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Paper code: ED-AFM (#41)
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.gitignore

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# VS Code
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.vscode
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# Tex
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*.aux
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*.log
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*.pdf
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# Other
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molecules
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*.csv

README.md

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## Papers
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The [`papers`](papers) subdirectory contains training scripts and datasets for specific publications. Currently we have the following:
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- [Automated structure discovery in atomic force microscopy](papers/asd-afm)
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- [Electrostatic Discovery Atomic Force Microscopy](papers/ed-afm)
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- [Structure discovery in Atomic Force Microscopy imaging of ice](papers/ice_structure_discovery)

docs/source/reference/mlspm.models.rst

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Alias of :class:`mlspm.image.models.ASDAFMNet`
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.. class:: mlspm.models.AttentionUNet
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Alias of :class:`mlspm.image.models.AttentionUNet`
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.. class:: mlspm.models.EDAFMNet
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Alias of :class:`mlspm.image.models.EDAFMNet`
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.. autofunction:: mlspm.models.download_weights

mlspm/_weights.py

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"graph-ice-au111-bilayer": "https://zenodo.org/records/10054348/files/weights_ice-au111-bilayer.pth?download=1",
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"asdafm-light": "https://zenodo.org/records/10514470/files/weights_asdafm_light.pth?download=1",
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"asdafm-heavy": "https://zenodo.org/records/10514470/files/weights_asdafm_heavy.pth?download=1",
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"edafm-base": "https://zenodo.org/records/10606273/files/base.pth?download=1",
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"edafm-single-channel": "https://zenodo.org/records/10606273/files/single-channel.pth?download=1",
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"edafm-CO-Cl": "https://zenodo.org/records/10606273/files/CO-Cl.pth?download=1",
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"edafm-Xe-Cl": "https://zenodo.org/records/10606273/files/Xe-Cl.pth?download=1",
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"edafm-constant-noise": "https://zenodo.org/records/10606273/files/constant-noise.pth?download=1",
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"edafm-uniform-noise": "https://zenodo.org/records/10606273/files/uniform_noise.pth?download=1",
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"edafm-no-gradient": "https://zenodo.org/records/10606273/files/no-gradient.pth?download=1",
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"edafm-matched-tips": "https://zenodo.org/records/10606273/files/matched-tips.pth?download=1",
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}
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The following weights are available:
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- ``'graph-ice-cu111'``: PosNet trained on ice clusters on Cu(111). (https://doi.org/10.5281/zenodo.10054348)
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- ``'graph-ice-au111-monolayer'``: PosNet trained on monolayer ice clusters on Au(111). (https://doi.org/10.5281/zenodo.10054348)
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- ``'graph-ice-au111-bilayer'``: PosNet trained on bilayer ice clusters on Au(111). (https://doi.org/10.5281/zenodo.10054348)
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- ``'asdafm-light'``: ASDAFMNet trained on molecules containing the elements H, C, N, O, and F. (https://doi.org/10.5281/zenodo.10514470)
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- ``'asdafm-heavy'``: ASDAFMNet trained on molecules additionally containing Si, P, S, Cl, and Br. (https://doi.org/10.5281/zenodo.10514470)
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- ``'graph-ice-au111-monolayer'``: PosNet trained on monolayer ice clusters on Au(111).
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(https://doi.org/10.5281/zenodo.10054348)
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- ``'graph-ice-au111-bilayer'``: PosNet trained on bilayer ice clusters on Au(111).
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(https://doi.org/10.5281/zenodo.10054348)
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- ``'asdafm-light'``: :class:`.ASDAFMNet` trained on molecules containing the elements H, C, N, O, and F.
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(https://doi.org/10.5281/zenodo.10514470)
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- ``'asdafm-heavy'``: :class:`.ASDAFMNet` trained on molecules additionally containing Si, P, S, Cl, and Br.
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(https://doi.org/10.5281/zenodo.10514470)
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- ``'edafm-base'``: :class:`.EDAFMNet` used for all predictions in the main ED-AFM paper and used for comparison in
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the various tests in the supplementary information of the paper. (https://doi.org/10.5281/zenodo.10606273)
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- ``'edafm-single-channel'``: :class:`.EDAFMNet` trained on only a single CO-tip AFM input.
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(https://doi.org/10.5281/zenodo.10606273)
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- ``'edafm-CO-Cl'``: :class:`.EDAFMNet` trained on alternative tip combination of CO and Cl.
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(https://doi.org/10.5281/zenodo.10606273)
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- ``'edafm-Xe-Cl'``: :class:`.EDAFMNet` trained on alternative tip combination of Xe and Cl.
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(https://doi.org/10.5281/zenodo.10606273)
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- ``'edafm-constant-noise'``: :class:`.EDAFMNet` trained using constant noise amplitude instead of normally distributed
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amplitude. (https://doi.org/10.5281/zenodo.10606273)
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- ``'edafm-uniform-noise'``: :class:`.EDAFMNet` trained using uniform random noise amplitude instead of normally
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distributed amplitude. (https://doi.org/10.5281/zenodo.10606273)
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- ``'edafm-no-gradient'``: :class:`.EDAFMNet` trained without background-gradient augmentation.
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(https://doi.org/10.5281/zenodo.10606273)
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- ``'edafm-matched-tips'``: :class:`.EDAFMNet` trained on data with matched tip distance between CO and Xe,
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instead of independently randomized distances. (https://doi.org/10.5281/zenodo.10606273)
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Arguments:
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weights_name: Name of weights to download.

mlspm/datasets.py

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"AFM-ice-relaxed": "https://zenodo.org/records/10362511/files/relaxed_structures.tar.gz?download=1",
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"ASD-AFM-molecules": "https://zenodo.org/records/10562769/files/molecules.tar.gz?download=1",
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"AFM-camphor-exp": "https://zenodo.org/records/10562769/files/afm_camphor.tar.gz?download=1",
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"ED-AFM-molecules": "https://zenodo.org/records/10609676/files/molecules_rebias.tar.gz?download=1",
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"ED-AFM-data": "https://zenodo.org/records/10609676/files/edafm-data.tar.gz?download=1",
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}
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- ``'AFM-ice-relaxed'``: https://doi.org/10.5281/zenodo.10362511
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- ``'ASD-AFM-molecules'``: https://doi.org/10.5281/zenodo.10562769 - 'molecules.tar.gz'
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- ``'AFM-camphor-exp'``: https://doi.org/10.5281/zenodo.10562769 - 'afm_camphor.tar.gz'
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- ``'ED-AFM-molecules'``: https://doi.org/10.5281/zenodo.10609676 - 'molecules_rebias.tar.gz'
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- ``'ED-AFM-data'``: https://doi.org/10.5281/zenodo.10609676 - 'edafm-data.tar.gz'
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Arguments:
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name: Name of the dataset to download.

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