| Name | Xponge JSON |
| Version |
1.4.3
JSON |
| download |
| home_page | https://gitee.com/gao_hyp_xyj_admin/xponge |
| Summary | A Python package to perform pre- and post-processing of molecular simulations |
| upload_time | 2024-01-18 01:46:55 |
| maintainer | |
| docs_url | None |
| author | Yijie Xia |
| requires_python | >=3.6 |
| license | |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# Welcome to Use Xponge!
## Introduction
``Xponge`` is a lightweight and easy to customize python package to perform pre- and post-processing of molecular simulations.
### What can Xponge do?
Xponge includes three major categories of functionality, namely, the simulation system construction, simulation data transformation and analysis, and automated workflows for complex simulations. ``Xponge`` is mainly designed for the molecular dynamics (MD) program [SPONGE](https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjoc.202100456)[1], but it can also output some general format files such as mol2 and PDB, so it may help the other molecular modelling programs too.
## Installation
Xponge can be used on all operating systems (Windows/Linux/MacOS). Some functions (See [here](https://spongemm.cn/xponge_doc/dependency.html#unavalable-functions-on-windows) for the detailed list) to do the quantum chemistry calculations can not be used on Windows because `pyscf` is not available on Windows.
### 1. pip install
```bash
pip install Xponge
```
### 2. source setup
- 2.1 Download or clone the source from the gitee or github repository
The gitee repository is [here](https://gitee.com/gao_hyp_xyj_admin/xponge).
The github repository is [here](https://github.com/xia-yijie/xponge).
git clone http://gitee.com/gao_hyp_xyj_admin/xponge.git
git clone http://github.com/xia-yijie/xponge.git
- 2.2 Open the directory where you download or clone the repository
- 2.3 (Optional) Configure the environment
It is recommended to use `conda` to configure the environment. Two `yml` files named `install_requirements.yml` and `extras_requirements.yml` are provided in the repository.
It is recommanded to use the file `install_requirements.yml` to configure the environment. The file will only install the basic dependent packages. If a `ModuleNotFoundError` is raised when you are using `Xponge`, then install the module. This allows you to avoid installing many modules that you will never use, and also makes `Xponge` more cross-platform compatible. Here are the commands to use `install_requirements.yml`.
```bash
conda env create -f install_requirements.yml
conda activate Xponge
```
All the dependent packages are listed in the [dependencies](#dependencies) section. If you don't want to install the dependent packages one by one (which can be really annoying), the file `extras_requirements.yml` can help you with the environment configuration except the packages `mindspore` and `mindsponge`. The two packages should be installed according to your device (e.g. whether the backend is CPU, GPU or Huawei Ascend Processors) and can not be simply installed by conda. Here are the commands to use `extras_requirements.yml`.
```bash
conda env create -f extras_requirements.yml
conda activate Xponge
```
It is worth noting that `extras_requirements.yml` can not be used on Windows because `pyscf` is not available on Windows.
- 2.4 Run the command
```bash
python setup.py install
```
### Installation check
There are some unit tests in ``Xponge``. You can do the basic test to check whether the installation is successful like this:
```bash
Xponge test --do base -o test --verbose 1
```
Here, ``Xponge`` can be replaced to ``python -m Xponge``, ``python3 -m Xponge`` and so on according to your settings of the environmental variables. Some files will be generated after the test is finished.
## Quickstart
Here is a simple example.
```python
import Xponge
# Import the force field you need
import Xponge.forcefield.amber.ff14sb
# Build the molecule like this
peptide = ACE + ALA + NME
# or like this
peptide2 = NALA + ALA * 10 + CALA
# or like this
peptide3 = Xponge.Get_Peptide_From_Sequence("AAAAA")
# See the documentation for more usage!
# Save them as your favorite format
Xponge.save_pdb(peptide, "ala.pdb")
Xponge.save_mol2(peptide2, "ala12.mol2")
Xponge.save_sponge_input(peptide3, "ala5")
```
Then we can see `ala12.mol2` in VMD:
Here is another simple example.
