Try defining notnan

pandas/_libs/src/headers/cmath

@@ -8,9 +8,14 @@
 namespace std {
   __inline int isnan(double x) { return _isnan(x); }
   __inline int signbit(double num) { return _copysign(1.0, num) < 0; }
+  __inline int notnan(double x) { return not isnan(x); }
 }
 #else
 #include <cmath>
-#endif
 
+namespace std {
+  __inline int notnan(double x) { return x == x; }
+}
+
+#endif
 #endif

pandas/_libs/window.pyx

@@ -15,6 +15,7 @@ cnp.import_array()
 
 cdef extern from "src/headers/cmath" namespace "std":
     bint isnan(double) nogil
+    bint notnan(double) nogil
     int signbit(double) nogil
     double sqrt(double x) nogil
 
@@ -381,21 +382,21 @@ def roll_count(ndarray[double_t] input, int64_t win, int64_t minp,
                 count_x = 0.0
                 for j in range(s, e):
                     val = input[j]
-                    if not isnan(val):
+                    if notnan(val):
                         count_x += 1.0
 
             else:
 
                 # calculate deletes
                 for j in range(start[i - 1], s):
                     val = input[j]
-                    if not isnan(val):
+                    if notnan(val):
                         count_x -= 1.0
 
                 # calculate adds
                 for j in range(end[i - 1], e):
                     val = input[j]
-                    if not isnan(val):
+                    if notnan(val):
                         count_x += 1.0
 
             if count_x >= minp:
@@ -424,15 +425,15 @@ cdef inline void add_sum(double val, int64_t *nobs, double *sum_x) nogil:
     """ add a value from the sum calc """
 
     # Not NaN
-    if not isnan(val):
+    if notnan(val):
         nobs[0] = nobs[0] + 1
         sum_x[0] = sum_x[0] + val
 
 
 cdef inline void remove_sum(double val, int64_t *nobs, double *sum_x) nogil:
     """ remove a value from the sum calc """
 
-    if not isnan(val):
+    if notnan(val):
         nobs[0] = nobs[0] - 1
         sum_x[0] = sum_x[0] - val
 
@@ -538,7 +539,7 @@ cdef inline void add_mean(double val, Py_ssize_t *nobs, double *sum_x,
     """ add a value from the mean calc """
 
     # Not NaN
-    if not isnan(val):
+    if notnan(val):
         nobs[0] = nobs[0] + 1
         sum_x[0] = sum_x[0] + val
         if signbit(val):
@@ -549,7 +550,7 @@ cdef inline void remove_mean(double val, Py_ssize_t *nobs, double *sum_x,
                              Py_ssize_t *neg_ct) nogil:
     """ remove a value from the mean calc """
 
-    if not isnan(val):
+    if notnan(val):
         nobs[0] = nobs[0] - 1
         sum_x[0] = sum_x[0] - val
         if signbit(val):
@@ -671,7 +672,7 @@ cdef inline void remove_var(double val, double *nobs, double *mean_x,
     """ remove a value from the var calc """
     cdef double delta
 
-    if not isnan(val):
+    if notnan(val):
         nobs[0] = nobs[0] - 1
         if nobs[0]:
             # a part of Welford's method for the online variance-calculation
@@ -759,7 +760,7 @@ def roll_var(ndarray[double_t] input, int64_t win, int64_t minp,
                 val = input[i]
                 prev = input[i - win]
 
-                if not isnan(val):
+                if notnan(val):
                     if prev == prev:
 
                         # Adding one observation and removing another one
@@ -821,7 +822,7 @@ cdef inline void add_skew(double val, int64_t *nobs, double *x, double *xx,
     """ add a value from the skew calc """
 
     # Not NaN
-    if not isnan(val):
+    if notnan(val):
         nobs[0] = nobs[0] + 1
 
         # seriously don't ask me why this is faster
@@ -835,7 +836,7 @@ cdef inline void remove_skew(double val, int64_t *nobs, double *x, double *xx,
     """ remove a value from the skew calc """
 
     # Not NaN
-    if not isnan(val):
+    if notnan(val):
         nobs[0] = nobs[0] - 1
 
         # seriously don't ask me why this is faster
@@ -958,7 +959,7 @@ cdef inline void add_kurt(double val, int64_t *nobs, double *x, double *xx,
     """ add a value from the kurotic calc """
 
     # Not NaN
-    if not isnan(val):
+    if notnan(val):
         nobs[0] = nobs[0] + 1
 
         # seriously don't ask me why this is faster
@@ -973,7 +974,7 @@ cdef inline void remove_kurt(double val, int64_t *nobs, double *x, double *xx,
     """ remove a value from the kurotic calc """
 
     # Not NaN
-    if not isnan(val):
+    if notnan(val):
         nobs[0] = nobs[0] - 1
 
         # seriously don't ask me why this is faster
@@ -1088,7 +1089,7 @@ def roll_median_c(ndarray[float64_t] input, int64_t win, int64_t minp,
 
                 # setup
                 val = input[i]
-                if not isnan(val):
+                if notnan(val):
                     nobs += 1
                     err = skiplist_insert(sl, val) != 1
                     if err:
@@ -1099,14 +1100,14 @@ def roll_median_c(ndarray[float64_t] input, int64_t win, int64_t minp,
                 # calculate deletes
                 for j in range(start[i - 1], s):
                     val = input[j]
-                    if not isnan(val):
+                    if notnan(val):
                         skiplist_remove(sl, val)
                         nobs -= 1
 
                 # calculate adds
                 for j in range(end[i - 1], e):
                     val = input[j]
-                    if not isnan(val):
+                    if notnan(val):
                         nobs += 1
                         err = skiplist_insert(sl, val) != 1
                         if err:
@@ -1471,7 +1472,7 @@ def roll_quantile(ndarray[float64_t, cast=True] input, int64_t win,
 
                 # setup
                 val = input[i]
-                if not isnan(val):
+                if notnan(val):
                     nobs += 1
                     skiplist_insert(skiplist, val)
 
@@ -1480,14 +1481,14 @@ def roll_quantile(ndarray[float64_t, cast=True] input, int64_t win,
                 # calculate deletes
                 for j in range(start[i - 1], s):
                     val = input[j]
-                    if not isnan(val):
+                    if notnan(val):
                         skiplist_remove(skiplist, val)
                         nobs -= 1
 
                 # calculate adds
                 for j in range(end[i - 1], e):
                     val = input[j]
-                    if not isnan(val):
+                    if notnan(val):
                         nobs += 1
                         skiplist_insert(skiplist, val)