content stringlengths 6 1.03M | input_ids listlengths 4 535k | ratio_char_token float64 0.68 8.61 | token_count int64 4 535k |
|---|---|---|---|
<reponame>lucifer1004/Pluto.jl
### A Pluto.jl notebook ###
# v0.16.4
using Markdown
using InteractiveUtils
# ╔═╡ f7dfc33e-6ff8-44d6-a88e-bea5834a9d27
import A1
using A2
# ╔═╡ 360ee541-cbc4-4df6-bdc5-ea23fe08abdd
import A1, B1, .C1, D1.E1
using A2, B2, .C2, D2.E2
# ╔═╡ 8a4eff2d-5dbc-4056-a81b-da0618503467
import A1:... | [
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... | 1.449944 | 889 |
<reponame>memetics19/My_julia_practice-<gh_stars>1-10
#=
Author:= <NAME>
License:= MIT
UTF-8 =#
#=
In Julia the for loop is simple, Unlike python, matlab it won't use vectorized code.
`for.....end`
=#
println("***********************1st Example*************************")
for num = 1:10 # here the colon is u... | [
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796... | 2.868952 | 496 |
<reponame>joehuchette/Justitia.jl<gh_stars>1-10
"""
Subtypes are different approaches for solving an optimization problem. We use
"approach" to mean a configured algorithm: that is, the algorithm (e.g.
simplex), along with fixed values for all the algorithm hyperparemeters.
"""
abstract type AbstractApproach end
"""
S... | [
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620... | 3.924658 | 876 |
<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 UnitCommitment, Test, LinearAlgebra
@testset "Sensitivity" begin
@tests... | [
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2... | 1.627155 | 3,712 |
# Winston:
using Winston
# optionally call figure prior to plotting to set the size
figure(width=600, height=400)
# plot some data
pl = plot(cumsum(rand(500) - 0.5), "r", cumsum(rand(500) - 0.5), "b")
# display the plot (not done automatically!)
display(pl)
println("Press enter to continue: ")
readline(STDIN)
# save th... | [
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7,
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7,... | 3.016807 | 119 |
<filename>src/julia/Audio/music.jl
type Music
ptr::Ptr{Void}
function Music(ptr::Ptr{Void})
m = new(ptr)
finalizer(m, destroy)
m
end
end
function Music(filename::AbstractString)
Music(ccall((:sfMusic_createFromFile, libcsfml_audio), Ptr{Void}, (Ptr{Cchar},), filename))
end
fun... | [
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220,
... | 2.544471 | 832 |
<reponame>Joel-Dahne/ArbExtras.jl<gh_stars>1-10
"""
bounded_by(f, a::Arf, b::Arf, C::Arf; degree, abs_value, log_bisection, depth_start, maxevals, depth, threaded, verbose)
Return `true` if the function `f` can be shown to be bounded by `C` on
the interval `[a, b]`, i.e. `f(x) <= C` for all `x ∈ [a, b]`,
otherwise... | [
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11,
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3712,
31... | 2.514779 | 2,199 |
<gh_stars>10-100
using Revise
using POMDPModelChecking
using POMDPs
using POMDPModels
using POMDPSimulators
using BeliefUpdaters
using QMDP
using SARSOP
using POMCPOW
pomdp = TigerPOMDP()
function POMDPModelChecking.labels(pomdp::TigerPOMDP, s::Bool, a::Int64)
if (a == 1 && s) || (a == 2 && !s)
... | [
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... | 2.118077 | 1,643 |
<gh_stars>1-10
#-------------------------------------------------------------------
#* EMSO Model Library (EML) Copyright (C) 2004 - 2007 ALSOC.
#*
#* This LIBRARY is free software; you can distribute it and/or modify
#* it under the therms of the ALSOC FREE LICENSE as available at
#* http://www.enq.ufrgs.br/alsoc.
#*
... | [
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... | 2.500525 | 2,855 |
<filename>test/packages/DocumentedCode/src/organized_folder/v_func.jl
"""
v_func()
Lorem ipsum dolor sit amet.
"""
function v_func()
9
end
"""
v_func(cur_obj::GType)
Lorem ipsum dolor sit amet.
"""
function v_func(cur_obj::GType)
8
end
"""
v_func(cur_obj::AType)
Lorem ipsum dolor sit amet.
"""
func... | [
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716,
... | 2.21118 | 161 |
<reponame>giordano/DataScienceTutorials.jl<gh_stars>0
# Before running this, please make sure to activate and instantiate the environment
# corresponding to [this `Project.toml`](https://raw.githubusercontent.com/alan-turing-institute/DataScienceTutorials.jl/master/Project.toml) and [this `Manifest.toml`](https://raw.g... | [
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290,
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9386,
262,
2858,
198,
2,
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284,
685,
5661,
... | 2.950645 | 1,783 |
# benchmarks of reduction on views
using NumericExtensions
const a = rand(1000, 1000)
const a_sub = sub(a, 1:999, :)
const a_view = view(a, 1:999, :)
println("for sum:")
for dim = 1:2
# warmup
sum(a_sub, dim)
sum(a_view, dim)
# profile
et1 = @elapsed for i=1:100; sum(a_sub, dim); end
et2 = ... | [
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... | 2.041262 | 412 |
<reponame>raphaelpanta/julia-lang-exemplos
include("..\\src\\introducao.jl")
module IntroducaoTeste
include("error_handler_pt_br.jl")
end
using Base.Test
import Introducao
Test.with_handler(custom_handler) do
@test soma(1,2) == 2
end
| [
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7... | 2.520833 | 96 |
module Node
mutable struct node
mass
radius
position
velocity
end
export node
end
| [
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] | 2.702703 | 37 |
<gh_stars>1-10
using RCall, MixedModels, Test
using StatsBase: zscore
const LMM = LinearMixedModel
const GLMM = GeneralizedLinearMixedModel
@testset "merMod" begin
# this is available in MixedModels.dataset(:sleepstudy) but with different
# capitalization than in R
sleepstudy = rcopy(R"sleepstudy")
jlm... | [
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14993... | 2.526316 | 247 |
<filename>basics.jl
println(Sys.WORD_SIZE)
println("typeof(1): $(typeof(1))")
println("zero: $(zero(Float64))")
println("zero: $(one(Float64))")
for T in [Int8,Int16,Int32,Int64,Int128,UInt8,UInt16,UInt32,UInt64,UInt128]
println("$(lpad(T,7)): [$(typemin(T)),$(typemax(T))]")
end
x = [1,2,3] .^ 3
println("vector... | [
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7,
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4008,
4943,
198,
35235,
7203,
22570,
25,
29568,
22570,
7,
43879,... | 2.413509 | 1,821 |
"""
readMapFromFITS{T <: Number}(f::FITSIO.FITSFILE, column, t::Type{T})
readMapFromFITS{T <: Number}(fileName::String, column, t::Type{T})
Read a Healpix map from the specified (1-base indexed) column in a
FITS file. The values will be read as numbers of type T. If the code
fails, FITSIO will raise an excepti... | [
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198,
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220,
220,
1100,
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4863,
37,
2972... | 2.141118 | 2,218 |
"""
Bridges `CP.Reification{MOI.EqualTo}` to indicator constraints, both with equality
and inequalities (CP.DifferentFrom).
