content stringlengths 6 1.03M | input_ids listlengths 4 535k | ratio_char_token float64 0.68 8.61 | token_count int64 4 535k |
|---|---|---|---|
<reponame>anthofflab/paper-2021-scch4
#-------------------------------------------------------------------------------
# This function creates an instance of SNEASY+FUND.
#-------------------------------------------------------------------------------
# Load required packages.
using Mimi
using MimiFUND
using MimiSNEAS... | [
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2,
8778,... | 2.201095 | 3,287 |
# This file was generated, do not modify it.
import MLJ: schema, std, mean, median, coerce, coerce!, scitype
using DataFrames
using UrlDownload
using PyPlot
ioff() # hide
raw_data = urldownload("https://github.com/tlienart/DataScienceTutorialsData.jl/blob/master/data/wri_global_power_plant_db_be_022020.csv?raw=true")... | [
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... | 2.502187 | 1,372 |
abstract type CompilerHint end
abstract type ProgramStructureHint <: CompilerHint end
abstract type AddressingHint <: CompilerHint end
include("static/kernel_hint.jl")
include("static/switch_hint.jl")
include("static/dynamic_address_hint.jl")
| [
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... | 3.05 | 80 |
module ConvDiffMIPDECO
using jInv.Mesh
using jInv.ForwardShare
using jInv.Utils
using jInv.LinearSolvers
using jInv.InverseSolve
using KrylovMethods
using LinearAlgebra
using SparseArrays
using Printf
using DSP
function getBICGSTB(;PC=:jac,maxIter=1000,out=0,tol=1e-10)
bicg = (A,b; M=identity,tol=1e-10,maxIter=500,o... | [
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... | 2.539146 | 1,124 |
module TestAcquisition
using Test
using LinearAlgebra
using GaussianDistributions
using CovarianceFunctions
const Kernel = CovarianceFunctions
using SARA: ucb, inner_sampling, random_sampling, uncertainty_sampling,
integrated_uncertainty_sampling
@testset "acquisition" begin
l = 1/2
k = Kernel.Len... | [
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244... | 1.957198 | 1,285 |
<reponame>angus-lewis/SFFM
using Plots, SFFM
# include("../../src/SFFM.jl")
cme_9 = SFFM.MakeME(SFFM.CMEParams[9])
f = SFFM.pdf(cme_9)
F(x) = 1 - SFFM.cdf(cme_9)(x)
x = 0:0.05:1.5
plot(x,f.(x), label = "α exp(Sz) s")
plot!(x,f.(x.+0.3)./F.(0.3), label = "α exp(S(0.3+z)) s/α exp(S 0.3) e")
plot!(x,f.(x.+0.6)./F.(0.6... | [
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... | 1.725086 | 291 |
<reponame>JuliaPackageMirrors/Polyhedra.jl
function simplextest{Lib<:PolyhedraLibrary}(lib::Lib)
A = [1 1; -1 0; 0 -1]
b = [1, 0, 0]
linset = IntSet([1])
V = [0 1; 1 0]
ine = SimpleHRepresentation(A, b, linset)
poly1 = polyhedron(ine, lib)
@test !isempty(poly1)
inequality_fulltest(poly1, A, b, linset)
... | [
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... | 2.301826 | 931 |
<reponame>phyjonas/ImpuritySGPE<gh_stars>1-10
__precompile__
@everywhere module OneDim
using Random
using FFTW
include("helper.jl")
include("NewtonImp.jl")
include("SGPE.jl")
include("solver.jl")
include("modelA.jl")
include("modelA_fourier_galerkin.jl")
include("SGPE_fourier_galerkin.jl")
export NewtonImp,
phi... | [
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<filename>backend/anime_data/snapshots_10805.jl<gh_stars>1-10
{"score": 7.38, "score_count": 45917, "timestamp": 1562557262.0}
{"score": 7.39, "score_count": 44143, "timestamp": 1545775577.0}
{"score": 7.41, "score_count": 36841, "timestamp": 1492413902.0}
{"score": 7.42, "score_count": 34604, "timestamp": 1478750823.0... | [
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... | 2.362764 | 521 |
#!/usr/bin/env julia
using Luxor, Random
Random.seed!(42)
using Test
function test_circular_arrows_1(pos)
gsave()
froma = rescale(rand(1:100), 1, 100, 0, 2pi)
toa = rescale(rand(1:100), (1, 100), (0, 2pi))
sethue("black")
arrow(pos, 100, froma, toa, linewidth=rand(1:6), arrowheadlength=rand(10... | [
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19... | 2.211634 | 808 |
function EventBasedManeuverTriggers(arg0::AbstractDetector, arg1::AbstractDetector)
return EventBasedManeuverTriggers((AbstractDetector, AbstractDetector), arg0, arg1)
end
function event_occurred(obj::EventBasedManeuverTriggers, arg0::SpacecraftState, arg1::EventDetector, arg2::jboolean)
return jcall(obj, "eve... | [
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... | 2.789157 | 830 |
module StressTest
"""
dream(seconds)
Like Base.sleep() except maxes out the thread for a specified number of seconds. The minimum dream time is 1
millisecond or input of `0.001`.
"""
function dream(sec::Real)
sec ≥ 0 || throw(ArgumentError("cannot dream for $sec seconds"))
t = Timer(sec)
while isopen(... | [
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27... | 2.854015 | 137 |
"""
qubits(N::Int; mixed::Bool=false)
qubits(sites::Vector{<:Index}; mixed::Bool=false)
Initialize qubits to:
- An MPS wavefunction `|ψ⟩` if `mixed = false`
- An MPO density matrix `ρ` if `mixed = true`
"""
qubits(N::Int; mixed::Bool=false) = qubits(siteinds("Qubit", N); mixed=mixed)
