Why so many generated structures with hydrogen and/or helium? about xtal2png HOT 4 OPEN

xref: txie-93/cdvae#11

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Doesn't seem to be an issue with noble gases being represented very frequently, which of course isn't expected anyway since it's experimentally verified compounds. Maybe $He$ is "supposed to be" $H$ and more so has to do with the RGB unscaling.

• #82
• #81
• #76

from pymatviz.elements import ptable_heatmap_plotly

equimolar_compositions = train_inputs.apply(
    lambda s: Composition(re.sub(r"\d", "", s.formula))
)
fig = ptable_heatmap_plotly(equimolar_compositions)
fig.show()

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Also strange that there's not a single instance of oxygen in the generated structures, despite its prevalence. I don't see "adjacent" elements nitrogen or flourine either. Could be an issue with the scaling/unscaling, not enough data, bad model, bad representation, or biased sample. Last one seems unlikely.

Probably not an issue with data shuffling #84

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from #79

The formulas:

which seem somewhat better.

Interested to see how it goes with imagen-pytorch instead of denoising_diffusion_pytorch.

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