"""
struct ReificationEqualTo2IndicatorBridge{T <: Real} <: MOIBC.AbstractBridge
indic_true::MOI.ConstraintIndex{MOI.VectorAffineFunction{T}, MOI.Indicator{MOI.ACTIVATE_ON_ONE, MOI.EqualTo{T}}... | [
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2... | 2.239366 | 1,387 |
module SizeInterlacedTest
using SimplePNGs
using Test
include("common.jl")
using .TestCommon: load_json
pl(name) = SimplePNGs.load(joinpath("PngSuite", name*".png"))
@testset "Size test files" begin
@testset "1x1 paletted file, interlaced" begin
img1 = load_json("s01n3p01")
img2 = pl("s01i3p01")
... | [
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62,
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198,
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7,
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8,
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47,
10503,... | 1.900126 | 1,592 |
using Dates
@testset "util.jl" begin
p1 = DDR2import.util.Point(1.0, 2.0)
@test p1.lat == 1.0
@test p1.lon == 2.0
@test DDR2import.util.extract_lat("S123456") ≈ -12.58222222 atol = 0.0001
@test DDR2import.util.extract_lat("N123456.0") ≈ 12.58222222 atol = 0.0001
@test DDR2import.util.extract_l... | [
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1... | 2.238095 | 1,470 |
<reponame>tpr0p/Altro.jl
############################################################################################
# INFEASIBLE MODELS #
############################################################################################
struct Infeasib... | [
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2,
220,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
22... | 2.243124 | 2,727 |
module GatekeepHelperFlagSummitGem
using ..Ahorn, Maple
# Thanks to Communal Helper for most of this implementation
@mapdef Entity "GatekeepHelper/FlagSummitGem" FlagSummitGem(
x::Integer,
y::Integer,
index::Integer=0,
sprite::String="",
flag::String="",
particleColor::String="",
)
const pla... | [
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... | 2.581498 | 454 |
<gh_stars>0
coast(region=[110 140 20 35],
proj=(name=:Albers, center=[125 20], parallels=[25 45]),
frame=:ag,
resolution=:low,
area=250,
land=:green,
shore=:thinnest,
fmt=:png, savefig="1")
coast(region=[-88 -70 18 24], proj=(name=:eqdc, center=[-79 21], parallels=[19 23]),
... | [
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220,
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220,
220,
220,
220,
220,
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73,
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28,
25,
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1213,
11,
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11623,
1160,
4357,
30614,
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1495,
4153,
... | 2.160787 | 2,948 |
<filename>src/Assessors.jl
# ----------------------------------------------------
# --- Accessor.jl
# ----------------------------------------------------
# Function to access to radio parameters
getError(obj::UHDBinding) = UHDBindings.getError(obj);
getError(obj::RadioSim) = RadioSims.getError(obj);
getError(obj::SD... | [
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7,
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33... | 2.968062 | 908 |
<reponame>yakir12/polarimetryLab
push!(LOAD_PATH, pwd())
const assets = "assets"
using Images, ImageMagick, Colors, Photopolarimetry
import Tk.ChooseDirectory
#include("Photopolar.jl")
include("PhotopolarGUIfunctions.jl")
path = Input(ChooseDirectory())
flip = Input(false)
flop = Input(false)
torun = Input{Any}(leftb... | [
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11,
591... | 2.316055 | 2,180 |
d = [0 19 17 34 7 20 10 17 28 15 23 29 23 29 21 20 9 16 21 13 12;
19 0 10 41 26 3 27 25 15 17 17 14 18 48 17 6 21 14 17 13 31;
17 10 0 47 23 13 26 15 25 22 26 24 27 44 7 5 23 21 25 18 29;
34 41 47 0 36 39 25 51 36 24 27 38 25 44 54 45 25 28 26 28 27;
7 26 23 36 0 27 11 17 35 22 30 36 30 22 25 26 14 23 28 20 10;
20... | [
67,
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15,
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2608,
513,
2681,
1679,
1315,
1596,
1596,
1478,
1248,
4764,
1596,... | 2.158105 | 3,251 |
immutable NGramModel
ml::Dict{UTF8String, Float64}
n::Integer
end
getindex(m::NGramModel, gram::String) = get(m.ml, utf8(gram), 0.0)
function NGramModel(sentences::Vector{String}, n)
# Tokenize string
tokenize(s) = TextAnalysis.tokenize(TextAnalysis.EnglishLanguage, s)
# NGramize tokens
fu... | [
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11,... | 2.196591 | 880 |
abstract type CIService end
struct GitHubActions <: CIService
username::String
email::String
api_hostname::String
clone_hostname::String
function GitHubActions(;
