content stringlengths 6 1.03M | input_ids listlengths 4 535k | ratio_char_token float64 0.68 8.61 | token_count int64 4 535k |
|---|---|---|---|
<reponame>crstnbr/dqmc
using LightXML
"""
xml2parameters!(p::Params, input_xml)
Load `p` from XML file (e.g. `.in.xml`).
"""
function xml2parameters!(p, input_xml::AbstractString, verbose=true)
# READ INPUT XML
params = Dict{Any, Any}()
try
params = xml2dict(input_xml, verbose)
catch e
printl... | [
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... | 2.28536 | 806 |
<filename>deps/build.jl
import PyCall
# , Conda
# Conda.add("git")
# Conda.add("pip")
# Conda.add("cython")
# Conda.add("numpy")
# const pip = joinpath(Conda.BINDIR, "pip")
# proxy_arg = String[]
# if haskey(ENV, "http_proxy")
# push!(proxy_arg, "--proxy")
# push!(proxy_arg, ENV["http_proxy"])
# end
pip = ... | [
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<reponame>ModiaSim/ModiaResult
include("test_01_OneScalarSignal.jl")
include("test_02_OneScalarSignalWithUnit.jl")
include("test_03_OneVectorSignalWithUnit.jl")
include("test_04_ConstantSignalsWithUnit.jl")
include("test_05_ArraySignalsWithUnit.jl")
include("test_06_OneScalarMeasurementSignal.jl")
include("test_07_One... | [
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<gh_stars>1-10
#!/usr/bin/env julia
using GraphIdx.Io.Snap: open_snap, parse_snap_edges
using HDF5: h5open, attrs
fname = get(ARGS, 1, "com-youtube.txt.gz")
out = get(ARGS, 2, "out.h5")
output_bin = false
@time n, m, head, tail = open_snap(parse_snap_edges, fname)
isfile(out) && rm(out)
h5open(out, "w") do io
at... | [
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25... | 2.076 | 250 |
<reponame>ilkayn01/18.600-probability-RandomVariables
begin
using StatsBase
function coin_toss(n)
toss = []
head = 0
for i in 1:n
push!(toss, sample(["H", "T"], 1, replace = false))
end
for i in toss
if i == ["H"]
head += 1
end
end
return head/n
end
end
| [
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176... | 2.103704 | 135 |
module Lu_julia_dense
#
using Lu
#
ArgName = "julia_dense"
Descr = "Julia's default algorithm on a dense matrix."
#
type Dat{T}
prob::Lu.Problem{T}
A::Array{T,2}
#
Dat() = new()
end
#
function construct_dat(T::DataType)
return Dat{T}()
end
function fill_dat{T}(prob::Lu.Problem, dat::Dat{T})
dat.pro... | [
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... | 2.226576 | 587 |
let
n = 50
p = 3
t = (1:n)/n
Ut,Vt = egrss.generators(t,p);
Wt,c = egrss.potrf(Ut,Vt,1e-2*ones(n))
Yt,Zt = egrss.trtri(Ut,Wt,c)
Lref = cholesky(egrss.full(Ut,Vt) + Diagonal(1e-2*ones(n))).L
Lref_inv = LowerTriangular(tril(inv(Lref)));
L_inv = egrss.full_tril(Yt,Zt,1.0./c)
@test... | [
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... | 1.671875 | 256 |
"""
default_PARF(grid, ΔT, iterations)
Generate default hourly surface PAR.
"""
function default_PARF(grid, ΔT, iterations)
PAR = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.3871666666666666, 87.10258333333333, 475.78150000000016, 929.2737916666669,
1232.3633333333337, 1638.918916666667, 1823.7921666666664, 190... | [
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220,... | 1.992621 | 7,589 |
<filename>src/interpolation_utils.jl
function findRequiredIdxs(A::LagrangeInterpolation, t)
idxs = sortperm(A.t,by=x->abs(t-x))
idxs[1:(A.n+1)]
end
function spline_coefficients(n, d, k, u::Number)
N = zeros(n)
if u == k[1]
N[1] = one(u)
elseif u == k[end]
N[end] = one(u)
else
i = fi... | [
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<reponame>chkwon/TrafficAssignment.jl-<filename>src/frank_wolfe.jl
# Frank-Wolfe Methods
# CFW and BFW in Mitradijieva and Lindberg (2013)
# required packages: Graphs, Optim
include("misc.jl")
function BPR(x::Vector{Float64}, td::TA_Data)
bpr = similar(x)
for i in 1:length(bpr)
bpr[i] = td.free_flow_... | [
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<filename>src/distribution_functions.jl<gh_stars>0
using FFTW
using LinearAlgebra
using Statistics
export DistributionFunction
"""
DistributionFunction( grid1, grid2 )
"""
struct DistributionFunction
xgrid :: OneDGrid
vgrid :: OneDGrid
values :: Array{AbstractFloat, 2}
function DistributionFunc... | [
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... | 2.054054 | 666 |
module IEEE_754_2008
import Base: min, max, minmax, precision, ldexp, frexp
include("extensions.jl")
include("ulpufp.jl")
# include bypasses precompilation
# modulename = :QNaN; @eval begin import $modulename; using $modulename end
modulename = :QNaN; @eval importall $modulename
modulename = :SignificantBits; @eval ... | [
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... | 2.545455 | 330 |
using Documenter, TextStylometry
makedocs(
format = :html,
sitename = "Text Stylometry",
modules = [TextStylometry],
pages = [
"index.md",
"Corpus" => "corpus.md",
"Features" => "features.md",
"Measures" => "measures.md",
"Bootstrap measures" => "bootstrap.md",
... | [
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... | 2.164659 | 249 |
using Blue
using Test
| [
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198,
3500,
6208,
198
] | 3.285714 | 7 |
using ExpFamily
using Base.Test
@testset "gaussian" begin include("gaussian_test.jl") end
@testset "diaggaussian" begin include("diaggaussian_test.jl") end
@testset "gauss suffst" begin include("gaussian_suffstats_test.jl") end
@testset "gauss loglik" begin include("gaussian_loglik_test.jl") end... | [
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... | 2.609756 | 123 |
<gh_stars>0
# Basic Operators
# ---------------
"""
Count how many nucleotides satisfy a condition (i.e. f(seq[i]) -> true).
