1using CuArrays, FileIO, Colors, GPUArrays, BenchmarkTools 2using CuArrays: CuArray 3""" 4The function calculating the Julia set 5""" 6function juliaset(z0, maxiter) 7 c = ComplexF32(-0.5, 0.75) 8 z = z0 9for i in1:maxiter10 abs2(z) > 4f0 && return (i - 1...
imgb = imfilter(img, Kernel.gaussian(gaussian_smoothing));#convert images to Float to perform mathematical operationsimg_array = Float16.(channelview(img)); imgb_array = Float16.(channelview(imgb));#create a sharpened version of our image and fix values from 0 to 1sharpened = img_array ...
# => in expression starting at ...\LearnJulia.jl:211 catch e println(e) end # 报错时错误会指出出错的文件位置以及行号,标准库也一样 # 你可以在 Julia 安装目录下的 share/julia 文件夹里找到这些标准库 # 可以用 range 初始化数组 a = [1:5;] # => 5-element Array{Int64,1}: [1,2,3...
只需将数组转换为 GPUArrays(使用 gpu(array),就可以将整个计算移动到 GPU 并获得可观的速度提升。这要归功于 Julia 复杂的 AbstractArray 基础架构,使 GPUArray 可以无缝集成。随后,如果省略转换为 GPUArray 这一步,代码会按普通的 Julia 数组处理,但仍在 CPU 上运行。可以尝试将 use_gpu = true 改为 use_...
(float) dt: Time step size (float) t_max: Maximum time to solve the equation for (float) Returns: u: Solution to the advection equation (numpy array) """ # Compute the number of grid points and time steps nx = len(u0) nt = int(t_max / dt) # Create the solution array u = ...
1 cor(c_opt,array(df[:consump])) 0.9999999998435865 Thus, we consumption values produced by the numerically optimizer’s approximation to the demand for consumption are almost identical to those produced by the true demand for consumption. Putting it all together, we create a function that can ...
From Julia to Python Assuming you have NumPy installed (true by default if you use Conda), then a Juliaa::Arrayof NumPy-compatible elements is converted byPyObject(a)into a NumPy wrapper for thesame data, i.e. without copying the data. Julia arrays are stored incolumn-major order, and ...
Constructs which create uninitialized memory should only be used if there is a demonstrated performance impact and it should ensure that all memory is initialized in the same function in which the array is intended to be used.Example:function make_array(n::Int) A = Vector{Int}(undef, n) #...
false# => true1==1# => true2==1# => false1!=1# => false2!=1# => true1<10# => true1>10# => false2<=2# => true2>=2# => true# 链式比较1<2<3# => true2<3<2# => false# 字符串可以由「"」创建"This is a string."# 字符字面量可用「'」创建'a'# 字符串使用 ...
## Removing an entry permanently from a dictionary pop!(dictionary, 'J') dictionary Output: Dict{Char, Int64} with 2 entries: 'A' => 1 'B' => 2 Working with matrices A matrix is an array of numbers represented as a vector of vectors. Here’s how you can create a matrix. ...