function qubits(si... | [
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28... | 2.213556 | 1,077 |
<reponame>americast/GPUArrays.jl<filename>src/fft.jl
import CLFFT
# figure out a gc safe way to store plans.
# weak refs won't work, since the caching should keep them alive.
# But at the end, we need to free all of these, otherwise CLFFT will crash
# at closing time.
# An atexit hook here, which will empty the dictio... | [
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4... | 2.372017 | 922 |
<gh_stars>0
include("myfile.jl")
| [
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# Stubs - Can be used as references
struct Account <: QBObject end
struct ItemBasedExpenseLineDetail; end
struct Employee <: QBObject end
struct Vendor <: QBObject end
struct Customer <: QBObject end
struct Item <: QBObject end
struct Company <: QBObject
Id::Maybe{Int}
end
from_json(::Type{ItemBasedExpenseLineDet... | [
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... | 2.480144 | 1,108 |
function area_balance(
psi_container::PSIContainer,
expression::Symbol,
area_mapping::Dict{String, Array{PSY.Bus, 1}},
branches,
)
time_steps = model_time_steps(psi_container)
remove_undef!(psi_container.expressions[expression])
nodal_net_balance = psi_container.expressions[expression]
c... | [
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11,
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90,
3... | 2.294903 | 824 |
export Transition;
struct Transition
move::Move
label::String
end
| [
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] | 3.6 | 20 |
using ROCKS
using Documenter
makedocs(;
modules = [ROCKS],
authors = "<NAME>",
repo = "https://github.com/DaymondLing/ROCKS.jl/blob/{commit}{path}#L{line}",
sitename = "ROCKS.jl",
format = Documenter.HTML(;
prettyurls = get(ENV, "CI", "false") == "true",
canonical = "https://Daymond... | [
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29924,
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366,
5450... | 2.030387 | 362 |
<filename>src/rules/1 Algebraic functions/1.2 Trinomial products/1.2.1 Quadratic/.jl
include("1.2.1.1 (a+b x+c x^2)^p.jl")
include("1.2.1.2 (d+e x)^m (a+b x+c x^2)^p.jl")
include("1.2.1.3 (d+e x)^m (f+g x) (a+b x+c x^2)^p.jl")
include("1.2.1.4 (d+e x)^m (f+g x)^n (a+b x+c x^2)^p.jl")
include("1.2.1.5 (a+b x+c x^2)^p (d... | [
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10... | 1.507979 | 376 |
@testset "'Design' ............................. " begin
srand(1234)
function simonsDesign(r1, n1, r, n)
nvec = [[n1 for x1 in 0:r1]; [n for x1 in (r1 + 1):n1]]
cvec = [[Inf for x1 in 0:r1]; [r for x1 in (r1 + 1):n1]]
return Design(nvec, cvec)
end
# Simon's designs for beta = .2, alpha = .05, p1 ... | [
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module MPSKit
using TensorKit,KrylovKit,Parameters, Base.Threads,OptimKit
using LinearAlgebra:diag,Diagonal;
import LinearAlgebra
#bells and whistles for mpses
export InfiniteMPS,FiniteMPS,MPSComoving,PeriodicArray,MPSMultiline
export transfer_left,transfer_right
export leftorth,rightorth,... | [
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27923... | 2.601509 | 1,458 |
"""
get_potential(kout, kin, P, s::ShapeParams) -> sigma_mu
Given a shape `s` with `2N` discretization nodes, outer and inner wavenumbers
`kout`,`kin`, and the cylindrical harmonics parameter `P`, returns the potential
densities `sigma_mu`. Each column contains the response to a different harmonic,
where the... | [
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... | 1.700748 | 5,751 |
using LinearAlgebra
using OpenCL
const sum_kernel = "
__kernel void sum(__global float *a,
__global const float *b)
{
int gid = get_global_id(0);
a[gid] = a[gid] + b[gid];
}
"
a = zeros(Float32, 50_000)
b = ones(Float32, 50_000)
device, ctx, queue = cl.create_compute_contex... | [
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220,
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220... | 2.129231 | 325 |
<reponame>grahamstark/ScottishTaxBenefitModel
module TheEqualiser
#
# This module automatically adjusts taxes (it and ni, optionally)
# so the net cost of benefit or other changes
# is close to zero.
#
# TODO needs a lot of work:
#
# - more options - so basic rate only etc;
# - use passed-in functions to equalise (li... | [
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8,
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2,
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262,
2010,
157... | 2.713341 | 907 |
<reponame>kailaix/NNFEM.jl<gh_stars>10-100
include("hyperelasticity.jl")
#
ts = ExplicitSolverTime(Δt, NT)
ubd, abd = compute_boundary_info(domain, globaldata, ts)
Fext = compute_external_force(domain, globaldata, ts)
d0 = zeros(2domain.nnodes)
v0 = zeros(2domain.nnodes)
a0 = zeros(2domain.nnodes)
mode = "consiste... | [
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7,
1... | 2.115619 | 986 |
@testset "Decreasing2LP: $(fct_type), dimension $(dim), $(T)" for fct_type in ["vector of variables", "vector affine function"], dim in [2, 3], T in [Int, Float64]
mock = MOIU.MockOptimizer(MILPModel{T}())
model = COIB.Decreasing2LP{T}(mock)
if T == Int
@test MOI.supports_constraint(model, MOI.Vari... | [
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68... | 2.111296 | 1,204 |
<gh_stars>10-100
using Statistics
using Distributions
using ProgressMeter
#=
References
----------
[1] <NAME>. (2001). "Global sensitivity indices for nonlinear
mathematical models and their Monte Carlo estimates." Mathematics
and Computers in Simulation, 55(1-3):271-280,
doi:10.1016/S037... | [
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2... | 2.459131 | 3,707 |
<filename>test/utils_test.jl<gh_stars>10-100
@testset "Auxiliary Functions Test" begin
@testset "check constant columns" begin
@test_throws Exception PartialLeastSquaresRegressor.check_constant_cols([1.0 1;1 2;1 3])
@test_throws Exception PartialLeastSquaresRegressor.check_constant_cols([1.0;1;1][:,:])
@test_... | [
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19... | 2.621795 | 468 |
<filename>src/AdjustQuasiGLM.jl
"""
AdjustQuasiGLM(model, ϕ; level)
Estimates dispersion parameter, adjusts original GLM to reflect the dispersion and returns results in a pretty DataFrame.
Usage:
```julia-repl
AdjustQuasiGLM(model, ϕ; level)
```
Arguments:
- `model` : The `GLM` model.
