Order projection inference for geo plotting

ultraplot/internals/inputs.py

@@ -341,10 +341,23 @@ def _preprocess_or_redirect(self, *args, **kwargs):
                     if kwargs.get("latlon", None) is None:
                         kwargs["latlon"] = True
                 if self._name == "cartopy" and name in CARTOPY_FUNCS:
-                    if kwargs.get("transform", None) is None:
-                        kwargs["transform"] = PlateCarree()
+                    # Check if an input transform is given
+                    # else default to axis projection or
+                    # PlateCarree if no projection is set
+                    input_transform = kwargs.get("transform", None)
+                    if input_transform is not None:
+                        kwargs["transform"] = Proj(input_transform)
                     else:
-                        kwargs["transform"] = Proj(kwargs["transform"])
+                        # add projection for imshow as it
+                        # cannot be projected on particular
+                        # locations
+                        options = [
+                            self.projection if name == "imshow" else None,
+                            PlateCarree(),
+                        ]
+                        kwargs["transform"] = _not_none(
+                            *options,
+                        )
 
                 # Process data args
                 # NOTE: Raises error if there are more args than keys

ultraplot/tests/test_inputs.py

@@ -1,5 +1,5 @@
 import ultraplot as uplt, pytest, numpy as np
-from unittest.mock import Mock
+from unittest.mock import Mock, patch
 
 
 @pytest.mark.parametrize(
@@ -33,3 +33,24 @@ def tripcolor(self, tri, z, extra=None, kw=None):
 
     # Test that the decorator preserves the function name
     assert decorated.__name__ == "tripcolor"
+
+
+@pytest.mark.parametrize("transform", [None, uplt.constructor.Proj("merc")])
+def test_projection_set_correctly(rng, transform):
+
+    fig, ax = uplt.subplots(proj="merc")
+    fig.canvas.draw()
+    data = rng.random((10, 10))
+
+    with patch.object(ax, "imshow", wraps=ax.imshow) as mock_imshow:
+        # Call imshow with some dummy data
+        settings = dict(transform=transform)
+        ax.imshow(data, **settings)
+
+        # Assert that the transform keyword argument was set correctly
+        mock_imshow.assert_called_once()
+        _, kwargs = mock_imshow.call_args
+        assert "transform" in kwargs, "The 'transform' keyword argument is missing."
+        assert (
+            kwargs["transform"] == transform
+        ), f"Expected transform to be {expectation}, got {kwargs['transform']}"