Scalar Types

Spectral correlation analysis of time series (not supposed to be used)

Julia wrapper around the Mineos Earth normal mode package

Minc2 interface for Julia Language

Julia implementation of the Python package scikit-spatial.

Mikrubi: a model for species distributions using region-based records

Package holding options modeling and analysis codes

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A collection of microscopy tools

Piecewise polynomial interpolation in Julia

A Scryfall Julia wrapper for basic functionality of https://scryfall.com --- a MtG all-in-one look-up site.

Read and analyze EPOCH simulation data

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Orthogonal polynomials

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Searching configurations in abstract spaces using stochastic search methods

A web client for the Seasonal Streamflow Forecasting Service the Australian Bureau of Meteorology.

Dynamic graphs for simulating plant growth and development

MetaCommunityMetrics is a collection of tools and utilities for analyzing meta-communities in Julia. The current version is compatible with julia version 1.9.3.

Optical Spectroscopy Numerical Analysis and Processing Tools

Interface to PowerModels.jl using data in PowerSystems.jl format

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Advection implementation using Semi-Lagrangian numerical method

Memory-based collaborative filtering in Julia

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Subpackage of PowerDynamics.jl implementing the operation point search incl. interfaces to external power flow solvers

A single-file Julia libray using pack(1) alignment to pack value-typed instances into UInt8 arrays with extensible endianness.

A pure Julia package for querying and downloading Sentinel data.

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Installer for SpmImage Tycoon

PostgreSQL DBI driver

Julia arrays with elements saved to disk with serialization.

Politely ask other threads to do a little work, if they aren't too busy.

A web client for the 7-Day Streamflow Forecasting Service the Australian Bureau of Meteorology.

An implementation of Shamir's Secret Sharing protocol in Julia

Utilities for generating blocks for processing data, with optional padding

Connect the Julia REPL to a shared MATLAB session.

Formulate likelihood problems and solve them with maximum likelihood estimation (MLE)