- `data` : The `DataFrame` co... | [
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44,
... | 2.867371 | 852 |
struct Snowflake
n::UInt64
end
Snowflake(s::AbstractString) = Snowflake(parse(UInt64, s))
Base.show(io::IO, s::Snowflake) = print(io, string(s.n; base=10))
Base.:(==)(s::Snowflake, n::Integer) = s.n == n
Base.:(==)(n::Integer, s::Snowflake) = n == s.n
StructTypes.StructType(::Type{Snowflake}) = StructTypes.StringT... | [
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9... | 2.384 | 250 |
for quad_degree = 1:20 # Exceeding degree 20 seems unnecessary at this time
@eval begin
# Square
@generated function gauss_quadrature(form::Val{:legendre},
shape::RefSquare,
degree::Val{$quad_degree},
... | [
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220,
220,
220,
220,
220,
220,... | 1.522114 | 1,854 |
<reponame>IgorKohan/NormalHermiteSplines.jl<filename>src/Interpolate.jl<gh_stars>1-10
function _prepare(nodes::Matrix{T},
kernel::RK
) where {T <: AbstractFloat, RK <: ReproducingKernel_0}
n = size(nodes, 1)
n_1 = size(nodes, 2)
min_bound = Vector{T}(undef, n)
co... | [
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3712... | 1.692278 | 7,770 |
<filename>src/util.jl<gh_stars>10-100
Mcdf(f,fmin,fmax) = (1.0./f - 1.0/fmax) ./ (1.0/fmin - 1.0/fmax)
function selection(λ, f, tend, t1)
#define the equation for selection as above
s = (λ .* t1 + log.(f ./ (1 .- f))) ./ (λ .* (tend - t1))
return s
end
function selection2clone(λ, f1, f2, tend, t1, t2)
... | [
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13... | 2.286129 | 5,508 |
<gh_stars>0
# <NAME>, 2022
# Codes for chapter 11
# Code for section 11.1
# deserialization of source data frame
using DataFrames
using Serialization
walk = deserialize("walk.bin")
# Code for a note on conversion
x = [1.5]
x[1] = 1
x
# Code from section 11.1.1
Matrix(walk)
Matrix{Any}(walk)
Matrix{String}(walk)... | [
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3500,
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198... | 2.031832 | 1,288 |
#useful functions that do no directly call C code
function getAllVertCoords()
numV = num_entities[1]
vertCoords = zeros(3, numV) # storage for all vertex coordinates
coords_tmp = zeros(3,1) # temporary storage for vetex coordinates
for i=1:numV
apf.getVertCoords(coords_tmp, 3, 1)
vertCoords[:, i] = coords_tmp
... | [
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8... | 2.672727 | 385 |
const hotkeys = Hotkey[
Hotkey(
"ctrl + alt + shift + s",
SettingsWindow.showSettings
),
Hotkey(
"ctrl + shift + s",
showFileSaveDialog
),
Hotkey(
"ctrl + s",
menuFileSave
),
Hotkey(
"ctrl + o",
showFileOpenDialog
),
Hot... | [
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13,
12860,... | 1.815476 | 504 |
<reponame>agdestein/DiscreteFiltering.jl<filename>src/filter/filter.jl
"""
Abstract continuous filter.
"""
abstract type Filter end
"""
IdentityFilter()
Identity filter, which does not filter.
"""
struct IdentityFilter <: Filter end
"""
TopHatFilter(width)
Top hat filter, parameterized by a variable filte... | [
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... | 2.972881 | 295 |
# Converts a String to Languages.Language (using STR_TO_LANG)
convert(::Type{L}, lang::S) where {L<:Languages.Language, S<:AbstractString} = begin
TypeLang = get(STR_TO_LANG, strip(lowercase(lang)), Languages.English)
return TypeLang()
end
# Converts Languages.Language to String (using LANG_TO_STR)
convert(::T... | [
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25,
23... | 2.527972 | 1,144 |
<reponame>mforets/NeuralVerification.jl
"""
Planet(optimizer, eager::Bool)
Planet integrates a SAT solver (`PicoSAT.jl`) to find an activation pattern that maps a feasible input to an infeasible output.
# Problem requirement
1. Network: any depth, ReLU activation
2. Input: hyperrectangle or bounded hpolytope
3. O... | [
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50... | 2.290896 | 2,867 |
<filename>Julia-Packages/Plot3D/src/Face.jl<gh_stars>10-100
## Code dealing with Face
mutable struct Face
nvertex::Int64
X::Array{Float64,1}
Y::Array{Float64,1}
Z::Array{Float64,1}
I::Array{Int64,1}
J::Array{Int64,1}
K::Array{Int64,1}
end
"""Default Constructor for Face
"""
function Fac... | [
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220,
220,
220,
299,
3... | 1.890698 | 860 |
"""
reflect(v, n)
Reflect direction `v` at plane with normal `n`.
"""
function reflect(v, n)
@assert(abs(norm(n) - 1) < 1e-11, "surface normal must be normalized")
return v - 2*dot(v, n)*n
end
"""
refract(v, n, ni_over_nt)
Compute direction of refracted ray according to Snell's law,
or return `noth... | [
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7,
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... | 2.662679 | 1,254 |
module SparseIR
import PyCall: pyimport, PyNULL, PyVector, PyObject
const sparse_ir = PyNULL()
const pyspr = PyNULL()
const pyaugment = PyNULL()
const pysampling = PyNULL()
function __init__()
copy!(sparse_ir, pyimport_conda("sparse_ir", "sparse-ir", "spm-lab"))
copy!(pyspr, pyimport("sparse_ir.spr"))
co... | [
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9485,
33991,
3419,
198,... | 2.552727 | 275 |
<gh_stars>0
#= Instructions:
- Pkg.add("PkgBenchmark.jl")
- using PkgBenchmark
- results = benchmarkpkg("IntervalArithmetic")
- showall(results)
- results = judge("IntervalArithmetic", "v0.9.1") # compare current version to that tag
- showall(results)
