The Julia Language
Julia is a high-level dynamic programming language designed to address the needs of high-performance numerical analysis and computational science. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.
- Sign up for GitHub or sign in to edit this page
- Created by Jeff Bezanson, Stefan Karpinski, Viral B. Shah, Alan Edelman
- Released February 14, 2012
Here are 393 public repositories matching this topic...
The GR backend has implemented an :outer legend position, which is not reflected in the documentation.
Curated decibans of Julia programming language.
-
Updated
Nov 13, 2019 - Julia
A library for robust, efficient, general-purpose probabilistic programming
-
Updated
Nov 22, 2019 - Julia
Plots.jl shorthands
Plots.jl has a lot of small, easy-to-implement convenience functions and recipes that would be nice to have in AbstractPlotting, or StatsMakie.
-
stephist:
stephist(x)
stephist(x)
Make a histogram step plot (bin counts are represented using horizontal lines
instead of bars). See `histogram`. -
scatterhist:
scatterhist(x)
scattI was trying to use the Julia: Execute Code Cell Command, but I didn't know what was the delimiter for a cell. Finally, I found it, but It would be nice to have a comment about it :).
A benchmarking framework for the Julia language
-
Updated
Nov 19, 2019 - Julia
The error I get when I click on a URL in the documentation:
Couldn't resolve URL @ref
Configuring paths to API docs in project settings might help
External documentation for Array

I had my Clion shortcut in C:\JuliaPro-1.1.1.1 folder.

Closest candidates are:
add_node!(::Mesh, !Matched::Int64, ::Array{Float64,1}) at /home/jukka/repositories/JuliaFEM/src/preprocess.jl:64
I guess the automatic conversion should work, but nid is defined as Int64, maybe Integer would be better?
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
-
Updated
Nov 20, 2019 - Julia
"Deep Learning and Quantum Programming" Spring School @ Song Shan Lake
-
Updated
Nov 20, 2019 - Jupyter Notebook
COSMO: An ADMM-based solver for convex conic optimisation problems (LP, QP, SOCP, SDP, ExpCP, PowCP). Implemented in Julia
-
Updated
Nov 19, 2019 - Julia
Financial market technical analysis & indicators in Julia
-
Updated
Nov 4, 2019 - Julia
A JuMP-based Global Optimization Solver
-
Updated
Nov 19, 2019 - Julia
Julia syntax highlighting for Sublime Text 2/3
-
Updated
Nov 11, 2019 - Python
A JuMP-based Nonlinear Integer Program Solver
-
Updated
Nov 16, 2019 - Julia
In https://github.com/JuliaLang/julia/blob/606420a308d951ab810a05f6f6c50a1b805f2b47/base/reshapedarray.jl#L173-L177 it should be checked whether the requested array has offset axes.
Otherwise we can get segfaults. See #33603
In the 1D->1D case (
AbstractVector) there already is such a check:https://github.com/JuliaLang/julia/blob/606420a308d951ab810a05f6f6c50a1b805f2b47/base/reshapedarray.