The first argument should be a function which accepts a nucleotide as its parameter.
"""
function Base.count(f::Function, seq::BioSequence)
n = 0
for x in seq
if f(x)
... | [
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... | 2.174939 | 4,916 |
module Node_Test
using Compat
using Compat.Test
using IntervalArithmetic
using EAGOBranchBound
B = BnBModel([Interval(1.0,2.0),Interval(3.0,4.0)])
A1,A2,A3,A4,A5 = EAGOBranchBound.NS_depth_breadth(B)
@test A1 == [Interval(1.0,2.0),Interval(3.0,4.0)]
@test A2 == -Inf
@test A3 == Inf
@test A4 == 1
@test A5 == 1
end
| [
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... | 2.078431 | 153 |
<reponame>0382/CGcoefficient.jl<filename>src/WignerSymbols.jl
# This file contains the core functions of WignerSymbols and CG-coefficient.
"""
HalfInt = Union{Integer, Rational}
Angular momentum quantum numbers may be half integers and integers. With `HalfInt` type, you can use both `2` and `3//2` as parameters.
... | [
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2992... | 1.963303 | 5,123 |
using DataStructures
using Test
# Setup for pycall tests - done by travis, uncomment for manual run
# using Conda; ENV["PYTHON"] = Conda.PYTHONDIR
# using Pkg
# Pkg.build("PyCall")
# Conda.add_channel("conda-forge")
# Conda.add("cfgrib")
using PyCall
@testset "era5-levels-members DataSet parity" begin
test_fi... | [
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972... | 1.817183 | 10,289 |
<filename>src/CauchyBorn_Si.jl<gh_stars>1-10
module CauchyBorn
using JuLIP
using JuLIP.Potentials: StillingerWeber
import JuLIPMaterials.CLE: elastic_moduli
export WcbQuad
# "a fully equilibrated SW potential"
# function sw_eq()
# T(σ, at) = trace(stress(StillingerWeber(σ=σ), at))
# at = JuLIP.ASE.bulk("... | [
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... | 1.683883 | 1,607 |
######################################################################
# trajectory_generation.jl
######################################################################
# helper files
include("gradients.jl")
include("scoring.jl")
include("projection.jl")
include("printing.jl")
# actual methods
include("pto.jl")
inclu... | [
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29... | 2.424427 | 655 |
struct Model{D}
dims::Dims{3}
h::NamedTuple{(:ZZ, :X, :Z), NTuple{3, Float64}}
J::NamedTuple{(:ZZ, :X, :Z), NTuple{3, Vector{Float64}}}
∂Jt::Vector{Float64}
end
Base.size(M) = M.dims
Base.length(M) = prod(M.dims)
function couplings(θ::Vector{Float64})#, hx::Float64, hz::Float64)# ::ImmutableDi... | [
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4843... | 1.769446 | 1,787 |
<reponame>simsurace/AugmentedGPLikelihoods.jl
module AugmentedGPLikelihoods
using Reexport
using ChainRulesCore: @ignore_derivatives
using Distributions
@reexport using GPLikelihoods
using GPLikelihoods: AbstractLikelihood, AbstractLink
using IrrationalConstants
using LogExpFunctions
using MeasureBase
using MeasureTh... | [
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62,... | 3.07243 | 428 |
# This is a simple script which implements the "graphics hello world" described in chapter 2
# constants
rows = 200;
cols = 100;
max_color = 255; # colors go from 0-255
fio = open("outputs\\helloWorld.ppm", "w");
# format meta information, P3 format name, second line tells rows by column
println(fio, "P3\n$rows $cols\... | [
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467,
... | 2.512821 | 234 |
"""
solve_newton is a symbolic Newton-Ralphson solver
f is a symbolic equation to be solved (f ~ 0)
x is the variable to solve
x₀ is the initial guess
"""
function solve_newton(f, x, x₀; abstol=1e-8, maxiter=50)
xₙ = Complex(x₀)
∂f = differentiate(f, x)
for i = 1:maxiter
xₙ₊₁ = xₙ -... | [
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... | 1.839785 | 930 |
#
# Task
# move linear at constant velocity along x axis, 10m/s, starting from 0
# Track the state separate like a filter by using underlying Factor Graph operations instead.
# the next example will keep the data in the same factor, and achieve objective more efficiently.
using IncrementalInference
# state
# Contin... | [
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82,
11,
3599,
422,
657,
198,
198,
2,
17762,
262,
1181,
4553,
588,
257,
8106,
416,
1262,
10238,
27929,
29681,
4560,
2427,
13,
198,
2,... | 2.6192 | 625 |
using CompScienceMeshes, BEAST
using LinearAlgebra
using Profile
using StaticArrays
ttrc = X->ttrace(X,y)
T= tetmeshsphere(1.0,0.2)
X = nedelecc3d(T)
y = boundary(T)
@show numfunctions(X)
ϵ, μ, ω = 1.0, 1.0, 1.0; κ, η = ω * √(ϵ*μ), √(μ/ϵ)
ϵ_r = 5.0
function tau(x::SVector{U,T}) where {U,T}
5.0 -1.0
end
χ = t... | [
3500,
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44,
274,
956,
11,
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198,
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44800,
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926,
16740,
7,
55,
11,
88,
8,
198,
198,
51,
28,
28408,
76,
... | 1.916193 | 704 |
"""
theoretical_memory_bandwidth(; device::CuDevice=CUDA.device(); verbose=true)
Estimates the theoretical maximal GPU memory bandwidth in GiB/s.
