meca: Fix the bug when passing a dict of scalar values to the spec pa…

…rameter (#2174)

Co-authored-by: Wei Ji <[email protected]>

pygmt/src/meca.py

@@ -283,6 +283,10 @@ def meca(
 
         # convert dict to pd.DataFrame so columns can be reordered
         if isinstance(spec, dict):
+            # convert values to ndarray so pandas doesn't complain about "all
+            # scalar values". See
+            # https://github.com/GenericMappingTools/pygmt/pull/2174
+            spec = {key: np.atleast_1d(value) for key, value in spec.items()}
             spec = pd.DataFrame(spec)
 
         # expected columns are:

pygmt/tests/test_meca.py

@@ -291,3 +291,29 @@ def test_meca_dict_offset_eventname():
         event_name="Event20220311",
     )
     return fig
+
+
+@pytest.mark.mpl_image_compare(filename="test_meca_dict_eventname.png")
+def test_meca_spec_dict_all_scalars():
+    """
+    Test supplying a dict with scalar values for all focal parameters.
+
+    This is a regression test for
+    https://github.com/GenericMappingTools/pygmt/pull/2174
+    """
+    fig = Figure()
+    fig.basemap(region=[-125, -122, 47, 49], projection="M6c", frame=True)
+    fig.meca(
+        spec=dict(
+            strike=330,
+            dip=30,
+            rake=90,
+            magnitude=3,
+            longitude=-124,
+            latitude=48,
+            depth=12.0,
+            event_name="Event20220311",
+        ),
+        scale="1c",
+    )
+    return fig