https://github.com/cjen07/julia_port

example project to invoke julia functions in elixir to do scientific computing using port and metaprogramming
https://github.com/cjen07/julia_port

elixir erlang-port julia metaprogramming

Last synced: 10 days ago
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example project to invoke julia functions in elixir to do scientific computing using port and metaprogramming

• Host: GitHub
• URL: https://github.com/cjen07/julia_port
• Owner: cjen07
• License: mit
• Created: 2017-02-26T09:03:20.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2018-10-15T09:01:36.000Z (about 6 years ago)
• Last Synced: 2024-09-16T17:51:49.007Z (about 2 months ago)
• Topics: elixir, erlang-port, julia, metaprogramming
• Language: Elixir
• Homepage:
• Size: 559 KB
• Stars: 40
• Watchers: 1
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
## julia_port

example project to invoke julia functions in elixir to do scientific computing using port and metaprogramming

### news

* support julia v1.0.1

* support elixir v1.7.3

* support erlang 21.0

* the script_test is supported

* the real_test is removed because it does not support julia v1.0.1

### remarks

* the author will experiment with [tensorflow.jl](https://github.com/malmaud/TensorFlow.jl) for good reason

### prerequisite

* [julia](http://julialang.org/) installed and its access from shell

### Installation

the package can be installed

by adding `julia_port` to your list of dependencies in `mix.exs`:

```elixir

def deps do

  [{:julia_port, "~> 0.2.0"}]

end

```

remark: if you install the package as a dependency, in order to run `script_test`,

you have to move `./deps/julia_port/julia` and `./deps/julia_port/data` to `./julia` and `./data` respectively

### usage

* simple_test: arithmetics

```elixir

def simple_test(port) do

  port_send(port, "1+2")

  IO.puts port_receive(port, true)

end

```

* complex_test: linear algebra

```elixir

use GenFunction, [rand: 2, sum: 1, *: 2]

def complex_test(port) do

  rand(port, :a, 3, 3)

  rand(port, :b, 3, 3)

  JuliaPort.*(port, :c, :a, :b)

  port_receive(port, false)

  sum(port, :d, :c)

  IO.puts port_receive(port, true)

end

```

* script_test: linear regression

```elixir

use GenFunction, [load_data: 1, lr_train: 2, lr_test: 3]

def script_test(port) do

  include_script(port, "./julia/lr.jl")

  load_data(port, {:x_train, :y_train}, "./data/train")

  load_data(port, {:x_test, :y_test}, "./data/test")

  lr_train(port, :beta, :x_train, :y_train)

  port_receive(port, false)

  lr_test(port, :error, :x_test, :y_test, :beta)

  IO.puts port_receive(port, true)

end

```

* run

```elixir

iex -S mix

port = JuliaPort.init

# => #Port<0.5310>

JuliaPort.print_version port

# => received data: v"1.0.0"

JuliaPort.simple_test port

# => received data: 3

JuliaPort.complex_test port

# => received data: 5.710327361153192

JuliaPort.script_test port

# => received data: 0.9587912087912088

JuliaPort.terminate port

# => {#PID<0.143.0>, :close}

```