=#
using IntervalArithmetic
@benchgroup "Constructors" begin
... | [
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18335,
35339,
7203,
9492,
2100,
... | 2.300683 | 439 |
<reponame>gottacatchenall/DynamicGrids.jl
# Sequence rules over the [`SimData`](@ref) object,
# calling [`maprule!`](@ref) for each individual `Rule`.
function sequencerules!(simdata::AbstractSimData)
newsimdata = sequencerules!(simdata, rules(simdata))
_maybemask!(grids(newsimdata))
newsimdata
end
function... | [
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29,
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63,
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63,
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31,... | 2.845865 | 266 |
<gh_stars>0
module InterfaceSymbolicUtilsModule
using SymbolicUtils
import ..CoreModule: CONST_TYPE, Node, Options
import ..UtilsModule: isgood, isbad, @return_on_false
const SYMBOLIC_UTILS_TYPES = Union{<:Number,SymbolicUtils.Symbolic{<:Number}}
const SUPPORTED_OPS = (cos, sin, exp, cot, tan, csc, sec, +, -, *, /)
... | [
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... | 2.343258 | 3,560 |
fs1()
@testset "LX input" begin
set_curpath("index.md")
mkpath(joinpath(F.PATHS[:assets], "index", "code", "output"))
write(joinpath(F.PATHS[:assets], "index", "code", "s1.jl"), "println(1+1)")
write(joinpath(F.PATHS[:assets], "index", "code", "output", "s1a.png"), "blah")
write(joinpath(F.PATHS[:a... | [
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31,
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1,
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900,
62,
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7,
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6978,
7,
37,
13,
47,
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7998,
58,
25,
1966... | 2.15277 | 1,859 |
using Flux, CUDA, Test
using Flux: pullback
@testset "CUDNN BatchNorm" begin
@testset "4D Input" begin
x = Float64.(collect(reshape(1:12, 2, 2, 3, 1)))
m = BatchNorm(3)
cx = gpu(x)
cm = gpu(m)
y, back = pullback((m, x) -> m(x), m, x)
cy, cback = pullback((m, x) -> m... | [
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11,
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220,
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2... | 1.679153 | 614 |
const PAR_MAGIC = "PAR1"
const SZ_PAR_MAGIC = length(PAR_MAGIC)
const SZ_FOOTER = 4
const SZ_VALID_PAR = 2*SZ_PAR_MAGIC + SZ_FOOTER
# page is the unit of compression
mutable struct Page
colchunk::ColumnChunk
hdr::PageHeader
pos::Int
data::Vector{UInt8}
end
mutable struct PageLRU
refs::Dict{Column... | [
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16,
1,
198,
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62,
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62,
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2149,
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4129,
7,
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62,
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2149,
8,
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311,
57,
62,
6080,
2394,
1137,
796,
604,
198,
9979,
311,
57,
62,
23428,... | 2.408476 | 5,545 |
# Author: <NAME>, <EMAIL>
# Date: 12/11/2014
module AbstractGenerativeModelImpl
export AbstractGenerativeModel
abstract AbstractGenerativeModel
end #module
module AbstractGenerativeModelInterfaces
export get,
isterminal
function get() end
function isterminal() end
end #module
| [
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25,
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198,
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27741,
8645,
876,
17633,
198,
198,
397,
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27741,
8645,
876,
1763... | 3.217391 | 92 |
@testset "ModelKit - SLP" begin
@testset "CompiledHomotopy/InterpretedHomotopy" begin
@var x y a b c
f = [(2 * x^2 + b^2 * y^3 + 2 * a * x * y)^3, (a + c)^4 * x + y^2]
@var s sp[1:3] sq[1:3]
g = subs(f, [a, b, c] => s .* sp .+ (1 .- s) .* sq)
h = Homotopy(g, [x, y], s, [sp... | [
31,
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2617,
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532,
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47,
1,
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366,
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313,
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5310,
276,
28718,
313,
11081,
1,
2221,
198,
220,
220,
220,
220,
220,
220,
220,
2488,
778... | 1.675808 | 3,683 |
<filename>src/parsing.jl
function addkey!(membernames, nam)
if !haskey(membernames, nam)
membernames[nam] = gensym()
end
membernames[nam]
end
onearg(e::Expr, f) = e.head == :call && length(e.args) == 2 && e.args[1] == f
onearg(e, f) = false
mapexpr(f, e) = Expr(e.head, map(f, e.args)...)
replace_... | [
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8,
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220,
220,
220,
220,
220,
220,
... | 2.201792 | 4,911 |
<reponame>mattwigway/ArchGDAL.jl<gh_stars>100-1000
using Downloads
using SHA
# this file downloads files which are used during testing the package
# if they are already present and their checksum matches, they are not downloaded again
REPO_URL = "https://github.com/yeesian/ArchGDALDatasets/blob/master/"
# remote fil... | [
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973,
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4856,
262,
5301... | 2.341762 | 1,226 |
@testset "eigenvalues/eigenvectors: $MatT" for MatT in (AcbMatrix, AcbRefMatrix)
A = [
0.6873474041954415 0.7282180564881044 0.07360652513458521
0.000835810121029068 0.9256166870757694 0.5363310989411239
0.07387174694790022 0.4050436025621329 0.20226010388885896
]
B = [
0.898... | [
31,
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68,
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68,
9324,
303,
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25,
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1,
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51,
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357,
12832,
65,
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11,
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65,
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46912,
8,
198,
220,
220,
220,
317,
796,
685,
198,
220,
220,
220,
220,
220,
220,... | 1.683111 | 2,919 |
<gh_stars>0
module VortexHelperBowlPuffer
using ..Ahorn, Maple
@mapdef Entity "VortexHelper/BowlPuffer" BowlPuffer(x::Integer, y::Integer, noRespawn::Bool = false, explodeTimer::Number = 1.0)
const placements = Ahorn.PlacementDict(
"Pufferfish Bowl (Vortex Helper)" => Ahorn.EntityPlacement(
BowlPuffer,
... | [
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... | 2.422414 | 348 |
# Testing:
#
# - computation of sufficient statistics
# - distribution fitting (i.e. estimation)
#
using Distributions
using Base.Test
n0 = 100
N = 10^5
w = rand(n0)
# DiscreteUniform
x = rand(DiscreteUniform(10, 15), n0)
d = fit(DiscreteUniform, x)
@test isa(d, DiscreteUniform)
@test minimum(d) == minimum(x)
@t... | [
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3500,
7308,
13,
14402,
198,
198,
77,
15,
796,
1802,
198,
45... | 2.092162 | 3,700 |
using DiffEqFlux, Flux
using LinearAlgebra, Distributions
using Optim, GalacticOptim
using Test
function run_test(f, layer, atol)
data_train_vals = [rand(length(layer.model)) for k in 1:500]
data_train_fn = f.(data_train_vals)
function loss_function(component)
data_pred = [layer(x,component) for ... | [
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8,
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220,
2... | 2.412568 | 732 |
<reponame>grahamstark/ScottishTaxBenefitModel
#
# This is the benefit/tax credit/IT/MinWage/NI rates from April 2021
#
sys.it.savings_rates = [0.0, 20.0, 40.0, 45.0]
sys.it.savings_thresholds = [5_000.0, 37_700.0, 150_000.0]
sys.it.savings_basic_rate = 2 # above this counts as higher rate
sys.it.non_savings_rate... | [
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2,
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13,
... | 2.209059 | 5,343 |
<reponame>mipals/SymEGRSSMatrices
struct SymEGRQSMatrix{T,UT<:AbstractArray,VT<:AbstractArray,dT<:AbstractArray} <: AbstractMatrix{T}