"""
function theoretical_memory_bandwidth(dev::CuDevice=CUDA.device(); verbose=true, io::IO=stdout)
max_mem_clock_rate =
CUDA.attribute(dev, CUDA.CU_DEVICE_AT... | [
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8,
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26748,
262,
16200,
40708,
11362,
4088,
19484,
287,
8118,
33,
14,
82,... | 2.265052 | 1,445 |
# Tests for Reverse DDF DEA Models
@testset "ReverseDDFDEAModel" begin
# ------------------
# Input oriented
# ------------------
X = [2 2; 1 4; 4 1; 4 3; 5 5; 6 1; 2 5; 1.6 8]
Y = [1; 1; 1; 1; 1; 1; 1; 1]
# Reverse DDF for input :ERG
russelio = dearussell(X, Y, orient = :Input, rts = :VRS... | [
2,
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... | 2.066995 | 3,045 |
<reponame>TheCedarPrince/JuliaTutor.jl
using JuliaTutor
using Documenter
@info "Makeing documentation..."
makedocs(;
modules=[JuliaTutor],
authors="caseykneale",
repo="https://github.com/Humans-of-Julia/JuliaTutor.jl/blob/{commit}{path}#L{line}",
sitename="JuliaTutor.jl",
format=Documenter.HTML(;
... | [
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2... | 2.247525 | 303 |
<filename>R/RDKit/build_tarballs.jl
using BinaryBuilder, Pkg
name = "RDKit"
version = v"2022.03.1"
sources = [
GitSource("https://github.com/rdkit/rdkit.git", "7e205e0d93a3046c1eaab37120c9f6971194ddf2"),
DirectorySource("./bundled"),
]
script = raw"""
cd ${WORKSPACE}/srcdir/rdkit
# Fix name of static librar... | [
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410,
1,
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13,
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16,
1,
198,
198,
82... | 2.283429 | 875 |
using Dates
using ArgParse
include("../btg.jl")
include("../datasets/load_abalone.jl")
s = ArgParseSettings()
@add_arg_table! s begin
"--fast"
help = "use fast or not"
action = :store_true
end
parsed_args = parse_args(ARGS, s)
ind = 1:50
posx = 1:7
posc = 1:3
x = data[ind, posx]
Fx = data[ind, ... | [
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3419... | 1.986264 | 1,820 |
function WSM(A,b,C,d,XLB,XUB,VariableDef,Lambda;MyModel = [],TimeLim = 999999)
if MyModel == []
MyModel = WSM(A,b,C,d,XLB,XUB,VariableDef)
end
X = getindex(MyModel,:X);
ObjNum = size(C)[1];
m,n = size(A);
@objective(MyModel, Min, sum(Lambda[i]*(sum(C[i,j]*X[j] for j = 1:n )+d[i]) for i ... | [
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... | 1.95171 | 497 |
<reponame>ericphanson/TensorCast.jl
using .NamedArrays
# import TensorCast: namedarray # because Revise doesn't track these
namedarray(A::AbstractArray, syms...) = namedarray(A, syms)
namedarray(A::AbstractArray, syms::Tuple) = namedarray(NamedArray(A), syms)
function namedarray(A::NamedArrays.NamedArray, syms::Tu... | [
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131... | 2.220884 | 249 |
<reponame>gronniger/RubiSymbolics.jl
@testset "5.3 Inverse tangent" begin
include("5.3.2 (d x)^m (a+b arctan(c x^n))^p.jl")
include("5.3.3 (d+e x)^m (a+b arctan(c x^n))^p.jl")
include("5.3.4 u (a+b arctan(c x))^p.jl")
include("5.3.5 u (a+b arctan(c+d x))^p.jl")
include("5.3.6 Exponentials of inverse... | [
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... | 1.901961 | 204 |
<filename>src/web/model_DefsCommentId.jl
# This file was generated by the Julia Swagger Code Generator
# Do not modify this file directly. Modify the swagger specification instead.
if !isdefined(@__MODULE__, :DefsCommentId)
const DefsCommentId = String
else
@warn("Skipping redefinition of DefsCommentId to Stri... | [
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407,
13096,
428,
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13,
3401,
1958,
262,
1509,
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20... | 3.3 | 100 |
"""
Treat WAV files as lazy arrays stored on disk.
