Fix dualx alignment on log axes

ultraplot/scale.py

@@ -11,8 +11,12 @@
 import numpy.ma as ma
 
 from . import ticker as pticker
-from .internals import ic  # noqa: F401
-from .internals import _not_none, _version_mpl, warnings
+from .internals import (
+    _not_none,
+    _version_mpl,
+    ic,  # noqa: F401
+    warnings,
+)
 
 __all__ = [
     "CutoffScale",
@@ -370,7 +374,9 @@ def __init__(self, transform=None, invert=False, parent_scale=None, **kwargs):
             kwsym["linthresh"] = inverse(kwsym["linthresh"])
             parent_scale = SymmetricalLogScale(**kwsym)
         self.functions = (forward, inverse)
-        self._transform = parent_scale.get_transform() + FuncTransform(forward, inverse)
+        # Apply the function in data space, then parent scale (e.g., log).
+        # This ensures dual axes behave correctly when the parent is non-linear.
+        self._transform = FuncTransform(forward, inverse) + parent_scale.get_transform()
 
         # Apply default locators and formatters
         # NOTE: We pass these through contructor functions

ultraplot/tests/test_axes.py

@@ -4,6 +4,7 @@
 """
 import numpy as np
 import pytest
+
 import ultraplot as uplt
 from ultraplot.internals.warnings import UltraPlotWarning
 
@@ -130,6 +131,23 @@ def test_cartesian_format_all_units_types():
     ax.format(**kwargs)
 
 
+def test_dualx_log_transform_is_finite():
+    """
+    Ensure dualx transforms remain finite on log axes.
+    """
+    fig, ax = uplt.subplots()
+    ax.set_xscale("log")
+    ax.set_xlim(0.1, 10)
+    sec = ax.dualx(lambda x: 1 / x)
+    fig.canvas.draw()
+
+    ticks = sec.get_xticks()
+    assert ticks.size > 0
+    xy = np.column_stack([ticks, np.zeros_like(ticks)])
+    transformed = sec.transData.transform(xy)
+    assert np.isfinite(transformed).all()
+
+
 def test_axis_access():
     # attempt to access the ax object 2d and linearly
     fig, ax = uplt.subplots(ncols=2, nrows=2)