Rename transform parameter to trans

seaborn/_core/properties.py

@@ -86,7 +86,7 @@ def infer_scale(self, arg: Any, data: Series) -> Scale:
         if isinstance(arg, str):
             if any(arg.startswith(k) for k in trans_args):
                 # TODO validate numeric type? That should happen centrally somewhere
-                return Continuous(transform=arg)
+                return Continuous(trans=arg)
             else:
                 msg = f"Unknown magic arg for {self.variable} scale: '{arg}'."
                 raise ValueError(msg)

seaborn/_core/scales.py

@@ -368,7 +368,7 @@ def spacer(x):
 
     def _get_transform(self):
 
-        arg = self.transform
+        arg = self.trans
 
         def get_param(method, default):
             if arg == method:
@@ -407,7 +407,7 @@ class Continuous(ContinuousBase):
     A numeric scale supporting norms and functional transforms.
     """
     values: tuple | str | None = None
-    transform: str | Transforms | None = None
+    trans: str | Transforms | None = None
 
     # TODO Add this to deal with outliers?
     # outside: Literal["keep", "drop", "clip"] = "keep"
@@ -455,7 +455,7 @@ def tick(
                 f"Tick locator must be an instance of {Locator!r}, "
                 f"not {type(locator)!r}."
             )
-        log_base, symlog_thresh = self._parse_for_log_params(self.transform)
+        log_base, symlog_thresh = self._parse_for_log_params(self.trans)
         if log_base or symlog_thresh:
             if count is not None and between is None:
                 raise RuntimeError("`count` requires `between` with log transform.")
@@ -523,21 +523,23 @@ def label(
         }
         return new
 
-    def _parse_for_log_params(self, transform):
+    def _parse_for_log_params(
+        self, trans: str | Transforms | None
+    ) -> tuple[float | None, float | None]:
 
         log_base = symlog_thresh = None
-        if isinstance(transform, str):
-            m = re.match(r"^log(\d*)", transform)
+        if isinstance(trans, str):
+            m = re.match(r"^log(\d*)", trans)
             if m is not None:
                 log_base = float(m[1] or 10)
-            m = re.match(r"symlog(\d*)", transform)
+            m = re.match(r"symlog(\d*)", trans)
             if m is not None:
                 symlog_thresh = float(m[1] or 1)
         return log_base, symlog_thresh
 
     def _get_locators(self, locator, at, upto, count, every, between, minor):
 
-        log_base, symlog_thresh = self._parse_for_log_params(self.transform)
+        log_base, symlog_thresh = self._parse_for_log_params(self.trans)
 
         if locator is not None:
             major_locator = locator
@@ -595,7 +597,7 @@ def _get_locators(self, locator, at, upto, count, every, between, minor):
 
     def _get_formatter(self, locator, formatter, like, base, unit):
 
-        log_base, symlog_thresh = self._parse_for_log_params(self.transform)
+        log_base, symlog_thresh = self._parse_for_log_params(self.trans)
         if base is None:
             if symlog_thresh:
                 log_base = 10
@@ -646,7 +648,7 @@ class Temporal(ContinuousBase):
     # those yet, and having a clear distinction betewen date(time) / time
     # may be more useful.
 
-    transform = None
+    trans = None
 
     _priority: ClassVar[int] = 2
 

tests/_core/test_scales.py

@@ -54,12 +54,12 @@ def test_coordinate_defaults(self, x):
 
     def test_coordinate_transform(self, x):
 
-        s = Continuous(transform="log")._setup(x, Coordinate())
+        s = Continuous(trans="log")._setup(x, Coordinate())
         assert_series_equal(s(x), np.log10(x))
 
     def test_coordinate_transform_with_parameter(self, x):
 
-        s = Continuous(transform="pow3")._setup(x, Coordinate())
+        s = Continuous(trans="pow3")._setup(x, Coordinate())
         assert_series_equal(s(x), np.power(x, 3))
 
     def test_interval_defaults(self, x):
@@ -118,7 +118,7 @@ def test_color_with_transform(self, x):
 
         x = pd.Series([1, 10, 100], name="x", dtype=float)
         cmap = color_palette("ch:", as_cmap=True)
-        s = Continuous(transform="log")._setup(x, Color())
+        s = Continuous(trans="log")._setup(x, Color())
         assert_array_equal(s(x), cmap([0, .5, 1])[:, :3])  # FIXME RGBA
 
     def test_tick_locator(self, x):
@@ -184,7 +184,7 @@ def test_tick_minor(self, x):
 
     def test_log_tick_default(self, x):
 
-        s = Continuous(transform="log")._setup(x, Coordinate())
+        s = Continuous(trans="log")._setup(x, Coordinate())
         a = PseudoAxis(s._matplotlib_scale)
         a.set_view_interval(.5, 1050)
         ticks = a.major.locator()
@@ -193,28 +193,28 @@ def test_log_tick_default(self, x):
     def test_log_tick_upto(self, x):
 
         n = 3
-        s = Continuous(transform="log").tick(upto=n)._setup(x, Coordinate())
+        s = Continuous(trans="log").tick(upto=n)._setup(x, Coordinate())
         a = PseudoAxis(s._matplotlib_scale)
         assert a.major.locator.numticks == n
 
     def test_log_tick_count(self, x):
 
         with pytest.raises(RuntimeError, match="`count` requires"):
-            Continuous(transform="log").tick(count=4)
+            Continuous(trans="log").tick(count=4)
 
-        s = Continuous(transform="log").tick(count=4, between=(1, 1000))
+        s = Continuous(trans="log").tick(count=4, between=(1, 1000))
         a = PseudoAxis(s._setup(x, Coordinate())._matplotlib_scale)
         a.set_view_interval(.5, 1050)
         assert_array_equal(a.major.locator(), [1, 10, 100, 1000])
 
     def test_log_tick_every(self, x):
 
         with pytest.raises(RuntimeError, match="`every` not supported"):
-            Continuous(transform="log").tick(every=2)
+            Continuous(trans="log").tick(every=2)
 
     def test_symlog_tick_default(self, x):
 
-        s = Continuous(transform="symlog")._setup(x, Coordinate())
+        s = Continuous(trans="symlog")._setup(x, Coordinate())
         a = PseudoAxis(s._matplotlib_scale)
         a.set_view_interval(-1050, 1050)
         ticks = a.major.locator()
@@ -275,7 +275,7 @@ def test_label_unit_with_sep(self, x):
 
     def test_label_base_from_transform(self, x):
 
-        s = Continuous(transform="log")
+        s = Continuous(trans="log")
         a = PseudoAxis(s._setup(x, Coordinate())._matplotlib_scale)
         a.set_view_interval(10, 1000)
         label, = a.major.formatter.format_ticks([100])