username="github-actions[bot]",
email="41898282+<EMAIL>-<EMAIL>[<EMAIL>",
api_hostname="https://api.github.com",... | [
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... | 2.309497 | 895 |
<reponame>invenia/Patchwork.jl
# Use Julia's `jl_type_morespecific` function to emulate Julia's multiple dispatch across
# generic functions.
#
# Origin:
# https://github.com/JuliaLang/julia/blob/master/doc/src/devdocs/types.md#subtyping-and-method-sorting
type_morespecific(a, b) = ccall(:jl_type_morespecific, Bool, (A... | [
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2,
198... | 2.919903 | 824 |
"""
Facet (`Vector{Int64}`) -> `BellGame`
convert(
::Type{BellGame},
facet::Vector{Int64},
scenario::Union{BlackBox, LocalSignaling};
rep = "normalized"::String
)
"""
function convert( ::Type{BellGame},
facet::Vector{Int64},
scenario::Union{BlackBox,LocalSignaling};
... | [
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220,
220,
220,
220,
220,
... | 2.071243 | 4,239 |
"""
KMarkovEnvironment{OV, M<:POMDP, S, R<:AbstractRNG} <: AbstractEnvironment{OV}
A k-markov wrapper for MDPs and POMDPs, given a MDP or POMDP create an AbstractEnvironment where s_t = (o_t, ..., o_t-k)
The K-Markov observation is represented by a vector of k observations.
"""
mutable struct KMarkovEnvironment{OV,... | [
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632... | 2.470353 | 1,248 |
<filename>src/QuadOsc.jl
module QuadOsc
export quadosc
include("SeriesAccelerations.jl")
using .SeriesAccelerations
using QuadGK
@doc raw"""
quadosc(fn, a, Inf, fnzeros; ...)
Integrate the function `fn(x)` from `a` to `Inf`. The function `fnzeros(n)`
takes an integer `n` and is such that `fn(fnzeros(n)) == 0`.... | [
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... | 2.090646 | 1,037 |
<filename>src/hartree_fock.jl<gh_stars>1-10
module HartreeFock
export extract_tij_Uijlk, solve_scf
using LinearAlgebra
import PyCall: pyimport
"""
Extract tij and Uijlk from a FermionOperator object, representing a Hamiltonian.
The Hamiltonian must be number conserving, and is allowed to contain upto two-body opera... | [
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3... | 2.065149 | 1,274 |
<reponame>korzhimanov/Vasilek.jl<gh_stars>1-10
module VlasovBenchmarks
using BenchmarkTools
const SUITE = BenchmarkGroup()
include(joinpath(dirname(@__FILE__),"..","src","VlasovSolver","LaxWendroff.jl"))
import .LaxWendroff
SUITE["LaxWendroff"] = BenchmarkGroup()
SUITE["LaxWendroff c"] = BenchmarkGroup()
include(jo... | [
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12709,
... | 1.954821 | 1,815 |
export mutate
"Mutate: Change weights"
function mutate_weights(indiv::NEATInd, cfg::Dict)
# TODO: check original weight mutation
ind = NEATInd(indiv)
for c in ind.connections
if rand() < cfg["p_mut_weights"]
c.weight = c.weight + randn()*cfg["weight_factor"]
end
end
ind
... | [
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46,
25,
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2656,
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1514... | 2.349107 | 1,120 |
<reponame>gdalle/MultiAgentPathFinding.jl<filename>test/learn_agents.jl<gh_stars>0
## Imports
using Base.Threads
using Flux
using Graphs
using InferOpt
using MultiAgentPathFinding
using PythonCall
using ProgressMeter
using UnicodePlots
## Test
rail_generators = pyimport("flatland.envs.rail_generators")
line_generato... | [
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198,
2235,
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198,
198,
3500,
7308,
13,
16818,
82,
198,
3500,... | 2.4 | 1,250 |
<reponame>hennyg888/Oceananigans.jl
using Oceananigans.Architectures
using Oceananigans.BoundaryConditions
using Oceananigans.TurbulenceClosures: calculate_diffusivities!
import Oceananigans.TimeSteppers: update_state!
"""
update_state!(model::IncompressibleModel)
Update peripheral aspects of the model (halo reg... | [
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13,
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198,
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272,
34090,
13,
49646,
560,
25559,
1756,
198,
3500,
10692,
272,
34090,
13,
51,
5945,... | 2.696565 | 524 |
<reponame>akhand9999/IncrementalInference.jl<filename>src/CSMOccuranceUtils.jl
export CSMOccuranceType
export parseCSMVerboseLog, calcCSMOccurancesFolders, calcCSMOccuranceMax, printCSMOccuranceMax, reconstructCSMHistoryLogical
# [cliqId][fsmIterNumber][fsmFunctionName] => (nr. call occurances, list global call seque... | [
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29,
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9429,
11770,
535,
3874,
6030,
198,
39344,
21136,
7902,
44,
13... | 2.261017 | 2,950 |
using AutoTest
Package = "BlackBoxOptim"
using BlackBoxOptim
function run(packagename, srcdir = "src", testdir = "test";
testfileregexp = r"^test_.*\.jl$",
srcfileregexp = r"^.*\.jl$")
testfiles = AutoTest.findfiles(testdir, testfileregexp; recursive = true) # in AutoTest this is false
srcfiles = Au... | [
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1,
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320,
198,
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7,
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480,
11,
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15908,
796,
366,
10677,
1600,
1332,
15908,
796,
366,
9288,
8172,
... | 2.590361 | 249 |
using RealInterface
using Base.Test
import SpecialFunctions, NaNMath
for f in RealInterface.UNARY_ARITHMETIC
@test isa(eval(Base, f), Function)
end
for f in RealInterface.BINARY_ARITHMETIC
@test isa(eval(Base, f), Function)
end
for f in RealInterface.UNARY_MATH
@test isa(eval(Base, f), Function)
end
for... | [
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198,
220,
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220,
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9288,
318,
64,
7,
182... | 2.526077 | 441 |
<filename>src/OceanTurbulenceParameterEstimation.jl
module OceanTurbulenceParameterEstimation
export OneDimensionalTimeSeries, InverseProblem, FreeParameters,
IdentityNormalization, ZScore, forward_map, observation_map,
eki, lognormal_with_mean_std, iterate!, EnsembleKalmanInversion, UnscentedKalmanIn... | [
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35,
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7575,
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11,
554,
4399,
40781,
11,
3232,
48944,
11,
220,
19... | 3.17193 | 285 |
<gh_stars>1-10
# Raw memory management
export Mem, available_memory, total_memory
module Mem
using ..VectorEngine
using ..VectorEngine.VEDA: vedaMemAlloc, vedaMemPtr, vedaMemFree, vedaMemGetInfo,
vedaMemAllocHost, vedaMemFreeHost
using Printf
#
# buffers
#
# a chunk of memory allocated using the VEDA APIs... | [
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196... | 2.356749 | 4,897 |
<filename>src/utilities.jl<gh_stars>0
import LowRankModels: copy_estimate, copy
export copy_estimate, copy
function copy_estimate(g::GFRM)
return GFRM(g.A,g.losses,g.r,g.k,
g.observed_features,g.observed_examples,
copy(g.U),copy(g.W))
end
| [
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192... | 2.037594 | 133 |
n = 9 # rand(1:10)
@test matrixdepot("clement", Float64, n) == matrixdepot("clement", n)
A = matrixdepot("clement", n)
B = matrixdepot("clement", n, 1)
@test diag(A+A', 1) == n*ones(n-1)
@test issymmetric(Array(B))
θ = matrixdepot("clement", 1)
println("'clement' passed test...")