```python
import Xponge
import Xponge.forcefield.amber.tip3p
box = Xponge.BlockRegion(0, 0, 0, 60, 60, 60)
region_1 = Xponge.BlockRegion(0, 0, 20, 20, 20, 40)
region_2 = Xponge.BlockRegion(0, 0, 40, 20, 20, 60)
region_3 = Xponge.BlockRegion(0, 0, 0, 20, 20, 20)
region_4 = Xponge.SphereRegion(20, 10, 30, 10)
region_5 = Xponge.BlockRegion(20, 0, 20, 60, 60, 60)
region_2or3 = Xponge.UnionRegion(region_2, region_3)
region_4and5 = Xponge.IntersectRegion(region_4, region_5)
t = Xponge.Lattice("bcc", basis_molecule=CL, scale=4)
t2 = Xponge.Lattice("fcc", basis_molecule=K, scale=3)
t3 = Xponge.Lattice("sc", basis_molecule=NA, scale=3)
mol = t.Create(box, region_1)
mol = t2.create(box, region_2or3, mol)
mol = t3.create(box, region_4and5, mol)
Xponge.Save_PDB(mol, "out.pdb")
```
Then we can see `out.pdb` in VMD:
## Detailed usage and API documentation
All can be seen [here](https://spongemm.cn/xponge_doc/index.html).
## Contribution Guideline
If you want to contribute to the main codebase or report some issues, see [here](https://spongemm.cn/xponge_doc/contribution_guide.html) for the guides.
## Dependencies
`Xponge` does not depend on other packages except numpy for its basic use.
However, there are some complicated functions that depend on some other packages. If you do not install the dependent package, you can not use the related functions.
Here is the list of all packages which may be uesd:
| package name | description | how to install |
| ------------------| --------------------------------- | ------------------------------ |
| XpongeLib | c/c++ compiled library for Xponge | `pip install XpongeLib` |
| pyscf [2-4] | quantum chemistry | `pip install pyscf` |
| geometric[5] | geometry optimization | `pip install geometric` |
| rdkit[6] | cheminformatics | `conda install -c rdkit rdkit` |
| MDAnalysis[7-8] | trajectory analysis | `pip install MDAnalysis` |
| matplotlib | plot and visualization | `pip install matplotlib` |
| mindspore[9] | AI framework for machine learning | See the [official website](https://www.mindspore.cn/install)|
| mindsponge[1] | end-to-end differentiable MD | See the [official website](https://www.mindspore.cn/mindscience/docs/en/master/mindsponge/intro_and_install.html)|
## References
[0] Y. Xia, Y. Q. Gao, *J. Open Source Softw.* (2022) DOI:[10.21105/joss.04467](https://doi.org/10.21105/joss.04467)
[1] Y.-P. Huang, et al. *Chinese J. Chem.* (2022) DOI: [10.1002/cjoc.202100456](https://doi.org/10.1002/cjoc.202100456)
[2] Q. Sun, et al. *J. Chem. Phys.* (2020) DOI: [10.1063/5.0006074](https://doi.org/10.1063/5.0006074)
[3] Q. Sun, et al. Wiley Interdiscip. *Rev. Comput. Mol. Sci.* (2018) DOI: [10.1002/wcms.1340](https://doi.org/10.1002/wcms.1340)
[4] Q. Sun, *J. Comp. Chem.* (2015) DOI: [10.1002/jcc.23981](https://doi.org/10.1002/jcc.23981)
[5] L.-P. Wang, C.C. Song, *J. Chem. Phys.* (2016) DOI: [10.1063/1.4952956](https://doi.org/10.1063/1.4952956)
[6] RDKit: Open-source cheminformatics. https://www.rdkit.org
[7] R. J. Gowers, et al. Proceedings of the 15th Python in Science Conference (2016) DOI: [10.25080/majora-629e541a-00e](https://doi.org/10.25080/majora-629e541a-00e)
[8] N. Michaud-Agrawal, et al. *J. Comput. Chem.* (2011) DOI: [10.1002/jcc.21787](https://10.1002/jcc.21787)
[9] MindSpore: An Open AI Framwork. https://www.mindspore.cn/
