x2sys_cross: Fix IndexError to allow empty dataframe outputs (#4060)

Fixes `IndexError: index 0 is out of bounds for axis 0 with size 0` when
x2sys_cross returns no crossovers. An empty dataframe should be returned instead.
Do so by not checking column names when the dataframe is empty due to
no available crossovers.

Author: weiji14

pygmt/src/x2sys_cross.py

@@ -250,9 +250,12 @@ def x2sys_cross(
                     unit = time_unit.upper() if time_unit in "wd" else time_unit
                     scale = 1.0
 
-            columns = result.columns[2:4]
-            result[columns] *= scale
-            result[columns] = result[columns].apply(pd.to_timedelta, unit=unit)
-            if columns[0][0] == "t":  # "t" or "i":
-                result[columns] += pd.Timestamp(lib.get_default("TIME_EPOCH"))
+            if len(result) > 0:  # if crossovers exist (more than one output row)
+                columns: pd.Index = result.columns[2:4]  # i_1/i_2 or t_1/t_2 columns
+                result[columns] *= scale
+                result[columns] = result[columns].apply(pd.to_timedelta, unit=unit)
+
+                if columns[0][0] == "t":  # "t" or "i":
+                    result[columns] += pd.Timestamp(lib.get_default("TIME_EPOCH"))
+
             return result

pygmt/tests/test_x2sys_cross.py

@@ -308,3 +308,26 @@ def test_x2sys_cross_trackvalues():
             assert output.shape == (14338, 12)
             npt.assert_allclose(output.z_1.mean(), -2422.418556, rtol=1e-4)
             npt.assert_allclose(output.z_2.mean(), -2402.268364, rtol=1e-4)
+
+
+@pytest.mark.usefixtures("mock_x2sys_home")
+def test_x2sys_cross_output_dataframe_empty(tracks):
+    """
+    Test that x2sys_cross can output an empty dataframe (when there are no crossovers)
+    without any errors.
+
+    Regression test for
+    https://forum.generic-mapping-tools.org/t/issue-with-x2sys-in-pygmt-solved/6154
+    """
+    with TemporaryDirectory(prefix="X2SYS", dir=Path.cwd()) as tmpdir:
+        tag = Path(tmpdir).name
+        x2sys_init(tag=tag, fmtfile="xyz", force=True)
+
+        tracks = [tracks[0][:5]]  # subset to less rows so there won't be crossovers
+        output = x2sys_cross(tracks=tracks, tag=tag, coe="i")
+
+        assert isinstance(output, pd.DataFrame)
+        assert output.shape == (0, 0)
+        assert output.empty
+        columns = list(output.columns)
+        assert columns == []