| [
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8,
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32,
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17593,
10378,
313,
7203,
66,
... | 2.358333 | 120 |
@testset "Global Quantities" begin
# Test Residual
T = Float64
N = 10
dt = 0.1
p = 3
i = 2
model = UnicycleGame(p=p)
probsize = ProblemSize(N,model)
x0 = rand(SVector{model.n,T})
opts = Options()
Q = [Diagonal(rand(SVector{model.ni[i],T})) for i=1:p]
R = [Diagonal(rand(... | [
31,
9288,
2617,
366,
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220,
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838,
198,
220,
220,
220,
288,
83,
796,
657,
13,
16,
198,
2... | 1.897356 | 643 |
using SubHunt
using Test
using Random
using POMDPs
using POMDPPolicies
using POMDPSimulators
using DiscreteValueIteration
using ParticleFilters
using POMDPModelTools
using QMDP
@testset "VI" begin
rng = MersenneTwister(6)
pomdp = SubHuntPOMDP()
# show(STDOUT, MIME("text/plain"), SubVis(pomdp))
solver... | [
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350,
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47,
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444,
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350,
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35,
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320,
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198,
3500,
8444,
8374,
11395,
29993,
341,
198,
3500,
2142,
15... | 2.178049 | 820 |
# InflationTotalCPI - Implementación para obtener la medida estándar de ritmo
# inflacionario a través de la variación interanual del IPC
struct InflationTotalCPI <: InflationFunction
end
# Extender el método para obtener el nombre de esta medida
measure_name(::InflationTotalCPI) = "Variación interanual IPC"
measure_... | [
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987,
272,
723... | 2.598485 | 528 |
<filename>src/BinaryProvider.jl
__precompile__()
module BinaryProvider
using Compat
using Compat.Libdl
# Utilities for controlling verbosity
include("LoggingUtils.jl")
# Include our subprocess running functionality
include("OutputCollector.jl")
# External utilities such as downloading/decompressing tarballs
include("... | [
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3082,
265,
13,
25835,
25404,
198,
198,
2,
41086,
329,
12755,
15942,
16579,
198... | 3.232704 | 318 |
using HDF5
HDF5File <: HDF5Object
HDF5Object
| [
198,
3500,
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37,
20,
198,
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39,
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20,
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39,
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20,
10267,
198
] | 2 | 24 |
<gh_stars>0
#TYPES
"""
AbstractModel
abstract type for models
"""
abstract type AbstractModel end
"""
AbstractDependenceStructure
Types inheriting from abstract type `AbstractDependenceStructure`
"""
abstract type AbstractDependenceStructure end
"""
FullIndependence <: AbstractDependenceStructure
Ty... | [
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29,
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198,
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220,
220,
27741,
17633,
198,
198,
397,
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329,
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198,
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198,
397,
8709,
2099,
27741,
17633,
886,
628,
628,
198,
37811,
198,
220,
220,
220,
... | 3 | 735 |
function linsolve_cg( LF::LF3dGrid, b::Array{Float64,1};
x0 = nothing,
NiterMax = 1000, TOL=5.e-10,
convmsg=true, showprogress=false )
#
Npoints = size(b)[1]
if x0 == nothing
x = zeros(Float64, Npoints)
else
x = copy(x0)
end
#
r = z... | [
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62,
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37,
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220,
220,
220,
220,
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220,
220,
220,
220,
220,
220,
220,
... | 1.871237 | 598 |
using LowRankModels
# test losses in losses.jl
srand(1);
losses = [
QuadLoss(),
QuadLoss(10),
L1Loss(),
L1Loss(5.2),
HuberLoss(),
HuberLoss(4),
HuberLoss(3.1, crossover=3.2),
PeriodicLoss(2*pi),
PeriodicLoss(2*pi, 4),
PoissonLoss(20),
PoissonLoss(22,4.1),
OrdinalHingeLoss(1,10),
OrdinalHingeLoss(2,7,5),
Logistic... | [
3500,
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27520,
5841,
1424,
198,
198,
2,
1332,
9089,
287,
9089,
13,
20362,
198,
82,
25192,
7,
16,
1776,
198,
198,
22462,
274,
796,
685,
198,
4507,
324,
43,
793,
22784,
198,
4507,
324,
43,
793,
7,
940,
828,
198,
43,
16,
43,
79... | 2.428101 | 911 |
using SerialPorts
