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Merged
merged 1 commit into from
Apr 27, 2022
Merged

PERF: use C version of np.empty #46878

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28 changes: 14 additions & 14 deletions pandas/_libs/lib.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -873,7 +873,7 @@ def get_level_sorter(
"""
cdef:
Py_ssize_t i, l, r
ndarray[intp_t, ndim=1] out = np.empty(len(codes), dtype=np.intp)
ndarray[intp_t, ndim=1] out = cnp.PyArray_EMPTY(1, codes.shape, cnp.NPY_INTP, 0)

for i in range(len(starts) - 1):
l, r = starts[i], starts[i + 1]
Expand Down Expand Up @@ -2255,11 +2255,11 @@ def maybe_convert_numeric(
int status, maybe_int
Py_ssize_t i, n = values.size
Seen seen = Seen(coerce_numeric)
ndarray[float64_t, ndim=1] floats = np.empty(n, dtype='f8')
ndarray[complex128_t, ndim=1] complexes = np.empty(n, dtype='c16')
ndarray[int64_t, ndim=1] ints = np.empty(n, dtype='i8')
ndarray[uint64_t, ndim=1] uints = np.empty(n, dtype='u8')
ndarray[uint8_t, ndim=1] bools = np.empty(n, dtype='u1')
ndarray[float64_t, ndim=1] floats = cnp.PyArray_EMPTY(1, values.shape, cnp.NPY_FLOAT64, 0)
ndarray[complex128_t, ndim=1] complexes = cnp.PyArray_EMPTY(1, values.shape, cnp.NPY_COMPLEX128, 0)
ndarray[int64_t, ndim=1] ints = cnp.PyArray_EMPTY(1, values.shape, cnp.NPY_INT64, 0)
ndarray[uint64_t, ndim=1] uints = cnp.PyArray_EMPTY(1, values.shape, cnp.NPY_UINT64, 0)
ndarray[uint8_t, ndim=1] bools = cnp.PyArray_EMPTY(1, values.shape, cnp.NPY_UINT8, 0)
ndarray[uint8_t, ndim=1] mask = np.zeros(n, dtype="u1")
float64_t fval
bint allow_null_in_int = convert_to_masked_nullable
Expand Down Expand Up @@ -2479,11 +2479,11 @@ def maybe_convert_objects(ndarray[object] objects,

n = len(objects)

floats = np.empty(n, dtype='f8')
complexes = np.empty(n, dtype='c16')
ints = np.empty(n, dtype='i8')
uints = np.empty(n, dtype='u8')
bools = np.empty(n, dtype=np.uint8)
floats = cnp.PyArray_EMPTY(1, objects.shape, cnp.NPY_FLOAT64, 0)
complexes = cnp.PyArray_EMPTY(1, objects.shape, cnp.NPY_COMPLEX128, 0)
ints = cnp.PyArray_EMPTY(1, objects.shape, cnp.NPY_INT64, 0)
uints = cnp.PyArray_EMPTY(1, objects.shape, cnp.NPY_UINT64, 0)
bools = cnp.PyArray_EMPTY(1, objects.shape, cnp.NPY_UINT8, 0)
mask = np.full(n, False)

if convert_datetime:
Expand Down Expand Up @@ -2785,7 +2785,7 @@ cdef _infer_all_nats(dtype, ndarray datetimes, ndarray timedeltas):
else:
# ExtensionDtype
cls = dtype.construct_array_type()
i8vals = np.empty(len(datetimes), dtype="i8")
i8vals = cnp.PyArray_EMPTY(1, datetimes.shape, cnp.NPY_INT64, 0)
i8vals.fill(NPY_NAT)
result = cls(i8vals, dtype=dtype)
return result
Expand Down Expand Up @@ -2888,7 +2888,7 @@ def map_infer(
object val

n = len(arr)
result = np.empty(n, dtype=object)
result = cnp.PyArray_EMPTY(1, arr.shape, cnp.NPY_OBJECT, 0)
for i in range(n):
if ignore_na and checknull(arr[i]):
result[i] = arr[i]
Expand Down Expand Up @@ -3083,7 +3083,7 @@ cpdef ndarray eq_NA_compat(ndarray[object] arr, object key):
key is assumed to have `not isna(key)`
"""
cdef:
ndarray[uint8_t, cast=True] result = np.empty(len(arr), dtype=bool)
ndarray[uint8_t, cast=True] result = cnp.PyArray_EMPTY(arr.ndim, arr.shape, cnp.NPY_BOOL, 0)
Py_ssize_t i
object item

Expand Down
8 changes: 4 additions & 4 deletions pandas/_libs/tslib.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -123,7 +123,7 @@ def format_array_from_datetime(
ndarray[int64_t] consider_values
bint show_ms = False, show_us = False, show_ns = False
bint basic_format = False
ndarray[object] result = np.empty(N, dtype=object)
ndarray[object] result = cnp.PyArray_EMPTY(values.ndim, values.shape, cnp.NPY_OBJECT, 0)
object ts, res
npy_datetimestruct dts

Expand Down Expand Up @@ -349,7 +349,7 @@ def array_with_unit_to_datetime(
# and are in ignore mode
# redo as object

oresult = np.empty(n, dtype=object)
oresult = cnp.PyArray_EMPTY(values.ndim, values.shape, cnp.NPY_OBJECT, 0)
for i in range(n):
val = values[i]

Expand Down Expand Up @@ -668,7 +668,7 @@ cdef ndarray[object] ignore_errors_out_of_bounds_fallback(ndarray[object] values
Py_ssize_t i, n = len(values)
object val

oresult = np.empty(n, dtype=object)
oresult = cnp.PyArray_EMPTY(values.ndim, values.shape, cnp.NPY_OBJECT, 0)

for i in range(n):
val = values[i]
Expand Down Expand Up @@ -730,7 +730,7 @@ cdef _array_to_datetime_object(

assert is_raise or is_ignore or is_coerce

oresult = np.empty(n, dtype=object)
oresult = cnp.PyArray_EMPTY(values.ndim, values.shape, cnp.NPY_OBJECT, 0)

# We return an object array and only attempt to parse:
# 1) NaT or NaT-like values
Expand Down
4 changes: 2 additions & 2 deletions pandas/_libs/tslibs/period.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -1057,7 +1057,7 @@ def period_asfreq_arr(ndarray[int64_t] arr, int freq1, int freq2, bint end):
cdef:
Py_ssize_t n = len(arr)
Py_ssize_t increment = arr.strides[0] // 8
ndarray[int64_t] result = np.empty(n, dtype=np.int64)
ndarray[int64_t] result = cnp.PyArray_EMPTY(arr.ndim, arr.shape, cnp.NPY_INT64, 0)

_period_asfreq(
<int64_t*>cnp.PyArray_DATA(arr),
Expand Down Expand Up @@ -1440,7 +1440,7 @@ def extract_ordinals(ndarray values, freq) -> np.ndarray:
cdef:
Py_ssize_t i, n = values.size
int64_t ordinal
ndarray ordinals = np.empty((<object>values).shape, dtype=np.int64)
ndarray ordinals = cnp.PyArray_EMPTY(values.ndim, values.shape, cnp.NPY_INT64, 0)
cnp.broadcast mi = cnp.PyArray_MultiIterNew2(ordinals, values)
object p

Expand Down