Documentation: https://github.com/baggepinnen/LazyWAVFiles.jl
## Quick start
### LazyWAVFile
```
f1 = LazyWAVFile(joinpath(d,"f1.wav"))
f1[1]
f1[1:5]
size(f1)
f1.fs # Get the sample rate
[f1; f2] # Creates a `DistributedWAVFile`
```
### DistributedWAVFile
```
df = ... | [
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2235,
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... | 2.300578 | 2,595 |
<reponame>Keno/AC274.jl
# This file is ugly. Don't look at it. Should be replaced by fixed-size arrays/tuples
using Polynomials
import Base: getindex, start, done, next, length, size, eltype,
promote_rule, zero, one, zeros, ones, conj, copy
using ImmutableArrays
using Meshes
import Meshes: Vertex2
# C... | [
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8231,
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... | 1.808736 | 1,511 |
<reponame>NYUEcon/GrowthModels
module X
using CompEcon
immutable Agent
ρ::Float64
α::Float64
β::Float64
end
_unpack(a::Agent) = (a.ρ, a.α, a.β)
immutable Exog
A::Float64
B::Float64
τ::Float64
φᵥ::Float64
vbar::Float64
p::Matrix{Float64}
Π::Vector{Float64}
xp::Matrix{Float... | [
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... | 1.812524 | 2,587 |
# Common utilities
##### common types
"""
Base type for the output of clustering algorithm.
"""
abstract type ClusteringResult end
# generic functions
"""
nclusters(R::ClusteringResult)
Get the number of clusters.
"""
nclusters(R::ClusteringResult) = length(R.counts)
"""
counts(R::ClusteringResult)
Get t... | [
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... | 2.642384 | 453 |
export init_random_pars!
"""
build_rng_generator_T(T::abstractArray, seed)
builds an RNG generator for the type of T.
Defaults to MersenneTWister.
"""
function build_rng_generator_T(arrT::Array, seed)
return MersenneTwister(seed)
end
"""
init_random_pars!([rng=GLOBAL_RNG], net; sigma=0.01 )
Initiali... | [
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371,
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329,
262,
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286... | 2.37971 | 345 |
using Test
using ImageCore
using IterTools
using ReferenceTests
using ImageDistances
# general distances should cover any combination of number_types and color_types unless it's special designed
include("testutils.jl")
include("hausdorff.jl")
include("metrics.jl")
include("ciede2000.jl")
nothing
| [
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290,
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62,
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4556,
340,
338,
2041,
3... | 3.670732 | 82 |
<reponame>mattBrzezinski/MassInstallAction.jl
"""
MassInstallAction
Install or update GitHub Action workflows on repositories
API (all require qualification with `MassInstallAction`):
- Workflow creation: `Workflow`, `compat_helper`, `tag_bot`
- Workflow installation: `install`
"""
module MassInstallAction
incl... | [
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17614,
357,
439,
2... | 3.223022 | 139 |
using Flux
using Zygote
using CUDA
abstract type NNStructure end
"""
(nn::NNStructure)(x::AbstractArray{Float32,3})
Make NNStructure able to work with batches.
"""
(nn::NNStructure)(ts::AbstractTrajectoryState) = throw(ErrorException("missing function (::$(typeof(nn)))(::$(typeof(ts)))."))
function (nn::NNStruct... | [
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90,
43... | 2.637931 | 406 |
<reponame>banyan-team/banyan-julia<filename>Banyan/src/tasks.jl
#########
# Tasks #
#########
mutable struct DelayedTask
# Fields for use in processed task ready to be recorded
used_modules::Vector
code::String
value_names::Vector{Tuple{ValueId,String}}
effects::Dict{ValueId,String}
pa_union::V... | [
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198,
76,
18187,
28... | 2.667598 | 358 |
using CMAEvolutionStrategy
if isinstalled("scipy.optimize")
include("scipy_optimize.jl")
using .SciPyOptimize
end
function local_search!(
objective::Function,
ip::Vector{Int64},
population::Matrix{Float64},
n_population::Int64,
n_gene::Int64;
method::String,
... | [
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220,
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764,
50,
97... | 1.95288 | 1,528 |
<gh_stars>0
using FreeType
using Base.Test
library = Array(FT_Library, 1)
error = FT_Init_FreeType(library)
@test error == 0
| [
27,
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62,
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29,
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7,
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8,
198,
31,
9288,
4049,
6624... | 2.73913 | 46 |
#---------------------------------------------------------------------#
#This routine advances the solution in time using
#a simple General Order RK method.
#Written by <NAME> / <NAME> on 9/21/19
# Department of Applied Mathematics
# Naval Postgraduate School
# Monterey, CA 93943-5216
#---... | [
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2,
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22... | 2.27762 | 353 |
<filename>src/constants.jl
# Air Constants
const GAMMA_AIR = 1.4 # Adiabatic index or ratio of specific heats (dry air at 20º C)
const R_AIR = 287.05287 # Specific gas constant for dry air (J/(Kg·K))
# Air at sea level conditions h=0 (m)
const RHO0 = 1.225 # Density at sea level (kg/m3)
const P0 = 101325.0 # Press... | [
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3... | 2.256517 | 1,688 |
module Proc
export cubeAnomalies, removeMSC, gapFillMSC, normalizeTS, simpleAnomalies,
sampleLandPoints, getMSC, filterTSFFT, getNpY, getMedSC, DATfitOnline,
spatialinterp, extractLonLats, cubePCA, rotation_matrix, transformPCA, explained_variance,exportcube
using ..DAT, ..Cubes
import Dates.year
"""
getNpY(cu... | [
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198,
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23441,
2025,
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444,
11,
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34,
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51,
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6... | 2.591398 | 372 |
<filename>test/joint_limits.jl
using LCPSim
