Test cases fail due to ValueErrror

[kimusaku]

Describe the bug Currently, executing pytest causes ValueError.

To Reproduce run the following command on main branch:

pytest -k test_classifier_category_binary_num_proba[target_category_binary_num-auc]

script

``` _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ tests/sapientml/test_generatedcode.py:107: in _execute generator.generate_pipeline(dataset, task) sapientml_core/generator.py:219: in generate_pipeline dataset, sapientml_results = self.generate_code(dataset, task) sapientml_core/generator.py:265: in generate_code dataset_summary = summarize_dataset(df, task) # type: ignore sapientml_core/params.py:403: in summarize_dataset meta_features_m = generate_model_meta_features(df_train, task.target_columns, is_clf_task) sapientml_core/meta_features.py:1178: in generate_model_meta_features meta_feature_dict = _collect_model_meta_features(user_training, target_column_name) sapientml_core/meta_features.py:275: in _collect_model_meta_features feature_dict.update(_collect_csv_column_with_ttest(dataX, datay[catg_target_columns])) sapientml_core/meta_features.py:495: in _collect_csv_column_with_ttest p = _get_ttest_pvalue(column, yc) sapientml_core/meta_features.py:455: in _get_ttest_pvalue _, p = scipy.stats.ttest_ind(c1, c2, equal_var=False) venv-split-before-transform/lib/python3.10/site-packages/scipy/stats/_axis_nan_policy.py:573: in axis_nan_policy_wrapper res = hypotest_fun_out(*samples, **kwds) venv-split-before-transform/lib/python3.10/site-packages/scipy/stats/_stats_py.py:7005: in ttest_ind v1 = _var(a, axis, ddof=1) venv-split-before-transform/lib/python3.10/site-packages/scipy/stats/_stats_py.py:1110: in _var var = _moment(x, 2, axis, mean=mean, xp=xp) venv-split-before-transform/lib/python3.10/site-packages/scipy/stats/_stats_py.py:1080: in _moment eps = xp.finfo(dtype).eps * 10 _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ cls = , dtype = def __new__(cls, dtype): try: obj = cls._finfo_cache.get(dtype) # most common path if obj is not None: return obj except TypeError: pass if dtype is None: # Deprecated in NumPy 1.25, 2023-01-16 warnings.warn( "finfo() dtype cannot be None. This behavior will " "raise an error in the future. (Deprecated in NumPy 1.25)", DeprecationWarning, stacklevel=2 ) try: dtype = numeric.dtype(dtype) except TypeError: # In case a float instance was given dtype = numeric.dtype(type(dtype)) obj = cls._finfo_cache.get(dtype) if obj is not None: return obj dtypes = [dtype] newdtype = numeric.obj2sctype(dtype) if newdtype is not dtype: dtypes.append(newdtype) dtype = newdtype if not issubclass(dtype, numeric.inexact): > raise ValueError("data type %r not inexact" % (dtype)) E ValueError: data type not inexact venv-split-before-transform/lib/python3.10/site-packages/numpy/core/getlimits.py:516: ValueError ==================================================================== short test summary info ===================================================================== FAILED tests/sapientml/test_generatedcode.py::test_classifier_category_binary_num_proba[target_category_binary_num-auc] - ValueError: data type not inexact ```

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