use numpy isna function, remove unneeded lines

Author: CloseChoice

pandas/_libs/groupby.pyx

@@ -26,7 +26,7 @@ from numpy cimport (
     uint32_t,
     uint64_t,
 )
-from numpy.math cimport NAN
+from numpy.math cimport NAN, isinf
 
 cnp.import_array()
 
@@ -67,15 +67,6 @@ cdef enum InterpolationEnumType:
     INTERPOLATION_NEAREST,
     INTERPOLATION_MIDPOINT
 
-cdef inline bint check_inf(numeric_t ai) nogil:
-
-    if numeric_t == cython.float:
-        if (ai == MINfloat32) or (ai == MAXfloat32):
-            return True
-    else:
-        if (ai == MINfloat64) or (ai == MAXfloat64):
-            return True
-
 cdef inline float64_t median_linear(float64_t* a, int n) nogil:
     cdef:
         int i, j, na_count = 0
@@ -266,10 +257,10 @@ def group_cumsum(numeric_t[:, ::1] out,
 
                 # For floats, use Kahan summation to reduce floating-point
                 # error (https://en.wikipedia.org/wiki/Kahan_summation_algorithm)
-                if (numeric_t == float32_t) or (numeric_t == float64_t):
+                if numeric_t is float32_t or numeric_t is float64_t:
                     if val == val:
                         # if val or accum are inf/-inf don't use kahan
-                        if check_inf(val) or check_inf(accum[lab, j]):
+                        if isinf(val) or isinf(accum[lab, j]):
                             accum[lab, j] += val
                             out[i, j] = accum[lab, j]
                         else:
@@ -576,7 +567,6 @@ def group_add(add_t[:, ::1] out,
                 for j in range(K):
                     val = values[i, j]
 
-                    #  function to release gil for the whole block
                     if (val == MAXfloat64) or (val == MINfloat64):
                         sumx[lab, j] = val
                         break