This package is a meta-package for a wide variety of commonly used Julia packages. It is designed to make it easy to include one package that handles the diversity of technical computing requirements for an undergraduate degree.
Topics (and the packages that support them)
- Discrete Mathematics
- Graph algorithms:
LightGraphs.jl
- Combinatorics:
Combinatorics.jl
- Graph algorithms:
- Engineering
- Signals:
DSP.jl
,FFTW.jl
- Image Processing:
Images.jl
- Signals:
- Numerical and Scientific Computing
- Sparse matrices:
SparseArrays
,SuiteSparse
- Differential equations:
DifferentialEquations.jl
- Polynomials:
Polynomials.jl
- Sparse matrices:
- Optimization and Operations Research
- Modeling:
JuMP.jl
for Linear Programs and Nonlinear Problems - Root finding:
Roots.jl
- Modeling:
- Statistics
- Multivariate:
MultivariateStats.jl
- Simple functions:
Statistics
- Multivariate:
And this also includes a variety of useful utility packages in the base Julia library and beyond to make working with files and output easy.
Random
DelimitedFiles
IterTools
Printf
SpecialFunctions
BenchmarkTools
JSON.jl
HDF5.jl
Plots.jl
CSV.jl
This takes a typical Julia install and provides all the functions needed for almost any undergraduate project.
- Morphing Carl Gustav Jacobi to David Young via an iterative method (from Numerical Methods by Greenbaum and Chartier)