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Merged
merged 1 commit into from
Jan 30, 2022
Merged

BLD: remove MSVC workaround #45008

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48 changes: 0 additions & 48 deletions pandas/_libs/src/headers/cmath
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64 changes: 31 additions & 33 deletions pandas/_libs/window/aggregations.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,11 @@

import cython

from libc.math cimport round
from libc.math cimport (
round,
signbit,
sqrt,
)
from libcpp.deque cimport deque

from pandas._libs.algos cimport TiebreakEnumType
Expand All @@ -19,14 +23,8 @@ from numpy cimport (

cnp.import_array()


cdef extern from "../src/headers/cmath" namespace "std":
bint isnan(float64_t) nogil
bint notnan(float64_t) nogil
int signbit(float64_t) nogil
float64_t sqrt(float64_t x) nogil

from pandas._libs.algos import is_monotonic

from pandas._libs.dtypes cimport numeric_t


Expand Down Expand Up @@ -94,7 +92,7 @@ cdef inline void add_sum(float64_t val, int64_t *nobs, float64_t *sum_x,
float64_t y, t

# Not NaN
if notnan(val):
if val == val:
nobs[0] = nobs[0] + 1
y = val - compensation[0]
t = sum_x[0] + y
Expand All @@ -110,7 +108,7 @@ cdef inline void remove_sum(float64_t val, int64_t *nobs, float64_t *sum_x,
float64_t y, t

# Not NaN
if notnan(val):
if val == val:
nobs[0] = nobs[0] - 1
y = - val - compensation[0]
t = sum_x[0] + y
Expand Down Expand Up @@ -197,7 +195,7 @@ cdef inline void add_mean(float64_t val, Py_ssize_t *nobs, float64_t *sum_x,
float64_t y, t

# Not NaN
if notnan(val):
if val == val:
nobs[0] = nobs[0] + 1
y = val - compensation[0]
t = sum_x[0] + y
Expand All @@ -213,7 +211,7 @@ cdef inline void remove_mean(float64_t val, Py_ssize_t *nobs, float64_t *sum_x,
cdef:
float64_t y, t

if notnan(val):
if val == val:
nobs[0] = nobs[0] - 1
y = - val - compensation[0]
t = sum_x[0] + y
Expand Down Expand Up @@ -300,8 +298,8 @@ cdef inline void add_var(float64_t val, float64_t *nobs, float64_t *mean_x,
cdef:
float64_t delta, prev_mean, y, t

# `isnan` instead of equality as fix for GH-21813, msvc 2017 bug
if isnan(val):
# GH#21813, if msvc 2017 bug is resolved, we should be OK with != instead of `isnan`
if val != val:
return

nobs[0] = nobs[0] + 1
Expand All @@ -325,7 +323,7 @@ cdef inline void remove_var(float64_t val, float64_t *nobs, float64_t *mean_x,
""" remove a value from the var calc """
cdef:
float64_t delta, prev_mean, y, t
if notnan(val):
if val == val:
nobs[0] = nobs[0] - 1
if nobs[0]:
# Welford's method for the online variance-calculation
Expand Down Expand Up @@ -450,7 +448,7 @@ cdef inline void add_skew(float64_t val, int64_t *nobs,
float64_t y, t

# Not NaN
if notnan(val):
if val == val:
nobs[0] = nobs[0] + 1

y = val - compensation_x[0]
Expand Down Expand Up @@ -478,7 +476,7 @@ cdef inline void remove_skew(float64_t val, int64_t *nobs,
float64_t y, t

# Not NaN
if notnan(val):
if val == val:
nobs[0] = nobs[0] - 1

y = - val - compensation_x[0]
Expand Down Expand Up @@ -520,7 +518,7 @@ def roll_skew(ndarray[float64_t] values, ndarray[int64_t] start,
with nogil:
for i in range(0, N):
val = values_copy[i]
if notnan(val):
if val == val:
nobs_mean += 1
sum_val += val
mean_val = sum_val / nobs_mean
Expand Down Expand Up @@ -623,7 +621,7 @@ cdef inline void add_kurt(float64_t val, int64_t *nobs,
float64_t y, t

