From 73a145b08f10e85ad4260d6a851de0f8cd5867dd Mon Sep 17 00:00:00 2001 From: Kamal Choudhary Date: Tue, 30 Jul 2019 22:54:00 -0400 Subject: [PATCH] pypi update (#47) * Created using Colaboratory * Created using Colaboratory * Created using Colaboratory * Created using Colaboratory * Created using Colaboratory * Created using Colaboratory * Created using Colaboratory * Created using Colaboratory * Created using Colaboratory * Created using Colaboratory * Created using Colaboratory * Delete Python_novice.ipynb * Add files via upload * Update README.rst * Update README.rst * coverage update * no boltztrap test * vaspwf update * colab figs * Update README.rst * colab figs * Update README.rst * version update * pypi readme update * pypi notes update --- README.rst | 66 ++++++++++++++++++++++++++------------ jarvis/dev_notes/pypi_note | 1 + setup.py | 3 +- 3 files changed, 47 insertions(+), 23 deletions(-) diff --git a/README.rst b/README.rst index 3feb08ea..f984b146 100644 --- a/README.rst +++ b/README.rst @@ -15,7 +15,7 @@ :target: https://codecov.io/gh/knc6/jarvis JARVIS -===== +========== Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated framework for computational science using density functional theory, classical force-field/molecular dynamics and machine-learning. The jarvis-tools package can be used for high-throughput computation, data-analysis, and training machine-learning models. Some of the packages used in the jarvis-tools package are shown below. JARVIS-official website: https://jarvis.nist.gov @@ -24,8 +24,10 @@ classical force-field/molecular dynamics and machine-learning. The jarvis-tools :target: https://jarvis.nist.gov/ .. image:: https://github.com/knc6/jarvis/blob/master/jarvis/colab/colab_figures/statistics.JPG :target: https://jarvis.nist.gov/ + Installing JARVIS ------------------ +-------------------- + - We recommend installing miniconda environment from https://conda.io/miniconda.html :: bash Miniconda3-latest-Linux-x86_64.sh (for linux) @@ -55,30 +57,42 @@ Installing JARVIS Jupyter notebooks ----------------- -- Python for beginners:: + +- Python for beginners: + .. image:: https://github.com/knc6/jarvis/blob/master/jarvis/colab/colab_figures/novice.JPG :target: https://colab.research.google.com/github/knc6/jarvis/blob/master/jarvis/colab/python_novice_notebook.ipynb -- JARVIS-DFT data analysis:: + +- JARVIS-DFT data analysis: + .. image:: https://github.com/knc6/jarvis/blob/master/jarvis/colab/colab_figures/jdft.JPG :target: https://colab.research.google.com/github/knc6/jarvis/blob/master/jarvis/colab/jarvis_dft_explore_notebook.ipynb -- JARVIS-ML training:: + +- JARVIS-ML training: + .. image:: https://github.com/knc6/jarvis/blob/master/jarvis/colab/colab_figures/jml_train.JPG :target: https://colab.research.google.com/github/knc6/jarvis/blob/master/jarvis/colab/jarvis_ml_quick_train_notebook.ipynb -- Comparing ML algorithms:: + +- Comparing ML algorithms: + .. image:: https://github.com/knc6/jarvis/blob/master/jarvis/colab/colab_figures/compareml.JPG :target: https://colab.research.google.com/github/knc6/jarvis/blob/master/jarvis/colab/compare_ml_algorithms_notebook.ipynb -- JARVIS-FF data-analysis:: + +- JARVIS-FF data-analysis: + .. image:: https://github.com/knc6/jarvis/blob/master/jarvis/colab/colab_figures/jff.JPG :target: https://colab.research.google.com/github/knc6/jarvis/blob/master/jarvis/colab/jarvis_ff_explore_notebook.ipynb + - See more in the plot-gallery below References ----------------- -- JARVIS-FF:: + +- JARVIS-FF: 1) Evaluation and comparison of classical interatomic potentials through a user-friendly interactive web-interface, Nature: Sci Data. 4, 160125 (2017).https://www.nature.com/articles/sdata2016125 2) High-throughput assessment of vacancy formation and surface energies of materials using classical force-fields, J. Phys. Cond. Matt. 30, 395901(2018).http://iopscience.iop.org/article/10.1088/1361-648X/aadaff/meta -- JARVIS-DFT:: +- JARVIS-DFT: 3) High-throughput Identification and Characterization of Two-dimensional Materials using Density functional theory, Scientific Reports 7, 5179 (2017).https://www.nature.com/articles/s41598-017-05402-0 4) Computational Screening of High-performance Optoelectronic Materials using OptB88vdW and TBmBJ Formalisms, Scientific Data 5, 180082 (2018).https://www.nature.com/articles/sdata201882 5) Elastic properties of bulk and low-dimensional materials using van der Waals density functional, Phys. Rev. B, 98, 014107 (2018).https://journals.aps.org/prb/abstract/10.1103/PhysRevB.98.014107 @@ -86,14 +100,14 @@ References 7) High-throughput Discovery of Topologically Non-trivial Materials using Spin-orbit Spillage, Nature: Sci. Rep. 9, 8534,(2019), https://www.nature.com/articles/s41598-019-45028-y 8) Accelerated Discovery of Efficient Solar-cell Materials using Quantum and Machine-learning Methods, Chem. Mater., https://pubs.acs.org/doi/10.1021/acs.chemmater.9b02166 9) Data-driven Discovery of 3D and 2D Thermoelectric Materials , https://arxiv.org/abs/1903.06651. -- JARVIS-ML:: +- JARVIS-ML: 10) Machine learning with force-field inspired descriptors for materials: fast screening and mapping energy landscape, Phys. Rev. Mat., 2, 083801 (2018).,https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.2.083801 11) Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics, MRS