\nrows[0] shape: (1,)\nrows[1] shape: (1,)\nresult shape: (1, 2)\n","stderr_tail":"","stdout_sha256":"83e7fe91af23cd478255ff47958ec8b9fbebff7cd06ca4fba470357d5acc77f8","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-21.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:28:48.356052Z","duration_s":1.556381,"timed_out":false,"image_before":"44825034-a93b-4b9a-b3cc-d8ea874ec80c","image_after":"28f45cf2-eaea-40e2-a6bd-4491fd88ab71","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-22","seq":22,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform -xvs 2>&1 | tail -80","path":null,"exit_code":0,"stdout_tail":"        axis : int, optional\n            The axis in the result array along which the input arrays are stacked.\n    \n        out : ndarray, optional\n            If provided, the destination to place the result. The shape must be\n            correct, matching that of what stack would have returned if no\n            out argument were specified.\n    \n        dtype : str or dtype\n            If provided, the destination array will have this dtype. Cannot be\n            provided together with `out`.\n    \n            .. versionadded:: 1.24\n    \n        casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional\n            Controls what kind of data casting may occur. Defaults to 'same_kind'.\n    \n            .. versionadded:: 1.24\n    \n    \n        Returns\n        -------\n        stacked : ndarray\n            The stacked array has one more dimension than the input arrays.\n    \n        See Also\n        --------\n        concatenate : Join a sequence of arrays along an existing axis.\n        block : Assemble an nd-array from nested lists of blocks.\n        split : Split array into a list of multiple sub-arrays of equal size.\n    \n        Examples\n        --------\n        >>> arrays = [np.random.randn(3, 4) for _ in range(10)]\n        >>> np.stack(arrays, axis=0).shape\n        (10, 3, 4)\n    \n        >>> np.stack(arrays, axis=1).shape\n        (3, 10, 4)\n    \n        >>> np.stack(arrays, axis=2).shape\n        (3, 4, 10)\n    \n        >>> a = np.array([1, 2, 3])\n        >>> b = np.array([4, 5, 6])\n        >>> np.stack((a, b))\n        array([[1, 2, 3],\n               [4, 5, 6]])\n    \n        >>> np.stack((a, b), axis=-1)\n        array([[1, 4],\n               [2, 5],\n               [3, 6]])\n    \n        \"\"\"\n        arrays = [asanyarray(arr) for arr in arrays]\n        if not arrays:\n            raise ValueError('need at least one array to stack')\n    \n        shapes = {arr.shape for arr in arrays}\n        if len(shapes) != 1:\n>           raise ValueError('all input arrays must have the same shape')\nE           ValueError: all input arrays must have the same shape\n\n/usr/local/lib/python3.10/site-packages/numpy/core/shape_base.py:449: ValueError\n=============================== warnings summary ===============================\n../usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428\n  /usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428: PytestConfigWarning: Unknown config option: collect_ignore\n  \n    self._warn_or_fail_if_strict(f\"Unknown config option: {key}\\n\")\n\n../usr/local/lib/python3.10/site-packages/copulas/__init__.py:18\n  /usr/local/lib/python3.10/site-packages/copulas/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n    from pkg_resources import iter_entry_points\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n=========================== short test summary info ============================\nFAILED tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.47s =========================\n","stderr_tail":"","stdout_sha256":"7cfb77678619b296bf97a66d4af6d849ce932503bbd32a7f5dd05ac473fac5e8","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-22.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:28:54.435556Z","duration_s":1.918669,"timed_out":false,"image_before":"28f45cf2-eaea-40e2-a6bd-4491fd88ab71","image_after":"4e93c729-0a91-432e-86f7-f994e4efd698","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-23","seq":23,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python3 -c \"\nimport numpy as np\nfrom unittest.mock import Mock, patch\nimport pandas as pd\nfrom rdt.transformers.numerical import ClusterBasedNormalizer\n\n# Patch randomness to make it deterministic\nnp.random.seed(10)\n\ntransformer = ClusterBasedNormalizer(max_clusters=3)\ntransformer._bgm_transformer = Mock()\n\nmeans = np.array([\n    [0.90138867],\n    [0.09169366],\n    [0.499]\n])\ntransformer._bgm_transformer.means_ = means\n\ncovariances = np.array([\n    [[0.09024532]],\n    [[0.08587948]],\n    [[0.27487667]]\n])\ntransformer._bgm_transformer.covariances_ = covariances\n\nprobabilities = np.array([\n    [0.01519528, 0.98480472, 0.],\n    [0.01659093, 0.98340907, 0.],\n    [0.012744, 0.987256, 0.],\n    [0.012744, 0.987256, 0.],\n    [0.01391614, 0.98608386, 0.],\n    [0.99220664, 0.00779336, 0.],\n    [0.99059634, 0.00940366, 0.],\n    [0.9941256, 0.0058744, 0.],\n    [0.99465502, 0.00534498, 0.],\n    [0.99059634, 0.00940366, 0.]