Ut::UT
Vt::VT
d::dT
n::Int
p::Int
function SymEGRQSMatrix{T,UT,VT,dT}(Ut,Vt,d,n,p) where
{T,UT<:AbstractArray,VT<:AbstractArray,dT<:AbstractArray}
Up, Un = siz... | [
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27,
25,
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19182,
11,
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51,
27,
25,
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... | 2.132092 | 1,128 |
using DataFrames
using DuckDB
using Test
using Dates
using UUIDs
test_files = [
"test_appender.jl",
"test_basic_queries.jl",
"test_config.jl",
"test_connection.jl",
"test_df_scan.jl",
"test_prepare.jl",
"test_transaction.jl",
"test_sqlite.jl",
"test_replacement_scan.jl",
"test_t... | [
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198,
220,
220,
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366,
... | 2.180952 | 315 |
<reponame>RalphAS/SLICOTMath.jl
# Portions translated from SLICOT-Reference distribution
# Copyright (c) 2002-2020 NICONET e.V.
function run_mb03bd(datfile, io=stdout)
NIN = 5
NOUT = 6
KMAX = 6
NMAX = 50
LDA1 = NMAX
LDA2 = NMAX
LDQ1 = NMAX
LDQ2 = NMAX
LDWORK = KMAX + max( 2*NMAX, 8*K... | [
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13,
19... | 1.843279 | 1,793 |
# Do not share a stream between processes
# The token would be shared so putting would give InvalidSequenceTokenException a lot
struct CloudWatchLogHandler{F<:Formatter} <: Handler{F, Union{}}
stream::CloudWatchLogStream
channel::Channel{LogEvent} # only one task should read from this channel
fmt::F
end
"... | [
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92,
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25,
32412,
... | 2.657081 | 1,391 |
##### multi dimensional advection
##### For incompressible model only
##### calculate tendencies in x direction
@kernel function calc_Gcˣ_kernel!(Gc, c, u, g::AbstractGrid, ΔT)
i, j, k = @index(Global, NTuple)
### offset index for halo points
ii = i + g.Hx
jj = j + g.Hy
kk = k + g.Hz
@inbounds G... | [
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0,
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11,
... | 2.133333 | 2,715 |
<gh_stars>10-100
# Using the ZigZagBoomerang with Turing with the BouncyParticle sampler
# (The approach taken here is retrieving the likelihood function from Turing and sampling
# directly with ZigZagBoomerang and not using Turings `AbstractMCMC` )
using Turing
using ZigZagBoomerang
const ZZB = ZigZagBoomerang
usin... | [
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318,
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262,
14955,
2163,
422,
3914... | 2.48294 | 1,524 |
######################################################################
# Additional errors used in the library.
# -----
# Licensed under MIT License
export CancellationError
struct CancellationError <: Exception
what
end
CancellationError() = CancellationError(nothing)
function Base.showerror(io::IO, err::Cancell... | [
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220,
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... | 2.882813 | 256 |
@inline function initialize!(integrator,cache::ExplicitRKConstantCache,f=integrator.f)
integrator.kshortsize = 2
integrator.k = eltype(integrator.sol.k)(integrator.kshortsize)
integrator.fsalfirst = f(integrator.t,integrator.uprev)
end
@inline function perform_step!(integrator,cache::ExplicitRKConstantCache,f=in... | [
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... | 2.027609 | 1,811 |
module FluspectMod
#using GSL
using Polynomials
using Statistics
# Matlab reading
using MAT
# Numerical integration package (Simson rule)
using QuadGK
# Is this OK?
file_Opti = joinpath(dirname(pathof(FluspectMod)), "Optipar2017_ProspectD.mat")
const minwle = 400.; # PAR range
const maxwle = 700.;
const minwlf = 6... | [
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8,
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38,
42,
... | 1.923092 | 15,330 |
using MyPkgDemo
using Documenter
makedocs(;
modules=[MyPkgDemo],
authors="MegamindHenry",
repo="https://github.com/MegamindHenry/MyPkgDemo.jl/blob/{commit}{path}#L{line}",
sitename="MyPkgDemo.jl",
format=Documenter.HTML(;
prettyurls=get(ENV, "CI", "false") == "true",
canonical="http... | [
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198,
220,... | 2.038462 | 286 |
<reponame>sisl/GrammarExpts.jl
#*****************************************************************************
# Written by <NAME>, <EMAIL>
# *****************************************************************************
# Copyright ã 2015, United States Government, as represented by the
# Administrator of the National A... | [
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6184,... | 2.307604 | 6,076 |
<reponame>JuliaPackageMirrors/NearestNeighbors.jl
# Does not test leafsize
# Does not test different metrics
import Distances.evaluate
@testset "knn" begin
@testset "metric" for metric in metrics
@testset "tree type" for TreeType in trees_with_brute
# 8 node rectangle
data = [0.0 0.... | [
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31,
9288,
2617,... | 1.862106 | 921 |
<reponame>ArbitRandomUser/Javis.jl
"""
ObjectSetting
The current settings of an [`Object`](@ref) which are saved in `object.current_setting`.
# Fields
- `line_width::Float64`: the current line width
- `mul_line_width::Float64`: the current multiplier for line width.
The actual line width is then: `mul_line_wi... | [
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... | 2.943515 | 956 |
#------------------------------------------------------------------------------
"""
excise(x...)
Remove all lines where the is a NaN/missing in any of the x arrays
# Examples
- `x1 = excise(x)`
- `(y1,x1) = excise(y,x)`
"""
function excise(x...)
n = length(x)
vv = FindNNPs(x...) #find rows with NaN/... | [
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<reponame>UnofficialJuliaMirror/Nabla.jl-49c96f43-aa6d-5a04-a506-44c7070ebe78<filename>src/sensitivities/indexing.jl
# Implementation of reverse-mode sensitivities for `getindex`.
import Base.getindex
for i = 1:7
T = Expr(:curly, :Tuple, fill(:Any, i)...)
is_node = Expr(:vect, true, fill(false, i - 1)...)
