Numerical Analysis Packages
-
Grid.jl46Interpolation and related operations on grids
-
RandomMatrices.jl76Random matrices package for Julia
-
LinearExpressions.jl6Linear symbolic expressions for the Julia language
-
Sobol.jl70Generation of Sobol low-discrepancy sequence (LDS) for the Julia language
-
InplaceOps.jl54Convenient macros for in-place matrix operations in Julia
-
LinearMaps.jl282A Julia package for defining and working with linear maps, also known as linear transformations or linear operators acting on vectors. The only requirement for a LinearMap is that it can act on a vector (by multiplication) efficiently.
-
ApproXD.jl28B-splines and linear approximators in multiple dimensions for Julia
-
Expokit.jl22Julia implementation of EXPOKIT routines
-
Interpolations.jl444Fast, continuous interpolation of discrete datasets in Julia
-
FastGaussQuadrature.jl262Julia package for Gaussian quadrature
-
KNITRO.jl61Julia interface to the Artelys Knitro solver
-
Dopri.jl4A Julia wrapper for the DOPRI5 and DOP853 integrators.
-
EiSCor.jl0Julia wrapper of the Fortran library for efficiently solving structured matrix eigenvalue problems using unitary core transformations
-
SolveDSGE.jl67A Julia package to solve, simulate, and analyze nonlinear DSGE models.
-
GridInterpolations.jl41Multidimensional grid interpolation in arbitrary dimensions
-
CompEcon.jl44Julia versions of the CompEcon routines by Miranda and Fackler.
-
LowRankApprox.jl88Fast low-rank matrix approximation in Julia
-
AMD.jl16Approximate Minimum Degree Ordering in Julia
-
FastTransforms.jl228:rocket: Julia package for orthogonal polynomial transforms :snowboarder:
-
Indicators.jl205Financial market technical analysis & indicators in Julia
-
IntervalConstraintProgramming.jl60Calculate rigorously the feasible region for a set of real-valued inequalities with Julia
-
SciMLSensitivity.jl248A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
-
SciMLExpectations.jl59Fast uncertainty quantification for scientific machine learning (SciML) and differential equations
-
QuadGK.jl210Adaptive 1d numerical Gauss–Kronrod integration in Julia
-
FiniteDiff.jl202Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support
-
StateSpaceRoutines.jl80Package implementing common state-space routines.
-
NumericalIntegration.jl55Basic numerical integration routines for presampled data.
-
RollingFunctions.jl90Roll a window over data; apply a function over the window.
-
FEniCS.jl84A scientific machine learning (SciML) wrapper for the FEniCS Finite Element library in the Julia programming language
-
IntervalRootFinding.jl116Find all roots of a function in a guaranteed way with Julia
-
HCubature.jl135Pure-Julia multidimensional h-adaptive integration
-
PartialLeastSquaresRegressor.jl34Implementation of a Partial Least Squares Regressor
-
LibCEED.jl148CEED Library: Code for Efficient Extensible Discretizations
-
PiecewiseInterpolation.jl1Interpolate data with known discontinuities
-
SummationByPartsOperators.jl46A Julia library of summation-by-parts (SBP) operators used in finite difference, Fourier pseudospectral, continuous Galerkin, and discontinuous Galerkin methods to get provably stable semidiscretizations, paying special attention to boundary conditions.
-
FDM.jl237High accuracy derivatives, estimated via numerical finite differences (formerly FDM.jl)
-
FiniteDifferences.jl237High accuracy derivatives, estimated via numerical finite differences (formerly FDM.jl)
-
Simplices.jl1Compute exact simplex intersections in N dimensions.
-
Preconditioners.jl44A few preconditioners for iterative solvers.
-
Arpack.jl60Julia Wrappers for the arpack-ng Fortran library
Loading more...