using Base.Test
using RigidBodyDynamics
using RigidBodyDynamics: Bounds
using StaticArrays: SVector
using Gurobi
@testset "joint limits" begin
@testset "1D mechanism" begin
world = RigidBody{Float64}("world")
mech = Mechanism(world; gravity=SVector(0, 0, ... | [
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25,
347,
3733,
198,
3500,
36... | 1.957223 | 1,426 |
<filename>src/backwardsfiltering.jl<gh_stars>1-10
"""
GuidRecursions{TL,TM⁺,TM, Tμ, TH, TLt0, TMt⁺0, Tμt0}
GuidRecursions defines a struct that contains all info required for computing the guiding term and
likelihood (including ptilde term) for a single shape
## Arguments
Suppose t is the specified (fixed) time g... | [
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11,
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11,
24811... | 1.947795 | 2,835 |
<filename>src/Interface.jl
module Interface
include("SpectralSolver.jl")
include("NewtonSolver.jl")
include("SchwarszchildModes.jl")
using .NewtonSolver
using .Schwarzschild
using .SpectralSolver
#P = ModeParameters((l=2,s=2,m=0,n=0,a=0.01,ω = 0.373672 - 0.0889623*im,Alm = 0, Nmax = 300, lmax = 10))
function GetMod... | [
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4... | 1.815279 | 877 |
<filename>src/tools/grid3D.jl
"""
```
grid3D(solute,solute_atoms,mddf_result,output_file; dmin=1.5, ddax=5.0, step=0.5)
```
This function builds the grid of the 3D density function and fills an array of
mutable structures of type Atom, containing the position of the atoms of
grid, the closest atom to that position, ... | [
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28,
... | 2.313384 | 1,838 |
<gh_stars>0
using GitWorkers
## ---------------------------------------------------------------
# cmd for run the server
# julia 'SERVER_SCRIPT_PATH'
## ---------------------------------------------------------------
# run to reset all
# gw_create_devland(;
# sys_root = "SYSTEM_ROOT",
# clear_repos = true,
#... | [
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62,
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1783,
243... | 3.406593 | 182 |
using Images, JLD
function main()
w = 2000
h = 2000
points = load("./sets/15k.jld", "points")
img = zeros(RGB,w,h)
for c::ComplexF64 in points
i::Int = 0
z::ComplexF64 = c
while abs(z) < 3 && i < 5000
x::Int = trunc(Int,(real(z) + 2)*w/3); y::Int = tr... | [
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... | 1.757485 | 334 |
<reponame>hmorlon/JPANDA<filename>src/clads/clads_output.jl
"""
A structure containig the informations about the resulot of a ClaDS run. Contains the following fields :
- `tree::Tree`: the phylogeny on which the analysis was performed.
- `chains::Array{Array{Array{Float64,1},1},1}` : the mcmc chains
- `rtt_chains::Arr... | [
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377,
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286,
257,
271... | 2.362809 | 1,538 |
<reponame>brendanjohnharris/NonstationaryProcesses.jl<gh_stars>0
using NonstationaryProcesses
using Plots
lorenz = lorenzSim(
X0 = [0.0, -0.01, 9.0],
parameter_profile = (constantParameter, constantParameter, constantParameter),
parameter_profile_parameters = (10.0, 28.0, 8/3), # Sprott's recomendation
... | [
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... | 2.119777 | 359 |
@testset "Storage data misspecification" begin
# See https://discourse.julialang.org/t/how-to-use-test-warn/15557/5 about testing for warning throwing
warn_message = "The data doesn't include devices of type GenericBattery, consider changing the device models"
model = DeviceModel(GenericBattery, BookKeeping... | [
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14,
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41948,
14... | 2.609869 | 1,297 |
<reponame>byuflowlab/Composites.jl<gh_stars>0
import Composites
# Step 1: Identify Material Properties
e1 = [181e9,203e9,38.6e9,76e9]
e2 = [10.3e9,11.2e9,8.27e9,5.5e9]
g12 = [7.17e9,8.4e9,4.14e9,2.3e9]
nu12 = [0.28,0.32,0.26,0.34]
rho = zeros(Float64,4)
xt = [1500.0,3500.0,1062.0,1400.0]*1e6
xc = [1500.0,1540.0,610.0,... | [
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24,
... | 2.204873 | 903 |
maxiter = 1000
using Stopping
stp = NLPStopping(nlp, NLPAtX(nlp.meta.x0) )
Lp = Inf
my_unconstrained_check(nlp, st; kwargs...) = unconstrained_check(nlp, st, pnorm = Lp; kwargs...)
stp.meta.optimality_check = my_unconstrained_check
#stp.meta.optimality_check = unconstrained_check
stp.meta.max_iter = maxiter
stp.m... | [
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8,
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43,
79,
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198,
19... | 2.169394 | 3,666 |
"""
add_input(state, agent_idx, post_list, config)
Create new directed edges from other agents.
# Arguments
- `state`: A tuple of the current graph and agent_list
- `agent_idx`: Agent index
- `post_list`: List of all published posts in network
- `config`: `Config` object as provided by `Config`
See also: [`Config... | [
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63,
25,
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286... | 2.042076 | 1,426 |
<filename>test/gherkin/scenario_test.jl
# Copyright 2018 <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | [
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... | 2.056195 | 7,901 |
<gh_stars>0
function mandel( c )
z = c
itrMax = 80
for n in 1:itrMax
if abs(z) > 2
return n-1
end
z = z^2 + c
end
return itrMax
end
| [
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... | 1.681416 | 113 |
<reponame>UltraHeckerNick/MechanicalPrograms_small
using LinearAlgebra
#Givens from Problem Statement
#Elastic Modulus(psi),Area(in^2),length(in),Force(lb)
E = 1.9*10^6
A = 8
l = 3*12
l2 = 3*sqrt(2)*12
F = 500
# Torsional Stiffness Function
k(A,E,l) = (A*E)/l
# k_local(Elastic Modulus,Area,length,theta,... | [
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7,
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72,
828,... | 1.755258 | 1,046 |
<gh_stars>0
module NetSci01
using LightGraphs, GraphPlot
using Distributions
export readnetwork, samplenetwork
const line_regex = r"^(\d+)\s(\d+)"
"Read a space separated file into an (undirected) Graph in an efficient way."
