Quick Start

Julia is just-in-time (JIT) compiled, which means that the first time you run a block of code it will be slow. Users new to Julia are strongly encouraged to start with the Docker version provided with the Tutorial. The version bundled in the Docker container comes with an optimized system image, which has a much reduced JIT lag. It also simplifies the installation. The version in the Docker container/tutorial can also be used to work with the package.

Documentation

The tutorial is a guided tour of the package, including background information on the instrument and technique. The Manual section gives high-level examples on how to use the code. There is some overlap between the tutorial, the notebooks and the manual. The Library section is a browsable version of the code. It serves as reference to learn more about the definitions of operators, data types, and functions.

Local Installation

The package can be installed from the Julia package prompt with

julia> ]add  https://github.com/mdpetters/DifferentialMobilityAnalyzers.jl.git

The closing square bracket switches to the package manager interface and the add command installs the package and any missing dependencies. To return to the Julia REPL hit the delete key.

To load the package run

julia> using DifferentialMobilityAnalyzers

Additional dependencies are needed when running the notebooks on the local install.

julia> ] add Calculus DataFrames Distributions Glob IJulia Interpolations LambertW LinearAlgebra LsqFit NetCDF ORCA PlotlyJS Plots Printf ProgressMeter Random SpecialFunctions StatsBase Gadfly Compose