@... | [
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29... | 2.253054 | 573 |
module WaveFD
using Base.Threads, CvxCompress, DSP, Distributed, DistributedArrays, FFTW, LinearAlgebra, NearestNeighbors, Random, SpecialFunctions, StaticArrays, Statistics, WaveFD_jll
import
Base.convert,
Base.copy,
Base.get,
Base.min,
Base.max,
Base.maximum,
Base.show,
Base.size
abstract type Language end
struct ... | [
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1... | 2.509772 | 614 |
<filename>julia/emit_log_direct.jl
using AMQPClient
const VIRTUALHOST = "/"
const HOST = "127.0.0.1"
function send()
# 1. Create a connection to the localhost or 127.0.0.1 of virtualhost '/'
connection(; virtualhost=VIRTUALHOST, host=HOST) do conn
# 2. Create a channel to send messages
channel... | [
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1,
6... | 2.121547 | 543 |
<gh_stars>0
# Question
# What is the largest prime factor of the number 600851475143 ?
# Time
# O(n) any better solution??
function sieve(a)
# find all the prime numbers less than or equal to a
sieve = collect(1:a)
# now from this iterate from 2 and remove all their multiples
index = ones(Bool, a)
... | [
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7... | 2.659193 | 223 |
<gh_stars>1-10
abstract type AbstractModelSet end
# using CSV
# using DataFrames
"""
WindFarmModelSet(wakedeficitmodel, wake_deflection_model, wake_combination_model, local_ti_model)
Container for objects defining models to use in wind farm calculations
# Arguments
- `wake_defiict_model::AbstractWakeDeficitModel... | [
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44189,
198,
2,
1262,
6060,
35439,
198,
198,
37811,
198,
220,
220,
220,
3086,
48412,
17633,
7248,
7,
86,
4335,
891,
3628,
19849,
11,
... | 2.519399 | 8,583 |
<gh_stars>10-100
"""
SeisSort(in, out;<keyword arguments>)
Sort a seis file using its header words
# Arguments
* `in`: input filename >> a text file with information about data extent, data and header file names; a binary file containing data and a binary file containing headers.
* `out`: output filename
# Keywo... | [
27,
456,
62,
30783,
29,
940,
12,
3064,
198,
37811,
198,
220,
220,
220,
1001,
271,
42758,
7,
259,
11,
503,
26,
27,
2539,
4775,
7159,
43734,
198,
198,
42758,
257,
384,
271,
2393,
1262,
663,
13639,
2456,
198,
198,
2,
20559,
2886,
198... | 2.239437 | 1,278 |
<reponame>ethansaxenian/RosettaDecode
using Printf, Distributions, IterTools
newv(n::Int, p::Float64) = rand(Bernoulli(p), n)
runs(v::Vector{Int}) = sum((a & ~b) for (a, b) in zip(v, IterTools.chain(v[2:end], v[1])))
mrd(n::Int, p::Float64) = runs(newv(n, p)) / n
nrep = 500
for p in 0.1:0.2:1
lim = p * (1 - p)
... | [
27,
7856,
261,
480,
29,
2788,
504,
897,
268,
666,
14,
35740,
15253,
10707,
1098,
198,
3500,
12578,
69,
11,
46567,
507,
11,
40806,
33637,
198,
198,
3605,
85,
7,
77,
3712,
5317,
11,
279,
3712,
43879,
2414,
8,
796,
43720,
7,
23927,
2... | 1.867868 | 333 |
export discreteApprox!, discreteApprox, discreteNormalApprox, discreteNormalApprox!
# ----------------------- objective functions for max entropy calcs --------------------------
function expΔTx!(tmpvec::Vector, ΔT::AbstractMatrix, x::AbstractVector)
mul!(tmpvec, ΔT, x)
tmpvec .= exp.(tmpvec)
end
# objective
fun... | [
39344,
28810,
4677,
13907,
28265,
28810,
4677,
13907,
11,
28810,
26447,
4677,
13907,
11,
28810,
26447,
4677,
13907,
0,
198,
198,
2,
41436,
6329,
9432,
5499,
329,
3509,
40709,
2386,
6359,
220,
22369,
438,
198,
198,
8818,
1033,
138,
242,
... | 2.373108 | 2,246 |
mutable struct zmp_com_observer_state_t <: LCMType
utime::Int64
com::SVector{2, Float64}
comd::SVector{2, Float64}
ground_plane_height::Float64
end
@lcmtypesetup(zmp_com_observer_state_t)
| [
76,
18187,
2878,
1976,
3149,
62,
785,
62,
672,
15388,
62,
5219,
62,
83,
1279,
25,
22228,
44,
6030,
198,
220,
220,
220,
3384,
524,
3712,
5317,
2414,
198,
220,
220,
220,
401,
3712,
50,
38469,
90,
17,
11,
48436,
2414,
92,
198,
220,
... | 2.204301 | 93 |
function save_data!(A::Array{T,1}, dset::HDF5Dataset, src_ind::AbstractRange{Int}, dest_ind::AbstractRange{Int}) where T
dsel_id = HDF5.hyperslab(dset, src_ind)
V = view(A, dest_ind)
memtype = HDF5.datatype(A)
memspace = HDF5.dataspace(V)
HDF5.h5d_write(dset.id, memtype.id, memspace.id, dsel_id, dset.xfer, V)... | [
8818,
3613,
62,
7890,
0,
7,
32,
3712,
19182,
90,
51,
11,
16,
5512,
288,
2617,
3712,
39,
8068,
20,
27354,
292,
316,
11,
12351,
62,
521,
3712,
23839,
17257,
90,
5317,
5512,
2244,
62,
521,
3712,
23839,
17257,
90,
5317,
30072,
810,
30... | 2.128866 | 194 |
const DEBUG_ENABLED = Ref(false)
const DEBUG_CALLBACK = Ref{Function}()
@export struct GLDebugInfo <: Iterable
type::String
source::String
message::String
severity::String
end
function debug_message_callback(
_source::GLenum,
_type::GLenum,
::GLuint,
_severity::GLenum,
::GLsizei,
_m... | [
9979,
16959,
62,
1677,
6242,
30465,
796,
6524,
7,
9562,
8,
198,
9979,
16959,
62,
34,
7036,
31098,
796,
6524,
90,
22203,
92,
3419,
198,
198,
31,
39344,
2878,
10188,
27509,
12360,
1279,
25,
40806,
540,
198,
220,
220,
2099,
3712,
10100,
... | 2.23269 | 881 |
function sqlite3_errmsg()
return ccall( (:sqlite3_errmsg, sqlite3_lib),
Ptr{Uint8}, () )
end
function sqlite3_errmsg(db::Ptr{Void})
@NULLCHECK db
return ccall( (:sqlite3_errmsg, sqlite3_lib),
Ptr{Uint8}, (Ptr{Void},), db )
end
function sqlite3_open(file::AbstractString... | [
198,
8818,
44161,
578,
18,
62,
8056,
19662,
3419,
198,
220,
220,
220,
1441,
269,
13345,
7,
357,
25,
25410,
578,
18,
62,
8056,
19662,
11,
44161,
578,
18,
62,
8019,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
... | 2.01475 | 4,000 |
type Job
cmd :: AbstractString
jobid :: Int
pbs_id :: Int
end
function ex(job)
output = "$(job.pbs_id)-$(myid()-1).out"
err = "$(job.pbs_id)-$(myid()-1).err"
println("start $(job.jobid)-th job on process $(myid()-1).")