function readnetwork(filename::String, limit::Number = Inf; fromzero::Bool = false)
gra... | [
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489,
268,
316,
1818,
198,
198,
9979,
1627,
62,
260,
25636,... | 2.066556 | 2,404 |
using Nemo, GibbsTypePriors, JLD
grid_k = [collect(1:25:10000); 10000]
Vnk_numerical_accuracy = GibbsTypePriors.Vnk_NGG.(10000, grid_k, 1.2, 0.6) |> x -> accuracy_bits.(x)
save("test/graphical_tests/saves_for_graphical_tests/accuracy_Vnk_10000.jld", "Vnk_numerical_accuracy", Vnk_numerical_accuracy)
| [
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62,
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605,
62,
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6030,
47,
8... | 2.270677 | 133 |
using Harmonie_namelists
using Test
# These are very basic test. Once we have JSONSchema files for namelists
# we could validate the namelists much better
# Check that the mechanism where we take variables from the ENVironment works
@testset "ENV" begin
dicts = read_namelist.(["global", "canari"])
totdict... | [
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262,
299,
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1023,
881,
136... | 2.612094 | 678 |
<filename>src/InvariantMeasures/InvariantDistributions/plot_recipes.jl
using RecipesBase
@recipe f(::Type{InvariantDistribution}, ivd::InvariantDistribution) = ivd.dist
| [
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31,
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431,
277,
7,
3712,
6030,
90,
19904,
2743,
415,
20344... | 2.881356 | 59 |
using CounterTools
using Test
# Function for compiling read/write tests
function compile_test_program(kernel; ntimes = 10, array_size = 100000000)
commands = [
"g++",
"-march=native",
"-mtune=native",
"-mcmodel=large",
"-DSTREAM_ARRAY_SIZE=$array_size",
"-DFUNCTION=$... | [
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220,
9729... | 2.288557 | 402 |
# Starting example file for working with chars and strings in Julia
# Julia has a specific character type
myChar = 'x' # use single quotation mark for character
println(Int(myChar))
println(Char(120))
# Strings are defined using double quotes or triple quotes
myStr = "This is a sample string in Julia"
myOtherStr = ""... | [
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7,
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7,
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40... | 3.218659 | 343 |
<reponame>JuliaApproximation/HierarchicalSingularIntegralEquations.jl
##
# Represent a binary hierarchical Domain, Space, and Fun
##
mutable struct HierarchicalDomain{S,T,HS} <: ApproxFun.UnivariateDomain{T}
data::HS
HierarchicalDomain{S,T,HS}(data::HS) where {S,T,HS} = new{S,T,HS}(data)
end
mutable struct ... | [
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29,
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11,
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11,
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198,
2235,
198,
198,
7... | 1.824781 | 4,794 |
using Alexya
@init "Drawing" 1200 800
@layout aside(:v, 220)
mutable struct Sketch
points::Vector{Point}
color::Color
stroke::Real
fill::Bool
end
trash = Sketch[]
sketchs = Sketch[]
clear() = empty!(sketchs)
# ------------- ------------- Controls ------------- -------------
# Background color
bg =... | [
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198,
198,
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278,
1,
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7,
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90,
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92,
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220,
220,
220,
3124,
3... | 2.213693 | 964 |
# tests for the environment type and related functions.
# using Base.Test
# using PyPlot
# push!(LOAD_PATH, ".")
# include("includes.jl")
function get_test_uavs()
actions = [-1., 1., 0.]
joint_actions = ones(3, 3)
joint_actions[:, 1] = -1
r = collect(1:10)
q_table = zeros(10^7, size(joint_action... | [
2,
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2099,
290,
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... | 2.212505 | 2,607 |
<reponame>Ashymad/praca.inz<filename>tests/julia/tests/four1/test.jl
# four1 test
Fs = 1000; # Sampling frequency
T = 1/Fs; # Sampling period
function prepare_input(input_size)
t = (0:input_size-1)*T; # Time vector
S = zeros(2^ceil(log2(input_size)))
S[1:inp... | [
27,
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29,
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16,
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198,
198,
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796,
8576,
26,
220,
220,
220,
2... | 1.904437 | 586 |
export ScaledBeta, TrGeometric, TrBinomial, StringCategorical, likelihood, log_likelihood
export normalising_const
## Scaled beta distribution
"""
Scaled Beta distribution. Instantiate with ScaledBeta() e.g.
```
d = ScaledBeta(α, β, 0.0, 10.0)
```
would make a ScaledBeta type d which is bounded by 0.0 and 10.0. Note
- ... | [
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62,
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198,
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1446,
3021,
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6082,
198,
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198,
3351,
3... | 2.360848 | 1,793 |
function train_surrogate_model(sModelsProblem::SModelsProblem; verbose::Bool=false, saveToDisk::Bool=false, robust::Bool=true)
starting_date = date_now()
#initialization:
#--------------
# regression model to predict the continuous output:
clfr = MLPRegressor(solver="lbfgs", alpha=1e-5, hidden_layer_sizes =... | [
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15942,
577,
3712,
33,
970,
28,
9562,
11,
3613,
2514,
40961,
3712,
33,
970,
28,
9562,
11,
12373,
3712,
33,
970,
28,
7942,
8,
62... | 2.722296 | 6,010 |
struct WendlandC4{T} <: SPHKernel
n_neighbours::Int64
norm_1D::T
norm_2D::T
norm_3D::T
end
"""
WendlandC4(T::DataType=Float64, n_neighbours::Integer=216)
Set up a `WendlandC4` kernel for a given DataType `T`.
