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"author": "Morten Ledum",
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"description": "OccamTools\n·\n[](https://travis-ci.com/mortele/OccamTools) [](https://www.codacy.com?utm_source=github.com&utm_medium=referral&utm_content=mortele/OccamTools&utm_campaign=Badge_Grade) [](https://codecov.io/gh/mortele/OccamTools) [](https://www.gnu.org/licenses/gpl-3.0) [](https://badge.fury.io/py/occamtools)\n=========\nAnalysis and synthesis tools for [OCCAM](#OCCAM) molecular dynamics/hybrid particle-field simulations.\n\nInput to [OCCAM](#OCCAM) consists mainly of three file types; `fort.1` (simulation metadata), `fort.3` (particle and bond parameters), and `fort.5` (positions and bond structure). The output from the run is a `fort.8` file, adhering to the [`.xyz`](https://en.wikipedia.org/wiki/XYZ_file_format) file format. The `occamtools` python package provides a reader for these file formats (both input and output) and generates a single object containing all the information about the simulation, making analysis of simulation runs and comparison between runs easier.\n\nInstallation\n---------\nInstall by (requires **python >= 3.6**)\n```bash\n> pip install occamtools\n```\n\nUsage\n---------\n**Loading data**\n·\nLoading simulation data is done by\n```python\nimport numpy as np\nfrom occamtools import OccamData\n\ndata = OccamData('your/file/or/directory/here')\n```\nwhere the `data` object now holds all information about the simulation run, e.g. print what kinds of particles a simulation consists of\n```python\nprint('Simulation consists of...')\nfor type_name in data.type_dict:\n num_type = sum(data.type == data.type_dict[type_name])\n print(f' - {num_type} particles of type {type_name}')\n\n# Simulation consists of...\n# - 400 particles of type H\n# - 100 particles of type C\n# - 250 particles of type Ar\n# ...\n```\nor make a simple plot of particles in a section of the simulation box diffusing (requires `pip install asciichartpy`)\n```python\nfrom asciichartpy import plot\n\nindices = (data.x[0, :] > 20.0) & (data.x[0, :] < 25.0)\ndiffused = data.x[-1, indices]\nbins, hist = np.histogram(diffused)\nprint(plot(bins.tolist(), hist.tolist()))\n\n# 9.00 \u2524 \u256d\u2500\u256e\n# 8.00 \u2524 \u2502 \u2570\u256e\n# 7.00 \u2524 \u2502 \u2502\n# 6.00 \u2524 \u256d\u256f \u2570\u256e\n# 5.00 \u2524 \u2502 \u2570\u256e\n# 4.00 \u2524 \u2502 \u2502\n# 3.00 \u2524\u256d\u256f \u2502\n# 2.00 \u2524\u2502 \u2570\u256e\n# 1.00 \u253c\u256f \u2570\n```\nor plot the deviations of the total kinetic energy from the mean over the simulation run (again requires `pip install asciichartpy`)\n```python\nkinetic_energy_deviations = data.kinetic_energy - np.mean(data.kinetic_energy)\nprint(plot(kinetic_energy_deviations.tolist()))\n\n# 60.53 \u2524 \u256d\u256e\n# 50.62 \u2524 \u2502\u2502 \u256d\u256e\u256d\u256e\n# 40.71 \u2524 \u2502\u2502 \u2502\u2502\u2502\u2502 \u256d\u256e\n# 30.81 \u2524 \u2502\u2502 \u2502\u2502\u2502\u2502 \u2502\u2502 \u256d\u256e \u256d\u2500\n# 20.90 \u2524 \u256d\u256e \u2502\u2502 \u2502\u2502\u2502\u2502 \u256d\u2500\u256e \u2502\u2502 \u2502\u2502 \u2502\n# 10.99 \u2524 \u2502\u2502 \u256d\u2500\u256e \u256d\u256e \u256d\u256f\u2502 \u2502\u2502\u2502\u2502\u256d\u256e \u2502 \u2502 \u256d\u256e \u2502\u2502 \u2502\u2502 \u2502\n# 10.09 \u2524 \u2502\u2502 \u2502 \u2502 \u2502\u2502 \u2502 \u2502 \u2502\u2502\u2502\u2502\u2502\u2570\u256e \u2502 \u2570\u256e\u2502\u2502 \u2502\u2502 \u256d\u256e \u2502\u2502\u256d\u256e\u256d\u256e\u2502\n# 0.18 \u253c\u256e\u2502\u2502 \u2502 \u2502 \u2502\u2502 \u2502 \u2570\u256e \u2502\u2502\u2502\u2570\u256f \u2502 \u2502 \u2570\u256f\u2502\u256d\u256e \u2502\u2570\u256e\u2502\u2502\u256d\u256e\u2502\u2502\u2502\u2502\u2502\u2502\u2502\n# -00.73 \u2524\u2502\u2502\u2502 \u2502 \u2502 \u2502\u2502 \u2502 \u2570\u2500\u256f\u2502\u2502 \u2502\u256d\u256f \u2502\u2502\u2570\u2500\u2500\u256f \u2570\u256f\u2502\u2502\u2502\u2502\u2502\u2502\u2502\u2502\u2502\u2502\n# -10.64 \u2524\u2502\u2502\u2502\u256d\u256f \u2502 \u2502\u2502\u256d\u256f \u2502\u2502 \u2502\u2502 \u2570\u256f \u2502\u2502\u2502\u2502\u2502\u2502\u2502\u2502\u2570\u256f\n# -20.54 \u2524\u2502\u2502\u2570\u256f \u2502 \u2502\u2570\u256f \u2570\u256f \u2570\u256f \u2502\u2502\u2502\u2502\u2502\u2502\u2570\u256f\n# -30.45 \u2524\u2570\u256f \u2570\u2500\u256f \u2502\u2502\u2502\u2502\u2570\u256f\n# -40.36 \u2524 \u2502\u2502\u2502\u2502\n# -50.26 \u2524 \u2502\u2502\u2570\u256f\n# -60.17 \u2524 \u2570\u256f\n```\n\n**File storage**\n·\nBehind the scenes, `.npy` (for numpy arrays) and `.json` (for anything else) files are used to represent the simulation data. By default, loading a simulation run causes the saving of small (relative to the original `fort.5/7/8`) binary files containing the data. These are used to load from on subsequent calls. This means calls to `OccamData.load('your/file/here')` of `OccamData('your/file/here')` will be significantly faster *after* the first call. In this specific example, a 25x speedup is achieved (but your mileage may vary).\n\n\nRunning tests with `tox`\n---------\nAssuming python `3.7` is already installed, install separate `3.6` and `3.8` instances using `pyenv` by\n```bash\n> brew install pyenv\n> pyenv install 3.6.6\n> pyenv install 3.8-dev\n```\nand then inside the `occamtools` directory do\n```bash\n> git clone git@github.com:mortele/OccamTools.git occamtools\n> cd occamtools\n> pyenv local 3.6.6 3.8-dev\n> pip3 install tox-pyenv\n> tox\n```\nwhich will run unit tests (using `pytest`) with python versions `3.6`, `3.7`, and the `3.8` development build.\n\nOCCAM\n---------\nOCCAM is a program for Molecular Dynamics Simulations able to perform Hybrid Particle-Field (PF) Theoretical Molecular Dynamics simulations. This recent PF technique combines molecular dynamics (MD) and self consistent field theory (SCF). [Read more.](http://www.occammd.org/about/)\n\n[](http://www.occammd.org/)\n\nChangelog\n---------\n**0.3.3**: Add option to not save `.npy` files when loading `OccamData` objects. Fix a bug causing errors when reading very short `.xyz` files. Fix a bug causing the grid size to not correctly update when using `replace_in_fort3`.
\n**0.3.2**: Add testing with python alpha version `3.8-dev`, stream line travis integration and coverage reporting.
\n**0.3.1**: Move the `bins` keyword argument to `histogram` from an explicit argument to `**kwargs` handled by `np.histogram`.
\n**0.3.0**: Add histogram computation capabilities.
\n**0.2.7**: Add the `velocity_traj` flag to `fort1` file reader.
\n**0.2.6**: Add proper testing for python `3.6` and `3.7` using [`tox`](https://pypi.org/project/tox/).
\n**0.2.5**: Change python version required to `>=3.6` (from `>=3.7`).
\n**0.2.4**: Add functionality for reading `.xyz` files with additional velocity information, as output by OCCAM when the `velocity_traj` flag is set in `fort.1`.
\n**0.2.3**: Code clean-up.
\n**0.2.2**: Extend `repace_in_fort3` to allow for changing compressibility and non-bonded interactions. Fix a bug causing new particle types added to break the chi matrix when writing `fort.3` files.
\n**0.2.1**: Update the `__all__` variable of `__init__.py` to reflect newly added classes and methods.
\n**0.2.0**: Add functionality for editing `fort.3` files (in-place or creating new ones).
\n**0.1.0**: Add functionality for editing `fort.1` files (in-place or creating new ones).
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