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REF: separate out indexer/mask preprocessing code in algorithms.take_nd #39728

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merged 1 commit into from
Feb 10, 2021
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REF: separate out indexer/mask preprocessing code in algorithms.take_nd #39728

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64 changes: 37 additions & 27 deletions pandas/core/algorithms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1661,6 +1661,40 @@ def take(arr, indices, axis: int = 0, allow_fill: bool = False, fill_value=None)
return result


def _take_preprocess_indexer_and_fill_value(
arr, indexer, axis, out, fill_value, allow_fill
):
mask_info = None

if indexer is None:
indexer = np.arange(arr.shape[axis], dtype=np.int64)
dtype, fill_value = arr.dtype, arr.dtype.type()
else:
indexer = ensure_int64(indexer, copy=False)
if not allow_fill:
dtype, fill_value = arr.dtype, arr.dtype.type()
mask_info = None, False
else:
# check for promotion based on types only (do this first because
# it's faster than computing a mask)
dtype, fill_value = maybe_promote(arr.dtype, fill_value)
if dtype != arr.dtype and (out is None or out.dtype != dtype):
# check if promotion is actually required based on indexer
mask = indexer == -1
needs_masking = mask.any()
mask_info = mask, needs_masking
if needs_masking:
if out is not None and out.dtype != dtype:
raise TypeError("Incompatible type for fill_value")
else:
# if not, then depromote, set fill_value to dummy
# (it won't be used but we don't want the cython code
# to crash when trying to cast it to dtype)
dtype, fill_value = arr.dtype, arr.dtype.type()

return indexer, dtype, fill_value, mask_info


def take_nd(
arr,
indexer,
Expand Down Expand Up @@ -1700,8 +1734,6 @@ def take_nd(
subarray : array-like
May be the same type as the input, or cast to an ndarray.
"""
mask_info = None

if fill_value is lib.no_default:
fill_value = na_value_for_dtype(arr.dtype, compat=False)

Expand All @@ -1712,31 +1744,9 @@ def take_nd(
arr = extract_array(arr)
arr = np.asarray(arr)

if indexer is None:
indexer = np.arange(arr.shape[axis], dtype=np.int64)
dtype, fill_value = arr.dtype, arr.dtype.type()
else:
indexer = ensure_int64(indexer, copy=False)
if not allow_fill:
dtype, fill_value = arr.dtype, arr.dtype.type()
mask_info = None, False
else:
# check for promotion based on types only (do this first because
# it's faster than computing a mask)
dtype, fill_value = maybe_promote(arr.dtype, fill_value)
if dtype != arr.dtype and (out is None or out.dtype != dtype):
# check if promotion is actually required based on indexer
mask = indexer == -1
needs_masking = mask.any()
mask_info = mask, needs_masking
if needs_masking:
if out is not None and out.dtype != dtype:
raise TypeError("Incompatible type for fill_value")
else:
# if not, then depromote, set fill_value to dummy
# (it won't be used but we don't want the cython code
# to crash when trying to cast it to dtype)
dtype, fill_value = arr.dtype, arr.dtype.type()
indexer, dtype, fill_value, mask_info = _take_preprocess_indexer_and_fill_value(
arr, indexer, axis, out, fill_value, allow_fill
)

flip_order = False
if arr.ndim == 2 and arr.flags.f_contiguous:
Expand Down