Skip to main content

Some useful tools related to Amber and DP.

Project description


Some useful tools related to Amber and DP.


pip install dpamber


corr: generating data for DPRc models

DOI:10.1021/acs.jctc.1c00201 Citations

corr tool generates DeePMD-kit training data for DPRc from AMBER sander low-level QM/MM data and high-level data. For details of DPRc, read the DPRc paper.

Before using this tool, one need to prepare low-level and high-level QM/MM data:

$$ E_\text{hl}(\mathbf R)=E_\text{hl,QM}(\mathbf R)+E_\text{hl,QM/MM}(\mathbf R)+E_\text{MM}(\mathbf R) $$

$$ E_\text{ll}(\mathbf R)=E_\text{ll,QM}(\mathbf R)+E_\text{ll,QM/MM}(\mathbf R)+E_\text{MM}(\mathbf R) $$

Low-level and high-level data should use the same coordinate and the same MM method, but different QM methods. So, the correction energy for training will be

$$ \Delta E (\mathbf R) = E_\text{hl}(\mathbf R) - E_\text{ll}(\mathbf R) = (E_\text{hl,QM}(\mathbf R) - E_\text{ll,QM}(\mathbf R)) + (E_\text{hl,QM/MM}(\mathbf R) - E_\text{ll,QM/MM}(\mathbf R)) $$

An example of the command is

dpamber corr --cutoff 6. --qm_region ":1" --parm7_file some_param.param7 --nc --hl high_level --ll low_level --out dataset

where --cutoff takes cutoff radius of the QM/MM interaction for training. --qm_region takes AMBER mask format for the QM region. --parm7_file and --nc take the PARM7 file and the trajectory (NetCDF) file, respectively. --ll and --hl are the prefixes of low-level and high-level files, including the mdout file (.mdout), the mden file (.mden) and the mdfrc file (.mdfrc). The output dataset directory should be put in --out.

See details from dpamber corr -h.

devi: calculate model deviation

devi can be used to calculate the model deviation of a given trajectory. You need to install DeePMD-kit using

pip install dpamber[dpgpu]

See dpamber devi -h for details.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dpamber-0.4.0.tar.gz (300.8 kB view hashes)

Uploaded Source

Built Distribution

dpamber-0.4.0-py3-none-any.whl (16.1 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page