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Merged
merged 4 commits into from
Apr 5, 2020
Merged

CLN: Added static types _libs/algos #33271

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12b346a
CLN: Added static types
Apr 3, 2020
bb7ed3b
Merge remote-tracking branch 'upstream/master' into CLN-StaticTypes-_…
Apr 4, 2020
4380d59
Revert cdef on the dict
Apr 4, 2020
0e60fb5
Revert cdef of lim
Apr 4, 2020
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39 changes: 15 additions & 24 deletions pandas/_libs/algos.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -50,18 +50,17 @@ from pandas._libs.khash cimport (

import pandas._libs.missing as missing

cdef float64_t FP_ERR = 1e-13

cdef float64_t NaN = <float64_t>np.NaN

cdef int64_t NPY_NAT = get_nat()
cdef:
float64_t FP_ERR = 1e-13
float64_t NaN = <float64_t>np.NaN
int64_t NPY_NAT = get_nat()

tiebreakers = {
'average': TIEBREAK_AVERAGE,
'min': TIEBREAK_MIN,
'max': TIEBREAK_MAX,
'first': TIEBREAK_FIRST,
'dense': TIEBREAK_DENSE,
"average": TIEBREAK_AVERAGE,
"min": TIEBREAK_MIN,
"max": TIEBREAK_MAX,
"first": TIEBREAK_FIRST,
"dense": TIEBREAK_DENSE,
}


Expand Down Expand Up @@ -120,6 +119,7 @@ cpdef ndarray[int64_t, ndim=1] unique_deltas(const int64_t[:] arr):
kh_int64_t *table
int ret = 0
list uniques = []
ndarray[int64_t, ndim=1] result

table = kh_init_int64()
kh_resize_int64(table, 10)
Expand Down Expand Up @@ -261,7 +261,7 @@ def kth_smallest(numeric[:] a, Py_ssize_t k) -> numeric:

@cython.boundscheck(False)
@cython.wraparound(False)
def nancorr(const float64_t[:, :] mat, bint cov=0, minp=None):
def nancorr(const float64_t[:, :] mat, bint cov=False, minp=None):
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The generated C code for this was not changed

cdef:
Py_ssize_t i, j, xi, yi, N, K
bint minpv
Expand Down Expand Up @@ -325,7 +325,7 @@ def nancorr(const float64_t[:, :] mat, bint cov=0, minp=None):

@cython.boundscheck(False)
@cython.wraparound(False)
def nancorr_spearman(const float64_t[:, :] mat, Py_ssize_t minp=1):
def nancorr_spearman(const float64_t[:, :] mat, Py_ssize_t minp=1) -> ndarray:
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Does adding these return annotations to the def like this change anything?

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for functions that arent cdef/cpdef its ornamental

cdef:
Py_ssize_t i, j, xi, yi, N, K
ndarray[float64_t, ndim=2] result
Expand Down Expand Up @@ -581,7 +581,7 @@ D

@cython.boundscheck(False)
@cython.wraparound(False)
def backfill(ndarray[algos_t] old, ndarray[algos_t] new, limit=None):
def backfill(ndarray[algos_t] old, ndarray[algos_t] new, limit=None) -> ndarray:
cdef:
Py_ssize_t i, j, nleft, nright
ndarray[int64_t, ndim=1] indexer
Expand Down Expand Up @@ -810,18 +810,14 @@ def rank_1d(
"""
cdef:
Py_ssize_t i, j, n, dups = 0, total_tie_count = 0, non_na_idx = 0

ndarray[rank_t] sorted_data, values

ndarray[float64_t] ranks
ndarray[int64_t] argsorted
ndarray[uint8_t, cast=True] sorted_mask

rank_t val, nan_value

float64_t sum_ranks = 0
int tiebreak = 0
bint keep_na = 0
bint keep_na = False
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The generated C code for this was not changed

bint isnan, condition
float64_t count = 0.0

Expand Down Expand Up @@ -1034,19 +1030,14 @@ def rank_2d(
"""
cdef:
Py_ssize_t i, j, z, k, n, dups = 0, total_tie_count = 0

Py_ssize_t infs

ndarray[float64_t, ndim=2] ranks
ndarray[rank_t, ndim=2] values

ndarray[int64_t, ndim=2] argsorted

rank_t val, nan_value

float64_t sum_ranks = 0
int tiebreak = 0
bint keep_na = 0
bint keep_na = False
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The generated C code for this was not changed

float64_t count = 0.0
bint condition, skip_condition

Expand Down