"""
WendlandC4(T::DataType=Float64, n_neighbours::Integer=216) = WendlandC4{T}(n_neighbou... | [
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51,
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220,
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... | 2.028965 | 2,106 |
<filename>test/template.jl
@info "Test template pattern..."
println("Brew coffee process")
coffee = Coffee("", "")
prepare(coffee)
println()
println("Brew tea process")
tea = Tea("", "")
prepare(tea)
| [
27,
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29,
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7,
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8,
198,
198,... | 2.942029 | 69 |
"""
Function to obtain the output current time series of a Dynamic Inverter model out of the DAE Solution. It receives the simulation inputs,
the dynamic device and bus voltage. It is dispatched for device type to compute the specific current.
"""
function compute_output_current(
sim::Simulation,
dynamic_devic... | [
37811,
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290,
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13,
632,
318,
26562,
329... | 2.57451 | 510 |
<reponame>UnofficialJuliaMirrorSnapshots/REDCap.jl-ba918724-fbf9-5e4a-a61c-87e95654e718
"""
REDCap.Config(url::String, key::String; ssl::Bool = true)
Struct to hold api url and key/superkey.
`APIConfigObj = Config("http...","ABCD...")`
This will be passed to all function calls to both orient and authorize the api_pu... | [
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29,
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19,
64,
12,
64,
5333,
66,
12,
5774,
68,
3865,
39111,
68,
45720,
198... | 3.061508 | 504 |
<reponame>rdeits/LoewnerJohnEllipsoids.jl
__precompile__()
module LoewnerJohnEllipsoids
using Convex
export inner_ellipsoid,
outer_ellipsoid,
box,
barrier_value
type LinearConstraint{T<:Real}
# Represents the constraint a * x <= b
a::Vector{T}
b::T
end
type Ellipsoid{T}
# Represents an ellipsoid as t... | [
27,
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261,
480,
29,
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6706,
413,
1008,
7554,
30639,
541,
568,
2340,
198,
198,
3500,
1482,
303,
87,
198,... | 2.356842 | 950 |
module TestGradient
using Test
using LinearAlgebra
using BlockFactorizations
using CovarianceFunctions
using CovarianceFunctions: EQ, RQ, Dot, ExponentialDot, NN, Matern, MaternP,
Lengthscale, input_trait, GradientKernel, ValueGradientKernel, GradientKernelElement,
DerivativeKernel, ValueDerivativeKern... | [
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39751,
2743,
590,
24629,
2733,
25,
36529,
11,
371,
48,
11,
22875,
11,
5518... | 1.987597 | 2,822 |
using Base.Meta
using JuMP: _valid_model, _error_if_cannot_register, object_dictionary, variable_type
using JuMP.Containers
# Parse raw input to define the upper bound for an interval set
function _parse_one_operator_parameter(
_error::Function, infoexpr::_ParameterInfoExpr, ::Union{Val{:<=}, Val{:≤}},
upper)
... | [
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12102,
62,
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62,
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62,
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62,
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62,
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198,
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12585,
7378,
13,
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50221,
198,
198,
2,
2547,
... | 2.425947 | 31,903 |
<reponame>BradLyman/AWS.jl<filename>src/services/polly.jl
# This file is auto-generated by AWSMetadata.jl
using AWS
using AWS.AWSServices: polly
using AWS.Compat
using AWS.UUIDs
"""
DeleteLexicon()
Deletes the specified pronunciation lexicon stored in an AWS Region. A lexicon which has been deleted is not availab... | [
27,
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261,
480,
29,
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12,
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416,
30865,
9171,
14706,
13,
20362,
198,
3500,
30865,
198,
3500,... | 3.609436 | 3,815 |
<gh_stars>10-100
using Yao
using QuAlgorithmZoo
using YaoBlocks.ConstGate
using Test
using LinearAlgebra
@testset "hadamard test" begin
n = 2
U = chain(put(n, 2=>Rx(0.2)), put(n, 1=>Rz(1.2)), put(n, 1=>phase(0.4)))
US = chain(2n, put(2n, (3,4)=>U),
chain(2n, [swap(2n,i,i+n) for i=1:n]))
reg... | [
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198,
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31,
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2617,
366,
18108,
321,
446... | 1.834395 | 314 |
<reponame>akazachk/UnitCommitment2.jl<filename>test/instance_test.jl<gh_stars>0
# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitComm... | [
27,
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480,
29,
461,
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6935,
270,
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29,
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198,
2,
11801,
6935,
270,
434,
13,
20362,
25,
30011,
1634,
15... | 1.894844 | 3,452 |
# ---
# title: 994. Rotting Oranges
# id: problem994
# author: Indigo
# date: 2021-02-18
# difficulty: Medium
# categories: Breadth-first Search
# link: <https://leetcode.com/problems/rotting-oranges/description/>
# hidden: true
# ---
#
# In a given grid, each cell can have one of three values:
#
# * the value `0` ... | [
2,
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2,
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25,
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198,
2,
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25,
28731,
400,
12,
... | 2.044232 | 1,153 |
import .CUDA
function Base.cconvert(::Type{MPIPtr}, buf::CUDA.CuArray{T}) where T
Base.cconvert(CUDA.CuPtr{T}, buf) # returns DeviceBuffer
end
function Base.unsafe_convert(::Type{MPIPtr}, X::CUDA.CuArray{T}) where T
reinterpret(MPIPtr, Base.unsafe_convert(CUDA.CuPtr{T}, X))
end
# only need to define this for... | [
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51,
30072,
810,
309,
198,
220,
220,
220,
7308,
13,
535,
261,
1851,
7,
4363... | 2.394984 | 319 |
include("area.jl")
include("vectorin.jl")
include("volume.jl")
function Assemblein(IK,JK,VK,con,Node, Ele, Cen, Face_in, EE, NU, FF)
@inbounds @sync @distributed for i = 1:size(Face_in,1)
v1 = Volume(Node[Face_in[i,1],1],Node[Face_in[i,1],2],Node[Face_in[i,1],3],
Node[Face_in[i,2],1],N... | [
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11,
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11,
19667,
11,
15987,
11,
327,
... | 1.386845 | 3,968 |
<gh_stars>0
module MinimalPerfectHash
export CHD
include("chd.jl")
include("chdhasher.jl")
include("chdconstructor.jl")
#include("chd_new.jl")