function _end_of_command(ser)
for i in 0:2
write(stdout, 0xff)
write(ser, 0xff)
end
end
function _execute_command(ser, cmd)
println(cmd)
write(ser, cmd)
_end_of_command(ser)
end
function main()
ser = SerialPort("COM4", 9600)
_execute_command(ser, "page 0"... | [
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220,
220,
... | 2.180952 | 210 |
<gh_stars>0
using Distributed
using Distributions
nb_draws = 100000
function inside_circle(x::Float64, y::Float64)
output = 0
if x^2 + y^2 <= 1
output = 1
end
return output
end
function pi_serial(nbPoints::Int64 = 128 * 1000; d=Uniform(-1.0,1.0))
#draw NbPoints from within the square centered in... | [
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11,
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8,
198,
220,
220,
220... | 2.512281 | 285 |
#=
From
"CAV 2020 Tutorial: Probabilistic Programming: A Guide for Verificationists"
https://www.youtube.com/watch?v=yz5uUf_03Ik&t=2657s
Around @23:30
Summary Statistics
parameters mean std naive_se mcse ess rhat ess_per_sec
Symbol Float64 Float64 Float64 F... | [
2,
28,
628,
220,
3574,
198,
220,
366,
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1,
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13,
785,
14,
8340,
30,
85,
28,
45579,
20,
84,
52,
69,
... | 1.992545 | 939 |
function main(dataPath)
lines = parse(readall(pipeline(`cat $[dataPath]ratings.csv`, `wc -l`)))
@time ratings = readdlm(dataPath * "ratings.csv", ',', header=true, dims=(lines, 4))
ratingsHeader = ratings[2]
ratings = ratings[1]
order = shuffle(collect(1:size(ratings)[1]))
ratings = ratings[order, :]
trainEnd ... | [
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198,
197,
31,
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10109,
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110... | 2.599379 | 322 |
<reponame>biomass-dev/BioMASS.jl
using PyCall
function __init__()
py"""
import os
import shutil
import re
def main(model_path):
''' Convert fitparam/n/*.dat -> out/n/*.npy
Parameters
----------
model_path : str
Path to your model written in Julia.
... | [
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12972,
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198,
220,
220,
220,
1330,
28686,
198,
220,
220,
22... | 1.385652 | 2,746 |
using hyporheicBiogeochemistry, DifferentialEquations
α = 1.6; τ₋ = 0.01; τ₊ = 1000.0; k = 0.0; V_frac = 1.0
q = qCalc_powerLaw(α, τ₋, τ₊, V_frac)
p = (q, α, τ₋, τ₊, k)
h(p,t) = [50.0]
u0 = [100.0]
tspan = (1000.0, 2000.0)
f = build_sam_model_dde(E_powerLaw, foc, tspan[1])
j = build_sam_model_dde2(E_powerLaw, foc, t... | [
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13,
15,
2... | 2.151862 | 349 |
<reponame>grahamas/AxisIndices.jl<gh_stars>10-100
using Documenter
using AxisIndices
using LinearAlgebra
using Metadata
using Statistics
makedocs(;
modules=[AxisIndices],
format=Documenter.HTML(),
pages=[
"index.md",
"references.md",
],
repo="https://github.com/Tokazama/AxisIndices... | [
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1... | 2.287081 | 209 |
<reponame>UnofficialJuliaMirror/IntArrays.jl-45d23951-e9a5-545c-8049-e4c4887f5525<filename>src/matrix.jl
const IntMatrix{w,T} = IntArray{w,T,2}
function IntMatrix{w,T}(m::Integer, n::Integer, mmap::Bool=false) where {w,T}
return IntArray{w,T}((m, n), mmap)
end
function IntMatrix{w,T}(mmap::Bool=false) where {w,T}... | [
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69,
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27,
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... | 2.244361 | 266 |
<filename>test/tracers_test.jl
using eFEM, Test
| [
27,
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29,
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62,
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198,
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37,
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11,
6208,
220,
198
] | 2.45 | 20 |
@ghdef mutable struct Installation
id::Union{Int, Nothing}
end
namefield(i::Installation) = i.id
@api_default function create_access_token(api::GitHubAPI, i::Installation, auth::JWTAuth; headers = Dict(), options...)
headers["Accept"] = "application/vnd.github.machine-man-preview+json"
payload = gh_post_... | [
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13,
312,
628,
198,
31,
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62,
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2163,
2251,
62,
1552... | 2.818824 | 425 |
"""
#### function ```get_line_params(xi::Float64, df::DataFrame)```
<br>
Description of ```get_line_params```
-----------------------------------------
Returns the parameters a,b of linear approximation y = ax +b. For the segment where the random number ξ falls into.