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"description": "# Welcome to Use Xponge!\r\n\r\n## Introduction\r\n\r\n``Xponge`` is a lightweight and easy to customize python package to perform pre- and post-processing of molecular simulations.\r\n\r\n### What can Xponge do?\r\n\r\nXponge includes three major categories of functionality, namely, the simulation system construction, simulation data transformation and analysis, and automated workflows for complex simulations. ``Xponge`` is mainly designed for the molecular dynamics (MD) program [SPONGE](https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjoc.202100456)[1], but it can also output some general format files such as mol2 and PDB, so it may help the other molecular modelling programs too.\r\n\r\n## Installation\r\n\r\nXponge can be used on all operating systems (Windows/Linux/MacOS). Some functions (See [here](https://spongemm.cn/xponge_doc/dependency.html#unavalable-functions-on-windows) for the detailed list) to do the quantum chemistry calculations can not be used on Windows because `pyscf` is not available on Windows.\r\n\r\n### 1. pip install\r\n\r\n```bash\r\npip install Xponge\r\n```\r\n\r\n### 2. source setup\r\n\r\n- 2.1 Download or clone the source from the gitee or github repository\r\n\r\n The gitee repository is [here](https://gitee.com/gao_hyp_xyj_admin/xponge).\r\n The github repository is [here](https://github.com/xia-yijie/xponge).\r\n\r\n git clone http://gitee.com/gao_hyp_xyj_admin/xponge.git\r\n git clone http://github.com/xia-yijie/xponge.git\r\n\r\n- 2.2 Open the directory where you download or clone the repository\r\n\r\n- 2.3 (Optional) Configure the environment\r\n\r\n It is recommended to use `conda` to configure the environment. Two `yml` files named `install_requirements.yml` and `extras_requirements.yml` are provided in the repository.\r\n\r\n It is recommanded to use the file `install_requirements.yml` to configure the environment. The file will only install the basic dependent packages. If a `ModuleNotFoundError` is raised when you are using `Xponge`, then install the module. This allows you to avoid installing many modules that you will never use, and also makes `Xponge` more cross-platform compatible. Here are the commands to use `install_requirements.yml`.\r\n\r\n ```bash\r\n conda env create -f install_requirements.yml\r\n conda activate Xponge\r\n ```\r\n\r\n All the dependent packages are listed in the [dependencies](#dependencies) section. If you don't want to install the dependent packages one by one (which can be really annoying), the file `extras_requirements.yml` can help you with the environment configuration except the packages `mindspore` and `mindsponge`. The two packages should be installed according to your device (e.g. whether the backend is CPU, GPU or Huawei Ascend Processors) and can not be simply installed by conda. Here are the commands to use `extras_requirements.yml`.\r\n\r\n ```bash\r\n conda env create -f extras_requirements.yml\r\n conda activate Xponge\r\n ```\r\n\r\n It is worth noting that `extras_requirements.yml` can not be used on Windows because `pyscf` is not available on Windows.\r\n\r\n- 2.4 Run the command\r\n\r\n ```bash\r\n python setup.py install\r\n ```\r\n\r\n### Installation check\r\n\r\nThere are some unit tests in ``Xponge``. You can do the basic test to check whether the installation is successful like this:\r\n\r\n```bash\r\nXponge test --do base -o test --verbose 1\r\n```\r\n\r\nHere, ``Xponge`` can be replaced to ``python -m Xponge``, ``python3 -m Xponge`` and so on according to your settings of the environmental variables. Some files will be generated after the test is finished.\r\n\r\n## Quickstart\r\n\r\nHere is a simple example.\r\n\r\n```python\r\nimport Xponge\r\n# Import the force field you need\r\nimport Xponge.forcefield.amber.ff14sb\r\n# Build the molecule like this\r\npeptide = ACE + ALA + NME\r\n# or like this\r\npeptide2 = NALA + ALA * 10 + CALA\r\n# or like this\r\npeptide3 = Xponge.Get_Peptide_From_Sequence(\"AAAAA\")\r\n# See the documentation for more usage!