open(io->println(io, "start $(job.jobid)-th job on process $(myid()-1)."... | [
4906,
15768,
198,
220,
220,
220,
23991,
7904,
27741,
10100,
198,
220,
220,
220,
1693,
312,
7904,
2558,
198,
220,
220,
220,
279,
1443,
62,
312,
7904,
2558,
198,
437,
198,
198,
8818,
409,
7,
21858,
8,
198,
220,
220,
220,
5072,
796,
... | 2.3 | 360 |
<reponame>johnnychen94/NiLang.jl
export rot, plshift, prshift, arshift
"""
rot(a, b, θ)
rotate variables `a` and `b` by an angle `θ`
"""
function rot(a, b, θ)
s, c = sincos(θ)
a*c-b*s, a*s+b*c
end
"""
plshift(x, n)
periodic left shift.
"""
plshift(x, n) = (x << n) | (x >> (sizeof(x)*8-n))
"""
p... | [
27,
7856,
261,
480,
29,
30686,
3281,
6607,
5824,
14,
34153,
43,
648,
13,
20362,
198,
39344,
5724,
11,
458,
30846,
11,
778,
30846,
11,
610,
30846,
198,
198,
37811,
198,
220,
220,
220,
5724,
7,
64,
11,
275,
11,
7377,
116,
8,
198,
... | 1.945652 | 276 |
struct VolumePartsIter{
TM<:AbstractMatrix,
TV<:AbstractVector,
Tg <: AbstractVector,
Tts<:AbstractVector,
Texpand<:NamedTuple,
T<:Real} <: AbstractVolumePartsIter{TM, TV, T}
#parameters
A::TM
Ã::TM #factored A, used in regressions
G::TM
g::Tg #vector version by referene of G, sho... | [
198,
198,
7249,
14701,
42670,
29993,
90,
198,
220,
220,
220,
21232,
27,
25,
23839,
46912,
11,
198,
220,
220,
220,
3195,
27,
25,
23839,
38469,
11,
198,
220,
220,
220,
309,
70,
1279,
25,
27741,
38469,
11,
198,
220,
220,
220,
309,
91... | 2.066796 | 6,677 |
# ===============================================================
# Discretize using the correction hull of the matrix exponential
# ===============================================================
"""
CorrectionHull{EM} <: AbstractApproximationModel
Discretization using the correction hull of the matrix exponenti... | [
2,
46111,
4770,
25609,
855,
198,
2,
8444,
1186,
1096,
1262,
262,
17137,
23644,
286,
262,
17593,
39682,
198,
2,
46111,
4770,
25609,
855,
198,
198,
37811,
198,
220,
220,
220,
35074,
39,
724,
90,
3620,
92,
1279,
25,
27741,
4677,
13907,
... | 2.388522 | 1,969 |
module PIPS_NLP
# package code goes here
end # module
include("ParPipsNlp.jl")
include("PipsNlp.jl") | [
21412,
30434,
3705,
62,
45,
19930,
198,
198,
2,
5301,
2438,
2925,
994,
628,
198,
437,
1303,
8265,
198,
198,
17256,
7203,
10044,
47,
2419,
45,
34431,
13,
20362,
4943,
198,
17256,
7203,
47,
2419,
45,
34431,
13,
20362,
4943
] | 2.6 | 40 |
<reponame>Datseris/FractalDimension
# %% Sensititivy to trajectory length
using DrWatson
@quickactivate :FractalDimension # uses DynamicalSystems, PyPlot
include(srcdir("style.jl"))
using DynamicalSystems, PyPlot
# %%
N = 1*10^5
systems = [:koch, :henon_chaotic]
slabels = ["Koch", "Hénon"]
qs = 2:4
Cmethod = "standard... | [
27,
7856,
261,
480,
29,
35,
1381,
263,
271,
14,
37,
974,
282,
29271,
3004,
198,
2,
43313,
14173,
270,
270,
452,
88,
284,
22942,
4129,
198,
3500,
1583,
54,
13506,
198,
31,
24209,
39022,
1058,
37,
974,
282,
29271,
3004,
1303,
3544,
... | 2.176623 | 770 |
<gh_stars>0
macro shared_fields_stanmodels()
return esc(:(
name::AbstractString; # Name of the Stan program
model::AbstractString; # Stan language model program
n_chains::Vector{Int64}; # Number of chains
seed::StanBase.RandomSeed; # Seed section of cmd to ru... | [
27,
456,
62,
30783,
29,
15,
198,
20285,
305,
4888,
62,
25747,
62,
14192,
27530,
3419,
198,
220,
1441,
3671,
7,
37498,
198,
220,
220,
220,
1438,
3712,
23839,
10100,
26,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
22... | 2.535135 | 555 |
@ms include("solvers/annealing.jl")
function loop_annealing(args)
instances = [
# "02",
# "03",
# "05",
# "08",
# "09",
# "10",
# "11",
"12",
# "13"
]
println("Instance n° & Cost & Time")
for instance_name in instances
inst... | [
31,
907,
2291,
7203,
34453,
690,
14,
21952,
4272,
13,
20362,
4943,
198,
198,
8818,
9052,
62,
21952,
4272,
7,
22046,
8,
198,
220,
220,
220,
10245,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
366,
2999,
1600,
198,
220,
2... | 1.893855 | 716 |
# Julia 0.6
function singleNumber(vector)
reduce(xor, vector)
end
a = [1,1,2,3,3]
println(singleNumber(a))
| [
2,
22300,
657,
13,
21,
198,
8818,
2060,
15057,
7,
31364,
8,
198,
197,
445,
7234,
7,
87,
273,
11,
15879,
8,
198,
