Make better test for binned data

stingray/crossspectrum.py

@@ -1573,10 +1573,19 @@ def _initialize_from_any_input(
             data1 = data1.apply_gtis(inplace=False)
             data2 = data2.apply_gtis(inplace=False)
 
-            if hasattr(data1, "counts"):
+            data1_is_binned = (
+                "counts" in data1.array_attrs() or "_counts" in data1.internal_array_attrs()
+            )
+            data2_is_binned = (
+                "counts" in data2.array_attrs() or "_counts" in data2.internal_array_attrs()
+            )
+
+            if data1_is_binned and data2_is_binned:
                 assert data2.time.size == data1.time.size and np.allclose(
                     data2.time - data1.time, 0
                 ), "Time arrays are not the same"
+            elif data1_is_binned or data2_is_binned:
+                raise ValueError("Please use input data of the same kind")
 
         if isinstance(data1, EventList):
             spec = crossspectrum_from_events(

stingray/tests/test_crossspectrum.py

@@ -724,6 +724,15 @@ def test_make_crossspectrum_diff_lc_counts_shape(self):
             with pytest.raises(AssertionError, match="Time arrays are not the same"):
                 Crossspectrum(self.lc1, lc_)
 
+    def test_make_crossspectrum_lc_and_evts(self):
+        counts = np.array([1] * 10001)
+        dt = 0.0001
+        time = np.arange(0.0, 1.0001, dt)
+        lc_ = Lightcurve(time, counts, gti=[[time[0] - dt / 2, time[-1] + dt / 2]])
+        ev_ = EventList(time)
+        with pytest.raises(ValueError, match="Please use input data of the same kind"):
+            Crossspectrum(ev_, lc_, skip_checks=True)
+
     def test_make_crossspectrum_diff_lc_stat(self):
         lc_ = copy.deepcopy(self.lc1)
         lc_.err_dist = "gauss"