\r\n# Save them as your favorite format\r\nXponge.save_pdb(peptide, \"ala.pdb\")\r\nXponge.save_mol2(peptide2, \"ala12.mol2\")\r\nXponge.save_sponge_input(peptide3, \"ala5\")\r\n```\r\n\r\nThen we can see `ala12.mol2` in VMD:\r\n\r\n\r\n\r\nHere is another simple example.\r\n\r\n```python\r\nimport Xponge\r\nimport Xponge.forcefield.amber.tip3p\r\n\r\nbox = Xponge.BlockRegion(0, 0, 0, 60, 60, 60)\r\nregion_1 = Xponge.BlockRegion(0, 0, 20, 20, 20, 40)\r\nregion_2 = Xponge.BlockRegion(0, 0, 40, 20, 20, 60)\r\nregion_3 = Xponge.BlockRegion(0, 0, 0, 20, 20, 20)\r\nregion_4 = Xponge.SphereRegion(20, 10, 30, 10)\r\nregion_5 = Xponge.BlockRegion(20, 0, 20, 60, 60, 60)\r\nregion_2or3 = Xponge.UnionRegion(region_2, region_3)\r\nregion_4and5 = Xponge.IntersectRegion(region_4, region_5)\r\nt = Xponge.Lattice(\"bcc\", basis_molecule=CL, scale=4)\r\nt2 = Xponge.Lattice(\"fcc\", basis_molecule=K, scale=3)\r\nt3 = Xponge.Lattice(\"sc\", basis_molecule=NA, scale=3)\r\nmol = t.Create(box, region_1)\r\nmol = t2.create(box, region_2or3, mol)\r\nmol = t3.create(box, region_4and5, mol)\r\nXponge.Save_PDB(mol, \"out.pdb\")\r\n```\r\n\r\nThen we can see `out.pdb` in VMD:\r\n\r\n\r\n\r\n## Detailed usage and API documentation\r\n\r\nAll can be seen [here](https://spongemm.cn/xponge_doc/index.html).\r\n\r\n## Contribution Guideline\r\n\r\nIf you want to contribute to the main codebase or report some issues, see [here](https://spongemm.cn/xponge_doc/contribution_guide.html) for the guides.\r\n\r\n## Dependencies\r\n\r\n`Xponge` does not depend on other packages except numpy for its basic use.\r\n\r\nHowever, there are some complicated functions that depend on some other packages. If you do not install the dependent package, you can not use the related functions.\r\n\r\nHere is the list of all packages which may be uesd:\r\n\r\n| package name | description | how to install |\r\n| ------------------| --------------------------------- | ------------------------------ |\r\n| XpongeLib | c/c++ compiled library for Xponge | `pip install XpongeLib` |\r\n| pyscf [2-4] | quantum chemistry | `pip install pyscf` |\r\n| geometric[5] | geometry optimization | `pip install geometric` |\r\n| rdkit[6] | cheminformatics | `conda install -c rdkit rdkit` |\r\n| MDAnalysis[7-8] | trajectory analysis | `pip install MDAnalysis` |\r\n| matplotlib | plot and visualization | `pip install matplotlib` |\r\n| mindspore[9] | AI framework for machine learning | See the [official website](https://www.mindspore.cn/install)|\r\n| mindsponge[1] | end-to-end differentiable MD | See the [official website](https://www.mindspore.cn/mindscience/docs/en/master/mindsponge/intro_and_install.html)|\r\n\r\n## References\r\n\r\n[0] Y. Xia, Y. Q. Gao, *J. Open Source Softw.* (2022) DOI:[10.21105/joss.04467](https://doi.org/10.21105/joss.04467)\r\n\r\n[1] Y.-P. Huang, et al. *Chinese J. Chem.* (2022) DOI: [10.1002/cjoc.202100456](https://doi.org/10.1002/cjoc.202100456)\r\n\r\n[2] Q. Sun, et al. *J. Chem. Phys.* (2020) DOI: [10.1063/5.0006074](https://doi.org/10.1063/5.0006074)\r\n\r\n[3] Q. Sun, et al. Wiley Interdiscip. *Rev. Comput. Mol. Sci.* (2018) DOI: [10.1002/wcms.1340](https://doi.org/10.1002/wcms.1340)\r\n\r\n[4] Q. Sun, *J. Comp. Chem.* (2015) DOI: [10.1002/jcc.23981](https://doi.org/10.1002/jcc.23981)\r\n\r\n[5] L.-P. Wang, C.C. Song, *J. Chem. Phys.* (2016) DOI: [10.1063/1.4952956](https://doi.org/10.1063/1.4952956)\r\n\r\n[6] RDKit: Open-source cheminformatics. https://www.rdkit.org\r\n\r\n[7] R. J. Gowers, et al. Proceedings of the 15th Python in Science Conference (2016) DOI: [10.25080/majora-629e541a-00e](https://doi.org/10.25080/majora-629e541a-00e)\r\n\r\n[8] N. Michaud-Agrawal, et al. *J. Comput. Chem.* (2011) DOI: [10.1002/jcc.21787](https://10.1002/jcc.21787)\r\n\r\n[9] MindSpore: An Open AI Framwork. https://www.mindspore.cn/\r\n",
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