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[python-package] prefix is_numpy_1d_array with _ (#5520)
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Madnex authored Oct 7, 2022
1 parent 2230134 commit 3eb68e8
Showing 1 changed file with 6 additions and 6 deletions.
12 changes: 6 additions & 6 deletions python-package/lightgbm/basic.py
Original file line number Diff line number Diff line change
Expand Up @@ -177,7 +177,7 @@ def _is_numeric(obj: Any) -> bool:
return False


def is_numpy_1d_array(data: Any) -> bool:
def _is_numpy_1d_array(data: Any) -> bool:
"""Check whether data is a numpy 1-D array."""
return isinstance(data, np.ndarray) and len(data.shape) == 1

Expand Down Expand Up @@ -205,7 +205,7 @@ def is_1d_list(data: Any) -> bool:
def _is_1d_collection(data: Any) -> bool:
"""Check whether data is a 1-D collection."""
return (
is_numpy_1d_array(data)
_is_numpy_1d_array(data)
or is_numpy_column_array(data)
or is_1d_list(data)
or isinstance(data, pd_Series)
Expand All @@ -214,7 +214,7 @@ def _is_1d_collection(data: Any) -> bool:

def list_to_1d_numpy(data, dtype=np.float32, name='list'):
"""Convert data to numpy 1-D array."""
if is_numpy_1d_array(data):
if _is_numpy_1d_array(data):
return cast_numpy_array_to_dtype(data, dtype)
elif is_numpy_column_array(data):
_log_warning('Converting column-vector to 1d array')
Expand Down Expand Up @@ -320,7 +320,7 @@ def param_dict_to_str(data: Optional[Dict[str, Any]]) -> str:
return ""
pairs = []
for key, val in data.items():
if isinstance(val, (list, tuple, set)) or is_numpy_1d_array(val):
if isinstance(val, (list, tuple, set)) or _is_numpy_1d_array(val):
def to_string(x):
if isinstance(x, list):
return f"[{','.join(map(str, x))}]"
Expand Down Expand Up @@ -515,7 +515,7 @@ def c_float_array(data):
"""Get pointer of float numpy array / list."""
if is_1d_list(data):
data = np.array(data, copy=False)
if is_numpy_1d_array(data):
if _is_numpy_1d_array(data):
data = convert_from_sliced_object(data)
assert data.flags.c_contiguous
if data.dtype == np.float32:
Expand All @@ -535,7 +535,7 @@ def c_int_array(data):
"""Get pointer of int numpy array / list."""
if is_1d_list(data):
data = np.array(data, copy=False)
if is_numpy_1d_array(data):
if _is_numpy_1d_array(data):
data = convert_from_sliced_object(data)
assert data.flags.c_contiguous
if data.dtype == np.int32:
Expand Down

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