``
"""
function get_line_params(xi::Float... | [
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198,
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2163,
7559,
63,
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62,
1370,
62,
37266,
7,
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2414,
11,
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3712,
6601,
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8,
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63,
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29,
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220,
220,
220,
12489,
286,
7559,
63,
1136,
62,
1370,
62,
37266,
15506... | 2.222668 | 997 |
<reponame>findmyway/MLStyle.jl
module MLStyle
export @case, @data, @match, Pattern, Case, Failed, failed, PatternDef, pattern_match, app_pattern_match, (..), enum_next
include("utils.jl")
include("Err.jl")
using MLStyle.Err
include("Match.jl")
using MLStyle.Match
include("ADT.jl")
using MLStyle.ADT
include("Match... | [
27,
7856,
261,
480,
29,
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1820,
1014,
14,
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774,
293,
198,
198,
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2488,
7442,
11,
2488,
7890,
11,
2488,
15699,
11,
23939,
11,
8913,
11,
22738,
11,
4054,
11,
23939,
7469,
11,
3912,
6... | 2.662338 | 154 |
using HDF5
using JSON
savepath = "SARA/NatCom2020/outer/data/"
xrd_file = "Bi2O3_19F44_01_outer_xrd_gradients_input_noise_iSARA.h5"
# savefile = "Bi2O3_19F44_01_outer_xrd_gradients_no_input_noise.h5"
xrd_f = h5open(savepath * xrd_file, "r")
xrd_temperatures = read(xrd_f, "temperatures")
xrd_dwelltimes = read(xrd_f, "d... | [
3500,
5572,
37,
20,
198,
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6978,
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366,
50,
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14,
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14,
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14,
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46,
18,
62,
1129,
37,
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62,
486,
62,
39605,
62,
87,... | 2.093785 | 885 |
using Test
using LinearAlgebraicRepresentation
Lar = LinearAlgebraicRepresentation
using ViewerGL
GL = ViewerGL
@testset "GLShader.jl" begin
# function GLShader(vertex, fragment)
@testset "GLShader" begin
@test
@test
@test
@test
end
# function releaseGpuResources(shader::GLShader)... | [
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8763,
198,
198,
31,
9288,
2617,
366,
8763,
2484,
5067,
13,
2036... | 2.27762 | 353 |
using SatelliteToolbox
"""
T = disturbance(sun_vecs, air_density, current_qua)
擾乱によるトルクの計算
# Arguments
- `sun_vecs`: 太陽方向ベクトル@SEOF
- `air_density`：大気密度
- `sat_velocity`:衛星速度ベクトル@seof
- `current_qua`: 現在の姿勢クォータニオン
# Returns
- `T`: 擾乱によるトルクの合計
"""
function disturbance(sun_vecs, air_density, sat_velocity, current_qua... | [
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109,
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230,
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13298,
9202,
14099,
5641,
164,
101,
... | 1.489472 | 5,414 |
# -*- coding: utf-8 -*-
# ---
# jupyter:
# jupytext:
# formats: ipynb,jl:hydrogen
# text_representation:
# extension: .jl
# format_name: hydrogen
# format_version: '1.3'
# jupytext_version: 1.10.3
# kernelspec:
# display_name: Julia 1.6.4
# language: julia
# name: julia-1... | [
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220,
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25,
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11,
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25,
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... | 2.000837 | 1,195 |
<reponame>JuliaBinaryWrappers/czmq_jll.jl
# Use baremodule to shave off a few KB from the serialized `.ji` file
baremodule czmq_jll
using Base
using Base: UUID
import JLLWrappers
JLLWrappers.@generate_main_file_header("czmq")
JLLWrappers.@generate_main_file("czmq", UUID("bada3277-1da5-58a9-94c6-da212cd39369"))
end # ... | [
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21412,... | 2.382979 | 141 |
<reponame>dourouc05/ConstraintProgrammingExtensions.jl
"""
Bridges `CP.GlobalCardinality` to `CP.Count`.
"""
struct GlobalCardinalityFixedOpen2CountBridge{T} <: MOIBC.AbstractBridge
cons_count::Vector{MOI.ConstraintIndex{MOI.VectorAffineFunction{T}, CP.Count{MOI.EqualTo{T}}}}
end
function MOIBC.bridge_constraint(
... | [
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261,
480,
29,
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66,
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14,
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198,
33,
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1292,
414,
63,
284,
4600,
8697,
13,
12332,
44646,
198,
37811,
198,
... | 2.167095 | 1,167 |
module LevenshteinToolkit
# ----------------------------------------
# EXPORTED INTERFACE
# ----------------------------------------
export distance_matrix
export distance_row
export dfa
export nfa
export check
export draw
include("matrix.jl")
include("row.jl")
include("automata.jl")
end
| [
21412,
1004,
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25391,
15813,
198,
198,
2,
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982,
198,
2,
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15490,
1961,
23255,
49836,
198,
2,
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982,
198,
198,
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5253,
62,
6759,
8609,
198,
39344,
5253,
62,
808,
198,
198,
39344,
288,
13331,
198,
393... | 3.6875 | 80 |
<filename>src/filters.jl<gh_stars>0
"""
```math
\\tilde X = \\hat X_{t+1|t} = A\\hat X_{t|t}
```
"""
function KalmanFilter(M::LGSSM, y)
RR = M.R * M.R'
SS = M.S * M.S'
ydim, qdim = size(M.B)
xdim, pdim = size(M.R)
n = size(y, 1)
ϵ = zeros(ydim, 1, n)
Γ = zeros(ydim, ydim, n)
Γ⁻¹ = zero... | [
27,
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29,
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14,
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1010,
13,
20362,
27,
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62,
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29,
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198,
198,
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63,
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198,
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83,
10,
16,
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83,
92,
796,
317,
6852,
5183,
1395,
2... | 1.404023 | 4,574 |
module MCMC
Base.warn("MCMC.jl has moved to Lora.jl. Development in Lora.jl will continue. MCMC.jl is a placeholder for the future merge of various independent MCMC implementations in Julia, including Lora.jl.")
end
| [
21412,
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13,
13122,
9655,
13,
20362,
318,
257,
46076,
329,
262,
2003,
20121,
286... | 3.633333 | 60 |
using BoardGames
struct RandomStrategy <: Strategy end
function BoardGames.getmove(board, s::RandomStrategy)
rand(getmoves(board))