# Not NaN
if notnan(val):
if val == val:
nobs[0] = nobs[0] + 1

y = val - compensation_x[0]
Expand Down Expand Up @@ -656,7 +654,7 @@ cdef inline void remove_kurt(float64_t val, int64_t *nobs,
float64_t y, t

# Not NaN
if notnan(val):
if val == val:
nobs[0] = nobs[0] - 1

y = - val - compensation_x[0]
Expand Down Expand Up @@ -702,7 +700,7 @@ def roll_kurt(ndarray[float64_t] values, ndarray[int64_t] start,
with nogil:
for i in range(0, N):
val = values_copy[i]
if notnan(val):
if val == val:
nobs_mean += 1
sum_val += val
mean_val = sum_val / nobs_mean
Expand Down Expand Up @@ -796,7 +794,7 @@ def roll_median_c(const float64_t[:] values, ndarray[int64_t] start,
# setup
for j in range(s, e):
val = values[j]
if notnan(val):
if val == val:
nobs += 1
err = skiplist_insert(sl, val) == -1
if err:
Expand All @@ -807,7 +805,7 @@ def roll_median_c(const float64_t[:] values, ndarray[int64_t] start,
# calculate adds
for j in range(end[i - 1], e):
val = values[j]
if notnan(val):
if val == val:
nobs += 1
err = skiplist_insert(sl, val) == -1
if err:
Expand All @@ -816,7 +814,7 @@ def roll_median_c(const float64_t[:] values, ndarray[int64_t] start,
# calculate deletes
for j in range(start[i - 1], s):
val = values[j]
if notnan(val):
if val == val:
skiplist_remove(sl, val)
nobs -= 1
if nobs >= minp:
Expand Down Expand Up @@ -1077,22 +1075,22 @@ def roll_quantile(const float64_t[:] values, ndarray[int64_t] start,
# setup
for j in range(s, e):
val = values[j]
if notnan(val):
if val == val:
nobs += 1
skiplist_insert(skiplist, val)

else:
# calculate adds
for j in range(end[i - 1], e):
val = values[j]
if notnan(val):
if val == val:
nobs += 1
skiplist_insert(skiplist, val)

# calculate deletes
for j in range(start[i - 1], s):
val = values[j]
if notnan(val):
if val == val:
skiplist_remove(skiplist, val)
nobs -= 1
if nobs >= minp:
Expand Down Expand Up @@ -1202,7 +1200,7 @@ def roll_rank(const float64_t[:] values, ndarray[int64_t] start,
# setup
for j in range(s, e):
val = values[j] if ascending else -values[j]
if notnan(val):
if val == val:
nobs += 1
rank = skiplist_insert(skiplist, val)
if rank == -1:
Expand All @@ -1229,14 +1227,14 @@ def roll_rank(const float64_t[:] values, ndarray[int64_t] start,
# calculate deletes
for j in range(start[i - 1], s):
val = values[j] if ascending else -values[j]
if notnan(val):
if val == val:
skiplist_remove(skiplist, val)
nobs -= 1

# calculate adds
for j in range(end[i - 1], e):
val = values[j] if ascending else -values[j]
if notnan(val):
if val == val:
nobs += 1
rank = skiplist_insert(skiplist, val)
if rank == -1:
Expand Down Expand Up @@ -1472,7 +1470,7 @@ cdef inline void add_weighted_var(float64_t val,
cdef:
float64_t temp, q, r

if isnan(val):
if val != val:
return

nobs[0] = nobs[0] + 1
Expand Down Expand Up @@ -1518,7 +1516,7 @@ cdef inline void remove_weighted_var(float64_t val,
cdef:
float64_t temp, q, r

if notnan(val):
if val == val:
nobs[0] = nobs[0] - 1

if nobs[0]:
Expand Down Expand Up @@ -1588,7 +1586,7 @@ def roll_weighted_var(const float64_t[:] values, const float64_t[:] weights,
w = weights[i % win_n]
pre_w = weights[(i - win_n) % win_n]

if notnan(val):
if val == val:
if pre_val == pre_val:
remove_weighted_var(pre_val, pre_w, &t,
&sum_w, &mean, &nobs)
Expand Down