\n])\ntransformer._bgm_transformer.predict_proba.return_value = probabilities\n\ntransformer.valid_component_indicator = np.array([True, True, False])\ntransformer.null_transformer = Mock()\ndata = pd.Series([0.01, 0.02, -0.01, -0.01, 0.0, 0.99, 0.97, 1.02, 1.03, 0.97])\n\n# Run transform\noutput = transformer._transform(data)\nprint('Output shape:', output.shape)\nprint('Output:', output)\n\" 2>&1","path":null,"exit_code":1,"stdout_tail":"/RDT/rdt/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n  from pkg_resources import iter_entry_points\nTraceback (most recent call last):\n  File \"<string>\", line 46, in <module>\n  File \"/RDT/rdt/transformers/numerical.py\", line 494, in _transform\n    if data.ndim > 1:\nTypeError: '>' not supported between instances of 'Mock' and 'int'\n","stderr_tail":"","stdout_sha256":"54d7d2e41db6a4634e47f691ebeb9cdc48f4d4ef9f2a1b13fd44a9421c0890f8","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-23.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:29:02.403066Z","duration_s":1.504941,"timed_out":false,"image_before":"4e93c729-0a91-432e-86f7-f994e4efd698","image_after":"7aa4f85a-5fac-432a-a56d-ceee24cfbc30","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-24","seq":24,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python3 -c \"\nimport numpy as np\nfrom unittest.mock import Mock, patch\nimport pandas as pd\nfrom rdt.transformers.null import NullTransformer\nfrom rdt.transformers.numerical import ClusterBasedNormalizer\n\n# Patch randomness to make it deterministic\nnp.random.seed(10)\n\ntransformer = ClusterBasedNormalizer(max_clusters=3)\ntransformer._bgm_transformer = Mock()\n\nmeans = np.array([\n    [0.90138867],\n    [0.09169366],\n    [0.499]\n])\ntransformer._bgm_transformer.means_ = means\n\ncovariances = np.array([\n    [[0.09024532]],\n    [[0.08587948]],\n    [[0.27487667]]\n])\ntransformer._bgm_transformer.covariances_ = covariances\n\nprobabilities = np.array([\n    [0.01519528, 0.98480472, 0.],\n    [0.01659093, 0.98340907, 0.],\n    [0.012744, 0.987256, 0.],\n    [0.012744, 0.987256, 0.],\n    [0.01391614, 0.98608386, 0.],\n    [0.99220664, 0.00779336, 0.],\n    [0.99059634, 0.00940366, 0.],\n    [0.9941256, 0.0058744, 0.],\n    [0.99465502, 0.00534498, 0.],\n    [0.99059634, 0.00940366, 0.]\n])\ntransformer._bgm_transformer.predict_proba.return_value = probabilities\n\ntransformer.valid_component_indicator = np.array([True, True, False])\nnull_transformer = NullTransformer()\ntransformer.null_transformer = null_transformer\ndata = pd.Series([0.01, 0.02, -0.01, -0.01, 0.0, 0.99, 0.97, 1.02, 1.03, 0.97])\n\n# Run transform\noutput = transformer._transform(data)\nprint('Output shape:', output.shape)\nprint('Output:', output)\n\" 2>&1","path":null,"exit_code":1,"stdout_tail":"/RDT/rdt/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n  from pkg_resources import iter_entry_points\nTraceback (most recent call last):\n  File \"<string>\", line 48, in <module>\n  File \"/RDT/rdt/transformers/numerical.py\", line 527, in _transform\n    return np.stack(rows, axis=1)\n  File \"/usr/local/lib/python3.10/site-packages/numpy/core/shape_base.py\", line 449, in stack\n    raise ValueError('all input arrays must have the same shape')\nValueError: all input arrays must have the same shape\n","stderr_tail":"","stdout_sha256":"19d723690e2e69a2399e0c8096bd01e3ecab9827a16ab48bf7908471c1825e68","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-24.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:29:10.471520Z","duration_s":1.4987300000000001,"timed_out":false,"image_before":"7aa4f85a-5fac-432a-a56d-ceee24cfbc30","image_after":"dd245bb4-8c28-441a-9851-6a1b7309e08c","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-25","seq":25,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python3 -c \"\nimport numpy as np\nfrom unittest.mock import Mock, patch\nimport pandas as pd\nfrom rdt.transformers.null import NullTransformer\nfrom rdt.transformers.numerical import ClusterBasedNormalizer\n\n# Patch randomness to make it deterministic\nnp.random.seed(10)\n\ntransformer = ClusterBasedNormalizer(max_clusters=3)\ntransformer._bgm_transformer = Mock()\n\nmeans = np.array([\n    [0.90138867],\n    [0.09169366],\n    [0.499]\n])\ntransformer._bgm_transformer.means_ = means\n\ncovariances = np.array([\n    [[0.09024532]],\n    [[0.08587948]],\n    [[0.27487667]]\n])\ntransformer._bgm_transformer.covariances_ = covariances\n\nprobabilities = np.array([\n    [0.01519528, 0.98480472, 0.],\n    [0.01659093, 0.98340907, 0.],\n    [0.012744, 0.987256, 0.],\n    [0.012744, 0.987256, 0.],\n    [0.01391614, 0.98608386, 0.],\n    [0.99220664, 0.00779336, 0.],\n    [0.99059634, 0.00940366, 0.],\n    [0.9941256, 0.0058744, 0.],\n    [0.99465502, 0.00534498, 0.],\n    [0.99059634, 0.00940366, 0.]\n])\ntransformer._bgm_transformer.predict_proba.return_value = probabilities\n\ntransformer.valid_component_indicator = np.array([True, True, False])\nnull_transformer = NullTransformer()\ntransformer.null_transformer = null_transformer\ndata = pd.Series([0.01, 0.02, -0.01, -0.01, 0.0, 0.99, 0.97, 1.02, 1.03, 0.97])\n\n# Run transform - add debugging\ndata_trans = transformer._transform(data.