437,
198,
198,
64,
796,
685,
16,
11,
16,
11,
17,
11,
18,
11,
18,
60,
198,
35235,
7,
29762,
15057,
7,
64,
4008,
... | 2.270833 | 48 |
<gh_stars>1-10
using TimeSeries, MarketData, Base.Dates
FactCheck.setstyle(:compact)
FactCheck.onlystats(true)
facts("collapse operations") do
context("collapse squishes correctly") do
@fact collapse(cl, week, first).values[2] --> 97.75
@fact collapse(cl, week, first).timestamp[2] --> Date(... | [
27,
456,
62,
30783,
29,
16,
12,
940,
198,
3500,
3862,
27996,
11,
220,
5991,
6601,
11,
7308,
13,
35,
689,
198,
29054,
9787,
13,
2617,
7635,
7,
25,
5589,
529,
8,
198,
29054,
9787,
13,
8807,
34242,
7,
7942,
8,
198,
198,
37473,
7203... | 2.091514 | 4,360 |
export
FoldSet,
FOLD_TRAIN,
FOLD_TEST,
foldset_match,
foldset_withhold,
check_fold_match
#########################################
const FOLD_TRAIN = 1
const FOLD_TEST = 2
immutable FoldSet
assignment::Vector{Int} # assignment[i] = j means the ith element is assigned to fold j
fold... | [
39344,
198,
220,
220,
220,
39957,
7248,
11,
628,
220,
220,
220,
376,
15173,
62,
51,
3861,
1268,
11,
198,
220,
220,
220,
376,
15173,
62,
51,
6465,
11,
628,
220,
220,
220,
5591,
2617,
62,
15699,
11,
198,
220,
220,
220,
5591,
2617,
... | 2.640052 | 764 |
<reponame>byuflowlab/AircraftSystems
#=##############################################################################################
Filename: solve_rotor.jl
Author: <NAME>
Contact: <EMAIL>
README: define an `Action` object to solve a CCBlade rotor
=#####################################################################... | [
27,
7856,
261,
480,
29,
1525,
84,
2704,
4883,
397,
14,
32,
27002,
11964,
82,
198,
2,
28,
29113,
29113,
14468,
7804,
4242,
2235,
198,
35063,
25,
8494,
62,
10599,
273,
13,
20362,
198,
13838,
25,
1279,
20608,
29,
198,
17829,
25,
1279,
... | 2.941134 | 1,376 |
module SpecialMatrices
import Base: getindex, size, *
struct JordanBlock{T<:Number} <: AbstractMatrix{T}
blocks::Vector{Int}
diag::T
end
size(A::JordanBlock) = Tuple([1; 1] * sum(A.blocks))
function getindex(A::JordanBlock{T}, i::Int, j::Int) where T <: Number
if i == j
A.diag
elseif i > j || j > i + ... | [
198,
21412,
6093,
19044,
45977,
198,
198,
11748,
7308,
25,
220,
651,
9630,
11,
2546,
11,
1635,
198,
198,
7249,
8078,
12235,
90,
51,
27,
25,
15057,
92,
1279,
25,
27741,
46912,
90,
51,
92,
198,
220,
7021,
3712,
38469,
90,
5317,
92,
... | 2.148867 | 309 |
<gh_stars>0
#--------------------------------------------------------------------
# DNSS.jl
# Soham 03-2022
#--------------------------------------------------------------------
module DNSS
using NLsolve, Random, LinearAlgebra, Printf, Distributed
using PyPlot, LaTeXStrings
export Manifold, Space, Produc... | [
27,
456,
62,
30783,
29,
15,
198,
2,
10097,
650,
198,
2,
45080,
5432,
13,
20362,
198,
2,
311,
1219,
321,
7643,
12,
1238,
1828,
198,
2,
10097,
650,
198,
198,
21412,
45080,
5432,
628,
220,
220,
220,
1262,
22879,
82,
6442,
11,
14534,
... | 3.01519 | 395 |
"""
```
plot_scenario(m, var, class, scen; title = "", kwargs...)
plot_scenario(m, vars, class, scen; untrans = false, fourquarter = false,
plotroot = figurespath(m, \"scenarios\"), titles = [], tick_size = 1,
kwargs...)
```
Plot `var` or `vars` *in deviations from baseline* for the alternative scenario
speci... | [
37811,
198,
15506,
63,
198,
29487,
62,
1416,
39055,
7,
76,
11,
1401,
11,
1398,
11,
4408,
26,
3670,
796,
366,
1600,
479,
86,
22046,
23029,
198,
198,
29487,
62,
1416,
39055,
7,
76,
11,
410,
945,
11,
1398,
11,
4408,
26,
1418,
26084,
... | 2.249321 | 1,472 |
<filename>src/ICD10Utilities.jl
module ICD10Utilities
using CSV, TypedTables, Dates, CategoricalArrays, Missings
using FileIO
import Base: isless, show, (==)
export ICDOPTS
export AbstractICD10
export ICD10
export ICD10AM, ACHI
export ICD10CA, ICD10CM, ICD10GM
export ICD10CM
export ICD10AMAge
export icd3
export isv... | [
27,
34345,
29,
10677,
14,
2149,
35,
940,
18274,
2410,
13,
20362,
198,
21412,
314,
8610,
940,
18274,
2410,
198,
198,
3500,
44189,
11,
17134,
276,
51,
2977,
11,
44712,
11,
327,
2397,
12409,
3163,
20477,
11,
4544,
654,
198,
3500,
9220,
... | 2.518681 | 455 |
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