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

     ).