__class__(data)) if False else None\n\n# Manual trace\nsuper_transform = transformer.null_transformer.transform(data)\nprint('super_transform shape:', super_transform.shape if hasattr(super_transform, 'shape') else type(super_transform))\n\nif super_transform.ndim > 1:\n    data_arr, model_missing_values = super_transform[:, 0], super_transform[:, 1]\nelse:\n    data_arr = super_transform\n    model_missing_values = None\n\nprint('data_arr shape:', data_arr.shape if hasattr(data_arr, 'shape') else type(data_arr))\n\ndata_reshaped = data_arr.reshape((len(data_arr), 1))\nprint('data_reshaped shape:', data_reshaped.shape)\n\nmeans_reshaped = transformer._bgm_transformer.means_.reshape((1, transformer.max_clusters))\nprint('means_reshaped shape:', means_reshaped.shape)\n\nstds_reshaped = np.sqrt(transformer._bgm_transformer.covariances_).reshape((1, transformer.max_clusters))\nprint('stds_reshaped shape:', stds_reshaped.shape)\n\ncomponent_probs = transformer._bgm_transformer.predict_proba(data_reshaped)\nprint('component_probs shape before filter:', component_probs.shape)\n\ncomponent_probs = component_probs[:, transformer.valid_component_indicator]\nprint('component_probs shape after filter:', component_probs.shape)\n\nselected_component = np.zeros(len(data_arr), dtype='int')\nfor i in range(len(data_arr)):\n    component_prob_t = component_probs[i] + 1e-6\n    component_prob_t = component_prob_t / component_prob_t.sum()\n    selected_component[i] = np.random.choice(\n        np.arange(transformer.valid_component_indicator.sum()),\n        p=component_prob_t\n    )\nprint('selected_component:', selected_component)\n\nvalid_indices = np.where(transformer.valid_component_indicator)[0]\nprint('valid_indices:', valid_indices)\n\nselected_cluster = valid_indices[selected_component]\nprint('selected_cluster:', selected_cluster)\n\nselected_means = means_reshaped[0, selected_cluster]\nprint('selected_means shape:', selected_means.shape, 'values:', selected_means)\n\nselected_stds = stds_reshaped[0, selected_cluster]\nprint('selected_stds shape:', selected_stds.shape, 'values:', selected_stds)\n\ndata_minus_means = data_reshaped - selected_means\nprint('data_minus_means shape:', data_minus_means.shape)\n\nnormalized = (data_minus_means) / (transformer.STD_MULTIPLIER * selected_stds)\nprint('normalized shape:', normalized.shape)\n\nnormalized = np.clip(normalized, -.99, .99)\nprint('normalized after clip shape:', normalized.shape)\n\nnormalized_1d = normalized.reshape([-1, 1])[:, 0]\nprint('normalized_1d shape:', normalized_1d.shape, 'values:', normalized_1d)\n\nrows = [normalized_1d, selected_component]\nprint('rows[0] shape:', rows[0].shape, 'values:', rows[0])\nprint('rows[1] shape:', rows[1].shape, 'values:', rows[1])\n\ntry:\n    result = np.stack(rows, axis=1)\n    print('result shape:', result.shape)\nexcept Exception as e:\n    print('Error stacking:', e)\n\" 2>&1","path":null,"exit_code":0,"stdout_tail":"/RDT/rdt/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n  from pkg_resources import iter_entry_points\nsuper_transform shape: (10,)\ndata_arr shape: (10,)\ndata_reshaped shape: (10, 1)\nmeans_reshaped shape: (1, 3)\nstds_reshaped shape: (1, 3)\ncomponent_probs shape before filter: (10, 3)\ncomponent_probs shape after filter: (10, 2)\nselected_component: [1 1 1 1 1 0 0 0 0 0]\nvalid_indices: [0 1]\nselected_cluster: [1 1 1 1 1 0 0 0 0 0]\nselected_means shape: (10,) values: [0.09169366 0.09169366 0.09169366 0.09169366 0.09169366 0.90138867\n 0.90138867 0.90138867 0.90138867 0.90138867]\nselected_stds shape: (10,) values: [0.29305201 0.29305201 0.29305201 0.29305201 0.29305201 0.30040859\n 0.30040859 0.30040859 0.30040859 0.30040859]\ndata_minus_means shape: (10, 10)\nnormalized shape: (10, 10)\nnormalized after clip shape: (10, 10)\nnormalized_1d shape: (100,) values: [-0.06969212 -0.06969212 -0.06969212 -0.06969212 -0.06969212 -0.74181357\n -0.74181357 -0.74181357 -0.74181357 -0.74181357 -0.06116121 -0.06116121\n -0.06116121 -0.06116121 -0.06116121 -0.73349157 -0.73349157 -0.73349157\n -0.73349157 -0.73349157 -0.08675394 -0.08675394 -0.08675394 -0.08675394\n -0.08675394 -0.75845757 -0.75845757 -0.75845757 -0.75845757 -0.75845757\n -0.08675394 -0.08675394 -0.08675394 -0.08675394 -0.08675394 -0.75845757\n -0.75845757 -0.75845757 -0.75845757 -0.75845757 -0.07822303 -0.07822303\n -0.07822303 -0.07822303 -0.07822303 -0.75013557 -0.75013557 -0.75013557\n -0.75013557 -0.75013557  0.76633696  0.76633696  0.76633696  0.76633696\n  0.76633696  0.07374234  0.07374234  0.07374234  0.07374234  0.07374234\n  0.74927514  0.74927514  0.74927514  0.74927514  0.74927514  0.05709834\n  0.05709834  0.05709834  0.05709834  0.05709834  0.79192968  0.79192968\n  0.79192968  0.79192968  0.79192968  0.09870834  0.09870834  0.09870834\n  0.09870834  0.09870834  0.80046059  0.80046059  0.80046059  0.80046059\n  0.80046059  0.10703034  0.10703034  0.10703034  0.10703034  0.10703034\n  0.74927514  0.74927514  0.74927514  0.74927514  0.74927514  0.05709834\n  0.05709834  0.05709834  0.05709834  0.05709834]\nrows[0] shape: (100,) values: [-0.06969212 -0.06969212 -0.06969212 -0.06969212 -0.06969212 -0.74181357\n -0.74181357 -0.74181357 -0.74181357 -0.74181357 -0.06116121 -0.06116121\n -0.06116121 -0.06116121 -0.06116121 -0.73349157 -0.73349157 -0.73349157\n -0.73349157 -0.73349157 -0.08675394 -0.08675394 -0.08675394 -0.08675394\n -0.08675394 -0.75845757 -0.75845757 -0.75845757 -0.75845757 -0.75845757\n -0.08675394 -0.08675394 -0.08675394 -0.08675394 -0.08675394 -0.75845757\n -0.75845757 -0.75845757 -0.75845757 -0.75845757 -0.07822303 -0.07822303\n -0.07822303 -0.07822303 -0.07822303 -0.75013557 -0.75013557 -0.75013557\n -0.75013557 -0.75013557  0.76633696  0.76633696  0.76633696  0.76633696\n  0.76633696  0.07374234  0.07374234  0.07374234  0.07374234  0.07374234\n  0.74927514  0.74927514  0.74927514  0.74927514  0.74927514  0.05709834\n  0.05709834  0.05709834  0.05709834  0.05709834  0.79192968  0.79192968\n  0.79192968  0.79192968  0.79192968  0.09870834  0.09870834  0.09870834\n  0.09870834  0.09870834  0.80046059  0.80046059  0.80046059  0.80046059\n  0.80046059  0.10703034  0.10703034  0.10703034  0.10703034  0.10703034\n  0.74927514  0.74927514  0.74927514  0.74927514  0.74927514  0.05709834\n  0.05709834  0.05709834  0.05709834  0.05709834]\nrows[1] shape: (10,) values: [1 1 1 1 1 0 0 0 0 0]\nError stacking: all input arrays must have the same shape\n","stderr_tail":"","stdout_sha256":"d57745e3d26096f2d32110ce990d39eaa84ce6b437928f70aa9f493e096a9cb8","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-25.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:29:19.429870Z","duration_s":1.500578,"timed_out":false,"image_before":"dd245bb4-8c28-441a-9851-6a1b7309e08c","image_after":"d8bf3dde-96fb-41db-9ecb-1883a840e707","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-26","seq":26,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-2d280dc3ed94489bb557d2aca28c766c/bin/busybox sh -c 'mkdir -p /RDT/rdt/transformers && cp /opt/receipts-2d280dc3ed94489bb557d2aca28c766c/incoming/433b12e064bbb4cf7d7ccc120f40f6664c2892e9092c65a55aac97ff0f735abb /RDT/rdt/transformers/numerical.py'","path":"rdt/transformers/numerical.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"433b12e064bbb4cf7d7ccc120f40f6664c2892e9092c65a55aac97ff0f735abb","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-26.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:29:28.112086Z","duration_s":0.004626,"timed_out":false,"image_before":"d8bf3dde-96fb-41db-9ecb-1883a840e707","image_after":"aa33da26-b991-4f20-9e4f-526654b2e7dd","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-27","seq":27,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform -xvs 2>&1 | tail -30","path":null,"exit_code":0,"stdout_tail":"============================= test session starts ==============================\nplatform linux -- Python 3.10.19, pytest-9.0.2, pluggy-1.6.0 -- /usr/local/bin/python\ncachedir: .pytest_cache\nrootdir: /RDT\nconfigfile: setup.cfg\nplugins: anyio-4.12.1, Faker-40.4.0, cov-7.0.0\ncollecting ... collected 1 item\n\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform PASSED\n\n=============================== warnings summary ===============================\n../usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428\n  /usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428: PytestConfigWarning: Unknown config option: collect_ignore\n  \n    self._warn_or_fail_if_strict(f\"Unknown config option: {key}\\n\")\n\n../usr/local/lib/python3.10/site-packages/copulas/__init__.py:18\n  /usr/local/lib/python3.10/site-packages/copulas/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n    from pkg_resources import iter_entry_points\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n======================== 1 passed, 2 warnings in 1.33s =========================\n","stderr_tail":"","stdout_sha256":"865d062c8eeeb20755b7fdc0ef3b69918bb2f01db0385cebfa3cf819985f76bc","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-27.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:29:30.391982Z","duration_s":1.8500969999999999,"timed_out":false,"image_before":"aa33da26-b991-4f20-9e4f-526654b2e7dd","image_after":"4b7d7715-f36d-489c-83b7-00058395263d","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-28","seq":28,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer -xvs 2>&1 | tail -60","path":null,"exit_code":0,"stdout_tail":"============================= test session starts ==============================\nplatform linux -- Python 3.10.19, pytest-9.0.2, pluggy-1.6.0 -- /usr/local/bin/python\ncachedir: .pytest_cache\nrootdir: /RDT\nconfigfile: setup.cfg\nplugins: anyio-4.12.1, Faker-40.4.0, cov-7.0.0\ncollecting ... collected 10 items\n\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__fit PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__fit_catch_warnings PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__fit_missing_value_replacement PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__get_current_random_seed_random_states_is_none PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__reverse_transform PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__reverse_transform_helper PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__reverse_transform_missing_value_replacement_missing_value_replacement_from_col PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__reverse_transform_missing_value_replacement_missing_value_replacement_random PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform_missing_value_replacement PASSED\n\n=============================== warnings summary ===============================\n../usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428\n  /usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428: PytestConfigWarning: Unknown config option: collect_ignore\n  \n    self._warn_or_fail_if_strict(f\"Unknown config option: {key}\\n\")\n\n../usr/local/lib/python3.10/site-packages/copulas/__init__.py:18\n  /usr/local/lib/python3.10/site-packages/copulas/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n    from pkg_resources import iter_entry_points\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n======================== 10 passed, 2 warnings in 1.45s ========================\n","stderr_tail":"","stdout_sha256":"81abf81a099b12fa35751aaf598fbb377c759b3d517f211858262c537f6a73eb","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-28.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:29:35.996200Z","duration_s":1.986268,"timed_out":false,"image_before":"4b7d7715-f36d-489c-83b7-00058395263d","image_after":"00d4ac52-4559-48b3-aa03-0216cf074c01","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-29","seq":29,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py -xvs 2>&1 | tail -80","path":null,"exit_code":0,"stdout_tail":"t_numerical.py::TestFloatFormatter::test__reverse_transform_enforce_computer_representation PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__reverse_transform_enforce_min_max_values PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__reverse_transform_enforce_min_max_values_with_nulls PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__reverse_transform_learn_rounding_scheme_false PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__reverse_transform_rounding_big_numbers_type_int PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__reverse_transform_rounding_negative_type_float PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__reverse_transform_rounding_none_dtype_int PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__reverse_transform_rounding_none_with_nulls PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__reverse_transform_rounding_none_with_nulls_dtype_int PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__reverse_transform_rounding_small_numbers PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__reverse_transform_rounding_zero_decimal_places PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__transform PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__validate_values_within_bounds PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__validate_values_within_bounds_floats PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__validate_values_within_bounds_over_maximum PASSED\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__validate_values_within_bounds_under_minimum PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test___init__super_attrs PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test___init__str_distr PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test___init__non_distr PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__get_distributions_copulas_not_installed PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__get_distributions PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__get_univariate_instance PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__get_univariate_tuple PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__get_univariate_class PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__get_univariate_error PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__fit PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__fit_missing_value_generation_from_column PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__fit_catch_warnings PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__copula_transform PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__transform PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__transform_missing_value_generation_is_random PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__reverse_transform PASSED\ntests/unit/transformers/test_numerical.py::TestGaussianNormalizer::test__reverse_transform_missing_value_generation PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__fit PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__fit_catch_warnings PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__fit_missing_value_replacement PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__get_current_random_seed_random_states_is_none PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__reverse_transform PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__reverse_transform_helper PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__reverse_transform_missing_value_replacement_missing_value_replacement_from_col PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__reverse_transform_missing_value_replacement_missing_value_replacement_random PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform PASSED\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__transform_missing_value_replacement PASSED\n\n=============================== warnings summary ===============================\n../usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428\n  /usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428: PytestConfigWarning: Unknown config option: collect_ignore\n  \n    self._warn_or_fail_if_strict(f\"Unknown config option: {key}\\n\")\n\n../usr/local/lib/python3.10/site-packages/copulas/__init__.py:18\n  /usr/local/lib/python3.10/site-packages/copulas/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n    from pkg_resources import iter_entry_points\n\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__fit_learn_rounding_scheme_true_max_decimals\n  /RDT/rdt/transformers/numerical.py:112: UserWarning: No rounding scheme detected for column 'None'. Data will not be rounded.\n    warnings.warn(\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n======================== 58 passed, 3 warnings in 1.45s ========================\n","stderr_tail":"","stdout_sha256":"83cfe30c94feec94409110dd2c94a986f27d35083e6cc13ab7f206d4c2699b45","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-29.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:29:41.507835Z","duration_s":2.046262,"timed_out":false,"image_before":"00d4ac52-4559-48b3-aa03-0216cf074c01","image_after":"02f17ead-1a63-492a-9671-7b3915381cd1","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-30","seq":30,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__fit -xvs 2>&1 | tail -20","path":null,"exit_code":0,"stdout_tail":"cachedir: .pytest_cache\nrootdir: /RDT\nconfigfile: setup.cfg\nplugins: anyio-4.12.1, Faker-40.4.0, cov-7.0.0\ncollecting ... collected 1 item\n\ntests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__fit PASSED\n\n=============================== warnings summary ===============================\n../usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428\n  /usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428: PytestConfigWarning: Unknown config option: collect_ignore\n  \n    self._warn_or_fail_if_strict(f\"Unknown config option: {key}\\n\")\n\n../usr/local/lib/python3.10/site-packages/copulas/__init__.py:18\n  /usr/local/lib/python3.10/site-packages/copulas/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n    from pkg_resources import iter_entry_points\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n======================== 1 passed, 2 warnings in 1.47s =========================\n","stderr_tail":"","stdout_sha256":"83cc41a3e2345aaaf6bdf0eb124d783dae059754e5b9184c352b01ec21199f7c","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-30.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:29:47.169118Z","duration_s":1.933642,"timed_out":false,"image_before":"02f17ead-1a63-492a-9671-7b3915381cd1","image_after":"0ddb071c-1589-4e3e-9a2f-c7677181e5e0","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-31","seq":31,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && git diff rdt/transformers/numerical.py","path":null,"exit_code":0,"stdout_tail":"diff --git a/rdt/transformers/numerical.py b/rdt/transformers/numerical.py\nindex d0edb29..43b522a 100644\n--- a/rdt/transformers/numerical.py\n+++ b/rdt/transformers/numerical.py\n@@ -383,10 +383,13 @@ class ClusterBasedNormalizer(FloatFormatter):\n     \"\"\"Transformer for numerical data using a Bayesian Gaussian Mixture Model.\n \n     This transformation takes a numerical value and transforms it using a Bayesian GMM\n-    model. It generates two outputs, a discrete value which indicates the selected\n+    model. It generates two outputs: a discrete value which indicates the selected\n     'component' of the GMM and a continuous value which represents the normalized value\n     based on the mean and std of the selected component.\n \n+    The ``STD_MULTIPLIER`` attribute (default 4) is used to scale the standard deviation\n+    when normalizing values, ensuring the transformed data falls within a reasonable range.\n+\n     Args:\n         model_missing_values (bool):\n             **DEPRECATED** Whether to create a new column to indicate which values were null or\n@@ -463,7 +466,6 @@ class ClusterBasedNormalizer(FloatFormatter):\n             n_components=self.max_clusters,\n             weight_concentration_prior_type='dirichlet_process',\n             weight_concentration_prior=0.001,\n-            n_init=1,\n             random_state=self._get_current_random_seed()\n         )\n \n@@ -496,8 +498,6 @@ class ClusterBasedNormalizer(FloatFormatter):\n         means = self._bgm_transformer.means_.reshape((1, self.max_clusters))\n \n         stds = np.sqrt(self._bgm_transformer.covariances_).reshape((1, self.max_clusters))\n-        normalized_values = (data - means) / (self.STD_MULTIPLIER * stds)\n-        normalized_values = normalized_values[:, self.valid_component_indicator]\n         component_probs = self._bgm_transformer.predict_proba(data)\n         component_probs = component_probs[:, self.valid_component_indicator]\n \n@@ -510,15 +510,22 @@ class ClusterBasedNormalizer(FloatFormatter):\n                 p=component_prob_t\n             )\n \n-        aranged = np.arange(len(data))\n-        normalized = normalized_values[aranged, selected_component].reshape([-1, 1])\n+        # Map valid component indices to original cluster indices\n+        valid_indices = np.where(self.valid_component_indicator)[0]\n+        selected_cluster = valid_indices[selected_component]\n+\n+        # Use broadcasting: means shape is (1, max_clusters), select per-component means\n+        # Reshape to (n, 1) for proper broadcasting with data (n, 1)\n+        selected_means = means[0, selected_cluster].reshape(-1, 1)  # shape: (n, 1)\n+        selected_stds = stds[0, selected_cluster].reshape(-1, 1)    # shape: (n, 1)\n+        normalized = (data - selected_means) / (self.STD_MULTIPLIER * selected_stds)\n         normalized = np.clip(normalized, -.99, .99)\n-        normalized = normalized[:, 0]\n+        normalized = normalized.reshape([-1, 1])[:, 0]\n         rows = [normalized, selected_component]\n         if self.null_transformer and self.null_transformer.models_missing_values():\n             rows.append(model_missing_values)\n \n-        return np.stack(rows, axis=1)  # noqa: PD013\n+        return np.stack(rows, axis=1)\n \n     def _reverse_transform_helper(self, data):\n         normalized = np.clip(data[:, 0], -1, 1)\n@@ -546,8 +553,6 @@ class ClusterBasedNormalizer(FloatFormatter):\n \n         recovered_data = self._reverse_transform_helper(data)\n         if self.null_transformer and self.null_transformer.models_missing_values():\n-            data = np.stack([recovered_data, data[:, -1]], axis=1)  # noqa: PD013\n-        else:\n-            data = recovered_data\n+            data = np.stack([recovered_data, data[:, -1]], axis=1)\n \n         return super()._reverse_transform(data)\n","stderr_tail":"","stdout_sha256":"abaa65de3255d82e9bda5df7d59a1fda00d58968a8c2bb7f9e06f7e199e08bc3","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-31.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:29:52.955108Z","duration_s":0.005943,"timed_out":false,"image_before":"0ddb071c-1589-4e3e-9a2f-c7677181e5e0","image_after":"c0e63f15-7080-4ac5-8094-a393de7ccdd7","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-32","seq":32,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest tests/unit/transformers/test_numerical.py --tb=short 2>&1 | tail -20","path":null,"exit_code":0,"stdout_tail":"\ntests/unit/transformers/test_numerical.py .............................. [ 51%]\n............................                                             [100%]\n\n=============================== warnings summary ===============================\n../usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428\n  /usr/local/lib/python3.10/site-packages/_pytest/config/__init__.py:1428: PytestConfigWarning: Unknown config option: collect_ignore\n  \n    self._warn_or_fail_if_strict(f\"Unknown config option: {key}\\n\")\n\n../usr/local/lib/python3.10/site-packages/copulas/__init__.py:18\n  /usr/local/lib/python3.10/site-packages/copulas/__init__.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n    from pkg_resources import iter_entry_points\n\ntests/unit/transformers/test_numerical.py::TestFloatFormatter::test__fit_learn_rounding_scheme_true_max_decimals\n  /RDT/rdt/transformers/numerical.py:112: UserWarning: No rounding scheme detected for column 'None'. Data will not be rounded.\n    warnings.warn(\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n======================== 58 passed, 3 warnings in 1.57s ========================\n","stderr_tail":"","stdout_sha256":"1fea224774fa56e4b2b9e487e9420698d8b815d83121df861dd719a2890c417a","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-32.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:29:56.664758Z","duration_s":1.9953049999999999,"timed_out":false,"image_before":"c0e63f15-7080-4ac5-8094-a393de7ccdd7","image_after":"6fd3fda5-5790-4cf9-881a-f245fc71311e","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-33","seq":33,"branch_id":"agent1","kind":"command","cmd":"cd /RDT && python -m pytest \"tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__fit\" -xvs 2>&1 | grep -E \"(PASSED|FAILED|Expected|Actual)\"","path":null,"exit_code":0,"stdout_tail":"tests/unit/transformers/test_numerical.py::TestClusterBasedNormalizer::test__fit PASSED\n","stderr_tail":"","stdout_sha256":"a55ec4191b81b24302edb2a81e5e508748da04832d65c9ae42b41a1de7de65fa","log_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/logs/agent1/agent1-33.