Comm., 1-18 https://doi.org/10.1557/mrc.2019.95 Pypi, Readthedocs and Slideshare links ------------------ +----------------------------------------- https://pypi.org/project/jarvis-tools https://jarvis-tools.readthedocs.io/en/latest/ @@ -101,61 +115,71 @@ Pypi, Readthedocs and Slideshare links https://www.slideshare.net/KAMALCHOUDHARY4 Running the examples ------------------ +-------------------------------- - For running high-throughput calculations, set HPC/system related information in env_variables - Run py.test in tests folder to ensure basic setup -- LAMMPS example:: +- LAMMPS example: An example calculation for Aluminum is given in the lammps folder for running EAM calculation (https://github.com/usnistgov/jarvis/blob/master/jarvis/lammps/examples/basic_input_output.py). Untar the example folder using tar -xvzf Al03.eam.alloy_nist.tgz . Change the 'parameters' variable and run jlammps.py. -- VASP example:: +- VASP example: Similarly, an example calculation for Silicon is given in vasp folder (https://github.com/usnistgov/jarvis/blob/master/jarvis/vasp/examples/runstruct_pyvasp.py). The input is a POSCAR file, which is already provided. executable paths, pseudopotential directory path and Special_POTCAR.yaml path needs to be adjusted in joptb88vdw.py top section. The master.py can be submitted to the queuing system with qsub sub.sh. -- ML example:: +- ML example: We trained machine learning models using JARVIS-DFT data on bandgaps, formation energies and elastic modulus and other properties. We used both chemical and structural descriptors during GradientBoostingRegression training. Example of getting 1557 descriptors for a system is given at: https://github.com/usnistgov/jarvis/blob/master/jarvis/sklearn/examples/desc_example.py -- Access to JARVIS database:: +- Access to JARVIS database: Our database is freely available at https://www.ctcms.nist.gov/~knc6/JVASP.html, https://www.ctcms.nist.gov/jarvisml/, https://www.ctcms.nist.gov/~knc6/periodic.html, and https://www.ctcms.nist.gov/~knc6/JLAMMPS.html for JARVIS-DFT, JARVIS-ML and JARVIS-FF. We can also load the dataset using python scripts similar to https://github.com/knc6/jarvis/blob/master/jarvis/db/static/explore_db.py . -- Uploading your data using JARVIS-API:: +- Uploading your data using JARVIS-API: In addition to downloading/browsing through the JARVIS-database, one can also upload their data and query using JARVIS-API. Follow the instructions in https://github.com/usnistgov/jarvis/blob/master/jarvis/db/mdcs/mdcs_api.py Founders ------------------ +-------------------------------- Kamal Choudhary, Francesca Tavazza (NIST) Contributors ------------------ +----------------------------------- Daniel Wheeler, Faical Yannick Congo, Kevin Garrity, Brian DeCost, Adam Biacchi, Lucas Hale, Andrew Reid, Marcus Newrock (NIST) Plot-gallery with additional jupyter notebooks ------------------ +----------------------------------------------------- .. class:: center .. image:: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/RDF.png + :Notebook: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/RDF%2CPRDF%2CADF%2CDDF.ipynb .. image:: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/ADF-a.png + :Notebook: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/RDF%2CPRDF%2CADF%2CDDF.ipynb .. image:: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/ADF-b.png + :Notebook: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/RDF%2CPRDF%2CADF%2CDDF.ipynb .. image:: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/DDF.png + :Notebook: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/RDF%2CPRDF%2CADF%2CDDF.ipynb .. image:: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/bandstr.jpg + :Notebook: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/band_structure.ipynb .. image:: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/Dos.png + :Notebook: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/band_structure.ipynb .. image:: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/Wulff.png + :Notebook: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/Wulff.ipynb .. image:: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/BoltzTrap.png + :Notebook: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/Boltztrap.ipynb .. image:: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/kp_converg.png + :Notebook: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/Convergence.ipynb .. image:: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/en_converg.png -:Notebook: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/Convergence.ipynb + +:Notebook: https://github.com/usnistgov/jarvis/blob/master/jarvis/db/static/Convergence.ipynb \ No newline at end of file diff --git a/jarvis/dev_notes/pypi_note b/jarvis/dev_notes/pypi_note index d0f3df3c..6a228d07 100644 --- a/jarvis/dev_notes/pypi_note +++ b/jarvis/dev_notes/pypi_note @@ -11,4 +11,5 @@ password = xyz +++++++++++++++++++++++++ python setup.py sdist bdist_wheel --universal +twine check dist/* twine upload dist/* diff --git a/setup.py b/setup.py index bde94e2a..be5e852f 100644 --- a/setup.py +++ b/setup.py @@ -11,10 +11,9 @@ setup( name="jarvis-tools", - version="2019.07.23.1", + version="2019.7.31", long_description=long_d, - long_description_content_type='text/markdown', install_requires=[ "numpy==1.16.3", "scipy==1.2.1",