项目作者: AtsushiSakai

项目描述 :
Julia interface for SciPy
高级语言: Julia
项目地址: git://github.com/AtsushiSakai/SciPy.jl.git
创建时间: 2020-05-30T11:22:50Z
项目社区:https://github.com/AtsushiSakai/SciPy.jl

开源协议:MIT License

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SciPy.jl

Build Status
Stable
Dev
version
pkgeval
deps

drawing

SciPy.jl is a Julia interface for SciPy using PyCall.jl.

You can use many useful scientific functions of SciPy from Julia codes.

Requirements

Julia 1.6 or higher.

Install

  1. using Pkg; Pkg.add("SciPy")

and then just import it with using SciPy.

If you want to use latest development code:

  1. import Pkg; Pkg.add(Pkg.PackageSpec(name="SciPy", rev="master"))

What to do if installation failed?

Read an error message you get carefully. Since SciPy.jl depends on PyCall.jl to call Python functionalities from Julia, we also recommend to read Specifying the Python version
section of PyCall.jl
.

See also this instruction_1 and instruction_2 in this issue

Example

  1. using SciPy
  2. using PyPlot # Pkg.add("PyPlot")
  3. points1 = rand(15, 2)
  4. points2 = rand(15, 2)
  5. figure(figsize=(6, 6))
  6. plot(points1[:, 1], points1[:, 2], "xk", markersize=14)
  7. plot(points2[:, 1], points2[:, 2], "og", markersize=14)
  8. kd_tree1 = spatial.KDTree(points1)
  9. kd_tree2 = spatial.KDTree(points2)
  10. indexes = kd_tree1.query_ball_tree(kd_tree2, r=0.2)
  11. for i in 1:length(indexes)
  12. for j in indexes[i]
  13. plot([points1[i, 1], points2[j+1, 1]], [points1[i, 2], points2[j+1, 2]], "-r")
  14. end
  15. end

Documentation

You can check latest documentation here:

Maintainers