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T22:30:02.374582Z","duration_s":1.8875989999999998,"timed_out":false,"image_before":"6fd3fda5-5790-4cf9-881a-f245fc71311e","image_after":"b6bc6384-9661-4233-88f2-d5ef4ab602c4","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-34","seq":34,"branch_id":"agent1","kind":"diff","cmd":"compute patch in executor staging agent1-d81d34e85f4d4f7a8b45ed9ccf32df7d: /opt/homebrew/Cellar/git/2.53.0/bin/git -c core.hooksPath=/dev/null -c core.attributesFile=/dev/null -c diff.external= -c core.quotePath=false add -A && /opt/homebrew/Cellar/git/2.53.0/bin/git -c core.hooksPath=/dev/null -c core.attributesFile=/dev/null -c diff.external= -c core.quotePath=false diff --cached --binary --no-ext-diff --no-textconv --no-renames d1719a9debb6832f751f402fb3c9432c35e2793e","path":null,"exit_code":0,"stdout_tail":"diff --git a/rdt/transformers/numerical.py b/rdt/transformers/numerical.py\nindex d0edb29..43b522a 100644\n--- a/rdt/transformers/numerical.py\n+++ b/rdt/transformers/numerical.py\n@@ -383,10 +383,13 @@ class ClusterBasedNormalizer(FloatFormatter):\n     \"\"\"Transformer for numerical data using a Bayesian Gaussian Mixture Model.\n \n     This transformation takes a numerical value and transforms it using a Bayesian GMM\n-    model. It generates two outputs, a discrete value which indicates the selected\n+    model. It generates two outputs: a discrete value which indicates the selected\n     'component' of the GMM and a continuous value which represents the normalized value\n     based on the mean and std of the selected component.\n \n+    The ``STD_MULTIPLIER`` attribute (default 4) is used to scale the standard deviation\n+    when normalizing values, ensuring the transformed data falls within a reasonable range.\n+\n     Args:\n         model_missing_values (bool):\n             **DEPRECATED** Whether to create a new column to indicate which values were null or\n@@ -463,7 +466,6 @@ class ClusterBasedNormalizer(FloatFormatter):\n             n_components=self.max_clusters,\n             weight_concentration_prior_type='dirichlet_process',\n             weight_concentration_prior=0.001,\n-            n_init=1,\n             random_state=self._get_current_random_seed()\n         )\n \n@@ -496,8 +498,6 @@ class ClusterBasedNormalizer(FloatFormatter):\n         means = self._bgm_transformer.means_.reshape((1, self.max_clusters))\n \n         stds = np.sqrt(self._bgm_transformer.covariances_).reshape((1, self.max_clusters))\n-        normalized_values = (data - means) / (self.STD_MULTIPLIER * stds)\n-        normalized_values = normalized_values[:, self.valid_component_indicator]\n         component_probs = self._bgm_transformer.predict_proba(data)\n         component_probs = component_probs[:, self.valid_component_indicator]\n \n@@ -510,15 +510,22 @@ class ClusterBasedNormalizer(FloatFormatter):\n                 p=component_prob_t\n             )\n \n-        aranged = np.arange(len(data))\n-        normalized = normalized_values[aranged, selected_component].reshape([-1, 1])\n+        # Map valid component indices to original cluster indices\n+        valid_indices = np.where(self.valid_component_indicator)[0]\n+        selected_cluster = valid_indices[selected_component]\n+\n+        # Use broadcasting: means shape is (1, max_clusters), select per-component means\n+        # Reshape to (n, 1) for proper broadcasting with data (n, 1)\n+        selected_means = means[0, selected_cluster].reshape(-1, 1)  # shape: (n, 1)\n+        selected_stds = stds[0, selected_cluster].reshape(-1, 1)    # shape: (n, 1)\n+        normalized = (data - selected_means) / (self.STD_MULTIPLIER * selected_stds)\n         normalized = np.clip(normalized, -.99, .99)\n-        normalized = normalized[:, 0]\n+        normalized = normalized.reshape([-1, 1])[:, 0]\n         rows = [normalized, selected_component]\n         if self.null_transformer and self.null_transformer.models_missing_values():\n             rows.append(model_missing_values)\n \n-        return np.stack(rows, axis=1)  # noqa: PD013\n+        return np.stack(rows, axis=1)\n \n     def _reverse_transform_helper(self, data):\n         normalized = np.clip(data[:, 0], -1, 1)\n@@ -546,8 +553,6 @@ class ClusterBasedNormalizer(FloatFormatter):\n \n         recovered_data = self._reverse_transform_helper(data)\n         if self.null_transformer and self.null_transformer.models_missing_values():\n-            data = np.stack([recovered_data, data[:, -1]], axis=1)  # noqa: PD013\n-        else:\n-            data = recovered_data\n+            data = np.stack([recovered_data, data[:, -1]], axis=1)\n \n         return super()._reverse_transform(data)\n","stderr_tail":"","stdout_sha256":"abaa65de3255d82e9bda5df7d59a1fda00d58968a8c2bb7f9e06f7e199e08bc3","log_path":null,"tree_digest":"ffe7ee6e470151ce2ed466f71793307f5162d62823c36711c5d9b37a70362eaf","tree_download_s":1.7174545840825886,"started_at":"2026-10-03T22:30:14.636504Z","duration_s":0.06399491708725691,"timed_out":false,"image_before":"b6bc6384-9661-4233-88f2-d5ef4ab602c4","image_after":"b6bc6384-9661-4233-88f2-d5ef4ab602c4","junit":null,"diff":{"files":[{"path":"rdt/transformers/numerical.py","added":16,"deleted":11,"category":"source","status":"modified"}],"patch_sha256":"abaa65de3255d82e9bda5df7d59a1fda00d58968a8c2bb7f9e06f7e199e08bc3","patch_path":"~/dev/nebius-hackathon/pilot/v2-arm-lightning/sdv-dev__rdt-704/runs/pilot-sdv-dev__rdt-704-f446a75699/artifacts/agent1/agent1-34.patch"},"patch_sha256":"abaa65de3255d82e9bda5df7d59a1fda00d58968a8c2bb7f9e06f7e199e08bc3","dropped_paths":[],"snapshot_sha":"d1719a9debb6832f751f402fb3c9432c35e2793e"}