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# Dependencies
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`YASS.jl` relies on several specialized external packages. These packages actively maintained and well trusted within the Julia ecosystem. If this changes, `YASS.jl` will remove these dependencies and if necessary implement the specialized code in-house. Here the dependencies are listed with links to their repos to give credit to their work but also to provide transperancy.
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YASS relies on several specialized external packages. These packages actively maintained and well trusted within the Julia ecosystem. If this changes, YASS will remove these dependencies and if necessary implement the specialized code in-house. Here the dependencies are listed with links to their repos to give credit to their work but also to provide transperancy.
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Packages within the Julia standard library are listed seperately since they are expected to be maintained as well as the Julia langague itself. For each dependency there is a short description of how it is used in `YASS.jl`, or why it is considered for removal.
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Packages within the Julia standard library are listed seperately since they are expected to be maintained as well as the Julia langague itself. For each dependency there is a short description of how it is used in YASS, or why it is considered for removal.
-[JLD2](https://github.com/JuliaIO/JLD2.jl): This package is currently only used to load neural network data for potentials. This functionality can be covered by the `Serialization` package, which can reduce the total dependency count. Note, this is a well maintained package and users are encouraged to use it alongside `YASS.jl`.
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-[DataFrames](https://github.com/JuliaData/DataFrames.jl): This package does not add any functionality to `YASS.jl`, but rather enchances user exerpience. However, this can be achieved by users using the package alongside `YASS.jl`, rather than it being a dependency. Note, this is a well maintained package and users are encouraged to use it alongside `YASS.jl`.
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-[JLD2](https://github.com/JuliaIO/JLD2.jl): This package is currently only used to load neural network data for potentials. This functionality can be covered by the `Serialization` package, which can reduce the total dependency count. Note, this is a well maintained package and users are encouraged to use it alongside YASS.
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-[DataFrames](https://github.com/JuliaData/DataFrames.jl): This package does not add any functionality to YASS, but rather enchances user exerpience. However, this can be achieved by users using the package alongside YASS, rather than it being a dependency. Note, this is a well maintained package and users are encouraged to use it alongside YASS.
Copy file name to clipboardExpand all lines: docs/src/index.md
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!!! warning "YASS.jl is still in the pre-release phase"
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This package is still very early in its development, and there are more mature molecular dynamics packages in Julia. For instance, [Molly.jl](https://juliamolsim.github.io/Molly.jl/stable/) and [NQCDynamics.jl](https://nqcd.github.io/NQCDynamics.jl/stable/) both offer molecular dyanmics in Julia.
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Yet Another Simulation Suite (`YASS.jl`) aims to offer users a simple, intuitive and easy-to-use molecular dynamics enviornment. It draws inspiration from Python's [ASE](https://wiki.fysik.dtu.dk/ase/index.html), but is intended to be faster and offer users more flexibility. The flexibility comes from the relative ease with which users can add their own methods to dynamics or other components of `YASS.jl`.
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Yet Another Simulation Suite (YASS) aims to offer users a simple, intuitive and easy-to-use molecular dynamics enviornment. It draws inspiration from Python's [ASE](https://wiki.fysik.dtu.dk/ase/index.html), but is intended to be faster and offer users more flexibility. The flexibility comes from the relative ease with which users can add their own methods to dynamics or other components of YASS.
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### Installation
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`YASS.jl` is not yet on the general registry, so for now installation can be done via GitHub.
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YASS is not yet on the general registry, so for now installation can be done via GitHub.
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```julia-repl
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pkg> add https://github.com/Cavenfish/YASS.jl
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```
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If you are more adventerous, you can consider installing the `dev` branch of `YASS.jl`. This will get updates more frequently, which gives users more features but also comes with increased chances of bugs.
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If you are more adventerous, you can consider installing the `dev` branch of YASS. This will get updates more frequently, which gives users more features but also comes with increased chances of bugs.
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```julia-repl
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pkg> add https://github.com/Cavenfish/YASS.jl#dev
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```
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### Features
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Currently, `YASS.jl` is able to perform the following simulations/calculations on molecular systems.
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Currently, YASS is able to perform the following simulations/calculations on molecular systems.
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# Molecular Dynamics Simulations
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`YASS.jl` provides functionality for classical molecular dynamics simulations in different ensembles. This guide explains how to set up and run MD simulations.
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YASS provides functionality for classical molecular dynamics simulations in different ensembles. This guide explains how to set up and run MD simulations.
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## Basic Usage
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The simplest way to run an MD simulation is in the NVE (microcanonical) ensemble:
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```julia
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usingYASS
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usingYetAnotherSimulationSuite
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# Read initial structure
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water =readSystem("water.xyz")
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```
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### NVT Ensemble
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The NVT ensemble maintains constant temperature using a thermostat. `YASS.jl` supports several thermostats:
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The NVT ensemble maintains constant temperature using a thermostat. YASS supports several thermostats:
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# Thermostats
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`YASS.jl` includes some pre-written thermostats for use in molecular dyunamics simulations. However, it is also fairly easy to create a custom thermostat to use in simulations.
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YASS includes some pre-written thermostats for use in molecular dyunamics simulations. However, it is also fairly easy to create a custom thermostat to use in simulations.
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The included thermostats are:
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Here the `Berendsen` thermostat is shown to illustrate how to create a custom thermostat. Custom thermostats require a struct for their parameters and an action function.
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# Geometry Optimizations
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`YASS.jl` provides geometry optimization capabilities through [Optim.jl](https://julianlsolvers.github.io/Optim.jl/stable/). This section explains how to optimize molecular structures and crystal cells.
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YASS provides geometry optimization capabilities through [Optim.jl](https://julianlsolvers.github.io/Optim.jl/stable/). This section explains how to optimize molecular structures and crystal cells.
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## Basic Usage
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The simplest way to optimize a molecular structure is:
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```julia
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using YASS
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using Optim
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using YetAnotherSimulationSuite
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# Read initial structure
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molecule =readSystem("water.xyz")
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# Run geometry optimization
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optimized =opt(TIP4Pf(), YASS.LBFGS(), molecule)
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optimized =opt(TIP4Pf(), LBFGS(), molecule)
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# Save optimized structure
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write("optimized.xyz", optimized)
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```
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## Optimization Algorithms
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`YASS.jl` provides access to all Optim.jl algorithms. You can either use them through `YASS`:
Copy file name to clipboardExpand all lines: docs/src/potentials/customPot.md
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# Custom Potentials
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`YASS.jl` allows you to implement custom potentials for molecular simulations. This guide demonstrates how to create a custom potential using a Lennard-Jones potential for gold (Au) as an example. To create a custom potential, you need three components:
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YASS allows you to implement custom potentials for molecular simulations. This guide demonstrates how to create a custom potential using a Lennard-Jones potential for gold (Au) as an example. To create a custom potential, you need three components:
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1.`PotVars` struct - Holds potential parameters
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2. Initializer function - Sets up the potential
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3. Evaluation functions - Calculate energies and forces
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