add low level 2d profile plot function and 2d profile function#1652
add low level 2d profile plot function and 2d profile function#1652
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Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## develop #1652 +/- ##
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+ Coverage 84.33% 84.34% +0.01%
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Files 164 164
Lines 14340 14448 +108
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+ Hits 12093 12186 +93
- Misses 2247 2262 +15 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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- Fix colorbar layout using constrained_layout (no more overlap) - Always extend axes to parameter bounds; remove show_bounds parameter - Auto-generate scale-aware axis labels from problem.x_scales - Accept optional x_labels override to match 1D profiles API - Pairplot-style label cleanup: parameter names on edges only, ratio label kept on off-edge diagonal subplots - Reset MaxNLocator on diagonal subplots to avoid dense tick marks - Add smoke tests for visualize_2d_profile and profile_lowlevel_2d - Add 2D profile cell to getting_started.ipynb
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Remaining TODO list from @EchoRLiu
This will be taken care of in the another PR dealing with profiling enhancements.
This is weird, I saw it a couple of times. We'll need to check what happens, why does profiling stop prematurely sometimes. It might be the weird conditions in adaptive searches that doesn't have a else, so profiling can fail silently. Needs to be investigated.
Good as initial visualization, can be changed via user.
For another PR as it deals with general profiling. |
- Compute global vmin/vmax across all off-diagonal panels so the colorbar accurately represents all subplots - Add profile_color parameter for diagonal 1D profile line color - Add vmin/vmax parameters to profile_lowlevel_2d for external control
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Thanks, looks mostly good to me. Two minor things looking at https://pypesto--1652.org.readthedocs.build/en/1652/example/getting_started.html:
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PaulJonasJost
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One thing that is bugging me a bit is that if we have a lot of points in a small intervall, the black borders of the point overshadow the coloring.

This PR is to address #1651.
To do so, I added two new visualization functions:
profile_lowlevel_2d()- Visualizes the relationship between two parameters during profilingvisualize_2d_profile()- High-level n by n profile grid:profile_lowlevel_2d()This would provide a complete overview of how parameters interact during profile likelihood computation