name: debug_axes description: プロットのスケール（対数軸など）、目盛、表示範囲の不具合を診断し、意図した見た目に修正する

Debug Plot Axes Skill

This skill is for resolving issues where plot axis scales (especially log scales) or display ranges (ylim/xlim) in gwexpy do not appear as intended.

Diagnostic Procedures

1. Verify Internal State:

   • Create a reproduction script and output ax.get_yscale() or ax.get_ylim() to confirm if the internal setting is actually 'log'.

2. Identity Visual Linearity Issues:

   • If the internal state is 'log' but it visually appears linear, it is often due to the data range being too narrow (e.g., 1.0 vs 2.23).
   • Check if ticks are appropriately placed via ax.get_yticks().

3. Confirm Judgment Logic:

   • Check if determine_yscale or determine_xscale in gwexpy/plot/defaults.py correctly recognizes the data, using debug prints if necessary.

Correction Guidelines

1. Enforce Scale Application:

   • Explicitly call ax.set_yscale() after super().__init__ within Plot.__init__ in gwexpy/plot/plot.py.
   • Always call ax.autoscale_view() after application to force a visual update.

2. Automatic Range Expansion (Log Scale specific):

   • If the data range is less than 100x (2 orders of magnitude), log scales often show few ticks, appearing linear.
   • Implement or fix determine_ylim logic to ensure a range of approximately 2 orders of magnitude centered around the median.

3. Robust Type Checking:

   • Since isinstance checks may fail due to environment differences (import sources), use duck-typing such as type(obj).__name__ or hasattr(obj, 'frequencies') alongside it.

4. Prevent Duplicate Display in IPython/Jupyter:

   • Set _repr_html_ = None in the Plot class to prevent duplicate displays (repr and plt.show).