CLN/PERF: simplify tslib.get_time_micros

pandas/_libs/tslib.pyx

@@ -730,29 +730,6 @@ cpdef array_to_datetime(ndarray[object] values, errors='raise',
         return oresult
 
 
-# ----------------------------------------------------------------------
-# Accessors
-
-
-def get_time_micros(ndarray[int64_t] dtindex):
-    """
-    Datetime as int64 representation to a structured array of fields
-    """
-    cdef:
-        Py_ssize_t i, n = len(dtindex)
-        pandas_datetimestruct dts
-        ndarray[int64_t] micros
-
-    micros = np.empty(n, dtype=np.int64)
-
-    for i in range(n):
-        dt64_to_dtstruct(dtindex[i], &dts)
-        micros[i] = 1000000LL * (dts.hour * 60 * 60 +
-                                 60 * dts.min + dts.sec) + dts.us
-
-    return micros
-
-
 # ----------------------------------------------------------------------
 # Some general helper functions
 

pandas/_libs/tslibs/fields.pyx

@@ -23,6 +23,26 @@ from np_datetime cimport (pandas_datetimestruct, pandas_timedeltastruct,
 from nattype cimport NPY_NAT
 
 
+def get_time_micros(ndarray[int64_t] dtindex):
+    """
+    Return the number of microseconds in the time component of a
+    nanosecond timestamp.
+
+    Parameters
+    ----------
+    dtindex : ndarray[int64_t]
+
+    Returns
+    -------
+    micros : ndarray[int64_t]
+    """
+    cdef:
+        ndarray[int64_t] micros
+
+    micros = np.mod(dtindex, 86400000000000, dtype=np.int64) // 1000LL
+    return micros
+
+
 def build_field_sarray(ndarray[int64_t] dtindex):
     """
     Datetime as int64 representation to a structured array of fields

pandas/core/indexes/datetimes.py

@@ -926,7 +926,7 @@ def _get_time_micros(self):
         values = self.asi8
         if self.tz is not None and self.tz is not utc:
             values = self._local_timestamps()
-        return libts.get_time_micros(values)
+        return fields.get_time_micros(values)
 
     def to_series(self, keep_tz=False):
         """