Petrosian Correction Grid `nan` Value Bug

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Input In [226], in <cell line: 1>()
----> 1 PetrosianCorrection('full_grid.yaml')

File /mnt/f/lcbg/petrofit/petrofit/petrosian.py:594, in PetrosianCorrection.__init__(self, grid_file)
    592 self._grid_file = grid_file
    593 self.grid = self._read_grid_file()
--> 594 self.regressor = self._train()

File /mnt/f/lcbg/petrofit/petrofit/petrosian.py:674, in PetrosianCorrection._train(self)
    671 N = np.array(N)
    673 clf = DecisionTreeRegressor()
--> 674 clf.fit(X, N)
    675 return clf

File ~/miniconda3/envs/petrofit/lib/python3.10/site-packages/sklearn/tree/_classes.py:1342, in DecisionTreeRegressor.fit(self, X, y, sample_weight, check_input)
   1313 def fit(self, X, y, sample_weight=None, check_input=True):
   1314     """Build a decision tree regressor from the training set (X, y).
   1315 
   1316     Parameters
   (...)
   1339         Fitted estimator.
   1340     """
-> 1342     super().fit(
   1343         X,
   1344         y,
   1345         sample_weight=sample_weight,
   1346         check_input=check_input,
   1347     )
   1348     return self

File ~/miniconda3/envs/petrofit/lib/python3.10/site-packages/sklearn/tree/_classes.py:172, in BaseDecisionTree.fit(self, X, y, sample_weight, check_input)
    170 check_X_params = dict(dtype=DTYPE, accept_sparse="csc")
    171 check_y_params = dict(ensure_2d=False, dtype=None)
--> 172 X, y = self._validate_data(
    173     X, y, validate_separately=(check_X_params, check_y_params)
    174 )
    175 if issparse(X):
    176     X.sort_indices()

File ~/miniconda3/envs/petrofit/lib/python3.10/site-packages/sklearn/base.py:591, in BaseEstimator._validate_data(self, X, y, reset, validate_separately, **check_params)
    589 if "estimator" not in check_X_params:
    590     check_X_params = {**default_check_params, **check_X_params}
--> 591 X = check_array(X, input_name="X", **check_X_params)
    592 if "estimator" not in check_y_params:
    593     check_y_params = {**default_check_params, **check_y_params}

File ~/miniconda3/envs/petrofit/lib/python3.10/site-packages/sklearn/utils/validation.py:899, in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator, input_name)
    893         raise ValueError(
    894             "Found array with dim %d. %s expected <= 2."
    895             % (array.ndim, estimator_name)
    896         )
    898     if force_all_finite:
--> 899         _assert_all_finite(
    900             array,
    901             input_name=input_name,
    902             estimator_name=estimator_name,
    903             allow_nan=force_all_finite == "allow-nan",
    904         )
    906 if ensure_min_samples > 0:
    907     n_samples = _num_samples(array)

File ~/miniconda3/envs/petrofit/lib/python3.10/site-packages/sklearn/utils/validation.py:146, in _assert_all_finite(X, allow_nan, msg_dtype, estimator_name, input_name)
    124         if (
    125             not allow_nan
    126             and estimator_name
   (...)
    130             # Improve the error message on how to handle missing values in
    131             # scikit-learn.
    132             msg_err += (
    133                 f"\n{estimator_name} does not accept missing values"
    134                 " encoded as NaN natively. For supervised learning, you might want"
   (...)
    144                 "#estimators-that-handle-nan-values"
    145             )
--> 146         raise ValueError(msg_err)
    148 # for object dtype data, we only check for NaNs (GH-13254)
    149 elif X.dtype == np.dtype("object") and not allow_nan:

ValueError: Input X contains infinity or a value too large for dtype('float32').
PetroFit / petrofit

Petrosian Correction Grid `nan` Value Bug #162