end
| [
3500,
5926,
24474,
198,
198,
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220,
220,
220,
43720,
7,
1136,
76,
5241,
7,
3526,
4008,
1... | 3.133333 | 45 |
# This file is a part of JuliaFEM.
# License is MIT: see https://github.com/JuliaFEM/JuliaFEM.jl/blob/master/LICENSE.md
# # Generating local matrices for problems
using JuliaFEM
# Plane stress Quad4 element with linear material model:
# In JuliaFEM the plane stress element can be defined using Quad4 element which
#... | [
2,
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318,
257,
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37,
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544,
37,
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13,
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14,
2436,
672,
14,
9866,
14,
43,
2149,
24290,
... | 3.235294 | 663 |
<gh_stars>1-10
export RecipeInflation, filter_state!, vortexassim
struct RecipeInflation <: InflationType
"Parameters"
p::Array{Float64,1}
end
# Filtering function to bound the strength of the vortices and sources
function filter_state!(x, config::VortexConfig)
@inbounds for j=1:config.Nv
# Ensure that vor... | [
27,
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62,
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29,
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12,
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220,
220,
220,
366,
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1,
198,
220,
220,
220,
... | 1.973014 | 1,964 |
<gh_stars>100-1000
using Revise
using ADCME
using PyCall
using LinearAlgebra
using PyPlot
using SparseArrays
using Random
# Random.seed!(233)
# TODO: specify your input parameters
A = sprand(10,5,0.3)
f = rand(10)
sol = A\f
u = constant(A)\f
sess = Session()
init(sess)
@show run(sess, u)-sol
# error()
# TODO: cha... | [
27,
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62,
30783,
29,
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3163,
20477,
198,
3500,
14534,
198,
2,
... | 2.053645 | 727 |
<gh_stars>1-10
# SPDX-License-Identifier: X11
# 2020-11-14
using Random
function geninput(bound::Integer, fn::AbstractString)
X = collect(-bound:bound)
Y = collect(-bound:bound)
n = 2bound + 1
println("Shuffling...")
shuffle!(X)
shuffle!(Y)
println("Printing to $fn...")
open(fn, "w") do f
for i... | [
27,
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62,
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29,
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8818,
2429,
15414,
7,
7784,
3712,
46541,
11,
24714,
3712,
2383... | 2.004082 | 245 |
module PackageName
# Write your package code here.
print("Hello Julia, Git and Kraken!")
end
| [
21412,
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2,
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15496,
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11,
15151,
290,
43392,
2474,
8,
198,
198,
437,
198
] | 3.428571 | 28 |
using CairoMakie
using ElectronDisplay
using FFTW
using LinearAlgebra
using Scapin.Elasticity
using Scapin.Bri17
const T = Float64
const d = 2
C = Hooke{d,T}(1.0, 0.3)
α = (0.25, 0.25) # Fraction of the domained that is polarized
N_coarse = (4, 4)
r_max = 9
N_fine = (2^r_max) .* N_coarse
results = Dict()
for r ∈ 0:... | [
3500,
23732,
44,
461,
494,
198,
3500,
5903,
1313,
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198,
198,
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309,
796... | 1.736165 | 777 |
<filename>test/test_tools.jl
module TestTools
using Test
using Mimi
import Mimi:
getproperty, reset_compdefs
reset_compdefs()
#utils: prettify
@test Mimi.prettify("camelCaseBasic") == Mimi.prettify(:camelCaseBasic) == "Camel Case Basic"
@test Mimi.prettify("camelWithAOneLetterWord") == Mimi.prettify(:camelWithA... | [
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651,
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11,
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62,
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82,
198,
198,
425... | 2.433393 | 563 |
SubWorker{T,A,PT} = RemoteChannel{Channel{Vector{SubProblem{T,A,PT}}}}
ScenarioProblemChannel{S} = RemoteChannel{Channel{ScenarioProblems{S}}}
Work = RemoteChannel{Channel{Int}}
Progress{T <: AbstractFloat} = Tuple{Int,Int,SubproblemSolution{T}}
ProgressQueue{T <: AbstractFloat} = RemoteChannel{Channel{Progress{T}}}
f... | [
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90,
50,
92,
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21520,
29239,
90,
29239,
90,
3351,
... | 1.76566 | 4,071 |
# tests for the synchronous task runner
import Arbiter.Sync: run_tasks
import Arbiter.ArbiterTasks: ArbiterTask
import Arbiter.ArbiterGraphs: NodeSet, ImmutableNodeSet
facts("empty") do
# solve no tasks
results = run_tasks(())
@fact results.completed --> ImmutableNodeSet()
@fact results.failed --> Im... | [
2,
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329,
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263,
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... | 2.476427 | 403 |
# Julia wrapper for header: /usr/local/include/sodium.h
# Automatically generated using Clang.jl wrap_c, version 0.0.0
@c Int32 sodium_init () libsodium
@c Int32 crypto_auth_hmacsha512256 (Ptr{Uint8}, Ptr{Uint8}, Uint64, Ptr{Uint8}) libsodium
@c Int32 crypto_auth_hmacsha512256_verify (Ptr{Uint8}, Ptr{Uint8}, Uint64, P... | [
2,
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15,
13,
15,
198,
198,
31,
66,
2558,
2624,
21072,
... | 2.318304 | 5,212 |
#! format: off
using PowerSystems
using PowerSimulations
using PowerSystemCaseBuilder
using Cbc #solver
solver = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 1, "ratioGap" => 0.5)
sys = build_system(PSITestSystems, "test_RTS_GMLC_sys")
for line in get_components(Line, sys)
if (get_base_voltage(get_fro... | [
2,
0,
5794,
25,
572,
198,
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82,
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796,
6436,
7509,
62,
4480,
62,
1078,
7657,
7,
34,
... | 2.588384 | 396 |
module HypergraphsEpidemics
using CSV
using DataFrames
using Query
using Tables
using Dates
using DataStructures
using Distributions
using SimpleHypergraphs
using Statistics
using Combinatorics
using Pipe: @pipe
using Random
using JSON
using JSON3
using Serialization
export Person
export Household
export Company
expo... | [
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46567,
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3500,
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34960,
82,
198,
... | 3.331707 | 205 |
using Test
# test the seg error functions
using EMIRT
using EMIRT.Evaluate
@testset "test evaluate" begin
# get test data
aff = EMIRT.IOs.imread(joinpath(dirname(@__FILE__),"../assets/aff.h5"))
lbl = EMIRT.IOs.imread(joinpath(dirname(@__FILE__),"../assets/lbl.h5"))
lbl = Array{UInt32,3}(lbl)
# compare python code ... | [
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1,
2221,
220,
198,
198,
2,
651,
1332,
1366,
198,
2001,
796,
17228,... | 2.360424 | 283 |
"""
gen_ref_dirs(dimension, n_paritions)
Generates Das and Dennis's structured reference points. `dimension` could be
the number of objective functions in multi-objective functions.
