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From the discussion that came up in #5985 - that PR proposed 4 contour plots - on a mixture of log and linear axes - that should look identical but didn't, until fixed in the PR. If we make the same plots as a smoothed heatmap, they look identical as far as the smoothing goes, but we lose the first row of bricks on each log axis because its far edge would be at a negative coordinate:
Also closer to what we already do with smoothed heatmaps (the same mock after Plotly.restyle(gd,{'type':'heatmap', 'zsmooth':'best'}) - the four variants look slightly different but I think this is actually a symptom of some funny and potentially incorrect things we're doing with extending beyond the data values to make the outer edges of the heatmap bricks - we may want to adapt this for log axes too, especially as this results in us dropping the first row/column in this case!):
Can we do a better job of picking brick edges in this case?
From the discussion that came up in #5985 - that PR proposed 4 contour plots - on a mixture of log and linear axes - that should look identical but didn't, until fixed in the PR. If we make the same plots as a smoothed heatmap, they look identical as far as the smoothing goes, but we lose the first row of bricks on each log axis because its far edge would be at a negative coordinate:
Can we do a better job of picking brick edges in this case?
The figure above would be:
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