end # module
| [
27,
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4943,
198,
17256,
7203,
354,
67,
41571,
273,
... | 2.548387 | 62 |
using AcronymGenerator
using Test
@testset "AcronymGenerator.jl" begin
# Write your tests here.
end
| [
3500,
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4948,
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220,
220,
220,
1303,
19430,
534,
5254,
994,
13,
198,
437,
198
] | 2.837838 | 37 |
<reponame>sdangelis/GenomePermutations.jl
"""
anyoverlapping(a::GenomicFeatures.Interval{T},
b::GenomicFeatures.IntervalCollection{S})
Extend GenomicFeatures.isoverlapping to linearly check if interval a.
overlaps collection. Return true or false
```jldoctest
using GenomicFeatures
a = GenomicFeatures.Interval("chr... | [
27,
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261,
480,
29,
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8368,
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462,
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90,
51,
5512,
198,
197,
65,
3712,
13746,
10179,
235... | 2.746891 | 1,608 |
<gh_stars>0
### A Pluto.jl notebook ###
# v0.19.0
using Markdown
using InteractiveUtils
# This Pluto notebook uses @bind for interactivity. When running this notebook outside of Pluto, the following 'mock version' of @bind gives bound variables a default value (instead of an error).
macro bind(def, element)
quote... | [
27,
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4487,
198,
198,
2,
770,
32217,
20922,
3544,
2488,
21653,
329,
9427,... | 1.717629 | 2,564 |
# Examples presented in class - Lecture 1
# LP Resource allocation
using JuMP, Cbc
# JuMP is for implementing math. programming models;
# Cbc is for solving them.
# Example 1 - resource allocation
# Problem data
i = 1:2 # i=1: Seattle; i=2: San Diego
j = 1:3 # j=1: New York; j=2: Chicago; j=3: Miami
C = [350 600] #... | [
2,
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4981,
26,
198,
2,
327,
15630,
318,
329,
18120,
606,
13... | 2.700508 | 394 |
@testset "Periodic Kernel" begin
x = rand()*2; v1 = rand(3); v2 = rand(3);
r = rand(3)
k = PeriodicKernel(r = r)
@test kappa(k, x) ≈ exp(-0.5x)
@test k(v1, v2) ≈ exp(-0.5 * sum(abs2, sinpi.(v1 - v2) ./ r))
@test k(v1, v2) == k(v2, v1)
@test PeriodicKernel(3)(v1, v2) == PeriodicKernel(r = one... | [
31,
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198,
220,
220,
220,
374,
796,
43720,
7,
18,
8,
19... | 2.130742 | 283 |
include("maximin.jl")
include("cc_maximin.jl")
include("minimax.jl")
include("custom.jl")
include("no_obj.jl")
| [
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13,
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4943,
198,
17256,
7203,
3919,
62,
26801,
... | 2.466667 | 45 |
struct NotOffloadableError
ir
sv
reason
end
function Base.showerror(io::IO, e::NotOffloadableError)
println(io, "The specified function is not offloadable. The offending IR was:")
Base.IRShow.show_ir(io, e.ir; verbose_linetable=false)
if isa(e.reason, String)
println(io, e.reason)
e... | [
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220,
220,
220,
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220,
220,
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198,
220,
220,
220,
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198,
437,
198,
198,
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789,
1472,
7,
952,
3712,
9399,
11,
304,
3712,
3673,
9362,
2220,
540,
12331,... | 2.101914 | 2,247 |
using AdventOfCodeSolutions
using Test
function input(puzzle::Puzzle{2020, 6, n}) where n
io = openInput(puzzle)
return read(io, String)
end
function parseInput(input)
groups = split(input, "\n\n")
return map(group -> split(group, '\n', keepempty = false), groups)
end
function solve(::Puzzle{2020, 6,... | [
3500,
33732,
5189,
10669,
50,
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198,
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6208,
198,
198,
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79,
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3712,
47,
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90,
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11,
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299,
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220,
220,
220,
33245,
796,
1280,
20560,
7,
79,
9625,
8,
198,
220,
220,
220... | 2.419142 | 303 |
<gh_stars>1-10
# [[file:~/GitHub/J4Org.jl/docs/main.org::*A%20documented%20Julia%20=Foo=%20module][A documented Julia =Foo= module:1]]
module Foo
export Point, norm, foo
import Base: norm
#+Point L:Point_struct
# This is my Point structure
#
# *Example:*
#
# Creates a point $p$ of coordinates $(x=1,y=2)$.
#
# #+... | [
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544,
4,
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28,
37,
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28,
... | 2.294355 | 496 |
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