"""
function gen_ref_dirs(dimension, n_paritions)
return gen_weights(dimension, n_paritions)
end
function gen_weights(a, b)
... | [
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220,
220,
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7,
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307,
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286,
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5499,
287,
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... | 2.244311 | 835 |
<reponame>fingolfin/CompileBot.jl<filename>test/TestPackage3.jl/test/runtests.jl<gh_stars>10-100
using Test, TestPackage3
@static if VERSION > v"1.3"
@test hello3("Julia") == "Hello, Julia"
elseif VERSION > v"1.2"
@test domath3(2.0) ≈ 7.0
else
multiply3(2.0) == 8.0
end
| [
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27,
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62,
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29,
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11,
... | 2.241935 | 124 |
<reponame>UzielLinares/TaylorModels.jl<filename>src/validatedODEs.jl
# Some methods for validated integration of ODEs
const _DEF_MINABSTOL = 1.0e-50
"""
remainder_taylorstep!(f!, t, x, dx, xI, dxI, δI, δt, params)
Returns a remainder for the integration step for the dependent variables (`x`)
checking that the so... | [
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286,
440,
7206,
82,
198,
198,
9979,
4808,
32... | 1.972592 | 15,470 |
<gh_stars>0
@testset "Protting" begin
@testset "DistPlot1D" begin
# TODO
end
@testset "DistPlot2D" begin
# TODO
end
@testset "CornerPlot" begin
# TODO
end
end
| [
27,
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198,
220,
886,
628,
220,
2488,
9288,
2617,
366,
20344,... | 2.228916 | 83 |
<gh_stars>10-100
using RecurrenceAnalysis, DelimitedFiles, Statistics
# Measure the times (in ms) of evaluating an expression n times
macro measuretime(ex, n)
quote
# Train the expression and get the result
result = $(esc(ex))
t = zeros($n)
for i in 1:$n
t[i] = 1000*(@el... | [
27,
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29,
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8,
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281,
5408,
299,
1661,
198,
20285,
305,
3953,
2435,
7,
1069,
... | 2.042553 | 564 |
"""
dt = DotTheta( (x,y) -> dot(x,y) / length(x) )
This parametric type allows to define a new dot product from the one saved in `dt::dot`. More precisely:
dt(u1, u2, p1::T, p2::T, theta::T) where {T <: Real}
computes, the weigthed dot product ``\\langle (u_1,p_1), (u_2,p_2)\\rangle_\\theta = \\theta \\Re \\langle... | [
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198,
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284,
8160,
257,
649,
16605,
1720,
422,
262,
530,
7448,
287... | 2.494313 | 8,353 |
using Test, Onda, Dates, Random, UUIDs
@testset "pretty printing" begin
@test repr(TimeSpan(6149872364198, 123412345678910)) ==
"TimeSpan(01:42:29.872364198, 34:16:52.345678910)"
signal = Signal([:a, :b, Symbol("c-d")], Nanosecond(3), Nanosecond(Second(12345)),
:unit, 0.25, -0.5,... | [
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268... | 1.628696 | 2,063 |
<gh_stars>0
#################### Discrete Gibbs Sampler ####################
#################### Types and Constructors ####################
const DGSUnivariateDistribution =
Union{Bernoulli, Binomial, Categorical, DiscreteUniform,
Hypergeometric, NoncentralHypergeometric}
const DSForm = ... | [
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198,
220,
22... | 2.696024 | 1,635 |
cd(@__DIR__); include("setups/grid7x3.jl")
pyplot(dpi = 200)
## (a) eigenvectors by nondecreasing eigenvalue ordering
plot(layout = Plots.grid(3, 7))
for i in 1:N
heatmap!(reshape(𝚽[:, i], (Nx, Ny))', c = :viridis, cbar = false,
clims = (-0.4,0.4), frame = :none, ratio = 1, ylim = [0, Ny + 1],
... | [
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304,
9324,
303,
5217,
416,
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721,
260,
2313,
304,
... | 1.987755 | 490 |
# not working.
using LinearAlgebra, FFTW
import BSON, Statistics, Random
import PyPlot
import NMRSpectraSimulator
include("../src/NMRCalibrate.jl")
import .NMRCalibrate
# for loading something with Interpolations.jl
import OffsetArrays
import Interpolations
import PlotlyJS
import Plots
Plots.plotly()
import Destr... | [
2,
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13,
198,
198,
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8890,
8927,
198,
198,
17256,
7203,
40720,
10677,
1... | 2.53159 | 459 |
/**
* This class models a cloud storage API.
*/
class Cloud {
int{L} cloud;
/**
* Put a value into the cloud.
*/
void put(int x) {
this.cloud = x;
}
/**
* Put the only value the cloud stores.
*/
int get() {
return this.cloud;
}
}
| [
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6143,
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220,
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1988,
656,
262,
6... | 2.300813 | 123 |
<reponame>UnofficialJuliaMirror/ProteinEnsembles.jl-186d2b2d-8ad5-54a6-bcea-66047609c611
# Tests for align.jl
@testset "Align" begin
coords_one = [
1.0 0.0 0.0;
0.0 1.0 0.0;
0.0 0.0 0.0;
]
coords_two = [
0.0 -1.0 0.0;
1.0 0.0 0.0;
1.0 1.0 1.0;
]
tran... | [
27,
7856,
261,
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29,
3118,
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544,
27453,
1472,
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829,
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4051,
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12,
65,
344,
64,
12,
39885,
2857,
31751,
66,
21,
1157,
... | 1.635536 | 2,527 |
module Jags
using Compat, Pkg, Documenter, DelimitedFiles, Unicode, MCMCChains, StatsPlots
#### Includes ####
include("jagsmodel.jl")
include("jagscode.jl")
if !isdefined(Main, :Stanmodel)
include("utilities.jl")
end
"""The directory which contains the executable `bin/stanc`. Inferred
from `Main.JAGS_HOME` or `E... | [
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198,
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3775... | 2.348341 | 422 |
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